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<p>The Western Himalaya exhibits strong elevation-dependent climate gradients that are inadequately resolved by coarse-resolution Global Climate Models (GCMs). To enhance the representation of terrain-controlled processes, high-resolution (9&#xa0;km) dynamical downscaling was performed using the Weather Research and Forecasting (WRF) model. This simulation was driven by Coupled Model Intercomparison Project Phase 6 (CMIP6) data from the bias corrected high-resolution configuration of Max Planck Institute Earth System Model (MPI-ESM-HR) model for the 1985–2014 period. Evaluation of the resulting simulation was conducted using India Meteorological Department (IMD) precipitation observations and Indian Monsoon Data Assimilation and Analysis (IMDAA) temperature fields, with further benchmarking provided against the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 Land dataset (ERA5-Land). The spatial distribution of precipitation is well represented by the WRF simulation, including monsoon-dominated south–north gradients and winter precipitation associated with western disturbances. Although domain-mean annual biases are small, elevation-dependent analysis reveals systematic overestimation of winter precipitation above ~ 3000&#xa0;m. Extreme precipitation exhibits a pronounced non-monotonic vertical structure, with 95th and 99th percentile intensities peaking at mid-elevations (~ 1500–2500&#xa0;m), consistent with orographic uplift and subsequent moisture depletion at higher elevations. The downscaled simulation captures this terrain-controlled organization while moderately intensifying upper-tail events within the mid-elevation orographic precipitation belt in the Western Himalaya. Temperature fields display realistic spatial gradients and environmental lapse rates comparable to reanalysis estimates, indicating thermodynamic consistency across elevation bands. Relative comparison with ERA5-Land further highlights the added value of high-resolution dynamical downscaling in complex terrain. The results demonstrate that CMIP6-driven regional downscaling effectively resolves elevation-dependent mean and extreme climate structure over the Western Himalaya, providing a physically consistent high-resolution baseline for subsequent analyses of projected climate change under the Shared Socioeconomic Pathways SSP2-4.5 and SSP5-8.5 scenarios.</p>

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CMIP6-driven high-resolution WRF downscaling over the Western Himalaya: elevation-dependent structure of mean and extreme climate

  • 期刊论文

  • 发表日期：

    2026年7月9日

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  • Kuldeep Sharma,
  • Deepak Singh Bisht,
  • Vishal Singh,
  • Sahidul Islam,
  • Ashwini Ranade,
  • Mohammad Sajeed,
  • Surjeet Singh

摘要

The Western Himalaya exhibits strong elevation-dependent climate gradients that are inadequately resolved by coarse-resolution Global Climate Models (GCMs). To enhance the representation of terrain-controlled processes, high-resolution (9 km) dynamical downscaling was performed using the Weather Research and Forecasting (WRF) model. This simulation was driven by Coupled Model Intercomparison Project Phase 6 (CMIP6) data from the bias corrected high-resolution configuration of Max Planck Institute Earth System Model (MPI-ESM-HR) model for the 1985–2014 period. Evaluation of the resulting simulation was conducted using India Meteorological Department (IMD) precipitation observations and Indian Monsoon Data Assimilation and Analysis (IMDAA) temperature fields, with further benchmarking provided against the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 Land dataset (ERA5-Land). The spatial distribution of precipitation is well represented by the WRF simulation, including monsoon-dominated south–north gradients and winter precipitation associated with western disturbances. Although domain-mean annual biases are small, elevation-dependent analysis reveals systematic overestimation of winter precipitation above ~ 3000 m. Extreme precipitation exhibits a pronounced non-monotonic vertical structure, with 95th and 99th percentile intensities peaking at mid-elevations (~ 1500–2500 m), consistent with orographic uplift and subsequent moisture depletion at higher elevations. The downscaled simulation captures this terrain-controlled organization while moderately intensifying upper-tail events within the mid-elevation orographic precipitation belt in the Western Himalaya. Temperature fields display realistic spatial gradients and environmental lapse rates comparable to reanalysis estimates, indicating thermodynamic consistency across elevation bands. Relative comparison with ERA5-Land further highlights the added value of high-resolution dynamical downscaling in complex terrain. The results demonstrate that CMIP6-driven regional downscaling effectively resolves elevation-dependent mean and extreme climate structure over the Western Himalaya, providing a physically consistent high-resolution baseline for subsequent analyses of projected climate change under the Shared Socioeconomic Pathways SSP2-4.5 and SSP5-8.5 scenarios.