Abstract
During past decades, the Great South of Madagascar is known to be facing persistent and severe drought. Thus, this study investigated the characteristics of future hydrological droughts (2025–2099) in this particular region under three emission scenarios that is the Shared Socio-economic Pathways (SSP) 1–2.6, SSP2-4.5, and SSP5-8.5 for three time periods of 24 years namely near future (NF, 2025–2049), mid-future (MF, 2050–2074), and far future (FF, 2075–2099). For that, monthly precipitation and minimum and maximum temperature from six global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 were downscaled with Bias-Correction Spatial Disaggregation (BCSD). The drought characteristics were identified using the Standardized Precipitation Evapotranspiration Index-12 (SPEI-12) and the run theory. The results showed that thanks to the BCSD, corrected GCMs showed better agreement with observed data (1950–2014) from ERA5. The results also suggested that the number of drought events per decade in the south of Madagascar will significantly increase starting from the middle of this century. Overall, droughts in the Great South will become shorter (less than 12 months), except under SSP5-8.5 in the FF with an average duration of 14 months. Starting from the MF, the Great South will suffer from more intense and severe drought, particularly under SSP5-8.5. Furthermore, the drought frequency in the region will rise in the future. The number of drought events that start during the early rainy season will also increase which may significantly impact the food security in the region. The findings of this study can help policymakers tailor climate adaptation strategies, water management policy, and food policy.
Similar content being viewed by others
Data availability
The datasets used in the current study are available at the Earth System Grid Federation (ESGF) and the Copernicus Climate Change Service for providing the ERA5 climate data.
References
Abiodun BJ, Makhanya N, Petja B, Abatan AA, Oguntunde PG (2019) Future projection of droughts over major river basins in Southern Africa at specific global warming levels. Theoret Appl Climatol 137(3–4):1785–1799. https://doi.org/10.1007/s00704-018-2693-0
Afshar MH, Şorman AÜ, Tosunoğlu F, Bulut B, Yilmaz MT, Danandeh Mehr A (2020) Climate change impact assessment on mild and extreme drought events using copulas over Ankara, Turkey. Theor Appl Climatol 141(3–4):1045–1055. https://doi.org/10.1007/s00704-020-03257-6
Anderson W, Taylor C, McDermid S, Ilboudo-Nébié E, Seager R, Schlenker W, Cottier F, de Sherbinin A, Mendeloff D, Markey K (2021) Violent conflict exacerbated drought-related food insecurity between 2009 and 2019 in sub-Saharan Africa. Nature Food 2(8):603–615. https://doi.org/10.1038/s43016-021-00327-4
Ayugi B, Ngoma H, Babaousmail H, Karim R, Iyakaremye V, Lim Kam Sian KTC, Ongoma V (2021) Evaluation and projection of mean surface temperature using CMIP6 models over East Africa. J African Earth Sci 181:104226. https://doi.org/10.1016/j.jafrearsci.2021.104226
Ayugi B, Shilenje ZW, Babaousmail H, Lim Kam Sian KTC, Mumo R, Dike VN, Iyakaremye V, Chehbouni A, Ongoma V (2022) Projected changes in meteorological drought over East Africa inferred from bias-adjusted CMIP6 models. Natural Hazards 113(2):1151–1176. https://doi.org/10.1007/s11069-022-05341-8
Başakın EE, Ekmekcioğlu Ö, Özger M (2021) Drought prediction using hybrid soft-computing methods for semi-arid region. Model Earth Syst Environ 7(4):2363–2371. https://doi.org/10.1007/s40808-020-01010-6
Berhanu D, Alamirew T, Taye MT, Tibebe D, Gebrehiwot S, Zeleke G (2023) Evaluation of CMIP6 models in reproducing observed rainfall over Ethiopia. J Water Climate Change 14(8):2583–2605. https://doi.org/10.2166/wcc.2023.502
