Regional climate-weather research and forecasting model

Xin Zhong Liang, Min Xu, Xing Yuan, Tiejun Ling, Hyun I. Choi, Feng Zhang, Ligang Chen, Shuyan Liu, Shenjian Su, Fengxue Qiao, Yuxiang He, Julian X.L. Wang, Kenneth E. Kunkel, Wei Gao, Everette Joseph, Vernon Morris, Tsann Wang Yu, Jimy Dudhia, John Michalakes

Research output: Contribution to journalArticlepeer-review

90 Scopus citations

Abstract

Regional climate-weather research and forecasting model, an extension of the WRF, incorporate a comprehensive ensemble of alternative physics representations, and facilitate seamless applications for regional weather forecasting and climate prediction. For model evaluation, daily total precipitation and daily mean surface air temperature data are based on measurements from 7,235 National Weather Service cooperative stations across the United States. A preliminary test demonstrated the capability of a physics ensemble approach to improve precipitation prediction at regional-local scales. The skill enhancement, with increased occurrence of higher correlation coefficients and smaller rms errors, is most pronounced during summer, followed by autumn and spring, but rather weak in winter.

Original languageEnglish (US)
Pages (from-to)1363-1387
Number of pages25
JournalBulletin of the American Meteorological Society
Volume93
Issue number9
DOIs
StatePublished - Sep 2012

ASJC Scopus subject areas

  • Atmospheric Science

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