Global precipitation datasets: implications for the study of extreme rainfall in mountain areas
Global climate datasets are a useful alternative to the spatiotemporal deficiency of gauged records. While the use of such products has widespread, their reliability for detection of extreme rainfall events in complex terrains has large uncertainties. This study evaluates the potential application o...
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| Autores principales: | , , |
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| Formato: | Artículo revista |
| Lenguaje: | Español |
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Facultad de Ciencias Exactas y Naturales y Agrimensura
2024
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| Materias: | |
| Acceso en línea: | https://revistas.unne.edu.ar/index.php/fce/article/view/7735 |
| Aporte de: |
| Sumario: | Global climate datasets are a useful alternative to the spatiotemporal deficiency of gauged records. While the use of such products has widespread, their reliability for detection of extreme rainfall events in complex terrains has large uncertainties. This study evaluates the potential application of global daily precipitation datasets for extreme rainfall assessment in the Sierras Australes Bonaerenses (Argentina). Two commonly used products are compared, Global Unified Gauge-Based Analysis of Daily Precipitation (CPC) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS). The precipitation indices Rx1d, Rx5d and SDII together with R13 and R25 were selected to explore the series performance relative to the magnitude and frequency of extremes, respectively. Results show low to moderate fit for the five indices, with greater inconsistencies in the intensity and frequency of events. Both magnitude and frequency are underestimated, with errors that increase with the rainfall potential of the stations. Spatial variations in fit and reliability are also evident, and result from the topographic contrast between mountain and extra-mountain sectors. Although CPC yields better results than CHIRPS, it is concluded that neither of both is suitable for assessment of extreme rainfall events and variability in the Sierras Australes Bonaerenses, due to limitations of scale and topography. |
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