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Title: 気象庁数値予報データ(GPV)の統計的検証
Other Titles: Validation of JMA numerical prediction data (GPV) by statistical analysis
Authors: 山田, 賢治  KAKEN_name
池淵, 周一  KAKEN_name
田中, 賢治  kyouindb  KAKEN_id
相馬, 一義  KAKEN_name
Author's alias: YAMADA, Kenji
IKEBUCHI, Shuichi
TANAKA, Kenji
SOUMA, Kazuyoshi
Keywords: GPV
降水予測
RSM
ダム
GPV
rainfall prediction
RSM
dam
Issue Date: 1-Apr-2006
Publisher: 京都大学防災研究所 / Disaster Prevention Research Institute Kyoto University
Journal title: 京都大学防災研究所年報. B = Disaster Prevention Research Institute annuals. B
Volume: 49
Issue: B
Start page: 601
End page: 615
Abstract: ダムを適切に管理・運用するためには,精度の高い降水予測が必要である。本研究では51時間先までの予測値を得ることができる気象庁数値予報GPVを検証することで,GPV降水予測量の誤差傾向を季節毎に評価指標を用いて評価した。さらに評価した結果をもとに,ダム流域周辺メッシュや同時刻に存在する他の初期時刻モデルのGPV降水予測量の利用可能性を検討した。これによって,ダム流域において現モデルの性能でより信頼度の高い降水予測情報を得ることができるかを検討した。
It is important to predict rainfall with high accuracy in dam basins because rainfall prediction is necessary to control and operate dams properly. Major methods for prediction are kinematic or physical. Japan meteorological agency (JMA) numerical forecasting is one of physical prediction methods. Grid point value (GPV) is output of JMA numerical forecasting. Its resolution is insufficient to reproduce phenomena unique to mountainous regions. Therefore, downscaling by another high-resolution rainfall forecasting model is a major method to advance accuracy in a lot of researches. In this study, it is examined how accurate GPV is, and formulated how to take advantage of GPV efficiently.
URL: http://www.dpri.kyoto-u.ac.jp/dat/nenpo/no49/49b0/a49b0p65.pdf
URI: http://hdl.handle.net/2433/26654
Appears in Collections:No.49 B

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