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Precipitation Estimates from SMOS Sea-Surface Salinity

Abstract : Two L-Band (1.4 GHz) microwave radiometer missions, SMOS (Soil Moisture and Ocean Salinity) and SMAP (Soil Moisture Active and Passive) currently provide Sea Surface Salinity (SSS) measurements. At this frequency, salinity is measured in the first centimetre below the sea surface, which makes it very sensitive to the presence of fresh water lenses linked to rain events. A relationship between salinity anomaly (ΔS) and rain rate (RR) is derived in the Pacific Inter Tropical Convergence Zone from SMOS SSS measurements and Special Sensor Microwave Imager/Sounder (SSMIS) RR. It is then used to develop an algorithm to estimate RR from SMOS SSS measurements. A heuristic function is developed to correct the SMOS-estimated negative RR due to measurements noise. Correlation between SMOS and SSMIS RR and between SMOS and Integrated MultisatellitE Retrievals for GPM (IMERG) RR are high when SMOS and SSMIS passes are less than 15mn apart (r=0.7 at 1°×1° resolution), showing a good quality of SMOS RR retrievals. When the time shift between SMOS and SSMIS passes increases, the correlation between SMOS and IMERG RR diminishes. This suggests that L-band radiometry can provide information complementary to GPM missions to improve RR products interpolated at high temporal resolution. The retrieval is successfully tested on SMAP SSS. We also check that our algorithm provides reliable estimates of RR when averaged at a monthly time scale.
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Contributor : Catherine Cardon Connect in order to contact the contributor
Submitted on : Tuesday, December 22, 2020 - 9:47:39 AM
Last modification on : Friday, August 5, 2022 - 11:54:43 AM


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Distributed under a Creative Commons Attribution - NonCommercial 4.0 International License


  • HAL Id : insu-01563248, version 1
  • DOI : 10.1002/qj.3110
  • WOS : 000457053200009


Alexandre Supply, Jacqueline Boutin, Jean-Luc Vergely, Nicolas Martin, Audrey Hasson, et al.. Precipitation Estimates from SMOS Sea-Surface Salinity. Quarterly Journal of the Royal Meteorological Society, 2018, 144 (S1), pp.103-119. ⟨10.1002/qj.3110⟩. ⟨insu-01563248⟩



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