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Terra Mission (EOS/AM-1)

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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.

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)



Mission status:

• September 8, 2017: During the monsoon season, heavy rains regularly pummel South Asia. But the summer monsoon of 2017 was different. In August 2017, day-after-day of punishing rainfall caused catastrophic flooding in northern India, Nepal, and Bangladesh. 11)

- More than 40 million people in the three countries have been afflicted. Hundreds of villages have been submerged, and tens of thousands of homes have been destroyed. Millions of people are living in refugee camps, and vast tracts of farmland and grazing land has been inundated.

- One of the hardest hit areas is Bihar, a state in East India with a vast expanse of flat, fertile land. Flooding grew severe there after heavy rains on August 10, 2017. By September, nearly 17 million people in that state alone had been affected by floods, according to the United Nations Office for the Coordination of Humanitarian Affairs. Roughly 7,000 villages in Bihar have flooded and more than 700,000 people have been displaced.

- The images of Figures 5 and 6 show how Bihar's waterways changed through the monsoon.


Figure 5: MODIS on the Terra satellite acquired this image of the Ganges, Koshi, and several other rivers on September 6, 2017, when flood water covered large swaths of the landscape (image credit: NASA Earth Observatory, images by Jesse Allen, using data from LAADS (Level 1 and Atmospheres Active Distribution System), story by Adam Voiland)


Figure 6: This MODIS image on Terra shows the same area on May 24, 2017, before monsoon rains began (image credit: NASA Earth Observatory, images by Jesse Allen, using data from LANCE (Land Atmosphere Near real-time Capability for EOS), story by Adam Voiland)

• September 2, 2017: On August 31, 2017, MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite acquired a false-color image (top) of extensive flooding along the Texas coast and around the Houston metropolitan area in the aftermath of Hurricane Harvey. A second image shows the same area on August 20, four days before the storm made landfall. 12)

- Both images were made with a combination of visible and infrared light (MODIS bands 7-2-1) that highlights the presence of water on the ground. Water is generally dark blue or black in this type of image, but rivers also can appear light blue because they carry large amounts of suspended sediment. Turn on the image-comparison tool to spot areas that have been inundated by rainwater and coastal surges.

- On August 31, MODIS also captured natural-color images of the area. Note the tan and brown rivers and bays full of flood water from Harvey. Scientists and civil authorities have some concerns about urban and industrial pollutants being mixed into the floodwater runoff. Along the coast, muddy, sediment-laden waters from inland pour into the Gulf of Mexico, which also was churned up by the relentless storm.

- According to the National Weather Service, 51.88 inches (131.8 cm) of rain were recorded at Cedar Bayou, Texas—the highest rainfall total for any storm in recorded U.S. history. Meteorologists at The Washington Post noted that that is as much rain as usually falls in Houston in an entire year and in Los Angeles in four years. By most accounts, Harvey produced more cumulative rainfall than any storm in the U.S. meteorological record — as much as 24 trillion gallons of water (unofficial estimates).

- In addition to providing satellite imagery and data of the storm, NASA has started flying its UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) aboard a Gulfstream III aircraft to collect high-resolution radar observations over rivers, flood plains, and critical infrastructure. That data can be compared and combined with SAR data from satellites such as the Sentinel- 1A and 1B missions of ESA.


Figure 7: False-color image of MODIS, acquired on Aug. 31, 2017, showing extensive flooding along the Texas coast and around the Houston metropolitan area in the aftermath of Hurricane Harvey (image credit: NASA Earth Observatory, images by Jesse Allen, using data from LANCE (Land Atmosphere Near real-time Capability for EOS), Story by Mike Carlowicz)


Figure 8: Detail image of the Houston region (image credit: NASA Earth Observatory, images by Jesse Allen, using data from LANCE (Land Atmosphere Near real-time Capability for EOS), Story by Mike Carlowicz)

• September 1, 2017: What remains of the large inland lake is a fraction of what it was in the 1950s and 60s. In those years, the government of the former Soviet Union diverted so much water from the Amu Darya and Syr Darya—the regions's two major rivers—to irrigate farmland, that it pushed the hydrologic system beyond the point of sustainability. During subsequent decades, the fourth largest lake in the world shrank to roughly a tenth of its former size and divided into several smaller bodies of water. 13)

- The image of Figure 9, captured by MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite, shows the Aral Sea in Central Asia on August 22, 2017. While the lake is much smaller in August 2017 than it was in the 1960s, some growth in the eastern lobe of the South Aral represents an improvement over August 2014, when that lobe was completely dry.

- Instead of pooling in one large basin, water flowing down the two rivers now ends up in either the North Aral Sea (fed by the Syr Darya) or the South Aral Sea (fed by Amu Darya). The Kok-Aral dike and dam, finished in 2005, separates the two water bodies and prevents flow out of the North Aral into the lower-elevation South Aral. The dam has actually led fisheries in the North Aral Sea to rebound, even as it has limited flow into the South basin.

- Managers use a sluice gate to let some water flow from the North Aral into the South Aral. During wet and snowy years, these releases are common; in dry years, they are rare. In 2017, heavy outflow from the North Aral in the winter, spring, and summer caused the eastern lobe of the South Aral to partially refill, explained Philip Micklin, a geographer emeritus from Western Michigan University.

- Large releases from the Toktogul Dam, a reservoir on a tributary of the Syr Darya, increased the flow of the Syr in the winter. In the spring, unusually warm temperatures melted enough snow pack and glacial ice in the Tien Shan to keep the river high. To a lesser degree, flow from the Amu Darya may have contributed to the partial replenishment of the eastern lobe in 2017 as well.

- The images of Figures 10 and 11 show the pathway water follows as it flows down the Syr Darya, into the North Aral Sea, and eventually the South Aral Sea. OLI (Operational Land Imager) on Landsat-8 collected the images on August 5, 2017. At the time, the sluice gates at the dam appeared to be open, and water was flowing past the Tsche-Bas Gulf and into the South Aral.

- "However, this year's events do not signal a restoration of the eastern lobe as a permanent feature," said Micklin. "Since the early 2000s, the eastern lobe revitalizes during heavy flow years and then dries completely, or nearly completely in low flow years. I see this process continuing for the foreseeable future."


Figure 9: MODIS image of the Aral Sea in Russia, acquired on August 22, 2017 (image credit: NASA Earth Observatory image by Jesse Allen, using Terra MODIS data from the LANCE (Land Atmosphere Near real-time Capability for EOS), Story by Adam Voiland)


Figure 10: This detail image the the Aral Sea was acquired on Aug. 5, 2017, with OLI on Landsat-8 (image credit: NASA Earth Observatory image by Jesse Allen,using Landsat-8 data from the USGS, Story by Adam Voiland)


Figure 11: A further detail image of the North Aral Sea was acquired on Aug. 5, 2017 with OLI on Landsat-8. At the time, the sluice gates at the Kok-Aral Dam appeared to be open, and water was flowing past the Tsche-Bas Gulf and into the South Aral Sea ( (image credit: NASA Earth Observatory image by Jesse Allen,using Landsat-8 data from the USGS, Story by Adam Voiland)

• August 27,2017: Goldstrike mine in northeastern Nevada is one of the largest gold mines in the world. In 2016, the mine produced 1.1 million ounces of gold (corresponding to 34,100 kg). Only two other operations—the Grasberg mine in Indonesia and the Muruntau mine in Uzbekistan—produced more. 14)

- On September 25, 2016, ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) on NASA's Terra satellite captured this false-color image of the mine (Figure 12). Vegetation appears red. Water is dark blue. Bare rock appears in shades of brown and gray. The most noticeable feature is the Betze-Post open-pit mine, which is managed by Barrick Gold Corporation and has a depth of more than 500 meters. Smaller open-pit mines operated by other companies are also visible northwest and southeast of the Betze-Post pit.

- Trucks transport ore from the bottom of the pit to nearby processing facilities, where gold is concentrated and extracted. On average, there is roughly 0.1 ounce of gold per ton of ore. Processing typically involves crushing ore into powder, exposing it to high temperatures and pressures, and leaching material out of liquid slurries. Leftover slurry is stored in tailing ponds, where solids settle out. In addition to its large open-pit mine, Goldstrike has two underground mines that also produce ore.

- One of the key issues facing mines is water management. Open-pit mining requires pumping groundwater out of adjacent aquifers in order to prevent the pit from flooding. At Goldstrike, operators pump several thousand gallons of groundwater per minute to keep the water table below the level of the pit. Some of this water is used to process ore, but some of it gets used in other ways or pumped backed into the ground. For instance, the water used to irrigate the circular fields southwest of the Betze-Post pit comes from groundwater pumping related to the mining.

- While the company that operates Goldstrike mine maintains a network of monitoring wells and stream gages to track how mine activities are affecting the aquifer, it also has used InSAR (Interferometric Synthetic Aperture Radar) data from satellites as part of its monitoring efforts. Since each monitoring well can cost between $300,000 to $500,000, and InSAR offers a big-picture view of the aquifer, a satellite perspective can offer an effective way of monitoring subsidence, uplift, and other changes in the Earth's crust associated with groundwater pumping, the company noted. InSAR observations show subsidence in areas near the mines and uplift in areas southwest of the mines.


Figure 12: ASTER image of the Goldstrike mine in northeastern Nevada, acquired on September 25, 2016 (NASA Earth Observatory, image by Jesse Allen, using data from NASA/GSFC/METI/ERSDAC/JAROS, and U.S./Japan ASTER Science Team, story by Adam Voiland)

• August 19, 2017: NASA's Terra satellite was built to observe Earth, and for more than 17 years its imagers have looked downward for 24 hours a day, collecting images needed to study the planet's surface, oceans, and atmosphere. However, the satellite recently trained its eyes on a different celestial body. 15)

- On August 5, 2017, Terra made a partial somersault, rotating its field of view away from Earth to briefly look at the Moon and deep space. This "lunar maneuver" was choreographed to allow the mission team to recalibrate Terra's imagers—MODIS (Moderate Resolution Imaging Spectroradiometer), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), and MISR (Multi-angle Imaging SpectroRadiometer). The Terra operations team last made such a maneuver in 2003.

- The orbital gymnastics are necessary for radiometric calibration; that is, making sure MODIS, MISR, and ASTER are properly recording the amount of light emitted and reflected by surfaces on Earth. In the harsh environment of space, satellite instruments are bombarded by high-energy particles, cosmic rays, and strong ultraviolet light, and this inevitably leads to degradation in the sensors over time. If changes in sensitivity are not properly accounted for, the images would start to make it appear as if Earth were growing darker or lighter—which would throw off scientific efforts to characterize air pollution, cloud cover, and other elements of the environment.

- The lunar surface provides a good eye test for the imagers. "The Moon is like a standard candle or lamp: the amount of energy from it is well known," said Kurt Thome, project scientist for Terra. "If you look at it periodically, it allows you to see if your instruments are changing over time."

- Since the Moon's surface brightness has been stable over the 17-year life of the mission—and, in fact, for thousands of years—the images of the lunar surface can be used as a standard for calibration. Terra can also observe the Moon without any atmospheric effects (such as turbulence, scattering, and absorption), which can add significant uncertainty in measured values.

- The image of Figure 13 was acquired by ASTER, while MODIS acquired the a further image. MODIS has actually been looking at the Moon monthly for nearly its entire mission, but MISR and ASTER do not have this capability or proper angles for such a view. "MODIS can peek out of the corner and get a view of the Moon," Thome said. "For MODIS, it has been a great way to understand the instrument over its lifetime and notice any changes."


Figure 13: ASTER image of the moon acquired on August 6, 2017 (image credit: NASA, images by Michael Abrams, Abbey Nastan, and Jesse Allen)


Figure 14: MISR images of the moon acquired on August 6, 2017 (image credit: NASA, images by Michael Abrams, Abbey Nastan, and Jesse Allen; Story by Tassia Owen, Abbey Nastan, and Michael Carlowicz)

- The nine images of Figure 14 come from MISR's nine imagers. The MISR operations team uses several methods to calibrate the data regularly, all of which involve imaging something with a known (or independently measured) brightness and correcting the images to match that brightness. Every month, MISR views two panels of a special material called Spectralon, which reflects sunlight in a very particular way. ASTER, meanwhile, views a set of lamps that light up its reflective bands. Periodically, this calibration is checked by a team on the ground that measures the brightness of a flat, uniformly colored surface on Earth (such as a dry desert lakebed) while MISR and ASTER fly overhead. The lunar maneuver offers a third opportunity to check the brightness calibration of MISR.

