Abstract
The L-band radiometer onboard the Soil Moisture Active Passive (SMAP mission is used to retrieve sea surface salinity (SSS over global ocean. In the Arctic seas, one of the major challenges of SSS remote sensing is the presence of sea ice. This paper proposes a data-driven ice correction (IC algorithm which extracts emission from the water portion of measured brightness temperature (TB in scenes mixed with water and ice. Emission of the ice portion was removed based on estimation according to the ice fraction (fice in the satellite footprint and ice signature derived from surrounding pixels. The IC algorithm is applied to SMAP TB data to obtain TB with ice correction (TBIC, which are used for SSS retrieval using the standard JPL SMAP CAP processing system. We show that the algorithm is most effective near the ice edge, thereby increasing the fice threshold for possible SSS retrieval to 15% from the current 3% without IC. SMAP SSS are validated using in situ salinity collected during NASAs Ocean Melting Greenland (OMG mission from 2016 to 2020 along the Greenland coast. The number of collocations between OMG and SMAP daily gridded salinity increased by more than 30% with IC. The statistical analysis shows a similar retrieval accuracy with or without IC, with the standard deviation of the difference between OMG and SMAP of 1.41 psu (with IC and 1.42 psu (without IC . The bias adjusted SMAP SSS depicts salinity patterns and gradients around Greenland consistent with OMG measurements.
Highlights
Arctic sea ice has dramatically changed over the last few decades
sea surface salinity (SSS) fields over global oceans have been observed by three satellite missions based on L-band microwave radiometry: NASA’s Aquarius [7] and the Soil Moisture Active Passive (SMAP) [8], and ESA’s Soil Moisture and Ocean Salinity (SMOS) [9], [10]
L-band sensitivity to oceanic salinity decreases in cold water [11], satellite SSS remains valuable in monitoring Arctic SSS, supported by the finding that the variability of SSS observed in the Arctic largely exceeds the satellite SSS uncertainty (~1 psu) [12] forced by sea ice and river discharges variability [5], [6]
Summary
Arctic sea ice has dramatically changed over the last few decades. Areas covered by perennial ice - ice that has survived at least one melt season - shrank from covering more than twothirds of the surface area of the Arctic Basin in the late 1970s to about one-third [1], [2]. TB received from a footprint consisting of both ice and water (TBmeas.) likely exceeds TBwater, resulting in false low SSS estimation if a retrieval algorithm designed for homogeneous seawater is used. Analyzing SMAP measurements and collocated sea ice concentration and ice type data, we found that MESMA was not applicable for our operational retrieval. This is mainly because the spatial/temporal variance of the sea ice surface associated with surface melting, snow covering, roughness etc.
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