Minimize Terra Mission

Terra Mission (EOS/AM-1)

Spacecraft    Launch    Mission Status    Sensor Complement    EOS    References   

Terra (formerly known as EOS/AM-1) is a joint Earth observing mission within NASA's ESE (Earth Science Enterprise) program between the United States, Japan, and Canada. The US provided the spacecraft, the launch, and three instruments developed by NASA (CERES, MISR, MODIS). Japan provided ASTER and Canada MOPITT. The Terra spacecraft is considered the flagship of NASA's EOS (Earth Observing Satellite) program. In February 1999, the EOS/AM-1 satellite was renamed by NASA to “Terra”. 1) 2) 3) 4)

The objective of the mission is to obtain information about the physical and radiative properties of clouds (ASTER, CERES, MISR, MODIS); air-land and air-sea exchanges of energy, carbon, and water (ASTER, MISR, MODIS); measurements of trace gases (MOPITT); and volcanology (ASTER, MISR, MODIS). The science objectives are:

• To provide the first global and seasonal measurements of the Earth system, including such critical functions as biological productivity of the land and oceans, snow and ice, surface temperature, clouds, water vapor, and land cover;

• To improve the ability to detect human impacts on the Earth system and climate, identify the “fingerprint” of human activity on climate, and predict climate change by using the new global observations in climate models;

• To help develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts

• To start long-term monitoring of global climate change and environmental change.

Complemented by aircraft and ground-based measurements, Terra data will enable scientists to distinguish between natural and human-induced changes.


Figure 1: Illustration of the Terra spacecraft (image credit: NASA)


Terra consists of a spacecraft bus built by Lockheed Martin Missiles and Space (LMMS) in Valley Forge, PA. The spacecraft is constructed with a truss-like primary structure built of graphite-epoxy tubular members. This lightweight structure provides the strength and stiffness needed to support the spacecraft throughout its various mission phases. The zenith face of the spacecraft is populated with equipment modules (EMs) housing the various spacecraft bus components. The EMs are sized and partitioned to facilitate pre-launch integration and test of the spacecraft.

EPS (Electrical Power Subsystem): A large single-wing solar array (size of 9 m x 5 m = 45 m2), deployed on the sunlit side of the spacecraft, maximizes both its power generation capability and the cold-space FOV (Field of View) available to instrument and equipment module radiators. The average power of the satellite is 2.53 kW provided by a GaAs/Ge solar array (max of 7.5 kW @ 120 V at BOL). The solar array is based on on a prototype lightweight flexible blanket solar array technology developed by TRW (use of single-junction GaAs/Ge photovoltaics). A coilable mast is used for the deployment of the solar array. The Terra spacecraft represents the first orbiting application of a 120 VDC high voltage spacecraft electrical power system implemented by NASA. A PDU (Power Distribution Unit) has been designed to provide 120 DC (±4%) under any load conditions. This regulated voltage, in turn, is achieved via a sequential shunt unit (SSU) and the 2 BCDUs. A NiH2 (nickel hydrogen) battery is used (54 cells series connected) to provide power during eclipse phases of the orbit. 5) 6) 7)


Figure 2: Coilable mast deployer for the Terra solar array (image credit: NASA)

GN&C (Guidance Navigation and Control) subsystem: Terra is a three-axis stabilized design with a single rotating solar array. The GN&C subsystem is made up of sensors, actuators, an ACE (Attitude Control Electronics) unit, and software. A three-channel IRU (Inertial Reference Unit) determines body rates in all control modes. Solid-state star trackers provide fine attitude updates, processed by a Kalman filter to maintain precise 3-axis inertial knowledge. A 3-axis magnetometer senses the Earth's geomagnetic field, primarily for magnetic unloading of reaction wheels, but also as a sensor to determine an attitude failure during a deep space calibration maneuver. 8)

The backup sensors include an ESA (Earth Sensor Assembly) for roll and pitch sensing, and coarse sun sensors for pitch and yaw sensing of the sun line relative to the solar array. A fine sun sensor is used in the event that one star tracker fails or during the backup stellar acquisition mode. In addition to these sensors, a gyro-compassing computation is performed for backup yaw attitude determination.

A reaction wheel assembly provides primary attitude control. During normal mode, a wheel speed controller is available to bias the wheel speeds at a range that avoids zero rpm crossings (stagnation point). Magnetic torquer rods regulate the wheel momentum to < 25% capacity in four-wheel mode and < 50% capacity in the three-wheel mode (backup mode). Thrusters are used for attitude control during all velocity change maneuvers and for backup attitude control and wheel momentum unloading.

GN&C is a fault-tolerant system that includes an FDIR (Fault Detection, Isolation and Recovery) capability unique to each of the different operational control modes. If an attitude fault is detected, FDIR transfers all control functions to the ACE unit configured to use all redundant hardware. Once in safe mode, FDIR is disabled.

Sensor component



Mission heritage

Solid State Star Tracker (SSST)


BATC / CT-601


Earth Sensor Assembly) (ESA)


Ithaco / conical scanning


Coarse Sun Sensor (CSS)


Adcole / 42060


Fine Sun Sensor (FSS)


Adcole / 42070


Three Axis Magnetometer (TAM)




Inertial Reference Unit (IRU)


Kearfott / SKIRU-DII






Actuator component




Reaction Wheel Assembly (RWA)


Honeywell / EOS-AM

Similar to EUVE

Magnetic Torquer Rod (MTR)


Ithaco / TR500CFR


Attitude Control Thruster

6 (x 2)

Olin Aerospace (Primex)


Delta-v thruster

2 (x 2)

Olin Aerospace (Primex)


Table 1: Overview of GN&C sensors and actuators


Figure 3: Artist' view of the Terra spacecraft in orbit (image credit: NASA)

The design life of the Terra spacecraft is six years. The spacecraft bus is of size of 6.8 m (length) x 3.5 m (diameter) and has a total launch mass of 5,190 kg. The total payload mass is 1155 kg.

RF communications: The primary Terra telemetry data transmissions are via TDRS (Tracking & Data Relay Satellite) system. A steerable HGA (High Gain Antenna) and associated electronics are mounted on a deployed boom extending from the zenith side of the spacecraft. This location maximizes the amount of time available for TDRS communications via this antenna without obstruction by other pads of the spacecraft. Emergency communication is done via the nadir or zenith omni antenna. Command and engineering telemetry data are transmitted in S-band. The science data recorded onboard are transmitted via Ku-band at 150 Mbit/s. The nominal mode of operation is to acquire two 12 minute TDRSS contacts per orbit. During each TDRSS contact, both S-band and Ku-band transmission is being used.

The average data rate of the payload is 18.545 Mbit/s (109 Mbit/s peak); onboard recorders for data collection of one orbit. Mission operations are performed at GSFC. 9)

Broadcast of data: Besides Ku-band and S-band communication, Terra is also capable of downlinking science data via X-band. The X-band communication can be operated in three different modes, Direct Broadcast (DB), Direct Downlink (DDL) and Direct Playback (DP). DB and DDL is used to directly transmit real-time MODIS and ASTER science data respectively to users.

The DAS (Direct Access System) provides a backup option for direct transmission in X-band. DAS supports transmission of data to ground stations of qualified EOS users around the world. These users fall into three categories:

- EOS team participants and interdisciplinary scientists

- International meteorological and environmental agencies

- International partners who require data from their EOS instruments


Figure 4: The Terra spacecraft in the cleanroom of LMMS at Valley Forge (image credit: LMMS)

Launch: The launch of the Terra spacecraft took place on Dec. 18, 1999 from VAFB, CA, on an Atlas-Centaur IIAS rocket.


Figure 5: Photo of the Terra satellite launch on 18 Decmber 1999 (6:57 UTC) from VAFB, CA (image credit: NASA)

Orbit: Sun-synchronous circular orbit, altitude = 705 km, inclination = 98.5º, period = 99 minutes (16 orbits per day, 233 orbit repeat cycles). The descending nodal crossing is at 10:30 AM.

Orbit determination is performed by TONS (TDRS Onboard Navigation System) which estimates Terra's position and velocity, drag coefficient, and master oscillator frequency bias. TONS is updated by Doppler measurements at the spacecraft's receivers and provides the attitude control software with a desired pointing ephemeris. Ground-based orbital elements are uplinked daily for backup navigation.

As of March 1, 2001, the Landsat-7, EO-1, SAC-C and Terra satellites are flying the so-called “morning constellation” or “morning train” (a loose formation demonstration of a single virtual platform). There is 1 minute separation between Landsat-7 and EO-1, a 15 minute separation between EO-1 and SAC-C, and a 1 minute separation between SAC-C and Terra. The objective is to compare coincident observations (imagery) from various instruments (synergistic effects). 10)

Figure 6: NASA's Terra mission at 10 years on-orbit (video credit: NASA)

Note: As of March 2020, the previously single large Terra file has been split into two files, to make the file handling manageable for all parties concerned, in particular for the user community.

This article covers the Terra mission and its imagery in the period 2020, in addition to some of the mission milestones.

Terra status and imagery in the period 2019

Terra status and imagery in the period 2018-1999

Mission status and imagery for the period 2020+2021

• April 13, 2021: Although there are telltale signs that a volcano is likely to erupt in the near future – an uptick in seismic activity, changes in gas emissions, and sudden ground deformation, for example – accurately predicting such eruptions is notoriously hard. 11)

- This is, in part, because no two volcanoes behave in exactly the same way and because few of the world’s 1,500 or so active volcanoes have monitoring systems in place. Under the best of circumstances, scientists can accurately forecast an eruption of a monitored volcano several days before it happens. But what if we knew months or even years in advance?

- Using satellite data, scientists at NASA’s Jet Propulsion Laboratory in Southern California and the University of Alaska, Fairbanks have developed a new method that brings us closer to that reality. The research was recently published in Nature Geoscience. 12)

- “The new methodology is based on a subtle but significant increase in heat emissions over large areas of a volcano in the years leading up to its eruption,” said lead author Társilo Girona, formerly of JPL and now with the University of Alaska, Fairbanks. “It allows us to see that a volcano has reawakened, often well before any of the other signs have appeared.”

- The study team analyzed 16 ½ years of radiant heat data from the Moderate Resolution Imaging Spectroradiometers (MODIS) – instruments aboard NASA’s Terra and Aqua satellites – for several types of volcanoes that have erupted in the past two decades. Despite the differences between the volcanoes, the results were uniform: In the years leading up to an eruption, the radiant surface temperature over much of the volcano increased by around 1 degree Celsius from its normal state. It decreased after each eruption.


Figure 7: Photo of eruption at Mount Redoubt in Alaska in 2009 (photo credit: Game McGimsey, USGS)

- “We’re not talking about hotspots here but, rather, the warming of large areas of the volcanoes,” said co-author Paul Lundgren of JPL. “So it is likely related to fundamental processes happening at depth.”

- In particular, the scientists believe that the heat increase may result from the interaction between magma reservoirs and hydrothermal systems. Magma (molten rock below Earth’s surface) contains gases and other fluids. When it rises through a volcano, the gases diffuse to the surface and can give off heat. Similarly, this degassing can facilitate the up-flow of underground water and the elevation of the water table, as well as hydrothermal circulation, which can increase soil temperature. But scientists say other processes may also be at play, because while their understanding of volcano behavior is improving, it remains limited.

- “Volcanoes are like a box of mixed chocolates: They may look similar, but inside there is a lot of variety between them and, sometimes, even within the same one,” Lundgren said. “On top of that, only a few volcanoes are well monitored, and some of the most potentially hazardous volcanoes are the least frequently eruptive, which means you can’t rely strictly on historical records.”

Combining Data

- The new method is significant on its own, but it may provide even more insight into volcano behavior when combined with data from models and other satellites.

- In a study published in Scientific Reports last summer, Lundgren used interferometric synthetic aperture radar (InSAR) data to analyze long-term deformation at Argentina’s Domuyo Volcano. At the time, scientists weren’t certain whether Domuyo was a dormant or extinct volcano, or whether it was just a mountain. Lundgren’s research cleared that up quickly. He unexpectedly detected a period of inflation, which is when part of a volcano expands as a new mass of magma moves upward and pushes rock out of the way. It turns out that Domuyo is very much a volcano – and an active one.

- Next, Lundgren compared this deformation time series to the thermal time series Társilo Girona created for Domuyo Volcano. Lundgren’s goal: to determine whether the two processes – an increase in both radiant surface temperature over large areas of the volcano and deformation – were connected.

- “We found that the thermal time series very much mimicked the deformation time series but with some time separation,” said Lundgren. “Even though it remains unclear which process is likely to happen first, by showing the correlation, we can connect the processes through physics-based interpretations rather than simply relying on what we are able to observe at the subsurface.”

- In other words, combining the datasets provides clues about what’s happening deeper inside the volcano and how the various processes influence and interact with each other – data that can improve the accuracy of models used to forecast eruptions.

- “Although the research does not answer all of the questions, it opens the door to new remote sensing approaches – especially for distant volcanoes – that should get us some fundamental insights into competing hypotheses for how volcanoes behave in general dynamic terms over timescales of a few years to decades,” Lundgren added.

Looking Ahead

- Moving forward, the scientists will test the thermal time series method on more volcanoes and continue to fine-tune its precision.

- “One of the goals is to one day have a tool that can be used in near real-time to check for volcanic activity in volcanic areas,” said Girona. “Even for small eruptions, there is evidence of thermal unrest before the initiation of the eruption event, so the new method helps bring us a little closer to that goal.”

- The data help to supplement existing tools used at monitored volcanoes. But they also greatly increase the number of volcanoes for which potentially life-saving data can be made available.

- “Using the new thermal method that detects changes in the surface temperature around volcanoes and the InSAR ground-surface deformation measurements helps enable volcano observatories around the word to identify which volcanoes are the most likely to erupt and which volcanoes should be instrumented for closer observations,” Lundgren said. “In using satellite data, you increase the scope of what can be monitored on a regular basis.”

- As for the once-largely-ignored Domuyo, the story is still evolving: It is one of several volcanoes recently prioritized by the Argentine government to be outfitted with a monitoring system.

• April 8, 2021: The Kafue River—the longest river flowing entirely within Zambia—winds more than 1500 km (900 miles) until it joins the Zambezi River. Before reaching the Zambezi, the Kafue’s west-to-east course crosses a flat, shallow floodplain known as the Kafue Flats. 13)

- The disturbance caused by annual floods plays an important role in the Kafue Flats ecosystem. Historically, naturally occurring floods that peaked along the flats from March to May provided vital habitat for spawning fish; when the floodplain dried around October, grazers moved in to eat the newly grown grasses.

- Dams built for hydropower in the 1970s upstream and downstream of Kafue Flats altered that rhythm. “Since the dams were built, the natural dynamics of high and low flows have been strongly reduced,” said Fritz Kleinschroth, a landscape ecologist at Swiss Federal Institute of Technology (ETH Zürich), who has used satellite images and field surveys to study decades-long changes in the region. “Nowadays, the less-flooded areas are dominated by shrublands, and the more permanently humid zones are comprised of reeds and species like papyrus.” With less water flowing through, trees and shrubs moved in, spawning grounds were lost, and human settlements were disturbed.


Figure 8: To reduce the impacts of this new streamflow, people began to mimic the natural flooding dynamics with artificial flood releases, or so-called “environmental flows.” The recently flooded Kafue Flats are visible in this image, acquired on April 1, 2021, with the MODIS instrument on NASA’s Terra satellite (image credit: NASA Earth Observatory image by Lauren Dauphin, using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- The inundated network of channels and lagoons span the plain, which measures about 240 km long and up to 50 km wide (30 miles). It crosses moderately settled land: the town of Kafue lies along the north bank, and green areas southeast of the flats are irrigated sugar cane fields. River water also passes through Blue Lagoon and Lochinvar National Parks, but even these conservation areas have been altered.

- “Biological invasions are a big issue both from ecological and economic points of views, and everything should be done to prevent the spreading of non-native species in the first place,” Kleinschroth said. But given that invasive plants like hyacinth have been in the region for decades (despite efforts to eradicate them), researchers set out to see if there were any benefits.


Figure 9: This photograph shows a detailed view of the Kafue Flats wetlands, acquired via drone by ATEC-3D for a 2020 study by Kleinschroth and colleagues. The bright green fringe consists of water hyacinth and Amazon frogbit—two exotic floating plant species that the scientists observed amid other native and non-native aquatic plants (image credit: NASA Earth Observatory. The photo was made by ATEC-3D, provided by Fritz Kleinschroth and Scott Winton/ETH Zürich) 14)

- Scott Winton, a biogeochemist at ETH Zürich, and colleagues used data from Landsat images, water samples, and models to find that near the Kafue Gorge Dam, floating plants absorb 19 percent of the total phosphorus and 2.8 percent of the total nitrogen in the river water. In excess, these nutrients can cause blooms of algae and cyanobacteria. Consequences include the release of harmful toxins and the formation of oxygen dead zones that can lead to fish kills and cause methane emissions.

- “In this situation, we ask the question: how can we live with these invasions and are there certain benefits that can be harnessed?” said Kleinschroth, a co-author on the 2020 paper published in Scientific Reports. “And here the novelty is indeed that the mass occurrence of these ‘nuisance’ plants is actually helping to reduce the pollution that is coming from untreated wastewater.” 15)

• March 12, 2021: On March 11, 2011, a magnitude 9.1 earthquake jolted the seafloor about 70 km (45 miles) offshore of Japan’s Tohoku region. It was the largest quake recorded in Japan and the fourth largest in the world since seismic recording began around 1900. 16)

- Within an hour, tremendous tsunami waves inundated much of the eastern Japanese coast, sending 5- to 10-meter walls of water into coastal towns and cities. In Miyako, Iwate Prefecture, the runup height from the tsunami—the maximum elevation that water moved upland from the shore—reached 40.5 meters (133 feet) above sea level. Near Sendai, flood waters penetrated 10 kilometers (6 miles) inland.

- According to the U.S. Geological Survey, the earthquake moved Japan’s main island of Honshu eastward by 2.4 meters (8 feet) and dropped about 400 km (250 miles) of coastline by 0.6 meters (2 feet). The tsunami affected a 2000-kilometer stretch of coast and inundated more than 400 km2 of land in Iwate, Miyagi, and Fukushima prefectures.

- The March 2011 tsunami killed more than 1,700 residents (about 8 percent of the population) of Rikuzentakata and destroyed 80 percent of its residential areas. More than 70,000 trees in the Takatamatsubara pine forest on the waterfront—planted in the 17th century as a tidewater control—were washed away. Flood waters sat for weeks on rice paddies and other agricultural land. Satellites captured scenes of the devastation just one day and three days after the event. On March 14, 2011, The Mainichi Daily News declared: “Rikuzentakata has been erased.”

- A decade later, the area is still rebuilding. A 12.5-meter (41-foot) high concrete seawall now stands along two kilometers of the waterfront in Rikuzentakata. (More than 430 kilometers/265 miles of seawalls have been built up and down the Tohoku coast.) Engineers and construction crews also carried in massive amounts of soil and rock to raise the level of the land by 10 meters before new buildings were constructed. And local officials launched a project in 2017 to plant 40,000 tree seedlings along the town’s coastline.


Figure 10: One of the hardest hit coastal cities in Japan is still working to recover. Some of the worst devastation was observed at Rikuzentakata (Iwate). The images were acquired in 2007, 2011, and 2021 by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), a joint Japanese and U.S. instrument on NASA’s Terra satellite. The images combine infrared, red, and green wavelengths of light to make false-color images that distinguish between water, vegetation, and urban infrastructure. In the 2011 image, most of the areas in purple-blue were flooded or denuded (image credit: NASA Earth Observatory images by Joshua Stevens, using data from NASA/METI/AIST/Japan Space Systems, and the U.S./Japan ASTER Science Team. Story by Michael Carlowicz)

- According to the Japan Reconstruction Agency, nearly 400,000 buildings were destroyed or irreparably damaged and another 750,000 were partially destroyed across the country in March 2011. Nearly 16,000 people were killed and 2,500 are still listed as missing. The meltdown and explosions at the nearby Fukushima Daichi nuclear plant between March 12-15, 2011, added to the misery and displacement of Japanese citizens. More than 21,000 hectares of farmland were destroyed by flooding and by salt water; some has been reclaimed and some has returned to wildland. The World Bank estimated it to be the costliest natural disaster in world history. According to some estimates, Japan has spent nearly $300 billion (U.S) on rebuilding the region to date.

- Visit our Tohoku/Sendai gallery to see twenty other images and stories from the days and months after the earthquake and tsunami.

• March 10, 2021: For at least a century, air, ocean, and land temperatures on Earth have been steadily rising. For at least the past forty years, the planet has been growing a bit greener. Now researchers have found that the greening of the planet can change the movement of air near the land surface in ways that offset at least some warming. Essentially, global warming would be even worse were it not for extra greenery changing how and where heat builds up across the landscape. 17)

- In 2019, remote sensing scientists Chi Chen, Ranga Myneni, and colleagues at Boston University used satellite observations to show that vegetation cover had increased globally by 5 percent since the early 2000s. In 2020, the research group linked that increase in greenness to a slight offset in global temperatures.

- Now, in a new study, Chen and colleagues have worked to decipher how that greening could affect land temperatures. Using satellite data and advanced computer models, they found that increased vegetation has a cooling effect that comes from an increased efficiency in the vertical movement of heat and water vapor between the land surface and atmosphere.

