Wavelet-based verification of the quantitative precipitation forecast

被引:12
|
作者
Yano, Jun-Ichi [1 ,2 ]
Jakubiak, Bogumil [3 ]
机构
[1] Meteo France, CNRM, 42 Av Coriolis, F-31057 Toulouse, France
[2] CNRS, F-31057 Toulouse, France
[3] Warsaw Univ, Interdisciplinary Ctr Math Modelling, Warsaw, Poland
关键词
Qualitative precipitation forecast (QPF); Verification; Wavelet; Object-based analysis; COAMPS; METHODS INTERCOMPARISON PROJECT; OBJECT-BASED VERIFICATION; CONVECTIVE CLOUD SYSTEMS; OPTICAL-FLOW; PART II; SCALE; MESOSCALE; MODEL; DECOMPOSITION; DISPLACEMENT;
D O I
10.1016/j.dynatmoce.2016.02.001
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
This paper explores the use of wavelets for spatial verification of quantitative precipitation forecasts (QPF), and especially the capacity of wavelets to provide both localization and scale information. Two 24-h forecast experiments using the two versions of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) on 22 August 2010 over Poland are used to illustrate the method. Strong spatial localizations and associated intermittency of the precipitation field make verification of QPF difficult using standard statistical methods. The wavelet becomes an attractive alternative, because it is specifically designed to extract spatially localized features. The wavelet modes are characterized by the two indices for the scale and the localization. Thus, these indices can simply be employed for characterizing the performance of QPF in scale and localization without any further elaboration or tunable parameters. Furthermore, spatially-localized features can be extracted in wavelet space in a relatively straightforward manner with only a weak dependence on a threshold. Such a feature may be considered an advantage of the wavelet-based method over more conventional "object" oriented verification methods, as the latter tend to represent strong threshold sensitivities. The present paper also points out limits of the so-called "scale separation" methods based on wavelets. Our study demonstrates how these wavelet-based QPF verifications can be performed straightforwardly. Possibilities for further developments of the wavelet-based methods, especially towards a goal of identifying a weak physical process contributing to forecast error, are also pointed out. (C) 2016 The Authors. Published by Elsevier B.V.
引用
收藏
页码:14 / 29
页数:16
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