Samantray et al. (2025) Studying the dynamics of cloudburst events over Indian Himalayan region using model simulation

Identification

• Journal: Modeling Earth Systems and Environment
• Year: 2025
• Date: 2025-12-02
• Authors: Payoshni Samantray, K. C. Gouda
• DOI: 10.1007/s40808-025-02680-w

Research Groups

• CSIR Fourth Paradigm Institute, Bangalore, India
• Department of Physics, Visvesvaraya Technological University, Belagavi, India
• Academy of Scientific and Innovative Research, Ghaziabad, India

Short Summary

This study utilized a high-resolution Weather Research and Forecasting (WRF) model to simulate and analyze six cloudburst events in the Indian Himalayan Region (IHR) during the 2022 monsoon season. The model effectively replicated the spatial and temporal distribution of heavy rainfall, demonstrating a strong correlation with India Meteorological Department (IMD) data and providing insights into the dominant atmospheric conditions driving these extreme events.

Objective

• To study the dominant atmospheric conditions leading to cloudburst formation in the Indian Himalayan Region (IHR).
• To compare WRF model simulations of cloudburst events with observed datasets.
• To identify spatial and temporal biases in WRF simulations of cloudbursts.
• To contribute to the improvement of modeling techniques for disaster preparedness and mitigation.

Study Configuration

• Spatial Scale: Indian Himalayan Region (IHR), specifically Jammu & Kashmir, Himachal Pradesh, and Uttarakhand. The WRF model was configured with a single high-resolution domain of 3 km horizontal grid spacing.
• Temporal Scale: Monsoon season of 2022, focusing on six representative cloudburst events. Each event was simulated for 72 hours (48 hours lead time from the event, with model simulation until the next day of the event), providing hourly outputs.

Methodology and Data

• Models used:
  • Weather Research and Forecasting (WRF) model version 4.3.3 (Advanced Research WRF - ARW).
  • Parameterization schemes:
    • Cumulus: Kain-Fritsch (new Eta)
    • Planetary Boundary Layer (PBL): Yonsei University (YSU) scheme
    • Microphysics: WSM 6-class simple ice scheme
    • Longwave Radiation: Rapid Radiative Transfer Model (RRTM)
    • Shortwave Radiation: Dudhia scheme
    • Land-atmosphere interactions: MM5 Monin–Obukhov scheme
• Data sources:
  • Initial and Boundary Conditions: NCEP-FNL (Final) reanalysis data (6-hourly, 1° x 1° grid).
  • Validation Data:
    • India Meteorological Department (IMD) daily observed rainfall data.
    • Global Precipitation Measurement Mission (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) (0.1° spatial resolution, hourly).
    • CPC MORPHing technique (CMORPH) Climate Data Record (CDR) (high-resolution global precipitation analysis).

Main Results

• The WRF model demonstrated strong performance in simulating cloudburst events, particularly when validated against IMD data, showing a correlation coefficient (CC) of 0.84, a Root Mean Square Error (RMSE) of 45.07 mm, a bias of -9.5 mm, and a Critical Success Index (CSI) of 0.5.
• Model performance varied with satellite-based datasets:
  • GPM: CC = -0.45, RMSE = 137.47 mm, bias = -11.75 mm, CSI = 0.25.
  • CMORPH: CC = -0.49, RMSE = 119.03 mm, bias = +36.5 mm, CSI = 0.
• Key atmospheric mechanisms identified as conducive to cloudbursts:
  • Convective Available Potential Energy (CAPE): Ranged from 650 to 1300 J/kg, consistently exceeding the convective threshold of 500 J/kg.
  • Convective Inhibition Energy (CINE): Remained low (< 50 J/kg), indicating minimal resistance to convective initiation.
  • Relative Humidity (RH): Mid-tropospheric levels often exceeded 75%, with some cases showing 80-100% humidity, indicating sustained moisture availability.
  • Outgoing Longwave Radiation (OLR): Values below 200 W/m² to 240 W/m², correlating with cold cloud tops and deep convective systems.
  • Vertical Wind Shear: Between 850 and 200 hPa varied from 7.7 to 15.4 m/s (15 to 30 knots), conducive to convective organization. U-component shear between 500 and 950 hPa reached 12-25 m/s.
  • Vorticity: Positive vorticity at 500 hPa (1.2 × 10⁻⁵ to 2.0 × 10⁻⁵ s⁻¹) and low-level (925 hPa) relative vorticity (8 × 10⁻⁵ to 15 × 10⁻⁵ s⁻¹) frequently coincided with CAPE maxima and topographic convergence zones.
  • Wind Patterns: Low-level easterly/south-easterly convergence and upper-level subtropical jet streams (up to 23 m/s) created strong vertical wind shear and orographic lifting, intensifying precipitation.
• The model generally captured the intensity and location of cloudburst events, though spatial shifts of approximately 0.5° to 1° (40-100 km) were observed in some simulations compared to IMD data.

Contributions

• This study provides a high-resolution (3 km) regional modeling approach using the WRF model to simulate and understand cloudburst events over the complex terrain of the Indian Himalayan Region.
• It offers a comprehensive analysis of the atmospheric dynamics (CAPE, CINE, RH, OLR, wind shear, vorticity) associated with six specific cloudburst events, contributing to a deeper understanding of their formation mechanisms.
• The research rigorously validates model outputs against multiple observational datasets (IMD, GPM, CMORPH), highlighting the model's strengths and limitations with different data sources.
• The findings contribute to enhancing predictive modeling capabilities for cloudbursts, which is crucial for improved disaster preparedness and mitigation strategies in hazard-prone mountainous regions.

Funding

• WOS scheme of DST, Government of India
• National Mission on Himalayan Studies (NMHS) of Ministry of Environment, Forest and Climate Change (MoEFCC), Government of India (grant no: GBPNI/NMHS-2019–20/MG/315)
• CSIR Mission Mode Project (MMP055202)

Citation

@article{Samantray2025Studying,
  author = {Samantray, Payoshni and Gouda, K. C.},
  title = {Studying the dynamics of cloudburst events over Indian Himalayan region using model simulation},
  journal = {Modeling Earth Systems and Environment},
  year = {2025},
  doi = {10.1007/s40808-025-02680-w},
  url = {https://doi.org/10.1007/s40808-025-02680-w}
}