Improved soil moisture estimation from TRMM precipitation radar backscatter corrected for azimuth modulation

Document Type

Conference Proceeding

Publication Date


Publication Title

2009 AGU Fall Meeting


American Geophysical Union


Tropical Rainfall Measuring Mission (TRMM) has proved to be a milestone in advancing the understanding of global rain in relation to the hydrologic cycle and climate. TRMM Precipitation Radar (TRMMPR), provides Ku-band HH polarization backscatter (σ°) measurements which are sensitive to physical and electrical characteristics of the surface. TRMMPR σ° measurements are made at an incidence angle (θ) range of 0°–17° and four azimuth angles. The four azimuth angles (φ) result from ascending and descending passes and cross track scanning on both sides of satellite path. The average four φ values of TRMM σ° measurements are 12°, 167°, 191°, and 346° (measuring clockwise from geographical North direction). Generally, σ° φ-dependence is ignored in the retrieval of geophysical parameters (e.g., rain, soil moisture, vegetation, and soil roughness). Since σ° modulation with the θ and φ depends on the large scale surface directional geometrical characteristics, it can significantly impact the results of the derived parameters over the mountainous regions. In this research, we quantify the dependence of σ° φ-dependence on the surface topography to improve the accuracy of soil moisture retrieval model. σ° φ-dependence is related to surface geometrical variables (elevation, slope, and aspect). σ° θ-dependence is modeled by a quadratic equation and normalized σ° at θ=10° for each φ [denoted by A(φ)] is computed. The numerical offset among A(φ) values is a function of surface slope and slope-orientation. Figure 1a shows the difference between A(191°) and A(12°) and compares it to the elevation (1b), slope (1c), and aspect (1d) maps. It is evident that areas with highly varying surface slope can significantly change the normalized backscatter at different azimuth angles. Accounting this variation into the rain and soil moisture retrieval algorithms can improve the retrieval accuracy. An azimuth angle correction term is computed and used to correct σ° measurements before retrieving soil moisture. It is shown that accounting for φ-dependence improves the soil moisture retrieval in the mountainous arid regions.


Global rainfall; Precipitation; Remote sensing; Soil moisture; Tropical Rainfall Measuring Mission (TRMM)


Environmental Monitoring | Geographic Information Sciences | Meteorology




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