Skip to main content

Advertisement

SpringerLink
Log in

Attribution of seasonal temperature changes in Sri Lanka to anthropogenic and natural forcings using CMIP5 simulations

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Abstract

The human–environment interactions are entwined across different spatio-temporal scales. The prime focus of this study is to investigate the wide range of changes happening in seasonal maximum and minimum temperatures (Tmax and Tmin) during 1950–2012 over the island country Sri Lanka in the deep tropics and to analyse associated important drivers explaining these changes. Fingerprint-based detection and attribution (D&A) analysis formally decipher the rudimentary causes of climate change by investigating the extent to which pattern of response to anthropogenic forcing (i.e., fingerprints) from climate model simulations explains the observed changes. Coupled Model Intercomparison Project Phase-5 experiment simulations are utilized to perform fingerprint-based D&A analysis for the first time in Sri Lanka. The PiControl experiment simulations which include only natural internal variability of climate could not explain the observed changes in seasonal Tmax and Tmin. However, the unequivocal attribution to human‐induced climate change (historical GHG and historical experiment simulations) was not possible in most of the cases except a few. Even though climate change impact is prominent in extra-tropics, an unusual human-induced climate change signature in deep-tropics is manifested in the present study.

Research highlights

  • Fingerprint-based formal detection and attribution approach is utilized

  • Observed temperature changes are not due to natural internal climate variability

  • Climate change impact is prominent in deep-tropics

  • Change in temperature is significant over whole of Sri Lanka

  • Large-scale atmospheric circulation patterns have a strong influence on hydroclimatology of Sri Lanka

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

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

References

  • Bindoff N L et al. 2013 Detection and attribution of climate change: From global to regional; In: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, https://doi.org/10.1017/CBO9781107415324.022.

  • Bonfils C et al. 2008 Detection and attribution of temperature changes in the mountainous western United States; J. Climate 21 6404–6424.

    Article  Google Scholar 

  • Caesar J et al. 2011 Changes in temperature and precipitation extremes over the Indo-Pacific region from 1971 to 2005; Int. J. Climatol. 31 791–801.

    Article  Google Scholar 

  • Change I C 2007 The physical science basis; Contribution of Working Group I to the fourth assessment report of the Intergovernmental Panel on Climate Change, 996.

  • De Silva C, Weatherhead E, Knox J W and Rodriguez-Diaz J 2007 Predicting the impacts of climate change – a case study of paddy irrigation water requirements in Sri Lanka; Agric. Water Manag. 93 19–29.

    Article  Google Scholar 

  • De Silva J and Sonnadara D 2016 Century scale climate change in the central highlands of Sri Lanka; J. Earth Syst. Sci. 125 75–84.

    Article  Google Scholar 

  • Dileepkumar R, Achuta Rao K and Arulalan T 2018 Human influence on sub-regional surface air temperature change over India; Sci. Rep. 8 1–9.

    Article  Google Scholar 

  • Dissanayake D 2020 Land use change and its impacts on land surface temperature in Galle City, Sri Lanka; Climate 8 65.

    Article  Google Scholar 

  • Dissanayake D, Morimoto T, Ranagalage M and Murayama Y 2019 Land-use/land-cover changes and their impact on surface urban heat islands: Case study of Kandy City, Sri Lanka; Climate 7 99.

    Article  Google Scholar 

  • Droogers P and Aerts J 2005 Adaptation strategies to climate change and climate variability: A comparative study between seven contrasting river basins; Phys. Chem. Earth Parts A/B/C 30 339–346.

    Article  Google Scholar 

  • Esham M and Garforth C 2013 Agricultural adaptation to climate change: Insights from a farming community in Sri Lanka; Mitig. Adapt. Strateg. Global Change 18 535–549.

    Article  Google Scholar 

  • Flato G et al. 2014 Evaluation of climate models; In: Climate change 2013: The physical science basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, pp. 741–866.

  • Francis P and Gadgil S 2013 A note on new indices for the equatorial Indian Ocean oscillation; J. Earth Syst. Sci. 122 1005–1011.

    Article  Google Scholar 

  • Harris I, Jones P D, Osborn T J and Lister D H, 2014 Updated high-resolution grids of monthly climatic observations – the CRU TS3. 10 Dataset; Int J. Climatol. 34 623–642.

    Article  Google Scholar 

  • Hasselmann K F 1979 On the signal-to-noise problem in atmospheric response studies; In: Joint Conference of Royal Meteorological Society, American Meteorological Society, Deutsche Meteorologische Gesellschaft and the Royal Society, Roy. Meteorol. Soc., pp. 251–259.

  • Hegerl G, Luterbacher J, González-Rouco F, Tett S F, Crowley T and Xoplaki E 2011 Influence of human and natural forcing on European seasonal temperatures; Nature Geosci. 4 99–103.

    Article  Google Scholar 

  • Hidalgo H G et al. 2009 Detection and attribution of streamflow timing changes to climate change in the western United States; J. Climate 22 3838–3855.

