Sensitivity Analysis of Start Point of Extreme Daily Rainfall Using CRHUDA and Stochastic Models

Abstract

Forecasting extreme precipitation is one of the basic actions of warning systems in Latin America and the Caribbean (LAC). With thousands of economic losses and severe damage caused by floods in urban areas, hydrometeorological monitoring is a priority in most countries in the LAC region. The monitoring of convective precipitation, cold fronts, and hurricane tracks are the most demanded technological developments for early warning systems in the region. However, predicting and forecasting the onset time of extreme precipitation is a subject of life-saving scientific research. Developed in 2019, the CRHUDA (Crossing HUmidity, Dew point, and Atmospheric pressure) model provides insight into the onset of precipitation from the Clausius–Clapeyron relationship. With access to a historical database of more than 600 storms, the CRHUDA model provides a prediction with a precision of six to eight hours in advance of storm onset. However, the calibration is complex given the addition of ARMA(p,q)-type models for real-time forecasting. This paper presents the calibration of the joint CRHUDA+ARMA(p,q) model. It is concluded that CRHUDA is significantly more suitable and relevant for the forecast of precipitation and a possible future development for an early warning system (EWS).