Bidou JE, Droy I (2007) Poverty and food vulnerability in the south of Madagascar: the contribution of a diachronic approach on a panel of households. Mondes En Developpement 35(4). https://doi.org/10.3917/med.140.0045
Boucher O, Servonnat J, Albright AL, Aumont O, Balkanski Y, Bastrikov V, Bekki S, Bonnet R, Bony S, Bopp L, Braconnot P, Brockmann P, Cadule P, Caubel A, Cheruy F, Codron F, Cozic A, Cugnet D, D’Andrea F, … Vuichard N (2020) Presentation and evaluation of the IPSL‐CM6A‐LR climate model. J Adv Model Earth Syst 12(7). https://doi.org/10.1029/2019MS002010
Cannon AJ, Sobie SR, Murdock TQ (2015) Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes? J Clim 28(17):6938–6959. https://doi.org/10.1175/JCLI-D-14-00754.1
Cherchi A, Fogli PG, Lovato T, Peano D, Iovino D, Gualdi S, Masina S, Scoccimarro E, Materia S, Bellucci A, Navarra A (2018) Global mean climate and main patterns of variability in the CMCC‐CM2 coupled model. J Adv Model Earth Syst 2018MS001369. https://doi.org/10.1029/2018MS001369
Chiang F, Mazdiyasni O, AghaKouchak A (2021) Evidence of anthropogenic impacts on global drought frequency, duration, and intensity. Nat Commun 12(1):2754. https://doi.org/10.1038/s41467-021-22314-w
Cook BI, Mankin JS, Marvel K, Williams AP, Smerdon JE, Anchukaitis KJ (2020) Twenty‐first century drought projections in the CMIP6 forcing scenarios. Earth’s Future 8(6). https://doi.org/10.1029/2019EF001461
Coppola E, Raffaele F, Giorgi F, Giuliani G, Xuejie G, Ciarlo JM, Sines TR, Torres-Alavez JA, Das S, di Sante F, Pichelli E, Glazer R, Müller SK, Abba Omar S, Ashfaq M, Bukovsky M, Im E-S, Jacob D, Teichmann C, … Rechid D (2021) Climate hazard indices projections based on CORDEX-CORE, CMIP5 and CMIP6 ensemble. Clim Dynamics 57(5–6):1293–1383. https://doi.org/10.1007/s00382-021-05640-z
Dong Z, Liu H, Baiyinbaoligao HuH, Khan MYA, Wen J, Chen L, Tian F (2022) Future projection of seasonal drought characteristics using CMIP6 in the Lancang-Mekong River Basin. J Hydrol 610:127815. https://doi.org/10.1016/j.jhydrol.2022.127815
Dunne JP, Horowitz LW, Adcroft AJ, Ginoux P, Held IM, John JG, Krasting JP, Malyshev S, Naik V, Paulot F, Shevliakova E, Stock CA, Zadeh N, Balaji V, Blanton C, Dunne KA, Dupuis C, Durachta J, Dussin R, … Zhao M (2020) The GFDL Earth System Model Version 4.1 (GFDL‐ESM 4.1): Overall coupled model description and simulation characteristics. J Adv Model Earth Syst 12(11). https://doi.org/10.1029/2019MS002015
Eyring V, Bony S, Meehl GA, Senior CA, Stevens B, Stouffer RJ, Taylor KE (2016) Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9(5):1937–1958. https://doi.org/10.5194/gmd-9-1937-2016
Fan X, Duan Q, Shen C, Wu Y, Xing C (2020) Global surface air temperatures in CMIP6: historical performance and future changes. Environ Res Lett 15(10):104056. https://doi.org/10.1088/1748-9326/abb051
Fayad D (2023) Food insecurity and climate shocks in Madagascar. Selected Issues Papers 2023(037):1. https://doi.org/10.5089/9798400242601.018
Gebrechorkos SH, Pan M, Lin P, Anghileri D, Forsythe N, Pritchard DMW, Fowler HJ, Obuobie E, Darko D, Sheffield J (2022) Variability and changes in hydrological drought in the Volta Basin, West Africa. J Hydrol: Regional Studies 42:101143. https://doi.org/10.1016/j.ejrh.2022.101143
Haile GG, Tang Q, Hosseini‐Moghari S, Liu X, Gebremicael TG, Leng G, Kebede A, Xu X, Yun X (2020) Projected impacts of climate change on drought patterns over East Africa. Earth’s Future 8(7). https://doi.org/10.1029/2020EF001502
Hameed M, Ahmadalipour A, Moradkhani H (2020) Drought and food security in the Middle East: an analytical framework. Agric for Meteorol 281:107816. https://doi.org/10.1016/j.agrformet.2019.107816
