Study of Cold Wave and Cold Stress in the Four Metropolitan Cities of India for the Period 1985–2020

Authors

  • Priyankar Kumar

    Centre for Ocean, River, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India

  • Arun Chakraborty

    Centre for Ocean, River, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India

  • Sakshi Sharma

    Centre for Ocean, River, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India

  • Mohd Sayeed Ul Hasan

    Centre for Ocean, River, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India

    Department of Civil Engineering, Aliah University, New Town, West Bengal, 700160, India

  • Anup Upadhyaya

    Centre for Ocean, River, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India

DOI:

https://doi.org/10.30564/jasr.v7i2.6268
Received: 22 February 2024; Revised: 11 April 2024; Accepted: 26 April 2024; Published Online: 30 April 2024

Abstract

Cold waves, cold nights and warm nights are major threats to human beings during winter due to climate change in different parts of India. The analysis of these has been studied for four major metropolitan cities (Chennai, Mumbai, Kolkata, and Delhi) of India during the period 1985–2020. The authors have used the 90th and 10th percentile threshold to identify the cold nights, warm nights and cold waves during the winter season. The degree of discomfort and cold stress category are identified using the Humidity Index (HD), and the Universal Thermal Climate Index (UTCI). The results indicate that the cold night event in Mumbai is ~0.36% higher than both Kolkata and Chennai cities but it is ~0.42% higher than Delhi. The number of cold wave events in Delhi is 53.5% higher than in Kolkata during the period of the study. It is also observed from the study of UTCI that the possibility of slight cold stress in the Delhi region during cold nights is 59.36% more than in other metropolitan cities. The study indicates that in the winter season, the climate of Delhi is more dynamic but for Kolkata it is relatively less dynamic.

Keywords:

Thermal stress, Cold wave, Humidity Index (HD), Universal Thermal Climate Index (UTCI)

References

[1] Añel, J.A., Fernández-González, M., Labandeira, X., et al., 2017. Impact of cold waves and heat waves on the energy production sector. Atmosphere. 8(11), 209. DOI: https://doi.org/10.3390/atmos8110209

[2] Ratnam, J.V., Behera, S.K., Annamalai, H., et al., 2016. ENSO's far reaching connection to Indian cold waves. Scientific Reports. 6, 37657. DOI: https://doi.org/10.1038/srep37657

[3] Sandeep, A., Prasad, V.S., 2020. On the variability of cold wave episodes over Northwest India using an NGFS retrospective analysis. Pure and Applied Geophysics. 177, 1157–1166. DOI: https://doi.org/10.1007/s00024-019-02335-9

[4] Shrestha, S., Peel, M.C., Moore, G.A., 2023. Cold waves in Terai region of Nepal and farmer's perception of the effect of fog events and cold waves on agriculture. Theoretical and Applied Climatology. 151, 29–45. DOI: https://doi.org/10.1007/s00704-022-04262-7

[5] De, U.S., Dube, R.K., Rao, G.P., 2005. Extreme weather events over India in the last 100 years. Journal of Indian Geophysical Union. 9(3), 173–187.

[6] Raghavan, K., 1967. A climatological study of severe cold waves in India. Mausam. 18(1), 91–96.

[7] Si, D., Ding, Y., Jiang, D., 2021. A low-frequency downstream development process leading to the outbreak of a mega-cold wave event in East Asia. Journal of the Meteorological Society of Japan. Ser. II. 99(5), 1185–1200. DOI: https://doi.org/10.2151/jmsj.2021-058

[8] Zhang, Y., Si, D., Ding, Y., et al., 2022. Influence of major stratospheric sudden warming on the unprecedented cold wave in East Asia in January 2021. Advances in Atmospheric Sciences. 39, 576–590. DOI: https://doi.org/10.1007/s00376-022-1318-9

[9] Ren, P., Gao, L., Zheng, J., et al., 2023. Key factors of the strong cold wave event in the winter of 2020/21 and its effects on the predictability in CMA-GEPS. Atmosphere. 14(3), 564. DOI: https://doi.org/10.3390/atmos14030564