- When viewing Earth, MISR's cameras are fixed at nine different angles, with one (called An) pointed straight down, four pointed forwards (Af, Bf, Cf, and Df) and four angled backwards (Aa, Ba, Ca, and Da). The A, B, C, and D cameras have different focal lengths, with the most oblique (D) cameras having the longest focal lengths in order to preserve spatial resolution on the ground. During the lunar maneuver, however, the spacecraft rotated so that each camera saw the almost-full Moon straight on. This means that the different focal lengths produce images with different resolutions (D cameras produce the sharpest). These grayscale images were made with raw data from the red spectral band of each camera.

- After 17 years of collecting valuable data and dwindling fuel supplies, Terra is nearing the end of the mission, but not before it double-checks its data one last time. The lunar calibration is important not only for the accuracy of Terra's instruments, but also providing data that are used to calibrate other satellites (including weather).

• On July 6, 2017, MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite captured this image of sunglint on the waters around Crete and the Aegean Islands (Figure 15). 16)

- The phenomenon of sunglint is a matter of optics. Areas where the sea surface is smoother reflect more sunlight directly back to the satellite's imager. In contrast, areas of rougher water appear darker because light is scattered in many more directions.

- Dry, cool winds from the north, called the Etesian winds, are common over the Aegean Sea during summer. On the windward side of the islands, those winds pile up the water and disturb the surface. But as those air masses run into the islands and their rocky peaks, a "wind shadow" with much calmer winds (and seas) form on the leeward side of islands (in this case, the south sides). Darker areas amid the bright streaks could be the result of wind or water turbulence, or perhaps breaks in the wind-blocking land topography.


Figure 15: Sunglint image of the Aegean islands, acquired with MODIS on July 6, 2017 (image credit: NASA Earth Observatory, image by Jeff Schmaltz, caption by Kathryn Hansen)

• July 5, 2017: Icy lakes and rivers make a significant footprint on the Arctic landscape. Though widely dispersed, lakes cover as much as 40 to 50 percent of the land in many parts of the Arctic, and seasonal lake and river ice covers roughly 2 percent of all of Earth's land surfaces. Since lakes and rivers have the highest evaporation rate of any surface in high latitudes, understanding and monitoring seasonal ice cover is critical to accurately forecasting the weather and understanding regional climate processes. 17)

- Lake and river ice also affects the people who live in the Arctic. Seasonal ice roads serve as a key transportation route for many communities. Ice jams can produce sudden and dangerous hazards to hydroelectric power facilities, infrastructure, and human settlements. Changing ice conditions make shipping and boating a challenge. And ice is involved in a range of hydrological processes that can affect the quality of drinking water.

- Nonetheless, lake and river ice generally gets the least attention from ice scientists. According to one analysis, scientists publish roughly 50 scientific articles related to lake or river ice each year. In comparison, well over 600 articles get written about glaciers, 500 about snow, 350 about sea ice, and 250 about permafrost.

- Satellites could help fill this gap. In fact, since the number of ground-based ice monitoring stations has declined since the 1980s, satellites offer one of the most promising means of monitoring lake and river ice over large areas, noted the authors of a book chapter about the state of lake and river ice research.

- On May 29, 2017, MODIS on NASA's Terra satellite captured this image of ice covering the Amundsen Gulf, Great Bear Lake, and numerous small lakes in the northern reaches of Canada's Northwest Territories and Nunavut. Sea ice generally forms in the Gulf of Amundsen in December or January and breaks up in June or July. Lake and river ice in this area follow roughly the same pattern, though shallow lakes freeze up earlier in the fall and melt earlier in the spring than larger, deeper lakes.


Figure 16: On May 29, 2017, MODIS on NASA's Terra satellite captured this image of ice covering the Amundsen Gulf, Great Bear Lake, and numerous small lakes in the northern reaches of Canada's Northwest Territories and Nunavut (image credit: NASA Earth Observatory, image by Joshua Stevens, using MODIS data, story by Adam Voiland)

• May 14, 2017: Strong desert winds in mid-May 2017 lofted a huge dust plume from western Africa and carried it over the Atlantic Ocean. At 12:10 UTC on May 9, 2017, the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument on NASA's Terra satellite acquired this natural-color image of airborne sand and other aerosols. The plume stretched southwest to the Cabo Verde (Cape Verde) islands and beyond (Figure 17). 18)

- Africa is the world's largest source of dust to the atmosphere, contributing about 70 percent of the global total. Airborne mineral dust from the world's deserts delivers nutrients to the land and ocean, and affects the atmosphere and climate.


Figure 17: A dust storm over western Africa acquired by MODIS on May 9, 2017 (image credit: NASA Earth Observatory, image by Jeff Schmaltz)

• April 30, 2017: It might look like something mysterious is happening in the waters off of Oman, but this dark, sinuous shape has a completely natural explanation. On April 11, 2017, the MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite captured this natural-color image of the Arabian Sea (Figure 18). 19)

- Smooth water reflects sunlight like a mirror, particularly when viewed from above. Areas where that light is reflected by the water at the same angle that a satellite views it—when the Sun, the satellite, and the sea are lined up—appear brighter than surrounding areas. Viewed globally, sunglint shows up as long, linear streaks down the center of a swath of satellite data.

- This image shows a detailed view of sunglint in the Middle East. What's interesting is that the sunglint (bright area) is interrupted. Dark areas indicate surface waters that have been roughened by wind, causing sunlight to reflect in many directions. That means less light is reflected directly back toward the satellite. In this way, sunglint can be used to discern phenomena like wind patterns that are not directly visible in natural-color imagery.


Figure 18: A large Sunglint region in the Arabian Sea interrupted by dark ares of wind-roughened surface waters. This image was acquired on April 11, 2017 with the MODIS instrument (image credit: NASA Earth Observatory, image by Jeff Schmaltz, text by Kathryn Hansen)

• March 28, 2017: A long-dormant volcano on Russia's Kamchatka Peninsula erupted in March 2017. Several satellites caught images of a thick, ash-laden plume trailing from Kambalny. MODIS on NASA's Terra satellite captured a natural-color image of the Kambalny Volcano and its plume on March 25, 2017, the day after it began to erupt. By 1:34 p.m. local time (01:34 Universal Time) that day, the plume stretched about 100 km to the southwest (Figure 19). A dark stain is visible to the west of the plume, where ash has covered the snow. By March 26, ash falls would cover the ground on both sides of the volcano. 20)

- OMI ( Ozone Monitoring Instrument) on on NASA's Aura satellite observed an airborne plume of sulfur dioxide (SO2) trailing south of Kamchatka on March 26 (Figure 20). "The higher SO2 amounts downwind could be due to multiple factors," said Simon Carn, an atmospheric scientist at Michigan Technological University, "including variable emissions at the volcano (such as an initial burst), increasing altitude of the plume downwind, or decreasing ash content downwind."

- Invisible to the human eye, SO2 can harm people as well as the environment. According to a recent study, volcanoes collectively emit 20 to 25 million tons of SO2 into the atmosphere per year.

- An alert from the Kamchatka Volcanic Eruption Response Team warned of sporadic ash plumes rising up to 8 km above sea level. The activity could affect international and low-flying aircraft in the region, the group said.


Figure 19: MODIS image of the Kambalny ash plume, captured on March 26, 2017 (01:34 UTC), image credit: NASA Earth Observatory, image by Jeff Schmaltz and Joshua Stevens)


Figure 20: OMI image of the Kambalny ash plume, acquired on March 26, 2017 (image credit: NASA Earth Observatory, image by Joshua Stevens)

• March 26, 2017: New Zealand's Tasman Glacier is a massive block of ice, but it is no bulwark. The longest glacier in the country is neither immovable nor permanent. Instead, it continues to shrink by the day. 21)

- In Figure 21, captured on December 30, 1990, by the TM (Thematic Mapper) on the Landsat-4 satellite, the Tasman Glacier stretched like a serpentine tongue. The image of Figure 22 was acquired on January 29, 2017, by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. Both false-color images use white to show frozen snow or ice, and blue for water. Brown represents bare ground, while red areas are covered in vegetation.

- In the 26 years between images, the ice has retreated an average of 180 meters per year, according to New Zealand's National Institute of Water and Atmospheric Research. Before 1973, Tasman Lake did not exist. In the past decade, it has swollen to a length of 7 km. The lake growth is a direct result of the glacier's decline. The Tasman Glacier retreated 4.5 km from 1990 to 2015 mostly through calving, according to Mauri Pelto, a glaciologist at Nichols College. Researchers have predicted the lake will "increase dramatically in the near future" as the glacier produces more meltwater. The footprint of nearby Murchison Lake (below Murchison Glacier) has also grown.

- New Zealand is home to more than 3,000 glaciers, many of which are in decline. The Tasman Glacier is one of several that drains into Lake Pukaki, which is used to generate hydroelectric power. Further downstream, the same water feeds the Waitaki River, a habitat to trout and salmon.


Figure 21: Tasman Glacier false-color image of the Thematic Mapper instrument on Landsat-4, acquired on Dec. 30, 1990 (image credit: NASA Earth Observatory, image by Jesse Allen and Joshua Stevens)


Figure 22: Tasman Glacier false-color image of JAXA's ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) on NASA's Terra satellite, acquired on Jan. 29, 2017 (image credit: NASA Earth Observatory, image by Jesse Allen and Joshua Stevens)

• February 21, 2017: Heat waves are not unusual in Australia. A subtropical belt of high pressure that flows over the continent regularly delivers pulses of hot, dry air to the surface in the summer. Yet even by Australian standards, the intense heat wave of February 2017 has been remarkable. 22)

- When a high-pressure system stalled over central Australia, extreme temperatures emerged first in South Australia and Victoria and then spread to New South Wales, Queensland, and Northern Territory. With overheated bats dropping from trees and bushfires burning out of control, temperatures smashed records in many areas.

- Figure 23 shows peak land surface temperatures between February 7 and 14, 2017, a period when some of the most extreme heating occurred. The map is based on data collected by MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite. Note that it depicts land surface temperatures, not air temperatures. Land surface temperatures reflect how hot the surface of the Earth would feel to the touch in a particular location. They can sometimes be significantly hotter or cooler than air temperatures.

- On February 12, 2017, air temperatures rose to 46.6°C in the coastal city of Port Macquarie, New South Wales, breaking the city's all-time record by 3.3º C. Two days earlier, the average maximum temperature across all of New South Wales hit a record-setting 42.4°C — a record that was broken the next day when it rose to 44.0°C. In some places, the duration of the heatwave has been noteworthy. Mungindi, a town on the border of Queensland and New South Wales, endured 52 days in a row when maximum temperatures exceeded 35°C — a record for New South Wales.

- Many scientists see exceptional heat waves like this as part of a broader trend. For instance, one study published by the Climate Council of Australia concluded that heatwaves — defined as at least three days of unusually high temperatures — grew significantly longer, more intense, and frequent between 1971 and 2008.


Figure 23: MODIS on Terra acquired this image map of Australian land surface temperatures in the period Feb. 7-14, 2017 (image credit: NASA Earth Observatory, image by Jesse Allen, caption by Adam Voiland)

• February 12, 2017: Covering about 400,000 hectares (4000 km2) in Iran's Khuzestan province, the Shadegan wetlands are the largest in Iran (Figure 24). At their center is Shadegan Pond, a large but shallow body of water surrounded by a varied landscape of sugar plantations, date palm orchards, small towns, and military fortifications. The Karun River winds along its western edge. Fields of sugar cane stand northwest of it. The town of Shadegan—which is flanked by long, narrow orchards — lies to its east. 23)

- Environmental conditions at the wetlands vary throughout the year. In the fall and winter, rains in the Zagros Mountains send water flooding through an intricate series of shallow lagoons and marshes. Many of these areas dry out during the summer months. This image was acquired in the fall, when the area was relatively dry.