- There are several ways vegetation can alter temperatures at the surface. Changing leaf area can change albedo, or how much sunlight is absorbed or reflected by a landscape. More greenery can also change land surface resistance, or how well water can penetrate and be retained by soil and leaves. And it can change emissivity, or how the surface emits or reflects longwave radiation.

- But according to the new study, the strongest cooling effect comes from the way increasing leaf cover leads to less aerodynamic resistance, or how features on the ground increase or decrease drag and turbulence in the air above. In many environments, extra leaves can enhance the efficiency of vertical air mixing, allowing more heat and water vapor to rise into the atmosphere. Extra leaves may also increase the amount of water transpired (exhaled) by plants, allowing even more water to be transferred. That extra moisture can carry away a significant amount of heat from the ground level and lead to cooler surfaces.


Figure 11: This map shows the trends in the “leaf area index” around the world from 2000 to 2014. Leaf area index (LAI) is a measure of the amount of leaf area relative to ground area during the growing season. LAI is computed from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on NASA’s Terra and Aqua satellites. Note that the map does not show overall greenness, but how greenness has changed since 2000 (image credit: NASA Earth Observatory images by Joshua Stevens, using data from Chen, C., et al. (2020). Story by Michael Carlowicz, with Kassie Perlongo, NASA Ames Research Center)

- In their studies, Chen and colleagues have found that most vegetated areas on Earth (about 93 percent) see their land surfaces cool when leaf area increases. Since 2000, at least 30 percent of areas with more leaf coverage have been cooled by it, while 5 percent have grown warmer.


Figure 12: The map shows global changes in land surface temperatures over the same period due to the increased leaf area. It is derived from satellite observations and from the Community Land Model. Note that the map depicts land surface temperatures (LSTs), not air temperatures. LSTs reflect how hot the surface of the Earth would feel to the touch in a particular location, and they can sometimes be significantly hotter or cooler than air temperatures. - Global warming would be worse were it not for extra vegetation that changes how and where heat builds up across the landscape (image credit: NASA Earth Observatory)

- “In the fight against climate change, plants are the lonely-only defenders,” said Chen, now a postdoctoral researcher at the Lawrence Berkeley National Lab. “Stopping deforestation and ecologically sensible large-scale tree-planting could be one simple, but not sufficient, defense against climate change.”

- The study authors noted, however, that the cooling effect from extra vegetation is large from an energy dissipation perspective, but it is small compared to the pace and intensity of global warming.

• February 16, 2021: With approximately 300 days of sunshine annually, and persistent, dry onshore winds provoked by the Benguela current, Namibia is quite dry for much of the year. The rainy season (November through April) is modest by most precipitation standards in the world. This year, it has brought an abundance. 18)

- January 2021 saw rainfall totals double to triple the norm in the northeastern, central, and southern parts of Namibia. According to a weather monitor in Windhoek, 228 mm (9 inches) of rain fell in January; the long-term average is 85 mm (3 inches). The period of relatively abundant rains followed a December that brought about 25 percent more rain than normal. The wet season rainfall totals are the highest since 2010 and 2011. (This map shows precipitation anomalies as recorded by NOAA's Climate Prediction Center.)


Figure 13: The two natural-color images show the landscape greening due to the rain. They were acquired on 7 February 2021 and on 29 January 2020 (Figure 14) by the MODIS instrument on NASA’s Terra satellite. This map shows changes in the “greenness” of the landscape in February 2021 compared to the 20-year average for the month (Read more about the Normalized Difference Vegetation Index.). The landscape has been transformed by the wettest rainy season since 2011 (image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview. Story by Michael Carlowicz)

- The strong rainfall has been a boon to farmers in the region, as nearly half of Namibia’s people depend on subsistence farming. The extra rain has filled many reservoirs behind the country’s dams. At the same time, the typically dry region has sporadic storm-drain systems, and some roads are poorly equipped to handle heavy rain. Flash floods and overflowing ephemeral rivers posed problems for much of January.

- “It has been a good year for sure, even across into Botswana and South Africa,” wrote Frank Eckardt, a researcher at the University of Cape Town. “We had similar good rains in 2000 and 2011. There is a periodicity to it, which is essential for replenishing surface and groundwater storage. It will also provide much grazing for lifestock and, later, biomass for burning. By April the rains will be gone.” He noted, however, that the region has been getting drier over the long term.


Figure 14: MODIS image of Namibia on 29 January 2020 (image credit: NASA Earth Observatory)


Figure 15: NDVI of Namibia in the period January 24 - February 7, 2021 (image credit: NASA Earth Observatory)

• February 8, 2021: In January 2020, the sky over Sweden delivered an early valentine to people on the ground in the form of a heart-shaped hole in the clouds. Unfortunately, the sky appeared heartless to NASA satellites looking down from above. But other cases of the unusual atmospheric display—so-called “fallstreak holes”—dotted the sky that month over the southern United States. 19)


Figure 16: The natural-color and false-color (Figure 17) images, acquired with MODIS on NASA's Terra satellite on January 29, 2021, show fallstreak holes west of Atlanta, Georgia (image credit: NASA Earth Observatory images by Joshua Stevens, using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- Fallstreak holes, also known as hole-punch clouds, are the result of cold air temperatures and atmospheric instability. Viewed from below, it can appear as if part of the cloud is falling out of the sky. As it turns out, that is actually what’s happening.

- The phenomenon occurs in mid-level clouds composed of liquid water droplets that are super-cooled; that is, the droplets remain liquid even when temperatures are below the typical freezing point of water (32°F, or 0°C). But even super-cooled droplets have their limits. The additional cooling that occurs over the wings of aircraft, for example, can push the droplets to the point of freezing as an airplane passes through the cloud layer. Ice crystals beget more ice crystals as the liquid droplets continue to freeze. They eventually grow heavy enough that the ice crystals fall out of the sky, leaving behind a void in the cloud layer.


Figure 17: False-color image of fallstreak holes west of Atlanta, Georgia on January 29, 2021 (image credit: NASA Earth Observatory)

- The falling ice crystals are often visible in the center of the holes. They are especially apparent in the false-color image at the top of this page, which uses a combination of infrared and visible light (MODIS bands 7-2-1) to distinguish between water and ice. In this view, ice clouds (blue) appear centered within the voids in the water clouds (white).

- Both ascending and descending aircraft are a common trigger for fallstreak holes and their longer, skinner cousins, canal clouds. It is no coincidence that the holes are located near busy airport hubs.


Figure 18: This natural-color image shows a similar scene on January 7, 2021, northwest of Miami, Florida. The locations are more than 500 miles apart, but the physics behind the phenomenon is the same. All of the images were acquired by the MODIS instrument on NASA’s Terra satellite (image credit: NASA Earth Observatory)

• February 4, 2021: With winter in full swing, the Wasatch and Uinta mountains in the Southern Rockies are still building their snowpack. Come springtime, snowmelt will be flowing downstream, delivering important water resources to lakes, reservoirs, and people. The question is: when does all this melting begin? 20)


Figure 19: The map shows the timing of snowmelt within the Great Salt Lake basin in spring 2018, after a particularly bleak year for the region’s snowpack. The basin spans parts of Utah, Idaho, and Wyoming, but only the basin’s eastern side (highlighted) contributes water to the Great Salt Lake. Areas west of the lake are desert. The map uses data derived from the MODIS instrument on NASA’s Terra satellite to indicate the day of the year that each pixel transitioned from snow-covered to snow-free. Melting tends to start at warmer, lower elevations in February (yellow). It follows on for the next several months (darker greens and blues) at ever higher elevations (image credit: NASA Earth Observatory images by Lauren Dauphin, using data from Hall, Dorothy, et al. (2021). Story by Kathryn Hansen)

- “Most of North America is covered in snow in the winter, but the timing of when the snow comes and goes can be very different from place to place,” said Donal O’Leary, a scientist at Battelle Memorial Institute’s National Ecological Observatory Network, and author of the snowmelt timing maps. “These maps show the date that the snow melted away completely, exposing the bare earth below.”

- O’Leary noted that snowmelt timing maps have primarily been used in studies of spring vegetation phenology; that is, how the melting of snow influences the emergence of grasses and flowers, which in turn influences things like animal hibernation and migrations.


Figure 20: The maps are also helping scientists understand the water cycle around mountains and valleys. In particular, they might help them discern some reasons behind the Great Salt Lake’s recent history of water woes. According to measurements from MODIS, the lake in 2000 spanned 1,550 square miles (4,020 km2). By 2019, it had shrunk by 370 square miles (960 km2)—more than three times the area of Salt Lake City (image credit: NASA Earth Observatory)

- The water flowing into the Great Salt Lake comes primarily from streams and rivers (66 percent)—most notably from the Bear, Jordan, and Weber rivers that run down from the mountains. Contributions also come from rain and snow falling directly on and around the lake (31 percent) and from groundwater (3 percent).

- “We have the tools now—satellites and ancillary geophysical data—combined with two decades of MODIS data that allow us to study the environmental contributions to the desiccation of the Great Salt Lake and other terminal lakes,” said Dorothy Hall, a research scientist at the Earth Science Interdisciplinary Center at the University of Maryland.

- Hall and colleagues showed in recent research that melting in the Great Salt Lake basin has generally been trending earlier since 2000, the start of the MODIS era. By 2018, snow in the Great Salt Lake basin east of the lake had melted on average more than a week earlier than in 2000.

- Premature melting skews the water cycle, allowing more runoff to be lost to the atmosphere through evaporation as the water flows from the mountains to the lake. Hall notes, however, that the relative contribution of this early snowmelt to the lake’s desiccation is not yet clear. “The magnitude of the snowmelt is a very important source of runoff that ends up in the Great Salt Lake,” Hall said. “But so far we have not been able to separate the effects of climate change from the effects of consumption for human uses.”

• January 27, 2021: In the Chinese province of Yunnan, soaring mountain ridges flank a series of deep river gorges. The ridges rise well above 5000 meters (16,000 feet), while the lower parts of the gorges lie just a few hundred meters above sea level. 21)


Figure 21: When the MODIS instrument on NASA’s Terra satellite observed the region on January 6, 2021, one of the most striking features was an ephemeral one—long rows of parallel clouds that traced some of the ridges [image credit: NASA Earth Observatory images by Joshua Stevens, using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview and topographic data from the Shuttle Radar Topography Mission (SRTM). Story by Adam Voiland]

- These orographic clouds form when the shape of the landscape (in this case, the ridges) forces moist air up to altitudes high enough and cold enough for the water vapor to condense. After the air passes over the ridges, it sinks downward again, allowing the air to warm as it descends and preventing clouds from forming until another ridge forces the air upward again. Orographic clouds can take many shapes and forms, but they move slowly and often appear stationary because their formation is so dependent on the shape of the land surface below.

- Between the rows of clouds, look for glimpses of the headwaters of three of Asia’s major rivers: the Jinsha (Yangtze), Lancang (Mekong), and Nujiang (Salween). Parts of two large lakes (Erhai and Chenghai) are also visible. The rivers and rugged terrain comprise part of the Three Parallel Rivers of Yunnan Protected Areas—a UNESCO World Heritage Site.

- The site is known as one of the most biodiverse areas in a temperate climate. According to one estimate, the area hosts at least 6,000 species of plants, 173 species of mammals, and 417 species of birds.


Figure 22: This image shows land elevation data for the region from the Shuttle Radar Topography Mission (SRTM), image credit: NASA Earth Observatory)

• January 25, 2021: Nearly 75 percent of Kenya’s people rely on farming for their food and income, so environmental issues like drought, locusts, and climate change can put many lives and livelihoods at risk. Crop insurance programs can help mitigate those risks, but it is not always easy to know where resources are needed. Now NASA-funded scientists are working with colleagues in Kenya to make better assessments of agricultural needs through the use of satellite data. 22)

- In the first few years of the country’s crop insurance program, Kenyan agriculture agents collected much of their information through in-person visits, traveling to individual farms to determine how crops were performing and if financial assistance was necessary. It was labor-intensive and time-consuming. Officials urgently needed timely information spanning vast areas of the country—and that is where NASA Earth observations came in.

- “We suggested that instead of looking for farmers, we look at fields by using products derived from NASA satellite data,” said Catherine Nakalembe, a geographical scientist at the University of Maryland and a leader of the Africa section of the NASA-funded Harvest program. By adding satellite observations into their models and calculations, managers of Kenya’s agricultural insurance program could more readily assess critical information necessary to help farmers.

- Grants from the USAID-NASA SERVIR program allowed the Harvest team and the Regional Center for Mapping of Resources for Development (RCMRD) to incorporate satellite data on rainfall, soil moisture, and land use in ways that can inform Kenya’s agriculture monitoring programs. It also supported efforts to assess crop conditions from afar by using a technique called “cropland masks.” These mapping tools use computer analyses of satellite images and data to build highly localized views of where crops are growing and the health of those fields. The Kenyan ministry and researchers in the RCMRD can then confirm the satellite data by sampling crop conditions on the ground.


Figure 23: This map is a cropland mask for Kenya in 2019. It uses data from Europe's Sentinel-2 satellite to show where crops were growing at the time. Such data are used in the Kenya crop monitor and will be incorporated into the insurance program, allowing the Ministry of Agriculture to better focus time and money. Agriculture officials estimated that the increase in efficiency has already saved 70 percent in costs and staff time. Those savings, in part, helped the program reach 425,000 farmers in 2019, compared to just 30,000 in 2015 (image credit: NASA Earth Observatory images by Joshua Stevens, using data from the Level-1 and Atmosphere Archive & Distribution System (LAADS) and Land Atmosphere Near real-time Capability for EOS (LANCE), and cropland data courtesy of Catherine Nakalembe/University of Maryland. Story by Lia Poteet, NASA Earth Applied Sciences, with Mike Carlowicz, Earth Observatory)


Figure 24: Image of Terra MODIS instrument (image credit: NASA Earth Observatory)

- If project plans come to fruition, the cropland masks will eventually inform efforts like the Crop Conditions Bulletin, released monthly by the Kenyan Ministry of Agriculture. Researchers currently produce broad national maps indicating where conditions are favorable or unfavorable for specific crops such as maize. With such data, agriculture ministers can more quickly discern where to focus their evaluation and monitoring efforts.

- SERVIR is a joint venture between the U.S. Agency for International Development (USAID) and NASA’s Earth Applied Sciences Program. Named for the Spanish and French word “to serve,” the program provides Earth observations and research to help developing countries address critical challenges in food security and other environmental issues. The SERVIR hub in Eastern and Southern Africa is regionally implemented by RCMRD.

• January 8, 2021: The Goldilocks zone typically refers to the habitable area around a star where conditions are right for the existence of liquid water and possibly life. But on Earth, the South Atlantic Ocean has its own kind of Goldilocks zone. In spring and summer, conditions in the Argentine Sea off Patagonia often become just right for phytoplankton, and populations of the plant-like organisms explode into enormous blooms. 23)


Figure 25: In late 2020, satellite images started to show the colorful signature of phytoplankton blooms off the coast of Argentina and around the Falkland Islands (Islas Malvinas). Vivid greens and blues still swirled in the sea on January 5, 2021, when the MODIS instrument on NASA’s Terra satellite acquired this natural-color image [image credit: NASA Earth Observatory images by Lauren Dauphin, using Landsat data from the U.S. Geological Survey and using MODIS data from NASA EOSDIS LANCE and GIBS/Worldview. Story by Kathryn Hansen, with image interpretation from Barney Balch (Bigelow Laboratory for Ocean Sciences), Ana Dogliotti (Institute for Astronomy and Space Physics-CONICET/UBA), and Vivian Lutz (CONICET/INIDEP)]


Figure 26: The OLI instrument on Landsat-8 acquired this scene on 2 January 2021. It shows a detailed view of phytoplankton in Grande Bay, off of Argentina’s Santa Cruz province. Part of the Santa Cruz River is visible at the top-left (image credit: NASA Earth Observatory)

- Rivers like the Santa Cruz carry nutrients from the land and deliver them to the ocean, promoting phytoplankton growth. (Suspended sediment could be contributing some of the color visible in these images.) Another source of nutrients is dust from Patagonia, which strong westerly winds can carry offshore and drop on the ocean surface.

- But phytoplankton blooms are also stimulated by the ocean’s complex circulation patterns and abundant fronts—where separate water masses (with distinct temperatures, saltiness, and nutrients) meet. At the Brazil-Malvinas Confluence, for example, warm, saltier tropical waters flow south and meet the cooler, fresher waters flowing north from the Southern Ocean. Along a front, the rising of a less-dense water mass can carry nutrients up to the surface, where phytoplankton also have ample sunlight to fuel their growth.

- Without a physical sample, it’s not possible to say for sure which type of phytoplankton are present in these images. Scientists found dinoflagellates (Prorocentrum minimum) while collecting samples during an intense bloom in spring 2005; diatoms (Chaetocceros debilis) dominated a bloom in early summer 2003. Both phytoplankton groups tend to appear various shades of green in satellite images. In December 2008, scientists also found a dense bloom of coccolithophores (Emiliania huxleyi), which tend to turn the ocean a chalky green-blue.

- Notice the color gradients across the images. Bright green areas could be a mix of dinoflagellates, diatoms, and coccolithophores; in the bluer areas, coccolithophores likely dominate. Coccolithophores can continue to grow in waters where iron has been depleted, whereas diatoms need both silicate and iron.

- Whichever species were blooming, their abundance indicates the biological richness along Patagonia’s continental shelf, which is the site of some of the world’s richest fisheries.

• January 5, 2021: On a clear day, the towering peaks on Fogo, Santa Antão, and São Nicolau stand out amid the flatter islands of Cabo Verde (Cape Verde). These three volcanic islands, the tallest in the archipelago, stand high enough to generate rain shadow effects that support unique dry forests on some of the islands. 24)

- The height also helps these islands disturb passing air masses and clouds in a way that Theodore von Kárman—an accomplished mathematician, aerospace engineer, and one of the Jet Propulsion Laboratory’s founders—likely would have appreciated. The trails are called von Kármán vortex streets, a distinctive pattern that can occur when a fluid passes a tall, isolated, stationary object. In 1912, von Kármán was the first to describe the oscillating flow features in mathematical terms while he was working as a graduate assistant for the pioneering German fluid dynamicist Ludwig Prandtl.

- Though a French scientist was the first to photograph the feature, von Kármán’s key insight was a mathematical proof demonstrating that staggered vortices were the most lasting flow pattern that such features can produce. “I found that only the anti-symmetric arrangement could be stable, and only for a certain ratio of the distance between the rows and the distance between two consecutive vortices of each row,” von Kármán later wrote about the discovery. In other words, the vortices are always offset and never line up.

- Von Kármán was a student at the University of Göttingen (Germany) when he made his insight about the vortices. He remained in Germany until 1930, with a three-year interruption to serve in the Austro-Hungarian army. Concerned about the rise of the Nazis in Germany, von Kármán accepted an offer to direct the new Daniel Guggenheim Aeronautical Laboratory at the California Institute of Technology in 1930. That lab later became NASA’s Jet Propulsion Laboratory in 1958.


Figure 27: The MODIS instrument on NASA’s Terra captured this image of the swirling trails of clouds on December 20, 2020. The dry forests appear slightly darker than the rest of the islands (image credit: NASA Earth Observatory image by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Adam Voiland)

• January 3, 2021: Transformation is common around the Aral Sea. Perhaps the most obvious shift has been the shrinking of the inland lake since the 1960s and its separation in 2007 into three distinct basins. But this region of Central Asia transforms in other ways, too: from hot and dry in the summer to cold and snowy in the winter. 25)


Figure 28: Winter was under way when the MODIS instrument on NASA’s Terra satellite acquired this image on December 27, 2020. Snow blanketed the ground around the North Aral Sea in Kazakhstan and areas west of the South Aral Sea in Uzbekistan (image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- Notice that the North Aral Sea appears entirely frozen over. Fishermen in the small town of Tastubek, Kazakhstan, on the lake’s north side, endure winters with sub-zero temperatures, yet they continue to fish on the lake through holes dug in the ice. (For comparison, summertime temperatures rise above 40°C (110°F). On the day this image was acquired, the high temperature in Tastubek was -9°C (15°F).

- Toward the east, the dry bed of the Aral Sea’s eastern basin is now sometimes referred to as the Aralkum Desert. Recent research has shown that in wintertime, the lake’s desiccation could cause precipitation in the immediate area to fall as snow as opposed to rain because the dry surface is colder than a wet one. In contrast, the dry surface is thought to lead to substantial regional warming in summer.

• December 21, 2020: Drought is a perennial problem in the semi-arid Sahel region of Africa. But in 2020, in Mali and other countries in West Africa, excessive rainfall has been the problem at times. Exceptionally heavy summer rains pushed seasonal floods on the Niger River and its inland delta to destructive levels. 26)

- In late October, floodwaters reached their peak height at Mopti, a town at the confluence of the Niger and Bani Rivers. Water levels in the delta were recorded at 670 centimeters (22 feet) on October 26 and remained at that level until November 2, according to Mali’s National Directorate of Water Resources. That tied the peak water levels from 2018, the highest since 1969.

- After November 2, waters receded at Mopti even as they continued to rise at points downstream such as Akka and Diré. It typically takes water a full six months from falling in the Guinea Highlands to reach the ocean at the Niger Delta in Nigeria. People watch the timing of flooding closely because it affects when rice can be grown, when fish will be available to catch, and when pastures can be ready for grazing. Water levels were expected to be low enough in mid-December 2020 for the annual cattle crossing on the Niger River at Diafarabé. In the much anticipated event, nomadic herders drive cattle across the river toward rich grazing lands in the inland delta and are reunited with their families after months apart.

