Skip to main content

Advertisement

Log in

Increased seasonal rainfall in the twenty-first century over Ghana and its potential implications for agriculture productivity

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

The slightest change in rainfall could have a significant impact on rain-fed agriculture in countries like Ghana. This study evaluated for the first time the performance of the statistical downscaling model (SDSM-DC) at 2m spatial resolution in simulating rainfall in Ghana for the base period 1981–2010. It further analysed the projected changes in seasonal rainfall pattern across different agro-ecological zones for the twenty-first century under RCP 4.5 and 8.5 emission scenarios over Ghana. Ensemble mean of simulated rainfall data (2011–2099) generated by 43 GCMs in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used as base factors for local future climate scenarios generation. Performance analysis of SDSM-DC shows a Nash–Sutcliffe efficiency, percent bias and RMSE observations standard deviation ratio of 0.88, −19 and 0.34, respectively. Generally, seasonal rainfall amount is expected to increase between 10 and 40% in all the agro-ecological zones in Ghana by the end of the twenty-first century. Off-season rainfall in December–February shows more than 100% increase in the Guinea Savannah zone. Rainfall projected under RCP 4.5 was on average 2% higher than RCP 8.5 in all the seasons throughout the century. Based on these results, it is appropriate to suggest a high incidence of flooding across Ghana in the twenty-first century. This could have dire consequences on agriculture which contribute to a large proportion of Ghana’s GDP. Therefore, for sustainable food production and security in the twenty-first century, Ghana needs climate adaptation policies and programmes that encourage the design and implementation of early warning systems of meteorological hazards and the introduction of new crop varieties that are flood tolerant.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Source: Authors)

Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Abbasnia, M., & Toros, H. (2016). Future changes in maximum temperature using the statistical downscaling model (SDSM) at selected stations of Iran. Modeling Earth Systems and Environment, 2, 1–7. https://doi.org/10.1007/s40808-016-0112-z.

    Article  Google Scholar 

  • Abdo, K. S., Fiseha, B. M., Rientjes, T. H. M., Gieske, A. S. M., & Haile, A. T. (2009). Assessment of climate change impacts on the hydrology of Gilgel Abay catchment in Lake Tana basin, Ethiopia. Hydrological Processes, 23, 3661–3669.

    Google Scholar 

  • Abkar, A., & Habibnajad, M. (2014). Sensitivity of the Statistical Downscaling Model (SDSM) to reanalysis data in arid areas. Arid Biome Scientific and Research Journal, 4, 11–27.

    Google Scholar 

  • Abubakari, A. H., Nyarko, G., Yidana, J. A., Mahunu, G. K., Abagale, F. K., Quainoo, A., et al. (2012). Comparative studies of soil characteristics in Shea parklands of Ghana. Journal of Soil Science and Environmental Management, 3(4), 84–90. https://doi.org/10.5897/JSSEM11.145.

    Article  CAS  Google Scholar 

  • Acheampong, P. K. (1982). Rainfall anomaly along the coast of Ghana its nature and causes Geografiska Annaler. Series A Physical Geography, 64(3/4), 199–211.

    Google Scholar 

  • Adem, A. A., Melesse, A. M., Tilahun, S. A., Setegn, S. G., Ayana, E. K., Wale, A., & Assefa, T. T. (2014). Climate change projections in the Upper Gilgel Abbay River catchment, Bule Nile Basin Ethiopia. In A. M. Melesse, W. Abtew, & S. G. Setgn (Eds.), Nile River BasinChapter 19, Chapter 19 (pp. 363–388). Switzerland: Springer.

    Chapter  Google Scholar 

  • Adhikari, T. R., & Devkota, L. P. (2016). Climate Change and Hydrological Responses in Himalayan Basins, Nepal. In R.B. Sing, U. Schickhoff, & S. Mal (Eds.), Climate Change, Glacier Response, and Vegetation Dynamics in the Himalaya. (pp. 65–85). Newyork: Springer International Publishing.

    Google Scholar 

  • Adu-Prah, S., Appiah-Opoku, S., & Aboagye, D. (2017). Spatiotemporal evidence of recent climate variability in Ghana. African Geographical Review. https://doi.org/10.1080/19376812.2017.1404923.

