SMOS (Soil Moisture and Ocean Salinity)
SMOS (Soil Moisture and Ocean Salinity) Mission
SMOS is an ESA Explorer Opportunity science mission, a technology demonstration satellite project in ESA's Living Planet Program, in cooperation with CNES (France) and CDTI (Center for Technological and Industrial Development), Madrid, Spain. 1) 2) 3) 4) 5)
Known as ESA's ‘Water Mission', SMOS will improve our understanding of Earth's water cycle, providing much-needed data for modelling of the weather and climate, and increasing the skill in numerical weather and climate prediction. One of the highest priorities in Earth science and environmental policy issues today is to understand the potential consequences of modification of Earth's water cycle due to climate change. The influence of increases in atmospheric greenhouse gases and aerosols on atmospheric water vapor concentrations, clouds, precipitation patterns and water availability must be understood in order to predict the consequences for water availability for consumption and agriculture. 6)
The main science objective of the SMOS mission is to demonstrate observations of SSS (Sea Surface Salinity) over oceans and SM (Soil Moisture) over land to advance climatologic, meteorologic, hydrologic, and oceanographic applications. Soil moisture is a key variable in the hydrologic cycle. Over land, water and energy fluxes at the surface/atmosphere interface are strongly dependent upon soil moisture. SM is an important variable for numerical weather and climate models as well as in surface hydrology and in vegetation monitoring. Knowledge of the global distribution of salt in the oceans and of its annual and inter-annual variability, is crucial for understanding the role of the ocean and the climate system. Ocean circulation is mainly driven by the momentum and heat fluxes through the atmosphere/ocean interface, it is dependent on water density gradients, which in turn can be traced by the observation of SSS and SST (Sea Surface Temperature). 7) 8) 9) 10) 11) 12) 13) 14) 15)
Soil moisture can be retrieved from brightness temperature observations. Due to the large dielectric contrast between dry soil and water, the soil emissivity "epsilon" at a particular microwave frequency depends upon the moisture content. At L-band in particular, the sensitivity to soil moisture is very high, whereas sensitivity to atmospheric disturbances and surface roughness is minimal. 16) 17) 18)
Figure 1: Schematic view of Earth's water cycle (image credit: ESA, CNES)
Table 1: Scientific requirements for soil moisture retrieval 19)
For sea water, the dielectric constant is determined by the electrical conductivity and the microwave frequency. The ocean surface emissivity is a function of the dielectric constant and the state of the surface roughness. In principle it is possible to retrieve SSS from brightness temperature observations. - Mission requirements call for typical values to resolve specific phenomena:
• Barrier layer effects on the tropical Pacific heat flux: accuracy of 0.2 psu (practical salinity unit), with a spatial resolution of 100 km x 100 km, and a revisit time of 30 days.
Note: SSS is defined in practical salinity units (1 psu = 0.1%) and ranges from about 32 to 37 psu. In other words, salinity describes the concentration of dissolved salts in water; the psu value expresses the conductivity ratio. The average SSS is 35 psu, which is equivalent to 35 grams of salt in 1 liter of water. The sensitivity of brightness temperature to salinity is about 0.5 K/psu at a water temperature of 20ºC, decreasing to about 0.25 K/psu at 0ºC.
Salinity links the climatic variations of the global water cycle and ocean circulation: 20)
- Salinity is required to determine seawater density, which in turn governs ocean circulation
- Salinity variations are governed by freshwater fluxes due to precipitation, evaporation, runoff and the freezing and melting of ice.
• Halosteristic adjustment of heat storage from the sea level: 0.2 psu, a spatial resolution of 200 km x 200 km, and a repeat cycle of 7 days
• North Atlantic thermohaline circulation: 0.1 psu, a spatial resolution of 100 km x 100 km, and a repeat cycle of 30 days
• Surface freshwater flux balance: 0.1 psu, a spatial resolution of 300 km x 300 km, and a revisit time of 30 days.
Background on SMOS development: Twenty-six years after the first attempt to retrieve soil moisture from space (Skylab L-band radiometer experiment in 1973, referred to as S-194) and following seven years of technology development at ESA (since 1992), the SMOS Earth Explorer Mission was selected for implementation in November 1999 by ESA's Program Board for Earth Observation (PB/EO). Since then, a successful Phase A feasibility study (2000-2001) and a Phase B (2002) for further definition and critical breadboarding have been completed (the Phase B payload design was completed in Oct. 2003). Approval for full implementation was given in Nov. 2003. The SMOS project is now well consolidated, the payload implementation Phase C/D started in mid-2004. The CDR (Critical Design Review) of the payload took place in Nov. 2005. Delivery of the fully tested payload PFM (Proto-Flight Model) to Alcatel Cannes is scheduled for the end of 2006. 21)
In addition to SMOS, the SAC-D/Aquarius mission is currently under joint development by NASA and CONAE (Argentinian Space Agency). Aquarius will follow up the successful Skylab demonstration mission and employs a combined L-band real-aperture radiometer with an L-band scatterometer. The combined measurements will be focused on measurement of global sea-surface salinity. A launch of SAC-D/Aquarius is scheduled for 2010. Aquarius will cover the oceans in 8 days with a spatial resolution of 100 km, though its sensitivity to salinity will be better than that of SMOS due to its different design.
The SMOS satellite uses the generic Proteus bus developed by CNES and Alcatel Alenia Space (formerly Alcatel Space Industries). This standard platform has been designed to accommodate a wide field of missions, orbits, attitudes, instruments, and launch vehicles. Proteus has simple, well defined interfaces. The platform architecture is generic. Adaptations are limited to minor changes in software modules and launch vehicle interface.
The S/C bus is a box, nearly 1 m per side, with all the equipment units accommodated on four lateral panels and the lower plate. The platform TCS (Thermal Control Subsystem) relies on passive radiators and active regulation with heaters. Electrical power is generated by two symmetric wing arrays with single-axis step motors. Each wing is composed of four deployable panels (1.5 m x 0.8 m) covered with silicon cells which provide 685 W orbital average after 3 year mission (EOL). The power is distributed through a single non-regulated primary electrical bus (23/36 V) using a Li-ion battery.
Figure 2: Illustration of the deployed SMOS spacecraft (image credit: ESA)
The S/C is three-axis stabilized consisting of a PSM (Proteus Service Module) and a PLM (Payload Module). Typical pointing performance of better than 0.05º (3 σ) is provided by a control system with four reaction wheels and gyro-stellar attitude determination [attitude is provided by two STA (Star Tracker Assembly)]. Coarse sun sensors (8) and two 3-axis magnetometers provide attitude measurement and magnetic torquers generate torque. In addition, two of the four reaction wheels are used to provide gyroscopic stiffness. A GPS receiver provides S/C location data for accurate orbit determinations and onboard time delivery. 22) 23)
Due to the high variety of pointings to be handled with (earth pointing, yaw steering motion, inertial pointing, etc.) the AOCS concept has been based from the beginning on a gyro stellar hybridation with reaction wheel actuators unloaded through magnetotorquer bars, while safe hold mode only relies on kinetic momentum, coarse sun sensors and magnetic sensors and actuators, without the use of the four 1N thrusters in blow down mode limited to orbit control manoeuvres. This design has a proven robust behavior on all the LEO orbits which have been used in the realized missions.
The onboard command and data handling relies on a fully centralized architecture. The DHU (Data Handling Unit) performs most of the tasks through the central processor running the satellite software. It also supports the management of the communication links with all the satellite units either via discrete point-to-point lines or via a MIL-STD-1553B bus.
Figure 3: Schematic view of the command and control architecture (image credit: CNES)
SMOS is designed to operate mostly in an autonomous mode using the FDIR (Failure Detection Isolation and Recovery) concept (this permits to reduce drastically the working hours per day from the ground). The S/C bus is designed to operate in five distinct satellite modes: 1) normal autonomous operations mode, 2) safe hold mode, 3) star acquisition mode, 4) orbit correction mode with 2 thrusters, and 5) orbit correction mode with 4 thrusters. The SMOS spacecraft has a total mass of 658 kg (bus dry mass of 275 kg, 28 kg of hydrazine, four 1 N thrusters, payload module (PLM) of 355 kg). The design life is three years with a goal of five years.
The SMOS spacecraft features an attitude in which the boresight of the antenna is forward tilted by 32.5º with respect to nadir. This configuration enables measurements at line-of-sight angles between 0º - 50º. The satellite employs yaw steering about the local normal.
Figure 4: The stowed SMOS S/C with the bus at bottom and payload module on top (image credit: ESA)
Table 2: Overview of SMOS spacecraft parameters
TCS (Thermal Control Subsystem): The TCS is required to maintain all the payload equipment (MIRAS) within the specified temperature range with minimum heater power consumption. The most challenging requirements in operation are relevant to the stringent temperature control of the LICEF (Lightweight Cost-Effective Front-end) receivers. The TCS is based mainly on a passive design, supported by heater systems. All six LICEF receivers in each segment and the eighteen LICEF receivers on the Hub are installed on an aluminum doubler to minimize the gradients among them. 24)
Figure 5: Block diagram of the SMOS-MIRAS electrical architecture (image credit: ESA)
Legend to Figure 5: The TCS has two separate parts: (1) HM used for Measurement and Calibration Modes and controlled through CCU-CMN (Correlator and Control Unit-Coontrol and Monitoring Node) chain, and (2) HS used for SHM (Safe Hold Mode) and controlled through Proteus platform.
• Passive Thermal Control Design: The passive thermal control hardware incorporates: FSSM (Flexible Second Surface Mirror coatings) for thermal radiators, MLIs (Multi-Layer Insulation Blankets), Germanium coated black Kapton foil, black paint, aluminized tapes/low emissivity surface treatments, thermal doublers, interface fillers and thermal washers.