Harrington J, Wolski P, Pinto I, Ramarosandratana AM, Barimalala R, Vautard R, Philip S, Kew S, Singh R, Heinrich D, Arrighi J, Raju E, Thalheimer L, Razanakoto T, Van Aalst M, Li S, Bonnet R, Yang W, Otto FEL, Van Oldenborgh GJ (2022) Limited Role of Climate Change in Extreme Low Rainfall Associated with Southern Madagascar Food Insecurity, 2019–21. Environ Res Clim 1(2):021003. https://doi.org/10.1088/2752-5295/aca695
Hoffmann D, Gallant AJE, Arblaster JM (2020) Uncertainties in drought from index and data selection. J Geophys Res: Atmos 125(18). https://doi.org/10.1029/2019JD031946
IPC (2021) Madagascar [Grand South] : Food security and nutrition snapshot. https://rb.gy/wyibm Accessed 10–07–2023
IPCC (Ed.) (2023) Summary for policymakers. In Climate change 2021 – the physical science basis: working group I contribution to the sixth assessment report of the intergovernmental panel on climate change (pp 3–32). Cambridge University Press. https://doi.org/10.1017/9781009157896.001
Kaur A, Sood SK (2020) Deep learning based drought assessment and prediction framework. Eco Inform 57:101067. https://doi.org/10.1016/j.ecoinf.2020.101067
Khan R, Gilani H (2021) Global drought monitoring with drought severity index (DSI) using Google Earth Engine. Theoret Appl Climatol 146(1–2):411–427. https://doi.org/10.1007/s00704-021-03715-9
King-Okumu C, Tsegai D, Sanogo D, Kiprop J, Cheboiwo J, Sarr MS, Inacio da Cunha M, Salman M (2021) How can we stop the slow-burning systemic fuse of loss and damage due to land degradation and drought in Africa? Curr Opin Environ Sustain 50:289–302. https://doi.org/10.1016/j.cosust.2021.04.008
Kogan F, Guo W, Yang W (2019) Drought and food security prediction from NOAA new generation of operational satellites. Geomat Nat Haz Risk 10(1):651–666. https://doi.org/10.1080/19475705.2018.1541257
Leng G, Hall J (2019) Crop yield sensitivity of global major agricultural countries to droughts and the projected changes in the future. Sci Total Environ 654:811–821. https://doi.org/10.1016/j.scitotenv.2018.10.434
Li Z, Liu T, Huang Y, Peng J, Ling Y (2022) Evaluation of the CMIP6 precipitation simulations over global land. Earth’s Future 10(8). https://doi.org/10.1029/2021EF002500
Malik A, Kumar A, Salih SQ, Kim S, Kim NW, Yaseen ZM, Singh VP (2020) Drought index prediction using advanced fuzzy logic model: regional case study over Kumaon in India. PLoS ONE 15(5):e0233280. https://doi.org/10.1371/journal.pone.0233280
Masih I, Maskey S, Mussá FEF, Trambauer P (2014) A review of droughts on the African continent: a geospatial and long-term perspective. Hydrol Earth Syst Sci 18(9):3635–3649. https://doi.org/10.5194/hess-18-3635-2014
Mesbahzadeh T, Mirakbari M, Mohseni Saravi M, Soleimani Sardoo F, Miglietta MM (2020) Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP). Meteorol Appl 27(1). https://doi.org/10.1002/met.1856
Meza I, Siebert S, Döll P, Kusche J, Herbert C, Eyshi Rezaei E, Nouri H, Gerdener H, Popat E, Frischen J, Naumann G, Vogt JV, Walz Y, Sebesvari Z, Hagenlocher M (2020) Global-scale drought risk assessment for agricultural systems. Nat Hazard 20(2):695–712. https://doi.org/10.5194/nhess-20-695-2020
Mmame B, Sunitha P, Samatha K, Rao SR, Satish P, Amasarao A, Chandra Sekhar K (2023) Assessment of CMIP6 model performance in simulating atmospheric aerosol and precipitation over Africa. Adv Space Res 72(8):3096–3108. https://doi.org/10.1016/j.asr.2023.06.030
Nabaei S, Sharafati A, Yaseen ZM, Shahid S (2019) Copula based assessment of meteorological drought characteristics: regional investigation of Iran. Agric for Meteorol 276–277:107611. https://doi.org/10.1016/j.agrformet.2019.06.010
O’Neill BC, Kriegler E, Riahi K, Ebi KL, Hallegatte S, Carter TR, Mathur R, van Vuuren DP (2014) A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Clim Change 122(3):387–400. https://doi.org/10.1007/s10584-013-0905-2