    Article  Google Scholar 

  • Afrooz, A. H., Akbari, H., Rakhshandehroo, G. R., & Pourtouiserkani, A. (2015). Climate change impact on probable maximum precipitation in Chenar-Rahdar River Basin. Watershed Management, 2015, 36–47.

    Google Scholar 

  • Aguilar, M. Y., Pacheco, T. R., Tobar, J. M., & Quiñónez, J. C. (2009). Vulnerability and adaptation to climate change of rural inhabitants in the central coastal plain of El Salvador. Climate Research, 40, 187–198.

    Article  Google Scholar 

  • Ahmed, K. F., Wang, G., Yu, M., Koo, J., & You, L. (2015). Potential impact of climate change on cereal crop yield in West Africa. Climatic Change, 133, 321–334. https://doi.org/10.1007/s10584-015-1462-7.

    Article  Google Scholar 

  • Allen, M.R., O.P. Dube, W. Solecki, F. Aragon-Durand, W. Cramer, S. Humphreys, M. Kainuma, J. Kala, N. Mahowald, Y. Mulugetta, R. Perez, M. Wairiu, & K. Zickfeld. (2018). Framing and Context. In: Masson-Delmotte, V., P. Zhai, H.-O. Portner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Pean, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.). 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. In Press.

  • Amekudzi, L. K., Yamba, E. I., Preko, K., Asare, E. O., Aryee, J., Baidu, M., & Codjoe, S. N. A. (2015). Variabilities in rainfall onset, cessation and length of rainy season for the various agro-ecological zones of Ghana. Climate, 3, 416–434. https://doi.org/10.3390/cli3020416.

    Article  Google Scholar 

  • Amirabadizadeh, M., Ghazali, A. H., Huang, Y. F., & Wayayok, A. (2016). Downscaling daily precipitation and temperatures over the Langat River Basin in Malaysia: A comparison of two statistical downscaling approaches. International Journal of Water Resources and Environmental Engineering, 8, 120–136.

    Google Scholar 

  • AQUASTAT Survey (2005). Irrigation in Africa in figures – Ghana. FAO Aquastat.

  • Aryee, J. N. A., Amekudzi, L. K., Quansah, E., Klutse, N. A. B., Atiah, W. A., & Yorke, C. (2017). Development of high spatial resolution rainfall data for Ghana. International Journal of Climatology. https://doi.org/10.1002/joc.5238.

    Article  Google Scholar 

  • Asante, F. A., & Amuakwa-Mensah, F. (2015). Climate change and variability in Ghana: Stocktaking. Climate, 3, 78–99. https://doi.org/10.3390/cli3010078.

    Article  Google Scholar 

  • Ashiq, M. W., Zhao, C., Ni, J., & Akhtar, M. (2009). GIS-based high-resolution spatial interpolation of precipitation in mountain–plain areas of Upper Pakistan for regional climate change impact studies. Theoretical and Applied Climatology, 99(3–4), 239–253. https://doi.org/10.1007/s00704-009-0140-y.

    Article  Google Scholar 

  • Asumadu-Sarkodie, S., Owusu, P. A., & Rufangura, P. (2015). Impact analysis of flood in Accra. Ghana. Advances in Applied Science Research, 6(9), 53–78.

    Google Scholar 

  • Azad, S. (2015). Comparison of statistical downscaling techniques for development of future climate change scenarios for the coastal areas of Bangladesh. Institute of Water and Flood Management: Bangladesh University of Engineering and Technology.

    Google Scholar 

  • Babel, M. S., & Turyatunga, E. (2015). Evaluation of climate change impacts and adaptation measures for maize cultivation in the western Uganda agro-ecological zone. Theoretical and Applied Climatology, 119, 239–254.

    Article  Google Scholar 

  • Bader, D., Covey, C., Gutowski, W., Held, I., Kunkel, K., Miller, R., Tokmakian, R., and Zhang, M. (2008). Climate Models: An Assessment of Strengths and Limitations. US Department of Energy Publications. Paper 8. http://digitalcommons.unl.edu/usdoepub/8.

  • Bedia, J., Herrera, S., San Martín, D., Koutsias, N., & Gutiérrez, J. M. (2013). Robust projections of fire weather index in the mediterranean using statistical downscaling. Climatic Change, 120, 229–247. https://doi.org/10.1007/s10584-013-0787-3.