• Active Thermal Control Design: The two heater systems in the payload are named HM and HS (Figure 5).
- Electrical resistance heaters (HM in Figure 5) are installed on thermal doublers, on CMN Units and on segments structure and they are powered through CMN commands. This heater system is used to control the electronic equipment temperature in the instrument measurement/calibration modes and in PLM Off modes.
- The HS heaters (Figure 5) are installed on thermal doublers, on CMNs, on CCU, on X-band transmitter, on pyro unit, and on Lower Platform Optical Splitter. The HS heaters are powered from Proteus and controlled by thermostats. This heater system is used to keep equipment temperatures above the minimum non-operational limits (–20 ºC for most of the units) during satellite SHM and PLM Off modes. The system is fully redundant.
The TCS, as well as the rest of the payload design, has a distributed architecture. The central computer of the payload controls in closed loop remotely distributed units (12 in total) named CMN (Control and Monitoring Node) units. Each CMN unit acquires the telemetry of the temperature sensors (6 per heater line) for the heater control lines distributed in the Arms and in the Hub. The TCS is enabled during all payload operational modes including measurement and calibration.
Launch: The SMOS spacecraft was launched on November 2, 2009 on a Rockot launch vehicle (the 3rd stage of Rockot is Breeze-KM) of ELS (Eurockot Launch Services) from the Plesetsk Cosmodrome, Russia. The first burn of Breeze-KM is to acquire an elliptical transfer orbit. The second burn serves to circularize the orbit to its nominal parameters. A secondary payload on this flight is the PROBA-2 spacecraft of ESA. 25) 26) 27)
Some 70 minutes after launch, SMOS successfully separated from the Rockot's Breeze-KM upper stage. Shortly thereafter, the satellite's initial telemetry was acquired by the Hartebeesthoek ground station, near Johannesburg, South Africa. The upper stage then performed additional maneuvers to arrive at a slightly lower orbit and PROBA-2 was released too, some 3 hours into flight.
Note: The SMOS satellite has been in storage at Thales Alenia Space's facilities in Cannes, France since May 2008 awaiting for a third stage of the Rockot launcher to be assigned to the mission and a slot given for launch from the Russian Plesetsk Cosmodrome. SMOS is the second of ESA's Earth Explorer missions to launch after the GOCE (Gravity field and steady-state Ocean Circulation Explorer), which was launched on March 17, 2009.
Orbit: Sun-synchronous polar orbit, mean altitude = 755 km, inclination =98.44º, local equator crossing time at 6:00 AM on ascending node maintained within ±15 minutes, period of 100 minutes. The repeat cycle is 23 days with a 3 day subcycle. 28)
RF communications: An onboard solid-state recorder has a capacity of 3 Gbit for payload and TT&C data. Standard TT&C S-band communications are used (the downlink data rate is 722.116 kbit/s with QPSK modulation; the uplink has a data rate of 4 kbit/s). The CCSDS protocol is used for TT&C support. - The TT&C station is located in Kiruna (Sweden), operated by CNES (mission operations at CNES). Science data acquisition is in X-band at a data rate of 18.4 Mbit/s, the ground station is located at Villafranca, Spain.
Figure 6: Artist's view of the SMOS flight configuration (image credit: ESA, AOES Medialab)
Figure 7: Artist's view of the deployed MIRAS payload (image credit: ESA-AOES Medialab)
• November 30, 2019: Since the saltiness of ocean surface waters is a key variable in the climate system, understanding how this changes is important to understanding climate change. Thanks to ESA's Climate Change Initiative, scientists now have better insight into sea-surface salinity with the most complete global dataset ever produced from space. 29)
- If you're a keen sea-swimmer, you may have noticed that the water can be saltier in some places than others. This is because the saltiness of the water depends on nearby additions of freshwater from rivers, rain, glaciers or ice sheets, or on the removal of water by evaporation.
- The salinity of the ocean surface can be monitored from space using satellites to give a global view of the variable patterns of sea-surface salinity across the oceans.
Figure 8: Global sea-surface salinity maps from ESA's Climate Change Initiative showing the difference for the same period in 2012 and in 2017. Note the differences in the spreading of the Amazon and Mississippi River plumes (image credit: ESA Sea Surface Salinity CCI)
- Unusual salinity levels may indicate the onset of extreme climate events, such as El Niño. Global maps of sea-surface salinity are particularly helpful for studying the water cycle, ocean–atmosphere exchanges and ocean circulation, which are all vital components of the climate system transporting heat, momentum, carbon and nutrients around the globe.
- A new and ongoing project for ESA's Climate Change Initiative (CCI) – a research program dedicated to generating accurate and long-term datasets for 21 Essential Climate Variables, required by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change – has generated the most complete global dataset of sea-surface salinity from space to date.
- "The project aims to make a significant improvement to the quality and length of the datasets available for monitoring sea-surface salinity across the globe," says Susanne Mecklenburg, head of ESA's Climate Office. "We are keen to see this new dataset used and tested in a variety of applications, particularly to improve our understanding of the fundamental role that oceans have in climate."
- The research team, led by Jacqueline Boutin of LOCEAN and Nicolas Reul of IFREMER, has merged data from three satellite missions to create a global timeseries that spans nine years, with maps produced every week and every month at a spatial resolution of 50 km.
- They used observations of brightness temperature to derive sea-surface salinity from microwave sensors onboard the SMOS, Aquarius, and Soil Moisture Active Passive satellite missions.
- Dr Boutin said, "By combining and comparing measurements between the different sensors, the team has been able to improve the precision of maps of sea-surface salinity by roughly 30%."
- Salinity measurements taken since the 1950s indicate that globally, the more saline areas of the ocean are becoming saltier, and the freshwater areas are becoming fresher. The data for this, however, are relatively coarse, taken by ships.
- It is only since the beginning of the 21st century that ocean floats called Argo have been installed, on average every 300 km, to provide subsurface salinity vertical profiles between approximately 5 m and 2000 m depth at 10-day intervals.
- "Monitoring salinity from space helps to resolve spatial and temporal scales that are poorly sampled by in situ platforms that make direct observations, and fills gaps in the observing system," says Dr Boutin.
- Ocean–atmosphere exchanges are driven by winds around the globe, as well as by exchanges between the surface and subsurface ocean owing to changes in the density of the water itself. Water density depends on both temperature and salinity. Warm water is less dense than cold water, but salty water is denser than freshwater. At depth, ocean circulation is powered by differences in density between masses of water.
- Studying the global changes in salinity at the ocean surface can help climate scientists to model exchanges between the atmosphere and the ocean surface and between the ocean surface and the deeper ocean layers and predict change. Regional changes in salinity are linked to periodic inter-annual climate events such as the El Niño. Salinity is also implicated in the intensification of the global water cycle.
- To demonstrate the benefits of the new dataset, ESA's CCI Sea Surface Salinity project is carrying out a number of climate studies. These are focused on an improved understanding of the water cycle in the Bay of Bengal, an area prone to severe tropical cyclones, and in the Gulf of Guinea; on understanding the role of salinity on the stratification of the upper layer of the ocean and its effect on the air–sea exchanges; and on a climate variability reconstruction in the Atlantic that encompasses the recently-observed North Atlantic salinity anomaly.
- The team is currently working with climate scientists to compare the new dataset with in situ observations from Argo floats and ships, and with the output from models.
- The dataset is freely available for download from the CCI Open Data Portal.
• November 28, 2019: This week, the UN World Meteorological Organization announced that concentrations of greenhouse gases in the atmosphere have reached yet another high. This ongoing trend is not only heating up the planet, but also affecting the chemical composition of our oceans. Until recently, it has been difficult to monitor ‘ocean acidification', but scientists are exploring new ways to combine information from different sources, including from ESA's SMOS mission, to shed new light on this major environmental concern. 30)
- As the amount of atmospheric carbon dioxide continues to rise, our oceans are playing an increasingly important role in absorbing some of this excess. In fact, it was reported recently that the global ocean annually draws down about a third of the carbon released into the atmosphere by human activities.
- While this long-term absorption means that the planet isn't as hot as it would be otherwise, the process is causing the ocean's carbonate chemistry to change: seawater is becoming less alkaline – a process commonly known as ocean acidification.
- In turn, this is altering bio-geo-chemical cycles and having a detrimental effect on ocean life.
Figure 9: Figure 10: Sea butterfly: Ocean acidification is altering bio-geo-chemical cycles and having a detrimental effect on ocean life. Pteropods, tiny marine snails known as ‘sea butterflies', are an example of a particularly vulnerable species, where shell damage has been observed already in portions of the Arctic and Southern Ocean. Pteropods are hugely important in the polar food web, serving as a key food source for important fisheries species, such as salmon and cod (image credit: NOAA)
- With the damaging effects of ocean acidification already becoming evident, it is vital that the current shift in pH is monitored closely. Covering over 70% of Earth's surface, ocean wellbeing also has a bearing on the health and balance of the rest of the planet.
- Recent advances in data capture have included state-of-the-art pH instruments on ships and floats, but we can gain a global view by taking measurements from space. However, at present there aren't any spaceborne sensors that can measure pH directly.
- The use of satellites has not yet been thoroughly explored as an option for routinely observing ocean surface chemistry, but a paper published recently in Remote Sensing of Environment describes how scientists are testing new ways of merging different datasets to estimate and ultimately monitor ocean acidification.
