Application of SMAP Data for Ocean Surface Remote Sensing

The Soil Moisture Active Passive (SMAP) mission was launched January 31st, 2015. It is designed to measure the soil moisture over land using a combined active / passive L-band system. Due to the Aquarius mission, L-band model functions for ocean winds and salinity are mature and are directly applicable to the SMAP mission. In contrast to Aquarius, the higher resolution and scanning geometry of SMAP allow for wide-swath ocean winds and salinities to be retrieved.

First, we discuss the heritage of SMAP SSS algorithms, showing that SMAP and Aquarius show excellent agreement for the ocean surface roughness correction. Then, we give an overview of some newly developed algorithms that are only relevant to the SMAP system; a new galaxy correction and land correction enabling SSS retrievals up to 35 km from coast.

Next, we compare the performance of the SMAP SSS to in-situ salinity measurements obtained from ARGO floats, tropical moored buoys, and ship-based data. SMAP SSS has accuracy of 0.2 PSU on a monthly basis compared to ARGO gridded data in tropics and mid-latitudes. In tropical oceans, time series comparison of salinity by moored buoys indicates SMAP can track large salinity changes within a month. Synergetic analysis of SMAP, SMOS, and Argo data allows us to identify and exclude erroneous buoy data from assessment of SMAP SSS. The resulting SMAP-buoy matchup analysis gives a mean standard deviation (STD) of 0.22 PSU and correlation of 0.78 on weekly scale.

In addition to SSS, SMAP provides a view into tropical cyclones having much higher sensitivity than traditional scatterometers. We validate the high-winds using collocations with SFMR during tropical cyclones as well as triple-collocations with RapidScat and WindSat. Finally, we validate the size of hurricane wind fields retrieved with SMAP with the ATCF B-deck datasets. We find that SMAP gives good estimates of cyclone size and intensity, when averaged to the resolution of SMAP.