    Article  Google Scholar 

  • Bekele, H. M. (2009). Evaluation of climate change impact on upper blue Nile Basin Reservoirs (case study on Gilgel Gibe Reservoir, Ethiopia). Arbaminch: Arbaminch University.

    Google Scholar 

  • Bessah, E., Raji, A. O., Taiwo, O. J., Agodzo, S. K., & Ololade, O. O. (2019). The impact of varying spatial resolution of climate models on future rainfall simulations in the Pra River Basin (Ghana). Journal of Water and Climate Change. https://doi.org/10.2166/wcc.2019.258.

    Article  Google Scholar 

  • Bessah, E., Raji, A. O., Taiwo, O. J., Agodzo, S. K., & Ololade, O. O. (2018). Variable resolution modelling of near future mean temperature changes in the dry sub-humid region of Ghana. Modeling Earth Systems and Environment, 4(3), 919–933. https://doi.org/10.1007/s40808-018-0479-0.

    Article  Google Scholar 

  • Casanueva, A., Frías, M. D., Herrera, S., San-Martín, D., Kaminovic, K., & Gutiérrez, J. M. (2014). Statistical downscaling of climate impact indices: testing the direct approach. Climatic Change, 127, 547–560. https://doi.org/10.1007/s10584-014-1270-5.

    Article  Google Scholar 

  • CIAT (2011). Predicting the impact of climate change on Cashew growing Regions in Ghana and Cote D’Ivoire. International Center for Tropical Agriculture (CIAT) final report.

  • Codjoe, S. N. A., & Owusu, G. (2011). Climate change/variability and food systems: Evidence from the Afram Plains, Ghana. Regional Environmental Change, 11, 753–765.

    Article  Google Scholar 

  • Chen, S. T., Yu, P. S., & Tang, Y. H. (2010). Statistical downscaling of daily precipitation using support vector machines and multivariate analysis. Journal of Hydrology, 385, 13–22. https://doi.org/10.1016/j.jhydrol.2010.01.021.

    Article  Google Scholar 

  • Che Ros, F., Tosaka, H., Sidek, L. M., & Basri, H. (2016). Homogeneity and trends in long-term rainfall data, Kelantan River Basin, Malaysia. International Journal of River Basin Management, 14(2), 151–163. https://doi.org/10.1080/15715124.2015.1105233.

    Article  Google Scholar 

  • Chu, J. T., Xia, J., Xu, C. Y., & Singh, V. P. (2010). Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River. China. Theoretical and Applied Climatology, 99(1–2), 149–161. https://doi.org/10.1007/s00704-009-0129-6.

    Article  Google Scholar 

  • Crawford, T., Betts, N. L., & Favis-Mortlock, D. T. (2007). GCM grid box choice and predictor selection associated with statistical downscaling of daily precipitation over Northern Ireland. Climate Research, 34, 145–160. https://doi.org/10.3354/cr034145.

    Article  Google Scholar 

  • Dickson, K. B., & Benneh, G. (1995). A new Geography of Ghana (3rd ed.). London: Longman Book Company.

    Google Scholar 

  • Dosio, A., & Panitz, H. J. (2016). Climate change projections for CORDEXAfrica with COSMO-CLM regional climate model and differences with the driving global climate models. Climate Dynamics, 46, 1599–1625. https://doi.org/10.1007/s00382-015-2664-4.

    Article  Google Scholar 

  • Dressler, M. (2007). Interpolation methods for construction of surfaces. PhD thesis. Faculty of Mechatronics and Interdisciplinary Engineering Studies. Technical University of Liberec, Czech Republic.

  • Endris, H. S., Omondi, P., Jain, S., Lennard, C., Hewitson, B., Chang’a, L., et al. (2013). Assessment of the performance of CORDEX regional climate models in simulating East African rainfall. Journal of Climatology, 26(21), 8453–8475.

    Article  Google Scholar 

  • Ekwezuo, C. S., Nnamchi, H. C., & Phil-Eze, P. O. (2017). Projected changes in mean annual rainfall pattern over West Africa during the Twenty First Century. Pakistan Journal of Meteorology, 14(27), 1–11.