- While seasonal floods are common in Mali, the severity of the floods this year caused widespread damage. The United Nations Office for the Coordination of Humanitarian Affairs estimates that 1,160 homes were destroyed by flooding.


Figure 29: After intense rains fell in July and August in the Guinea Highlands and overloaded many streams and rivers, it took several weeks for flood waters to work their way through the vast inland delta in central Mali. When the MODIS instrument on NASA’s Terra satellite captured a natural-color image on October 29, 2020, water had spread widely across the nearly flat delta, which was once a lake bottom. Standing water appears black. Many flooded areas appear green because bourgou grass, rice, and other plants grow in the shallow flood waters (image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Adam Voiland)


Figure 30: For comparison, this image shows the dry landscape in May 2020, before the rains (image credit: NASA Earth Observatory)

• December 12, 2020: In late autumn 2020, a wide area of the northwestern United States and western Canada bathed in sunlight during a long spell of clear skies. The cloud-free conditions gave satellites an unimpeded view of the landscape, including this image of the snowcapped Rocky Mountains. 27)

- The clear skies were the result of a high-pressure weather system that parked over the region during the first week of December. In areas of high pressure, air slowly sinks to lower altitudes and warms, a pattern that inhibits cloud formation.


Figure 31: The Rockies stretch about 3,000 miles (4800 kilometers) across the western half of North America. This view shows a segment measuring about 400 miles (600 kilometers) long and spanning parts of two Canadian provinces (British Columbia and Alberta) and three U.S. states (Washington, Idaho, and Montana). The image above was acquired on December 3, 2020, with the MODIS instrument on NASA’s Terra satellite (image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)

Figure 32: Not all areas remained cloud free. This animation, composed with MODIS images from the Terra and Aqua satellites, shows the area once daily from December 1-5. Notice that clouds show up across the mountain valleys—filling in over the Columbia River, the Kootenay River, and along the Rocky Mountain Trench. Some of these clouds could also be fog, in areas where the base of the cloud is close to the ground (image credit: NASA Earth Observatory)

- The generally cloud-free skies kickstarted a phenomenon common in late fall and winter known as a temperature inversion. As the name implies, air temperatures become inverted from the normal warmer-to-cooler gradient from the ground to the higher atmosphere. Instead, air becomes colder near the ground than the air aloft. This happens when clear skies, especially at nighttime, allow heat from the Sun-warmed ground to easily escape back to space. The cooler, sometimes shaded ground sitting low in mountain valleys helps to chill the near-surface air, while the air above is still trying to shake the heat.

- When moist air near the ground is cooled to its dew point, low-level stratus clouds and fog can form in the valleys. Mountain snow cover can intensify the effect, by reducing daytime warming and by adding extra moisture to the air.

- While the inversion layer produces a stunning view from above, it can be hazardous to people on the ground. The phenomenon is associated with light winds and very little mixing of air masses, so sinking air can trap air pollution at low altitudes and cause poor air quality. According to the U.S. National Weather Service, an “air stagnation advisory” was in effect from December 3-5 for parts of northern Montana, Idaho, and Washington.

• December 3, 2020: In mid-November, about a month before the start of summer in the southern hemisphere, the Antarctic melting season is usually just starting. By that time this year, vast areas along the Antarctic Peninsula were already painted blue with meltwater. 28)

- By the end of November 2020, much of the meltwater on the ice had refrozen. But scientists want to know if this event was similar to a strong early season melt that launched the 2019-2020 melt season. Last year, unusually warm air and water led to record-breaking melting across the Larsen C Ice Shelf. It is the largest remaining ice shelf along the Antarctic Peninsula, even though it lost a Delaware-sized iceberg in 2017.

- Widespread melting on Larsen C, located just south of this image, was not apparent in natural-color satellite images. But scientists are watching how this season progresses. The ice shelf surface on the Larsen A was full of ponded meltwater just before its complete collapse in 1995; the same thing occurred before the near-complete collapse of Larsen B in 2002.

- Only a small remnant of the Larsen B Ice Shelf remains today, stabilized by fast ice in front of the shelf. Loss of the fast ice can destabilize the floating shelf ice, which in turn would allow glacial ice on land to flow unimpeded into the ocean. The effect has already been observed in the Larsen A and upper Larsen B embayments.


Figure 33: This natural-color image was acquired on November 21, 2020, by the MODIS instrument on NASA’s Terra satellite. The sea ice anchored to the peninsula’s coast appears light blue where the surface ice has melted. The white ice farther off the coast is a mixture of broken sea ice and small icebergs. Dark areas indicate open water [image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen, with image interpretation from Christopher Shuman (NASA/UMBC)]


Figure 34: This image, acquired on November 11, 2020, by the Operational Land Imager (OLI) on the Landsat-8 satellite, offers a detailed view of melting near the northernmost end of the Peninsula. The high temperature recorded that day at Esperanza Base measured 8ºC (47ºF). That was warmer than average for November, but not nearly as hot as the record-breaking 18.3ºC (64.9ºF) reached on February 6, 2020. Time will tell if temperatures this melt season will continue to climb and how the ice will respond (image credit: NASA Earth Observatory, Landsat data are used from the USGS)

• November 16, 2020: Iceberg A-68A made headlines in July 2017 when the Delaware-sized block of ice broke from the Larsen C Ice Shelf on the Antarctic Peninsula. The berg has regained the spotlight in austral spring 2020, as it is now drifting toward South Georgia, a remote island in the southern Atlantic Ocean. 29)

- In just over three years at sea, Iceberg A-68A has moved generally northward, passing the tip of the Antarctic Peninsula and floating into “Iceberg Alley.” According to David Long, a remote sensing and polar ice scientist at Brigham Young University, more than 90 percent of all Antarctic icebergs are swept along this path from the Weddell Sea toward the South Atlantic Ocean.

- “Most just don’t survive the journey from the Weddell to South Georgia,” Long said. So far, A-68A’s huge size has helped it survive the relatively warm, iceberg-killing waters of the South Atlantic that can cut like knives through lesser bergs.


Figure 35: The iceberg and island are both visible in this image, acquired on November 5, 2020, with the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. The berg now measures (151 km) 94 miles long and 48 km (30 miles) wide—comparable to the island’s length and width of 167 and 37 km (104 and 23 miles), respectively. It is less than 500 km (300 miles) from the island’s southwest shore [image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview, Reference Elevation Model of Antarctica (REMA) data from the Polar Geospatial Center at the University of Minnesota and data from the Antarctic Iceberg Tracking Database. Story by Kathryn Hansen, with image interpretation from David Long/BYU, Christopher Readinger/USNIC, and Christopher Shuman (NASA/UMBC)]

- While A-68A is following a similar path of many icebergs before it, the details of its journey are unique. In April 2020, A-68A was already adrift in relatively warm waters near the South Orkney Islands, about 800 km (500 miles) from where it broke from the Antarctic ice shelf in 2017. Over the course of the austral winter, sea ice grew to mostly surround A-68A, according to Christopher Readinger of the U.S. National Ice Center (USNIC). Then, currents and wind carried the iceberg out of the sea ice. For several months the berg meandered north, spinning and revolving around oceanic eddies, until it was recently kicked to the northeast toward South Georgia.

- News reports have pointed to a possible collision with the island, or that the iceberg could become stuck, or “grounded,” in the shallow waters surrounding it. Either outcome could mean trouble for the island’s abundant wildlife if the berg blocks the foraging routes of penguins and seals.

- “The currents and eddies are probably too chaotic to really make a prediction about where it will go and how fast it will get there besides some average component of north-east over the next few months,” Readinger said. “The recent news about it seems to be expecting that it will ground at South Georgia. I’m not so sure.”

- Long agrees, noting that historical precedent suggests the iceberg is likely to pass just south of South Georgia. “If it is close enough to the island, it could get caught in the vortex in ocean currents to the east of the island and be pulled back toward the island by counter currents, much as A-22A did more than a decade ago,” Long said. “If, however, it passes far enough to the south, it will miss the counter current the vortex and probably keep heading east-northeast.”

- Whether it becomes stuck or sails smoothy on by, Iceberg A-68A will eventually move past South Georgia. That’s when Readinger thinks the iceberg is likely to break up into smaller bergs, a few of which should be sizable enough to be named by the USNIC. For example, A-68C is located about 420 km (260 miles) northeast of Sough Georgia in the image at the top of this page. That new berg, identified in April 2020, is already breaking up into smaller pieces and will soon be too small for USNIC scientists to track.


Figure 36: The map shows the path of A-68A, based on data from the Antarctic Iceberg Tracking Database. Long and colleagues created the database in 1999 after tracking a similarly large berg (B-10A), image credit: NASA Earth Observatory

• October 29, 2020: For the fifth time this year, a named tropical storm or hurricane is going to make landfall in Louisiana. For the eleventh time in 2020, a named storm is going to hit the continental United States; according to meteorologist Jeff Masters, that is the most since nine made landfall in 1916. For just the sixth time in 170 years, a hurricane is going to come ashore in the U.S. on or after October 28. 30)

- At 1 p.m. Central Daylight Time on October 28, the National Hurricane Center (NHC) reported that the center of Zeta was about 155 miles (255 km) south-southwest of New Orleans. The category 2 storm had maximum sustained winds of 100 miles (155 km) per hour, with higher gusts. Hurricane-force winds stretched as far as 35 miles (55 km) from the center, and tropical storm-force winds extended to 150 miles (240 km).

- A hurricane warning was raised from Morgan City, Louisiana, to the border of Mississippi and Alabama. A storm surge warning was in effect from the mouth of the Atchafalaya River in Louisiana to Navarre, Florida, and specifically for Lake Borgne, Lake Pontchartrain, Pensacola Bay, and Mobile Bay. Forecasters said Zeta should make landfall in southeastern Louisiana by early evening on October 28 and then cross toward the Mississippi and Alabama coasts. Storm surges from 5 to 9 feet (1.5 to 3 meters) were expected from Dauphin Island to the mouth of the Mississippi River. The rapid movement of the storm system was expected to limit rainfall accumulation.

- Zeta previously made landfall on the Yucatan Peninsula of Mexico on October 26. It was the third time in a month that the Yucatan was hit by a tropical storm or hurricane. The storm brought 3 feet (1 meter) of storm surge and up to 7 inches (18 cm of rain) in some areas. Trees and power lines were damaged, but no deaths or severe injuries were reported.

- Zeta is the 27th named tropical storm of the 2020 Atlantic season and the 11th hurricane. The record is 28 named storms and 15 hurricanes, set in 2005. Hurricane season officially ends on November 30.


Figure 37: A natural-color image of Hurricane Zeta was acquired in the late morning on October 28, 2020, by the MODIS instrument on NASA’s Terra satellite (image credit: NASA Earth Observatory image by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Michael Carlowicz)

- The NASA Earth Applied Sciences Disasters Program has activated in support of the event, and is working to determine what NASA resources and capabilities may be available to aid risk reduction, response, and recovery. For hurricanes Laura, Sally, and Delta, the program worked closely with stakeholders from the Federal Emergency Management Agency (FEMA), the Louisiana National Guard, and the Alabama Emergency Management Agency.

• October 25, 2020: Like Earth, the dwarf planet of Pluto has mountains. Like their earthly cousins, some of those peaks are covered in blankets of white. But the origins of these ice-like deposits are very different. 31)

- According to new research published on October 13, 2020, in Nature Communications, some of the mountains discovered on Pluto during the flyby of the New Horizons spacecraft in 2015 are covered by a blanket of methane ice. An international team of scientists analyzed data from Pluto’s atmosphere and surface and used numerical simulations of its climate to reveal that these ice caps are created through different processes than they are on Earth.

- The study authors noted that “within the dark equatorial region of Cthulhu, bright frost containing methane is observed coating crater rims and walls as well as mountain tops, providing spectacular resemblance to terrestrial snow-capped mountain chains.”


Figure 38: The image on the left was acquired on July 14, 2015, when the New Horizons spacecraft approached Pluto. The Long-Range Reconnaissance Imager (LORRI) detected the presence of patchy bright deposits atop the Pigafetta Montes and Elcano Montes mountain ranges. The spacecraft’s Multispectral Visible Imaging Camera (data not shown) revealed signatures of methane. — The right image is a natural-color view of a section of the Alps range in Europe and was acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite on March 19, 2020 (image credit: NASA Earth Observatory image by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Pluto imagery courtesy of NASA/Johns Hopkins University Applied Physics Laboratory/Southwest Research Institute. Story by Frank Tavares, NASA Ames, with Mike Carlowicz)


Figure 39: Researchers find that ice caps on the mountains of Pluto are made of methane, but develop through an opposite process from that on Earth (image credit: NASA Earth Observatory)


Figure 40: On Earth, atmospheric temperatures decrease with altitude, and that cool air chills land surfaces at high elevations. When a moist wind moves toward and over a mountain on Earth, its water vapor cools and condenses, forming clouds and snow, as seen on mountaintops like the Alps. — But on Pluto, the opposite occurs. The dwarf planet’s atmosphere actually gets warmer with altitude because methane gas absorbs solar radiation. However, the atmosphere is too thin to affect surface temperatures, which remain constant with altitude. And unlike the way winds tend to ride up over mountains on Earth, the winds on Pluto mostly travel downslope (image credit: NASA Earth Observatory)

- “It is particularly remarkable to see that two very similar landscapes on Earth and Pluto can be created by two very dissimilar processes,” said Tanguy Bertrand, a postdoctoral researcher at NASA’s Ames Research Center and lead author on the paper. “Though theoretically objects like Neptune’s moon Triton could have a similar process, no other place in our solar system has ice-capped mountains like this besides Earth.”

- To understand how similar landscapes develop from different conditions and chemistries, the researchers at the Laboratoire de Météorologie Dynamique (France) developed a three-dimensional model simulating the atmosphere and surface of Pluto. They found that the dwarf planet’s atmosphere has more gaseous methane at its warmer, higher altitudes. That gas can saturate, condense, and then freeze directly on mountain peaks without any clouds forming. At lower altitudes on Pluto, there is no methane frost because there is too little methane for condensation to occur.

- This condensation process not only creates methane ice caps on Pluto’s mountains, but also similar features on its crater rims as well. The mysterious bladed terrain found in the Tartarus Dorsa region around Pluto's equator can also be explained by this cycle.

- “Pluto really is one of the best natural laboratories we have to explore the physical and dynamic processes involved when compounds that regularly transition between solid and gas states interact with a planetary surface,” said Bertrand. “The New Horizons flyby revealed astonishing glacial landscapes we continue to learn from.”

• October 17, 2020: Australia is a top iron ore producer and exporter in the world, holding nearly 30 percent of the estimated global supply. The majority of those reserves are found in Western Australia, home to one of the country’s largest and oldest iron ore mines. 32)

- The deposits at Mount Whaleback were discovered in 1957 by prospector Stan Hilditch. After World War II, Hilditch began exploring Western Australia for minerals. He concentrated their search in the hills because he believed the mountainous terrain would help the minerals precipitate. Searching in the Ophthalmia Range, he climbed up a hill and stumbled upon a massive iron ore deposit that soon became Mount Whaleback iron ore mine.

- Hilditch tried to open Mount Whaleback for business in 1961, after Australia lifted an embargo on exporting mineral goods. But in spite of the abundance of ore, he had trouble convincing companies to invest in his mine because the deposits were located far from the coast (for shipping) and with a very small population to work on extracting them. Eventually, Hildritch and his business partner sold their temporary reserves to an interested company for $10 million. The Mount Newman Mining Company later built the adjacent mining town, which is now home to about 8,000 people.

- The mine, which is still operating after more than five decades, stretches 5.5 km long and 1.5 km wide. The satellite image also shows several smaller mines nearby; the smaller mines and Mount Whaleback are now collectively known as Mount Newman. Deposits from these smaller mines are transported to Mount Whaleback, blended, and then sent to port.

- A lot of the iron ore found at Mount Whaleback is hematite, which has been the dominant iron ore mined in Australia since the 1960s. Pure hematite contains around 70 percent iron and ranges in color from silver to reddish brown. Iron is extracted from the minerals and commonly used for making steel.


Figure 41: The image shows the Mount Whaleback Iron Ore Mine, adjacent to the mining town of Newman. The image was acquired by the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) instrument on NASA’s Terra satellite on July 16, 2020. The image was composed from green, red, and near-infrared light, a combination that helps differentiate components of the landscape; water is black and vegetation is green (image credit: NASA Earth Observatory, image by Lauren Dauphin, using data from NASA/METI/AIST/Japan Space Systems, and U.S./Japan ASTER Science Team. Story by Kasha Patel)

- The ore at Whaleback mostly occurs in banded iron formations, appearing as colorful alternating layers of mineral deposits on the landscape. The formations were first started more than 2.5 billion years ago when the landmass was under water. Ancient forms of bacteria photosynthesized and released large amounts of oxygen; that oxygen reacted with seawater to form insoluble iron oxide. The iron would precipitate out of the salt water as minerals such as hematite, which then accumulated as sediment on the sea floor.


Figure 42: Photo of the Mount Whaleback Iron Ore Mine, taken in August 2013 by Graeme Churchard (CC BY 2.0 license), credit: NASA Earth Observatory

• October 12, 2020: Wave clouds (sometimes called undulatus or billow clouds) like these are the product of atmospheric gravity waves. They typically form when something forces a mass of air upward. The air cools as it rises and, if there is enough moisture in the air, the water condenses and forms clouds. After the air has passed over the obstacle, it typically sinks downward again. The air warms as it descends, preventing clouds from forming. But like ripples on a pond, the initial disturbance creates a propagating wave that continues to spread, causing air to rise and drop again and again until the wave dissipates. The end result is long lines of clouds that mark the crests of the waves, with cloud-free areas between them that correspond to the troughs of the waves. 33)

- Wave clouds often form when mountains or islands force the flow of air upward. But in this case, the undular bore was likely caused by masses of cool and warm air colliding, with the cool air pushing the warmer air upward. As the group of wave clouds passed Guadalupe Island, notice how cross-currents in the air flow created by the island’s rugged terrain made a pocket of air to the west less amenable to cloud formation.

- “Guadalupe Island often creates some awesome von Karman vortex streets, but making the cloud bands of an undular bore briefly disappear is one of its more impressive tricks,” said Scott Bachmeier, a meteorologist with the Cooperative Institute for Meteorological Satellite Studies at the University of Wisconsin-Madison.

- These were not the only eye-catching wave clouds along North America’s Pacific Coast in recent days. As Bachmeier also pointed out, northwesterly winds flowing past the rugged shoreline of Point Reyes, California, generated a series of striking cloud bands on October 3, 2020, that were similar to bow waves.


Figure 43: When the MODIS instrument on NASA's Terra satellite captured this natural-color image on 4 October 2020, a series of undulating cloud bands—an undular bore—rippled over the Pacific Ocean near Baja California (image credit: NASA Earth Observatory, image by Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Caption by Adam Voiland)

• October 2, 2020: Every day, some 1.3 million tons of sediment pour from the mouth of the Amazon River into the Atlantic Ocean. The abundance of sediment—bits of rocks, soil, and clay carried by currents or resting on the bottom—is what gives much of the main stem of the Amazon River its milky brown color. 34)

- Note also the low-altitude cumulus clouds, sometimes called popcorn clouds, tracing the landscape. Warm, humid air rises from the forest and cools as it rises, resulting in the development of the clouds. But the river waters—and the air above them—are cooler, so there is less moisture rising into the air.

- Almost all of the sediment that reaches the Atlantic Ocean via the Amazon River has traveled a tremendous distance, much of it from the foothills of the Andes Mountains in Peru and Bolivia. Hydrologists estimate that erosion from the mountainous far western part of the river basin contributes about 85 to 90 percent of all the sediment that reaches the sea.

- Most of the sediment comes from three “whitewater” rivers that flow through the western Amazon: the Marañón, the Ucayali, and Mamoré. In contrast, the “clearwater” rivers found in the southern Amazon lowlands and the leaf-stained “blackwater” rivers found in the western and northern Amazon transport minimal amounts of sediment.

- The effects of the sediment are not just aesthetic. The muddy water is loaded with nutrients (such as nitrogen and phosphorous) and organic matter that make whitewater rivers and the várzea floodplain forests particularly rich in plant and animal species, notably fish. The estuary region shown here is known for its many freshwater and marine catfish and croakers. Many of the commercial fisheries in the estuary target piramutaba and marine shrimp.


Figure 44: The natural-color image highlights the Amazon delta and estuary as it was observed by the MODIS instrument on NASA’s Terra satellite on July 29, 2020 (image credit: NASA Earth Observatory image by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview, caption by Adam Voiland)

• September 22, 2020: In the late summer of 2019, the waters off of Newfoundland teemed with phytoplankton for three weeks. It seemed extraordinary at the time. One year later, the Northwest Atlantic bloomed persistently for two months, and the reasons are not entirely clear. 35)

- The turquoise-colored bloom was likely made up of coccolithophores of the species Emiliania huxleyi, which are common to this area in summertime. The phytoplankton have chalky outer shells made of calcite, so they give the water a milky blue color when they aggregate in great numbers. Emiliania huxleyi cells are about 5 µm across — 1,000 times smaller than a grain of sand—so their numbers have to be incredibly abundant for MODIS to detect them.

