Analyzing the Image Warp Forecast Verification Method on Precipitation Fields from the ICP

Eric Gilleland, Johan Lindström, Finn Lindgren

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

Image warping for spatial forecast verification is applied to the test cases employed by the Spatial Forecast Verification Intercomparison Project (ICP), which includes both real and contrived cases. A larger set of cases is also used to investigate aggregating results for summarizing forecast performance over a long record of forecasts. The technique handles the geometric and perturbed cases with nearly exact precision, as would be expected. A statistic, dubbed here the IWS for image warp statistic, is proposed for ranking multiple forecasts and tested on the perturbed cases. IWS rankings for perturbed and real test cases are found to be sensible and physically interpretable. A powerful result of this study is that the image warp can be employed using a relatively sparse, preset regular grid without having to first identify features.
Original languageEnglish
Pages (from-to)1249-1262
JournalWeather and Forecasting
Volume25
Issue number4
Early online date5 Mar 2010
DOIs
Publication statusPublished - 1 Aug 2010

Keywords

  • forecast verification
  • precipitation
  • stochastic models
  • statistical forecasting

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