Development of an integrated multivariate trend-frequency analysis method: Spatial-temporal characteristics of climate extremes under global warming for Central Asia
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abstract
Temperature and precipitation are the two most critical climate variables and their extreme states have more severe impacts than average states on both human society and natural ecosystem. In this study, an integrated multivariate trend-frequency analysis (IMTFA) approach is developed for the risk assessment of climate extremes under the global warming. Through incorporating multiple time series analysis techniques (i.e., M-K test, Sen's slope estimator and Pettitt test) and copula function into a general framework, IMTFA is capable not only of analyzing the temporal trends and change points of extreme temperatures and precipitations, but also of quantifying their univariate and multivariate risks. IMTFA is applied to the Central Asia with considering a long-term (1881-2018) observation data. Our findings are: (i) significant wetting and warming trends were occurred in the Central Asia over past one hundred years, where 42.5%, 59.4% and 79.2% stations have change points for extreme precipitations, maximum and minimum temperatures, respectively; (ii) the occurrences of extreme climate events show obviously spatial heterogeneity, where the highest risks of meteorological drought, flood and frost events are occurred in the southwest, southeast and northeast regions, respectively; (iii) global warming significantly affects the intensities and frequencies of extreme precipitations and temperatures, and their univariate and multivariate risks are intensified in the most regions of Central Asia. The above findings can provide more valuable information for risk assessment and disaster adaptation of climate extremes in Central Asia.
