Abstract
Heatwaves are a major cause of environmental and health hazards. In a global warming scenario, the effect of heat stress associated with the increased frequency of heatwaves makes a large number of people vulnerable over the Indian subcontinent. For the development of a proper heatwave action plan in this region, heatwaves are required to be monitored, tracked, and predicted in real-time. In this study, we propose an operationally deployable empirical model using a set of indices to monitor and predict the heatwaves in the short range over the Indian region in real-time using gridded observation data and reanalysis data. The empirical operational model framework has two major components, (a) index-based monitoring over a spatial domain, and (b) temporal prediction over different locations (i.e. grid points). In the current version of the model framework, three heatwave indices are calculated for component (a), e.g., excess heat index, heat stress index, and excess heat factor index which were found suitable for the Indian region, and elsewhere. The advantage of these percentile-based and mean monthly exceedance-based indices is that they can be used to identify the heatwave affected blocks/districts/cities masking the local fluctuations. In addition, we also incorporate the effect of synoptic information like wind and humidity on heatwave intensity and duration in this component. This model component closely follows the existing operational criteria and the results from several cases are verified. For the second component (b), we have used a simple machine learning based method for the prediction of excess heat factor index to understand the recurrence properties of these indices. This simplistic method provides some reference skills for heatwave based on evolution memories. The results indicate that the overall heatwave indices can be predicted using this simplistic model up to a lead-time of 2–3 days for most of the regions of India.
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taken from Fig. 9. The black curve shows the EHF from observation. Forecasts for different lead-times are also shown
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Acknowledgements
Authors acknowledge the anonymous Reviewer/s for constructive comments. The authors acknowledge Head CRS, IMD his support and encouragement. Authors also gratefully acknowledge NCMRWF, Ministry of Earth Sciences, Government of India, for IMDAA reanalysis. IMDAA reanalysis was produced under the collaboration between UK Met Office, NCMRWF, and IMD with financial support from the Ministry of Earth Sciences, under the National Monsoon Mission Program.
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Narkhede, N., Chattopadhyay, R., Lekshmi, S. et al. An empirical model-based framework for operational monitoring and prediction of heatwaves based on temperature data. Model. Earth Syst. Environ. 8, 5665–5682 (2022). https://doi.org/10.1007/s40808-022-01450-2
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DOI: https://doi.org/10.1007/s40808-022-01450-2