In recent years, forest fire activities have increased in frequency and intensity over the Indian Himalayan region. Year 2024 witnessed numerous fires spread across the Himalayan states of India, causing devastating economic and environmental impacts. The sparse observational network across the Himalayas significantly limits the availability of real-time data, thereby constraining the timely dissemination of wildfire early warnings. This study elaborates on utilising an NWP model, such as the Weather Research and Forecasting Model, for the simulation of fire weather variables for the 2024 summer fire season across the northwestern Himalayan states. A very high-resolution WRF model is configured with the NCEP-FNL reanalysis dataset as the initial and boundary conditions, and simulations are carried out to reconstruct high-resolution fire weather conditions during the 2024 fire weather season across 24 identified fire clusters. The analysis suggests that the two major fire weather indicators (1) Vapour Pressure Deficit and (2) Fire weather indices from the Canadian Fire Danger Rating System blended with NWP model simulations could be a potential tool in identifying fire weather conditions for data sparse complex terrains and subsequently issuing fire weather alerts on a daily basis where the current Fire Danger rating system operates at 10-day intervals.