Understanding the dynamics of 2024 extreme heat event in India: spatial variability, hydrometeorological impacts, and model evaluation
File(s)
Published version
Author(s)
Verma, Akash
Khadke, Leena
Budakoti, Sachin
Type
Journal Article
Abstract
Heatwaves are becoming more intense, frequent, and prolonged due to global warming, posing significant risks to ecosystems and human societies. Despite their profound impact, detailed regional assessments of extreme heat events remain limited, particularly in India. This study addresses the gap by systematically investigating the 2024 extreme heat event in India. We evaluated the performance of various land surface schemes in simulating heat extremes using the Weather Research and Forecasting model and also assessed the accuracy of Global Forecast System (GFS) forecasts. Our analysis reveals a strong co-occurrence of drought and heat stress during the extreme heat event. This combination results in increased fire risk and negative impacts on vegetation productivity in regions affected by both drought and heat stress highlighting the severe consequences of this compound event. We compare different land surface models (RUC, Noah, Noah-MP, Noah-MP with dynamic vegetation, CLM) against India Meteorological Department (IMD) observations. We observe that Noah is optimal for reducing bias and RMSE, while Noah-MP with dynamic vegetation is most accurate for simulating extreme heat, with the highest hit rate and threat score for the 90th percentile threshold. Additionally, GFS maximum temperature forecasts for 1–3 day lead times perform well at short lead times, especially in Southern India but overestimate temperatures in heatwave-prone regions like the Indo-Gangetic Plains. Our findings highlight the importance of enhancing land surface models and forecasting systems to better predict extreme heat events, which is crucial for localized hazard and risk assessments and improving disaster management efficiency.
Date Issued
2025-08-15
Date Acceptance
2025-04-13
Citation
Atmospheric Research, 2025, 322
ISSN
0169-8095
Publisher
Elsevier
Journal / Book Title
Atmospheric Research
Volume
322
Copyright Statement
© 2025 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Subjects
CLIMATE EXTREMES
Compound extremes
DATA SET
Global forecast system
Heatwave
Land surface schemes
LEAD
Meteorology & Atmospheric Sciences
Physical Sciences
RAINFALL EVENT
RESOLUTION
Science & Technology
SIMULATION
SOIL-MOISTURE
WATER
WEATHER
Weather research and forecasting model
Publication Status
Published
Article Number
108154
Date Publish Online
2025-04-14