Producing Satellite-based Diurnal Time-scale Soil Moisture Retrievals using Existing Microwave Satellites and GNSS-R Data

Abstract:

The land atmospheric interaction is governed by soil moisture as it determines the partitioning of outgoing energy flux into latent and sensible heat fluxes; thus, we can predict how much water will remain on the ground or evaporate into lower atmosphere. Even though, there is a great anticipation that soil moisture data with diurnal temporal resolution from space can provide near-real-time antecedent wetness conditions and improve forecasting of extreme climate events, not many studies have been conducted to construct observation-based diurnal temporal resolution soil moisture data on a global-scale. In this study, we considered widely-used microwave-based satellites data including the Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), Advanced Scatterometer (ASCAT) on board the METOP-A/B/C satellites, Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the GCOM-W1 satellite, and the Cyclone Global Navigation Satellite System (CYGNSS). Previous studies have shown that the delay-Doppler Map (DDM) generated from global navigation satellite system (GNSS)’ signals of opportunity have a strong relationship with surface soil moisture. In 2017, NASA launched eight microsatellites called the Cyclone Global Navigation Satellite System (CYGNSS) to predict cyclone paths and studies have shown that the CYGNSS constellation can provide DDM approximately 5 times per day. Thus, we also considered CYGNSS data in this study.

The relative errors for each satellite system was calculated based on triple collocation Analysis (TCA) and their errors were counted when we constructed the diurnal soil moisture data. All microwave-based satellites soil moisture data were obtained around 1 a.m., 6 a.m., 9 a.m., 1 p.m., 6 p.m., and 9 p.m.; and CYGNSS filled the observation gap whenever CYGNSS observations available. The diurnal soil moisture was validated against in-situ soil moisture data from the International Soil Moisture Network (ISMN) and SMAP core sites. In the future study, over the areas where diurnal soil moisture data is available, we will assimilate diurnal soil moisture data into land surface models through Land Information System (LIS) and investigated the advantages of producing high-temporal resolution soil moisture data.