Satellite-based precipitation (SBP) products with global coverage have the potential to overcome the lack of information in places where there are no rain gauges to perform hydrological analyses; however, it is necessary to evaluate the reliability of the SBP products. In this study, we evaluated the performance of the Climate Prediction Center morphing technique with corrected bias (CMORPH-CRT) product in 14 sites in Mexico. The evaluation was carried out using two approaches: (1) using categorical metrics that include indicators of probability of detection (POD), false alarm rate (FAR), critical success index (CSI), and frequency bias index (FBI); and (2) through statistical indicators such as the mean absolute error (MAE), root mean square error (RMSE), relative bias (RB), and correlation coefficient (CC). The analysis was carried out with two levels of temporal aggregation: 30 min and daily. The results indicate that the CMORPH-CRT product overestimates the number of precipitation events in most cases since FBI values greater than 1 in 78.6% of analyzed stations were obtained. Also, we obtained CC values in the range of 0.018 to 0.625, which implied weak to moderate correlations, and found that in all stations, the CMORPH-CRT product overestimates the precipitation (RB > 0).

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.

La estimación de periodos de retorno de caudales tiene una gran incertidumbre debido a la poca o nula información disponible de datos medidos en muchas cuencas de México y del mundo. Este estudio muestra una metodología para generar una serie de tiempo sintética de caudales con mayor longitud que los datos observados y poder estimar periodos de retorno de caudales con menor incertidumbre. Para esto, se usan datos de repronósticos climatológicos del ECMWF, con un tiempo de espera de 5 a 8 días, como insumos en un modelo hidrológico agregado y continuo en la cuenca del Río La Silla, en Monterrey, México. El modelo hidrológico fue calibrado manualmente, obteniendo un comportamiento satisfactorio. Los periodos de retorno estimados a partir de las series de tiempo sintéticas son menores, pero muestran un comportamiento similar y están en su mayoría dentro del rango de incertidumbre a los obtenidos con datos observados. Finalmente, la incertidumbre se redujo de 2 a 7 veces dependiendo del periodo de retorno comparado, y para un periodo de retorno de 1000 años, esta se redujo alrededor de un 60%.

Urban Heat Islands (UHIs) are a significant urban climate phenomenon, exacerbating energy demand, air pollution, and public health issues. This research highlights the relevance of this approach for civil engineering education, emphasizing the importance of incorporating sustainable studies into curricula. For civil engineers, learning about UHI is not just about understanding the science behind these phenomena but it’s about applying their expertise to create solutions that lead to sustainable, resilient, and livable cities. By integrating UHI mitigation strategies into their projects, civil engineers with their actions and decisions can potentially contribute to reducing the negative impacts of urbanization and climate change. This study employs the knowledge of the Junior Students from the Civil Engineer Program from the Universidad Autónoma de Nuevo León, to apply the Local Climate Zones (LCZ) framework at a Level 1 and a multiscale approach to examine UHI dynamics across various spatial building scales, that go from microscale (building and street level) to mesoscale (neighborhood and city level) and/or regional scales. The findings underscore the potential for Civil Engineers Junior Students to design climate-resilient infrastructures that address UHI impacts, fostering sustainable urban development and better climate adaptation strategies.