Detecting Nonstationary Spatiotemporal Trends in Rainfall and Temperature Over Pakistan

Climate change has caused a significant change in temperature and rainfall patterns across the globe. This study explores the occurrence of annual and seasonal change points in Pakistan's rainfall and temperature using spatiotemporal trends analysis (1961–2017). Non-parametric tests including the Modified Mann-Kendall (MMK) (trend detection), Theil-Sen's slope estimator (magnitude of change), and the Pettitt-Mann-Whitney U test (PMW) (change point) were employed on non-autocorrelated and autocorrelated time series for 29 stations across Pakistan. Annual temperature exhibited a significant upward trend (p < 0.05) at eight stations. Similar trends were evident in post-monsoon (11 stations), pre-monsoon (10 stations), and winter (10 stations) at the 95% confidence level. Overall, annual temperature increased by an estimated 1.35% during 1961–2017. The year 1989 was identified as the most probable change point for both annual and seasonal temperatures. Notably, an increasing temperature trend persisted across all 29 stations throughout both periods (1961–1989 and 1990–2017) except pre-monsoon in the latter half. While total annual rainfall showed a 5.62% increase, only three stations displayed a statistically significant upward trend (p < 0.05). Similar patterns emerged for post-monsoon (1 station), pre-monsoon (2 stations), and winter (4 stations). The year 1994 was pinpointed as the most likely change point for annual and seasonal rainfall. Understanding these spatiotemporal trends is crucial for formulating effective climate change adaptation and mitigation strategies in Pakistan.