- Phytoplankton are common in the North Atlantic in spring and summer; they are also becoming more common around the Arctic Ocean and other far northern seas. But it is not often that one species blooms so much for so long because any given species needs just the right balance of sunlight, nutrients, water temperatures, and salinity. In recent years, Emiliania huxleyi has bloomed most abundantly in this area in mid-summer. It is not yet clear why the bloom here lasted so long and late in 2020.


Figure 45: Traces of phytoplankton first became visible southeast of St. John’s, Newfoundland, in mid-July 2020, and the floating, microscopic plant-like creatures were still visible to satellite imagers in mid-September. The natural-color images above were acquired by the MODIS instruments on NASA’s Terra and Aqua satellites on July 21, August 11, and September 5, 2020. Norman Kuring of NASA’s Ocean Color Group also created an animation of the event (image credit: NASA Earth Observatory images by Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview and bathymetry data from the General Bathymetric Chart of the Oceans (GEBCO). Story by Michael Carlowicz)

- “Seven weeks is a long time for a single bloom driven by a single nutrient enrichment event. Usually, those blooms last two to three weeks,” said Barney Balch, a biological oceanographer at Bigelow Laboratory for Ocean Sciences. “However, events this long are not uncommon for features that are continually being sustained by a specific ocean process—such as a supply of water with a specific suite of nutrients. (The Patagonian Shelf bloom is one such example.) In such long-lived features, the coccolithophores outcompete everything else and can sustain maximal growth rates for extended periods.”

- “One might guess that the location of the bloom was in some way tied to the submarine topography,” suggested Kuring. “Shelf-edge dynamics probably have something to do with funneling the right conditions to the bloom.”


Figure 46: The recent blooms have occurred near the edge of the Grand Banks and the Flemish Cap, underwater plateaus that are relatively shallow (50 to 200 meters depth) and sit at the edge of the continental shelf. The cold waters of the Labrador Current and the warmer waters of the Gulf Stream intersect and interact over these banks, creating circulation patterns that can enrich the waters with nutrients. The shape of the seafloor, which rises to these plateaus, also promotes upwelling of nutrients from the depths. Those abundant nutrients can enhance the productivity of phytoplankton (image credit: NASA Earth Observatory)

The plant-like organisms become food for zooplankton, shellfish, and other marine creatures on up the food chain. The waters near the Grand Banks are incredibly productive and home to some of the richest fisheries in the world, particularly for swordfish, haddock, lobster, cod, and scallops.

• September 14, 2020: Almost all of the 46 cm (18 inches) of rain that falls in Namibia's Etosha National Park each year arrives between October and March. The influx of moisture—a boon for the wildlife—completely transforms the landscape. It greens parched grasslands, replenishes ephemeral streams and watering holes, and sometimes pools enough to cover a flat basin with a layer of water that extends for thousands of square kilometers. 36)

- When the rains slow and then cease during the dry season (April through September), any water in the basin slowly evaporates, depositing salt and other minerals on the land surface in the process. Over time, this cycle of flooding and evaporation has built up a mineral-encrusted surface called a salt pan. In fact, the striking white surface of the salt pan is what originally earned Etosha Pan its name. In the language of the local Ovambo people, etosha means "great white place."


Figure 47: Repeated pooling and evaporation of water built this expansive salt pan in northern Namibia. In the series of false-color images, the bright salt pan offers a clear contrast with the parched (brown) landscapes that surround it in the dry season and the lush (green) landscapes of the wet season. All three images use a combination of infrared and visible light to increase the contrast between water and land. Water varies in color from electric blue to navy, with darker shades indicating deeper water. Living vegetation, even sparse vegetation, appears green. Orange areas are burn scars from recent fires. All of the false-color images (3) were acquired by the MODIS instrument on NASA’s Terra satellite. This image was acquired on 31 August 2020 (image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Adam Voiland)

- Notice that a few new burn scars are visible in the August 2020 image (Figure 47). They were likely intentionally set management fires, which help reduce the likelihood of more destructive fires breaking out later. The satellite imagery shows that the scar closest to the Ekuma River burned for a few days beginning on July 13, 2020.


Figure 48: This image was acquired on 17 January 2020 (image credit: NASA Earth Observatory)


Figure 49: This image was acquired on 11 December 2019 (image credit: NASA Earth Observatory)

- Though unusually dry weather left Etosha Pan without water in December 2019, just two months later a surge of rain had refilled much of it. By late August 2020, the salt pan had mostly dried again, aside from some water near the mouth of the Ekuma River.

- Etosha National Park supports large populations of elephants, lions, rhinos, and several other animals. The dry season is one of the best times for visitors to see animals because they often congregate around shrinking bodies of water.

• September 9, 2020: Many wildfires continue to rage in the western United States. 37)


Figure 50: On 9 September, the MODIS instrument on NASA’s Terra satellite captured this natural-color image of thick smoke streaming from a line of intense fires in Oregon and California. Many communities in the region are facing extremely poor and sometimes hazardous air quality (image credit: NASA Earth Observatory, images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview and data from DSCOVR EPIC. Caption by Adam Voiland)


Figure 51: The smoke was so thick and widespread on 9 September that it was easily visible from 1.5 million kilometers away from Earth at L1 (Lagrangian Point 1). When NASA’s EPIC (Earth Polychromatic Imaging Camera) on NOAA’s DSCOVR satellite acquired this image, large areas of Oregon, California, and the northeastern Pacific Ocean were obscured by smoke (image credit: NASA Earth Observatory)

• August 27, 2020: Government meteorologists issued unusually dire warnings as a large hurricane neared the U.S. Gulf Coast on August 26, 2020. After rapidly strengthening as it passed across the Gulf of Mexico, Hurricane Laura was poised to make landfall near the border between Texas and Louisiana. The category 4 storm was expected to unleash strong winds, heavy rains, and a potentially catastrophic storm surge on an area that has not taken a direct hit from a category 4 or 5 storm since the start of modern hurricane records. 38)

- The gravest concern was for a coastal zone extending from Sea Rim State Park, Texas, to Intracoastal City, Louisiana—an area that National Hurricane Center forecasters warned could face a storm surge of 15 to 20 feet (5 to 6 meters) at the coast and flood waters that penetrate as far as 40 miles (60 kilometers) inland.

- A storm surge occurs when cyclonic winds from an approaching storm push a wall of extra water onto the shore. The magnitude of a storm surge depends not only on a hurricane’s winds, but also on its speed, size, and the angle at which it approaches the coast. The timing of astronomical high and low tides can also affect the height of a surge. Storm surges are often the greatest threat to life and property from a hurricane.

- Hurricane Laura is also expected to deliver destructive winds and rain. Forecasters anticipate that hurricane-force winds will extend as far as 70 miles (100 km) from the storm's center into eastern Texas and western Louisiana. They expect rainfall totals of 5 to 10 inches (13 to 25 cm), with up to 15 inches in some areas—enough to cause dangerous flash floods.


Figure 52: Hurricane Laura is poised to cause an unusually large and damaging storm surge. MODIS on NASA’s Terra satellite acquired a natural-color image of Laura on August 26 at 12:20 p.m. as the storm neared the coast. The storm will make landfall late in the evening on August 26, before marching up the Mississippi Valley (image credit: NASA Earth Observatory, images by Joshua Stevens, using MODIS and VIIRS data from NASA EOSDIS/LANCE and GIBS/Worldview, the Joint Polar Satellite System (JPSS), Black Marble data from NASA/GSFC, and data from the Multiscale Ultrahigh Resolution (MUR) project. Story by Adam Voiland)


Figure 53: The VIIRS instrument on NOAA-20 acquired this image of Hurricane Laura at 2:20 a.m. Central Daylight Time on August 26, 2020. Clouds are shown in infrared using brightness temperature data, which is useful for distinguishing cooler cloud structures from the warmer surface below. That data is overlaid on composite imagery of city lights from NASA’s Black Marble dataset (image credit: NASA Earth Observatory)


Figure 54: This map shows sea surface temperatures (SSTs) around the continental U.S. and Mexico as of August 25. Water temperatures in the Gulf of Mexico were running about one degree Celsius (1.8º Fahrenheit) above average. SSTs above 27.8º Celsius (82º Fahrenheit) are generally needed to sustain and intensify hurricanes. Laura underwent a period of rapid intensification as it passed over the warm Gulf waters, with winds intensifying by 50 miles (80 km) per hour over a 24-hour period (image credit: NASA Earth Observatory)

- The data for the map of Figure 54 come from the MUR Global Foundation Sea Surface Temperature Analysis, produced at NASA’s Jet Propulsion Laboratory. It is based on observations from several satellite instruments, including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua and Terra platforms, the U.S. Navy microwave WindSat radiometer, and the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites.

- While warm water can contribute to rapid storm intensification, it is just one of several factors that influence it, explained NASA atmospheric scientist Gary Partyka. “Other things, like efficient outflow in the upper levels of a storm; whether the wind shear is low enough and the atmosphere is stable; and whether dry air is getting into the storm can be quite important as well,” he said. “The science is still quite a way from understanding why some tropical cyclones undergo rapid intensification and others do not.”

- One worrisome aspect of this storm is how many oil refining and petrochemical facilities lie in its path. In anticipation of possible problems, NASA’s Applied Sciences Disasters team has been assembling datasets and imagery (based on optical and synthetic aperture radar sensors) from the days leading up to the storm. “We’ll use these to flag anomalous water extent and start assessing damage later in the week, when satellites again pass over after areas that the storm has hit,” explained NASA researcher Lori Schultz.

• July 17, 2020: Poyang Lake—China’s largest freshwater lake—routinely fluctuates in size between the winter and summer seasons. Between 2019 and 2020, however, water levels went from barely there to the highest on record. 39)


Figure 55: This image, acquired with MODIS on NASA's Terra satellite, show the lake at its recent extreme low level on 8 December 2019. The images of Figures 55 and 56 are false color, using a combination of infrared and visible light (MODIS bands 7-2-1). Water appears black and navy blue; vegetation is bright green; clouds are white or cyan. This band combination makes it easier to see the boundary between water and land (image credit: NASA Earth Observatory images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- Winter is a dry time of year in eastern China, and the lake typically shrinks considerably. Pools of water mixed with patches of grass form important wetland habitat for migrating birds. But the yearly low water levels have been trending even lower, and in December 2019 they were the lowest in 60 years.

- Human influences on the lake’s inflow and outflow of water—landscape change, dams, and sand mining—have contributed to the lake’s decline in recent years. Water levels in winter 2019-2020 were made even worse by a drought, with little rainfall since July 2019.


Figure 56: MODIS on NASA's Terra satellite acquired this image on 14 July 2020 (image credit: NASA Earth Observatory)

- In June and July 2020, the pendulum swung to the other extreme. Since early June, unusually strong, stationary weather systems have produced frequent storms and heavy rainfall across the Yangtze River Basin. The early and intense start to the rainy season caused water levels to rise so that by July 13, Poyang Lake reached 22.6 meters—its highest level on record, and surpassing the previous record of 22.52 meters reached in 1998.

- Flooding has been widespread and deadly in recent weeks. Beyond Poyang Lake, dozens of rivers across central and eastern China have reached record highs. But the worst of it has been in Jiangxi Province and around Poyang. Authorities declared a “red alert” for flooding at Poyang Lake and nearby populated areas, including Nanchang, the provincial capital and its largest city.

• July 11, 2020: Appearing like swirls of soft-serve ice cream, the twists and twirls of these clouds off the western coast of Africa are a demonstration of the artistic nature of our planet and fluid dynamics. 40)


Figure 57: These cloud patterns—known as von Kármán vortices—are a familiar atmospheric phenomenon, especially in areas where trade winds are prevalent. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite acquired this image of vortices near the Canary Islands on July 9, 2020. Satellites have also spotted von Kármán vortices in this area at night (image credit: NASA Earth Observatory image by Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kasha Patel)

- Such vortices can form nearly anywhere that fluid flow—including an air mass, as shown here—is disturbed by a solid object. In this case, winds blowing across the ocean are disturbed by small, volcanic islands poking above the surface of the North Atlantic. The air mass, and clouds moving with it, blows around instead of over the islands.

- Physicist Theodore von Kármán, a co-founder of NASA’s Jet Propulsion Laboratory, was the first to describe the physical processes that create these chains of spiral eddies. As winds are rerouted around the landmasses, the flow slows down and creates a vertical wall of whirling air—with faster wind flowing past slower wind below. These sheets can wrap themselves into vortices and shed alternately off the two sides of the island. The clouds within the air stream, acting like “dusting fingerprints,” help show the details of the interrupted air flow. The pattern of the spirals depends on the intensity of the wind.

• July 5, 2020: From above, the linear features in the Kulunda steppe of southwestern Russia looks as if a large claw has scraped the land surface. In reality, the features are a byproduct of tectonic forces that folded rock layers in ways that created shallow, boggy valleys that are now filled with pine forests and lakes. 41)

- The expansive grasslands surrounding the valleys has a long history of being one of Russia’s most important breadbaskets. Intensive production and overuse during the Soviet era led to significant erosion of the soil in many places, but farmers in the area still manage to grow a range of crops, including wheat, sunflowers, buckwheat, soybeans, flax, peas, and sugar beets.

- MODIS on NASA’s Terra and Aqua satellites acquired this pair of images on April 1 and June 11, 2020. The forested valleys appear dark green in comparison to the lighter green and brown farmland that surrounds them. The loss of snow and ice cover is the most obvious seasonal change in the image pair, but notice also how the color of Lake Kuchukskoye shifts from green to pink.

- Many of the salt lakes in Russia’s Alta Krai district undergo a seasonal color change as populations of aquatic organisms such as salt-loving Halobacteria and brine shrimp increase in the summer. Many of the lakes achieve their most intense flamingo-shades of pink in July and August, when the water becomes especially salty due to hot, dry weather, which increases the rate of evaporation and lowers lake water levels.

- In recent years, Kuchukskoye’s water has usually turned pink by the last week of June or the first few weeks of July. This year, the color change happened earlier than usual—in the third week of May—likely because Siberia experienced an unusually intense and prolonged heat wave.


Figure 58: Linear features in the Kulunda region of southwestern Russia look as if a large claw has scraped the land surface. Terra image as of 1 April 2020 (image credit: NASA Earth Observatory, images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Caption by Adam Voiland)


Figure 59: Linear features in the Kulunda region of southwestern Russia look as if a large claw has scraped the land surface. Aqua image as of 11 June 2020 (image credit: NASA Earth Observatory,

• June 23, 2020: In 2008, atmospheric scientist Santiago Gassó authored a study that highlighted abnormally bright trails of clouds around remote peaks in the South Sandwich Islands. The unusual looking clouds were caused by volcanoes emitting sulfur dioxide and other gases and particles that interacted with passing clouds and made them brighter and more lasting than the surrounding clouds. 42)

- More than a decade later, the NASA and University of Maryland scientist is still tracking and learning from these “volcano track” clouds over the South Atlantic Ocean. In 2020, he watched several of them during a period of sustained period of activity on Mount Michael. For two weeks in mid-May, NASA satellites observed volcano tracks nearly every day.

- On some days, wide tracks extended for hundreds of kilometers from the volcano. But on most days, the tracks were thin and faint, indicating that the volcanic activity was not especially intense. Degassing of sulfur dioxide and other gases is routine on Mount Michael, which has a persistent lava lake roiling deep inside its central crater. On May 30, 2020, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite captured this false-color image of a volcano track near Mount Michael. Waves clouds and Von Kármán vortices are visible downwind of neighboring islands.

- Cloud brightening—the technical term is the Twomey effect—is something scientists have observed for decades. Clouds with extra particles from volcanoes have more and smaller cloud droplets than normal clouds. This means there are more surfaces to reflect light, making volcanically “polluted” clouds appear brighter than others. The same process produces bright ship track clouds over the ocean, except in that case the extra particles come from ship exhaust.


Figure 60: The MODIS instrument on NASA's Terra satellite acquired this image of the Mount Michel volcano on 30 May 2020 (image credit: NASA Earth Observatory, image by Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Adam Voiland)

- While faint volcano tracks can be difficult to see in natural-color imagery, near-infrared light can help. “When I look for volcano tracks with MODIS, I use the 3-6-7 band combination because it includes near-infrared channels that are particularly sensitive to changes in droplet size, a direct result of the volcanic particles entering the cloud,” explained Gassó. “That way the volcano track jumps out without me having to squint much.”

- The many active volcanoes, abundant cloud cover, routinely fierce winds of the “Roaring Forties”—plus the laws of fluid dynamics—often make for unusually beautiful swirls, patterns, and waves in the air above the South Sandwich islands.

- The island chain has also proven to be an ideal natural laboratory for science. “There is a lot of interest in how human-caused pollution affects clouds on a global scale and how it is affecting the climate. But in other areas of the world, it can be difficult to tell if cloud brightening is caused by shifts in meteorology or the presence of pollution particles,” said Gassó. “With the volcano tracks from the South Sandwich Islands, there is no question at all. The brightening is from volcanic ‘pollution,’ and that is really useful for developing models that can quantify how this cloud brightening effect works on a global scale.”

• June 12, 2020: Emiliania huxleyi is about one-tenth the size of a human hair. But in high enough concentrations —a “bloom”—this single-celled phytoplankton becomes visible from space. In May 2020, a vivid bloom of E. huxleyi colored the surface waters of a fjord in southern Norway. 43)


Figure 61: In May 2020, a vivid phytoplankton bloom colored the surface waters of the country’s second-longest fjord. The MODIS instrument on NASA’s Terra satellite acquired this image of Hardangerfjord on May 30, 2020. Blooms can persist for several weeks, but cloud-free views of the entire fjord—Norway’s second-longest—can be hard to come by. Natural-color satellite images show a hint of color on May 25, and by June 10 vivid color was still visible between the clouds (image credit: NASA Earth Observatory, image by Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- E. huxleyi is the most abundant species of coccolithophore, a type of phytoplankton that builds itself a shell of calcium carbonate disks, or “coccoliths.” The shells are so reflective that they can make otherwise dark blue water appear milky blue-green.


Figure 62: This photo by Irene Huse of Norway’s Institute of Marine Research, shows the ship-based view of water in Hardangerfjord that was turned turquoise by E. huxleyi (image credit: Norway's Institute of Marine Research)

- Spring and early summer are common times to see phytoplankton blooms in the North and Norwegian seas. In May and June 2019, a stunning bloom, likely composed primarily of E. huxleyi, showed up along the Norwegian coast and filled Sognefjord—the country’s longest and deepest fjord.

- Coccolithophores tend to be good competitors for nutrients, so they can grow well even under low-nutrient conditions that limit other phytoplankton. But other phytoplankton turn up in this region as well, and not all are as harmless as E. huxleyi. In 2019, a bloom of Chrysochromulina leadbeateri in the waters off northern Norway suffocated millions of farmed salmon.

• June 8, 2020: Each spring, the Canadian Arctic is the site of a fierce battle between water and ice. The flow of the Mackenzie River, swollen with meltwater, helps break up river ice and pushes north toward the Arctic Ocean. In some places, intact ice resists the pulses of water and spurs flooding. But spring warmth always prevails, and by summer the river flows freely into the Beaufort Sea. 44)

- The rush of fresh melt water, called a “freshet,” is important for the hydrology of the Mackenzie River Delta because it recharges groundwater and sustains lakes. The river also carries sediments and nutrients—much of it eroded from rocks far upstream in the Rocky Mountains—to the delta plain and coastal ocean. In the images above, some sediment had already made it past the ice into the Beaufort Sea. You can see it just peeking out from the land-fast ice in the May 23 image. It is much more distinct in the May 30 image, coloring the water with a muddy brown plume.

- The land-fast ice visible was still acting like a barrier as late as May 30. But when it eventually gives way, it will release a large pulse of warm water into the Arctic Ocean. Previous research has shown this early summer pulse can raise offshore water temperatures across hundreds of kilometers, helping to melt and disperse nearby sea ice. The effect on sea ice becomes more important as the global climate warms and larger volumes of warm freshwater are discharged.

- More immediately, with the ice barrier still intact and ice jams still clogging rivers, numerous riverside communities have been on alert for flooding. On June 1, the Mackenzie River’s East Channel near the town of Inuvik rose to 16.5 meters—the highest water level on record for that location. According to news reports, some people in the town were evacuated from their cabins.


Figure 63: These images (Figures 63 and 64), acquired one week apart in May 2020 with the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite, show just how fast the landscape changes at this time of year. In this May 23 image, the Mackenzie River and its tributaries are still mostly frozen (image credit: NASA Earth Observatory, images by Lauren Dauphin, using Landsat data from the U.S. Geological Survey. Story by Kathryn Hansen)


Figure 64: By May 30, melt and ice breakup on the river had worked its way north of Inuvik (image credit: NASA Earth Observatory)

• June 3, 2020: A structure in the Nares Strait known as an “ice arch” was still intact in late May 2020 when the MODIS instrument on NASA’s Terra satellite acquired this natural-color image. But check it out while you still can. This natural gatekeeper—which prevents sea ice from exiting the Arctic Ocean and drifting southward into Baffin Bay—typically breaks up each year by June or July. 45)

- The Arctic Ocean is considered a semi-enclosed ocean, as it is surrounded almost entirely by land. The northern coastlines of these land masses—Eurasia, North America, Greenland—and some scattered islands keep most of the sea ice penned up, making it less mobile than sea ice that forms around Antarctica.