O’Neill BC, Kriegler E, Ebi KL, Kemp-Benedict E, Riahi K, Rothman DS, van Ruijven BJ, van Vuuren DP, Birkmann J, Kok K, Levy M, Solecki W (2017) The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century. Glob Environ Chang 42:169–180. https://doi.org/10.1016/j.gloenvcha.2015.01.004
Randriamparany ST, Randrianalijaona TM (2022) The vulnerability of Antandroy women to droughts in Ambovombe Androy (Madagascar). Int J Disaster Risk Reduction 72:102821. https://doi.org/10.1016/j.ijdrr.2022.102821
Riahi K, van Vuuren DP, Kriegler E, Edmonds J, O’Neill BC, Fujimori S, Bauer N, Calvin K, Dellink R, Fricko O, Lutz W, Popp A, Cuaresma JC, Kc S, Leimbach M, Jiang L, Kram T, Rao S, Emmerling J, Tavoni M (2017) The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Global Environ Change 42:153–168. https://doi.org/10.1016/j.gloenvcha.2016.05.009
Seneviratne SI, Zhang X, Adnan M, Badi W, Dereczynski C, Di Luca A, Ghosh S, Iskandar I, Kossin J, Lewis S, Otto F, Pinto I, Satoh M, Vicente-Serrano SM, Wehner M, Zhou B (2021) Weather and climate extreme events in a changing climate. In: climate change 2021 – the physical science basis (pp 1513–1766). Cambridge University Press. https://doi.org/10.1017/9781009157896.013
Serele C, Pérez-Hoyos A, Kayitakire F (2020) Mapping of groundwater potential zones in the drought-prone areas of south Madagascar using geospatial techniques. Geosci Front 11(4):1403–1413. https://doi.org/10.1016/j.gsf.2019.11.012
Sobhani B, Zengir VS (2020) Modeling, monitoring and forecasting of drought in south and southwestern, Iran Iran. Model Earth Syst Environ 6(1):63–71. https://doi.org/10.1007/s40808-019-00655-2
Song Z, Xia J, She D, Li L, Hu C, Hong S (2021) Assessment of meteorological drought change in the 21st century based on CMIP6 multi-model ensemble projections over mainland China. J Hydrol 601:126643. https://doi.org/10.1016/j.jhydrol.2021.126643
Su B, Huang J, Mondal SK, Zhai J, Wang Y, Wen S, Gao M, Lv Y, Jiang S, Jiang T, Li A (2021) Insight from CMIP6 SSP-RCP scenarios for future drought characteristics in China. Atmos Res 250:105375. https://doi.org/10.1016/j.atmosres.2020.105375
Swart NC, Cole JNS, Kharin VV, Lazare M, Scinocca JF, Gillett NP, Anstey J, Arora V, Christian JR, Hanna S, Jiao Y, Lee WG, Majaess F, Saenko OA, Seiler C, Seinen C, Shao A, Sigmond M, Solheim L, … Winter B (2019) The Canadian earth system model version 5 (CanESM5.0.3). Geosci Model Dev 12(11):4823–4873. https://doi.org/10.5194/gmd-12-4823-2019
Tan G, Ayugi B, Ngoma H, Ongoma V (2020) Projections of future meteorological drought events under representative concentration pathways (RCPs) of CMIP5 over Kenya. East Africa Atmos Res 246:105112. https://doi.org/10.1016/j.atmosres.2020.105112
Tatebe H, Ogura T, Nitta T, Komuro Y, Ogochi K, Takemura T, Sudo K, Sekiguchi M, Abe M, Saito F, Chikira M, Watanabe S, Mori M, Hirota N, Kawatani Y, Mochizuki T, Yoshimura K, Takata K, O’ishi R, … Kimoto M (2019) Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6. Geosci Model Dev 12(7):2727–2765. https://doi.org/10.5194/gmd-12-2727-2019
Tirivarombo S, Osupile D, Eliasson P (2018) Drought monitoring and analysis: standardised precipitation evapotranspiration index (SPEI) and standardised precipitation index (SPI). Phys Chem Earth Parts a/b/c 106:1–10. https://doi.org/10.1016/j.pce.2018.07.001
Tran-Anh Q, Ngo-Duc T, Espagne E, Trinh-Tuan L (2023) A 10-km CMIP6 downscaled dataset of temperature and precipitation for historical and future Vietnam climate. Sci Data 10(1):257. https://doi.org/10.1038/s41597-023-02159-2
Ukkola AM, De Kauwe MG, Roderick ML, Abramowitz G, Pitman AJ (2020) Robust future changes in meteorological drought in CMIP6 projections despite uncertainty in precipitation. Geophys Res Lett 47(11). https://doi.org/10.1029/2020GL087820
