Kilometer-Scale Convection-Permitting Simulations in Representing Winter Precipitation over the Indian Himalayas

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 topographies like the Hindu Kush Himalayas (HKH), where sparse observations and uncertainties in coarse-resolution datasets pose challenges. This study evaluates a regional AMIP-style k-scale (1 km) simulation, initialised from the ECMWF IFS analysis, for winter mean and extreme precipitation (December 2018-February 2019) in the HKH region, using high-resolution gridded precipitation datasets from multiple sources. The model realistically depicts the spatial distribution of precipitation, particularly the ridge-valley variations, often missed in coarser products. In general, it aligns more with reanalysis datasets but closely matches station observations too. Mean precipitation exhibits sensitivity to elevation, and the highest rates occur at about 2500 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 favourable 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 added value of k-scale convection-permitting models over coarser-resolution, parameterized models in resolving subgrid-scale processes, particularly in complex terrains like the HKH, without the need for convective parameterization.