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Incorporating the climate oscillations in the computation of meteorological drought over India

Author

Listed:
  • D. Chiru Naik

    (Indian Institute of Technology Delhi
    Indian Institute of Technology Ropar)

  • Sagar Rohidas Chavan

    (Indian Institute of Technology Ropar)

  • P. Sonali

    (Willis Towers Waston)

Abstract

Large-scale climate oscillations (e.g. Nino 3.4, SOI, MEI and IOD) govern the occurrence of meteorological droughts. The present study is envisaged to model non-stationary meteorological drought index, at the grid scale covering entire India by considering the large-scale climate oscillations affecting the phenomenon of precipitation. The non-stationary framework is considered to estimate the Standardized Precipitation Index (SPI), which in turn is used for analysing the frequency of severe and extreme drought events for two reference time periods (i.e. 1901–1950 and 1951–2018) at various timescales, viz. 3, 6, 9 and 12 months. The efficiency of non-stationary SPI (NSPI) approach over stationary SPI (SSPI) approach in characterizing the drought events is evaluated based on two precipitation datasets from the India Meteorological Department (IMD) and Climate Research Unit (CRU). The NSPI is observed to outperform the SSPI in assessing the meteorological droughts at majority of the grids over India as the timescale increases from 3 to 12 months. Different sets of climate oscillations with significant correlation with precipitation are identified for IMD and CRU datasets as well as for different reference periods, indicating that the drought characterization is sensitive to the chosen reference time period as well as the precipitation datasets considered for the analysis. Overall the NSPI approach is shown to provide reliable and robust determination of drought characteristics by incorporating the climate oscillations under changing climate. The findings from this study can be used to devise adaptation strategies to mitigate adverse impacts of droughts.

Suggested Citation

  • D. Chiru Naik & Sagar Rohidas Chavan & P. Sonali, 2023. "Incorporating the climate oscillations in the computation of meteorological drought over India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 2617-2646, July.
    • Handle: RePEc:spr:nathaz:v:117:y:2023:i:3:d:10.1007_s11069-023-05958-3
    DOI: 10.1007/s11069-023-05958-3
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    References listed on IDEAS

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    1. Aiguo Dai, 2011. "Drought under global warming: a review," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 2(1), pages 45-65, January.
    2. Kaustubh Salvi & Subimal Ghosh, 2016. "Projections of Extreme Dry and Wet Spells in the 21st Century India Using Stationary and Non-stationary Standardized Precipitation Indices," Climatic Change, Springer, vol. 139(3), pages 667-681, December.
    3. Yixuan Wang & Jianzhu Li & Ping Feng & Rong Hu, 2015. "A Time-Dependent Drought Index for Non-Stationary Precipitation Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5631-5647, December.
    4. Peter J. Webster & Andrew M. Moore & Johannes P. Loschnigg & Robert R. Leben, 1999. "Coupled ocean–atmosphere dynamics in the Indian Ocean during 1997–98," Nature, Nature, vol. 401(6751), pages 356-360, September.
    5. D. Pai & Latha Sridhar & Pulak Guhathakurta & H. Hatwar, 2011. "District-wide drought climatology of the southwest monsoon season over India based on standardized precipitation index (SPI)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 59(3), pages 1797-1813, December.
    6. Samra, J. S., 2004. "Review and analysis of drought monitoring, declaration and management in India," IWMI Working Papers H035617, International Water Management Institute.
    7. Stasinopoulos, D. Mikis & Rigby, Robert A., 2007. "Generalized Additive Models for Location Scale and Shape (GAMLSS) in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i07).
    8. Kevin E. Trenberth & Aiguo Dai & Gerard van der Schrier & Philip D. Jones & Jonathan Barichivich & Keith R. Briffa & Justin Sheffield, 2014. "Global warming and changes in drought," Nature Climate Change, Nature, vol. 4(1), pages 17-22, January.
    9. Poulomi Ganguli & M. Reddy, 2012. "Risk Assessment of Droughts in Gujarat Using Bivariate Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3301-3327, September.
    10. N. H. Saji & B. N. Goswami & P. N. Vinayachandran & T. Yamagata, 1999. "A dipole mode in the tropical Indian Ocean," Nature, Nature, vol. 401(6751), pages 360-363, September.
    11. G. Tsakiris & D. Pangalou & H. Vangelis, 2007. "Regional Drought Assessment Based on the Reconnaissance Drought Index (RDI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 821-833, May.
    12. Deepti Singh & Michael Tsiang & Bala Rajaratnam & Noah S. Diffenbaugh, 2014. "Observed changes in extreme wet and dry spells during the South Asian summer monsoon season," Nature Climate Change, Nature, vol. 4(6), pages 456-461, June.
    13. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
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