Department of Civil Engineering, Institute of Engineering and Technology Lucknow, 226021, India.
Research Article
World Journal of Advanced Research and Reviews, 2023, 19(03), 1187-1197
Article DOI: 10.30574/wjarr.2023.19.3.1963
Received on 15 August 2023; revised on 26 September 2023; accepted on 28 September 2023
In this comprehensive study, spanning five decades from 1973 to 2022, the increasing prevalence and duration of heat waves in India, particularly in central and northwest regions, are examined. These heat waves are found to be associated with elevated pressures, anticyclonic flow patterns, clear skies, and diminishing soil moisture. Furthermore, variations in sea surface temperatures (SST) in the tropical Indian Ocean and the central Pacific significantly influence the occurrence of heat waves in India. The study predicts longer and more frequent heat waves as a consequence of the warming tropical Indian Ocean and an increase in El Nino occ-urrences, highlighting the growing heat-related challenges facing the country. Analyses of the present climate using climate models agree with the highest temperature zones that have been observed, emphasizing the importance of radiative heating. This study determines the areas that are most vulnerable to heat waves and regions with the highest temperatures, and it pinpoints the cause as wind flow from these areas, which is induced by favourable atmospheric circulations. The findings of this investigation would have broad applications in both vulnerability and risk evaluation as well as prediction.
This study focused on the ERA-Interim and IMD gri-dded data sets in order to evaluate the validity of heatwave detection across several datasets. It looked at particular heatwave dates from March to June in several places and years, included Lucknow in 2016, Delhi in 2019, Jaipur in 2016, and Bhubaneswar in 1988. Among the two datasets, the research showed a statistically substantial agreement, especially during Lucknow's 2016 summer heatwave. However, Bhubaneswar had the lowest correlation, suggesting that the temperature profile in both datasets was identical. With a larger concentration of matched pixels at the mean temperature, Jaipur in 2019 had the best fit. The study's findings were summarized by pointing out the significance of the mid-temperature range from 30°C to 40°C in heatwave identification.
Heat weave; IMD Indian Meteorological Department); ERA5; Temperature Deta; EHF (Excess Heat Factor); NDMA (The National Disaster Management Authority).
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Yogesh Kumar Mishra, Amarendra Singh and Prabhat Kumar Patel. Investigation of the Indian summer in the state's popular capital and correlation between IMD and ERA5 dataset during the past five decades (1973–2022). World Journal of Advanced Research and Reviews, 2023, 19(3), 1187-1197. Article DOI: https://doi.org/10.30574/wjarr.2023.19.3.1963