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  • Author or Editor: Rong Zhang x
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Pao-Liang Chang
,
Jian Zhang
,
Yu-Shuang Tang
,
Lin Tang
,
Pin-Fang Lin
,
Carrie Langston
,
Brian Kaney
,
Chia-Rong Chen
, and
Kenneth Howard

Abstract

Over the last two decades, the Central Weather Bureau of Taiwan and the U.S. National Severe Storms Laboratory have been involved in a research and development collaboration to improve the monitoring and prediction of river flooding, flash floods, debris flows, and severe storms for Taiwan. The collaboration resulted in the Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system. The QPESUMS system integrates observations from multiple mixed-band weather radars, rain gauges, and numerical weather prediction model fields to produce high-resolution (1 km) and rapid-update (10 min) rainfall and severe storm monitoring and prediction products. The rainfall products are widely used by government agencies and emergency managers in Taiwan for flood and mudslide warnings as well as for water resource management. The 3D reflectivity mosaic and QPE products are also used in high-resolution radar data assimilation and for the verification of numerical weather prediction model forecasts. The system facilitated collaborations with academic communities for research and development of radar applications, including quantitative precipitation estimation and nowcasting. This paper provides an overview of the operational QPE capabilities in the Taiwan QPESUMS system.

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Bin Wang
,
Michela Biasutti
,
Michael P. Byrne
,
Christopher Castro
,
Chih-Pei Chang
,
Kerry Cook
,
Rong Fu
,
Alice M. Grimm
,
Kyung-Ja Ha
,
Harry Hendon
,
Akio Kitoh
,
R. Krishnan
,
June-Yi Lee
,
Jianping Li
,
Jian Liu
,
Aurel Moise
,
Salvatore Pascale
,
M. K. Roxy
,
Anji Seth
,
Chung-Hsiung Sui
,
Andrew Turner
,
Song Yang
,
Kyung-Sook Yun
,
Lixia Zhang
, and
Tianjun Zhou
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