Yang et al. (2025) Projected hydroclimatic changes in Xinjiang under bias-corrected CMIP6 scenarios

Identification

• Journal: Frontiers in Plant Science
• Year: 2025
• Date: 2025-12-09
• Authors: Xu Yang, Shao‐Fen Tian, Xin Cong, Mengxin Bai, Juncheng Zhang
• DOI: 10.3389/fpls.2025.1679735

Research Groups

• School of Geography, Liaoning Normal University, Dalian, Liaoning, China
• Center for Human Settlements, Liaoning Normal University, Dalian, Liaoning, China
• Research Base of Urban Agglomeration in Central-South Liaoning of China Urban Agglomeration Research Base Alliance, Liaoning Normal University, Dalian, Liaoning, China
• Liaoning Research Base for Synergistic Development of Human Settlements and Talents, Dalian, Liaoning, China
• Beijing Municipal Climate Center, Beijing Meteorological Service, Beijing, China
• Meteorological Bureau of Dashiqiao, Yingkou, China

Short Summary

This study projects future hydroclimatic changes in Xinjiang (2031–2060) using bias-corrected CMIP6 scenarios, revealing significant warming, increased potential evapotranspiration, and intensified drought risk, particularly in southern Xinjiang and eastern basins.

Objective

• To investigate the spatiotemporal evolution of key meteorological variables (temperature, precipitation, wind speed, relative humidity, downward shortwave radiation, potential evapotranspiration) and drought conditions (using SPEI) in Xinjiang during 2031–2060 under three CMIP6 Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5), utilizing bias-corrected climate projections.

Study Configuration

• Spatial Scale: Xinjiang, Northwest China, with a focus on a 10 km spatial resolution for the final bias-corrected dataset.
• Temporal Scale: Historical period (1961–2020) for validation and comparison, with future projections focusing on 2031–2060.

Methodology and Data

• Models used:
  • Multi-model ensemble of ten CMIP6 global climate models (CNRM-CM6-1, CNRM-ESM2-1, CanESM5, EC-Earth3, GFDL-ESM4, IPSL-CM6A-LR, MIROC6, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL).
  • Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ) method for bias correction and downscaling.
  • Penman-Monteith equation for potential evapotranspiration (PET) calculation.
  • 3-month Standardized Precipitation Evapotranspiration Index (SPEI-3) for drought analysis.
• Data sources:
  • China National Ground Meteorological Station Daily Meteorological Elements Dataset (V3.0) (105 stations in Xinjiang, 1961–2020).
  • ERA5 reanalysis data (0.25° × 0.25° spatial resolution).
  • Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) bias-corrected CMIP6 datasets (0.5° × 0.5° resolution).
  • Three-Dimensional Variational Xinjiang Meteorological Forcing Dataset (3DVAR-MF-XJ) (10 km spatial resolution, 1-hour temporal resolution, 1961–2014).

Main Results

• Xinjiang is projected to experience significant warming during 2031–2060, with rates of 0.20 °C/decade (SSP126), 0.58 °C/decade (SSP370), and 0.76 °C/decade (SSP585), intensifying under higher emission pathways and more pronounced in basins.
• Precipitation shows insignificant changes under SSP126 (slight reductions in northern Xinjiang basin), but continuous increases (>3.8 mm/decade) under SSP370 and SSP585, particularly in northern Xinjiang and the Tianshan region.
• Wind speeds are projected to increase by 0.17–0.26 m/s (2031–2060 relative to 1991–2020), with stable trends across scenarios and most notable increases in western mountainous regions and northern Tianshan.
• Relative humidity changes are slight (0.21–0.46%) and stable overall; SSP370 shows a wetting trend in basins, while northern Xinjiang becomes drier under SSP126 and SSP585.
• Downward shortwave radiation declines under SSP370 (-0.058 MJ/(m²·day)/decade) and SSP585 (-0.046 MJ/(m²·day)/decade), with more pronounced decreases in mountainous areas, while SSP126 projects a slight increase.
• Potential evapotranspiration (PET) consistently increases across all scenarios (21.5, 42.9, and 63.3 mm/decade for SSP126, SSP370, and SSP585, respectively), strengthening with emission intensity, especially in basins and eastern Xinjiang.
• The Standardized Precipitation Evapotranspiration Index (SPEI) shows decreasing trends (-0.112/decade for SSP126, -0.181/decade for SSP370, -0.236/decade for SSP585), indicating an increasing risk of aridification across Xinjiang.
• The Tarim Basin in southern Xinjiang and the eastern part of the region are identified as high-risk hotspots for drought, with severity intensifying under higher emission pathways.
• The study highlights a dominant "warming–enhanced evapotranspiration–intensified drought" pathway and a distinct hydroclimatic divergence characterized by a "wet north–dry south, intensified aridity in basins, and relatively moderated changes in mountainous areas."

Contributions

• First systematic application of the BCCAQ bias correction method in the arid zone of Xinjiang, significantly improving the fidelity of climate simulations over regions with complex topography.
• Integrates multiple meteorological variables (temperature, precipitation, wind speed, relative humidity, downward shortwave radiation, potential evapotranspiration) into the assessment of the SPEI, moving beyond precipitation-centered analyses and providing new insights into the mechanisms governing future hydroclimatic variability.
• Establishes a robust climatic foundation for agricultural development, water resource management, and vegetation adaptation in Xinjiang's arid regions.
• Delivers essential data support and scientific evidence for broader applications in botany and agricultural ecology.

Funding

• National Natural Science Foundation of China (Grant Nos. 42305055, 42201221, and 42471246)
• Special Fund for Basic Scientific Research Business Expenses of Universities in Liaoning Province (Grant No. LJ112410165045)
• Natural Science Foundation of Liaoning Province (Grant No. 2023-MS-254)
• General Research Project on the Economic and Social Development of Liaoning Province (Grant No. 2025lslybwzzkt-167)
• Liaoning Province Social Science Planning Fund Project (Grant No. L22CJY016)
• High-End Cultivation Project of Liaoning Normal University (Grant No. 25GDW001)

Citation

@article{Yang2025Projected,
  author = {Yang, Xu and Tian, Shao‐Fen and Cong, Xin and Bai, Mengxin and Zhang, Juncheng},
  title = {Projected hydroclimatic changes in Xinjiang under bias-corrected CMIP6 scenarios},
  journal = {Frontiers in Plant Science},
  year = {2025},
  doi = {10.3389/fpls.2025.1679735},
  url = {https://doi.org/10.3389/fpls.2025.1679735}
}