Figure 11: The changing chemistry of our oceans: As carbon dioxide builds up in the atmosphere, increasing amounts of carbon are entering the world's oceans, which is changing the chemical balance of seawater and leading to ocean acidification. Marine chemistry can be studied using four parameters: partial pressure of carbon dioxide in the water; dissolved inorganic carbon; alkalinity; potential of hydrogen (pH). Two of these parameters, along with measurements of salinity and temperature, allow us to understand the complete carbon chemistry of the ocean. Salinity and temperature can be detected from space by their effect on electromagnetic emissions from the ocean surface. ESA's SMOS mission provides information on ocean salinity – a key piece of the puzzle (video credit: ESA/Planetary Visions)
- The animation of Figure 11 illustrates how marine chemistry can be studied using four parameters: partial pressure of carbon dioxide in the water, dissolved inorganic carbon, alkalinity and pH. Any two of these parameters, along with measurements of salinity and temperature, allow us to understand the complete carbon chemistry of the ocean.
- ESA's SMOS mission and NASA's Aquarius mission, which both provide information on ocean salinity, have been key to the research. The work was made possible through access to thousands of collated and quality controlled measurements collected by the international community from ships and research campaigns.
- Lead author, Peter Land, from the Plymouth Marine Laboratory, UK, said, "The advent of salinity measurements from space, pioneered by SMOS, has opened up the exciting possibility of continuously monitoring the ocean carbonate chemistry, identifying areas most at risk, and helping us to understand this threat to our oceans."
- Jamie Shutler, from the University of Exeter, UK, added, "We were able to carry out this research through ESA's Earth Observation Science for Society program. We hope that the view from space can be used to help understand how ocean acidification is likely affecting our fisheries and marine ecosystems, on which we rely for food, health and tourism."
- This work is now being continued within the ESA's Ocean SODA (Satellite Oceanographic Datasets for Acidification) project as part of the ESA Ocean Science Cluster.
• November 4, 2019: As ESA's SMOS satellite celebrates 10 years in orbit, yet another result has been added to its list of successes. This remarkable satellite mission has shown that it can be used to measure how the temperature of the Antarctic ice sheet changes with depth – and it's much warmer deep down. 31)
Figure 12: Antarctica is fifth in size among the world's continents. Its landmass is almost wholly covered by a vast ice sheet. The continental ice sheet contains approximately 29 million km3 of ice, representing about 90 percent of the world's total. The average thickness is about 2.45 km (image credit: Pixabay)
- The Antarctic ice sheet is, on average, about 2 km thick, but in some places the bedrock is almost 5 km below the surface of this huge polar ice cap.
- Most of us would probably think that the temperature of ice, no matter how thick, remains pretty much the same throughout: basically very cold.
- However, although the surface of the ice sheet is cold, the temperature increases with depth primarily because of the basal geothermal heating from beneath Earth's crust. In places, it is warm enough to melt the ice, which accounts for the presence of lakes and a vast hydrological network at the bedrock.
Figure 13: ESA's SMOS mission has been used to show how the temperature of the Antarctic ice sheet changes with depth. The image shows how the ice is colder (blue) at the surface but warmer (red) at the base. Temperature is one of the things that determines how ice flows and slides over the bedrock beneath. In turn, this flow affects the temperature profile through strain heating – so it's a complicated process. Temperature information is also fundamental for understanding the presence of aquifers inside or at the bottom part of ice sheets. This can be relevant for indicating the presence of sub-glacial lakes, for example, which in turn influence ice-sheet dynamics (image credit: ESA/Planetary Visions)
- Nevertheless, there is little accurate information on exactly how temperature varies with depth other than from ice core borehole locations.
- Since the massive white ice sheets that blanket Antarctica and Greenland reflect incident solar radiation back out into space, they are extremely important regulators in the climate system and, therefore, play a key role in the health of our planet.
- But, ice sheets are also victims of climate change. For example, this year scientists discovered that warming ocean waters have caused the ice to thin so rapidly that a quarter of the glacier ice in West Antarctica is now unstable.
- With melting ice sheets largely responsible for rising sea levels, which, in turn, threaten hundreds of millions of people around the world, it is vital that more is understood about how temperature influences ice-sheet dynamics.
- Satellite data are used, in particular, to measure changes in the height of ice sheets and consequently their ‘mass balance', where the ice sheet ends and the floating ice shelves begin – their grounding lines, their surface temperature and how fast ice streams flow.
- However, temperature is one of the things that determines ice viscosity and how ice flows and slides over the bedrock beneath. In turn, ice flow affects the temperature profile through strain heating – so it's a complicated process.
Figure 14: Antarctica's internal temperature. Temperature is one of the things that determines ice viscosity and therefore how ice sheets flow and slide over the bedrock beneath. In turn, this flow affects the ice-sheet temperature profile through strain heating – so it's a complicated process. Information on temperature is also fundamental for understanding the presence of aquifers inside or at the bottom of ice sheets. This can be relevant for indicating the presence of sub-glacial lakes, for example, which in turn influence ice-sheet dynamics. ESA's SMOS satellite mission has shown that it can be used to measure how the temperature of the Antarctic ice sheet changes with depth (image credit: IFAC)
- Temperature information is also fundamental for understanding the presence of aquifers inside or at the bottom part of ice sheets. This can be relevant for indicating the presence of sub-glacial lakes, for example, which, in turn, influence ice-sheet dynamics.
- How temperature varies according to the depth of the ice is not something that could be measured from space until now – but according to a paper published recently in Science Direct, SMOS is opening up new opportunities to do so. 32)
- Giovanni Macelloni from the Institute of Applied Physics ‘Nello Carrara' of the National Research Council (IFAC-CNR) in Italy, said, "We typically get ice-sheet temperature profiles from models, or from in situ measurements taken in boreholes – but these are obviously fairly sparse."
- Information on temperature from space has, so far, been limited to the surface or just below the surface from thermal-infrared sensors and microwave sensors.
- The researchers from IFAC-CNR and the Institute of Environmental Geosciences in France, therefore used ESA's SMOS satellite to see if there is a way of gaining this information rather than relying on models and boreholes.
- "We combined SMOS' L-band passive microwave observations over Antarctica with glaciological and emission models to infer information on glaciological properties of the ice sheet at various depths, including temperature," continued Dr Macelloni.
- "With temperature playing such an important role in ice-sheet dynamics, we are happy to say that our research, when compared with models, shows a better estimation of temperature increase with depth, with the largest differences close to the bedrock. -SMOS is clearly opening up more possibilities that we ever thought when it was launched 10 years ago."
• October 31, 2019: SMOS has been in orbit for a decade. This remarkable satellite has not only exceeded its planned life in orbit, but also surpassed its original scientific goals. It was designed to deliver data on soil moisture and ocean salinity which are both crucial components of Earth's water cycle. By consistently mapping these variables, SMOS is not only advancing our understanding of the water cycle and the exchange processes between Earth's surface and the atmosphere, but is also helping to improve weather forecasts and contributing to climate research as well as contributing to a growing number of practical everyday applications. 33)
Figure 15: SMOS 10 year in orbit (video credit: ESA)
• August 2019: The SMOS satellite was launched on 2 November 2009, and it is the ESA second Earth Explorer Opportunity mission. After almost 10 years of successful Operations, the status of the SMOS mission is excellent. However, SMOS observations are significantly affected by RF interference (RFI) in several world areas. 34)
- Since the first SMOS mission observations, its radiometer in the passive band 1400-1427 MHz detected RFI sources. Any emission in this band is prohibited by ITU Radio-Regulations (RR No.5340). To successfully accomplish the decrease in the global number of interfering sources, two parties are required: SMOS RFI team – to detect, monitor and report the cases of harmful interference – and national regulatory authorities – to investigate and take remedial actions to solve the RFI case (i.e. remove unauthorized devices, fix malfunctioning equipment or optimize operational settings). Some examples of devices causing interference are presented in this paper, showing the impact on the SMOS science data according to the topology of the interfering device.
Worldwide RFI Status
- As the SMOS satellite measures the brightness temperature (BT) in the surface of the Earth, the detected RFI sources are classified in three levels: moderate, strong and very strong sources.
Figure 16: Number of active RFI per Region and Strength (Nov. 2018), image credit: ESA, CNES
- In Europe, North America and China, the improvement in the RFI scenario between 2010 and nowadays is mostly a consequence of the actions taken by spectrum management national authorities following the RFI reports provided by ESA. In other areas such as Middle-East and Southern-Asia, it can be observed a quite dynamic scenario of the RFI emissions that are switched on/off without any specific reporting action initiated by ESA. 35)
- Taking into account the science pixels affected due to the interfering signals, the improvement is clear, especially during the early years of the SMOS mission, as extremely powerful sources were detected and switched off, cleaning large areas of polluted data as it can be seen in Figure 17. 36)
Figure 17: Evolution of RFI detection over land (% of pixels affected), image credit: ESA, CNES
- During these years, the SMOS RFI team has found several types of interference sources according to their topology, power and behavior. 37). They can be broken down by intensity: high power (a) vs low power (b); by emission features: omnidirectional (c) vs directive (d) vs pulsed (e) probably scanning beam; or by spatial distribution: extended (f) vs isolated (g). Three types of RFI sources have been detected in the purely passive band 1400-1427 MHz: (a) In-band emissions from either unauthorized or malfunctioning equipment, (b) Excessive out-of-band emissions from radar systems operating in the lower adjacent band, and (c) spurious emissions (intermodulation, harmonic and parasitic emissions) from devices operating in the upper adjacent band.
(a) Intensity: Very strong power emitters
- Very strong emitters (BT>5000 K) are the most damaging sources to science data, some of which achieving more than 1 million Kelvin manage to blind the entire instrument of the satellite, allowing large parts of data to be polluted (Figure 18, right). When the interfering source is close to the sea, it causes the same annoying effects on the SMOS ocean products, polluting large areas of ocean data (Figure18, left).