- The Shadegan wetlands support an array of living things. Sheep, cattle, and water buffalo roam the area, while Mesopotamian himri, carp, and catfish are commonly caught in the pond's waters. Dozens of bird species—including several types of ducks, terns, gulls, and egrets—can be found in Shadegan Wildlife Refuge.

- The refuge is one of the most important sites in the world for the marbled teal, a diving duck. Shadegan supports about 10,000 to 20,000 of these birds in the winter, about half of the world's population.


Figure 24: Image of the Shadegan Pond in Iran, acquired on September 3, 2012 with the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) of JAXA on the NASA's Terra satellite (image credit: NASA Earth Observatory image by Jesse Allen, caption by Adam Voiland)

• January 11, 2017: In January 2007, satellites captured an extraordinary example of hole-punch clouds visible over the southern United States. But occurrences of the cloud type, albeit usually less pronounced, show up every year over Earth's mid- and high-latitudes. A more recent display developed over eastern China, visible in the image of Figure 25, acquired on December 28, 2016, with MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite. 24)

- This strange phenomenon results from a combination of cold temperatures, air traffic, and atmospheric instability. If you were to look from below, it would appear as if part of the cloud was falling out of the sky. As it turns out, that's actually what's happening.

- The mid-level clouds are initially composed of liquid drops at a super-cooled temperature below 0° Celsius. As an airplane passes through the cloud, it creates a disturbance that triggers freezing. Ice particles then quickly grow in the place of the water droplets. Eventually the ice crystals in these patches of clouds grow large enough that they literally fall out of the sky—earning hole-punch clouds their alternate name: "fallstreak holes." Falling crystals are often visible in the center of the voids.

- The formations in this image are less like holes and more linear, like long canals. The same basic processes are responsible for producing both configurations. Whether the void takes on a circular or linear shape depends on differences such as cloud thickness, wind shear, and air temperature. Hole-punch and canal clouds can appear together, as they did in this image from December 2015. They often occur in the vicinity of an airports.


Figure 25: The MODIS instrument on Terra acquired this image on Dec. 28, 2016 over eastern China showing the display of canal clouds (image credit: NASA Earth Observatory, image by Joshua Stevens,caption by Kathryn Hansen)

• On November 24, 2016, Tokyo received its first November snowfall in more than half a century. The MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite captured this natural-color image the same day. The snow fell in and around the Japanese capital, coating the metropolitan area and accumulating along some sidewalks (Figure 26). 25)

- Figure 27, a false-color image from MODIS on Terra, shows a stark contrast between snow (blue) and clouds (white). The snow traces the contours of surrounding mountains and is distinguishable from clouds offshore. Central Tokyo is gray-brown in color, suggesting less accumulation or faster melting. Urban centers tend to shed snow faster than surrounding countryside because they are often hotter, a result of the urban heat island effect.

- The November dusting was caused by a cold air mass moving down from the Arctic, according to the Japan Meteorological Agency. Meteorologists connected the storm to the Arctic oscillation, a climate pattern that affects the northern hemisphere. Usually, high air pressure in the mid-latitudes prevents colder, low-pressure air seeping down from the Arctic. However, weaker pressure systems occasionally disrupt this barrier, and colder air can penetrate further south, as in this case.


Figure 26: Snow-covered Tokyo region as acquired by the MODIS instrument on November 25, 2016 (image credit: NASA Earth Observatory, image by Joshua Stevens)


Figure 27: False-color image of Tokyo, acquired on Nov. 25, 2016, showing the stark contrast between snow (blue) and clouds (white), image credit: NASA Earth Observatory, image by Joshua Stevens

• Sept. 8, 2016: In August 2016, the return of sunlight on the Antarctic Peninsula meant that the landscape became visible again in natural-color satellite imagery. That's when scientists saw something interesting: a rift along Larsen C—the continent's fourth-largest ice shelf—has grown considerably longer. 26)

- The scenario is similar to what occurred before a calving event and partial collapse of Larsen B in 2002. But exactly what's in store for Larsen C remains to be seen. "We don't know yet what will happen here," said Ala Khazendar of NASA's Jet Propulsion Laboratory.

- Figure 28 was acquired with MISR's downward-looking (nadir) camera. This natural-color image has a red tint due to the steep lighting angle, as the Sun does not reach far above the horizon in August. The ice shelf comprises the left half of the image, and thinner sea ice appears on the right.

- Figure 29 shows the same area. By combining these different angles in one image, one can discern surface roughness. Rougher surfaces appear pink and smoother areas appear purple. The ice shelf is generally smoother than the sea ice, with the exception of the crack—an indication that it is actively growing, according to the MISR team. Project MIDAS, a group in the United Kingdom that has been tracking the rift, reported that the crack grew 22 km over the past six months. It now stretches 130 km.

- Both images show other fissures as well, all of which terminate at about the same distance south of the lengthening crack. "People have been intrigued by this," Khazendar said. "It's quite a remarkable feature, how they open and then seem to stop opening." There are a few hypotheses as to why that happens. The cracks might come to a stop when they reach a suture zone—an area where sectors of ice feeding the shelf are advancing at different speeds, creating shear where they flow together. Ice in this zone is already so fractured that it halts further propagation of the big, crosswise cracks.

- The cracks also could have reached an area where marine ice has formed on the bottom of the ice shelf. Marine ice is relatively warm and less stiff, so it can accommodate higher levels of strain without fracturing. The crack that's actively lengthening, however, has overcome those obstacles. "What's happening now is different," Khazendar said. "This crack goes farther and has started propagating northwards."

- Even before signs of the lengthening appeared at the surface, Khazendar and colleagues suspected something was going on. A study in 2011 that measured ice velocity showed a "line" across the shelf; everything between that line and front of ice shelf was flowing noticeably faster than everything upstream. They proposed that the line traced the location of a crevasse growing upward along the bottom of the ice sheet. Then in 2014, the MIDAS team first detected the rift growing at the surface.

- "What might be happening is that there is enhanced melting at bottom of ice shelf, resulting in the removal of the softer marine ice, allowing fractures to be filled with ocean water," Khazendar said. "When that happens, it could cause pre-existing bottom crevasses to propagate up through the ice shelf."

- Cracks and calving of ice from the front of an ice shelf is a normal process. Shelves are fed by ice coming from glaciers and ice streams from the interior of the continent. They advance into the ocean until a calving event takes place. The shelf front retreats and then advances again. The whole cycle can occur over the span of a few decades. "That's just part of life for an ice shelf," Khazendar said. "That's how they behave."

- In the case of Larsen B, the big calving events took place with a frequency that did not allow enough time for the shelf to re-advance. As a result, the front of the shelf kept retreating in a run up to the big disintegration event that occurred in just six weeks in 2002. "The growing crack on Larsen C could be the beginning of a process that will end up like Larsen B," Khazendar said. "If a big calving event takes place, we will be interested to see how the shelf itself reacts. But all the indications so far are that it is relatively stable, albeit with intimations of change."


Figure 28: The rift is visible in this image acquired on August 22, 2016, with the MISR (Multi-angle Imaging SpectroRadiometer) instrument on Terra (image credit: NASA Earth Observatory images by Jesse Allen and the MISR Team)


Figure 29: Composite image of the same area from MISR's backward-, vertical-, and forward-pointing cameras (image credit: NASA Earth Observatory images by Jesse Allen and the MISR Team)

• July 12, 2016: NASA's Terra satellite observed a large dust storm off the coast of Chile. It is unusual to see such large dust events emerge from the west coast of South America, according to atmospheric scientists. Winds there "are not conducive to developing major dust storms like those that we see in North Africa or in Asia," said Joseph Prospero, an atmospheric scientist at the University of Miami. 27)

- The local topography hinders the formation of dust storms, as the Andes Mountains run along South America's western flank and block winds arising in the east. The mountain range stretches more than 7,000 km from north to south, and stands more than 500 km wide in some areas. Usually, dust storms during this time of year (southern, or austral, winter) will blow eastward toward the Atlantic Ocean, said Santiago Gasso, an aerosol scientist at NASA's Goddard Space Flight Center.

- Globally, natural sources account for roughly 75 percent of dust emissions, while anthropogenic (manmade) sources account for roughly 25 percent, according to research published in Reviews of Geophysics. On July 8, the source was natural. The image of Figure 30 suggests that the dust source is located between the Andes and the Pacific coast. The slice of land there is narrow, with steeply rising walls. The dust source could be on an elevated slope, making it easier for dust to lift and travel far. It also could be driven by low-level winds—possibly katabatic winds, which blow downslope off the continent. The term katabatic comes from the Greek "katabaino," meaning "to descend." Such winds develop as air that comes in contact with cold, high-altitude ground cools by radiation. The air increases in density, and flows downhill. It can pick up speed, causing gale-force winds.

- The stormy conditions that lofted the dust on July 8 also brought wind, rain, and snow leading to the closure of at least two airports, Chile's Teletrece news site reported.


Figure 30: On July 8, 2016, the MODIS instrument on Terra acquired this natural-color image of an airborne dust cloud off the coast of Chile (image credit: NASA Earth Observatory, Jeff Schmalz)

• May 18, 2016: April in Greenland is typically very cold, though some years buck the trend. In 2012, for example, the surface of the ice sheet started melting early and then experienced the most extensive melting since the start of the satellite record in 1978. Weather events and temperature anomalies this April suggest that 2016 may be off to a similar start.

- The temperature anomaly map of Figure 31 is based on data from MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite. Observed by satellites uniformly around the world, LSTs (Land Surface Temperatures) are not the same as air temperatures. Instead, they reflect the heating of the surface by sunlight, and they can sometimes be significantly hotter or cooler than air temperatures.

- "The most remarkable aspect here is the incredible departure from 2001-2010 average, especially deep in the ice sheet interior," said Santiago de la Peña, a research scientist at Ohio State University. "This is accentuated by the fact that the northern regions of the United States and Canada actually experienced cooler than usual temperatures." According to de la Peña, a high-pressure weather system sat over the ice sheet through most of April. The system caused temperatures across Greenland to spike, reaching or matching record temperatures in many places. "There have been occasional warming events in the past during spring over Greenland," he noted, "but they affected only local areas and were not as intense."

- Still, warming events in Greenland are not entirely without precedent. Research by Dorothy Hall, an emeritus scientist at NASA's Goddard Space Flight Center, has shown that major melt events like those in 2012 and 2002 are not uncommon.

- De la Peña thinks such events will become more common in the future as atmospheric warming in the Arctic brings about longer melt seasons. For now, he notes that it is still early to predict how the melt season in 2016 will unfold. "High temperatures are still being recorded in May, suggesting we will have major melt events during the summer."


Figure 31: The MODIS map of Terra shows land surface temperatures for April 2016 compared to the 2001–2010 average for the same month. Red areas were hotter than the long-term average; some areas were as much as 20º Celsius warmer. Blue areas were below average, and white pixels had normal temperatures. Gray pixels were areas without enough data, most likely due to excessive cloud cover (image credit: NASA Earth Observatory, image by Jesse Allen)

• May 7, 2016: In early May 2016, a destructive wildfire burned through Canada's Fort McMurray in the Northern Alberta region. Windy, dry, and unseasonably hot conditions all set the stage for the fire. Winds gusted over 32 km/hour, fanning the flames in an area where rainfall totals have been well below normal in 2016. Ground-based measurements showed that the temperature soared to 32º Celsius on May 3 as the fire spread. 28)

- Observed by satellites uniformly around the world, LSTs (Land Surface Temperatures) are not the same as air temperatures. Instead, they reflect the heating of the land surface by sunlight, and they can sometimes be significantly hotter or cooler than air temperatures (Figure 32). The intense heat coincided with a weather pattern called an omega block. A large area of high pressure stalled the usual progression of storms from west to east. In Alberta, that left sinking, hot air parked over the region while the block was in place. But even before the omega block emerged, seasonal data show that winter in Alberta was warmer than usual.

- According to Robert Field, a Columbia University scientist based at NASA's Goddard Institute for Space Studies, El Niño likely played a role in the warmth. The Virginia Hills fire in central Alberta (May 1998) burned under a similar El Niño phase. "That fire occurred under comparable fire danger conditions, part of which you can trace to El Niño," Field said.


