Abstract

In order to analyze the temporal and spatial evolution of meteorological drought and explore its driving factors, the inland river basin of Inner Mongolia (IMIRB) was taken as a typical research area, the Standardized Precipitation Evapotranspiration Index (SPEI) of various scales was calculated, and the spatio-temporal trend change characteristics of meteorological drought were analyzed combined with the modified Mann–Kendall trend test (MMK). The typical meteorological drought events were analyzed by using the three-dimensional identification method, and the spatio-temporal evolution characteristics and dynamic evolution law of meteorological drought were analyzed comprehensively and accurately. The driving effects of Pacific Decadal Oscillation (PDO), North Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and sunspot on meteorological drought were investigated by using the cross wavelet method. The results are as follows: (1) with the increase of SPEI time scale, the frequency of meteorological drought decreased, but the duration and intensity of drought increased; (2) the trend was greatest in spring, with the largest number of areas showing a significant downward trend in SPEI, the strongest persistence in intensity, and significant aridification characteristics; (3) summer meteorological droughts had the largest area of high intensity drought but the smallest area of high frequency areas, and winter droughts had the smallest area of high intensity drought but the largest percentage of high frequency areas; (4) the meteorological drought event that occurred from April 2017 to December 2017 was the most serious, and reached its maximum value in June 2017, which mainly experienced five processes: occurrence—intensification—attenuation—re-intensification—extinction; (5) atmospheric circulation factor, sunspot, and meteorological drought of IMIRB were correlated, and ENSO had the greatest effect on drought. This study provides effective theoretical support for IMIRB drought prevention and disaster reduction.

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