Enhancing Quantitative Precipitation Estimation Over the Continental United States Using a Ground-Space Multi-Sensor Integration Approach

被引：10

作者：

Cao, Qing ^{[1
,2
]}

Wen, Yixin ^{[1
,2
]}

Hong, Yang ^{[1
,2
,3
]}

Gourley, Jonathan J. ^{[1
,4
]}

Kirstetter, Pierre-Emmanuel ^{[1
,4
]}

机构：

[1] Univ Oklahoma, Hydrometeorol & Remote Sensing Lab, Norman, OK 73072 USA

[2] Univ Oklahoma, Adv Radar Res Ctr, Norman, OK 73072 USA

[3] Tsinghua Univ, Dept Hydraul Engn, Beijing 100084, Peoples R China

[4] NOAA, Natl Severe Storms Lab, Norman, OK 73072 USA

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2014年 / 11卷 / 07期

基金：

美国国家航空航天局;

关键词：

Quantitative precipitation estimation (QPE); satellite remote sensing; vertical profile of reflectivity (VPR); weather radar; VERTICAL PROFILES; MELTING-LAYER; RADAR; REFLECTIVITY; BAND; IDENTIFICATION; PERFORMANCE; ALGORITHM; WSR-88D; RAIN;

D O I：

10.1109/LGRS.2013.2295768

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：

Quantitative precipitation estimation (QPE) based on ground weather radar could be considerably affected by the broadening, ascent, and blockage of the radar beam. These problems are particularly prevalent in mountainous regions. The current study proposes a multi-sensor approach to improve the ground-radar QPE in complex terrain. The proposed method, namely the Vertical Profile of Reflectivity (VPR) Identification and Enhancement (VPR-IE), integrates NOAA's National Mosaic QPE (NMQ) system and NASA's Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) measurements. This study demonstrates promising performance of VPR-IE in the Mountainous West Region of the U. S. The potential error sources of this approach and its real-time implementation

引用

页码：1305 / 1309

页数：5

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