Figure 32: The temperature anomaly map is based on data from the MODIS instrument on the Terra satellite. The map shows the LST (Land Surface Temperature) from April 26 to May 3, 2016, compared to the 2000–2010 average for the same one-week period. Red areas were hotter than the long-term average; blue areas were below average. White pixels had normal temperatures, and gray pixels did not have enough data, most likely due to cloud cover (image credit: NASA Earth Observatory, image by Jesse Allen)

- The image of Figure 33 shows Fort McMurray on May 4, 2016, acquired by the Enhanced Thematic Mapper Plus (ETM+) on the Landsat-7 satellite. This false-color image combines shortwave infrared, near infrared, and green light (bands 5-4-2). Near- and short-wave infrared help penetrate clouds and smoke to reveal the hot spots associated with active fires, which appear red. Smoke appears white and burned areas appear brown. On this day the fire spanned about 100 km2; by the morning of May 5, it spanned about 850 km2 (Ref. 28).


Figure 33: ETM+ image of Landsat-7 of the Fort McMurray fire, acquired on May 4, 2016. Also visible in the Landsat image is the fire's complex pattern, with many active fronts (image credit: NASA Earth Observatory, image by Jesse Allen)

• May 4, 2016: April in Southeast Asia is usually a hot month, following the cool, dry season and preceding the monsoon season. But April 2016 was not your typical April. Throughout the month, ground-based measurements of air temperatures soared above average; one location in Thailand even broke the national record. 29)

- Satellite observations show a similarly hot picture. The map of Figure 34 shows land surface temperatures from April 2016 compared to the 2000–2012 average for the same month. Red areas were hotter than the long-term average by as much as 12º Celsius in some places; blue areas were below average. White pixels had normal temperatures, and gray pixels did not have enough data, most likely due to excessive cloud cover.

- According to news reports, at least 50 towns and cities matched or broke their daily air temperature records. On April 28, the temperature in Mae Hong Son was the highest ever recorded in Thailand, reaching 44.6 º Celsius.

- Southeast Asia was not the only area that endured intense heat in April. In India, ground-based measurements recorded temperatures 4-5º Celsius above normal. At least 300 people are reported to have died from heat-related complications during the month. A year earlier, more than 2,500 people died during India's 2015 heat wave—one of the five deadliest on record.


Figure 34: This temperature anomaly map is based on data from the MODIS instrument on NASA's Terra satellite, acquired in April 2016 (image credit: NASA Earth Observatory, image by Jesse Allen)

Legend to Figure 34: Observed by satellites uniformly around the world, land surface temperatures (LSTs) are not the same as air temperatures. Instead, they reflect the heating of the land surface by sunlight, and they can sometimes be significantly hotter or cooler than air temperatures.

• April 18, 2016: Long-term cloud cover study of MODIS data on Terra and on Aqua reveals species habitat. Much of Earth's biodiversity is concentrated in areas where not enough is known about species habitats and their wider distributions, making management and conservation a challenge. To address the problem, scientists at the University at Buffalo and Yale University used NASA satellite data to study cloud cover, which they found can help identify the size and location of important animal and plant habitats. 30) 31)

- Clouds influence such environmental factors as rain, sunlight, surface temperature and leaf wetness-all of which dictate where plants and animals can survive. As part of their study, researchers examined 15 years of data from NASA's Earth-orbiting Terra and Aqua satellites and built a database containing two images per day of cloud cover for nearly every square kilometer of the planet from 2000 to 2014. The study found that variations in cloud cover sharply delineated the boundaries of ecological biomes relevant to many unique species. 32)

- Advanced spatial assessment and monitoring of biodiversity in today's rapidly changing world is vital for managing future biological resources and a key element of several 2020 targets of the Convention on Biological Diversity and the Intergovernmental Platform on Biodiversity and Ecosystem Services. Growing evidence highlights the importance of fine-grain (≤1 km) climatic and environmental variability in driving the spatial distribution and abundance of organisms and the need to correctly capture this variation globally. Ecological research at regional to global extents remains reliant on environmental information that lacks important detail and is often interpolated between ground stations over vast distances of highly variable terrain.

- Cloud cover influences processes ranging from reproductive success in reptiles to leaf wetness, CO2 uptake, and the geographic distribution of plants. Especially in the tropics, seasonal variability of cloud cover is typically more important than day length and solar angle in reducing available solar irradiance, with multi-fold ecological consequences. These effects are difficult to observe in other remotely sensed products including vegetation indices, which for many parts of the world do not show much change throughout the year.

- The new 1 km dataset confirms equatorial South America, the Congo River basin in Africa, and Southeast Asia as the cloudiest regions of the world, with annual cloud frequencies (proportion of days with a positive cloud flag) ≥80% (Figure 35A). But, in contrast to existing evidence (S1 Table), the new product captures the frequency of cloud cover at substantially increased spatial resolution. In many regions (often but not always mountainous), cloud cover varies starkly over very short distances (Figure 35C), revealing variability hidden in spatially aggregated cloud products currently used in ecosystem, biodiversity, and climate modeling that are >100–10,000 times coarser.

- Remotely sensed information has the potential to revolutionize our understanding of spatial ecoclimatological patterns and processes through direct capture of environmental variation at fine spatial grain and global extent. Here, we have shown how global cloud dynamics can be quantified in unprecedented spatial detail and that cloud-associated factors are significantly associated with the distribution of various aspects of biodiversity habitats over large spatial scales.


Figure 35: Global 1 km cloud metrics. A) Mean annual cloud frequency (%) over 2000–2014. B) Inter-annual variability in cloud frequency (mean of 12 monthly standard deviations). C) Spatial variability (standard deviation of mean annual cloud frequency within a one-degree, ~110 km, circular moving window). D) Intra-annual variability in cloud frequency (standard deviation of 12 monthly mean cloud frequencies). Grey indicates the (A) median global cloud frequency (51%) and (B,D) median inter-annual variability (11%), blues indicate areas with below-median values, and reds indicate areas with higher-than-median values. Data are available only for MODIS land tiles, resulting in missing data in black tiles over oceans (image credit: A. M. Wilson, W. Jetz)


Figure 36: Seasonal cloud concentration. A) Color key illustrating the distribution of global cloud seasonality and concentration. The hue indicates the month of peak cloudiness, while the saturation and value indicate the magnitude of the concentration ranging from 0 (black, all months are equally cloudy) to 100 (all clouds are observed in a single month). B) Global distribution of seasonal cloud concentration with two red boxes indicating the locations of panels C and D. Coastlines shown in white, areas with no data are dark grey. C) Regional plot of northern South America illustrating the transition from June–July–August to December–January–February cloudiness with little seasonality (dark colors) at high elevations. D) Regional plot of southern Africa illustrating the transition from the Mediterranean climate in the southwest to the summer rainfall region in the northeast. Note the incursions of summer clouds and associated rainfall (red colors) along the southern coast. In C) and D), red lines indicate ecoregion boundaries (image credit: A. M. Wilson, W. Jetz)

• April 13, 2016: Antarctica has shed two new, large icebergs into the Southern Ocean. The bergs are the result of a crack that had been spreading across the Nansen Ice Shelf. The progression of the crack was visible in a pair of satellite images acquired in December 2013 and 2015. Ryan Walker and Christine Dow, glaciologists at NASA/GSFC (Goddard Space Flight Center), flew along the crack in late 2015. It was clearly still attached. On April 6, 2016, with southern winter soon to set in, satellite imagery indicated that the cracking ice front was still holding on. 33)

- The Nansen Ice Shelf previously measured about 35 km across and 50 km long. For comparison, the Drygalski Ice Tongue just south of Nansen stretches 80 km into the sea. Of the two bergs shed from Nansen, only one is large enough to meet the size criteria for naming and tracking by the U.S. National Ice Center. This larger piece is named C33.

- But why did the crack finally give out? According to Walker, summer melting probably helped weaken and break up the shelf fragments and sea ice (the mélange) within the crack, which acted like glue to keep the bergs attached. Summer melt also could have helped the deeply fissured ice to break further, completing the crack across the shelf.

- Once broken off, the new icebergs would have been blown away from the shelf by the strong katabatic winds that blow out to sea. "Nansen usually has pretty strong katabatic winds," Walker said.

- Walker emphasized that this is routine iceberg calving—there are indications that similar events occurred there in the 1960s—and not a collapse of the ice shelf. Still, some scientists are concerned for a different reason; the icebergs are threatening scientific equipment in the area. Scientists at New Zealand's National Institute of Water and Atmospheric Research (NIWA) say the bergs are deep enough that they cold snag a mooring deployed in Terra Nova Bay. The mooring collects data on the effects of climate change on sea ice and ice shelves.

- "We won't know until we go back next summer whether it is still there. We could lose a whole year of data. If that happens it will leave a gap in our research and that's unfortunate," said oceanographer Mike Williams in a NIWA press release. "However, it is a risk we have to take. We could see the crack from satellite images but predicting when an ice shelf will calve is difficult. It could have happened any time in the next five years."


Figure 37: On April 7, 2016, in the last days before winter darkness, MODIS on Terra acquired this image as the bergs broke away. (image credit: NASA Earth Observatory,, image by Jesse Allen)

As of April 1, 2016, all Earth imagery from the Japanese ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) instrument aboard NASA's Terra spacecraft since late 1999, is now available to users everywhere at no cost. The public will have unlimited access to the complete 16-plus-year database for Japan's ASTER instrument of METI (Ministry of Economy, Trade and Industry), which images Earth to map and monitor the changing surface of our planet. ASTER's database currently consists of more than 2.95 million individual scenes. The content ranges from massive scars across the Oklahoma landscape from an EF-5 tornado and the devastating aftermath of flooding in Pakistan, to volcanic eruptions in Iceland and wildfires in California. 34)

- Previously, users could access ASTER's global digital topographic maps of Earth online at no cost, but paid METI a nominal fee to order other ASTER data products. In announcing the change in policy, METI and NASA cited ASTER's longevity and continued strong environmental monitoring capabilities. Launched in 1999, ASTER has far exceeded its five-year design life and will continue to operate for the foreseeable future as part of the suite of five Earth-observing instruments on Terra.

- The broad spectral coverage and high spectral resolution of ASTER provide scientists in numerous disciplines with critical information for surface mapping and monitoring of dynamic conditions and changes over time. Example applications include monitoring glacial advances and retreats, monitoring potentially active volcanoes, identifying crop stress, determining cloud morphology and physical properties, evaluating wetlands, monitoring thermal pollution, monitoring coral reef degradation, mapping surface temperatures of soils and geology, and measuring surface heat balance.


Figure 38: In Dec. 2015, one of Nicaragua's largest volcanoes, Momotombo, erupted for the first time since 1905. Continued activity at the end of February and into March 2016 produced large ash columns and pyroclastic (superheated ash-and-block) flows. On March 2, 2016, ASTER captured the volcano's eruptive activity during the day with its visible bands, and the previous night with its thermal infrared bands. The composite image shows a large blue-gray ash cloud covering the volcano's summit. The superimposed night data show the hot flows (in yellow) on the northeast flank, and the active summit crater in white. The data cover an area of 17 km x 18 km, located at 12.7º north, 86.6º west. 35)

Legend to Figure 38: With its 14 spectral bands from the visible to the thermal infrared wavelength region and its high spatial resolution of 15 to 90 m, ASTER images Earth to map and monitor the changing surface of our planet. ASTER is one of five Earth-observing instruments launched Dec. 18, 1999, on Terra. The instrument was built by Japan's Ministry of Economy, Trade and Industry. A joint U.S./Japan science team is responsible for validation and calibration of the instrument and data products.

• In March 2016, the Southern United States received a remarkable amount of precipitation. In the days after the slow-moving weather system cleared out, flood waters rose across several major river basins. 36)

- On March 14, 2016, the MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite captured an image of flooding in the vicinity of the Mississippi and White rivers. The image of Figure 39 is false color, composed from a combination of infrared and visible light (MODIS bands 7-2-1). Flood water appears dark blue; saturated soil is light blue; vegetation is bright green; and bare ground is brown. This band combination makes it easier to see flood water.

