Skip to main content
SpringerLink
Log in

Statistical modelling of century-long precipitation and temperature extremes in Himachal Pradesh, India: generalized extreme value approach and return level estimation

  • Original Paper
  • Published:
Indian Journal of Physics Aims and scope Submit manuscript

Abstract

Climate variability, particularly, that of temperature and precipitation, has received a great deal of attention worldwide. In the present work, we have carried out a thorough statistical modelling of precipitation and temperature extremes by taking century-long (1901–2002) datasets into consideration for Himachal Pradesh, India. Globally, the patterns of extreme weather events have changed from longer and hotter heat waves to heavier rains. A fragile ecosphere, climatic change, and the unique geology of Himachal Pradesh have all led to a sharp increase in natural disasters in the hill state over time. The climate of the state varies by altitude. Since precipitation and temperature are the main driving forces behind climate change, quantifying these two variables over a range of return periods is crucial in policymaking for minimizing the potential harm brought on by variations in these atmospheric elements. The statistical modelling of the meteorological data and probabilistic forecasting were done using extreme value theory (EVT), an advanced statistical modelling approach that is widely acknowledged. The generalized extreme value (GEV) analysis approach of EVT is utilized for the probabilistic forecasting of the extremities. The extreme values and their probable occurrence are estimated once every 50, 80, 100, 120, 200, 250, 300, and 500 years, respectively. By estimating the probabilities of extreme events, we can better understand the potential risks and impacts of climate change and develop strategies to manage and mitigate these risks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. E Fischer and R Knutti Nature Clim. Change 6 986 (2016). https://doi.org/10.1038/nclimate3110

    Article  ADS  Google Scholar 

  2. L V Alexander et al J. Geophys. Res. Atmos. 111 1 (2006). https://doi.org/10.1029/2005JD006290

    Article  Google Scholar 

  3. B N Goswami, V Venugopal, D Sangupta, M S Madhusoodanan and P K Xavier Science 314 1442 (2006). https://doi.org/10.1126/science.1132027

    Article  ADS  Google Scholar 

  4. A Buerkert, E Fernandez, B Tietjen and E Luedeling Clim. Change 162 1399 (2020). https://doi.org/10.1007/s10584-020-02862-8

    Article  ADS  Google Scholar 

  5. H M Hanlon, D Bernie, G Carigi and J A Lowe Clim. Change 166 1 (2021). https://doi.org/10.1007/s10584-021-03100-5

    Article  Google Scholar 

  6. G A Meehl, F Zwiers, J Evans, T Knutson, L Mearns and P Whetton Bull. Am. Meteorol. Soc. 81 427 (2000). https://doi.org/10.1175/1520-0477(2000)081%3c0427:TIEWAC%3e2.3.CO;2