- There are a few passageways, however, that allow ice to escape in spring and summer. The main passage is through the Fram Strait between northeast Greenland and Svalbard. Another is through the Nares Strait between northwest Greenland and Ellesmere Island. Nares Strait is relatively narrow, but a southward flowing current ensures plenty of Arctic sea ice is lost there each year.

- How much ice is lost via the Nares Strait depends in part on how soon the ice arch breaks up each year. In 2019 the ice arch collapsed early, crumbling in mid-April and allowing ice to flow freely by May. Early breakups also occurred in 2017, 2010, and 2008. In 2007, the arch failed to form at all.


Figure 65: The ice arch in 2020 has proved to be more stable. Satellite images show the arch intact on May 22 and it remained so as of the publishing of this story (image credit: NASA Earth Observatory, images by Lauren Dauphin and Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- According to Walt Meier, a sea ice researcher at the National Snow and Ice Data Center, the timing of the breakup depends on factors including ice thickness, air temperature, and wind direction. Thick ice is more stable and tends to break-up later than thin ice. In the strait, thick ice can build up during winters with cold air temperatures; it can also accumulate from thick, multi-year ice that drifts in from the north and gets “wedged” in the strait.


Figure 66: By spring, warmer temperatures begin to melt the ice, causing it to thin and weaken. Temperatures in spring 2020 have been warmer than normal over the Nares Strait, although not as extreme as other parts of the Arctic including Siberia (image credit: NASA Earth Observatory)

- But you need more than thin ice and warm temperatures to destroy the ice arch. “Warmer temperatures in the spring don’t necessarily indicate an early break-up,” Meier said. “The ice needs to be weak enough to break up, but then the winds blowing in the right direction give it a ‘final kick’ for the arch to collapse.”

- The “right direction” refers to winds blowing parallel to the strait, forcing ice southward. Meier noted that over the past few months, a low-pressure circulation pattern in the central Arctic has resulted in winds blowing perpendicular to Nares Strait. “These are not winds that would tend to initiate the break-up,” he said.

- Meier speculated that this same wind pattern could be responsible for churning up the sea ice and causing tough conditions for the Polarstern—an icebreaker currently drifting in Arctic sea ice for the MOSAiC science expedition. “So, that large-scale circulation may have contributed to both ridging and thicker ice along Polarstern's route,” Meier said, “as well as winds that are favorable to preserving the arch.”

• May 20, 2020: The Gran Chaco is not the most well-known forest in South America. It is second in size and biodiversity to the neighboring Amazon rainforest. Unlike the moist Amazon, the Gran Chaco is located in a semi-arid climate; its vegetation is less colorful. But like the Amazon, the Gran Chaco has been facing rapid deforestation over recent years. 46)

- The Gran Chaco spans about 650,000 km2 (250,000 square miles) in Argentina, Paraguay, Bolivia, and Brazil—making it the largest dry forest in South America. It largely consists of shrubs and hardwood trees that provide habitat for thousands of plant species and hundreds of animal species. The native Wichí people have hunted and gathered on this land for decades.

- But observations by Landsat satellites indicate that roughly 20 percent—142,000 km2 (55,000 square miles)—of the forest was converted into farmland or grazing land from 1985-2013. From 2010 to 2018, more than 29,000 km2 (11,000 square miles) of the Gran Chaco was cleared for farms and ranches, according to the non-profit Guyra Paraguay. Much of the clearing took place in Argentina.

- The images of Figures 67 and 68, acquired with MODIS on NASA's Terra satellite, show the deforestation over a span of two decades around the Salta Province of northern Argentina. Much of the cleared land has been converted to farmland for growing soybeans and raising livestock. Argentina is the third-largest soybean producer in the world. Research shows that soybean production was a direct driver of deforestation in the forest in the 2000s. As soybean producers felt more pressure to keep up with global demand, they needed to find untapped land and began clearing forests and arid regions. Advances in technology made it easier to grow crops on these marginal lands, which were previously difficult to cultivate.


Figure 67: The MODIS image of 18 December 2000 shows a mix of cleared land and greener areas (image credit: NASA Earth Observatory)

- Controlling deforestation in Gran Chaco has been challenging. In 2007, Argentina enacted a national “forest law” mandating that local governments regulate the expansion of large-scale farming and establish practices to protect native forests. However, research shows that local governments were unable to enforce the law in certain protected zones, some of which actually experienced an increase in deforestation after the law was passed.


Figure 68: The MODIS image of 24 December 2019 shows much of the forest replaced by large fields (image credit: NASA Earth Observatory, images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kasha Patel)

• April 21, 2020: On March 25, 2020, the Indian government placed its 1.3 billion citizens under a strict lockdown to reduce the spread of the COVID-19 coronavirus. The country-wide mandate decreased activity at factories and severely reduced car, bus, truck, and airplane traffic. After just a week of reduced human activities, NASA satellite sensors observed aerosol levels at a 20-year low for this time of year in northern India. 47)

- Every year, aerosols from anthropogenic (human-made) sources contribute to unhealthy levels of air pollution in many Indian cities. Aerosols are tiny solid and liquid particles suspended in the air that reduce visibility and can damage the human lungs and heart. Some aerosols have natural sources, such as dust storms, volcanic eruptions, and forest fires. Others come from human activities, such as the burning of fossil fuels and croplands. Human-made aerosols tend to contribute most of the smaller particles that have greater potential for damaging human health.

- “We knew we would see changes in atmospheric composition in many places during the lockdown,” said Pawan Gupta, a Universities Space Research Association (USRA) scientist at NASA’s Marshall Space Flight Center. “But I have never seen aerosol values so low in the Indo-Gangetic Plain at this time of year.”

- In a typical early spring in the Ganges Valley of northern India, human activities generate the majority of aerosols. Motor vehicles, coal-fired power plants, and other industrial sources around urban areas produce nitrates and sulfates; coal combustion also produces soot and other carbon-rich particles. Rural areas add smoke—rich in black carbon and organic carbon—from cooking and heating stoves and from prescribed burns on farms (though farming fires more often occur at other times of year). By all accounts, the 2020 lockdown reduced those human-made emission sources.


Figure 69: The first five maps above show aerosol optical depth (AOD) measurements over India during the same March 31 to April 5 period for each year from 2016 through 2020. The sixth map (anomaly) shows how AOD in 2020 compared to the average for 2016-2019. Aerosol optical depth is a measure of how light is absorbed or reflected by airborne particles as it travels through the atmosphere. If aerosols are concentrated near the surface, an optical depth of 1 or above indicates very hazy conditions. An optical depth, or thickness, of less than 0.1 over the entire atmospheric vertical column is considered “clean.” The data were retrieved by the MODIS instrument on NASA’s Terra satellite (NASA Earth Observatory images by Joshua Stevens, using Terra MODIS analysis courtesy of Pawan Gupta/USRA/NASA. Story by Kasha Patel with image interpretation from Hiren Jethva, Rob Levy, and Ralph Kahn)

- Scientists expect aerosol levels to increase slightly in upcoming weeks in parts of India as seasonal dust storms begin. Dust concentrations are typically low in March and early April, before temperatures rise and strong westerly winds blow sand in from the Thar Desert and Arabian Peninsula. The question is whether overall AOD will remain below normal.

- “The hard part with understanding aerosols is that particles can move based on wind patterns and other meteorology,” said Robert Levy, program leader for NASA’s MODIS aerosol products. “You have to disentangle what is caused by the human fingerprint versus a meteorological factor.”


Figure 70: The chart shows daily average aerosol optical depth measurements over northern India from January 1 to April 5, 2020, as compared to the 2016-2019 average. Note that the rise in AOD at the end of February coincided with fire activity in the Indian state of Punjab and in neighboring Pakistan(image credit: NASA Earth Observatory)

- In the first few days of the lockdown, it was difficult to observe a change in the pollution signature. “We saw an aerosol decrease in the first week of the shutdown, but that was due to a combination of rain and the lockdown,” said Gupta. Around March 27, heavy rain poured over vast areas of northern India and helped clear the air of aerosols. Aerosol concentrations usually increase again after such heavy precipitation.

- “After the rainfall, I was really impressed that aerosol levels didn’t go up and return to normal,” Gupta added. “We saw a gradual decrease, and things have been staying at the level we might expect without anthropogenic emissions.”

- According to Gupta, AOD levels in northern India at the beginning of April were significantly below the norm for this time of year and the lowest in 20 years of MODIS observations. Ground observation stations in India have also reported a decrease in particle pollution in the region. Anecdotally, people in the northern state of Punjab have reported seeing the Himalayas for the first time in decades.

- In southern India though, the story is a little hazier. Satellite data show aerosol levels have not yet decreased to the same extent; in fact, levels seem to be slightly higher than in the past four years. The reasons are unclear, but could be related to recent weather patterns, agricultural fires, winds, or other factors.

- This a model scientific experiment,” said Levy about the lockdown and its effects on pollution. “We have a unique opportunity to learn how the atmosphere reacts to sharp and sudden reductions in emissions from certain sectors. This can help us separate how natural and human sources of aerosols affect the atmosphere.”

• April 20, 2020: Some Antarctic icebergs can persist for many years. A newborn child could go off to school, learn to drive, and become an adult all within the span of time it takes some of the largest icebergs to break up and melt away. Iceberg A-68A—now just a few months shy of its third birthday—is a youngster compared to some. But the mammoth berg has already had an impressive journey. 48)


Figure 71: The huge Antarctic iceberg has floated into warmer waters, but it is still mostly intact. On April 9, 2020, the MODIS instrument on NASA’s Terra satellite acquired this image of A-68A floating about 230 km west-southwest of the South Orkney Islands. The 95-mile-long iceberg appears to dwarf the 80-mile-long island chain (image credit: NASA Earth Observatory, image by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- In this image, A-68A is about 500 miles from where it broke away from the Larsen C Ice Shelf in July 2017. The journey, however, was not exactly direct. In its first year, the iceberg moved just 45 km (28 miles) as tides shuffled the Delaware-sized block of ice back and forth, occasionally smashing it against a rocky outcrop on the Antarctic Peninsula. The region’s powerful currents eventually won, and the iceberg has since been winding its way north through the Southern Ocean.

- A-68A seems to have hit the brakes in recent weeks, rotating in place without moving far. NASA/UMBC glaciologist Christopher Shuman thinks the berg could be caught up in a circulating mass of water, or “gyre.” Christopher Readinger, a scientist at the U.S. National Ice Center (NIC), agrees that a gyre or smaller-scale eddy could explain the berg’s motion. “This is behavior we’ve seen many times before with other bergs downstream of the peninsula,” Readinger said. “They just start circling for no apparent reason.”

- Icebergs passing through this area eventually get kicked to the east when they encounter the powerful Antarctic Circumpolar Current, which funnels through the Drake Passage. From that point, the ice can whip north into the warmer waters of the South Atlantic—a region where icebergs melt, break down, and ultimately die. That has been the fate of many fragments of another iceberg, B-15. The Connecticut-sized berg was the largest ever measured by satellites, but 20 years after breaking from the Ross Ice Shelf, only one piece is still large enough to be tracked by the NIC.

- A-68A is not quite at that point. “I’m surprised at how well it’s sticking together,” Readinger said. “It’s been in warmer water for a few months now and it’s not exactly a very thick berg, so I expect it will break up sometime soon, but it’s showing no signs of that yet.”

• April 4, 2020: Russia’s Lake Beloye holds just over 6 km3 of fresh water; drops in a bucket compared to the 24,000 km3 in Lake Baikal, the world’s largest freshwater lake by volume. Yet Beloye still manages to make a stately appearance in satellite imagery.


Figure 72: On March 17, 2020, the MODIS instrument on NASA's Terra satellite acquired this image of Lake Beloye in Russia’s Vologda region. It stands out in part because its water is shallowly spread across more than 1,000 km2 — larger than the average lake area in this part of northwest Russia (image credit: NASA Earth Observatory, image by Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)

- It also stands out because of the stark contrast of lake ice—some of it is likely snow-covered—with the surrounding landscape. The lake usually freezes over in early November and breaks up in late April. Thawing already appeared to be underway when this image was acquired, with thin gray ice along the southern coast near the historic town of Belozersk. If you click on this time series of raw images, small areas of open water were visible by March 30, before fresh snow appeared to cover the ice again on April 1.

- The shape of the lake is strikingly round. Many of the lakes in this region fill valleys and depressions left behind at the end of the last Ice Age when the enormous ice sheets retreated. That could be the case here or, as another source points out, the water could be filling a 100-million-year-old impact crater.

- While this image makes the lake appear isolated in the landscape, it’s actually connected to a series of rivers and canals that form the Volga-Baltic Waterway. In the area visible in this image, the waterway includes the Kovzha River, Lake Beloye, the Belozersky Canal (constructed along the lake’s southern side as a bypass), and the Sheksna River. This waterway, in turn, is connected to an even larger system of inland waterways known as the Unified Deep Water System of European Russia.

• March 30, 2020: Could Satellites Help Head Off a Locust Invasion? Researchers are using satellite data to understand where locusts may spread during the largest infestation in eastern Africa in decades.— A single desert locust (Schistocerca gregaria) can consume its body weight in vegetation in one day. That may not sound like much for one 2.5-gram locust, but when 40 million of them gather—considered a small swarm—they can devour as much food as 35,000 people. In one day, a small swarm can jeopardize a farmer’s livelihood. 49)

- Since December 2019, croplands in Kenya have been inundated by the voracious insects. By January 2020, at least 70,000 hectares (173,000 acres) of land were infested—Kenya’s worst locust event in 70 years. In February, the swarms spread to ten countries in eastern Africa, threatening food supplies for millions of people. Ethiopia and Somalia have seen their worst locust infestations in 25 years. The United Nations (UN) has warned that the upcoming rainy season may make things worse.

- NASA-funded scientists are partnering with the UN and relief organizations to better understand where locusts are likely to swarm. Using remote sensing observations of soil moisture and vegetation, researchers are tracking how environmental conditions influence locust life cycles and hoping to stop outbreaks before they spread.

- “The approach that helps prevent large-scale infestations is to catch the locusts very early in their life stages and get rid of their nesting grounds,” said Lee Ellenburg, the food security and agriculture lead for SERVIR at NASA’s Marshall Space Flight Center. The joint program between NASA and the U.S. Agency for International Development (USAID) uses satellite data to improve environmental decision-making in developing nations. The team also partnered with staff at the Desert Locust Information System of the UN Food and Agriculture Organization (FAO) to learn more about locust behavior.


Figure 73: This image shows average soil moisture over eastern Africa for January 14-20, 2020, during the early stages of the locust invasion. The preliminary estimates—developed by scientists at UCAR (University Corporation for Atmospheric Research) and the University of Colorado—use NASA’s CYGNSS (Cyclone Global Navigation Satellite System) microsatellites and are integrated with NASA’s model-based Land Information System (image credit: NASA Earth Observatory, images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview and soil moisture data from Cyclone Global Navigation Satellite System (CYGNSS) microsatellites integrated with NASA's model-based Land Information System. Story by Kasha Patel)

- The two maps (Figures 73 and 74) show two important environmental parameters for locust development: soil moisture and vegetation. Soil moisture is important because females almost always lay their eggs in wet, warm, sandy soil. In general, they do not lay their eggs unless the soil is moist down to 5-10 cm (2-4 inches) below the surface. After eggs hatch, the abundance of nearby vegetation becomes the important parameter because it provides sustenance for maturing locusts and guides migration patterns.

- Desert locusts have three main life stages: egg, hopper, and adult. Once they are mature adults, locusts are difficult to find on the ground and eradicate because they can fly 50 to 150 kilometers (30 to 90 miles) per day, especially if winds are strong. However, eggs and hoppers (when they’re still developing wings) have limited mobility and are easier to target.

- “The data we have so far show a strong correlation between the location of sandy, moist soils and locust activity,” said Ashutosh Limaye, NASA’s chief scientist for SERVIR. “Wherever there are moist, sandy locations, there are locusts banding or breeding.” Desert locusts rapidly reproduce, so SERVIR researchers are working with FAO to pinpoint potential breeding locations and suggest targeted areas for pesticide sprays.

- “Our goal is to learn from FAO how to find out where the breeding grounds are,” Ellenburg added. “If the prevailing conditions indicate that locusts will hatch and be taking off, the goal is to go early and destroy their nesting grounds.”


Figure 74: This map depicts changes in green vegetation across eastern Africa between Dec 15, 2019, and March 15, 2020. Derived from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite, the Normalized Difference Vegetation Index (NDVI) is a measure of the health and greenness of vegetation based on how much red and near-infrared light it reflects. Healthy vegetation with lots of chlorophyll reflects more near-infrared light and less visible light (image credit: NASA Earth Observatory)

- “Once locusts lay the eggs and hatch, they start looking for vegetation to feed on,” said Catherine Nakalembe, a food security researcher with SERVIR and NASA Harvest. “They start migrating, looking for more to eat, and then keep multiplying.”

- Nakalembe says vegetation across the region is much greener than average years—in fact, the greenest vegetation observed by satellite since 2000 for the December to March time period. Between October and December 2019, the Horn of Africa received up to four times more rainfall than average, making it one of the wettest “short rain seasons” in four decades. The extra rain made for robust plant growth and bountiful conditions for locusts.

- With the upcoming “long rain season” (March through May) in east Africa, conditions could be ripe for more infestations, Nakalembe notes. The NASA team is refining several satellite datasets to assess the damage already caused and to create forecasts of where and how much longer locust outbreaks might occur.

- “We work in close coordination with national ministries through our regional partners, and we hope the outcomes from our ongoing work can ultimately support those who are in the front line of managing the current outbreak,” said Nakalembe.

- The NASA SERVIR and Harvest programs are working closely with Global and Regional FAO offices, USAID, World Food Program (WFP), the SERVIR Hub in East and Southern Africa at the Regional Center of Resources for Mapping Development (RCMRD) in Nairobi, Kenya, the SERVIR Hub in West Africa at the AGRHYMET based in Niamey, Niger, the Greater Horn of Africa IGAD Climate Prediction and Applications Center, NASA Short-term Prediction Research and Transition Center (SPoRT) NASA Earth Science Disasters Program, and several satellite missions to provide information and direction on where resources should be directed to mitigate locust outbreaks.

• March 24, 2020: Winter is loosening its grip on the Northern Hemisphere, and greens and browns are replacing white on the landscape. But the seasonal change in March 2020 in Northern Europe is less dramatic than most years. 50)

- While snow covered much of Norway and the northern parts of Sweden and Finland, the southern end of each country appeared snow-free—including the capital cities of Oslo, Stockholm, and Helsinki. (For a seasonal comparison, see this image from March 2018.) The cities were virtually snow-free for much of winter 2019-20. For example, Helsinki saw no new snowfall in January or February, according to news reports. Numerous ski resorts across Europe had to rely on imported and artificial snow.

- Warm winter temperatures were one reason for the sparse snowfall. According to NOAA, the December 2019 to February 2020 period was the warmest on record in Europe, and the January-February period was the warmest on record for the Northern Hemisphere. “The strong polar vortex has kept much of the frigid air in the Arctic, leaving the mid-latitudes warmer and generally less snowy than normal,” said Jennifer Francis, a scientist at Woods Hole Research Center.


Figure 75: This natural-color satellite image shows snow cover in Scandinavia and the Baltic region in early spring 2020. It is a composite of two images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite on March 20 and 21. The composite maximizes the cloud-free area visible from space (image credit: NASA Earth Observatory images by Joshua Stevens, using data from the Level 1 and Atmospheres Active Distribution System (LAADS) and Land Atmosphere Near real-time Capability for EOS (LANCE), and MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Kathryn Hansen)


Figure 76: This map shows land surface temperature anomalies for January to March 2020 in northern Europe. Orange and red colors indicate areas that were warmer than average for the same three-month period from 2003 to 2018. The map is based on MODIS data from NASA’s Aqua satellite. Note that the map depicts land surface temperatures (LSTs), not air temperatures. LSTs are a measure of how hot the surface would feel to the touch and can sometimes be significantly hotter or cooler than air temperatures (image credit: NASA Earth Observatory)

- As a consequence of a strong polar vortex, the polar jet stream—westerly winds in the lower atmosphere that help move weather systems around the planet—stayed farther north than normal this winter. As a result, Francis noted, Pacific storms hit places like Washington and British Columbia while depriving the Sierras of snowfall. Atlantic storms, meanwhile, pummeled the United Kingdom and northwest Europe, but avoided parts of Central and Northern Europe.

• March4, 2020: In August 2019, fires in the Amazon dominated the news, inspiring concern from presidents and prime ministers to pop stars to the Pope. As smoke darkened South American skies, people wondered: What caused the fires? Were they unusual? What did they mean for the rainforest? 51)

- Editor’s Note: This story is part of a series. Please read part 1, part 2, and part 3 for a more complete picture of Amazon deforestation.

- Scientists at NASA and other international agencies worked overtime to answer such questions, using the satellite and ground-based information available in real-time. But the reality of science, statistics, and satellite observations is that understanding the causes and effects of a fire season takes time. Six months later, some of the answers are coming into clearer focus.

- “There is no question the 2019 Amazon fires were unusual, but they were unusual in specific areas and ways,” said Douglas Morton, chief of the Biospheric Sciences Laboratory at NASA’s Goddard Space Flight Center. “Fortunately, we did not see forest fires burning uncontrolled through the rainforest like we have during past drought years. What we did see was a worrisome increase in deforestation fires in certain parts of Brazil.”

