Spatial-temporal Differentiation and Prediction of Extreme Weather Events and Vegetation Cover in Guizhou Province Under Climate Change

Due to global warming and human activities, the frequency of extreme climate events in karst areas has increased. Taking Guizhou Province as the study area, based on daily meteorological data from 31 national meteorological stations, SPOT/VGT NDVI dataset, and CMIP6 future climate model in Guizhou Province, this paper explores the effects of the future extreme climate on NDVI under different scenarios in Guizhou Province by comprehensively applying the extreme climate index and the normalized difference vegetation index (NDVI). Using the all-subsets regression method, it builds a multiple regression model to predict the variation characteristics of the future vegetation cover. The results show that between 2021 and 2100: ① the number of the extreme temperature events associated with the warm index all have an increasing trend, and the number of the extreme temperature events associated with the cold index all have a decreasing trend; ② in the future, under the trend of increasing total annual precipitation, the number of precipitation days in a year will increase, while the frequency of moderate rainy days will decrease, and the frequency of extreme precipitation may increase; ③under the SSP245 scenario and the SSP585 scenario, the vegetation cover in most parts of Guizhou Province will show an increasing trend.