- The flooding was the result of an unusually strong low-pressure system that pulled in atmospheric moisture from both the Western Caribbean and the Eastern Pacific, according to meteorologists at Weather Underground. The system stalled over the southern states, and rainfall totals amounted to what would be expected to occur once every 200 years.

- The map of Figure 40 shows NASA's satellite-based estimates of rainfall over the Southern United States and the Gulf of Mexico from March 7–14. The brightest shades represent rainfall totals approaching 600 mm (24 inches) over the span of a week. The rainfall data represented in the map come from IMERG (Integrated Multi-Satellite Retrievals for GPM), a product of the GPM (Global Precipitation Measurement) mission. These regional, remotely sensed estimates may differ from the totals measured by ground-based weather stations.

- According to news reports, rain and flooding in the United States affected communities in Texas, Oklahoma, Arkansas, Louisiana, Mississippi, Tennessee, Alabama, and Kentucky. In Louisiana alone, the flooding was reported to have killed four people and damaged at least 5,000 homes.


Figure 39: Extend of flooding observed by the MODIS instrument on Terra [image credit: NASA Earth Observatory, using data from LANCE (Land Atmosphere Near real-time Capability for EOS), Jesse Allen]


Figure 40: IMERG data image of the GPM mission showing the total rainfall and the extend of the rainfall region in the US (image credit: NASA Earth Observatory, Joshua Stevens)

• Feb. 17, 2016: Two kinds of wave patterns are visible in the natural-color image of Figure 41, observed by MODIS on NASA's Terra satellite off the coast of Western Australia. Well offshore to the north and west, atmospheric waves are made visible by parallel bands of white clouds. Closer to the coast, the bright area of water is sunglint—the reflection of sunlight directly back toward the satellite imager. That sunglint makes it possible to see the faint ripples of internal waves; that is, large waves that propagate below the water surface, within the depths of the sea. 37)

- Waves form in the atmosphere for a variety of reasons. Sometimes the movement of an air mass over a bumpy feature—a mountain ridge, a volcano, or an island amidst a flat sea—will force air to rise or sink, creating ripples in the sky like those propagating across the surface of a pond. Other times, the collision of different air masses will cause a rippling effect.

- It is unclear what caused the atmospheric waves in the image of Figure41 . Off the west coast of Africa, we often see waves form when the dry air from the Sahara moves out over the much moister air over the tropical Atlantic Ocean. The dry air tends to push the moist air higher in the atmosphere, causing water vapor to form droplets and amass into clouds. The moist air rises, then gravity pulls it back down; the warm air rises again, then falls again. A series of cloud ripples mark the edges of the wave front as it propagates and dissipates.

- It is also possible—though perhaps less likely because of the distance—that the wave patterns in the image above have their origin inland. Western Australia is mostly desert and relatively flat, so it is possible that an atmospheric wave pattern formed when an air mass rode up over the Hamersley Range (just outside the scene) and out toward the sea.

- Internal waves are quirky phenomena that were scarcely known to science until the satellite era. They can be hundreds of meters tall and tens to hundreds of kilometers long. Enhanced by sunglint in the image above, these long wave forms moving across the sea surface are a visible manifestation of slow waves moving tens to hundreds of meters beneath the sea surface.

- Internal waves form because the ocean is layered. Deep water is cold, dense, and salty, while shallower water is relatively warmer, lighter, and fresher. The differences in density and salinity cause layers of the ocean to behave like different fluids. When tides, currents, and other large-scale effects of Earth's rotation and gravity drag water masses over some seafloor formations, it creates wave actions within the sea that are similar to those happening in the atmosphere.

- If you were on a boat, you would not necessarily see or feel internal waves because they are not expressed at the surface in different wave heights. Instead, they show up as smoother and rougher water surfaces that are visible from airplanes and satellites. As internal waves move through the deep ocean, the lighter water above flows up and down the crests and troughs. Surface water bunches up over the troughs and stretches over the crests, creating alternating lines of calm water at the crests and rough water at the troughs. Calm, smooth waters reflect more light directly back to the satellite, resulting in a bright, pale stripe along the length of the internal wave. The rough waters in the trough scatter light in all directions, forming a dark line.

- "There are definitely ocean internal waves in this image," said environmental engineer Nicole Jones of The University of Western Australia. "We have measured them off the coast of Ningaloo with instruments in the water. The different directions of the wave fronts are most likely due to the different seafloor slope directions in this region." She notes that internal waves play an important role in global ocean circulation and mixing, which is critical to understanding the ocean's role in climate and in the movement of nutrients and carbon from the depths to the surface and back. Jones and colleagues also study internal waves for their potential impact on drill rigs and other offshore structures.


Figure 41: On Feb. 10, 2016 (3:05 UTC), the MODIS instrument on Terra acquired this natural-color image of wave patterns off the coast of Western Australia (image credit: NASA Earth Observatory, Jeff Schmalz)

• February 3, 2016: Starting in early October 2015, farmers in southern Africa typically plant maize (corn)—an important food staple—across millions of hectares of land. But the first half of the 2015-2016 growing season was far from typical. Hot and dry conditions associated with a strong El Niño left experts wondering if a record agricultural drought was in the works. 38)

- Whether the season breaks a record won't be known until the growing season concludes in April 2016. But early in the season, when crops are normally planted, many areas saw inadequate growing conditions. According to Curt Reynolds of the USDA Foreign Agricultural Service, rainfall in South Africa's croplands from October through December 2015 was the lowest measured since at least 1981. With so little rainfall, sowing was delayed and plants could not emerge.

- Reynolds and others track growing conditions around the world by analyzing the NDVI (Normalized Difference Vegetation Index), a measure of how much plants absorb visible light and reflect infrared light. Drought-stressed vegetation reflects more visible light and less infrared light than healthy vegetation.

- This NDVI anomaly map above is based on data from the MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite. The map contrasts plant health in December 2015 against the 2000–2015 average for that month. Brown areas show where plant growth, or "greenness," was below normal. Greens indicate vegetation that is more widespread or abundant than normal for the time of year. Grays depict areas where data were not available, usually due to cloud cover.

- Three South African provinces—Free State, North West, and Mpumalanga—normally account for more than 80 percent of the country's maize/corn production. By January 24, 2016, Free State and North West still lacked green vegetation. Some greenery was visible in Mpumalanga, but the below-average levels hinted that crop yields would likely be low.


Figure 42: Drought in Southern Africa, acquired with MODIS on Terra in December 2015 (image credit: NASA Earth Observatory, Jesse Allen, Joshua Stevens)

- Assaf Anyamba, a remote sensing scientist with the NASA Goddard Earth Sciences Technology Center, noted that some areas were hit particularly hard by the drought. Among them was Lejweleputswa, a district in northwest Free State. The graph of Figure 43 the map shows how the measure of NDVI in Lejweleputswa midway through the 2015-2016 season compares to previous seasons and the mean from 2001–2015 (dashed gray line).


Figure 43: This temperature anomaly map is based on data from MODIS on Terra, it shows land surface temperatures in Dec. 2015 compared to the 2000–2015 average for that month. Red colors depict areas that were hotter than the average; blue colors were colder than average. White pixels were normal, and gray pixels did not have enough data (image credit: NASA Earth Observatory, Jesse Allen, Joshua Stevens)

• December 18, 2016: As of today, the Terra mission is 16 years on orbit. During this time the Terra satellite orbited the Earth more than 80,000 times, equivalent to a distance of > 5.6 billion km. 39)

- While Terra is not being replaced, Terra scientists eagerly await the launch of the Sentinel-3 spacecraft of ESA ( European Space Agency), scheduled for launch in early Feb. 2016. Sentinel-3 carries the OLCI (Ocean Land Color Instrument), which is similar to MODIS on Terra and Sentinel-3 will also have a morning crossing time like Terra.

- As the Flagship Earth Observing Satellite, Terra was the first satellite to look at Earth system science, collecting multiple types of data dedicated to various areas of Earth science. Scientists are able to document relationships between Earth's systems and examine their connections. In addition, Terra data has many applications that help people everyday.

• Nov. 18, 2015: Winter storms can blanket Iceland almost entirely with snow. The relative warmth of summer and fall, however, exposes a spectacular, varied landscape. "The visible snow cover is typical for this time of the year, compared to conditions during the past 15-20 years," said Thorsteinn Thorsteinsson, a glaciologist at the Icelandic Meteorological Office. He noted, however, that compared to the reference period of 1961-1990, snow cover is "almost certainly" less than average in the highland and mountain regions above 400 m in elevation. 40)

- The melting of seasonal snow cover accentuates the boundaries of Iceland's permanent ice caps. The ice caps appear smooth and rounded in contrast with the snow-covered interior plateau or the snow-capped ridges along the glacier-carved coastline. All ice caps in Iceland have been retreating rapidly and losing volume since 1995. In October 2015, however, scientists from the Icelandic Met Office showed that the Hofsjökull ice cap, outlined in red (Figure 44), had gained mass according to their ground-based measurements.

- An ice cap that has gained more mass than it has lost is said to have a positive mass balance. The graph below the image shows the annual mass balance of Thjórsárjökull, one of the ice cap's three basins, since the start of measurements in 1989. Thjórsárjökull's mass balance in 2015 was positive for the first time since 1993.

- The ice cap's reversal in 2015 is due to abundant winter precipitation and cool summer temperatures, explained Thorsteinsson. In spring 2015, the thickness of winter snowfall on the ice cap's three basins ranged from 25 to 60 percent above the 1995-2014 average. In the summer, melting was limited because of cool northerly winds.

- The situation changed in the fall, as September and October were unusually warm. When temperatures rise, melt water flows into the island's numerous lakes and reservoirs. Hálslón reservoir, the long and narrow feature on the east side, holds glacial meltwater. Öskjuvatn crater lake, Hágöngulón reservoir, and Thórisvatn natural lake and reservoir also stand out because they are dark and surrounded by snow.

- But one of the more prominent dark features just south of Öskjuvatn, is not water at all. "At first sight, one might think that this is another highland lake," Thorsteinsson said. "But actually, it is a fresh lava field" from the Holuhraun eruption from August 2014 to February 2015. During the eruption, lava poured from fissures just north of the Vatnajökull ice cap and near the Bárðarbunga volcano. By January 2015, the Holuhraun lava field had spread across more than 84 km2 . False-color satellite imagery here and here make it even more apparent that Holuhraun is not a lake.


Figure 44: MODIS on Terra acquired this this natural-color view of the Nordic island nation on November 9, 2015 (image credit: NASA Earth Observatory, Joshua Stevens, Jeff Schmaltz)


Figure 45: Illustration of the Hofsjökull ice cap water levels in the timeframe 1989 to 2015 (image credit: NASA Earth Observatory)

• October 21, 2015: Sierra Nevada is a Spanish name that means "snowy mountain range." While the term "snowy" has generally been true for most of American history, the mountain range has seen far less snow accumulation in recent years. The depth and breadth of the seasonal snowpack in any given year depends on whether a winter is wet or dry. Wet winters tend to stack up a deep snowpack, while dry ones keep it shallow. These images show the snowpack on the Sierra Nevada amid the wet year of 2011 (Figure 46) and the dry year of 2015 (Figure 47). They were acquired by MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA's Terra satellite. 41)

- Both images were acquired on March 31, about halfway through the water year. A "water year" is the 12-month period from October 1 through September 30. The snowpack on the Sierra Nevada has generally peaked and begins to melt by the beginning of April. Meltwater runoff from that snowpack helps replenish rivers and reservoirs while recharging the groundwater.

- The wet year of 2011 buffered the initial effects of drought that returned in 2012, but dry conditions deepened in subsequent years. By March 2015, about one-third of the ground-based monitoring sites in the Sierra Nevada recorded the lowest snowpack ever measured. Some sites reported no snow for the first time. One month later, only some sites—generally those at higher elevations—had any measureable snowpack.

