Abstract
Satellite-derived soil moisture products have become an important data source for the study of land surface processes and related applications. For satellites with sun-synchronous orbits, these products are typically derived separately for ascending and descending overpasses with different local acquisition times. Moreover, diurnal variations in land surface conditions, and the extent to which they are accurately characterized in retrieval algorithms, lead to distinct systematic and random error characteristics in ascending versus descending soil moisture products. Here, we apply two independent evaluation techniques (triple collocation and direct comparison against sparse ground-based observations) to quantify (correlation-based) accuracy differences in satellite-derived surface soil moisture acquired at different local acquisition times. The orbits from different satellites are separated into two overpass categories: AM (12:00 a.m. to 11:59 a.m. Local Solar Time) and PM (12:00 p.m. to 11:59 p.m. Local Solar Time). Results demonstrate how patterns in the accuracy of AM versus PM retrieval products obtained from a variety of active and passive microwave satellite sensors vary according to land cover and across satellite products with different local acquisition times.
Highlights
Soil moisture is a key state variable in land and atmosphere interactions and plays a critical role in determining the partitioning of precipitation and incoming radiation at the earth’s land surface
We examine the impact of local acquisition times and physical conditions in each individual retrieval algorithm on the correlation-based accuracy of satellite-derived surface soil moisture products retrieved from the application of: (1) the Land Parameter Retrieval Model (LPRM) to Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E), (2) the L-Band Microwave Emission of the Biosphere (L-MEB) algorithm to Soil Moisture and Ocean Salinity (SMOS), and (3)
The surface soil moisture anomalies are of the most interest compared to the raw time series, especially when systematic bias exists between satellite retrievals and land surface models (LSMs) simulations [30]
Summary
Soil moisture is a key state variable in land and atmosphere interactions and plays a critical role in determining the partitioning of precipitation and incoming radiation at the earth’s land surface. The increasing scientific recognition and urgent application demand for accurate soil moisture characterization have inspired recent developments towards global surface soil moisture measurement from active and passive microwave satellites. The Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) was the first passive microwave satellite program to routinely provide global surface soil moisture products [2]. It had a local equator overpass time at 1:30 a.m. The active microwave Advanced Scatterometer (ASCAT) was launched in October 2006 and remains in operation. It crosses the equator at 9:30 a.m
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