UNCCD (2022) Drought in numbers 2022 - restoration for readiness and resilience. https://rb.gy/p5x73. Accessed 19–07–2023
Vetter T, Reinhardt J, Flörke M, van Griensven A, Hattermann F, Huang S, Koch H, Pechlivanidis IG, Plötner S, Seidou O, Su B, Vervoort RW, Krysanova V (2017) Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins. Clim Change 141(3):419–433. https://doi.org/10.1007/s10584-016-1794-y
Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23(7):1696–1718. https://doi.org/10.1175/2009JCLI2909.1
Wang Q, Zeng J, Qi J, Zhang X, Zeng Y, Shui W, Xu Z, Zhang R, Wu X, Cong J (2021) A multi-scale daily SPEI dataset for drought characterization at observation stations over mainland China from 1961 to 2018. Earth Syst Sci Data 13(2):331–341. https://doi.org/10.5194/essd-13-331-2021
WFP (2022) Don’t look the other way: Madagascar in the grip of drought and famine. https://rb.gy/y8aw7. Accessed 22–06–2023
WHO (2023) Drought. https://rb.gy/bg6no. Accessed 19–07–2023
Wood AW, Leung LR, Sridhar V, Lettenmaier DP (2004) Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Change 62(1–3):189–216. https://doi.org/10.1023/B:CLIM.0000013685.99609.9e
World Meteorological Organization (2012) Standardized precipitation index user guide (M. Svoboda, M. Hayes and D. Wood)(WMO-N0.1090)
Wu T, Yu R, Lu Y, Jie W, Fang Y, Zhang J, Zhang L, Xin X, Li L, Wang Z, Liu Y, Zhang F, Wu F, Chu M, Li J, Li W, Zhang Y, Shi X, Zhou W, … Hu A (2021) BCC-CSM2-HR: a high-resolution version of the Beijing climate center climate system model. Geosci Model Dev 14(5):2977–3006. https://doi.org/10.5194/gmd-14-2977-2021
Xu L, Wang A (2019) Application of the bias correction and spatial downscaling algorithm on the temperature extremes from CMIP5 multimodel ensembles in China. Earth Space Sci 6(12):2508–2524. https://doi.org/10.1029/2019EA000995
Yazdandoost F, Moradian S, Izadi A, Aghakouchak A (2021) Evaluation of CMIP6 precipitation simulations across different climatic zones: uncertainty and model intercomparison. Atmos Res 250:105369. https://doi.org/10.1016/j.atmosres.2020.105369
Yevjevich VM (1967) An objective approach to definitions and investigations of continental hydrologic droughts. In: Hydrology paper no. 23. Fort Collins, Colorado State University, p 19
Zhai J, Mondal SK, Fischer T, Wang Y, Su B, Huang J, Tao H, Wang G, Ullah W, Uddin MJ (2020) Future drought characteristics through a multi-model ensemble from CMIP6 over South Asia. Atmos Res 246:105111. https://doi.org/10.1016/j.atmosres.2020.105111
Acknowledgements
The authors acknowledge the World Climate Research Programme, which, through its working group on coupled modeling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies that support CMIP6 and ESGF. The authors are also grateful to the Copernicus Climate Change Service for providing the ERA5 climate data.
Author information
Authors and Affiliations
Contributions
All authors contributed to the study’s conception and design. Conceptualization, data collection and analysis, formal analysis, data curation, and writing of the original draft were performed by Mirindra Finaritra Rabezanahary Tanteliniaina. Writing, review, and editing were performed by Mihasina Harinaivo Andrianarimanana. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
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.
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.
About this article
Cite this article
Rabezanahary Tanteliniaina, M.F., Andrianarimanana, M.H. Projection of future drought characteristics in the Great South of Madagascar using CMIP6 and bias-correction spatial disaggregation method. Theor Appl Climatol 155, 1871–1883 (2024). https://doi.org/10.1007/s00704-023-04727-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00704-023-04727-3