Figure 18: Effects of a very strong source in Indian Ocean March 2018 (left) and another in central Europe September 2017 (right), image credit: ESA, CNES
(b) Intensity: Moderate power emitters
- Although some interfering devices transmit with a low power (<1 W) within 1400-1427 MHz band, they are perfectly observed by the instrument, reaching a brightness temperature up to 1000 K. This low power makes geolocation by SMOS difficult as well as its location in the field. In some cases, the cause of the interfering signal is a leak in poorly isolated RF equipment, making it even more difficult to locate the source. In the following figures (Figures 19 and 20) an interfering television amplifier due to poor filtering is shown next to its observation on a SMOS Level-1 Land map.
Figure 19: Interfering television amplifier due to poor filtering after removing it (image credit: FCC United States)
Figure 20: US012 source (TV amplifier) Brightness Temperature observation on 2017-04-07 (image credit: ESA)
(c) Emission Pattern: Omnidirectional Antennas
- Omnidirectional antennas are observed in all the products of SMOS regardless of the direction of the passes. They are used for broadcasting applications, such as push-to-talk systems, TV/radio stations, etc. As an example, an interference was detected in Albania due to a TV/Radio broadcasting system (Figure 21).
- During measurements performed by Albanian authorities (AKEP Albania) by a spectrum analyzer in the band 1400-1427 MHz, resulted that source of interference was a broadcaster subject with audiovisual signal, "TV 6 + 1" and "Radio 6 + 1" which transmits analog TV and radio FM signal.
Figure 21: Measurements from transmission point of an interference due to a TV/Radio broadcasting system, frequency 1408.28 MHz, signal level -79 dBm (courtesy of AKEP Albania)
(d) Emission Pattern: Directional Antennas
- Considering the radiation pattern of the transmission device, we can distinguish the interfering directional antennas, by analyzing the differences between ascending and descending passes of SMOS. This type of sources is usually observed with different powers in the ascending and descending passes. In the ideal case, when the direction of the antennas is aligned with the satellite direction, they are observed in one direction, while not in the other.
- These types of sources are usually terrestrial radiolinks with different objectives: wireless CCTV cameras (Figure 22), point-to-point communication networks, data transmission systems, etc.
Figure 22: Detected interfering wireless audio/video transmitter used as part of a CCTV camera system (courtesy of FCC United States)
(e) Emission Pattern: Pulsed signals
- The most common sources of this kind are radars with excessive unwanted emission levels and they are very difficult to improve. Unwanted emissions limits to maximum levels are defined in RR Res.750 (rev WRC-15). They are easy to locate from space (<1km error) and also in the field. As they are usually very powerful sources, the impact on SMOS data is very harmful. An example of a pulse-shaped signal in the time domain is shown in Figure 23.
Figure 23: Interfering radar located by SMOS interference algorithms (top). Pulsed signal seen by SMOS in the time domain (bottom), image credit: ESA
(f) Spatial Distribution: Extended areas
- Regardless of their power, large areas of extended sources are observed in some urban zones. This distribution of interferences makes it very difficult to locate each source, since they could overlap each other and it is impossible to know exactly how many devices are interfering. In the following figures, several cases can be observed: Japan, where multiple low-power emitters create a large area of interference, and South Korea, where a mixture of powerful and weak emitters composes an area of overlapped interferences (Figure 24); and Moscow, where more than four powerful emitters blind its entire urban area (Figure 25).
Figure 24: Korea and Japan RFI probability map in April 2019 (image credit: ESA)
Figure 25: SMOS brightness temperature map over Moscow (image credit: ESA)
- Summary: The experience of SMOS with radio frequency interference these ten years shows that it is essential to protect the passive band 1400–1427 MHz from both illegal and excessive unwanted emissions. ESA and the SMOS RFI teams have devoted considerable resources to the detection and reporting of interference cases worldwide, with the associated impact in cost, manpower and definition of RFI processes. Important efforts have also been dedicated to increasing awareness about the negative impact of RFI in the scientific observations and about the importance to reinforce the ITU Radio Regulations at national level. It is necessary to emphasize that most of the interfering sources are due to excessive unwanted emissions from radars and TV/video transmitters in adjacent bands, and also to in-band unauthorized equipment (typically low-cost surveillance cameras). As shown in this paper, it is not necessary to emit too much power to pollute the science data of a satellite radiometer such as that of SMOS, and this pollution is equally impacting other types of science instruments such as radar satellites or radio telescopes. This is the reason why the 1400-1427MHz band is purely passive and the Radio-Regulation prohibit all emissions in the band (like other bands in other parts of the spectrum) and this is why all the involved parties have to be very careful not to transmit in these frequencies.
• June 12, 2019: As of 11 June 2019, measurements from ESA's SMOS mission are being fully integrated into ECMWF's forecasting system, allowing for a more accurate description of water content in soil. 38)
- Since its launch in 2009, ESA's SMOS (Soil Moisture and Ocean Salinity) mission has been providing global observations of emissions from Earth's surface, particularly soil moisture and ocean salinity – two important variables in the water cycle.
- Accurate weather forecasts are paramount for both commercial and leisure activities. The ECMWF (European Centre for Medium-Range Weather Forecasts) is the leading agency to provide global accurate weather forecasts. Its IFS (Integrated Forecasting System), a gigantic numerical weather prediction model, provides weather predictions 24 hours a day, seven days a week.
- Patricia de Rosnay, the Coupled Assimilation team leader at ECMWF comments that, "When using SMOS measurements in our operational forecasting system, we get a better description of the spatial distribution of the water in the soil.
- "These are important measurements to understand the complex interactions between the land surface and the atmosphere, which is crucial for our forecasting system."
- The weather is a complex process and a good prediction largely depends on the knowledge of Earth's atmosphere provided through a variety of observations from satellites, in situ data, balloons, buoys and other observing systems.
Figure 26: Weather forecast impact. The plots show the normalized error difference of the 2m air temperatures between the new and old forecasting systems, where negative values indicate an error reduction owing to the use of SMOS data. In summer 2017, a positive impact is statistically significant for the Northern Hemisphere, as seen in the right plot (image credit: ECMWF)
- These data need to be available fast in order to be beneficial for predictions. Producing geophysical soil-moisture measurements takes around eight hours after sensing.
Figure 27: Global soil moisture distribution. Mean soil moisture distribution for June, July and August 2017. The mean was computed from swath-based soil-moisture generated by the ‘neural network' in Near-Real-Time at ECMWF (image credit: ECMWF)
- A clever technique used to accelerate the production of these data is machine learning, for example using an artificial ‘neural network', which computes values of soil moisture from the satellite within seconds. It was adapted by CESBIO and LERMA to generate the information needed for operational forecasts.
- "Machine learning techniques are computationally efficient and are very fast tools to process large datasets quickly. Using neural networks was the key for the integration of SMOS measurements in time for the weather forecast," says Nemesio Rodriguez-Fernandez from CESBIO, and who designed and trained the neural network prior to the operational integration done by ECMWF.
- Using measurements from an Earth explorer satellite in 24/7 operations is a major achievement. So far, only SMOS measurements over land are being used to support general weather forecasts. Considering SMOS provides information in all weather conditions, SMOS also delivers new information for tracking hurricanes and measuring thin sea ice.
- In the future, the information provided by SMOS over oceans and the polar regions may also be used in combination with Earth-system models and data assimilation systems.
- ESA's SMOS mission scientist, Matthias Drusch, said, "Integrating SMOS measurements into ECMWF's forecasting system has been a major endeavor that started more than 15 years ago. This success story shows how models and even operational applications benefit from new observations."
- So far, SMOS is the only Earth explorer satellite providing measurements operationally for global medium-range weather forecasts. Currently, data from ESA'S Aeolus mission are being tested at ECMWF for operational forecasting system to be used in the near future.
Figure 28: Future potential use of SMOS. SMOS can potentially help in the future for the Copernicus Emergency and Management Service (CEMS), specifically for research and development related to the European Forest Fire Information System, SMOS measurements can be used to identify ignition potential, the available fuel for burning, and the modulation of fire emissions. For flood forecasting within the European Flood Awareness System (EFAS), SMOS can be used to assess the flood susceptibility (image credit: ECMWF)
• May 14, 2019: The length and precision with which climate scientists can track the salinity, or saltiness, of the oceans is set to improve dramatically according to researchers working as part of ESA's Climate Change Initiative. — Sea-surface salinity plays an important role in thermohaline ocean circulation. 39)
Figure 29: The most precise sea-surface salinity global dataset to date. Spanning nine years, the dataset is based on observations from the three satellite missions that measure sea-surface salinity from space - SMOS, SMAP and Aquarius (image credit: ESA–CCI)
- The research team, led by Jacqueline Boutin of LOCEAN (Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques) and Nicolas Reul of Ifremer, have generated the longest and most precise satellite sea-surface salinity global dataset to date.
- Spanning nine years, the dataset is based on observations from the three satellite missions that measure sea-surface salinity from space: ESA's SMOS and the US SMAP and Aquarius missions.
- "By combining and comparing measurements from the missions' various radiometers, the precision of sea-surface salinity maps is improved by roughly 30% thanks to the increased number of measurements and reduced inter-calibration error," comments Dr Boutin.
- The research project forms part of ESA's Climate Change Initiative, a program focused on generating global, long-term satellite-derived data products for 22 essential climate variables.
- Based on 40 years of empirical observations from space, the initiative supports the United Nations Framework Convention on Climate Change and Intergovernmental Panel on Climate Change – the bodies that assess and synthesize scientific evidence into information for policy and decision-makers.
- Sea-surface salinity is linked directly to density-driven ocean circulation patterns that transfer heat from the Tropics to the poles. Regional changes are also linked to periodic interannual climate events such as El Niño.