    Article  Google Scholar 

  • Hoerling M, Hurrell J, Eischeid J and Phillips A 2006 Detection and attribution of twentieth-century northern and southern African rainfall change; J. Climate 19 3989–4008.

    Article  Google Scholar 

  • Karunaratne A, Wheeler T 2014 Maize and climate change in Sri Lanka: Progress, trends, and challenges in simulating impacts; In: XXIX International Horticultural Congress on Horticulture: Sustaining Lives, Livelihoods and Landscapes, IHC2014 1112 55–62.

  • Kendall M 1975 Rank Correlation Methods; Charles Griffin, London.

    Google Scholar 

  • Khaliq M, Ouarda T B, Gachon P, Sushama L and St-Hilaire A 2009 Identification of hydrological trends in the presence of serial and cross correlations: A review of selected methods and their application to annual flow regimes of Canadian rivers; J. Hydrol. 368 117–130.

    Article  Google Scholar 

  • Klein Tank A et al. 2006 Changes in daily temperature and precipitation extremes in central and south Asia; J. Geophys. Res. Atmos. 111.

  • Mann H B 1945 Nonparametric tests against trend; Econometrica 13 245–259.

    Article  Google Scholar 

  • Mondal A and Mujumdar P 2012 On the basin‐scale detection and attribution of human‐induced climate change in monsoon precipitation and streamflow; Water Resour. Res. 48.

  • Naveendrakumar G, Vithanage M, Kwon H-H, Iqbal M, Pathmarajah S and Obeysekera J 2018 Five decadal trends in averages and extremes of rainfall and temperature in Sri Lanka; Adv. Meteorol. 2018 4217917.

    Article  Google Scholar 

  • Peiris T, Hansen J W and Zubair L 2008 Use of seasonal climate information to predict coconut production in Sri Lanka; Int. J. Climatol. 28 103–110.

    Article  Google Scholar 

  • Peiris T, Wijeratne M, Ranasinghe C, Aanadacumaraswamy A, Fernando M, Jayakody A and Ratnasiri J 2004 Impact of climate change on coconut and tea industry in Sri Lanka; In: 2nd AIACC regional workshop for Asia and the Pacific, Manila, Philippines, pp. 2–5.

  • Peng S et al. 2004 Rice yields decline with higher night temperature from global warming; Proc. Nat. Acad. Sci. 101 9971–9975.

    Article  Google Scholar 

  • Perkins-Kirkpatrick S and Gibson P 2017 Changes in regional heatwave characteristics as a function of increasing global temperature; Sci. Rep. 7 12256.

    Article  Google Scholar 

  • Perkins-Kirkpatrick S E, Fischer E M, Angélil O and Gibson P B 2017 The influence of internal climate variability on heatwave frequency trends; Environ. Res. Lett. 12 044005.

    Article  Google Scholar 

  • Pierce D W et al. 2008 Attribution of declining western US snowpack to human effects; J. Climate 21 6425–6444.

    Article  Google Scholar 

  • Pierce D W, Barnett T P, Santer B D and Gleckler P J 2009 Selecting global climate models for regional climate change studies; Proc. Natl. Acad. Sci. 106 8441–8446.

    Article  Google Scholar 

  • Raju K S, Sonali P and Kumar D N 2017 Ranking of CMIP5-based global climate models for India using compromise programming; Theoret. Appl. Climatol. 128 563–574.

    Article  Google Scholar 

  • Ranagalage M, Dissanayake D, Murayama Y, Zhang X, Estoque R C, Perera E and Morimoto T 2018a Quantifying surface urban heat island formation in the world heritage tropical mountain city of Sri Lanka; ISPRS Int. J. Geo-Infor. 7 341.

    Article  Google Scholar 

  • Ranagalage M, Estoque R C, Zhang X and Murayama Y 2018b Spatial changes of urban heat island formation in the Colombo District, Sri Lanka: Implications for sustainability planning; Sustainability 10 1367.

    Article  Google Scholar 

  • Ranagalage M, Estoque R C and Murayama Y 2017 An urban heat island study of the Colombo metropolitan area, Sri Lanka, based on Landsat data 1997–2017; ISPRS Int. J. Geo-Infor. 6 189.

    Article  Google Scholar 

  • Ranagalage M, Murayama Y, Dissanayake D and Simwanda M 2019 The impacts of landscape changes on annual mean land surface temperature in the tropical mountain city of Sri Lanka: A case study of Nuwara Eliya 1996–2017; Sustainability 11 5517.

    Article  Google Scholar 

  • Ranagalage M et al. 2020 Spatiotemporal variation of urban heat islands for implementing nature-based solutions: A case study of Kurunegala, Sri Lanka; ISPRS Int. J. Geo-Infor. 9 461.

    Article  Google Scholar 

  • Ribes A and Terray L 2013 Application of regularised optimal fingerprinting to attribution. Part II: Application to global near-surface temperature; Clim. Dyn. 41 2837–2853.

    Article  Google Scholar 

  • Saji N, Goswami B, Vinayachandran P and Yamagata T 1999 A dipole mode in the tropical Indian Ocean; Nature 401 360–363.