    Article  ADS  Google Scholar 

  7. B Orlowsky and S I Seneviratne Clim. Change 110 669 (2012). https://doi.org/10.1007/s10584-011-0122-9

    Article  Google Scholar 

  8. V V Kharin, F W Zwiers, X Zhang and G C Hegerl J. Clim. 20 1419 (2007). https://doi.org/10.1175/JCLI4066.1

    Article  ADS  Google Scholar 

  9. V V Kharin, F W Zwiers, X Zhang and M Wehner Clim. Change 119 345 (2013). https://doi.org/10.1007/s10584-013-0705-8

    Article  ADS  Google Scholar 

  10. S Chen et al J. Geophys. Res. Atmos. 124 11051 (2019). https://doi.org/10.1029/2019JD031016

    Article  ADS  Google Scholar 

  11. A Mondal, D Khare and S Kundu Theor. Appl. Climatol. 122 143 (2015). https://doi.org/10.1007/s00704-014-1283-z

    Article  ADS  Google Scholar 

  12. M R Bhutiyani, V S Kale and N J Pawar Clim. Change 85 159 (2007). https://doi.org/10.1007/s10584-006-9196-1

    Article  ADS  Google Scholar 

  13. S Sen Roy and R C Balling Geophys. Res. Lett. 32 1 (2005). https://doi.org/10.1029/2004GL022201

    Article  Google Scholar 

  14. E Towler, D Llewellyn, A Prein and E Gilleland Weather Clim. Extrem. 29 100260 (2020).

    Article  Google Scholar 

  15. D Koutsoyiannis Hydrol. Sci. J. 49 591 (2004).

    Google Scholar 

  16. D Chikobvu and R Chifurira S. Afr. J. Sci. 111 1 (2015).

    Article  Google Scholar 

  17. W M Thupeng Int. J. Appl. Math. Stat. Sci. (IJAMSS). 8 1 (2019).

    Google Scholar 

  18. S Beguería and S M Vicente-Serrano J. Appl. Meteorol. Climatol. 45 108 (2006).

    Article  ADS  Google Scholar 

  19. T-A Sampson and N A Kwadwo J. Math. Stat. 14 275 (2018).

    Article  Google Scholar 

  20. S B Sunday, N S Agog, P Magdalene, A Mubarak and G K Anyam Sci. World J. 15 73 (2020).

    Google Scholar 

  21. H B Hasan, N F B Ahmad Radi and S B Kassim Lect. Notes Eng. Comput. Sci. 2197 181 (2012).

    Google Scholar 

  22. W K Huang, M L Stein, D J McInerney, S Sun and E J Moyer Adv. Stat. Climatol. Meteorol. Oceanogr. 2 79 (2016).

    Article  ADS  Google Scholar 

  23. P Naveau, M Nogaj, C Ammann, P Yiou, D Cooley and V Jomelli Comptes Rendus Geosci. 337 1013 (2005).

    Article  ADS  Google Scholar 

  24. L G Cao, J Zhong, B Da Su, J Q Zhai and M Gemmer Adv. Clim. Chang. Res. 4 153 (2013). https://doi.org/10.3724/SP.J.1248.2013.153

    Article  Google Scholar 

  25. T A Buishand, L de Haan and C Zhou Ann. Appl. Stat. 2 624 (2008). https://doi.org/10.1214/08-AOAS159

    Article  MathSciNet  Google Scholar 

  26. N Varathan, K Perera and N Wikramanayake Statistical Modelling of Daily Extreme Rainfall in Colombo. Int. Conf. Sustain. Built Environ. 2010 (ICSBE 2010), December, pp 13–14 (2010)

  27. S Shahid Theor. Appl. Climatol. 104 489 (2011). https://doi.org/10.1007/s00704-010-0363-y

    Article  ADS  Google Scholar 

  28. J Carreau, L Neppel, P Arnaud and P Cantet J. la Société Française Stat. 154 119 (2013).

    Google Scholar 

  29. H Hasan and Y Wai Chung AIP Conf. Proc. 1309 372 (2010). https://doi.org/10.1063/1.3525139

    Article  ADS  Google Scholar 

  30. D Maposa, J J Cochran and M Lesaoana Estimating high quantiles of extreme flood heights in the lower Limpopo River basin of Mozambique using model based Bayesian approach Proc. 5th Int. Disaster Risk Conf. Integr. Risk Manag. Role Sci. Technol. Pract. IDRC Davos, pp 435–438 https://doi.org/10.5194/nhessd-2-5401-2014 (2014)

  31. S N Zaz, R Shakil Ahmad, R T Krishnamoorthy and Y B Viswanadhapalli Atmos. Chem. Phys. Discuss. 19 1 (2018).

    Google Scholar 

  32. W M Thupeng Int. J. Appl. Math. Stat. Sci. 8 1 (2020).

    Article  Google Scholar 

  33. N Gandhre, S Dauji and S Londhe SSRN Electron J (2020). https://doi.org/10.2139/ssrn.3697534

    Article  Google Scholar 

  34. C P Pandey, V Ahuja, L K Joshi and H Nandan J. Earth Syst Sci. 132 48 (2023). https://doi.org/10.1007/s12040-023-02057-6

    Article  ADS  Google Scholar 

  35. E Gilleland and R W Katz J. Stat. Softw. 72 1 (2016).

    Article  Google Scholar 

  36. M A Stephenson “Package ‘ evd’” (2018)

Download references

Author information

Authors and Affiliations

  1. Department of Physics, Gurukula Kangri (Deemed to Be University), Haridwar, Uttarakhand, India

    Vineet Ahuja, Hemwati Nandan & Parmanand P. Pathak

  2. Wadia Institute of Himalaya Geology, Dehradun, Uttarakhand, India

    Chhavi P. Pandey

  3. Department of Applied Science, Gurukula Kangri (Deemed to Be University), Haridwar, Uttarakhand, India

    Lokesh K. Joshi

  4. Department of Physics, Hemvati Nandan Bahuguna Garhwal University, Srinagar Garhwal, Uttarakhand, India

    Hemwati Nandan

  5. Center for Space Research, North-West University, Mafikeng, South Africa

    Hemwati Nandan

Authors
  1. Vineet Ahuja
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chhavi P. Pandey
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lokesh K. Joshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hemwati Nandan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Parmanand P. Pathak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chhavi P. Pandey.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 742 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ahuja, V., Pandey, C.P., Joshi, L.K. et al. Statistical modelling of century-long precipitation and temperature extremes in Himachal Pradesh, India: generalized extreme value approach and return level estimation. Indian J Phys (2023). https://doi.org/10.1007/s12648-023-03011-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12648-023-03011-4

Keywords

Search

Navigation