論文

査読有り
2016年

Precipitation nowcasting with three-dimensional space-time extrapolation of dense and frequent phased-array weather radar observations

Weather and Forecasting
  • Shigenori Otsuka
  • ,
  • Gulanbaier Tuerhong
  • ,
  • Ryota Kikuchi
  • ,
  • Yoshikazu Kitano
  • ,
  • Yusuke Taniguchi
  • ,
  • Juan Jose Ruiz
  • ,
  • Shinsuke Satoh
  • ,
  • Tomoo Ushio
  • ,
  • Takemasa Miyoshi

31
1
開始ページ
329
終了ページ
340
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1175/WAF-D-15-0063.1
出版者・発行元
AMER METEOROLOGICAL SOC

© 2016 American Meteorological Society. The phased-array weather radar (PAWR) is a new-generation weather radar that can make a 100-m-resolution three-dimensional (3D) volume scan every 30 s for 100 vertical levels, producing ~100 times more data than the conventional parabolic-antenna radar with a volume scan typically made every 5 min for 15 scan levels. This study takes advantage of orders of magnitude more rapid and dense observations by PAWR and explores high-precision nowcasting of 3D evolution at 1-10-km scales up to several minutes, which are compared with conventional horizontal two-dimensional (2D) nowcasting typically at O(100) km scales up to 1-6 h. A new 3D precipitation extrapolation system was designed to enhance a conventional algorithm for dense and rapid PAWR volume scans. Experiments show that the 3D extrapolation successfully captured vertical motions of convective precipitation cores and outperformed 2D nowcasting with both simulated and real PAWR data.

リンク情報
DOI
https://doi.org/10.1175/WAF-D-15-0063.1
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000370391800001&DestApp=WOS_CPL
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84958967599&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84958967599&origin=inward
ID情報
  • DOI : 10.1175/WAF-D-15-0063.1
  • ISSN : 0882-8156
  • eISSN : 1520-0434
  • SCOPUS ID : 84958967599
  • Web of Science ID : WOS:000370391800001

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