Abstract
The Federated Satellite System mission (FSSCat), winner of the 2017 Copernicus Masters Competition and the first ESA third-party mission based on CubeSats, aimed to provide coarse-resolution soil moisture estimations and sea ice concentration maps by means of the passive microwave measurements collected by the Flexible Microwave Payload-2 (FMPL-2). The mission was successfully launched on 3 September 2020. In addition to the primary scientific objectives, FMPL-2 data are used in this study to estimate sea surface salinity (SSS), correcting for the sea surface roughness using a wind speed estimate from the L-band microwave radiometer and GNSS-R data themselves. FMPL-2 was executed over the Arctic and Antarctic oceans on a weekly schedule. Different artificial neural network algorithms have been implemented, combining FMPL-2 data with the sea surface temperature, showing a root-mean-square error (RMSE) down to 1.68 m/s in the case of the wind speed (WS) retrieval algorithms, and RMSE down to 0.43 psu for the sea surface salinity algorithm in one single pass.
Highlights
In 1992, the United Nations (UN) established the Global Climate Observing System (GCOS) and defined the different Essential Climate Variables (ECV) [1] that need to be monitored for a better understanding of our climate and the effects of climate change [2,3].in 2015, seventeen Sustainable Development Goals (SDG) were defined to ensure sustainable human progress, reducing our footprint on planet Earth
Flexible Microwave Payload-2 (FMPL-2) Global Navigation Satellite System—Reflectometry (GNSS-R) data from [39], geo-located data over specular reflection points; FMPL-2 L-band microwave radiometry (MWR) data from [39], gridded into a 12.5 km EASE GRID 2.0 with polar projection [40]; ERA-5 hourly wind speed (WS) and sea surface temperature (SST) data re-gridded into a 12.5 km polar mesh from [41], as detailed in Figure 3a; Daily L4 sea surface salinity (SSS) from Soil Moisture and Ocean Salinity Mission (SMOS) from [42], as detailed in Figure 3b; L2 ASCAT MeteOp WS data set from [43] used as validation for the WS retrieval
The result of this ANN is comparable to the results found in other SSS studies using similar ranges of measurement [55,56]; in this case, SSS
Summary
In 1992, the United Nations (UN) established the Global Climate Observing System (GCOS) and defined the different Essential Climate Variables (ECV) [1] that need to be monitored for a better understanding of our climate and the effects of climate change [2,3].in 2015, seventeen Sustainable Development Goals (SDG) were defined to ensure sustainable human progress, reducing our footprint on planet Earth. In 1992, the United Nations (UN) established the Global Climate Observing System (GCOS) and defined the different Essential Climate Variables (ECV) [1] that need to be monitored for a better understanding of our climate and the effects of climate change [2,3]. SDG number thirteen entails taking urgent actions to combat climate change and its impacts on the planet, which requires the monitoring of these ECVs. The loss of sea ice volume in the poles [4] may threaten the thermohaline circulation (Figure 1a) [5] and the way in which oceans moderate the Earth’s temperature. One of the main drivers of the thermohaline circulation are the salinity changes in the oceans, which, together with surface temperature, determine the water density. The melting of the polar caps increases the amount of freshwater discharged into the oceans, which may change the warm shallow ocean currents and the cold and salty deep currents that moderate the
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