资源环境科技发展态势分析平台

Understanding dynamical changes in climate extremes are vital in predicting extreme climate events and lowering their associated impacts on the environment and society. The objectives of this study is to analyze the spatiotemporal variations in temperature extremes and their association with selected atmospheric circulation indices. We use daily maximum temperature (TX) and minimum daily temperature (TN) data for five glaciers in the Hunza district of central Karakoram for the period 1982–2019. We validate the European Reanalysis (ERA5) data with available observed and in-situ data before further analysis. A total of eight indices based on maximum and minimum temperatures are chosen. They include maximum of TX, minimum of TN, three warm indices, and three cold indices. The Mann-Kendall method and linear trend analysis were used to examine the trends, and Pearson correlation analysis was used to analyze the correlation between the temperature extremes and different atmospheric circulation patterns. The warm indices, including the number of warm nights, warm days, and Warm Spell Duration Index (WSDI), and TN and TX, showed increasing trends in the central Karakoram from 1982 to 2019. On the other hand, cold indices, including the number of cold nights, cold days, and Cold Spell Duration Indicator (CSDI), showed decreasing trends. Warm indices and TX showed significant positive correlations with atmospheric circulations. The Arctic Oscillation index (AO) displayed significant correlations with the warm indices (p < 0.01) and negative correlations with the cold indices. The results also showed that warm indices and extreme indices had no correlations with the ENSO index. These findings will provide useful insights in predicting extreme climate events and taking measures to reduce their associated impacts on the water resources in the Karakoram.