Kilometer‐Scale (1‐km) Convection‐Permitting Simulations Over the Hindu Kush‐Himalayan Region: Processes of Winter Precipitation

Abstract

Kilometer‐scale (k‐scale) simulations, with explicit treatment of convection at sub‐grid scales, are useful for understanding precipitation characteristics. Such simulations with their high spatiotemporal resolution can be particularly valuable in complex topographic regions, such as the Hindu Kush Himalayas (HKH), where sparse observations and uncertainties in coarse‐resolution data sets pose challenges. This study evaluates an AMIP style k‐scale (1 km) simulation, initialized from the ECMWF IFS analysis, for winter precipitation (December 2018–February 2019) over the HKH region, with a focus on mean and extreme characteristics, elevation‐dependent variability, and diurnal precipitation cycles. The kilometer‐scale simulations were validated using available station observations and multiple high‐resolution gridded precipitation data sets, including gauge‐based, satellite‐derived, and reanalysis products. The model shows high fidelity to the observed station‐based precipitation magnitudes and realistically depicts the spatial distribution of precipitation, particularly the ridge‐valley variations, often missed in coarser products. In general, it aligns more with reanalysis data sets and closely matches station observations as well. Mean precipitation exhibits sensitivity to elevation, and the highest rates occur at about 2,500 m in most of the reference products (observations/reanalysis), which the k‐scale model represents well. The diurnal cycle depicts sub‐daily precipitation maxima in the local afternoon and early morning hours. The analysis for precipitation extremes indicates the model's close fidelity with reanalysis products in capturing higher‐intensity and prolonged precipitation events in the western Himalayas. Radiosonde profiles and atmospheric thermodynamic characteristics highlight a highly saturated and unstable environment during extremes, which is favorable for enhanced convective developments and heavy precipitation. The model captures these atmospheric conditions well and represents the localized variations and intensifications in valley wind flows during extremes, which are often missed in coarser‐resolution and parameterized ERA5 data. Our findings highlight the fidelity of this k‐scale AMIP‐style model over coarser‐resolution, parameterized models in resolving subgrid‐scale processes in the complex terrain regions of the HKH.