Skip to main content
ARS Home » Research » Publications at this Location » Publication #109435
Title: PASSIVE MICROWAVE REMOTE SENSING OF ATMOSPHERIC AND LAND SURFACE PARAMETERSDURING THE SOUTHERN GREAT PLAINS HYDROLOGY EXPERIMENT 1997

Author
item DRUSCH, MATTHIAS - PRINCETON UNIV, NJ
item WOOD, ERIC - PRINCETON UNIV, NJ
item Jackson, Thomas

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/10/2001
Publication Date: N/A
Citation: N/A

Interpretive Summary: The impact of using atmospheric corrections on retrieving soil moisture from an existing passive microwave satellite was determined for the Southern Great Plains region of the U.S. A weak but persistent relationship exists between the satellite measured emissivity and surface soil moisture in this region. The existing satellite operates at high frequencies which has a level of sensitivity to variations in the atmospheric water vapor. Data to describe this effect are sparse in both time and space. In this study, the impact of ignoring this effect was evaluated using an extensive database collected in a field experiment. Results showed that for this region it is a minor effect and can be ignored. This makes the retrieval of soil moisture much more efficient especially in applications involving large regional multi-temporal forecasting.

Technical Abstract: In order to determine the potential of passive microwave remote sensing for soil moisture retrieval, data from the SGP97 experiment in Oklahoma were analyzed. A coupled soil emission/atmosphere radiative transfer model was used to investigate the spectral dependency of surface parameter retrieval on atmospheric effects. Using the atmospheric radiative transfer model and vertical profiles of air temperature and humidity obtained from radiosonde ascends, the atmospheric contributions to the top of the atmosphere brightness temperatures were calculated. Correcting the measured 19 GHz, brightness temperatures with soil temperature and the atmospheric contributions results in soil emissivities. These were compared to the volumetric soil moisture data. Atmospheric contributions affect the emissivity and depend upon the integrated water vapor, cloud liquid water path, and frequency of the soil moisture. However, it was found that for this study the retrieval at 19 GHz itself was not significantly improved b making this correction. This might be due to beam-filling and 3-D radiative transfer effects within the pixel and the small number of data points. The results of the analysis show that SSM/I measurements over sparsely vegetated areas can be used to discriminate wet, normal, and dry soil moisture conditions even without atmospheric corrections. Moreover, this study indicates that for the retrieval of cloud and atmospheric parameters from 19, 22, and 37 GHz measurements, the soil emissivity and therefore soil moisture have to be accurately known.