Rol del Vapor de Agua Troposférico como Predictor de Lluvia Extrema

Rainfall, and especially heavy rainfall, is one of the most difficult natural phenomena to predict. The main limitations in its estimation involve the complexity of the fluid dynamics equations used by numerical models, as well as the appropriate inclusion of convective events, which are characterized by being brief (<12 h), localized to small areas (<100 km²), and convective. This research presents an empirical exponential model relating the maximum possible rainfall rates (P_Max) to the amount of tropospheric water vapor (TPW), described by: = a exp(∗W). This proposed methodology would improve the estimation of the intensity and location of these events. To this end, four years (2009–2012) of high-resolution 5.1 km x 5.1 km, 1.6-second TRMM satellite data from level 2A12 were studied over the Coastal El Niño or El Niño 2 area in the Pacific Ocean (0°–5°S and 90°W–81°W). The parameters found were a = 0.0109 and b = 0.1076, demonstrating the viability of TPW as a reliable locator of rainfall events and an intensity estimator. Thus, this work presents a complementary, non-dynamic contribution to rainfall modeling, based on observed high-resolution variables.