    Article  Google Scholar 

  • Santer B D et al. 2007 Identification of human-induced changes in atmospheric moisture content; Proc. Natl. Acad. Sci. 104 15,248–15,253.

    Article  Google Scholar 

  • Schulz L and Kingston D G 2017 GCM-related uncertainty in river flow projections at the threshold for dangerous climate change: The Kalu Ganga river, Sri Lanka; Hydrol. Sci. J. 62 2369–2380.

    Article  Google Scholar 

  • Sen P K 1968 Estimates of the regression coefficient based on Kendall’s tau; J. Am. Stat. Assoc. 63 1379–1389.

    Article  Google Scholar 

  • Senanayake I P, Welivitiya W and Nadeeka P M 2013 Remote sensing based analysis of urban heat islands with vegetation cover in Colombo city, Sri Lanka using Landsat-7 ETM+ data; Urban Clim. 5 19–35.

    Article  Google Scholar 

  • Solomon S, Manning M, Marquis M and Qin D 2007 Climate change 2007-the physical science basis; Working group I contribution to the fourth assessment report of the IPCC Vol 4, Cambridge University Press, Cambridge.

  • Sonali P and Kumar D N 2013 Review of trend detection methods and their application to detect temperature changes in India; J. Hydrol. 476 212–227.

    Article  Google Scholar 

  • Sonali P, Kumar D N and Nanjundiah R S 2017a Intercomparison of CMIP5 and CMIP3 simulations of the 20th century maximum and minimum temperatures over India and detection of climatic trends; Theoret. Appl. Climatol. 128 465–489.

    Article  Google Scholar 

  • Sonali P, Nanjundiah R S and Kumar D N 2017b Linkage between global sea surface temperature and hydroclimatology of a major river basin of India before and after 1980; Environ. Res. Lett. 12 124002.

    Article  Google Scholar 

  • Sonali P and Nagesh Kumar D 2015 Detection and attribution of seasonal temperature changes in India with climate models in the CMIP5 archive; J. Water Clim. Change 7 83–102.

    Article  Google Scholar 

  • Sonali P and Nagesh Kumar D 2016 Spatio-temporal variability of temperature and potential evapotranspiration over India; J. Water Clim. Change 7 810–822.

    Article  Google Scholar 

  • Sonali P and Nagesh Kumar D 2020 Review of recent advances in climate change detection and attribution studies: A large-scale hydroclimatological perspective; J. Water Clim. Change 11 1–29.

    Article  Google Scholar 

  • Sonali P, Nanjundiah R S and Kumar D N 2018 Detection and attribution of climate change signals in South India maximum and minimum temperatures; Clim. Res. 76 145–160.

    Article  Google Scholar 

  • Sperber K et al. 2013 The Asian summer monsoon: An intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century; Clim. Dyn. 41 2711–2744.

    Article  Google Scholar 

  • Stocker T F et al. 2013 Climate change 2013: The physical science basis; Cambridge University Press, Cambridge.

    Google Scholar 

  • Taylor K E, Stouffer R J and Meehl G A 2012 An overview of CMIP5 and the experiment design; Bull. Am. Meteorol. Soc. 93 485–498.

    Article  Google Scholar 

  • Wickramasinghe D 2010 Chapter 15 Coastal ecosystems and climate vulnerability in Sri Lanka; In: Climate change adaptation and disaster risk reduction: An Asian perspective; Emerald Group Publishing Limited, pp. 307–326.

  • Wilcoxon F 1992 Individual comparisons by ranking methods; In: Breakthroughs in statistics, Springer, pp. 196–202.

  • Yue S, Pilon P, Phinney B and Cavadias G 2002 The influence of autocorrelation on the ability to detect trend in hydrological series; Hydrol. Proc. 16 1807–1829.

    Article  Google Scholar 

  • Yue S and Wang C 2004 The Mann–Kendall test modified by effective sample size to detect trend in serially correlated hydrological series; Water Res. Manag. 18 201–218.

    Article  Google Scholar 

  • Zubair L 2002 El Nino–southern oscillation influences on rice production in Sri Lanka; Int. J. Climatol. 22 249–260.

    Article  Google Scholar 

  • Zubair L et al. 2015 Climate Change Impacts on Rice Farming Systems in Northwestern Sri Lanka; Chapter 10.

  • Zubair L and Ropelewski C F 2006 The strengthening relationship between ENSO and northeast monsoon rainfall over Sri Lanka and southern India; J. Climate 19 1567–1575.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP the US Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Author information

Authors and Affiliations

  1. Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru, 560 012, India

    Sonali Pattanayak

Authors
  1. Sonali Pattanayak
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.

Corresponding author

Correspondence to Sonali Pattanayak.

Additional information

Communicated by Kavirajan Rajendran

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pattanayak, S. Attribution of seasonal temperature changes in Sri Lanka to anthropogenic and natural forcings using CMIP5 simulations. J Earth Syst Sci 130, 105 (2021). https://doi.org/10.1007/s12040-021-01594-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12040-021-01594-2

Keywords

Search

Navigation