SMOS sings the song of ice and fire
While ESA’s water mission continues to deliver key information on soil moisture and ocean salinity to advance our understanding of Earth, it is becoming increasingly important for ‘real world’ applications, further demonstrating the societal benefit of Earth observation.
During the 2nd SMOS Science Conference held in May at ESA’s European Space Astronomy Centre near Madrid, Spain, operational agencies such as Mercator Ocean, the European Centre for Medium-Range Weather Forecasts (ECMWF), and the Deputacío de Barcelona emphasised the potential for applications that benefit everyday life.
Peter Bauer from ECMWF said, “Continuity of L-band observations is of fundamental importance for operational agencies and numerical weather prediction.
“SMOS data have already shown their value for weather forecasting as soil moisture information is crucial for predictive skill beyond the medium range. SMOS data also have the potential to provide additional capabilities for re-analyses and the Copernicus Climate Change service in future.
“Longer time series are needed for such research to provide consolidated input.”
The Diputació de Barcelona has been using SMOS information in their summer forest fire prevention campaigns since 2012. Together with land-surface temperatures, SMOS’s daily soil moisture data provide a valuable all-weather tool to detect dry areas susceptible to wildfires.
“By using SMOS data, our ability to assess the risk of fire is now significant, with the overall fire detection rate now being at 87%,”said Ramon Riera from Diputació de Barcelona.
“Areas of more than 3000 hectares that are at risk of fire can now be detected, and even smaller areas of 500 hectares under threat are predicted correctly 60% of the time.”
Carrying an L-band radiometer, SMOS uses an innovative technique of capturing images of ‘brightness temperature’. These images correspond to radiation emitted from Earth’s surface to produce maps of soil moisture and ocean salinity – two key variables in the water cycle.
Over the Arctic, SMOS data have been used to derive the thickness of sea ice. The navigability in ice-infested waters critically depends on the ice thickness. Prof L. Kaleschke from the University of Hamburg has integrated these observations in computer models, improving the accuracy of sea-ice forecasts.
A prototype navigation system predicted the fastest and most economic routes through the ice-covered Barents Sea when tested back in March 2014.
In the future, such a system could support travel along the Northwest Passage and Northern Sea Route, as the shortest link between Europe and East Asia, and also the extraction and transportation of raw materials from the Arctic.
SMOS operations were recently extended until 2017 based on the excellent scientific results achieved so far. The extension will open the door to look at new ways of using SMOS data in research and applications, and offer further synergistic opportunities with other missions.
The data are already being used with those from the US Aquarius mission. Pierre-Yves Le Traon, from Mercator Ocean and Ifremer, said, “We are already systematically comparing data from SMOS and from the Aquarius mission with our Mercator Ocean global data assimilation system, and we are working on assimilating SMOS salinity data into our ocean models.
“SMOS data have great potential for ocean and climate research, for example tracing interannual climate variability through salinity distributions, which allows us to spot phenomena such as La Niña.
“Such observations are a significant step forward in ocean research and should be continued beyond the present suite of satellites providing them.”
After more than five years in orbit, results are clearly showing the great potential SMOS data have for operational applications as well as climate research. SMOS could also complement new missions, such as NASA’s SMAP, launched in January.
In addition, using SMOS data with those from the Copernicus Sentinel missions – in particular, Sentinel-1 and Sentinel-3 – will provide interesting synergistic datasets over oceans.