Evaluating the Performance and Applicability of Satellite Precipitation Products over the Rio Grande-San Juan Basin in Northeast Mexico

被引:0
作者
Vazquez-Rodriguez, Dariela A. [1 ]
Guerra-Cobian, Victor H. [1 ]
Bruster-Flores, Jose L. [1 ]
Fonseca, Carlos R. [2 ]
Yepez-Rincon, Fabiola D. [1 ]
机构
[1] Univ Autonoma Nuevo Leon, Fac Ingn Civil, Av Univ S-N, San Nicolas De Los Garza 66455, Mexico
[2] Univ Autonoma Estado Mexico, Inst Interamer Tecnol & Ciencias Agua, Km 14-5,Carretera Toluca Atlacomulco, Toluca 50120, Mexico
关键词
satellite-based precipitation products; CMORPH; IMERG; PERSIANN; Mexico; precipitation trend; spatial-temporal analysis; RAINFALL PRODUCTS; CMORPH;
D O I
10.3390/atmos15070749
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Accurate observation of precipitation data is crucial for hydrometeorological applications, requiring temporal and spatial precision. Satellite precipitation products offer a promising solution for obtaining precipitation estimates, facilitating long-term observations from global to local scales. However, assessing their accuracy compared to rain gauge observations is essential. This study aims to assess the accuracy and applicability of precipitation data from CMORPH, IMERG, and PERSIANN CCS in the Rio Grande-San Juan Basin in northeast Mexico. The evaluation of estimated precipitation was assessed using the Pearson and Spearman correlations, RMSE, MAE, and BIAS for both monthly and yearly averages. CMORPH showed minimal errors and low underestimation, while IMERG exhibited high correlations with consistent underestimation. PERSIANN CCS had lower correlations, significant overestimation, and higher errors. The Mann-Kendall (MK) test was used to determinate the precipitation trends of observed and estimated data. The observed data showed a significant positive trend in monthly averages, which is not reflected in the annual trend. Furthermore, negative annual trends were found in at least 10 stations across the basin. The application of satellite precipitation data yielded mixed outcomes, with CMORPH showing the highest level of agreement with the trend analysis results from rain gauge data. This demonstrates its reliability for weather and climate studies and suggests the potential for CMORPH to be used as an input in hydrological modeling.
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页数:20
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