A GCM Experiment on Time Sampling for Remote Sensing of Near-Surface Soil Moisture

Abstract

The use of microwave remote sensing opens new possibilities to study global soil moisture dynamics. The measured signal is proportional to the surface moisture and temperature of a thin soil layer. Several low-frequency microwave sensors, such as the Advanced Microwave Scanning Radiometer (AMSR) in C band and Soil Moisture and Ocean Salinity (SMOS) in L band, are now being flown (AMSR) or are scheduled to be launched in the near future (SMOS, in 2005) on sun-synchronous satellite platforms. Because of the diurnal cycle of the measured surface soil moisture content and its temporal variability, the restricted time sampling by an instrument in sun-synchronous orbit may be a source of error in the monthly mean quantities used for climate and land surface processes models. This paper presents a time sampling experiment, conducted with a general circulation model, in order to estimate the representativeness of the observations of the near-surface soil moisture, at a given time of the day, for the knowledge that can be gained of the monthly mean soil moisture. Due to the high temporal variability of the near-surface soil moisture, the impact of the revisit time of the satellite is shown to be critical for the estimated monthly mean soil moisture. This study emphasizes the requirement to develop and to use assimilation methods to produce meaningful soil moisture values from remotely sensed datasets.