Climate Forecasting Models for Precise Management Using Extreme Value Theory

The objective of this research was to develop a mathematical and statistical model for long-term prediction. The Extreme Value Theory (EVT) was applied to analyze the appropriate distribution model by using the peak-over-threshold approach with Generalized Pareto Distribution (GPD) to predict daily extreme precipitation and extreme temperatures in eight provinces located in the upper northeastern region of Thailand. Generally, each province has only ۱–۲ meteorological stations, so spatial analysis cannot be performed comprehensively. Therefore, the reanalysis data were obtained from the NOAA Physical Sciences Laboratory. The precipitation data were used for spatial analysis at the level of ۲۵ square kilometers, which comprises ۷۱ grid points, whereas the temperature data were used for spatial analysis at the level of ۵۰ square kilometers, which includes ۱۹ grid points. According to the analysis results, GPD was appropriate for the goodness of fit test with Kolmogorov-Smirnov Statistics (KS Test) according to the estimation for the return level in the annual return periods of ۲ years, ۵ years, ۱۰ years, ۲۵ years, ۵۰ years, and ۱۰۰ years, indicating the areas with daily extreme precipitation and extreme temperatures. The analysis results would be useful for supplementing decision-making in planning to cope with risk areas as well as in effective planning for resources and prevention. Doi: ۱۰.۲۸۹۹۱/CEJ-۲۰۲۳-۰۹-۰۷-۰۱۴ Full Text: PDF

Keywords:

Extreme Value Theory , Generalized Pareto Distribution , Precipitation , Temperature.