Nonstationary Spatiotemporal Projection of Drought Across Seven Climate Regions of China in the 21st Century Based on a Novel Drought Index

Climate change is increasing drought frequency and severity, so projecting spatiotemporal drought evolution across climate zones is critical for drought mitigation. Model biases, choice of drought index, and neglecting CO2 effects on potential evapotranspiration (PET) add large uncertainties to future drought projections. We selected 10 global climate models (GCMs) that participated in the Coupled Model Intercomparison Project Phase 6, and downscaled model outputs using the Bias Correction and Spatial Downscaling (BCSD) method. We then developed a CO2-aware Standardized Moisture Anomaly Index (SZI[CO2]) and used a three-dimensional drought identification method to extract duration, area, and severity, then analyzed their spatiotemporal dynamics. To account for nonstationarity, Copula-based approaches were used to estimate joint drought probabilities with time-varying parameters. Projections indicate wetting in southern Northwest China, Inner Mongolia, and western Tibetan Plateau (reduced drought frequency, duration, intensity), while Central and Southern China show a drying trend in the 21st century. Three-dimensional drought metrics exhibit strong nonstationarity; nonstationary Log-Normal and Generalized extreme value distribution fit most regions best. Under equal drought-characteristic values, co-occurrence probabilities are higher under SSP5-8.5 scenarios than SSP2-4.5 scenarios, with the largest scenario differences over the Tibetan Plateau, Central and Southern China.