[10] Dai, G., Li, C., Han, Z., et al., 2022. The nature and predictability of the East Asian extreme cold events of 2020/21. Advances in Atmospheric Sciences. 39, 566–575. DOI: https://doi.org/10.1007/s00376-021-1057-3

[11] Zhang, X., Fu, Y., Han, Z., et al., 2022. Extreme cold events from East Asia to north America in winter 2020/21: Comparisons, causes, and future implications. Advances in Atmospheric Sciences. 39, 553–565. DOI: https://doi.org/10.1007/s00376-021-1229-1

[12] Zhang, Y.X., Liu, Y.J., Ding, Y.H., 2021. Identification of winter long-lasting regional extreme low-temperature events in Eurasia and their variation during 1948–2017. Advances in Climate Change Research. 12(3), 353–362. DOI: https://doi.org/10.1016/j.accre.2021.05.005

[13] Bueh, C., Peng, J., Lin, D., et al., 2022. On the two successive supercold waves straddling the end of 2020 and the beginning of 2021. Advances in Atmospheric Sciences. 39, 591–608. DOI: https://doi.org/10.1007/s00376-021-1107-x

[14] Yao, Y., Zhang, W., Luo, D., et al., 2022. Seasonal cumulative effect of Ural blocking episodes on the frequent cold events in China during the early winter of 2020/21. Advances in Atmospheric Sciences. 39, 609–624. DOI: https://doi.org/10.1007/s00376-021-1100-4

[15] Overland, J.E., Wood, K.R., Wang, M., 2011. Warm Arctic—cold continents: climate impacts of the newly open Arctic Sea. Polar Research. 30(1), 15787. DOI: https://doi.org/10.3402/polar.v30i0.15787

[16] Wolter, K., Hoerling, M., Eischeid, J.K., et al., 2015. 3. How unusual was the cold winter of 2013/14 in the upper midwest?. Bulletin of the American Meteorological Society. 96(12), S10–S14.

[17] Yardley, J., Sigal, R.J., Kenny, G.P., 2011. Heat health planning: The importance of social and community factors. Global Environmental Change. 21(2), 670–679. DOI: https://doi.org/10.1016/j.gloenvcha.2010.11.010

[18] Auliciems, A., 1973. Thermal sensations of secondary schoolchildren in summer. Epidemiology & Infection. 71(3), 453–458. DOI: https://doi.org/10.1017/S002217240004643X

[19] Luterbacher, J., Dietrich, D., Xoplaki, E., et al., 2004. European seasonal and annual temperature variability, trends, and extremes since 1500. Science. 303(5663), 1499–1503. DOI: https://doi.org/10.1126/science.1093877

[20] Xoplaki, E., Luterbacher, J., Paeth, H., et al., 2005. European spring and autumn temperature variability and change of extremes over the last half millennium. Geophysical Research Letters. 32(15). DOI: https://doi.org/10.1029/2005GL023424

[21] Casty, C., Raible, C.C., Stocker, T.F., et al., 2007. A European pattern climatology 1766–2000. Climate Dynamics. 29, 791–805. DOI: https://doi.org/10.1007/s00382-007-0257-6

[22] Magyar, Z., Révai, T., 2013. What is the best clothing to prevent heat and cold stress? Experience with thermal manikin. West Indian Medical Journal. 62(2), 140–144.

[23] Jaswal, A.K., Tyagi, A., Bhan, S.C., 2013. Trends in extreme temperature events over India during 1969–2012. High-impact weather events over the SAARC region. Springer: Cham. pp. 365–382. DOI: https://doi.org/10.1007/978-3-319-10217-7_25

[24] Bhatla, R., Gupta, P., Tripathi, A., et al., 2016. Cold wave/severe cold wave events during post-monsoon and winter season over some stations of Eastern Uttar Pradesh, India. Journal of Climate Change. 2(1), 27–34.

[25] De, U.S., Mukhopadhyay, R.K., 1998. Severe heat wave over the Indian subcontinent in 1998, in perspective of global climate. Current Science. 75(12), 1308–1311.