- Salinity is implicated in the intensification of the global water cycle. Measurements of sea-surface salinity and sea-surface temperature, which determine the thickness of the surface mixed layer, have the potential to help understand the development of extreme weather events such as cyclones.
- Salinity measurements taken since the 1950s indicate global trends of saline areas of the ocean becoming saltier, and freshwater areas becoming fresher. The data for this however, is relatively coarse, as it is taken from ships. Only since the beginning of the 21st century has a fleet of ocean buoys, called Argo, provided subsurface-salinity measurements.
- According to Dr Boutin, "Monitoring salinity from space helps to resolve spatio-temporal scales that are not adequately sampled by in-situ platforms and fills gaps in the observing system.
- The team is currently working with climate scientists to compare this observational dataset with in-situ datasets and the output of models. This checks that the models are operating effectively and helps to refine and improve performance.
- To demonstrate the benefit of the new data, the project will use the new salinity data in a number of climate investigations to improve the understanding of the water cycle in the Bay of Bengal, an area prone to severe tropical cyclones.
- It will allow scientists to understand the role of salinity on the stratification of the upper layer of the ocean and air-sea exchanges.
• May 14, 2019: Just within the last couple of months, Cyclones Fani, Idai and Kenneth have brought devastation to millions. With the frequency and severity of extreme weather like this expected to increase against the backdrop of climate change, it is more important than ever to forecast and track events accurately. And, an ESA satellite is helping with the task in hand. 40)
- Soon to celebrate 10 years in orbit, SMOS was built to measure soil moisture and ocean salinity to better understand the water cycle. While science benefits from its measurements, the SMOS portfolio is being expanded to help with some everyday applications that include monitoring and improving forecasting of large storms.
- The problem with observing hurricanes and cyclones from space is that satellite's carrying camera-like instruments cannot see through masses of thick spinning cloud to measure wind speeds.
Figure 30: SMOS measuring storms. With the frequency and severity of extreme storms expected to increase against the backdrop of climate change, it is more important than ever to forecast and track events accurately. SMOS carries a microwave sensor to capture images of brightness temperature. These images correspond to radiation emitted from Earth's surface, which are then used to collect information on soil moisture and ocean salinity. Strong winds over oceans whip up waves and whitecaps, which in turn affect the microwave radiation from the surface. This means that although strong storms make it difficult to measure salinity, the changes in radiation can, however, be linked directly to the strength of the wind over the sea. Working together, ESA, OceanDataLab and Ifremer have started a SMOS wind data service, which provides near-realtime ocean-surface wind speeds. The services has been pre-operational since September 2018, providing data to selected users such as the NOAA National Hurricane Center, the U.S. Naval Research Laboratory and the Joint Typhoon Warning Center who are assessing the potential benefits (video credit: ESA/Planetary Visions)
- Traditionally, satellite scatterometer instruments have been the main source of information to measure wind speed over ocean waters, but SMOS can offer additional information when storms are severe.
- SMOS carries a microwave radiometer to capture images of brightness temperature. Measurements correspond to radiation emitted from Earth's surface, which are then used to derive information on soil moisture and ocean salinity.
- Strong winds over oceans whip up waves and whitecaps, which, in turn, affect the microwave emission from the surface. This means that the changes in radiation can be linked directly to the strength of the wind over the sea.
- Nicolas Reul, from Ifremer, said "While advances in our understanding of the physics underpinning the life cycle of tropical storms and their development into hurricanes and cyclones is advancing all the time, there is no substitute for improved measurement capability that can help define the character of a given storm.
- "Although SMOS data have a spatial resolution of 40 km, the wide-swath regular repeat coverage and ability to provide measurements of surface-wind speed structure at hurricane force in the presence of heavy precipitation is unique."
- The fact that SMOS can be used to estimate ocean-surface wind speeds in extreme weather has been known for a while – but as highlighted at this week's Living Planet Symposium, this is being put into practice.
- Experiments show that SMOS can, for example, help improve errors in forecast lead times by 36–72 hours in the extratropics.
- Working together, ESA, OceanDataLab and Ifremer have started a SMOS wind-data service, which provides near-realtime (3–6 hours from sensing) ocean-surface wind speeds.
- Since September 2018, the services has been ‘pre-operational', providing data to selected users such as the NOAA National Hurricane Center, the U.S. Naval Research Laboratory and the Joint Typhoon Warning Center who are assessing the potential benefits.
- The importance of this goes beyond the SMOS mission as the continuity of these kind of measurements is now being studied within the context of one of six a potential future Copernicus missions.
- ESA's Craig Donlon, explains, "The Copernicus Imaging Microwave Radiometer concept is a global coverage mission, but with a focus on the rapidly changing Arctic region, where both high winds and salinity play a major role in the ocean system. - There is no doubt that SMOS has allowed us to explore and further develop the enormous potential of L-band microwave radiometer measurements for the ocean."
Figure 31: Ocean-surface winds from SMOS (in knots) under Cyclone Idai on 13 March 2019. The wind radii estimates in each geographical storm quadrant are illustrated by black segments as deduced from SMOS data and by grey segments for the Automated Tropical Cyclone Forecast system. These line segments are terminated by blue, red and pink rectangles for wind radii of 34, 50 and 64 knots, respectively. The storm center tracks and direction are indicated by thick black curves with arrows (image credit: Ifremer)
• November 2018: ESA in collaboration with OceanDataLab (ODL) and IFREMER has started the implementation of a SMOS wind data service, which will provide, in near real time (3-6 hours from sensing), ocean surface wind speeds derived from SMOS data. The service is now pre-operational and has been tested with some expert users such as: the NOAA National Hurricane Center, the U.S. Naval Research Laboratory (NRL) and the Joint Typhoon Warning Center (JTWC) in order to assess potential benefit to use SMOS wind data for operational storm forecasting. First feedback from these operational users has been very positive. 41)
• September 25, 2018: With recent events in the news about the devastation brought by hurricanes and typhoons to the US and Asia, we are reminded of how important it is to predict the paths of these mighty storms and also learn more about how they develop. Many satellites have eyes on storms, but ESA's SMOS mission can offer an entirely new perspective. 42)
- Tracking and forecasting hurricanes across the ocean brings obvious benefits to those at sea and to those who live in places where they make landfall. While forecasters have excellent tools to hand to make these predictions, ESA's Soil Moisture and Ocean Salinity (SMOS) mission is now ready to add valuable information to help make these predictions even more accurate.
- SMOS was built for scientific research, mainly into Earth's water cycle. The satellite carries a novel microwave sensor to capture images of ‘brightness temperature'. These images correspond to radiation emitted from Earth's surface, which are then used to collect information on soil moisture and ocean salinity.
- Strong winds over oceans whip up waves and whitecaps, which in turn affect the microwave radiation from the surface. This means that although strong storms make it difficult to measure salinity, the changes in radiation can, however, be linked directly to the strength of the wind over the sea.
- The mission has a real advantage over satellites that carry optical images, which cannot see though the thick cloud of a hurricane, for example. Effectively, seeing through the storm, SMOS can deliver unique information on the speed of the wind near the sea surface at the base of the storm.
- While scientists have known how SMOS can do this for a few years now, the mission is now being tested to see if it can supply this information for operational hurricane services.
- Recently, SMOS has been used to image and track the wind under Hurricane Florence, Typhoon Mangkhut and Typhoon Jebi.
Figure 32: Wind speeds at the base of Hurricane Florence near the US measured by ESA's SMOS mission on 10 September 2018. The SMOS microwave radiometer MIRAS, which operates in the L-band, has the unique ability to see through clouds and rain to provide reliable estimates of surface wind speeds in intense storms (image credit: Ifremer)
Figure 33: Wind speeds at the base of Typhoon Mangkhut near the Philippines measured by ESA's SMOS mission on 14 September 2018. The SMOS microwave radiometer MIRAS, which operates in the L-band, has the unique ability to see through clouds and rain to provide reliable estimates of surface wind speeds in intense storms (image credit: Ifremer)
Figure 34: Wind speeds at the base of Typhoon Jebi near Japan measured by ESA's SMOS mission on 2 September 2018. The SMOS microwave radiometer MIRAS, which operates in the L-band, has the unique ability to see through clouds and rain to provide reliable estimates of surface wind speeds in intense storms (image credit: Ifremer)
- Buck Sampson from the US Naval Research Laboratory said, "ESA's SMOS mission can give us really interesting new information for operational storm forecasting, which we hope to use along with our traditional sources of data. SMOS measurements can help us keep track of the structure of a dangerous storm. Combining SMOS data with that from its US counterpart SMAP mission, will give us more timely information which is essential for monitoring major storms."
- Susanne Mecklenburg, ESA's SMOS mission manager, added, "While SMOS is still delivering important information to further our scientific understanding of Earth, it will be really exciting to see it being used for practical applications once this testing phase finishes at the end of the year. Every year, hurricanes bring misery to many people around the world, so the hope is that SMOS will be useful to make better predictions, and ultimately help decision-makers with their damage mitigation strategies."
