The Special Sensor Microwave / Imager (SSM/I) is a seven channel imaging radiometer carried onboard satellites of the Defense Meteorological Satellite Program. It has two linearly polarized channels at 19, 37, and 85 GHz, and one vertically polarized channel at 22 GHz. SSM/I imagery from three satellite systems (F10, F13, F14) obtained over the test site of the Southern Great Plains '97 Experiment (SGP97) are being analyzed for the period 5 to 12 July, 1997. The different overpass times of the three satellites on ascending and descending orbits provide 6 data points per day which exhibit the effect of diurnal temperature change on the brightness temperature. Examining data from each overpass separately, the area-averaged brightness temperatures at 19 and 37 GHz are seen to increase by up to 9K over the 6-day period of 5-10 July, followed by a decrease in the following 2 days. A decrease, then an increase in the polarization differences at 19 and 37 GHz over this period are also observed.
The main objective of this study is to provide a quantitative explanation for these features. To achieve this objective, a physical model is applied to relate SSM/I observations to variations in soil moisture and surface temperature as modulated by the effects of land cover type. This model has been developed at Aerojet by integrating physically-based sub-models describing the scattering, extinction, and emission properties of the lower atmosphere, the vegetation canopy, and the soil. The model operates over a wide frequency range, from lower microwave frequencies to millimeter wave frequencies, and is applicable to surface conditions ranging from bare soil to 100% vegetation cover.
For this study the model is used to perform numerical simulations with parameters characteristic of the SGP97 experiment area. Atmospheric profiles are taken from radiosonde ascents in the region, and soil moisture data for the period are expected to be available from the SGP97. The land surface cover types assumed to be present in the South Great Plains include agricultural crops, trees, grass, bare soil, etc. Comparison of the brightness temperature variations seen in the simulations with the observations will allow us to quantify the ability of the SSM/I to monitor the temporal change in soil moisture under various land cover and atmospheric conditions.