[26] Pai, D.S., Thapliyal, V., Kokate, P.D., 2004. Decadal variation in the heat and cold waves over India during 1971–2000. Mausam. 55(2), 281–292.

[27] Kumar, N., Jaswal, A.K., Mohapatra, M., et al., 2017. Spatial and temporal variation in daily temperature indices in summer and winter seasons over India (1969–2012). Theoretical and Applied Climatology. 129, 1227–1239. DOI: https://doi.org/10.1007/s00704-016-1844-4

[28] Chun, C., Xin, H.Y., 2018. Numerical simulation of wind wave in Bohai Sea induced by cold wave. IOP Conference Series: Earth and Environmental Science. 171, 012017. DOI: https://doi.org/10.1088/1755-1315/171/1/012017

[29] Solomon, S., Qin, D., Manning, M., et al., 2007. Climate Change 2007 The Physical Science Basis. Cambridge University Press: Cambridge.

[30] Hingane, L.S., Rupa Kumar, K., Ramana Murty, B.V., 1985. Long-term trends of surface air temperature in India. Journal of Climatology. 5(5), 521–528. DOI: https://doi.org/10.1002/joc.3370050505

[31] Johnson, N.C., Xie, S.P., Kosaka, Y., et al., 2018. Increasing occurrence of cold and warm extremes during the recent global warming slowdown. Nature Communications. 9, 1724. DOI: https://doi.org/10.1038/s41467-018-04040-y

[32] Coumou, D., Rahmstorf, S., 2012. A decade of weather extremes. Nature Climate Change. 2, 491–496. DOI: https://doi.org/10.1038/nclimate1452

[33] Kumar, P., Rai, A., Upadhyaya, A., et al., 2022. Analysis of heat stress and heat wave in the four metropolitan cities of India in recent period. Science of The Total Environment. 818, 151788. DOI: https://doi.org/10.1016/j.scitotenv.2021.151788

[34] Forecasting Manual IV-6, Part IV, Heat and Cold Waves in India [Internet]. India Meteorological Department. Available from: https://www.imdpune.gov.in/Reports/Forecasting_Mannuals/IMD_IV-6.pdf

[35] Chand, R., Singh, C., 2015. Movements of western disturbance and associated cloud convection. Journal of Indian Geophysical Union. 19(1), 62–70.

[36] Malik, P., Bhardwaj, P., Singh, O., 2020. Distribution of cold wave mortalities over India: 1978–2014. International Journal of Disaster Risk Reduction. 51, 101841. DOI: https://doi.org/10.1016/j.ijdrr.2020.101841

[37] Athira, K.S., Attada, R., Rao, V.B., 2024. Synoptic dynamics of cold waves over north India: Underlying mechanisms of distinct cold wave conditions. Weather and Climate Extremes. 43, 100641. DOI: https://doi.org/10.1016/j.wace.2024.100641

[38] Chakravarty, K., Bhangale, R., Das, S., et al., 2021. Unraveling the characteristics of precipitation microphysics in summer and winter monsoon over Mumbai and Chennai—the two urban-coastal cities of Indian sub-continent. Atmospheric Research. 249, 105313. DOI: https://doi.org/10.1016/j.atmosres.2020.105313

[39] Rajan, E.H.S., Amirtham, L.R., 2021. Impact of building regulations on the perceived outdoor thermal comfort in the mixed-use neighbourhood of Chennai. Frontiers of Architectural Research. 10(1), 148–163. DOI: https://doi.org/10.1016/j.foar.2020.09.002

[40] Vinayak, B., Lee, H.S., Gedam, S., et al., 2022. Impacts of future urbanization on urban microclimate and thermal comfort over the Mumbai metropolitan region, India. Sustainable Cities and Society. 79, 103703. DOI: https://doi.org/10.1016/j.scs.2022.103703

[41] Khan, A., Chatterjee, S., Bisai, D., 2015. On the long-term variability of temperature trends and changes in surface air temperature in Kolkata Weather Observatory, West Bengal, India. Meteorology Hydrology and Water Management. Research and Operational Applications. 3(2), 9–16.

