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<p>The complex terrain of the northwestern Himalayan mountainous states is highly susceptible to Heavy Rainfall Events (HREs). In terms of disaster preparedness and response, the situation worsens as the Numerical Weather Prediction (NWP) models fail to capture these HREs with adequate lead-time. The present study utilises the Weather Research and Forecasting (WRF) model, along with high-resolution land data assimilation (LDAS), to understand the dominant mechanisms that cause HRE events over the Himachal Pradesh and Uttarakhand states during August 12–16, 2023. Results suggest that, in the LDAS experiments, the better representation of soil moisture and evapotranspiration resulted in elevated near-surface relative humidity. This facilitates a lowering of horizontal wind speed, consequently increasing the residence time of moisture and the integrated water vapour (IWV) in the lower level. Additionally, the Lagrangian trajectory analysis reveals that the Arabian sea is major source of integrated vapour transport (IVT) and it is more prominent in the low-lying districts. The elevated moisture convergence in the lower levels facilitates stronger convective updrafts and consequent upper-level divergence, thereby strengthening the upper-level trough during the peak rainfall days (Days 2 and 3). This vertical coupling provides a precise depiction of moist convection over the region, thereby contributing to an enhancement in the accuracy of rainfall prediction in LDAS compared to control experiments (CNTL). The relative vorticity tendency analysis over two heavy rainfall stations, i.e., Bilaspur and Dharamshala, further confirms the presence of stronger lower level positive vorticity tendencies in LDAS, facilitating accurate rainfall prediction compared to CNTL.</p>

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Investigation of the land and atmospheric processes associated with the heavy rainfall events over the complex terrains of the Northwestern Himalayan States of India

  • 期刊论文

  • 发表日期：

    2026年2月3日

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  • Chandra Shekhar Satapathy,
  • Sandeep Pattnaik,
  • Vijay Vishwakarma,
  • Sankhasubhra Chakraborty,
  • R. Jenamani

摘要

The complex terrain of the northwestern Himalayan mountainous states is highly susceptible to Heavy Rainfall Events (HREs). In terms of disaster preparedness and response, the situation worsens as the Numerical Weather Prediction (NWP) models fail to capture these HREs with adequate lead-time. The present study utilises the Weather Research and Forecasting (WRF) model, along with high-resolution land data assimilation (LDAS), to understand the dominant mechanisms that cause HRE events over the Himachal Pradesh and Uttarakhand states during August 12–16, 2023. Results suggest that, in the LDAS experiments, the better representation of soil moisture and evapotranspiration resulted in elevated near-surface relative humidity. This facilitates a lowering of horizontal wind speed, consequently increasing the residence time of moisture and the integrated water vapour (IWV) in the lower level. Additionally, the Lagrangian trajectory analysis reveals that the Arabian sea is major source of integrated vapour transport (IVT) and it is more prominent in the low-lying districts. The elevated moisture convergence in the lower levels facilitates stronger convective updrafts and consequent upper-level divergence, thereby strengthening the upper-level trough during the peak rainfall days (Days 2 and 3). This vertical coupling provides a precise depiction of moist convection over the region, thereby contributing to an enhancement in the accuracy of rainfall prediction in LDAS compared to control experiments (CNTL). The relative vorticity tendency analysis over two heavy rainfall stations, i.e., Bilaspur and Dharamshala, further confirms the presence of stronger lower level positive vorticity tendencies in LDAS, facilitating accurate rainfall prediction compared to CNTL.