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Changes in climate extremes over Bangladesh at 1.5 °C, 2 °C, and 4 °C of global warming with high-resolution regional climate modeling

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Abstract

Global mean temperature is continuously rising and causing changes in the extreme climatic events. Following these changes, climate extremes—the rare events that reside in the tail of the distribution of essential climate variables—are expected to be further intensified, more frequent, and prolonged. Changes in extremes would vary spatially from region to region and thus need regional assessment for future adaptation planning. This study assesses the climate extremes at 1.5 °C, 2 °C, and 4 °C of global warming over Bangladesh which is one of the most vulnerable countries to climate change. Future changes in climate extremes are assessed using a subset of extreme temperature and precipitation indices devised by Expert Team on Climate Change Detection and Indices (ETCCDI). Projections from high-resolution regional climate model ensembles are used to derive extreme climate indices. Our analysis shows overall upward changes in warm indices and downward changes in cold indices at higher specific warming levels. We found a much higher increase in extreme rainfall compared with the annual total rainfall. Increasing variability of rainfall indices is found at higher specific warming levels. Our analysis also suggests a higher increase of temperature during the winter and post-monsoon seasons, as well as an increase in the 1-day and 5-day maximum rainfall during pre- and post-monsoon seasons. A significant regional difference is found in almost all the rainfall indices. The forecasted increase of extreme rainfall and consecutive dry days (CDD) over the northeast region indicates a possibility of an increase of flash floods in the future. Moreover, the increase in the extreme rainfall over the southeast region will increase the chances of landslides.

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References

  • Ahmed B (2014) Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh. Landslides, Springer Nature 12:1077–1095

    Article  Google Scholar 

  • Basher MA, Stiller-Reeve MA, Islam AKMS, Bremer S (2017) Assessing climatic trends of extreme rainfall indices over northeast Bangladesh. Theor Appl Climatol 134:441–452. https://doi.org/10.1007/s00704-017-2285-4

    Article  Google Scholar 

  • Becker RA, Chambers JM, Wilks AR (1988) The new S language. Wadsworth & Brooks, Pacific Grove

    Google Scholar 

  • Boer GJ, Lambert SJ (2001) Second-order space-time climate difference statistics. Clim Dyn 17(2–3):213–218

  • Booth BB, Harris GR, Murphy JM, House JI, Jones CD, Sexton D, Sitch S (2017) Narrowing the range of future climate projections using historical observations of atmospheric CO2. J Clim 30(8):3039–3053

    Article  Google Scholar 

  • Boucher O, Bellassen V, Benveniste H, Ciais P, Criqui P, Guivarch C, Treut HL, Mathy S, Séférian R (2016) Opinion: in the wake of Paris Agreement, scientists must embrace new directions for climate change research. Proc Natl Acad Sci 113:7287–7290

    Article  Google Scholar 

  • Bürger G, Murdock TQ, Werner AT, Sobie SR, Cannon AJ (2012) Downscaling extremes-an intercomparison of multiple statistical methods for present climate. J Clim Am Meteorol Soc 25:4366–4388

    Google Scholar 

  • Chen J, Gao C, Zeng X, Xiong M, Wang Y, Jing C, Krysanova V, Huang J, Zhao N, Su B (2017) Assessing changes of river discharge under global warming of 1.5°C and 2°C in the upper reaches of the Yangtze River Basin: approach by using multiple- GCMs and hydrological models. Quat Int, Elsevier BV 453:63–73

    Article  Google Scholar 

  • Fahad MGR, Saiful Islam AKM, Nazari R, Alfi Hasan M, Tarekul Islam GM, Bala SK (2017) Regional changes of precipitation and temperature over Bangladesh using bias-corrected multi-model ensemble projections considering high-emission pathways. Int J Climatol. https://doi.org/10.1002/joc.5284

  • Frank S, Havlík P, Soussana JF, Levesque A, Valin H, Wollenberg E et al (2017) Reducing greenhouse gas emissions in agriculture without compromising food security? Environ Res Lett 12(10):105004

