Evidence of Rainfall Signatures on X-Band Synthetic Aperture Radar Imagery Over Land

被引:29
|
作者
Marzano, Frank Silvio [1 ,2 ]
Mori, Saverio [1 ,2 ]
Weinman, James A. [3 ]
机构
[1] Univ Roma La Sapienza, Dept Elect Engn, I-00184 Rome, Italy
[2] Univ Aquila, Ctr Eccellenza Integraz Tecn Telerilevamento & Mo, I-67010 Laquila, Italy
[3] Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA
来源
关键词
Inversion methods; microwave modeling; precipitation; X-band synthetic aperture radar (X-SAR); PROFILING ALGORITHM; PASSIVE MICROWAVE; PRECIPITATION; REFLECTIVITY; BACKSCATTERING; RETRIEVAL; EVOLUTION;
D O I
10.1109/TGRS.2009.2034843
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Five spaceborne X-band synthetic aperture radars (X-SARs) are nowadays operating, and several more will be launched in the coming years. These X-SAR sensors, able to image the Earth's surface at metric resolution, may provide a unique opportunity to measure rainfall over land with spatial resolution of about a few hundred meters due to the moving-target degradation effects. This work is devoted to experimentally demonstrate this X-SAR capability, which can also be exploited to correct synthetic aperture radar (SAR) imagery for rainfall attenuation effects. Several case studies, selected from TerraSAR-X (TSX) overpasses over Europe and the southern U. S. in 2008, are qualitatively analyzed in terms of rainfall signatures. Visual validation of these rainfall SAR signatures is carried out by using available data from ground-based weather radars. A detailed data analysis for the case study of Hurricane "Gustav" on September 2, 2008, is carried out to assess a quantitative correlation among X-SAR response and near-surface precipitation rain rate. Two simplified empirical inversion algorithms, based on statistical regression and probability matching, are developed to retrieve rain rate from TSX cross-track ground-range measurements. The TSX-retrieved rain fields are compared to those estimated from the Next Generation Weather Radar (NEXRAD) in Mobile (Alabama, U. S.), showing a root-mean-square error less than 15 mm/h and a correlation of about 0.7.
引用
收藏
页码:950 / 964
页数:15
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