• August 23, 2018: SMOS online Science data are now freely available on the SMOS Online Dissemination Service, without needing to take additional registration steps to access the data. Products can be openly searched and browsed, but login with an ESA EO-SSO account is required in order to download files. This applies also to users already registered to SMOS data. — Additional information on the available SMOS data and how to access them can be found in the SMOS Data Access page. 43)
• July 2018: ESA's SMOS (Soil Moisture and Ocean Salinity) mission has been in orbit for over 8 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions is working well. The data for this whole period has been and is being processed with the operational version of the current Level-1 processor (version v620). Also a representative part of the same data set has been processed with a working version of a new processor (v720) which is now in preparation so that homogenous records of brightness temperatures have been made available. These rich and long data records have allowed learning important lessons from the in-flight experience, and shall eventually lead into the consolidation of the new Level-1 processor version (v720) with its corresponding auxiliary calibration and configuration files. Once the improvements are confirmed the new processor version shall be recommended for the operational chain. 44)
- The over 8 year flight experience of SMOS is very valuable for the definition of future L-band missions, in particular but not only, when considering an interferometric radiometer. The lessons learnt tell us how SMOS could be improved to attain better sensitivity, spatial resolution, swath (coverage or revisit time), robustness against RFI and stability. The improvements include system parameters such as element spacing or array geometry, subsystem improvements at all levels (antenna, receiver, harness and correlator), as well as calibration approaches and image reconstruction. In summary, the SMOS experience could be used to define a cost effective SMOS follow on mission.
• July 2018: The SMOS instrument MIRAS is operating nominally with the exception of some known on-board anomalies described in the MIRAS anomaly document. The cumulative data loss due to MIRAS instrument unavailability since the beginning of the routine operational phase (May 2010) amounts to 0.09% and the degraded data amounts to 0.60% (Figure 35). No data loss has occurred during the acquisition of MIRAS raw data at the ground stations since the beginning of the routine operational phase (May 2010). This result has been achieved by implementing an on-board data recording overlap strategy. 45)
Figure 35: SMOS mission data availability percentage since May 2010. Instrument data availability is extremely high, about 99%. Only 0.09% of data is lost due to MIRAS anomalies (image credit: SMOS FOS/ESA)
- Instrument calibration and data quality: Several on-board calibration activities are performed regularly and an overview of the calibration strategy implemented for the MIRAS instrument can be found in the SMOS calibration summary document. During calibration activities science data are not generated, therefore data users should consult the calibration plan for expected data unavailability.
- Radio Frequency Interference (RFI): Active RFI sources are continues monitored in term of intensity and geographical distribution as illustrated in Figure 36 and Figure 37. Information about the evolution of the RFI contamination can be found on the frequently updated RFI probability maps for land surfaces, generated fortnightly by CESBIO and available on the SMOS blog (http://www.cesbio.ups-tlse.fr/SMOS_blog/smos_rfi/).
Figure 36: Worldwide number of active RFI sources per continent and intensity in May 2018 (image credit: SMOS RFI team at ESA/ESAC)
Figure 37: Map of Europe showing the probability of SMOS persistent RFI occurrences during the period 17-31 May 2018 (image credit: SMOS RFI team at ESA/ESAC)
• April 11, 2018: A new methodology using a combination of debiased non-Bayesian retrieval, DINEOF (Data Interpolating Empirical Orthogonal Functions) and multifractal fusion has been used to obtain 6 years of SMOS SSS (Sea Surface Salinity) fields over the North Atlantic Ocean and the Mediterranean Sea. This product has been developed by the Barcelona Expert Center and the GHER (GeoHydrodynamics and Environment Research) group at University of Liège (Belgium), under the ESA STSE project "SMOS sea surface salinity data in the Mediterranean Sea (SMOS+ Med)". SMOS+ Med was lead by Dr. Aida Alvera-Azcarate, from GHER. 46) 47)
Figure 38: ESA's SMOS mission has been used to show how the saltiness of the western Mediterranean has varied over six years (image credit: ESA, SMOS SSS Team)
• September 2017: Current operations have been extended to 2019 and beyond, pending an extension review in 2018. CNES is reviewing the mission operations extension beyond 2017. Future data products include severe wind speed over oceans and freeze/thaw information over land. There has been a decrease in radio frequency interference, in particular over Europe, with more than 70% of sources being switched off. 48)
• September 5, 2017: Despite the welcome showers at the weekend, abnormally low soil-moisture conditions persist in central Italy (Figure 40). Scientists are using satellite data to monitor the drought that has gripped the country. - Wildfires, water scarcity and billions of euros worth of damage to agriculture are just some of the effects of this summer's drought in Italy – not to mention the relentless heat. News of potential water rationing in the capital have even made headlines worldwide. As local authorities work to mitigate the drought, scientists are turning their eyes to the sky for answers. 49)
- Satellite data on soil moisture show that soils in southern Tuscany have been drier than normal since December 2016. Even though drier than normal conditions occur regularly, the current situation is uniquely intense and persistent, similar to the droughts in 2007 and 2012.
- "In the first six months of 2017, we saw less than half of average rainfall in central Italy," said Luca Brocca from Italy's Research Institute for Geo-Hydrological Protection, of the National Research Council (IRPI-CNR). "The combination of low rainfall and high temperatures has led to drought, and we will need a significant amount of rainfall to replenish the water lost in the last eight months."
- "The combination of low rainfall and high temperatures has led to drought, and we will need a significant amount of rainfall to replenish the water lost in the last eight months."
- IRPI-CNR is closely monitoring the drought situation using a new, long-term and globally available near-real time extension of the satellite soil-moisture dataset from ESA's Soil Moisture CCI (Climate Change Initiative) project. The dataset has been developed by the Vienna University of Technology TU Wien and the Dutch company VanderSat B.V. and will soon be made available through the Copernicus Climate Change Service.
Figure 39: Italy soil moisture anomalies (image credit: C3S/ECMWF/TU Wien/VanderSat/EODC/AWST/Soil Moisture CCI)
Legend to Figure 39: Above-average (blue) and below-average (red) soil moisture for Italy from 1997 to 2017. Extremely low soil moisture was witnessed in 2003, 2013 and 2017. The data were compiled by ESA's Soil Moisture CCI project, and includes information from active and passive microwave sensors (such as those on the ERS, MetOp, SMOS, Aqua and GCOM-W1 satellite missions).
Figure 40: August 2017 soil moisture anomalies (image credit: C3S/ECMWF/TU Wien/VanderSat/EODC/AWST/Soil Moisture CCI)
Legend to Figure 40: Soil moisture in Italy during early August 2017 was particularly low in some areas (red). The data were compiled by ESA's Soil Moisture CCI project, and includes information from active and passive microwave sensors (such as those on the ERS, MetOp, SMOS, Aqua and GCOM-W1 satellite missions).
- Italy isn't the only country to have suffered from drought this summer: France and the Balkans have also been extremely dry – but central Italy exceeds the rest of Europe for abnormally low soil-moisture levels.
- Soil moisture data are collected by satellites measuring microwaves reflected or emitted by Earth's surface. The intensity of the measured signal depends on the amount of water in the soil. This information is important for improving short- and medium-term meteorological forecasting, as well as predicting hazardous events such as floods, droughts and heatwaves.
- Other spaceborne sensors can monitor effects of drought, such as the lowering water-levels in lakes. Some 30 km northwest of Rome, Lake Bracciano has seen a significant drop in water level. The receding shoreline is so prominent that it has become visible in optical satellite data. While this may mean more beach space for holidaymakers, it indicates a depleted supply of water for the Italian capital.
- Lake Bracciano's water level is closely monitored by local authorities but, in remote parts of the world, water levels of other large lakes can also be monitored by satellite radar altimeters, helping governments better manage water resources.
- Scientists will continue to use space-based tools to monitor drought conditions across Europe, as well as offer support to authorities dealing with water scarcity.
Figure 41: Parts of Italy's Lake Bracciano shoreline receded up to 60 m during the summer of 2017, as seen by the Copernicus Sentinel-2 satellite mission (image credit: ESA, the image contains modified Copernicus Sentinel data (2017), processed by ESA, CC BY-SA 3.0 IGO)
• July 2017: ESA's SMOS mission has been in orbit for over 7 years, with its MIRAS (Microwave Imaging Radiometer with Aperture Synthesis) instrumentation functioning well. This 7 year period has provided a wealth of information which has enabled us to understand and consolidate the performance of the payload in great detail. More importantly, we know now the things that work well, those that need improvement, and how the instrument could be enhanced if we were to build it again. 50)
The lessons learnt are being presented grouped into the following main headings:
1) RFI (Radio-Frequency Interference):
The 1400-1420 MHz band protected by the international Radio Regulations was found to be heavily polluted by illegal emissions in the band, by adjacent band emissions having strong leakage in band, as well as by unwanted emissions in the band due to faulty equipment mostly. Moreover a temporal, spatial and dynamic evolution of these sources around the world could be seen, their distribution and intensity changing over time.
A major effort was undertaken by ESA to switch off as many of these RFI sources as possible. Despite of the success in eliminating several hundreds of them, there are still as many which are active. A follow-on mission should be designed taking into account this fact and while continuing the effort in eliminating RFI sources, a new instrument would have to have RFI mitigation measures.
RFI mitigation can be dealt with at 3 levels, namely, array geometry and similarity, view geometry and on-board electronic counter-measures (similarly to NASA's Aquarius and SMAP missions).
2) Brightness Temperature (Level-1) over ocean:
SMOS ocean brightness temperature images are mainly affected by sensitivity, spatial ripple, temporal fluctuations (mostly orbital and seasonal), Sun tails, Sun in the back, Sun and galactic glint, and land-sea contamination. Each of these is underlined and addressed separately next.
The radiometric sensitivity of SMOS could be boosted by a factor 4 by widening the field of view of the sensor and the parallelizing receiver electronics. The spatial ripple present in the ocean images is currently removed through the so-called OTT (Ocean Target Transformation). This ripple is caused by a combined effect of aliasing, antenna pattern differences and brightness temperature outside the main field of view. Such spatial ripple could be reduced by making the antenna patterns more similar and decreasing the element spacing at the same time. A 50% reduction of the spatial ripple should be possible, pending of our ability to produce an array with the required antenna pattern similarity.
