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Estimation of Predictability with a Newly Derived Index to Quantify Similarity among Ensemble Members

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/52269

Title: Estimation of Predictability with a Newly Derived Index to Quantify Similarity among Ensemble Members
Authors: Yamada, Tomohito J. Browse this author →KAKEN DB
Koster, Randal D. Browse this author
Kanae, Shinjiro Browse this author
Oki, Taikan Browse this author
Keywords: Ensemble forecasting
Model evaluation/performance
Ranking methods
Issue Date: Jul-2007
Publisher: American Meteorological Society
Journal Title: Monthly Weather Review
Volume: 135
Issue: 7
Start Page: 2674
End Page: 2687
Publisher DOI: 10.1175/MWR3418.1
Abstract: This study reveals the mathematical structure of a statistical index, Ω, that quantifies similarity among ensemble members in a weather forecast. Previous approaches for quantifying predictability estimate separately the phase and shape characteristics of a forecast ensemble. The diagnostic Ω, on the other hand, characterizes the similarity (across ensemble members) of both aspects together with a simple expression. The diagnostic Ω is thus more mathematically versatile than previous indices.
Type: article
URI: http://hdl.handle.net/2115/52269
Appears in Collections:工学院・工学研究院 (Graduate School of Engineering / Faculty of Engineering) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 山田 朋人

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