- Scientists from the University of Arizona wrote in a September 2015 article in Nature Climate Change, that the low snowpack conditions of 2015 were truly extraordinary. Tree-ring records of precipitation anomalies and of temperature allowed them to reconstruct a 500-year history of snow water equivalent in the Sierra Nevada. The researchers found that the low snowpack of April 2015 was "unprecedented in the context of the past 500 years." 42)


Figure 46: The snowpack on the Sierra Nevada amid the wet year of 2011, acquired by the MODIS instrument on Terra on March 31, 2011 (image credit: NASA, Earth Observatory, Jesse Allen)


Figure 47: The snowpack on the Sierra Nevada amid the dry year of 2015, acquired by the MODIS instrument on Terra on March 31, 2015 (image credit: NASA, Earth Observatory, jesse Allen)

June 22, 2015: The NASA Science Senior Review Panel expects the Terra mission continuation through 2022, based on battery and fuel. Terra's long term data record is invaluable for teasing out subtle climate signals, including Earth's radiation budget, cloud properties, GPP (Gross Primary Productivity), Suomi-NPP, air pollution, radiative forcing, atmospheric composition, and aerosols. No spacecraft or instrument trends indicate that a major component is predicted to fail in the next 5 years. Normal on-orbit degradation is not expected to significantly limit the lifetime of any major spacecraft subsystem or component on-board within the next 5 years. 43)

- The Panel identified two Major Strengths, no Major Weaknesses, two Minor Strengths, and three Minor Weaknesses. The five instruments on Terra have continued to perform very well, which provides confidence that they will continue to perform at their current level through the proposed mission extension period. The propulsion, power, attitude determination and control, and primary communication systems continue to perform very well, maintain redundancies, and appear able to support science operations during the proposed mission extension period. - End of life planning is supported by a flight dynamics analysis that is well formulated with respect to constellation safety. The Terra mission benefits from ongoing efforts to modernize and improve ground systems, including multi-mission support modernization, operational scheduling, and IT security. However, overall data storage has been reduced by 17.2% due to the disabling of 10 of the total 58 PWA (Printed Wire Assembly) boards in the two spacecraft DMUs (Data Memory Units), thus reducing ASTER data collection significantly. The Terra batteries have two minor aging issues. The risk for the 4-year mission extension is expected to be higher.

- The Terra mission is now beyond 15 years of continuous data collection, providing fundamental observations of the Earth's Climate System, high-impact events, and adding value to other satellite missions and field campaigns. With 5 sensors providing a unique combination of spatial resolutions, temporal sampling, and multiple look angles, Terra is an exemplary mission that offers a tremendous long term data record capable of identifying subtle climate signals. The Terra mission is an international mission (US, Japan, and Canada) with broad participation among three NASA centers (JPL, Langley, and Goddard). The 5 sensors onboard Terra (ASTER, CERES, MISR, MODIS, and MOPPITT) collectively contribute to 81 calibrated and validated core data products. The value of Terra to the science and operational communities is unequivocal. The data distribution numbers for 2013 and 2014 exceed the combined distribution numbers for all other years combined – an indication of the continued and growing use of the data products. There were over 1,600 peer-reviewed papers in 2014, bringing the mission total to over 11,000. All of Terra's instruments are performing in exemplary fashion, except for ASTER's SWIR bands which were declared inoperable in 2009. Despite this, ASTER data have been used to produce 30 million tiles of the Global Digital Elevation Model -the most complete, consistent, high-resolution global topographic data set ever released.

• June 7, 2015: Looking up at the sky to enjoy the diversity and beauty of clouds is a pastime as ancient as humanity itself. Yet only during the past century—thanks to the Wright brothers and other pioneering aviators—have we had the ability to look down on clouds from above. 44)

- While a top-down view of clouds has led to important advances in meteorology and atmospheric science, it has also produced something much more difficult to quantify—simple beauty. For instance, on May 20, 2015, the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument on NASA's Terra satellite captured this view of several cloud vortices swirling downwind of the Canary Islands and Madeira.

- Theodore von Kármán, a Hungarian-American physicist (1881-1963), was the first to describe the physical processes that create long chains of spiral eddies like the ones shown in Figure 48. Known as von Kármán vortices, the patterns can form nearly anywhere when fluid flow is disturbed by an object. In this case, the unique flow occurs as winds rush past the tall peaks on the volcanic islands. As winds are diverted around these high areas, the disturbance in the flow propagates downstream in the form of vortices that alternate their direction of rotation.

- Satellite sensors have spotted von Kármán vortices around the globe before, including off of Guadalupe Island, near the coast of Chile, in the Greenland Sea, in the Arctic, and even next to a tropical storm. However, this scene is particularly notable for the fact that three distinct streams of vortices are visible.


Figure 48: Von Kármán vortices over the northwest coast of Africa, acquired on May 20, 2015 with MODIS on Terra (image credit: NASA Earth Observatory, Jeff Schmaltz)

•June 5, 2015: May is generally the hottest month in India, but even by local standards May 2015 was unusual. For nearly two weeks, many areas faced temperatures that were 5.5º C above normal. By June 4, the extreme weather had claimed the lives of more than 2,500 people, according to news reports. That put the heat wave among the five deadliest on record. Many of the victims were elderly, homeless, or construction workers. 45)

- By observing outgoing longwave radiation, the CERES (Clouds and Earth's Radiant Energy System) sensor on NASA's Terra satellite offers a different view of the intensity and breadth of the heat wave. Outgoing long wave radiation is a measure of the amount of energy emitted to space by Earth's surface, oceans, and atmosphere. The hotter an area is, the more energy it radiates. The false-color map (Figure 49) shows how much outgoing radiation left Earth's atmosphere between May 15 and May 27. The amount of heat energy radiated (in W/m2) is depicted in shades of purple. Light purple areas emitted the most longwave radiation and were the warmest. Darker purple areas emitted less radiation and were cooler.

- As observed by CERES, the hot weather was not limited to India. Pakistan, southern Iran, the United Arab Emirates, and Oman also faced extremely hot temperatures. On some days, it was even hotter in parts of Pakistan than it was in India, according to news reports. On June 3, temperatures soared to 50.7º Celsius in Sweihan, a town in the United Arab Emirates.

- Part of the reason the death toll has been so high in India is because of the humidity. Many of the deaths occurred in Andhra Pradesh and Telangana, states in southern India that faced extremely high humidity as well as extreme temperatures. High humidity increases the heat index and makes temperatures feel even warmer. Humidity plays a critical role in deadly heat waves because the human body relies on sweat to cool itself. If humidity gets too high, sweat cannot evaporate efficiently and the body begins to overheat.



Figure 49: This false-color map shows how much outgoing radiation left Earth's atmosphere between May 15-27, 2015 (image credit: NASA Earth Observatory image, Jesse Allen)

• June 4, 2015: The Nepal 7.8 magnitude Gorkha earthquake and its aftershocks. As millions of people regroup from earthquakes in Nepal, a team of international volunteers is combing through satellite imagery of the region to identify additional hazards: earthquake-induced landslides. "Landslides are a common secondary hazard triggered by earthquakes or rainfall," said Dalia Kirschbaum, a remote sensing scientist at NASA's Goddard Space Flight Center and a leader of a landslide mapping effort. "Because landslides can mobilize and move so quickly, they often cause more damage than people realize." 46)


Figure 50: Map of the Nepal Gorkha earthquake locations of landslide events and hazards acquired by instruments on various spacecraft (image credit: NASA Earth Observatory, Jesse Allen)

Legend to Figure 50: The colors represent the teams that found or are studying them. ICIMOD (red) stands for the International Centre for Integrated Mountain Development, an institution focused on improving the lives of people in the Hindu Kush Himalayan region. ICIMOD also serves as a regional hub for SERVIR, a joint initiative by NASA and the U.S. Agency for International Development. Both Kirschbaum and Kargel are members of NASA's SERVIR Applied Sciences team.

- As part of a disaster-relief response to the 7.8-magnitude Gorkha earthquake and its aftershocks, Kirschbaum and Jeff Kargel, a glaciologist at the University of Arizona, are organizing a group of volunteer scientists to identify where and when landslides have occurred in earthquake-affected areas of Nepal, China, and India. From April 25, the date of the first earthquake, to May 20, the team has collectively mapped nearly 1,000 landslides. Different subgroups have focused on disaster mapping, measurement and assessment, hazard impact, or communications. Some teams create damage proxy maps that tell the type and extent of the existing damage; others create vulnerability maps that show potential risks.

- Kargel helped form one landslide-mapping subgroup—the "induced hazards" team—in order to identify hazards triggered by the earthquakes and to help guide relief efforts. He found nearly 40 volunteers by reaching out to a NASA-supported network called Global Land Ice Measurements from Space (GLIMS). "It's stunning to see the level of commitment, passion, and forensic skill the volunteers are bringing to these tasks," said Kargel. "There are no words to describe this sense of mission that goes way above the scientific call of duty."

- Mapping landslides is especially important because of the impending monsoon season. The highest number of landslides occur during the rainy months between June and October, Kirschbaum noted. In general, if the land has slid in a specific area, it will have a higher likelihood of experiencing another landslide because the ground is unstable and more susceptible to environmental triggers like heavy rain. In the aftermath of the Gorkha earthquake, researchers are concerned that landslides will be even more frequent this year.

- The landslide mapping effort includes researchers from Nepal, the United States, Canada, the United Kingdom, China, Japan, Australia, and the Netherlands. The collaborators provided information that Nepalese government, military, and scientific entities could use to make informed decisions about evacuations and relief support. - The mapping effort will have a long-term benefit, as well. "How can we better understand landslide processes scientifically," Kirschbaum asked, "and then how can we use models, weather forecasts, and other tools to help government and science entities protect citizens?"

- The NASA-sponsored team is using satellite images to identify landslide locations, to characterize additional hazards (for example, dammed lakes), and to incorporate other useful information such as locations of nearby villages. Data sources include the Landsat satellites, the Earth Observing-1 satellite, the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) instrument on the Terra satellite, the WorldView and GeoEye satellites operated by Digital Globe, and image mosaics and topographic information accessible in Google Earth. As an example, Figure 51 is a natural-color view of the study area that was acquired by Landsat 8 on June 1, 2015.

- A U.K. mapping team (blue dots on the map) consists of scientists from the British Geological Survey (BGS) and Durham University. Like their NASA-sponsored colleagues, they are identifying landslides using satellite data from various sources and building a database for future study and for relief efforts.

- Researchers in Nagoya University (NGA; purple on the map) in Japan have identified more than 600 potential earthquake-induced landslides. An independent, Canadian-based group of MDA (MacDonald, Dettwiler and Associates Ltd.) has been locating landslides and potential landslides by analyzing areas before and after the earthquakes using data from RADARSAT-2 (orange-brown on the map), an Earth-observing satellite from the Canadian Space Agency.


Figure 51: Sample image of OLI on Landsat-8 acquired on June 1, 2015 (image credit: NASA Earth Observatory, Jesse Allen)

• June 2, 2015: Fourteen Years of Carbon Monoxide Measurements from MOPITT on Terra. Carbon monoxide is perhaps best known for the lethal effects it can have in homes with faulty appliances and poor ventilation. In the United States, the colorless, odorless gas kills about 430 people each year. However, the importance of carbon monoxide (CO) extends well beyond the indoor environment. Indoors or outdoors, the gas can disrupt the transport of oxygen by the blood, leading to heart and health problems. CO also contributes to the formation of tropospheric ozone, another air pollutant with unhealthy effects. And though carbon monoxide does not cause climate change directly, its presence affects the abundance of greenhouse gases such as methane and carbon dioxide. 47)

- Carbon monoxide forms whenever carbon-based fuels — including coal, oil, natural gas, and wood — are burned. As a result, many human activities and inventions emit carbon monoxide, including: the combustion engines in cars, trucks, planes, ships, and other vehicles; the fires lit by farmers to clear forests or fields; and industrial processes that involve the combustion of fossil fuels. In addition, wildfires and volcanoes are natural sources of the gas.

- Little was known about the global distribution of carbon monoxide until the launch of the Terra satellite in 1999. Terra carries a sensor MOPITT (Measurements of Pollution in the Troposphere) that can measure carbon monoxide in a consistent fashion on a global scale. With a swath width of 640 km, MOPITT scans the entire atmosphere of Earth every three days.