Ocean images present temporal fluctuations correlated with those experienced by the physical temperature of the antenna elements. For example there are some differences in the brightness temperature between ascending and descending passes along the orbit, and most noticeable, at the transitions into and out of the eclipse, the latter showing the most prominent effects. Two measures have been identified to reduce such thermally induced fluctuations, namely, a higher orbital altitude and an improved antenna design.
Sun tails are the side lobes of the point spread response of MIRAS at the position of the real Sun. The level of the Sun tails could be reduced by at least 10 dB, and the tails would be spaced further apart through the same techniques mentioned above to reduce the spatial ripple.
Sun in the back refers to the contamination of the Sun through the back lobes of MIRAS when the Sun is situated behind the antenna array. This contamination can be most effectively reduced by pointing the instrument nadir, this providing at least one out of 2 views of every pixel free of this Sun contamination per overpass.
Sun and galactic glint are produced by diffused scattering of their brightness temperature over the ocean or land surface. Typically the Sun glint is generated outside the extended alias-free region, but in very rough sea state conditions the Sun glint area can enter into the extended field of view. On the contrary, the galactic glint can happen within the alias-free or extended alias free field of views, depending on season and pass (ascending or descending). Both the Sun and the galactic glint effects can be minimized by pointing the instrument nadir, to enable two looks with different view angle geometry for every pixel, at least one of them with much reduced degradation.
Land-sea contamination is known to extend up to 1000 km from the coastlines in the current SMOS ocean images. A correction of this effect has only been possible at Level-2 thanks to the long data record, spanning over 7 years now. Land-sea contamination could be reduced at Level-1 by improving the synthetic beam efficiency and the use of the so-called ALL-LICEF mode with a 0.98 correction factor found experimentally.
3) Spatial resolution over land:
The spatial resolution of SMOS, 41 km at boresight, would need a major improvement to address much demanded hydrological applications at kilometer scale. There are several ways to approach this objective beyond the obvious one of enlarging the size of the instrument: through the array geometry and by synergistic use with SAR data.
An hexagon shaped array achieves a factor 1.22 better spatial resolution than a Y shaped array as SMOS for the same envelope. As an example, a 6.5 m diameter hexagon (thus smaller than the 8 m Y shape array of SMOS) flying at the same altitude as SMOS would achieve 33 km at boresight, better than SMOS. The spatial resolution performance could be further improved in proportion to the size of the array: an 8.5 m diameter hexagonal instrument would lead to 25 km at boresight (assuming the same altitude).
Even more drastic improvements in spatial resolution in the near future could result by overlapping the field of view with that from a SAR mission, as ESA's Sentinel-1 (this SAR operates at C-band; in the future there might even be a SAR mission working at L-band). That would allow using pixel disaggregation techniques resulting in highly improved spatial resolution by data combination.
4) Calibration strategy:
These are a number of areas of the calibration system of MIRAS where potential improvements have been identified: removal of the NIR (Noise Injection Radiometer) units, centralization of the calibration of the phase of the LO (Local Oscillators), reduction of the temporal fluctuations in the offset of the detector outputs, removal of the effect of heater status on the detector outputs and centralization of the noise injection for phase calibration. Each of these topics is discussed below.
Removal of the NIR units. Before the launch of SMOS, it was considered critical to measure the antenna temperature accurately and without temporal fluctuations. Therefore it was decided to launch 3 Noise Injection Radiometers for this purpose. The in-orbit experience has shown that the average of the antenna temperature of the 66 LICEF (Lightweight Cost-Effective Front-end) total power receivers is as stable, if not more, than that provided by the NIR units. The NIR units could thus be removed, resulting in a major simplification at both, overall instrument design (all receivers of a single type: the LICEF), but more importantly, in calibration strategy (the LICEF would be directly calibrated using the Cold Sky external maneuvers together with their internal matched load) and operations (much simplified calibration commands).
Better calibration of the LO phase. The LOs in SMOS are located inside the CMN (Control and Monitoring Node) units. There is one CMN unit per instrument segment (every arm, as well as the hub, has each 3 segments). The physical temperature of every CMN is controlled by a different part of the thermal control system, and hence the LO phases evolve independently of each other. The LO phase calibration requires periodic injections of correlated noise every 10 minutes to track their temporal evolution, this LO calibration being the most important contributor (1 %) to the total time spent in calibration (1.64%). Using LO parts less sensitive to physical temperature and having all LOs in the same box, i.e. using a centralized LO signal distribution, would allow spacing the LO calibrations to one quarter of the orbital period (25 minutes) if not removing their need entirely, reducing the total calibration time below 1%.
Temporal fluctuations in the detectors offsets. Rapid random changes in the offset of PMS (Power Measuring System) detectors of the LICEF receivers have been observed to happen. This has led to the need of introducing a weekly PMS offset calibration. Although the impact of such calibration is very limited (less than 0.02% of the total calibration time), such PMS offset fluctuations do affect the temporal stability of the ALL-LICEF mode. It is believed these PMS offset variations are mostly due to EMC (Electro-Magnetic Compatibility) effects within the LICEF receivers. Hence improving the EMC design of the PMS detectors and using voltage-to-frequency translation could mitigate those fluctuations greatly and improve the temporal stability of the ALL-LICEF mode.
Heater status impact on the detectors. The ON-OFF heater approach of the current thermal control in SMOS has been seen to affect the value of the LICEF PMS detector offsets, and moreover such effect depends on whether MIRAS is in calibration or in nominal observation mode. An exponential heater correction is in place currently, but there is a residual error affecting the antenna temperature due to this dependence of the PMS offsets on the heater status. This dependence is believed to be produced by a combination of EMC and thermal effects. A more robust PMS design from the EMC point of view but also from the thermal aspects could mitigate if not remove this unwanted effect. It would be necessary to add a PMS-heater sensitivity test within the payload test campaign to ensure the effect is indeed not happening. A thermal control based on a PID law as opposed to an ON-OFF approach would as well smooth its effects on the PMS offset.
Centralization of the noise injection for LO phase calibration. Currently, the CAS (Calibration System) is based on a distributed approach of overlapping 1-to-12 receiver signal distribution trees. This responded to the practical difficulty of implementing a centralized 1-to-72 receiver distribution network. The distributed approach requires 2 steps to activate first one half of the CAS noise sources, and then the other half, which consumes time, and leads to some error propagation. Similarly, the calibration of the fringe-washing function parameters of baselines not connected to the same CAS noise source has to follow a stepped approach based on phase closure relationships. A centralized noise injection distribution would today be possible thanks to the advance in optoelectronics, i.e. using optical cables and components instead of coaxial cables. The CAS signal could be thus generated centrally in a redundant unit and distributed to all receivers following a single distribution tree. Such approach would solve both limitations above described, i.e. the need for 2 step calibration and the propagation of errors, resulting potentially in a more accurate calibration and simplifying greatly the commanding of the calibration mode.
5) Open areas:
As introduced above, it has been empirically verified that, in the ALL-LICEF mode there is an efficiency factor of 0.98 that, when applied to all visibility samples outside the origin (0,0), shows to reduce the land-sea contamination. The explanation behind such efficiency factor has not been found yet but certainly reveals its effects only thanks to the fact, that we are measuring V(0,0) with a different hardware than the rest of the visibility samples. It is hence expected that removing the NIR units (as proposed earlier) shall also remove the need of such correction factor of unknown origin.
A consolidated result is the existence of a noise floor limit in the amplitude of systematic spatial ripple in SMOS images, below which, it is not possible to reach. The noise floor is determined by the combination of element spacing and antenna pattern similarity. The further away the element spacing is from that one for which no aliases can appear (0.58 times the central wavelength of the radiation in the case of hexagonal sampling, as it is SMOS), and the more dissimilar the antenna patterns are from each other, the larger the amplitude of the systematic spatial ripple is.
A second contributor to spatial ripple is the lack of perfect knowledge of the antenna patterns. Currently the SMOS Calibration and Level-1 team is working on techniques to reduce this contribution, such as the Initial Guess based Techniques (dubbed ‘Gibbs' approaches), the Floor Error Mask, the Pre-Distorted G-matrix and the Average Pattern Reconstruction.
• June 13, 2017: Satellites are helping to predict favorable conditions for desert locusts to swarm, which poses a threat to agricultural production and, subsequently, livelihoods and food security. 51)
- Desert locusts are a type of grasshopper found primarily in the Sahara, across the Arabian Peninsula and into India. The insect is usually harmless, but when they swarm they can migrate across long distances and cause widespread crop damage.
Figure 42: Ethiopia, July 1968 during a desert locust outbreak (image credit: FAO/ G. Tortoli)
- During the 2003–05 plague in West Africa, more than eight million people were affected. Up to 100% losses were reported on cereals, 90% on legumes and 85% on pasture. It took nearly $600 million and 13 million liter of pesticide to bring the plague under control.
- Swarming occurs when a period of drought is followed by good rains and rapid vegetation growth. These conditions trigger a period of abundant breeding and overcrowding, and the increased contact with other locusts can lead to the formation of large swarms. This behavior makes locusts more dangerous than grasshoppers.
- A 1 km2 swarm contains about 40 million locusts, which eat the same amount of food in one day as about 35,000 people. In other words, a swarm the size of the capital of Mali or the capital of Niger will eat the same amount of food as half the entire population of the respective country.
- Satellites can monitor the conditions that can lead to swarming locusts, such as soil moisture and green vegetation. ESA recently teamed up with international partners from Algeria, France, Mali, Mauritania, Morocco, Spain and the UN Food and Agriculture Organization (FAO) to test how data from satellites such as ESA's SMOS (Soil Moisture and Ocean Salinity mission), can be used to predict locust plagues.
