Performance-based projection of precipitation extremes over China based on CMIP5/6 models using integrated quadratic distance
The study analyzes the consistency of future precipitation extremes projected over China under moderate climate scenarios (RCP4.5 and SSP2-4.5) and extreme climate scenarios (RCP8.5 and SSP5-8.5), based on best models' ensembles for each extreme index (best-MME), best models' ensembles reg...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/740ce7d017784d0b8a0afbc0b7d9730f |
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| Sumario: | The study analyzes the consistency of future precipitation extremes projected over China under moderate climate scenarios (RCP4.5 and SSP2-4.5) and extreme climate scenarios (RCP8.5 and SSP5-8.5), based on best models' ensembles for each extreme index (best-MME), best models' ensembles regarding all indices (best-rankMME), and multi-model ensembles (MME). To select the best models, the integrated quadratic distance (IQD) combined with the Taylor skill score are used. This evaluation is a practical example of the benefits of using IQD to evaluate the models compared with root mean square error since the former is not sensitive to the similarity of the distribution's averages. All ensembles in each scenario consistently project the decrease of consecutive dry days (CDD) periods in western and northeast China, the increase of the number of days with heavy precipitation (R10mm) over the Qinghai-Tibet Plateau, and the increase of the precipitation intensity (SDII) in most of the Chinese territory. The moderate and extreme scenarios project very similar climate change patterns but more extreme scenarios show greater climate change signal magnitudes. In the case of the moderate scenarios, the most significant uncertainty relies on the CDD projections over southeastern China, where best-rankMME and MME project increasing CDD in the future whilst best-MME project decreasing CDD, although these changes are not statistically significant. Regarding extreme scenarios, the most significant uncertainty relies on the R10mm projections over southeastern China, where the best-MME CMIP5 projects decreasing R10mm (not statistically significant), whilst all the remaining ensembles project increasing values. |
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