Abstract
Understanding future hydroclimatic variability in arid regions is essential for sustainable development and climate adaptation. This study uses bias-corrected CMIP6 daily climate projections, derived by applying the BCCAQ method to ERA5 reanalysis and surface station data, to investigate the spatiotemporal evolution of key meteorological variables and drought conditions over Xinjiang during 2031–2060 under three SSP scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5). Results reveal significant warming trends across all scenarios, with stronger increases under high-emission pathways (up to 0.76°C/10a under SSP585), accompanied by enhanced potential evapotranspiration (PET) and widespread aridification. While precipitation shows an upward trend under SSP370 and SSP585, the warming-induced evaporative demand dominates, particularly in southern Xinjiang and the eastern basins. The SPEI index indicates an intensifying drought risk, with spatial patterns characterized by a “dry south–wet north” gradient and stronger basin aridification relative to mountainous regions. Moreover, this study highlights the physical mechanism linking temperature rise, enhanced PET, and intensified drought, providing robust empirical evidence for regional climate risk assessment and adaptation strategies in Central Asia. Despite methodological advantages, limitations associated with spatial resolution and structural uncertainty of GCMs persist, suggesting the need for integrating regional climate models (RCMs) and extreme event analyses in future research.
Related Publications
The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500
Abstract. Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has ...
Publication Info
- Year
- 2025
- Type
- article
- Volume
- 16
- Citations
- 0
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.3389/fpls.2025.1679735