基于 SPEI_PM 分析广西干旱时空变化及其与 ENSO 的关系.

Using monthly data from 19 meteorological stations in Guangxi Zhuang Autonomous region from 1961 to 2020, this study calculated the standardized precipitation evapotranspiration index (SPEI) based on the Penman-Monteith evapotranspiration model (SPEI_PM). The temporal and spatial variation of meteorological drought were analyzed via linear tendency estimation, and Mann-Kendall trend test. The correlation between El Niño-Southern Oscillation (ENSO) and meteorological drought in Guangxi was also explored by cross-correlation function, cross wavelet transform and wavelet coherence. The values for summer, autumn, and annual SPEI_PM from 1961 to 2020 exhibited a significant linear trend of increasing wetness over time. Annual and seasonal droughts throughout the region were predominately mild and moderate, with less frequent severe and extreme droughts. Spring droughts were concentrated in the central part of the region, summer droughts in the southwest, autumn droughts in the southeast and northeast, and winter droughts spread throughout the region. Annual droughts were concentrated in the northeast. The rate of drought occurrence as measured by the stations in Guangxi exhibited a distinctly chronological character. Large-scale droughts (especially severe and extreme droughts) across the entire region occurred most often in the 1960s, 1970s, and 2000s. The impact of ENSO on the meteorological drought in Guangxi was characterized by spatial heterogeneity. Correlation between the ocean Niño index (ONI) and meteorological drought was highest in the northeast and southeast, as well as the northwest. There was no significant correlation between drought and ONI in coastal areas and most southwestern parts of the region. As a typical example from meteorological stations in northeastern Guangxi, SPEI-3 and ONI at the Guilin Meteorological station showed interannual oscillation cycles of 16-48 months in the period 1962-1976, and 12-64 months in the period 1990-2019. These results can serve as a useful reference for future drought forecasting and assessment in Guangxi. [ABSTRACT FROM AUTHOR]