期刊名称：Advances in Statistical Climatology, Meteorology and Oceanography
印刷版ISSN：2364-3579
电子版ISSN：2364-3587
出版年度：2020
卷号：6
期号：1
页码：13-30
DOI：10.5194/ascmo-6-13-2020
出版社：Copernicus Publications
摘要：Abstract. Recently developed verification tools based on local wavelet spectra can isolate errors in the spatial structure of quantitative precipitation forecasts, thereby answering the question of whether the predicted rainfall variability is distributed correctly across a range of spatial scales. This study applies the wavelet-based structure scores to real numerical weather predictions and radar-derived observations for the first time. After tackling important practical concerns such as uncertain boundary conditions and missing data, the behaviour of the scores under realistic conditions is tested in selected case studies and analysed systematically across a large data set. Among the two tested wavelet scores, the approach based on the so-called map of central scales emerges as a particularly convenient and useful tool: summarizing the local spectrum at each pixel by its centre of mass results in a compact and informative visualization of the entire wavelet analysis. The histogram of these scales leads to a structure score which is straightforward to interpret and insensitive to free parameters like wavelet choice and boundary conditions. Its judgement is largely the same as that of the alternative approach (based on the spatial mean wavelet spectrum) and broadly consistent with other, established structural scores.