[42] Pandey, P., Kumar, D., Prakash, A., et al., 2012. A study of urban heat island and its association with particulate matter during winter months over Delhi. Science of the Total Environment. 414, 494–507. DOI: https://doi.org/10.1016/j.scitotenv.2011.10.043

[43] Jeganathan, A., Andimuthu, R., 2013. Temperature trends of Chennai city, India. Theoretical and Applied Climatology. 111, 417–425. DOI: https://doi.org/10.1007/s00704-012-0646-6

[44] Dile, Y.T., Srinivasan, R., 2014. Evaluation of CFSR climate data for hydrologic prediction in data‐scarce watersheds: An application in the Blue Nile River Basin. JAWRA Journal of the American Water Resources Association. 50(5), 1226–1241. DOI: https://doi.org/10.1111/jawr.12182

[45] Fuka, D.R., MacAllister, C.A., Degaetano, A.T., et al., 2013. Using the climate forecast system reanalysis dataset to improve weather input data for watershed models. Hydrological Processes. 28(22), 5613–5623. DOI: https://doi.org/10.1002/hyp.10073

[46] Saha, S., Moorthi, S., Pan, H.L., et al., 2010. The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society. 91(8), 1015–1058. DOI: https://doi.org/10.1175/2010BAMS3001.1

[47] Gelaro, R., McCarty, W., Suárez, M.J., et al., 2017. The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of Climate. 30(14), 5419–5454. DOI: https://doi.org/10.1175/JCLI-D-16-0758.1

[48] Mann, H.B., 1945. Nonparametric tests against trend. Econometrica: Journal of the Econometric Society. 13(3), 245–259.

[49] Kendall, M.G., 1975. Rank correlation methods. Griffin: London.

[50] Tabari, H., Marofi, S., Aeini, A., et al., 2011. Trend analysis of reference evapotranspiration in the western half of Iran. Agricultural and Forest Meteorology. 151(2), 128–136. DOI: https://doi.org/10.1016/j.agrformet.2010.09.009

[51] Koudahe, K., Djaman, K., Kayode, J.A., et al., 2018. Impact of climate variability on crop yields in Southern Togo. Environment Pollution and Climate Change. 2, 148.

[52] Panda, D.K., Mishra, A., Kumar, A., et al., 2014. Spatiotemporal patterns in the mean and extreme temperature indices of India, 1971–2005. International Journal of Climatology. 34(13), 3585–3603. DOI: https://doi.org/10.1002/joc.3931

[53] Masterson, J.M., Richardso, F.A., 1979. A method of quantifying human discomfort due to excessive heat and humidity. Environment Canada: Ontario.

[54] Błażejczyk, K., Jendritzky, G., Bröde, P., et al., 2013. An introduction to the universal thermal climate index (UTCI). Geographia Polonica. 86(1), 5–10.

[55] Coops, N.C., Wulder, M.A., Iwanicka, D., 2009. Demonstration of a satellite-based index to monitor habitat at continental-scales. Ecological Indicators. 9(5), 948–958. DOI: https://doi.org/10.1016/j.ecolind.2008.11.003

[56] Hargorove, W.V., 2001. Terrestrial ecoregions of North America: A conservation assessment. The Quarterly Review of Biology. 76(2), 256–257.

[57] Upadhyaya, A., Rai, A.K., Kumar, P., 2023. Anomalous rainfall trends in the North-Western Indian Himalayan Region (NW-IHR). Theoretical and Applied Climatology. 151(1), 253–272. DOI: https://doi.org/10.1007/s00704-022-04280-5

Downloads

How to Cite

Kumar, P., Chakraborty, A., Sharma, S., Sayeed Ul Hasan, M., & Upadhyaya, A. (2024). Study of Cold Wave and Cold Stress in the Four Metropolitan Cities of India for the Period 1985–2020. Journal of Atmospheric Science Research, 7(2), 83–113. https://doi.org/10.30564/jasr.v7i2.6268

Issue

Article Type

Article