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Evaluating statistical downscaling methods for future temperature and precipitation projections in the Qilian mountains
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DOI：10.3389/frsen.2026.1890112.png)
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Abstract
En 中文
The Qilian Mountains; a crucial ecological security barrier and water conservation region in northwestern China; are highly sensitive to climate change. Reliable climate projections are essential for regional environmental management; yet the performance of statistical downscaling methods in this complex mountainous region remains inadequately evaluated. This study evaluates four statistical downscaling methods—Delta Change Method (DCM); Quantile Mapping (QM); Multiple Linear Regression (MLR); and Random Forest (RF)—using station-based observations (1951–2025) and outputs from 34 CMIP6 climate models. Validation results indicate that RF achieved the highest R2 and the lowest RMSE for both temperature and precipitation; with superior stability across models; scenarios; and stations. Based on RF downscaling; future climate projections under SSP1–2.6; SSP2–4.5; SSP3–7.0; and SSP5–8.5 indicate a persistent warming and moderate wetting trend throughout the 21st century. Temperature is projected to increase at rates of 0.03 °C–0.31 °C/decade; while precipitation is projected to increase by approximately 3.2%–8.1% by the end of the century; although inter-model uncertainty remains substantial. Future climate change also exhibits pronounced seasonal and spatial heterogeneity; characterized by winter-dominated warming; reduced summer precipitation but increased autumn–winter precipitation; and strong elevation-dependent responses concentrated in high-elevation areas. The 0 °C isotherm is projected to rise by approximately 100–400 m by the late 21st century. These findings highlight the applicability of RF downscaling for station-scale climate projections in the Qilian Mountains and provide scientific support for regional climate adaptation; water resource management; and ecosystem conservation.
Keywords:
temperature
random forest
precipitation
projection
statistical downscaling
Qilian Mountains
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3.7
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560
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993
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