- Despite the nasty start to the 2019 fire season, year-end tallies of fire hot spot detections and burned area did not break all-time records. “The real nightmare scenario would have been deforestation fires at the level we had in 2019 during a drought year,” said Alberto Setzer, a senior scientist at Brazil’s National Institute for Space Research (INPE). “You would have seen fires spreading into the rainforest and burning unchecked for months.”


Figure 77: The reality of science, statistics, and satellites is that a deep understanding of the causes, effects, and severity of a fire season takes time. - The first signs that 2019 could be an especially tumultuous fire season emerged in the northern Brazilian state of Roraima. Between January and April 2019, satellites detected record numbers of hot spots, especially in areas where reports of deforestation were common, explained Setzer. By August, skies were unusually smoky across several states, many state governments had declared emergencies, and controversies about deforestation data and environmental policy simmered in the media (image credit: NASA Earth Observatory, images by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview, Fire Information for Resource Management System (FIRMS) data from NASA EOSDIS, and Landsat data from the USGS. Burned area anomalies data are courtesy of Louis Giglio. Story by Adam Voiland)


Figure 78: But it was not until the effects of the fires reached São Paulo, Brazil’s media and financial capital, that they became front page news. On August 19, 2019, accumulated smoke from fires in the Amazon and from particularly smoky fires in dry forests along the Bolivia-Paraguay border blew southeast, combined with unusually low clouds, and turned day into night in the city. People were baffled, and the eyes of the world turned to the fires in the rainforest. “There was an incredible hunger for information,” said Louis Giglio, a fire scientist at the University of Maryland and NASA Goddard (image credit: NASA Earth Observatory)

- When fire outbreaks occur, it can be hard to assess their extent or severity from the ground, but satellites can help. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on NASA and NOAA satellites detect hot spots associated with fires on a daily basis.

- “These ‘active fire’ data are one of the first things people look at,” said Giglio. “But it can be difficult to interpret what all those red spots on a map mean in real time, especially if you’re not an expert in remote sensing. It can be tough even if you are an expert in remote sensing.”

- One of the key things to remember about active fire maps such as the one maintained by NASA’s Fire Information for Resource Management System (FIRMS) is how different the fires can be, cautioned Giglio. In tropical South America, red dots may represent small seasonal agricultural fires burning in pastures or between fields; the same dots can also represent big piles of dried wood being torched after rainforest clearcutting; some may represent a fast-spreading grass fire or brush fire in dried-out wetlands or shrubby savannas; and still others may be knee-high fires creeping through the understory of rainforests.


Figure 79: MODIS fire detections in Brazil in the time frame 1 January 2003 to 31 December 2019 (image credit: NASA Earth Observatory)

- If you look at the total number of hotspots or square kilometers of burned area that satellites detected across South America, just in Brazil, or in certain Brazilian states in 2019, the raw numbers from FIRMS and INPE’s fire monitoring system do not stand out. The line chart above shows the total fire counts as observed in Brazil over nearly two decades of MODIS data.

- “If you are comparing fire detections or burned area from 2019 to the full MODIS record,” said Morton, “realize that you are comparing a year without extreme drought or uncontrolled forest fires to years such as 2005, 2007, and 2010 when there were.” Also, fire activity was extremely high in the early years (2001-2004) of MODIS observations because it was not until 2004 that Brazil enacted a series of environmental regulations that reduced fires and the rate of deforestation.

- During the past few years, there has been less emphasis on environmental enforcement and fire prevention, so deforestation has been increasing. “One of the ways some people have tried to game the system in recent years is by clearing land in a way that is difficult for satellites to detect—by clearing thin strips along the edge of the rainforest, for instance,” said Morton. “In 2019, deforestation fires started earlier in the dry season, and people burned large clearings. It was similar to fire activity in years with limited environmental enforcement and high deforestation, such as 2003-2004.”

- There is another reason the 2019 fire counts and burned area did not end up at the top of the long-term fire records. As public outrage peaked in August and September, the Brazilian government deployed tens of thousands of soldiers to the rainforest to fight fires. Then heavy rains dampened fire activity across much of Amazonia. By October, fire counts and burned area tallies had fallen to nearly record-low levels in many areas.

- “If the military hadn’t intervened and the rains hadn’t picked up, there is no doubt that the totals for the year would have been much higher,” said Setzer.


Figure 80: MODIS fire detections in Amazonas (State in Brazil) in the time frame 1 January 2003 to 31 December 2019 (image credit: NASA Earth Observatory)

- “Tallying active fire detections for a given area is a reasonable first step if you’re trying to quickly assess or characterize a fire season or fire outbreak. But it’s only that — a first step,” explained Niels Andela, one of Morton’s colleagues at NASA. “By looking at other measures like the intensity, location, and duration of fires, it became clear that 2019 was a departure from the norm.”

- One important point to understand: not all of the red spots on fire activity maps in 2019 were deforestation fires in the rainforest. “A closer look at land cover maps and high-resolution satellite imagery shows that many of the fire detections in 2019 were located in shrublands, grasslands, and savannas that people wouldn’t recognize as rainforest,” explained Giglio. According to INPE data, 34 percent of the total fire hot spots detected in Brazil in 2019 were in Amazonia, the rainforest. In contrast, 50 percent were in the Cerrado, a savanna region with spotty tree cover, plenty of pastures and farms, and large numbers of fires every year. Five percent or less burned in the Brazilian Pantanal—a grassy wetland region in southwestern Brazil—or other biomes.

- But in certain areas, the story looks different. Fires were especially common along the Trans-Amazonian highway in Brazil’s far western state of Amazonas. According to Giglio, MODIS made 11,516 fire detections in Amazonas in August, the second most the sensor has ever observed for the state in that month. As shown by the burned area map at the top of the page, severe fires also occurred along key highways in Parã, Mato Grosso, and Rondônia where new deforestation of rainforest is common.


Figure 81: MODIS fire observations on 28 October 2019 (image credit: NASA Earth Observatory)

- While fire activity declined sharply in September across the Brazilian rainforest, fire detections continued to rise in the Cerrado in September. And the Pantanal in Brazil received little relief from either the military or the weather. Intense fires—many of them uncontrolled pasture fires and some ignited by lightning—raced through dried grasslands there, as well as through nearby dry forests in Paraguay and Bolivia (most notably the Gran Chaco and Chiquitano forests) from August until November. The fires in this region jump out as an area of particularly anomalous burning in the burned area map at the top of the page. But if you look at the number of fire detections for Brazil, Paraguay, or Bolivia or for certain ecoregions, the numbers do not necessarily stand out because the fire detections get divided between three countries and multiple ecoregions.

- “One of the things I was reminded of during the 2019 Amazon fires—and after many big fire events around the world—is that you have to be really aware of how people are defining boundaries when you are interpreting statistics,” said Giglio. “If you aren’t careful, it is easy for important stories or anomalies to get lost or under- or over-represented.”

- For Setzer, 2019 was a potent reminder of the value of remote sensing. “In Brazil, we had people taking extreme views on both sides of this debate,” he said. “In August, we had people saying nothing of note was happening. You had others saying the entire rainforest had burned down. What actually happened was somewhere in the middle.”

- “We had a lot of scrutiny from politicians, from other scientists, from the media, even from common people who compared the satellite data on the Internet to what they were seeing on the ground. Virtually everybody came to the same conclusion: the satellite data was correct. And based on the satellite monitoring, control measures were taken,” said Setzer.

- For Morton and Andela, the 2019 fires underscored how much technology has improved and how much research is left to do. “There is a lot more we can glean from the data that satellites are already collecting—especially a measure of intensity called fire radiative power—and from nighttime observations of fires from VIIRS,” said Andela, who is currently working on a study about the 2019 fire season and a project with a NASA/USAID SERVIR Amazonia team to track understory fires with VIIRS. “Since VIIRS is extremely sensitive to fires and now there are two copies of VIIRS in orbit, our ability to detect and track small fires—even those burning underneath the canopy—has increased dramatically.”

- “But we also need new platforms for tracking fires because MODIS and VIIRS only take data during just a few short time windows each day,” said Morton, who is in the process of developing plans for a mission that would make measurements several times each day. “That leaves us guessing about what fires are doing the rest of the day.”

• February 28, 2020: The South Sandwich Islands are a string of small volcanic peaks in a remote part of the South Atlantic Ocean near Antarctica and South America. The three tallest islands—Saunders, Montagu, and Bristol—approach at least 1000 meters (3,300 feet) above sea level. 52)

- “Imagine being on a motor boat looking back at triangular, banded patterns forming behind you as wake waves ripple through the water,” said NASA research meteorologist Galina Wind. “This is the same effect, except the mountains are stationary and the surrounding air is rushing by at a good clip. The moving air hits the still mountain in the same way the prow of a moving boat hits still water.”

- As air funneled around the islands in February, its temperature and humidity was just right for the crests of the lee waves to rise and cool the air and form clouds. “At the wave crest, you get clouds. At the wave dip, no clouds,” said Wind. “Who knew mountains in the middle of the ocean and motor boats on a lake had so much in common?”

- Wave clouds would have formed on the leeward side all of the islands in the image, even though the patterns were not easily visible behind all of them. “For the three northern islands, the wakes are there, but there is another cloud layer on top, partially ruining the view,” said Wind. “Clouds have a habit of being multi-layered.”


Figure 82: As shown by this natural-color satellite image, that was enough height to disrupt air masses flowing around the islands and to create an interlocking series of mountain-wave clouds. The image was acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite around 11 a.m. local time on February 5, 2020, as westerly winds blew over the islands (image credit: NASA Earth Observatory, image by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Adam Voiland)

• February 25, 2020: In late February 2020, strong Saharan winds picked up dust from Africa and carried it over the Canary Islands, severely reducing visibility and disrupting travel by land and air. Some public officials described it as the worst sandstorm in decades. 53)

- Such dust events, known to islanders as “La Calima,” typically last several days. They are provoked by hot, dry southeasterly or easterly winds blowing out from Morocco and Western Sahara, and they are sometimes associated with the Saharan air layer. Calima storms turn the skies orange or red over the island chain.

- Due to strong winds—with gusts up to 120 kilometers (75 miles) per hour—and poor visibility, all airports across the Canary Islands were closed on February 22 and most stayed closed until February 24. Close to 800 flights were cancelled or re-routed. Some roads were also shut down due to limited visibility.

- Schools and universities were closed on February 24, and people were advised to keep their windows shut and to stay indoors due to poor air quality. Some Carnival events were postponed or curtailed due to the dusty conditions. Strong winds also whipped the flames from several wildfires on Tenerife and Gran Canaria, forcing the evacuation of 2,000 people.


Figure 83: The MODIS instrument on NASA’s Terra and Aqua satellites acquired these natural-color images of the storm on February 22 and 23, 2020. Gran Canaria, Fuerteventura, and Lanzarote appeared to be hardest hit by the storm, which started abruptly on February 22 and continued as rain clouds started to roll in on the 24th. Visibility was reduced to tens of meters in some places (NASA Earth Observatory, images by Joshua Stevens, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Michael Carlowicz)

• February 5, 2020: Persistent heavy rains across the Mississippi River watershed swelled the river to its banks, occasionally causing water to spill onto floodplains in late January 2020. By early February, the river was near or above flood stage in parts of Arkansas, Tennessee, Mississippi, and Louisiana, though high water has already crested in most places. 54)

- As of February 4, the NOAA Advanced Hydrological Prediction Service reported 3 river gauges with moderate flooding, 12 with minor flooding, and 17 near flood stage along the Lower Mississippi. The river crested in Natchez, Mississippi, on January 30, and approached major flood stage near Baton Rouge, Louisiana, on February 1. On the morning of February 4, the National Weather Service (NWS) was still issuing flood warnings for the river near Baton Rouge, Donaldsonville, and Red River Landing.

- NWS scientists noted that soils were nearly saturated across large sections of the Upper Mississippi watershed, leaving little capacity to soak up new rainfall. Much of the rainfall this winter has ended up flowing down the river. The Lower Mississippi usually sees its highest waters in April.

- In 2019, the Mississippi River was at or above flood stage for most of January through early August. Much of the region is still trying to rebuild and repair infrastructure as the 2020 spring flood season looms.


Figure 84: The MODIS instrument on NASA’s Terra satellite acquired this false-color image of the Mississippi Delta and the lower reaches of the river on 2 February 2020 (image credit: NASA Earth Observatory, image by Lauren Dauphin, using MODIS data from NASA EOSDIS/LANCE and GIBS/Worldview. Story by Mike Carlowicz)

Minimize Terra continued

Sensor complement: (ASTER, CERES (2 units), MISR, MODIS, MOPITT)

Measurement Region


Instruments used


Cloud properties
Radiative energy flux
Tropospheric chemistry
Aerosol properties
Atmospheric temperature
Atmospheric humidity


Land surface

Land cover and land use change
Vegetation dynamics
Surface temperature
Fire occurrence
Volcanic effects



Surface temperature
Phytoplankton and dissolved organic matter



Land ice change
Sea ice
Snow cover


Table 2: Overview of major physical process measurements of the Terra instruments

ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer):

ASTER is a Japanese instrument sponsored by METI (Ministry of Economy, Trade and Industry) and a cooperative project with NASA. The ASTER team leaders are Hiroji Tsu of ERSDAC (Japan) and Anne B. Kahle of JPL. ASTER management is provided by JAROS (Japan Resources Observation System Organization). ASTER was built by NEC, MELCO, Fujitsu, and Hitachi. A Joint US/Japan Science Team is responsible for instrument design, calibration, and validation. Previous instrument name: ITIR (Intermediate Thermal Infrared Radiometer).

Objective: Provision of high-resolution and multispectral imagery of the Earth's surface and clouds for a better understanding of the physical processes that affect climate change. Applications: studies of the surface energy balance (surface brightness temperature), plant evaporation, vegetation and soil characteristics, hydrologic cycle, volcanic processes, etc. 55) 56) 57) 58) 59) 60)

The ASTER instrument consists of three separate instrument subsystems; each subsystem operates in a different spectral region, has its own telescope(s), and is built by a different Japanese company. The subsystems are in the VNIR (Visible Near Infrared), SWIR (Shortwave Infrared) and TIR (Thermal Infrared) spectral regions. The VNIR and SWIR subsystems employ pushbroom imaging while the TIR subsystem performes whiskbroom imaging. ASTER is pointable in the cross-track direction such that any point on the globe may be observed at least once within 16 days in all 14 bands and once every 5 days in the VNIR bands. The absolute temperature accuracy is 3K in the 200-240 K range, 2K in the 240-270 K range, and 2 k in the 340-370 K range for TIR bands.

Total instrument mass=421 kg; power=463 W average, 646 W peak; data rate = 8.3 Mbit/s average and 89.2 Mbit/s peak; thermal control by 80 K Stirling cycle coolers, heaters, cold plate/capillary pumped loop, and radiators; pointing accuracy: for control = 1 km on ground (all axes), knowledge= 342 m on ground (per axis), stability=2 pixels for 60 seconds. shown in this figure.


Band No


Band No


Band No


Spectral bands in µm


0.52 - 0.60


1.600 - 1.700


8.125 - 8.475


0.63 - 0.69


2.145 - 2.185


8.475 - 8.825


0.76 - 0.86


2.185 - 2.225


8.925 - 9.275


0.76 - 0.86


2.235 - 2.285


10.25 - 10.95

Stereoscopic viewing
capability along-track


2.295 - 2.365


10.95 - 11.65


2.360 - 2.430



Ground resolution

15 m

30 m

90 m

IFOV (nadir)

21.5 µrad

42.6 µrad

128 µrad

Data rate

62 Mbit/s

23 Mbit/s

4.2 Mbit/s

Cross-track pointing

±24º (±318 km)

±8.55º (116 km)

±8.55º (116 km)

Swath width

60 km

60 km

60 km

Detector type

Si (CCD of 5000 elements,
4000 are used)

PtSi-Si Schottky barrier linear array, cooled to 80 K (Stirling cooler)

cooled to 80 K
(Stirling cooler)

Data quantization

8 bit

8 bit

12 bit

Radiometric accuracy




Table 3: ASTER instrument parameters of the three subsystems

The cooling capacity of the SWIR cryocooler is a nominal value of 1.2 W at 70 K; the measured power consumption is 43.5 W, which satisfies the requirement that it be less than 55 W. The cooling capacity of the TIR cryocooler is a nominal value of 1.2 W at 70 K; the measured power consumption is 50 W, which satisfies the requirement that it be less than 55 W. 61)

The VNIR subsystem, built by NEC Corporation, is a reflecting-refracting improved Schmidt design. VNIR features two telescopes, one nadir-looking with a three-spectral-band detector, and the other backward-looking with a single-band detector. The backward-looking telescope provides a second view of the target area in band 3B for stereo observations. Cross-track pointing is accomplished by rotating the entire telescope assembly. Band separation is through a combination of dichroic elements and interference filters that allow all three bands to view the same ground area simultaneously. Calibration of the nadir-pointing detectors is performed with two halogen lamps.



TM on Landsat 4/5

Wavelength Region

Band No.

Spectral Range (µm)

Band No.

Spectral Range (µm)





0.45 - 0.52


0.52 - 0.60
0.63 - 0.69
0.76 - 0.86


0.52 - 0.60
0.63 - 0.69
0.76 - 0.90




1.60 - 1.70

2.145 - 2.185
2.185 - 2.225
2.235 - 2.285
2.295 - 2.365
2.360 - 2.430


1.55 - 1.75


2.08 - 2.35



8.125 - 8.475
8.475 - 8.825
8.925 - 9.275
10.25 - 10.95
10.95 - 11.65


10.4 - 12.5

Table 4: Spectral range comparison of ASTER and TM (on Landsat)

The SWIR subsystem, built by MELCO (Mitsubishi Electric Company), uses a nadir-pointing aspheric refracting telescope. Cross-track pointing is accomplished by a pointing mirror. The size of the detector/filter combination requires a wide spacing of the detectors, causing in turn a parallax error of about 0.5 pixels per 900 m of elevation. This error is correctable if elevation data (DEM) are available. Two halogen lamps are used for calibration. The maximum data rate is 23 Mbit/s. 62)

The TIR subsystem employs a Newtonian catadioptric system with aspheric primary mirror and lenses for aberration correction. The telescope of the TIR subsystem is fixed to the platform, pointing and scanning is done with a single mirror. The line of sight can be pointed anywhere in the range ± 8.54º in the cross-track direction of nadir, allowing coverage of any point on Earth over the platform's 16 day repeat cycle. Each channel uses 10 mercury cadmium telluride (HgCdTe) detectors in a staggered array with optical bandpass filters over each detector element to define the spectral response. Each detector has its own pre- and post-amplifier for a total of 50. The detectors are being operated at 80 K using a mechanical split-cycle Stirling cooler. - In scanning mode, the mirror oscillates at about 7 Hz with data collection occurring over half the cycle. The scanning mirror is capable of rotating 180º from the nadir position to view an internal full-aperture reference surface, which can be heated to 340 K. 63)

Overview of some ASTER instrument characteristics:

• The Visible Near InfraRed (VNIR) telescope subsystem features a backward viewing band (next to a nadir viewing band) for high-resolution along-track stereoscopic observation (two-line VNIR imager)

• Provision of multispectral thermal infrared data of high spatial resolution (8 to 12 µm window region, globally)

• ASTER provides the highest spatial resolution surface spectral reflectance, temperature, and emissivity data within the Terra instrument suite

• The instrument provides the capability to schedule on-demand data acquisition requests

• The VNIR and SWIR subsystems employ pushbroom imaging while the TIR subsystem performes whiskbroom imaging

• ASTER provides band-to-band registration of the 14 spectral bands, not only within each subsystem, but also among the three subsystems. Accuracies of 0.2 pixels within each subsystem and 0.3 pixels among different subsystems are achieved.


Figure 85: Illustration of the VNIR and SWIR subsystems of ASTER (image credit: JPL)


Figure 86: Illustration of the TIR subsystem of ASTER (image credit: JPL)

CERES (Clouds and the Earth's Radiant Energy System):

The CERES instrument of NASA/LaRC was built by Northrop Grumman (formerly TRW Space and Technology Group) of Redondo Beach, CA (PI: Bruce Wielicki). Objective: Long-term measurement of the Earth's radiation budget and atmospheric radiation from the top of the atmosphere to the surface; provision of an accurate and self-consistent cloud and radiation database (input to WCRP international programs like TOGA, WOCE, and GEWEX). Retrieval of cloud parameters in terms of measured areal coverage, altitude, liquid water content, and shortwave and longwave optical depths. Specific science objectives are: 64) 65) 66) 67)

• For climate change analysis, provide a continuation of the ERBE record of radiative fluxes at the top of the atmosphere (TOA), analyzed using the same algorithms that produced the ERBE data.

• Double the accuracy of estimates of radiative fluxes at TOA and the Earth's surface.

• Provide the first long-term global estimates of the radiative fluxes within the Earth's atmosphere.

• Provide cloud property estimates that are consistent with the radiative fluxes from surface to TOA.


Figure 87: View of one CERES radiometer and location of instruments on the Terra spacecraft (image credit: NASA/LaRC)


Figure 88: Observation geometry of the CERES instruments on Terra (image credit: NASA/LaRC)

The CERES instrument assembly (of ERBE heritage) consists of a pair of broadband scanning radiometers (two identical instruments), referred to as FM-1 (Flight Module-1) and FM-2; one instrument operates in the cross-track mode for complete spatial coverage from limb to limb; the other one operates in a rotating scan plane (biaxial scanning) mode to provide angular sampling. The cross-track radiometer measurements are a continuation of the ERBS mission. The biaxially scanning radiometer provides angular flux information to improve model accuracy. A single cross-track CERES instrument is flown on TRMM (Tropical Rainfall Measuring Mission), while the dual-scanner instrument is flown on Terra (EOS/AM-1) and Aqua (EOS/PM-1).

