| Autor: |
Chunrui Guo, Ning Ning, Hao Guo, Yunfei Tian, Anming Bao, Philippe De Maeyer |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Atmosphere, Vol 15, Iss 10, p 1254 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2073-4433 |
| DOI: |
10.3390/atmos15101254 |
| Popis: |
ERA5-Land is a valuable reanalysis data resource that provides near-real-time, high-resolution, multivariable data for various applications. Using daily precipitation data from 301 meteorological stations in the Yellow River Basin from 2001 to 2013 as benchmark data, this study aims to evaluate ERA5-Land’s capability of monitoring extreme precipitation. The evaluation study is conducted from three perspectives: precipitation amount, extreme precipitation indices, and characteristics of extreme precipitation events. The results show that ERA5-Land can effectively capture the spatial distribution patterns and temporal trends in precipitation and extreme precipitation; however, it also exhibits significant overestimation and underestimation errors. ERA5-Land significantly overestimates total precipitation and indices for heavy precipitation and extreme precipitation (R95pTOT and R99pTOT), with errors reaching up to 89%, but underestimates the Simple Daily Intensity Index (SDII). ERA5-Land tends to overestimate the duration of extreme precipitation events but slightly underestimates the total and average precipitation of these events. These findings provide a scientific reference for optimizing the ERA5-Land algorithm and for users in selecting data. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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