Determination of Rainfall Probability Using Response Surface Method

Abstract

Forecasting rainfall is a major challenge, but it would be important as rainfall has a huge effect on the economy and food crises around the world. Currently, there are many mathematical models for weather forecast and for precipitation. Due to the phenomenon of desertification, precipitation forecasting is becoming increasingly important. In this article, a case study is presented on estimating the probability of rainfall using response surface method (RSM). After analyzing real data, a third-order surface model is presented for estimating the rainfall probability (the input parameters are the daily average temperature and the daily average humidity, and the output parameter is the summarized amount of the daily rainfall). It can be revealed that the presented method can be suitable for describing the real-time data used with sufficient accuracy. This study shows the efficiency and the applicability of RSM method for rain predicting.