The CERES instrument consists of three major subassemblies: 1) Cassegrain telescope, 2) baffle for stray light, and 3) detector assembly, consisting of an active and compensating element. Radiation enters the unit through the baffle, passes through the telescope and is imaged onto the IR detector. Uncooled infrared detection is employed.


Figure 89: Schematic view of the CERES instrument (image credit: NASA/LaRC)

Instrument parameters (2 identical scanners): total mass of 100 kg , power = 103 W (average, 2 instruments), data rate = 20 kbit/s, duty cycle = 100%, thermal control by heaters and radiators, pointing knowledge = 180 arcsec. The design life is six years. CERES measures longwave (LW) and shortwave (SW) infrared radiation using thermistor bolometers to determine the Earth's radiation budget. There are three spectral channels in each radiometer:

- VNIR+SWIR: 0.3 - 5.0 µm (also referred to as SW channel); measurement of reflected sunlight to an accuracy of 1%.

- Atmospheric window: 8.0 - 12.0 µm (also referred to as LW channel); measurement of Earth-emitted radiation, this includes coverage of water vapor

-Total channel radiance in the spectral range of 0.35 - 125 µm;. reflected or emitted infrared radiation of the Earth-atmosphere system, measurement accuracy of 0.3%.

Limb-to-limb scanning with a nadir IFOV (Instantaneous Field of View) of 14 mrad, FOV = ±78º cross-track, 360º azimuth. Spatial resolution = 10-20 km at nadir. Each channel consists of a precision thermistor-bolometer detector located in a Cassegrain telescope.

Instrument calibration: CERES is a very precisely calibrated radiometer. The instrument is measuring emitted and reflected radiative energy from the surface of the Earth and the atmosphere. A variety of independent methods used to verify calibration: 68)

• Internal calibration sources (blackbody, lamps)

• MAM (Mirror Attenuator Mosaic) solar diffuser plate. MAM is used to define in-orbit shifts or drifts in the sensor responses. The shortwave and total sensors are calibrated using the solar radiances reflected from the MAM's. Each MAM consists of baffle-solar diffuser plate systems, which guide incoming solar radiances into the instrument FOV of the shortwave and total sensor units.

• 3-channel deep convective cloud test

- Use night-time 8-12 µm window to predict longwave radiation (LW): cloud < 205K

- Total - SW = LW vs Window predicted LW in daytime for same clouds <205K temperatures

• 3-channel day/night tropical ocean test

• Instrument calibration:

- Rotate scan plane to align scanning instruments TRMM, Terra during orbital crossings (Haeffelin: reached 0.1% LW, window, 0.5% SW 95% configuration in 6 weeks of orbital crossings of Terra and TRMM)

- FM-1 and FM-2 instruments on Terra at nadir

Instrument heritage

Earth Radiation Budget Experiment (ERBE)

Prime contractor

Northrop Grumman (formerly TRW)

NASA center responsible

LaRC (Langley Research Center)

Three channels in each radiometer

Total radiance (0.3 to 100 µm); Shortwave (0.3 to 5 µm); Window (8 to 12 µm)


Limb to limb

Spatial resolution

20 km at nadir

Instrument mass, duty cycle

50 kg/scanner, 100%

Instrument power

47 W (average) per scanner, 104 W (peak: biaxial mode) both scanners

Data rate

10 kbit/scanner

Thermal control

Use of heaters and radiators

Thermal operating range

38±0.1ºC (detectors)

FOV (Field of View)

±78º cross-track, 360º azimuth


14 mrad

Instrument pointing requirements (3σ)

720 arcsec
180 arcsec
79 arcsec/6.6 sec

Instrument size

60 cm x 60 cm x 57.6 cm/unit

Table 5: CERES instrument parameters

The international CERES Science Team includes scientists from NASA, NOAA, US universities, France (CNRS), and Belgium (RMIB).

Data: A key element in the success of CERES, beyond the development of an instrument, is the development of data analysis and interpretation techniques for producing radiation and cloud products that meet the scientific objectives of the project.

MISR (Multi-angle Imaging SpectroRadiometer):

The MISR instrument was designed and developed by NASA/JPL (PI: D. J. Diner). Objective: provision of multiple-angle continuous sunlight coverage of the Earth with high spatial resolution (multidirectional observations of each scene within a time scale of minutes). MISR uses nine CCD pushbroom cameras to observe the Earth at nine discrete viewing angles: one at nadir, plus eight other symmetrical views at 26.1º, 45.6º, 60.0º, and 70.5º forward and aft of nadir. Images at each angle are obtained in four spectral bands centered at 0.446, 0.558, 0.672, and 0.866 µm. Each of the 36 instrument data channels (i.e. four spectral bands for each of the nine cameras) is individually commandable to provide ground sampling of 275 m, 550 m, or 1100 m. The swath is 360 km; multi-angle coverage (repeat cycle) of the entire Earth in nine days at the equator, and in two days at higher latitudes. By design, MISR is an along-track nine-line camera system, offering multidirectional observations of each ground (or target) scene. 69) 70) 71) 72)


View angle

Boresight angle

Swath offset angle

Effective focal length


70.3º forward



123.67 mm


60.2º forward



95.34 mm


45.7º forward



73.03 mm


26.2º forward



58.90 mm


0.1º nadir



58.94 mm


26.2º aftward



59.03 mm


45.7º aftward



73.00 mm


60.2º aftward



95.33 mm


70.6º aftward



123.66 mm

Table 6: MISR as-built camera pointing specifications

Application: MISR provides global maps of planetary and surface albedo (brightness temperature), and aerosols and vegetation properties. Monitoring of global and regional trends in radiatively important optical properties (eg., opacity, single scattering albedo, and scattering phase function) of natural and anthropogenic aerosols.


Figure 90: A camera of the MISR instrument with support electronics (image credit: NASA/JPL)


Figure 91: Cut-away view of the MISR instrument (image credit: NASA/JPL)

MISR images are acquired in two observing modes: global and local. The global mode provides continuous planet-wide observations, with most channels operating at moderate resolution; some selected channels operate at the highest resolution for cloud screening and classification, image navigation, and stereo-photogrammetry. The local mode provides data at the highest resolution in all spectral bands and all cameras for selected 300 km x 300 km regions. In addition to data products providing radiometrically calibrated and geo-rectified images, global mode data will be used to generate two standard (level 2) science products: TOA (Top-of-Atmosphere)/Cloud Product and the Aerosol/Surface Product.

MISR on-orbit radiometric calibration is performed bi-monthly, using deployable white spectralon panels to reflect diffuse sunlight into the cameras, and a set of photodiodes to measure the reflected radiance. Additionally, vicarious calibrations using field and AirMISR data are done on six-month intervals. Geometric calibration of the cameras is done using ground control points.



Mission life

6 years

Global coverage time

Every 9 days, with repeat coverage between 2-9 days depending on latitude

Cross-track swath width

360 km common overlap of all 9 cameras, FOV = ±60º along-track and ±15º cross-track.

Nine CCD cameras

Named An, Af, Aa, Bf, Ba, Cf, Ca, Df, and Da where fore, nadir, and aft viewing cameras have names ending with letters f, n, a respectively and four camera designs are named A, B, C, D with increasing viewing angle respectively

View angles at Earth surface

0º, 26.1º, 45.6º, 60.0º, and 70.5º

Spectral coverage

Four bands centered at 0.446, 0.558, 0.672, and 0.866 µm (blue, green, red, and NIR)

Spatial resolution

275 m, 550 m, or 1.1 km, selectable in-flight


CCDs, each camera with 4 independent line arrays (one per filter),1504 active pixels per line

Radiometric accuracy

3% at maximum signal

Detector temperature

-5 ±0.1º C (cooled by thermo-electric cooler) of focal plane

Structure temperature

5º C

Instrument mass, power

148 kg, 131 W peak and 83 W average

Instrument size

0.9 m x 0.9 m x 1.3 m

Data rate

3.3 Mbit/s average, 9.0 Mbit/s peak

Table 7: MISR instrument specification


Figure 92: Illustration of the MISR observing concept from Terra (image credit: NASA/JPL)

MODIS (Moderate-Resolution Imaging Spectroradiometer):

MODIS is a NASA/GSFC instrument; prime contractor is Raytheon SBRS, Goleta, CA, formerly Hughes SBRS (Science team leader: V. Salomonson); MODIS algorithm development by an international team of scientists from USA, UK, Australia, and France; there are four discipline groups: Atmosphere, Land, Oceans, and Calibration. 73) 74) 75) 76)

The instrument is flown on the Terra and Aqua satellites (prime instrument). Objective: to measure biological and physical processes on a global basis on time scales of 1 to 2 days. Specific science goals are:

• To determine surface temperature at 1 km resolution, day and night, with an absolute accuracy of 0.2 K for ocean and 1 K for land

• To obtain ocean color (ocean-leaving spectral radiance) from 415 to 653 nm

• To determine chlorophyll fluorescence within 50% at surface water concentrations of 0.5 mg per cubic meter of chlorophyll a

• To obtain chlorophyll a concentrations within 35%

• To obtain information on vegetation and land surface properties, land cover type, vegetation indices, and snow cover and snow reflectance

• To obtain cloud cover with 500 m resolution by day and 1000 m resolution at night

• To obtain cloud properties and aerosol properties

• To determine information on biomass burning

• To obtain global distribution of atmospheric stability and total precipitable water.


Figure 93: Artist's rendition of the MODIS instrument showing the 360º scan mirror (image credit: Hughes SBRS, NASA)


Figure 94: Schematic view of the MODIS instrument (image credit: Raytheon SBRS, NASA)





Instrument type

Opto-mechanical design (whiskbroom scanner)

Data rate

10.6 Mbit/s (peak daytime), 6.1 Mbit/s (orbital average)

Scan rate

20.3 rpm

Data quantization

12 bit


17.8 cm diameter off-axis, afocal (collimated) with intermediate field stop

Spatial resolution

250 m (bands 1-2)
500 m (bands 3-7)
1000 m (bands 8-36)


1.0 m x 1.6 m x 1.0 m

Swath width, FOV

2330 km, 110º (1354 pixels in cross-track)


229 kg

Swath length/scan

10 km (10 pixels in parallel along track)


162.5 W

Design life

6 years

Table 8: Some specification parameters of the MODIS instrument

MODIS is an optomechanical imaging spectroradiometer (whiskbroom type), consisting of a cross-track scan mirror (continuously rotating double-sided scan mirror assembly) and collecting optics, and a set of linear detector arrays with spectral interference filters located in four focal planes. To accommodate frequent infrared calibration (every 1.47 s), a 360º rotating paddle-mirror is centered within a scan cavity to provide the optical subsystem with sequential views of the five calibrators and the Earth.

The optical arrangement provides imagery in 36 discrete bands between 0.4 and 14.5 µm (21 bands within 0.4-3.0 µm range, 15 bands within 3-14.5 µm range). The spectral bands provide a spatial resolution of 250 m, 500 m, and at 1 km at nadir. MODIS heritage: AVHRR (POES), HIRS (POES), TM (Landsat), CZCS (Nimbus-7). In fact, the MODIS instrument is considered to be a next-generation AVHRR instrument, having 36 bands (AVHRR/3 has 6) and a spatial resolution of 250 m (AVHRR has 1 km).

A high-performance passive radiative cooler provides cooling to 83 K for the infrared bands on two HgCdTe FPAs (Focal Plane Assemblies). A new photodiode-silicon readout technology for the VNIR range provides unsurpassed quantum efficiency and low-noise readout with a very good dynamic range.


Figure 95: Functional architecture of the MODIS instrument (image credit: Raytheon SBRS)


Figure 96: Major elements of the MODIS instrument (image credit: NASA)

MODIS polarization sensitivity < 2% for the visible range out to 2.2 µm; the performance goal for SNR (Signal-to-Noise Ratio) and NEΔT (Noise-Equivalent Temperature Difference) values is 30-40% better than the required values in Table 9.; absolute irradiance accuracy of 5% for <3 µm and 1% for >3 µm; absolute temperature accuracy of 0.2 K for oceans and 1 K for land; daylight reflection and day/night emission spectral imaging; swath width of 2330 km at 110º FOV; scan rate = 20.3 rpm across track; instrument mass = 250 kg; duty cycle = 100%; power = 225 W (average); data rate = 6.2 Mbit/s (average), 10.6 Mbit/s (peak daytime), 3.2 Mbit/s (night); quantization = 12 bit. Instrument IFOV (spatial resolution) = 250 m (bands 1-2), =500 m (bands 3-7), = 1000 m (bands 8-36).

The observations are made at three spatial resolutions (nadir): 0.25 km for bands 1-2 with 40 detectors per band, 0.5 km for bands 3-7 with 20 detectors per band, and 1 km for bands 8-36 with 10 detectors per band. All the detectors, aligned in the along-track direction, are distributed on four focal plane assemblies (FPAs) according to their wavelengths: visible (VIS), near infrared (NIR), short- and mid-wave infrared (SMIR), and long-wave infrared (LWIR).

Primary Use

Band No.


Spectral Radiance
(W m-2 µm-1 sr-1)

Required SNR
(Required NEΔT
in K)

Resolution at nadir



0.620 - 0.670
0.841 - 0.876



250 m



0.459 - 0.479
0.545 - 0.565
1.230 - 1.250
1.628 - 1.652
2.105 - 2.155



500 m

Ocean Color/


0.405 - 0.420
0.438 - 0.448
0.483 - 0.493
0.526 - 0.536
0.546 - 0.556
0.662 - 0.672
0.673 - 0.683
0.743 - 0.753
0.862 - 0.877



1000 m

Water Vapor


0.890 - 0.920
0.931 - 0.941
0.915 - 0.965





3.660 - 3.840
3.929 - 3.989
3.929 - 3.989
4.020 - 4.080





4.433 - 4.598
4.482 - 4.549



Cirrus Clouds


1.360 - 1.390



Water Vapor


6.535 - 6.895
7.175 - 7.475
8.400 - 8.700





9.580 - 9.880





10.780 - 11.280
11.770 - 12.270



Cloud Top


13.185 - 13.485
13.485 - 13.785
13.785 - 14.085
14.085 - 14.385



Table 9: MODIS spectral performance parameters

MODIS onboard calibration employs various techniques for comprehensive verification of spectral, radiometric and spatial measurements. They include: 77) 78) 79) 80)

• Spectroradiometric Calibration Assembly (SRCA)

- Spectral calibration of reflective channel channel bandpasses

- Verification of spectral band registration

- DC restoration on every scan using a direct view of space

- Lunar calibration via the space-view port as well as periodic rotations of the S/C to enable full scans across the moon through the active scan aperture

• Blackbody (BB) calibration of thermal bands on every scan (a v-groove blackbody)

• Solar Diffuser (SD) reference

• Solar Diffuser Stability Monitor (SDSM)

The spectral mode of the SRCA device consists of a light source, a grating monochromator, and a beam collimator. The light source is a SIS (Spectral Integration Sphere) with lamps distributed inside. By combining the use of the spectral filters mounted on the filter wheel assembly and the grating monochromator, the SRCA is capable of performing spectral characterizations of the RSB (Reflective Solar Bands) ranging from 0.41 to 2.2 µm. Its spectral calibration is referenced to the ground equipment (SpMA) with high accuracy.


Figure 97: Schematic view of the SRCA device (image credit: NASA/GSFC)

The SD/SDSM system is used for the RSB calibration and BB for the TEB (Thermal Emissive Bands) calibration. The SRCA is primarily used for the sensor's spectral (RSB only) and spatial (TEB and RSB) characterization. The RSB calibration is reflectance based using a sensor’s view of diffusely reflected sunlight from a solar diffuser (SD) plate with a known bi-directional reflectance and distribution function (BRDF). Because of the solar exposure onto the SD plate, its reflectance properties slowly degrade on-orbit.

The Blackbody is located in front of and slightly above the Scan Mirror, which views the BB with every revolution. The BB assembly provides a full-aperture radiometric calibration source of the MWIR and LWIR bands to within 1 percent absolute accuracy. It provides known radiance levels and is also used in the DC restore operation (a space-view signal level provides the second level for all bands in the two-point calibration). In normal operation the BB is kept at the instrument’s ambient temperature (nominally 273 K), though it is possible to heat and control the BB to 315K. Twelve sensors below the assembly's surface monitor its temperature. Each sensor is calibrated to National Institute of Standards & Technology (NIST) traceable standards, and can determine the temperature of the assembly to within ± 0.1 K.


Figure 98: View of the BB assembly (image credit: NASA/GSFC)

To maintain the calibration and data quality, a solar diffuser stability monitor (SDSM) is used in tandem with the SD to track its degradation or BRDF changes. The SDSM system has a small integration sphere (SIS) with a single input aperture and nine filtered detectors. Each filter has a narrow spectral bandpass so that the change in reflectance is effectively monitored at nine discrete wavelengths between 0.4 µm and 1.0 µm. A three-position fold mirror enables the detectors to view sequentially a dark scene, direct sunlight, and illumination from the SD (Solar Diffuser). The direct sunlight is attenuated via a two-percent transmitting screen to keep the radiance within the dynamic range of the SDSM’s detector/amplifier combination.


Figure 99: The MODIS SD device (image credit: NASA/GSFC)


Figure 100: The SDSM device (image credit: NASA/GSFC)

MODIS product overview: MODIS provides global coverage every 1 to 2 days. It provides specific global survey data, which includes the following (some standard data products):

• Cloud mask: at 250 m and 1 km resolution by day and at night

• Aerosol concentration and optical properties: at 5 km resolution over oceans and 10 km over land during the day

• Cloud properties: characterized by optical thickness, effective particle radius, cloud droplet phase, cloud-top altitude, cloud-top temperature

• Vegetation and land-surface cover, conditions, and productivity, defined as:

- Vegetation indices corrected for atmospheric effects, soil, polarization, and directional effects

- Surface reflectance

- Land-cover type with identification and detection of change

- Net primary productivity, leaf-area index, and intercepted photosynthetically active radiation

• Snow and sea-ice cover and reflectance

• Surface temperature with 1 km resolution, day and night, with absolute accuracy goals of 0.3-0.5ºC for oceans and 1ºC for land surfaces.

• Ocean color: defined as ocean-leaving spectral radiance within 5% from 415-653 nm, based on adequate atmospheric correction from NIR sensor channels

• Concentration of chlorophyll-a within 35% from 0.05 to 50 mg/m3 for case 1 waters

• Chlorophyll fluorescence within 50% at surface water concentrations of 0.5 mg/m3 of chlorophyll-a.

MOPITT (Measurement of Pollution in the Troposphere):

MOPITT is a Canadian sensor supported by CSA, built by COM DEV, Cambridge, Ontario (PI: J. R. Drummond, University of Toronto). The MOPITT instrument design is of MAPS (Measurements of Air Pollution from Space) heritage, flown on STS-2 (November 12.-14, 1981), then on STS-13 (October 5 -13, 1984), and then twice in 1994 (STS-59, STS-68). MOPITT is the first satellite sensor to use gas correlation spectroscopy (A technique to increase the sensitivity of the instrument to the gas of interest by separating out the regions of the spectrum where the gas has absorption lines and integrating the signal from just those regions. The specific wavelengths are located using a sample of the gas as a reference for the spectrum). By using correlation cells of differing pressures, some height resolution can be obtained. Thus MOPITT has multiple channels to provide height resolution, it also carries multiple channels to afford some redundancy. Definitions of acronyms in Table 10: LMC (Length Modulator Cell), PMC (Pressure Modulator Cell). 81) 82) 83) 84) 85) 86) 87) 88)

The CO profile measurements are made using upwelling thermal radiance in the 4.6 µm fundamental band. The troposphere is resolved into about four layers with approximately 3 km vertical resolution, 22 km horizontal resolution and 10% accuracy. Pressure Modulated Cells (PMCs) are used to view the upper layers whilst Length Modulated Cells (LMCs) are used for the lower troposphere measurements. By varying the cell pressures the modulators can be biased to view the different layers.

The MOPITT instrument contains four optical chains initiated by four scan mechanisms, which are split into eight independent channels. Each channel uses a technique known as correlation spectroscopy to perform the science measurements. This uses a sample of gas in the optical path. By performing synchronous demodulation of the detected infrared signal, the system functions as a complex filter, providing very good spectral resolution and good sensitivity by incorporating several molecular lines simultaneously.


Figure 101: Isometric optical system layout of the MOPITT instrument (image credit: University of Toronto)


Figure 102: Schematic illustration of the MOPITT instrument (image credit: University of Toronto)


Figure 103: Schematic view of the correlation radiometry concept (image credit: NCAR, University of Toronto)


Figure 104: Photograph showing the finished PMC for MOPITT (image credit: Oxford Physics)

Channel No

Cell type

Cell Pressure (kPa)

Center Wavelength (cm-1)

Spectral band constituent




2166 (52)

CO thermal




4285 (40)

CO solar




2166 (52)

CO thermal




4430 (140)

CH4 solar




2166 (52)

CO thermal




4285 (40)

CO solar




2166 (52)

CO thermal




4430 (140)

CH4 solar

Table 10: Channel definition of MOPITT

The instrument measures emitted and reflected infrared radiance in the atmospheric column. Analysis of these data permit retrieval of tropospheric CO profiles and total column CH4. Objective: study of how these gases interact with the surface, ocean, and biomass systems (distribution, transport, sources and sinks). Measurements are performed on the principle of correlation spectroscopy utilizing both pressure-modulated and length-modulated gas cells, with detectors at 2.3, 2.4, and 4.7 µm. Vertical profile of CO (carbon monoxide) and total column of CH4 (methane) are to be measured; CO concentration in 4 km layers with an accuracy of 10%; CH4 column abundance accuracy is 1%.

