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Quantification of heat wave occurrences over the Indian region using long-term (1979–2017) daily gridded (0.5° × 0.5°) temperature data—a combined heat wave index approach

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Abstract

In the changing climate scenario, the changing heat wave frequency and magnitude have a direct impact on the agriculture, society, economic, and public health. Hence, development of easy and effective tools is essential for quantifying the heat wave incidences for better planning and management towards reducing the impacts of heat waves. In the present study, Climate Prediction Centre (CPC) global daily maximum temperature data along with the long-term normal data for the period 1979–2017 were used for quantification of heat wave conditions. Spatial and temporal sub-setting was carried out to restrict our study within the Indian region and March–July period, respectively. Based on heat wave criteria prescribed by the India Meteorological Department, different heat wave parameters, viz. frequency, magnitude, and extent, were estimated. A new approach, i.e. combined heat-wave index (CHI), was proposed to quantify the impact of heat wave in a profound manner. The efficacy of the overall method of assessing the impact of heat wave had increased by using this new approach. It was found that Rajasthan, Punjab Haryana, and Madhya Pradesh experienced high frequency as well as magnitude of heat wave, while it was lower in north-east, peninsular, and parts of northern India during our study period. The trend analysis for the heat wave parameters along with CHI was carried out over the Indian region during the last 39 years. The increasing trends were found over Rajasthan, Haryana, Punjab, East Madhya Pradesh, and Orissa, while places like Uttar Pradesh, Bihar, Chhattisgarh, Telangana, and Andhra Pradesh showed decreasing trend over the last 39 years. Peninsular and north-east India showed almost no trend regarding heat wave. Further, the month with the maximum contribution towards the seasonal heat wave and its deviation was also estimated. It was observed that the month of May was contributing most over parts of north-western and central India, while it was June in Punjab, Haryana, and western Rajasthan. Hence, the present methodology may be adopted for better planning and management of heat waves.

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Acknowledgments

We express our sincere thanks to Shri. Santanu Chowdhury, Director, National Remote Sensing Centre (NRSC), for his constant encouragement and suggestions. Guidance received from Dr. C. S. Jha (CGM, RCs) and Dr. D. Dutta (GM, RRSC-East) is duly acknowledged. We are also thankful to Climatic Prediction Center (CPC), NOAA, for providing gridded temperature data and India Meteorological Department (IMD) for providing the heat wave criteria. The authors are grateful to those anonymous reviewers for their constructive suggestions.

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Authors and Affiliations

  1. Regional Remote Sensing Centre-East, National Remote Sensing Centre, Kolkata, India

    Prabir Kumar Das, Chandrasekar Kamalakannan, Goru Srinivasa Rao & Soumya Bandyopadhyay

  2. Symbiosis Institute of Geoinformatics, Pune, India

    Ushashi Podder

  3. Teri School of Advanced Studies, Vasant Kunj, New Delhi, India

    Rituparna Das

  4. National Remote Sensing Centre, Hyderabad, India

    Uday Raj

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  1. Prabir Kumar Das
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  2. Ushashi Podder
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Correspondence to Prabir Kumar Das.

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Das, P.K., Podder, U., Das, R. et al. Quantification of heat wave occurrences over the Indian region using long-term (1979–2017) daily gridded (0.5° × 0.5°) temperature data—a combined heat wave index approach. Theor Appl Climatol 142, 497–511 (2020). https://doi.org/10.1007/s00704-020-03329-7

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