- At FAO, we have a decades-long track record of forecasting plagues and working closely with countries at greatest risk to implement control measures," said Keith Cressman, FAO's Senior Locust Forecasting Officer. "By bringing our expertise together with ESA's satellite capabilities we can significantly improve timely and accurate forecasting. Early warning means countries can act swiftly to control a potential outbreak and prevent massive food losses."
Figure 43: Soil moisture data from the SMOS satellite and NASA's MODIS instrument acquired between July and October 2016 were used by isardSAT and CIRAD to create this map showing areas with favorable locust swarming conditions (in red) during the November 2016 outbreak (image credit: CIRAD, SMELLS consortium)
- The SMOS satellite captures images of ‘brightness temperature' that correspond to radiation emitted from Earth's surface, which can be used to gain information on soil moisture at a resolution of 50 km per pixel.
- By combining this information with medium-resolution coverage from the MODIS instrument on NASA's Aqua and Terra satellites, the team downscaled SMOS soil moisture to a resolution of 1 km per pixel. The measurements were then used to create maps showing areas with favorable locust swarming conditions about 70 days ahead of the November 2016 outbreak in Mauritania.
- In the past, satellite-based locust forecasts were derived from information on green vegetation, meaning the favorable conditions for locust swarms were already present. This allowed for a warning period of only one month.
- Information on soil moisture, on the other hand, indicates how much water is available for eventual vegetation growth and favorable locust breeding conditions, and can therefore forecast the presence of locusts 2–3 months in advance. The additional time is essential for the local national authorities to organize preventive measures.
- "I use the data products to understand the current situation, as well as the evolution of locust outbreaks," said Ahmed Salem Benahi, Chief Information Officer for Mauritania's National Center for Locust Control. "We now have the possibility to see the risk of a locust outbreak one to two months in advance, which helps us to better establish preventive control."
- While the current data products are based on the SMOS and MODIS missions, information from the Copernicus Sentinel-3 mission will soon be integrated to ensure the long-term availability of the locust warnings.
- The team is also working on a similar product downscaling SMOS soil moisture with Sentinel-1 observations, which will allow a further increase of resolution to 100 m.
• May 11, 2017: ESA's SMOS mission maps variations in soil moisture and salt in the surface waters of the open oceans. When the satellite was designed, it was not envisaged that it would be able to measure salinity in smaller seas like the Mediterranean, but SMOS has again surpassed expectations. The satellite carries a microwave instrument to capture images of ‘brightness temperature', which correspond to microwave radiation emitted from Earth's surface and can be related to soil moisture and ocean salinity. While this information is fulfilling the mission's core objective of improving our understanding of Earth's water cycle, SMOS has found a multitude of other uses such as tracking hurricanes, measuring thin ice floating in the polar oceans and improving crop-yield forecasts. 52)
- Its measurements of salinity in the open oceans not only help us understand how our oceans are responding to climate change, but are also improving our understanding of issues such as ocean acidification and large-scale events like El Niño. However, these processes take a long time so smaller seas such as the Mediterranean, where processes occur over much shorter timescales, offer an ideal laboratory to study ocean dynamics. For instance, salinity maps are needed to understand how the flow of water from the Atlantic Ocean through the Strait of Gibraltar forms the Alboran Gyre in the western Mediterranean Sea.
Figure 44: Thanks to new processing techniques, SMOS can now be used to map salinity in the Mediterranean Sea. As an example, the image shows how salinity changed in the surface waters of the Alboran Sea 11–12 September 2014. The Alboran Sean is in the westernmost part of the Mediterranean Sea, between the Iberian Peninsula and North Africa (image credit: Barcelona Expert Center)
- Until recently, SMOS' observations of salinity in the Mediterranean were hampered for two reasons. The biggest issue, and one that was understood when the mission was designed, was one of ‘land–sea contamination'. This is because measurements taken over the surrounding land leach into the ocean data and affect the quality. The other problem, which was not foreseen, is the extent of radio interference.
- Once SMOS was launched in 2009, it transpired that its signal was being interrupted by numerous illegal transmitters around the world. However, by working with national frequency protection authorities, 75% of these transmitters have now been shut down. - Nevertheless, this is a laborious process and some regions, such as the Libyan coast and the eastern Mediterranean Sea, remain contaminated where mitigation strategies have not yet been successful.
- Thanks to the determination of scientists to address these problems and with the support of ESA's Earth Observation Support to Science Element, SMOS can now map salinity in much of the Mediterranean Sea.
- The Barcelona Expert Center in Spain has addressed both the problem of land–sea contamination and also reduced the effects of interference by making changes to the standard data processing chain. Antonio Turiel from the center said, "We look out over the Mediterranean Sea every day from our institute in Barcelona and we were determined to get to grips with the problem. "The solution we came up with actually meant going back to each individual measurement of brightness temperature and filtering and processing it in a different way."
Figure 45: When ESA's SMOS satellite was placed in orbit in 2009, it transpired that its signal was being interrupted by numerous illegal transmitters around the world. However, by working with national frequency protection authorities, 75% of these transmitters have now been shut down. Nevertheless, this is a laborious process and some regions, such as the Libyan coast and the eastern Mediterranean Sea, remain contaminated where mitigation strategies have not yet been successful (image credit: ESA)
- The University of Liege in Belgium has also tackled this issue by proposing a method for reducing noise. Aida Alvera Azcárate from the University of Liege said, "Land–sea contamination and radio-frequency interference in the Mediterranean Sea cause the level of unwanted signal in the data to be rather high. "We have developed an approach to extract the actual geophysical signal from the noisy data, increasing the accuracy of the final dataset."
- ESA's SMOS mission manager, Susanne Mecklenburg, said, "Both institutes have done fabulous work in addressing the limitations we were facing when looking at changes of salinity in the Mediterranean Sea. Their work extends the catalogue of applications that SMOS can support to benefit science and society at large. "Once again we see SMOS deliver way beyond its original promise – and I'm sure there will be more successes to come."
Figure 46: Thanks to new processing techniques, information from ESA's SMOS mission can be used to map salinity in the surface waters of the Mediterranean Sea. For example, daily maps can be created using DINEOF, which reduces noise and other sources of contamination. The image, which captures salinity on 3 March 2013, shows the fresher water from the Atlantic Ocean flowing through the Strait of Gibraltar into the Mediterranean Sea (image credit: University of Liege, Belgium)
• December 16, 2016: Although not designed to deliver information on ice, ESA's Earth Explorer SMOS satellite can detect thin sea-ice. Since its cousin, CryoSat-2, is better at measuring thicker ice scientists have found a way of using these missions together to yield an even clearer picture of the changing Arctic. 53)
- Carrying a radiometer, SMOS was designed capture images of brightness temperature. While these images can be turned into information on soil moisture and ocean salinity to improve our understanding of the water cycle, it turns out that these data can also be used to measure sea ice.
- In contrast, CryoSat carries a radar altimeter that measures freeboard of sea ice, which is the distance between the waterline and the top of the ice.
- This is being used to work out how the thickness of sea ice is changing and, in addition, how the volume of Earth's ice is being affected by the climate.
- Despite the two missions being very different, scientists from the University of Hamburg and the AWI (Alfred Wegener Institute) in Bremerhaven, Germany, who are involved in both Earth Explorer missions, have found a way of combining data from both satellites to gain a more complete picture of changes in the thickness of ice floating in Arctic waters. — While the accuracy of measurements from CryoSat-2 increases with increasing ice thickness, SMOS data are more accurate when the sea ice is relatively thin, less than about a meter.
Figure 47: The animation shows how data from CryoSat-2 and SMOS have been combined to yield a more accurate and comprehensive view of sea-ice thickness in the Arctic (image credit: AWI)
Figure 48: Although not designed to deliver information on ice, ESA's Earth Explorer SMOS satellite can detect thin sea-ice. By combining measurements from SMOS with measurements from CryoSat-2 the two different satellites missions are yielding an even clearer picture of the changing Arctic. SMOS is also helping to improve the accuracy of sea-ice forecasts, which could help marine traffic operators determine the safest and most economic routes through waters such as the Northwest Passage and the Northern Sea Route as the ice becomes thinner owing to climate change (image credit: ESA, M. Drusch)
- CryoSat measurements yield high-spatial resolution information and cover the Arctic every month. While SMOS offers daily images, they are a much coarser resolution than those of CryoSat-2. Robert Ricker from AWI said, "By combining ice-thickness estimates from CryoSat-2 and SMOS, we obtain a more accurate and comprehensive view on the actual state of Arctic sea ice. Users need timely information across the entire Arctic and we can meet their needs by combing information from these two different, but complementary satellite missions."
- The University of Hamburg is already using SMOS to provide daily maps of Arctic sea-ice thickness during the winter. These maps are produced within 24 hours of the measurements being taken in space. SMOS is also helping to improve the accuracy of sea-ice forecasts, which could help marine traffic operators to determine the safest and most economic routes through waters such as the Northwest Passage and the Northern Sea Route as the ice becomes thinner owing to climate change.
- In addition, both missions' archived data have been merged to generate information on thin sea-ice going back to 2010.
Figure 49: Sea-ice change from SMOS: Based on measurements from the SMOS mission, the animation shows changes in sea-ice thickness during November between 2010 and 2016. Although designed to improve our understanding of Earth's water cycle, SMOS is now being used to provide accurate measurements of thin sea-ice, complementing the CryoSat mission (image credit: University of Hamburg)
- This will make an important contribution to studies into the fragile component of the Earth system and help to understand annual variations and climate change. Lars Kaleschke, from the University of Hamburg, emphasized, "It is good see how information from two different types of measurements can be combined into one product to advance science and improve operational applications. It has now been demonstrated that using ice thickness information from SMOS improves the model computations and forecasts. It will be interesting to see how ocean current and air temperature models will benefit from a better understanding of the sea-ice fields."