Investigating the relationships between precipitable water vapor estimations and heavy rainfall over the Eastern Pacific Ocean and Ecuadorian regions

Abstract

Among the weather phenomena, rainfall is difficult to forecast, despite the theoretical and technical challenges inherently related to its prediction, its impact in economic and everyday activities, clearly justify its study. Numerical Weather Prediction Models are widely used to predict rainfall, such as the Weather Research & Forecasting Model (WRF), However, they underperform when is set to predict intense events and when working with complex and steep topographies. Recent studies have proposed the estimation of Precipitable Water Vapor PWV, as a tool that can help predict and understand the mechanisms that trigger intense rainfall. PWV is mainly sourced from satellite products and from indirectly measurements which derive it through the delay of the Global Navigation Positioning System (GNSS) signals quite accurately. Thus, the present work studies the relationship between intense rain and satellite sourced PWV over the ocean, the relationship of PWV-GNSS over the Coast, Sierra and Amazon of Ecuador, and the comparison of the PWV-GNSS with the data modeled in WRF. As main results, we point an empirical model between the satellite PWV and the maximum values of rainfall over the ocean. In addition, PWV-GNSS loading and unloading periods related to the diurnal cycle of rainfall over the land, and relationships with intense rain events were identified; and finally, the main discrepancies between the observed PWV-GNSS data and rainfall with WRF modeled data over areas of the Equatorial Andes.