Swath width = 616 km, spatial resolution = 22 x 22 km; instrument mass = 182 kg; power = 243 W; duty cycle = 100%; data rate = 25 kbit/s; thermal control by an 80 K Stirling cycle cooler, capillary-pumped cold plate and passive radiation; thermal operating range = 25º C (instrument) and 100 K (detectors).

MOPITT is designed as a scanning instrument. IFOV = 1.8º x 1.8º (22 km x 22 km at nadir). The instrument scan line consists of 29 pixels, each at 1.8º increments. The maximum scan angle is 26.1º off-axis which is equivalent to a swath width of 640 km. - MOPITT data products include gridded retrievals of CH4 with a horizontal resolution of 22 km and a precision of 1%. Gridded CO soundings are retrieved with 10% accuracy in three vertical layers between 0 and 15 km. Three-dimensional maps to model global tropospheric chemistry.

The instrument is self-calibrating in orbit and performs a zero measurement every 120 seconds and a reference measurement every 660 seconds. The instrument operation is practically autonomous, requiring very little commanding to keep it within the mission profile at all times. 89)


Figure 105: View of the MOPITT instrument (image credit: COM DEV)

MOPITT operations: MOPITT has suffered two anomalies since launch. On May 7, 2001 one of the two Stirling cycle coolers, which are used to keep the detectors at about 80 K, failed. The cooler fault compromised half of the instrument. After the fault, only channels 5, 6, 7, and 8 are delivering useful data. On Aug. 4, 2001 chopper 3 failed. Fortunately, it stopped in the completely open state, which permits to continue to use the data by adjusting the data processing algorithm accordingly.

EOS (Earth Observing System)

EOS is the centerpiece of NASA's Earth Science Enterprise (ESE). It consists of a science component and a data system supporting a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. 90) 91) 92) 93)

Background: The EOS program is a NASA initiative of the US Global Change Research Program (USGCRP). Planning for EOS began in the early 1980s, and an AO (Announcement of Opportunity) for the selection of instruments and science teams was issued in 1988. Early in 1990 NASA announced the selection of 30 instruments to be developed for EOS. Major budget constraints imposed by the US Congress forced the EOS program into a restructuring process in the time frame of 1991-92. In addition a rescoping of the EOS program occurred in 1992 leading to just half of the 1990 budget allocation (the HIRIS sensor was eliminated). The instruments adopted as part of the restructured/rescoped EOS program were chosen to address the key scientific issues associated with global climate change. This action reduced the required instruments to 17 that needed to fly by the year 2002 (six were deferred and seven instruments were deselected from the original 30). Furthermore, a shift occurred in the conceptual design of the EOS satellite platforms from “large observatories” to intermediate and smaller spacecraft that may be launched by smaller and existing launch vehicles. The EOS program experienced a further rebaselining process in 1994, due to a budget reduction of about 9%. This resulted in the cancellation of the combined EOS Radar and Laser Altimeter Mission (but rephasing the latter as two separate missions), deferring the development of some sensors and spreading the launch of missions by increasing the basic re-flight periods of missions from 5 to 6 years, and flying some EOS instruments on missions of partner space agencies (NASDA, RKA, CNES, ESA) in a framework of international cooperation. The EOS program includes instruments provided by international partners (ASTER, MOPITT, HSB, OMI) as well as an instrument developed by a joint US/UK partnership (HIRDLS).

The overall goal of the EOS program is to determine the extent, causes, and regional consequences of global climate change. The following science and policy priorities are defined for EOS observations (established by the EOS investigators working group and in coordination with the national and international Earth science community):

• Water and Energy Cycles: Cloud formation, dissipation, and radiative properties which influence the response of the atmosphere to greenhouse forcing, large-scale hydrology, evaporation

• Oceans: Exchange of energy, water, and chemicals between the ocean and atmosphere, and between the upper layers of the ocean and the deep ocean (including sea ice and formation of bottom water)

• Chemistry of the Troposphere and Lower Stratosphere: Links to the hydrologic cycle and ecosystems, transformations of greenhouse gases in the atmosphere, and interactions including climate change

• Land-Surface Hydrology and Ecosystem Processes: Improved estimates of runoff over the land surface and into the oceans. Sources and sinks of greenhouse gases. Exchange of moisture and energy between the land surface and the atmosphere. Changes in land cover

• Glaciers and Polar Ice Sheets: Predictions of sea level and global water balance

• Chemistry of the Middle and Upper Stratosphere: Chemical reactions, solar-atmosphere relations, and sources and sinks of radiatively important gases

• Solid Earth: Volcanoes and their role in climate change.

The original EOS mission elements (AM S/C series, PM S/C series, Chemistry S/C series) was redefined again in 1999. The EOS program space segment elements are now: Landsat-7, QuikSCAT, Terra, ACRIMSat, Aqua, Aura and ICESat.


Terra (EOS/AM-1) S/C

Aqua (EOS/PM-1 S/C)

Downlink center frequency

8212.5 MHz

8160 MHz


14 W

27.2 W


26 MHz

15 MHz

Data modulation



Data format



I/Q power ratio (nominal)



Operational duty cycle



Antenna coverage from nadir



Antenna polarization



Data rate

13 Mbit/s

15 Mbit/s

Data protocol standard



Instrument data provided



Table 11: Specification of Direct Broadcast (DB) service of Terra and Aqua satellites

EOS policy includes providing Direct Broadcast (DB) service to the user community; this applies to real-time MODIS data from the Terra spacecraft, as well as to the entire real-time data stream of the Aqua satellite. These data may be received by anyone with the appropriate receiving station, without charge. The broadcast data are transmitted in X-band. A 3 m antenna dish (minimum) should be sufficient for X-band data reception.

1) Special issue on EOS/AM-1 Platform, Instruments and Scientific Data, IEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No 4, July 1998



4) “Terra: Flagship of the Earth Observing System,” Press Kit, Nov. 1999, URL:

5) “TRW Completing Testing of EOS AM-1 Solar Array, First GaAs/Ge Flexible Blanket Solar Array,” May 13, 1997, URL:

6) M. J. Herriage, R. M. Kurland, C. D. Faust, E. M. Gaddy, D. J. Keys, “ EOS AM-1 GaAs/Ge flexible blanket solar array verification testprogram results,” Proceedings of the IECEC-97 (Energy Conversion Engineering Conference-1997), Vol. 1, pp.556-562, Honolulu, HI, USA, Sept. 27 to Aug. 1, 1997

7) D. J. Keys, “Earth Observing System (EOS) Terra spacecraft 120 volt power subsystem,” Proceedings of the IECEC-2000, Vol. 1, pp. 197-206, Las Vegas, NV, USA, July 24-28, 2000

8) J P. Chamoun, C. Connor, M. P. Hughes, R. P. Kozon, E. Moyer, R. E. Quinn, “Terra Spacecraft Deep Space Calibration Maneuver design and Execution,” Proceedings of the 27th annual AAS Guidance and Control Conference, Breckenridge, CO, Feb. 4-8, 2004, Guidance and Control 2004, Volume 118, ed. by J. D. Chapel and R. D. Culp, pp. 573-591, AAS 04-075

9) D. J. Keys, “Earth Observing System (EOS) TERRA spacecraft 120 volt power subsystem,” 35th Intersociety Energy Conversion Engineering Conference and Exhibit (IECEC), Las Vegas, NV, July 24-28, 2000, AIAA Collection of Technical Papers, Vol. 1 (A00-37701 10-44)

10) C. Filici, M. Suarez, “SAC-C Positioning in the Earth Morning Constellation,” Third International Workshop on Satellite Constellations and Formation Flying, Pisa, Italy, Feb. 24-26, 2003, pp. 57-62

11) Esprit Smith, ”NASA Satellites Detect Signs of Volcanic Unrest Years Before Eruptions,” NASA/JPL News Release 2021-081, 13 April 2021, URL:

12) Társilo Girona, Vincent Realmuto & Paul Lundgren, ”Large-scale thermal unrest of volcanoes for years prior to eruption,” Nature Geoscience, Volume 14, pp: 238-241, Published: 11 March 2021,

13) ”Zambia’s Kafue Flats,” NASA Earth Observatory, Image of the Day for 8 April 2021, URL:

14) Fritz Kleinschroth, R. Scott Winton, Elisa Calamita, Fabian Niggemann, Martina Botter, Bernhard Wehrli & Jaboury Ghazoul, ”Living with floating vegetation invasions,” Ambio, Volume 50, pp. 125-137, Published: 28 July 2020,, URL:

15) R. Scott Winton, Fritz Kleinschroth, Elisa Calamita, Martina Botter, Cristian R. Teodoru, Imasiku Nyambe & Bernhard Wehrli, ”Potential of aquatic weeds to improve water quality in natural waterways of the Zambezi catchment,” Scientific Reports, Volume 10, Article number: 15467, Published: 22 September 2020,

16) ”Ten Years After the Tsunami,” NASA Earth Observatory, Image of the Day for 12 March 2021, URL:

17) ”Greening Landscape Changes Air Flow,” NASA Earth Observatory, Image of the Day for 10 March 2021, URL:

18) ”Abundant Rain Turns Namibia Green,” NASA Earth Observatory, Image of the Day for 16 February 2021, URL:

19) ”Falling for Fallstreaks,” NASA Earth Observatory, Image of the Day for 8 February 2021, URL:

20) ”Snowmelt Timing Near the Great Salt Lake,” NASA Earth Observatory, Image of the Day for 4 February 2021, URL:

21) ”Cloudy Ridges in Yunnan,” NASA Earth Observatory, Image of the Day for 27 January 2021, URL:

22) ”NASA Data Aid Food Security Assessments in Kenya,” NASA Earth Observatory, Image of the Day for 25 January 2021, URL:

23) ”Phytoplankton Factory in the Argentine Sea,” NASA Earth Observatory, Image of the Day for 8 January 2021, URL:

24) ”The Stability of von Kármán’s Vortices,” NASA Earth Observatory, Image of the Day for 5 January 2021, URL:

25) ”Aral Sea in Winter,” NASA Earth Observatory, Image of the Day for 3 January 2021, URL:

26) ”An Inland Delta Flooded,” NASA Earth Observatory, Image of the Day for 21 December 2020, URL:

27) ”Foggy Mountain Breakdown,” NASA Earth Observatory,” Image of the Day for 12 December 2020, URL:

28) ”Early Melting Along the Antarctic Peninsula,” NASA Earth Observatory, Image of the Day for 3 December 2020, URL:

29) ”Iceberg A-68A Nears South Georgia,” NASA Earth Observatory, Image of the Day for 16 November 2020, URL:

30) ”Hurricane Zeta Arrives on the Gulf Coast,” NASA Earth Observatory, Image of the Day for 29 October 2020, URL:

31) ”Snowy and Icy Peaks with Very Different Origins,” NASA Earth Observatory, Image of the Day for 25 October 2020, URL:

32) ”Mining for Iron at Mount Whaleback,” NASA Earth Observatory, Image of the Day for 17 October 2020, URL:

33) ”The Undulations of Wave Clouds,” NASA Earth Observatory, Image of the Day for 12 October 2020, URL:

34) ”Mud from the Andes Carried by the Amazon,” NASA Earth Observatory, Image of the Day for 2 October 2020, URL:

35) ”Persistent Phytoplankton,” NASA Earth Observatory, Image of the Day for 22 September 2020, URL:

36) ”Cycles of Wet and Dry in Etosha Pan,” NASA Earth Observatory, Image of the Day for 14 September 2020, URL:

37) ”A Wall of Smoke on the U.S. West Coast,” NASA Earth Observatory, 9 September 2020, URL:

38) ”A Dangerous Storm Nears the Gulf Coast,” NASA Earth Observatory, Image of the Day for 27 August 2020, URL:

39) ”Poyang Lake Extremes,” NASA Earth Observatory, Image of the Day for 17 July 2020, URL:

40) ”Canary Curls,” NASA Earth Observatory, 11 July 2020, URL:

41) ”Shifting Seasons on the Steppe,” NASA Earth Observatory, Image of the Day for 5 July 2020, URL:

42) ”Volcanic Emissions Can Change Clouds,” NASA Earth Observatory, Image of the Day for 23 June 2020, URL:

43) ”Norwegian Fjord Turns Turquoise,” NASA Earth Observatory, Image of the Day for 12 June 2020, URL:

44) ”Breakup Along the Mackenzie River,” NASA Earth Observatory, Image of the Day for 8 June 2020, URL:

45) ”Ice Arch Persists Despite Warm Arctic,” NASA Earth Observatory, Image of the Day for 3 June 2020, URL:

46) ”Deforestation in Argentina’s Gran Chaco,” NASA Earth Observatory, Image of the Day for 20 May 2020, URL:

47) ”Airborne Particle Levels Plummet in Northern India,” NASA Earth Observatory, Image of the Day for 21 April 2020, URL:

48) ”A-68A Holding it Together,” NASA Earth Observatory, 20 April 2020, URL:

49) ”Could Satellites Help Head Off a Locust Invasion?,” NASA Earth Observatory, Image of the Day for 30 March 2020, URL:

50) ”Snow-Parched Scandinavia,” NASA Earth Observatory, Image of the Day for 24 March 2020, URL:

51) ”Reflecting on a Tumultuous Amazon Fire Season,” NASA Earth Observatory, Image of the Day for4 March 2020, URL:

52) ”Sandwiched Wave Clouds,” NASA Earth Observatory, Image of the Day for 28 February 2020, URL:

53) ”Dust Blankets the Canary Islands,” NASA Earth Observatory, Image of the Day for 25 February 2020, URL:

54) ”Winter Flooding on the Mississippi,” NASA Earth Observatory, Image of the Day for 5 February 2020, URL:

The information compiled and edited in this article was provided by Herbert J. Kramer from his documentation of: ”Observation of the Earth and Its Environment: Survey of Missions and Sensors” (Springer Verlag) as well as many other sources after the publication of the 4th edition in 2002. - Comments and corrections to this article are always welcome for further updates (

55) Y. Yamaguchi, A. B. Kahle, H. Tsu, T. Kawakami, M. Pniel, “Overview of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER),” IEEE Transactions on Geoscience and Remote Sensing, Vol. 36,, pp. 1062-1071, 1998.


57) ASTER, EOS Reference Handbook, 1999, pp. 102-105

58) Y. Yamaguchi, H. Tsu, H. Fujisada, “Scientific basis of ASTER instrument design,” Proceedings of SPIE (The International Society for Optical Engineering), Vol. 1939, 1993, pp. 150-160

59) M. Abrams, S. Hook, “ASTER User Handbook,” Version 1

60) Y. Yamaguchi, H. Fujisada, A. B. Kahle, H. Tsu, M. Kato, H. Watanabe, I. Sato, M. Kudoh, “ASTER Instrument Performance, Operation Status, and Application to Earth Sciences,” Proceedings of IGARSS 2001, Vol. 3, pp.:1215 - 1216, Sydney, Australia, July 9-13, 2001

61) M. Kawada, H. Akao, M. Kobayashi, et al., “Performance evaluation of ASTER cryocooler in orbit,” Proceedings of SPIE, Vol. 4881, 9th International Symposium on Remote Sensing, Aghia Pelagia, Crete, Greece, Sept. 23-27, 2002


63) H. Fujisada, M. Ono, “Overview of ASTER design concept,” in. Future European and Japanese Remote Sensing Sensors and Programs,” SPIE Vol 1490, Bellingham, WA, April 1-2, 1991, pp. 244-254

64) NASA/LaRC CERES brochure, URL:

65) “CERES on Terra,” NASA, URL:

66) B. R. Barkstrom, B. A. Wielicki, “Bruce R. Barkstrom and Bruce A. Wielicki,” Proceedings of IGARSS 2000, Honolulu, Hawaii, USA, July 24-28, 2000


68) R. S. Wilson, R. B. Lee, et al., “On-orbit solar calibrations using the Aqua Clouds and Earth's Radiant Energy System (CERES) in-flight calibration system,” Proceedings of SPIE, Vol. 5151, 2003, pp. 288-299

69) D. J. Diner, J. C. Beckert, G. W. Bothwell, J. I. Rodriguez, (2002). “Performance of the MISR Instrument During Its First 20 Months in Earth Orbit.,” IEEE Transactions on. Geoscience and Remote Sensing. Vol. 40, No 7, July 2002, pp. 1449-1466

70) C. J. Bruegge, D. J. Diner, “Instrument verification tests on the Multi-angle Imaging SpectroRadiometer (MISR),”. In Earth Observing System II, Proceedings of SPIE, Vol. 3117, San Diego, CA, July. 1997

71) D. J. Diner, C.J. Bruegge, J. V., G. W. Bothwell, E. D. Danielson, V. G. Ford, L. E. Hovland, K. L. Jones, M. L. White, “A Multi-angle Imaging SpectroRadiometer for terrestrial remote sensing from the Earth Observing System,” International. Journal of Imaging Systems and Technology, Vol. 3, 1991, pp. 92-107


73) Rebecca Lindsey, David Herring, “MODIS brochure,” NASA/GSFC, URL:


75) C. Schueler, W. L. Barnes, “Next-Generation MODIS for Polar Operational Environmental Satellites,” Journal of Atmospheric and Oceanic Technology, Vol. 15, Issue 2, April 1998, pp.430-439, URL:

76) R. Wolfe, “MODIS Calibration, Geolocation and Production,” EOS Snow and Ice Workshop, November 15, 2004, URL:

77) Information provided by C. Schueler and J. Thunen of Hughes SBRC (now Raytheon SBRS)

78) X. Xiong, N. Che, B. Guenther, W. L. Barnes, V. V. Salomonson, “Five Years of Terra MODIS On-Orbit Spectral Characterization,” Proceedings of SPIE Conference Optics and Photonics 2005, San Diego, CA, USA, July 31-Aug. 4, 2005, Vol. 5882

79) W. Barnes, X. Xiong, T. Salerno, B. Breen, C. Salo, “Operational activities and on-orbit performance of Terra MODIS on-board calibrators,” Proceedings of SPIE Conference Optics and Photonics 2005, San Diego, CA, USA, July 31-Aug. 4, 2005, Vol. 5882



82) J. R. Drummond, “MOPITT: 12 Years of Planning and 2.5 Years of Operations,” Proceedings of IGARSS 2002, Toronto, Canada, June 24-28, 2002

83) R. Deschambault, J. Hackett, D. Henry, T. Girard, F. Nichitiu, J. Zou, R. Irvine, J. R. Drummond, “MOPITT Flight Operations,” Proceedings of IGARSS 2002, Toronto, Canada, June 24-28, 2002

84) L. Emmons, D. Edwards, J. Gille, J.-L. Attié, M. Deeter, J. Warner, D. Ziskin, J. Drummond, E. McKernan, L. Yurganov, L. Jounot, B. Tolton, “MOPITT Validation Summary,” July 2001

85) J. R. Drummond, P. L. Bailey, G. Brasseur, G. R. Davis, J. C. Gille, G. D. Peskett, H. K. Reichle, N. Roulet, G. S. Mand, J. C. McConnell, “Early Mission Planning for the MOPITT Instrument,” URL:

86) J. R. Drummond, G. S. Mand, “The Measurement of Pollution in the Troposphere (MOPITT) Instrument: Overall Performance and Calibration Requirements,” Journal of Atmospheric and Oceanic Technology, Vol. 13, 1996, pp. 314-320,

87) D. Caldwell, J. Hackett, A. S. Gibson, J. R. Drummond, F. Nichitiu, “The Design and Flight Performance of the MOPITT Instrument Mechanisms,” Proceedings of the 11th European Space Mechanisms and Tribology Symposium, ESMATS 2005, 21-23 September 2005, Lucerne, Switzerland. Edited by B. Warmbein. ESA SP-591, Noordwijk, Netherlands: ESA Publications Division, ISBN 92-9092-902-2, 2005, pp. 99 - 106, URL:


89) J. Zou, F. Nichitiu, J. R. Drummond, “The Calibration of the MOPITT instrument,” Proceedings of IGARSS 2002, Toronto, Canada, June 24-28, 2002

90) G. Asrar, R. Greenstone (editors), “MTPE/EOS Reference Handbook 1995,” NASA/GSFC

91) “Earth Observing System,” Reference Handbook 1990, and 1991, NASA/GSFC

92) “Optical Remote Sensing of the Atmosphere,” 1990 Technical Digest Series of the Optical Society of America, Volume 4, pp. 23-58

93) G. Asrar, D. J. Dokken, “EOS Reference Handbook,” March 1993, NASA

The information compiled and edited in this article was provided by Herbert J. Kramer from his documentation of: ”Observation of the Earth and Its Environment: Survey of Missions and Sensors” (Springer Verlag) as well as many other sources after the publication of the 4th edition in 2002. - Comments and corrections to this article are always welcome for further updates (

Spacecraft    Launch    Mission Status    Sensor Complement    EOS    References    Back to top