HR: 09:00h
AN: H21C-05    [PDF]
TI: Soil Moisture Estimation Using Surface Backscattering Coefficients Observed by the Tropical Rain Measurement Mission Precipitation Radar
AU: Seto, S
EM: seto@crl.go.jp
AF: Communications Research Laboratory, 4-2-1 Nukui-Kitamachi, Tokyo, 184-8795 Japan
AU: * Robock, A
EM: robock@envsci.rutgers.edu
AF: Department of Environmental Sciences, Rutgers University, 14 College Farm Road, New Brunswick, NJ 08901 United States
AU: Luo, L
EM: lluo@Princeton.EDU
AF: Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544 United States
AU: Oki, T
EM: taikan@iis.u-tokyo.ac.jp
AF: Institute of Industrial Science, University of Tokyo, 4-6-1 Meguro-ku, Komaba, Tokyo, 153-8505 Japan
AU: Iguchi, T
EM: iguchi@crl.go.jp
AF: Communications Research Laboratory, 4-2-1 Nukui-Kitamachi, Tokyo, 184-8795 Japan
AU: Musiake, K
EM: musiake@educ.fukushima-u.ac.jp
AF: Fukushima University, 1 Kanayagawa, Fukushima, 960-1296 Japan
AB: Soil moisture affects many important hydrological and meteorological processes on various scales and it is important to know the global distribution of soil moisture. Microwave remote sensing is an indispensable method of obtaining this information. We used the first space-borne precipitation radar, on the Tropical Rainfall Measuring Mission satellite, for this purpose by examining backscattering not from rainfall but from the land surface under no precipitation conditions. The spatial pattern of the land surface backscattering coefficient ($\sigma\deg$) is determined mainly by the incident angle and vegetation. The seasonal pattern of $\sigma\deg$ in general does not depend on different incident angles, except in the Sahel region, where there is a large impact of from the temporal change of vegetation. We propose a soil moisture estimation algorithm that considers a mosaic of different vegetation types in each scene. The vegetation fraction is determined by the $\sigma\deg$ observed at an incident angle of $3\deg$ and then the temporal change of $\sigma\deg$ for bare soil is calculated with observation at an angle of $12\deg$. Because $\sigma\deg$ observed at $12\deg$ is not strongly affected by change of vegetation, the algorithm can simulate the seasonal pattern well even in the Sahel where vegetation changes drastically. This algorithm generally works well in regions without heavy vegetation. The algorithm works well when tested for estimating daily soil moisture in Oklahoma at a latitude of about $35\deg$N.
DE: 1640 Remote sensing
DE: 1694 Instruments and techniques
DE: 1866 Soil moisture
DE: 3322 Land/atmosphere interactions
SC: Hydrology [H]
MN: 2003 Fall Meeting