DocumentCode
56756
Title
Enhancing Quantitative Precipitation Estimation Over the Continental United States Using a Ground-Space Multi-Sensor Integration Approach
Author
Qing Cao ; Yixin Wen ; Yang Hong ; Gourley, Jonathan J. ; Kirstetter, Pierre-Emmanuel
Author_Institution
Hydrometeorology & Remote Sensing Lab., Univ. of Oklahoma, Norman, OK, USA
Volume
11
Issue
7
fYear
2014
fDate
Jul-14
Firstpage
1305
Lastpage
1309
Abstract
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 over the Continental United States are addressed as well.
Keywords
atmospheric precipitation; atmospheric techniques; meteorological radar; remote sensing by radar; Continental United States; Mountainous West region; NASA Tropical Rainfall Measuring Mission; NOAA NMQ system; National Mosaic QPE; TRMM precipitation radar; VPR enhancement; VPR identification; complex terrain; ground weather radar; ground-radar QPE; ground-space multisensor integration approach; mountainous regions; quantitative precipitation estimation; radar beam; vertical profile of reflectivity; Meteorology; Pollution measurement; Radar measurements; Radar remote sensing; Real-time systems; Spaceborne radar; Quantitative precipitation estimation (QPE); satellite remote sensing; vertical profile of reflectivity (VPR); weather radar;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2013.2295768
Filename
6709806
Link To Document