- Since CO has a lifetime in the troposphere of about one month, it persists long enough to be transported long distances by winds, but not long enough to mix evenly throughout the atmosphere. As a result, MOPITT's maps show significant geographic variability and seasonality. To view month by month maps of carbon monoxide, visit the carbon monoxide page in Earth Observatory's global maps section.

- In Africa, for example, agricultural burning shifts north and south of the equator with the seasons, leading to seasonal shifts in carbon monoxide. Fires are also the dominant source of carbon monoxide pollution in South America and Australia. In the United States, Europe, and eastern Asia, the highest carbon monoxide concentrations occur around urban areas and tend to be a result of vehicle and industrial emissions. However, wildfires burning over large areas in North America, Russia, and China also can be an important source.

- Terra has been in orbit long enough to observe significant changes over time. To illustrate how global carbon monoxide concentrations have changed, maps of the mission's first (2000) and most recent full year (2014) of data are shown in Figure 52. The maps depict yearly average concentrations of tropospheric carbon monoxide at an altitude of 3,700 meters (12,000 feet). Concentrations are expressed in parts per billion by volume (ppbv). A concentration of 1 ppbv means that for every billion molecules of gas in a measured volume, one of them is a carbon monoxide molecule. Yellow areas have little or no carbon monoxide, while progressively higher concentrations are shown in orange and red. Places where data was not available are gray. For both years, the data has been averaged, which eliminates seasonal variations.

- According to MOPITT, carbon monoxide concentrations have declined since 2000 (Figure 52). The decrease is particularly noticeable in the Northern Hemisphere. Most air quality experts attribute the decline to technological and regulatory innovations that mean vehicles and industries are polluting less than they once did. Interestingly, while MOPITT observed slight decreases of carbon monoxide over China and India, satellites and emissions inventories have shown that other pollutants like sulfur dioxide and nitrogen dioxide have risen during the same period.

- "For China, nitrogen dioxide emissions are mostly from the power and transportation sectors and have grown significantly since 2000 with the increase in demand for electricity," explained Helen Worden, an atmospheric scientist from the National Center for Atmospheric Research (NCAR). "Carbon monoxide emissions, however, have a relatively small contribution (less than 2 percent) from the power sector, so vehicle emissions standards and improved combustion efficiency for newer cars have lowered carbon monoxide in the atmosphere despite the fact that there are more vehicles on the road burning more fossil fuel."

- As illustrated by the maps, the news is also generally positive for the Southern Hemisphere, where deforestation and agricultural fires are the primary source of carbon monoxide. In South America, MOPITT observed a slight decrease in carbon monoxide; other satellites have observed decreases in the number of small fires and areas burned, suggesting a decrease in deforestation fires since 2005. Likewise, MOPITT has observed decreases in the amount of carbon monoxide over Africa. "There have been fewer fires in Africa, so that is a big part of the story there," explained Worden. "However, growing cities might be increasing of the amount of CO in some areas of equatorial Africa."

- The line graph of Figure 53 shows the long-term trend as well as monthly variations in carbon monoxide concentrations. While the overall trend is downward, several peaks and valleys are visible. For instance, some researchers attribute the peak from around 2002 to 2003 to an unusually active fire season in the boreal forests of Russia. The dip in carbon monoxide emissions from 2007 to 2009 also matches a decline in global fire emissions. In addition, researchers have noted that this dip overlaps with a global financial crisis that started in late 2008 and caused global manufacturing output to decline.


Figure 52: Earth's CO concentration acquired with MOPITT on Terra in 2000 (top) and in 2014 (bottom), image credit: NASA Earth Observatory, Jesse Allen and Joshua Stevens


Figure 53: Long-term CO concentration trend and monthly variations as measured by MOPITT (image credit: NASA Earth Observatory, Jesse Allen and Joshua Stevens)

• On April 22, 2015, the Calbuco volcano in southern Chile began erupting for the first time since 1972. An ash cloud rose at least 15 km above the volcano (Figure 54), menacing the nearby communities of Puerto Montt (Chile) and San Carlos de Bariloche (Argentina). The eruption led the Chilean Emergency Management Agency and the Chilean Geology and Mining Service (SERNAGEOMIN) to order evacuations within a 20 km radius around the volcano. About 1,500 to 2,000 people were evacuated; no casualties have been reported so far. 48)


Figure 54: At 14:20 UTC on April 23, 2015, the MODIS instrument on the Terra satellite acquired a natural-color image of the extensive ash plume (image credit: NASA Earth Observatory, Joshua Stevens, Jeff Schmalz)

• In Feb. 2015, the Terra spacecraft and its payload continue to provide key data to address the interrelationships between Earth's various systems, long after its planned lifetime. With only one minor glitch, those data continue to be obtained and disseminated to a wide range of communities, giving further testimony to the excellence of those far-sighted individuals and organizations responsible for Terra and its increasingly large family of LEO (Low Earth Orbit) remote-sensing instruments. 49)

- On Dec. 18, 2014 the Terra spacecraft was 15 years on orbit. Terra is still operating at near-full capability, now nine years beyond its designed six year lifetime, with only slight reductions in its data-gathering capabilities. The Terra mission has enabled new discoveries in Earth System Science. Dedicated engineers and scientists work together to calibrate instruments, process and store the vast quantities of data returned, validate results, and continue to coax cutting edge science out of aging hardware.

• Dec. 10, 2014: The mountains surrounding Kashmir Valley now trap air a bit like they once trapped water. The high ridges can set up airflow patterns that concentrate smoke and other airborne pollutants near the valley floor, causing outbreaks of haze (Figure 55). 50)

- Haze is most likely to occur when warm, buoyant air moves over cooler, denser air—a situation meteorologists call a temperature inversion. Temperature inversions often develop on winter nights as the surface loses heat and chills the air immediately above. Mountain valleys often strengthen inversions because cold air from mountaintops tends to flow down slopes and push warmer air up from the floor in the process. Snow cover also increases the likelihood of an inversion because snow cools the air near the surface by reflecting much of the Sun's energy rather than absorbing it. With a temperature inversion in place, air in the valley becomes stagnant; the warm air above it acts like a cap and prevents pollutants from dispersing.

- Much of the haze visible in the image likely had its origins in charcoal production or the burning of biomass. Charcoal is widely used to heat homes in the Kashmir Valley in the winter and emits several types of polluting gases and aerosol particles into the atmosphere.


Figure 55: Haze in the Kashmir Valley, acquired by MODIS on Terra on Dec. 5, 2014 (image credit: NASA, Jeff Schmalz)

Legend to Figure 55: About 4.5 million years ago, the Kashmir Valley was at the bottom of a large lake, encircled by a ring of rugged mountains. Much of the lake's water has long since drained away through an outlet channel on the valley's west side. However, evidence of the lake remains in the bowl-like shape and the clay and sand deposits on the valley floor.

• May 21, 2014: Fires in Russia in May 2014 fueled pyrocumulus clouds that pumped smoke high into the atmosphere. With dozens of forest fires burning in Russia's Irkutsk region, authorities have declared a state of emergency (Figure 56). 51)

Some of the blazes likely began on farms but then spread into forests due to high winds and warm temperatures. As seen on Worldview, MODIS began to detect small fires in Irkutsk on May 14. Many were along rivers near farmland. After burning at a moderate level for a few days, the size and intensity of the fires increased significantly on May 18.

In addition to producing thick plumes of smoke, the fires fueled numerous pyrocumulus clouds—tall, cauliflower-shaped clouds that billowed up above the smoke. Pyrocumulus are similar to cumulus clouds, but the heat that forces the air to rise—which leads to cooling and condensation of water vapor—comes from fire instead of sun-warmed ground. In satellite images, pyrocumulus clouds appear as opaque white patches hovering over darker smoke.


Figure 56: The MODIS instrument on Terra captured this image on May 18, 2014 (image credit: NASA Earth Observatory)

Legend to Figure 56: The red outlines indicate hot spots where MODIS detected unusually warm surface temperatures associated with fires. The image is centered at 56.76º North and 105.47º East.

• The Terra spacecraft and its sensor complement (except the SWIR bands on ASTER) are operating nominally in 2014.


Figure 57: Big Island of Hawaii captured by the MODIS instrument on Terra on January 26, 2014 (image credit: NASA Earth Observatory) 52)

Legend of Figure 57: The remarkably cloud-free view shows the range of ecological diversity present on the island. Many of the world's climate zones can be found on Hawaii for two related reasons: rainfall and altitude. The Big Island is home to Mauna Kea, the tallest sea mountain in the world at 4,205 m and the tallest mountain on the planet—if you measure from seafloor to summit, a distance of more than 9,800 m.

Despite Mauna Kea's height, it is Mauna Loa that dominates the island. With an altitude of about 4,169 m — the actual number varies depending on volcanic activity — Mauna Loa is the most massive mountain in the world. Temperatures dip low at the summit of these peaks, resulting in a tree-free polar tundra, pale brown in this image.

The mountains help shape rainfall patterns on Hawaii so that desert landscapes exist side-by-side with rainforests. In fact, average yearly rainfall ranges from 204 mm to 10,271 mm . Trade winds blow mostly from the east-northeast, and the sea-level breezes hit the mountains and get forced up, forming rainclouds. The east side of the island is lush and green with tropical rainforest. Much less moisture makes it to the lee side of the mountains. The northwestern shores of Hawaii are desert. Kona, on the western shore, receives plenty of rain because the trade winds curve back around the mountains and bring rain. Pale green areas on all sides of the island are agricultural land and grassland.

The other environmental force painting Hawaii's canvas is volcanism. Mauna Loa and Mauna Kea are both volcanic, though only Mauna Loa has been active recently. However, in this department, Kilauea is the superlative: It is one of the world's most active volcanoes. A small puff of steam rises from an erupting vent in this image. Black and dark brown lava flows extend from both Kilauea and Mauna Loa.

• January 2014: A swirling mass of Arctic air moved south into the continental United States in early January 2014. On January 3, the air mass began breaking off from the polar vortex, a semi-permanent low-pressure system with a center around Canada's Baffin Island. The frigid air was pushed south into the Great Lakes region by the jet stream, bringing abnormally cold temperatures to many parts of Canada and the central and eastern United States.

- When the cold air passed over the relatively warm waters of Lake Michigan and Lake Superior, the contrast in temperatures created a visual spectacle. As cold, dry air moved over the lakes, it mixed with warmer, moister air rising off the lake surfaces, transforming the water vapor into fog—a phenomenon known as steam fog. 53)

The result: One of the coldest Arctic outbreaks in two decades has plunged into the USA, bringing bitterly cold temperatures to the Midwest, South and East. 54)


Figure 58: Natural color image of MODIS on Terra captured on January 6, 2013 showing fog forming over the lakes and streaming southeast with the wind (image credit: NASA)


Figure 59: A false color image of MODIS on Terra acquired on January 6, 2014which helps to illustrate the difference between snow (bright orange), water clouds (white), and mixed clouds (peach), image credit: NASA

• December 01, 2013: Offshore from Argentina, spring is in bloom. Massive patches of floating phytoplankton colored the ocean in November 2013. These microscopic, plant-like organisms are the primary producers of the ocean, harnessing sunlight to nourish themselves and to become food for everything from zooplankton to fish to whales. 55)


Figure 60: The MODIS instrument on NASA's Terra satellite acquired this natural-color image on Nov. 26, 2013 (image credit: NASA)

Legend to Figure 60: The chalky blue swirls in the South Atlantic Ocean, as well as fainter streaks of yellow and green, are evidence of abundant growth of phytoplankton across hundreds of kilometers of the sea. These organisms contain pigments (such as chlorophyll) or minerals (calcium carbonate) that appear blue, green, white, or other colors depending on the species. The phytoplankton in this image are likely a blend of diatoms, dinoflagellates, and coccolithophores. Near the coast, the discoloration of the water could be phytoplankton or it might be sediment runoff from rivers.

These phytoplankton help fuel one of the world's best fishing grounds, particularly for shortfin squid, hake, anchovies, whiting, and sardines. The area known as the Patagonian "shelf-break front," is a crossroads of currents—Circumpolar, Brazil, and Malvinas—where nutrients are carried in from southern waters or churned up from the edge of the continental shelf.

