Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020GL089624 |
Evaluation of daily precipitation extremes in reanalysis and gridded observation‐based datasets over Germany | |
Guannan Hu; Christian L. E. Franzke | |
2020-08-30 | |
发表期刊 | Geophysical Research Letters |
出版年 | 2020 |
英文摘要 | Accurate and reliable gridded datasets are important for analyzing extreme weather and climate events. Specifically, these datasets should produce extreme value statistics that are close to reality. Here we use various statistical methods to evaluate the quality of four gridded data products in representing daily precipitation extremes. The data products are the COSMO‐REA6 regional reanalysis, the ERA5 global reanalysis, and the E‐OBS and HYRAS gridded observation‐based datasets. The statistical methods we use offer a thorough insight into the quality of the different datasets by providing temporal and spatial extreme value statistics of daily precipitation. Our results show that all datasets except HYRAS underestimate the magnitude of daily precipitation extremes when compared with weather station data. Moreover, the reanalysis datasets give generally worse extreme value statistics of daily precipitation than the gridded observation‐based datasets. In particular, the reanalysis datasets often fail in reproducing the accurate timing of observed daily precipitation extremes. |
领域 | 气候变化 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/293084 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | Guannan Hu,Christian L. E. Franzke. Evaluation of daily precipitation extremes in reanalysis and gridded observation‐based datasets over Germany[J]. Geophysical Research Letters,2020. |
APA | Guannan Hu,&Christian L. E. Franzke.(2020).Evaluation of daily precipitation extremes in reanalysis and gridded observation‐based datasets over Germany.Geophysical Research Letters. |
MLA | Guannan Hu,et al."Evaluation of daily precipitation extremes in reanalysis and gridded observation‐based datasets over Germany".Geophysical Research Letters (2020). |
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