The Human Factor: Increasing the Risk of Weather Extremes in Central Asia

Bias-adjusted and downscaled climate data are essential for regional impact studies. In some cases, a “counterfactual” baseline climate data that isolates the human-induced influences is also required for impact studies that focus on the anthropogenic influence. We examine how human activities have influenced the frequency and intensity of extreme temperature and precipitation events in Central Asia (CA) from 1960 to 2014. We use two sets of simulations from six climate models that are part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) and the Coupled Model Inter-comparison Project phase 6 (CMIP6). One set (labelled as hist-nat) includes only natural factors (solar and volcanic activity) and the other set (labelled as hist) includes both natural and human factors (such as greenhouse gas emissions). We bias-correct and statistically downscale these simulations using the Climatologies at high resolution for the earth’s land surface areas dataset (CHELSA) to a finer spatial resolution (0.25°× 0.25°) to better capture the regional climate variability and impacts. We find that human factors have increased the risk of extreme heat events by four times across most of CA in the hist simulations compared to the hist-nat simulations. We also find that human factors have enhanced the likelihood and magnitude of extreme precipitation events over CA in the hist simulations, especially over Kyrgyzstan and Tajikistan, where landslides and floods are common hazards. Our results suggest that human-induced climate change has contributed to more severe weather extremes over vulnerable regions of CA. Our high-resolution data set is publicly available and can be used for further studies on the causes and consequences of extreme events in CA.