    Article  Google Scholar 

  • Friedlingstein P, Andrew RM, Rogelj J, Peters GP, Canadell JG, Knutti R et al (2014) Persistent growth of CO2 emissions and implications for reaching climate targets. Nat Geosci 7(10):709–715

    Article  Google Scholar 

  • Grillakis MG, Koutroulis AG, Tsanis IK (2013) Multisegment statistical bias correction of daily GCM precipitation output. J Geophys Res-Atmos 118(8):3150–3162

  • Gu H, Yu Z, Yang C, Ju Q, Yang T, Zhang D (2018) High-resolution ensemble projections and uncertainty assessment of regional climate change over China in CORDEX East Asia. Hydrol Earth Syst Sc 22(5):3087

  • Hulme M (2016) 1.5 C and climate research after the Paris Agreement. Nat Clim Chang, Springer Nature 6:222–224

    Article  Google Scholar 

  • IPCC 2019 Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Masson-Delmotte V, Zhai P, Pörtner HO, Roberts D, Skea J, Shukla PR, Pirani A, Moufouma-Okia W, Péan C, Pidcock R, Connors S, Matthews JBR, Chen Y, Zhou X, Gomis MI, Lonnoy E, Maycock T, Tignor M, Waterfield T (eds.)

  • Islam N, Uyeda H, Ferdousi N, Abdullah S (2009) Understanding the rainfall climatology and detection of extreme weather events in the SAARC region part II utilization of RCM data. A collaborative research project between Synoptic Division of SMRC and HyARC of Nagoya University. Dhaka. SAARC Meteorological Research Centre (SMRC)

  • Khan MJU, Islam AS, Das MK, Mohammed K, Bala SK, Islam GT (2019) Observed trends in climate extremes over Bangladesh from 1981 to 2010. Clim Res 77(1):45–61

    Article  Google Scholar 

  • Khatun MA, Rashid MB, Hygen HO (2016) MET report: climate of Bangladesh. Norwegian meteorological institute, (08)

  • King AD, Karoly DJ, Henley BJ (2017) Australian climate extremes at 1.5 °C and 2 °C of global warming. Nat Clim Chang, Springer Nature 7:412–416

    Article  Google Scholar 

  • Lehner F, Coats S, Stocker TF, Pendergrass AG, Sanderson BM, Raible CC, Smerdon JE (2017) Projected drought risk in 1.5°C and 2°C warmer climates. Geophys Res Lett, Wiley-Blackwell 44:7419–7428

    Article  Google Scholar 

  • Mohammed K, Islam AS, Islam GT, Alfieri L, Bala SK, Khan, MJU (2017) Extreme flows and water availability of the Brahmaputra River under 1.5 and 2 C global warming scenarios. Clim Change 145(1–2):159–175

  • Nowreen S et al (2012) An indicator of climate change in the south west region of Bangladesh. Int J Clim Chang Impacts Response 4(3):47–60

    Article  Google Scholar 

  • Nowreen S, Murshed SB, Islam AKMS, Bhaskaran B, Hasan MA (2014) Changes of rainfall extremes around the haor basin areas of Bangladesh using multi-member ensemble RCM. Theor Appl Climatol, Springer Nature 119:363–377

    Article  Google Scholar 

  • Peters GP, Andrew RM, Canadell JG, Friedlingstein P, Jackson RB, Korsbakken JI et al (2020) Carbon dioxide emissions continue to grow amidst slowly emerging climate policies. Nat Clim Chang 10(1):3–6

