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Weather radar networks are an excellent tool for quantitative precipitation estimation (QPE), due to their high resolution in space and time, particularly in remote mountain areas such as the Tropical Andes. Nevertheless, reduction of the temporal and spatial resolution might severely reduce the quality of QPE. Thus, the main objective of this study was to analyze the impact of spatial and temporal resolutions of radar data on the cumulative QPE. For this, data from the world&rsquo, s highest X-band weather radar (4450 m a.s.l.), located in the Andes of Ecuador (Paute River basin), and from a rain gauge network were used. Different time resolutions (1, 5, 10, 15, 20, 30, and 60 min) and spatial resolutions (0.5, 0.25, and 0.1 km) were evaluated. An optical flow method was validated for 11 rainfall events (with different features) and applied to enhance the temporal resolution of radar data to 1-min intervals. The results show that 1-min temporal resolution images are able to capture rain event features in detail. The radar&ndash, rain gauge correlation decreases considerably when the time resolution increases (r from 0.69 to 0.31, time resolution from 1 to 60 min). No significant difference was found in the rain total volume (3%) calculated with the three spatial resolution data. A spatial resolution of 0.5 km on radar imagery is suitable to quantify rainfall in the Andes Mountains. This study improves knowledge on rainfall spatial distribution in the Ecuadorian Andes, and it will be the basis for future hydrometeorological studies.

Las redes de radar meteorológico son una excelente herramienta para la Estimación de Precipitación Cuantitativa (QPE), debido a su alta resolución en el espacio y tiempo, particularmente en áreas montañosas remotas como los Andes tropicales. Sin embargo, la reducción de la resolución temporal y espacial podría reducir la calidad de la QPE. El objetivo principal de este estudio fue analizar el impacto de la resolución espacial y temporal de los datos de radar en el QPE acumulativo. Para esto, se utilizaron los datos del radar meteorológico de banda X más alto del mundo ubicado en los Andes de Ecuador (cuenca del río Paute) y de una red de pluviómetros. Se evaluaron diferentes resoluciones temporales (1, 5, 10, 15, 20, 30 y 60 minutos) y espaciales (0,5, 0,25 y 0,1 km). Se validó un método de flujo óptico para once eventos de lluvia y se aplicó para mejorar la resolución temporal de los datos del radar en intervalos de 1 minuto. Los resultados muestran que las imágenes de resolución temporal de 1 minuto pueden capturar en detalle las características del evento de lluvia. La correlación radar-pluviómetro disminuye considerablemente cuando aumenta la resolución de tiempo (r de 0,69 a 0,31 para tiempos de 1 min a 60 min). No se encontraron diferencias significativas en el volumen total de agua (3%) calculado con datos de las tres resoluciones espaciales. La resolución espacial de 0,5 km en imágenes de radar es adecuada para cuantificar las precipitaciones en la montaña de los Andes. Weather radar networks are an excellent tool for Quantitative Precipitation Estimation (QPE), due to their high resolution in space and time, particularly in remote mountain areas such as the Tropical Andes. Nevertheless, the reduction of the temporal and spatial resolution might severely reduce the quality of QPE. Thus, the main objective of this study was to analyze the impact of spatial and temporal resolution of radar data on the cumulative QPE. For this, data from the world's highest X-band weather radar (4450 m a.s.l.) located in the Andes of Ecuador (Paute river basin) and from a rain gauge network were used. Different time resolution (1-, 5-, 10-, 15-, 20-, 30- and 60-min) and spatial resolutions (0.5, 0.25 and 0.1 km) were evaluated. An optical flow method was validated for eleven rainfall events (with different features) and applied to enhance the temporal resolution of radar data to 1-min intervals. The results show that 1-min temporal resolution images are able to capture in detail rain event features. The radar-rain gauge correlation decreases considerably when the time resolution increases (r from 0.69 to 0.31 for time resolution from 1-min to 60-min). No significant difference was found in the total water volume (3%) calculated with the three spatial resolutions data. Spatial resolution of 0.5 km on radar imagery is suitable to quantify rainfall in the mountain Andes. Magíster en Ecohidrología Cuenca