Nonparametric tests of extremes of daily maximum temperatures based on the breaking records: A case study in Seoul and Busan during 1961-2022

Nonparametric tests of extremes of daily maximum temperatures based on the breaking records: A case study in Seoul and Busan during 1961-2022

An observation in a time series is called an upper record if it is greater than all previous observations in the series. Also it is called a lower record than all previous observations in the series. Therefore, the analysis of record-breaking events is of interest in fields such as climatology, economics and sports. As an alternative to the classical extreme value theory, which are based on the fit of generalized extreme value (GEV) distribution, generalized Pareto (GP) distribution and Poisson processes, this work is based on the study of record-breaking events to analyze non-stationarity in the extremes. The contribution of this work is the use of the statistical tools developed by Castillo-Mateo et al. (2023) to assess and analyze the effect of global warming in the extreme and record breaking events using daily maximum temperature series in Seoul and Busan over 1961-2022. These test statistics consider the information based on the four different types of record, that is, forward upper, forward lower, backward upper and backward lower. Also, change point detection is implemented based on records.