    Article  Google Scholar 

  • Piontek F, Müller C, Pugh TAM, Clark DB, Deryng D, Elliott J, de Jesus Colón González F, Flörke M, Folberth C, Franssen W, Frieler K, Friend AD, Gosling SN, Hemming D, Khabarov N, Kim H, Lomas MR, Masaki Y, Mengel M, Morse A, Neumann K, Nishina K, Ostberg S, Pavlick R, Ruane AC, Schewe J, Schmid E, Stacke T, Tang Q, Tessler ZD, Tompkins AM, Warszawski L, Wisser D, Schellnhuber HJ (2013) Multisectoral climate impact hotspots in a warming world. Proc Natl Acad Sci 111:3233–3238

    Article  Google Scholar 

  • Roy B, Islam AS, Islam GT, Khan MJU, Bhattacharya B, Ali MH, Khan AS, Hossain MS, Sarker GC, Pieu NM (2019) Frequency analysis of flash floods for establishing new danger levels for the rivers in the northeast haor region of Bangladesh. J Hydrol Eng 24(4):05019004

    Article  Google Scholar 

  • Schleussner C-F, Rogelj J, Schaeffer M, Lissner T, Licker R, Fischer EM, Knutti R, Levermann A, Frieler K, Hare W (2016) Science and policy characteristics of the Paris Agreement temperature goal. Nat Clim Chang, Springer Nature 6:827–835

    Article  Google Scholar 

  • Shahid S (2009) Spatio-temporal variability of rainfall over Bangladesh during the time period 1969–2003. Asia Pac J Atmos Sci 45:375–389

    Google Scholar 

  • Shahid S (2011) Trends in extreme rainfall events of Bangladesh. Theor Appl Climatol 104(3–4):489–499. https://doi.org/10.1007/s00704-010-0363-y

  • Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013) Climate extremes indices in the CMIP5 multimodel ensemble: part 2. Future climate projections. J Geophys Res Atmos, Wiley-Blackwell 118:2473–2493

    Article  Google Scholar 

  • SMRC (2009) Understanding the rainfall climatology and detection of extreme weather events in the SAARC region: Part II- Utilization of RCM data. SAARC Meteorological Research Centre (SMRC), Dhaka

  • Van Vuuren DP, Edmonds JA, Kainuma M, Riahi K, Weyant J (2011) A special issue on the RCPs. Clim Change 109(1–2):1

  • Weedon GP, Balsamo G, Bellouin N, Gomes S, Best MJ, Viterbo P (2014) The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data. Water Resour Res, Wiley Online Library 50:7505–7514

    Article  Google Scholar 

  • Zaman AM, Molla MK, Pervin IA, Rahman SM, Haider AS, Ludwig F, Franssen W (2017) Impacts on river systems under 2 C warming: Bangladesh Case Study. Clim Serv 7:96–114

  • Zhang X, Yang F (2004) RClimDex (1.0) user manual. Climate Research Branch Environment Canada, 22

  • Zhang X, Alexander L, Hegerl GC, Jones P, Tank AK, Peterson TC, Trewin B, Zwiers FW (2011) Indices for monitoring changes in extremes based on daily temperature and precipitation data. Wiley Interdiscip Rev Clim Chang, Wiley-Blackwell 2:851–870

    Article  Google Scholar 

Download references

Funding

The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no. 603864 (HELIX: High-End cLimate Impacts and eXtremes; http://www.helixclimate.eu).

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Authors and Affiliations

  1. Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh

    Md Jamal Uddin Khan, A. K. M. Saiful Islam, Sujit Kumar Bala & G. M. Tarekul Islam

Authors
  1. Md Jamal Uddin Khan
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  2. A. K. M. Saiful Islam
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  3. Sujit Kumar Bala
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  4. G. M. Tarekul Islam
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Correspondence to A. K. M. Saiful Islam.

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Khan, M.J.U., Islam, A.K.M.S., Bala, S.K. et al. Changes in climate extremes over Bangladesh at 1.5 °C, 2 °C, and 4 °C of global warming with high-resolution regional climate modeling. Theor Appl Climatol 140, 1451–1466 (2020). https://doi.org/10.1007/s00704-020-03164-w

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  • DOI: https://doi.org/10.1007/s00704-020-03164-w

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