• June 2013: The 2013 Senior Review evaluated 13 NASA satellite missions in extended operations: ACRIMSAT, Aqua, Aura, CALIPSO, CloudSat, EO-1, GRACE, Jason-1, OSTM, QuikSCAT, SORCE, Terra, and TRMM. The Senior Review was tasked with reviewing proposals submitted by each mission team for extended operations and funding for FY14-FY15, and FY16-FY17. Since CloudSat, GRACE, QuikSCAT and SORCE have shown evidence of aging issues, they received baseline funding for extension through 2015. 56)

- The Science Panel endorses the continuation of the Terra mission because it will extend the records for numerous data products used to monitor and understand changes in climate and the effects of those changes on land, ocean, and atmosphere over the next few years. The Terra mission has already accumulated 13 years of data from five instruments, each of which provides valuable data for scientific questions pertaining to the Earth and its changes, including 79 core products as well as support for monitoring and relief efforts for natural and man-made disasters. The continuation of the Terra mission would extend the baseline of these measurements and, for some instruments, provide continuity linking past and future missions.

- The products from Terra are invaluable to a large number of scientific investigations related to the Earth system and global change. From the perspective of the Science Panel, the data from MODIS, alone, justifies that the mission be continued.

• In June 2013, a wildfire broke out in Black Forest, a wooded suburb of Colorado Springs, CO, USA. The fire charred more than 5,700 hectare, destroying 509 homes and killing two people. The Black Forest fire was the most destructive in the state's history. 57)

Figure 61 provides an image of the burn scar on June 21, 2013. Vegetation-covered land is red in the false-color image, which includes both visible and infrared light. Patches of unburned forest are bright red. Unburned grasslands are pink. The darkest gray and black areas are the most severely burned. Buildings, roads, and other developed areas appear light gray and white.

The most severe damage occurred north of Shoup Road, but the severity varied widely by neighborhood. Cathedral Pines, for instance, escaped largely unscathed. Many residents of that neighborhood put rocks around their homes, removed vegetation and dead trees from their yards, avoided using mulch, and followed other fire prevention strategies that helped keep flames back long enough for fighters to save homes

One key building that escaped the flames was Edith Wolford elementary school. Though it was in the middle of an area that was severely burned, the school survived intact partly because of the large, treeless parking lot surrounding it.


Figure 61: Aftermath of Colorado's most destructive wildfire observed by the ASTER instrument on the Terra satellite on June 21, 2013 (image credit: NASA)

• The MODIS instrument on Terra captured this image (Figure 62) of the Canary Islands (off the coast of West Africa) on June 15, 2013. 58)


Figure 62: Play of light on water as observed by MODIS, a result of sunglint (NASA, Jeff Schmaltz LANCE/EOSDIS MODIS Rapid Response Team)

Legend to Figure 62: In the image, wavy, windsock-like tails stretch to the southwest from each of the islands. The patterns are likely the result of winds roughening or smoothing the water surface in different places. Prevailing winds in the area come from the northeast, and the rocky, volcanic islands create a sort of wind shadow—blocking, slowing, and redirecting the air flow. That wind, or lack of it, piles up waves and choppy water in some places and calms the surface in others, changing how light is reflected. Ocean currents, oil or pollution slicks, and internal waves can also alter surface patterns, though none are necessarily visible in this image.

• The Terra spacecraft and its sensor complement (except the SWIR bands on ASTER) are operating nominally in 2013. NASA extended the mission to 2015 (after the 2011 review). 59)


Figure 63: MODIS image of a dust storm that blew out of Libya and across the Mediterranean Sea in late March 2013 (image credit: NASA)

Legend to Figure 63: MODIS on NASA's Terra satellite acquired this natural-color image of the dust storm on March 30, 2013. The dust plumes arose hundreds of kilometers inland, and dust stretched across the Mediterranean Sea toward southern Italy. - Southwest of the coastal city of Banghazi (Benghazi), an especially thick dust plume spanned roughly 100 km , and the plume was thick enough to completely hide the ocean surface below. 60)


Figure 64: Air over Beijing China on January 14, 2013 as observed with the MODIS instrument (image credit: NASA, Jeff Schmaltz)

Legend to Figure 64: Residents of Beijing and many other cities in China were warned to stay inside in mid-January 2013 as the nation faced one of the worst periods of air quality in recent history. The Chinese government ordered factories to scale back emissions, while hospitals saw spikes of more than 20 to 30 % in patients complaining of respiratory issues, according to news reports. 61)

• The Terra spacecraft and its instruments are operating nominally in 2012 (> 12 years on orbit). - In June 2011, the NASA Earth Science Senior Review recommended an extension of the Terra mission as baseline up to 2013 and a further extension as baseline up to 2015.


Figure 65: MODIS natural color image of the eastern half of the Black Sea observed on May 18, 2012 (image credit: NASA) 62)

Legend to Figure 65: Enriched by nutrients carried in by the Danube, Dnieper, Dniester, Don and other rivers, the waters of the Black Sea are fertile territory for the growth of phytoplankton. The bounty is a mixed blessing. The milky, light blue and turquoise-colored water in the middle of the sea is likely rich with blooming phytoplankton that trace the flow of water currents. Closer to the coast, the colors include more brown and green, perhaps a brew of sediment and organic matter washing out from rivers and streams, though it may also be a sign of phytoplankton. Puffs of spring clouds linger over parts of the coastline.


Figure 66: Natural color image of MODIS acquired on January 23, 2012 showing a winter storn in the Pacific Northwest (image credit: NASA)

• The Terra spacecraft and its instruments are operating nominally in 2011. Terra is a huge success, and continuation of the data collection 11 year TERRA record from the five instruments: ASTER, CERES, MISR, MODIS, MOPITT, is critical to a wide array of earth system science.

According to the NASA Earth Science Senior Review 2011, the Terra platform is expected to remain fully functional through 2017 (battery, fuel, subsystems performance). The main failure to date is the SWIR bands on ASTER. But there continues to be significant use of the ASTER data from optical and TIR bands, and from the new global DEM. 63)


Figure 67: Waves of dust dance off the African Coast - this MODIS natural color image was taken on Sept. 23,2011 (image credit: NASA)

Legend to Figure 67: The dust plumes sport a wave-like appearance—bands of thick dust alternating with bands of relatively clear air. Some waves extend westward while others curve toward the south in giant arcs. At the end of one curving wave of dust, a line of clouds extends southward over the sea. These ribbon-like patterns might result from atmospheric waves. - Sand seas sprawl over much of Mauritania, and the abundant sand provides plentiful material for dust storms. This dust storm hasn't yet reached Cape Verde, which lies to the southwest, but the dust appears headed in that general direction.

• More than a decade after launch, the Terra spacecraft and its instruments are operating nominally in 2010 (design life of six years). The spacecraft remains in extraordinary good condition and with enough fuel to provide its service for another 6-7 years to come. 64) 65) 66)

All five instruments onboard the spacecraft continue to gather scientific data, although one of the three telescopes on ASTER is no longer working. ASTER stopped capturing useful SWIR imagery in 2008. The spacecraft is still working on its primary spacecraft components with one exception - the DASM (Direct Access System Module) which broadcasts MODIS data to 150 sites around the world, experienced a failure in 2008. The mission team switched the broadcast services to the redundant module.

The MISR instrument has been collecting global Earth data from NASA's Terra satellite since February 2000. With its nine along-track view angles, four visible/near-infrared spectral bands, intrinsic spatial resolution of 275 m, and stable radiometric and geometric calibration, no instrument that combines MISR's attributes has previously flown in space. The more than 10-year (and counting) MISR data record provides unprecedented opportunities for characterizing long-term trends in aerosol, cloud, and surface properties, and includes 3-D textural information conventionally thought to be accessible only to active sensors. Technology development is underway to extend future multiangle measurements to broader spectral range (ultraviolet to thermal infrared), wider spatial swaths (enabling more rapid global coverage), and accurate polarimetric imaging. 67)

• In the summer 2010, the project is reporting that many lessons have been learned from MODIS instrument operation, calibration, performance, algorithm refinements, and calibration coefficient LUT (Look Up Tables) updates. Listed in the following are some important factors that need to be considered to assure sensor performance and data quality: 68) 69)

- Comprehensive pre-launch calibration and characterization

- Dedicated calibration and validation effort throughout entire mission

- Close interactions among science and calibration teams and input from users

- Complete documentation on instrument operation concept, sensor calibration ATBD (Algorithm Theoretical Basis Document), algorithm and LUT update procedures, and sensor performance.

MODIS lessons have provided and will continue to provide valuable information for future missions and sensors, such as the VIIRS on the NPP and JPSS, ABI on GOES-R, OLI and TIRS on LDCM, and CLARREO. — Since launch, both Terra and Aqua MODIS have provided an unprecedented amount of high quality data and made significant contributions to the studies of short- and longterm changes in the Earth's system.

Terra spacecraft deep space calibration: In early 2003, the Terra S/C performed two deep space calibration maneuvers. The objective of the maneuvers is to provide the science instruments with calibration opportunities using the cold background of deep space and also the stable lunar surface as calibration targets. These maneuvers help to identify and to quantify payload data inaccuracies, such as scan-dependent offsets, allowing for the correction and for more accurate data products. Additionally, the lunar calibration maneuver enables inter-calibration with other spacecraft (e.g. SeaWiFS/SeaStar, Aqua MODIS) observing the same illumination reference.

A 240º pitch maneuver is designed to protect the instrument deck from sun exposure and also to provide a steady-state slew during the lunar viewing. The 35 minutes eclipse period and the requirements for a nearly perfect moon placement and continuous communications coverage impose a strict timing constraint on the execution of the maneuvers. The GN&C has to perform beyond the experience and constraints of a heritage system design. - When Terra executed the maneuvers, FDIR protection as well as the S/C attitude and instrument performance met or exceeded all expectations.

• MOPITT operational history: First data were collected in March 2000 and then almost continuously from March 22, 2000 until May 7, 2001 at which point the instrument was shut down due to an anomaly. However, data collection in reduced mode (less height resolution) was resumed on August 23, 2001 and has continued since then. It has produced a complete dataset of CO over the globe period of 14 months from March 2000 to May 2001 (reduced resolution data set after Aug. 2001). It has provided one of the first global dynamic pictures of tropospheric pollution and its transport on both the regional and global scale. Continued coverage will enable the science team to examine more aspects of the large-scale transport within the lower atmosphere.

An appropriately chosen redundancy scheme has extended the life of the instrument beyond the mission requirements. The success of the instrument can be attributed to its long life mechanisms, which continue to operate at high speeds. With the LMC motors currently exceeding 2 billion rotations, and the choppers over 5 billion rotations, the successful mechanism design has been proven on orbit. MOPITT has made upwards of 60 million measurements, and an application has been made to NASA to extend the Terra mission from nominally 6 years to 10 years, based on the success of MOPITT and the other instruments on the spacecraft (see Ref. 102).

• The commissioning phase of Terra (checkout and verification) lasted until Feb. 23, 2000 when the spacecraft reached also its final orbit. After this the observatory began its observations phase collecting scientific data.


Minimize Sensor Complement

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. 70) 71) 72) 73) 74) 75)

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. 76)

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. 77)

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. 78)

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


Figure 69: 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: 79) 80) 81) 82)

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


Figure 71: 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 72: 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: 83)

• 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. 84) 85) 86) 87)


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


Figure 74: 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 75: 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. 88) 89) 90) 91)

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


Figure 77: 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 78: Functional architecture of the MODIS instrument (image credit: Raytheon SBRS)


Figure 79: 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: 92) 93) 94) 95)

• 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 80: 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 81: 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 82: The MODIS SD device (image credit: NASA/GSFC)


Figure 83: 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). 96) 97) 98) 99) 100) 101) 102) 103)

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


Figure 85: Schematic illustration of the MOPITT instrument (image credit: University of Toronto)


Figure 86: Schematic view of the correlation radiometry concept (image credit: NCAR, University of Toronto)


Figure 87: 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. 104)


Figure 88: 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. 105) 106) 107) 108)

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.


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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 (

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