    Google Scholar 

  • Ellis, J., & Galvin, K. A. (1994). Climate patterns and land-use practices in the dry zones of Africa. BioScience, 44, 340–349.

    Article  Google Scholar 

  • Farajzadeh, M., Oji, R., Cannon, A. J., Ghavidel, Y., & Bavani, A. M. (2015). An evaluation of single-site statistical downscaling techniques in terms of indices of climate extremes for the Midwest of Iran. Theoretical and Applied Climatology, 120, 377–390. https://doi.org/10.1007/s00704-014-1157-4.

    Article  Google Scholar 

  • Feng-Wen, C., & Chen-Wuing, L. (2012). Estimation of spatial rainfall distribution using inverse-distance weighting (idw) in the middle Taiwan. Paddy Water Environment, 10, 209–222.

    Article  Google Scholar 

  • Fiseha, B. M., Melesse, A. M., Romano, E., Volpi, E., & Fiori, A. (2012). Statistical downscaling of precipitation and temperature for the upper tiber basin in Central Italy. International Journal of Water Sciences. https://doi.org/10.5772/52890.

    Article  Google Scholar 

  • Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins, W., et al. (2013). Evaluation of Climate Models. In T. F. Stocker, D. Qin, G. K. Plattner, M. Tignor, S. K. Allen, J. Boschung, et al. (Eds.), 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: Cambridge University Press.

    Google Scholar 

  • Giorgi, F., Jones, C., & Asrar, G. R. (2009). Addressing climate information needs at the regional level the CORDEX framework. World Meteorological Organization (WMO) Bulletin, 58(3), 175.

    Google Scholar 

  • Gulacha, M. M., & Mulungu, D. M. M. (2016). Generation of climate change scenarios for precipitation and temperature at local scales using SDSM in Wami-Ruvu River Basin Tanzania. Physics and Chemistry of the Earth. https://doi.org/10.1016/j.pce.2016.10.003.

    Article  Google Scholar 

  • GSS. (2011). Annual Report. Ghana Statistical Service (GSS): Accra.

    Google Scholar 

  • Hashmi, M. Z., Shamseldin, A. Y., & Melville, B. W. (2011). Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stochastic Environmental Research and Risk Assessment, 25, 475–484. https://doi.org/10.1007/s00477-010-0416-x.

    Article  Google Scholar 

  • Haylock, M. R., Cawley, G. C., Harpham, C., Wilby, R. L., & Goodess, C. M. (2006). Downscaling heavy precipitation over the UK: A comparison of dynamical and statistical methods and their future scenarios. International Journal of Climatology, 26, 1397–1415. https://doi.org/10.1002/joc.1318.

    Article  Google Scholar 

  • Hoegh-Guldberg, O., D. Jacob, M. Taylor, M. Bindi, S. Brown, I. Camilloni, A. Diedhiou, R. Djalante, K.L. Ebi, F. Engelbrecht, J. Guiot, Y. Hijioka, S. Mehrotra, A. Payne, S.I. Seneviratne, A. Thomas, R. Warren, and G. Zhou, 2018: Impacts of 1.5oC Global Warming on Natural and Human Systems. In: Masson-Delmotte, V., P. Zhai, H.-O. Portner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Pean, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.). 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. In Press.

  • Honaker, J., King, G., & Blackwell, M. (2018). AMELIA II: A Program for Missing Data. Retrieved July 08, 2019, from http://gking.harvard.edu/amelia.

  • Honaker, J., King, G., & Blackwell, M. (2019). AMELIA II: A Program for Missing Data Version 1.7.6. Retrieved March 30, 2020, from https://cran.r-project.org/web/packages/Amelia/vignettes/amelia.pdf.

  • Huang, J., Zhang, J., Zhang, Z., Xu, C., Wang, B., & Yao, J. (2011). Estimation of future precipitation change in the Yangtze River basin by using statistical downscaling method. Stochastic Environmental Research and Risk Assessment, 25(6), 781–792. https://doi.org/10.1007/s00477-010-0441-9.

    Article  Google Scholar 

  • Hewitson, B., Lennard, C., Nikulin, G., & Jones, C. (2012). CORDEX-Africa: a unique opportunity for science and capacity building. CLIVAR Exchanges, 17(3), 6–7.

    Google Scholar 

  • IPCC. (2007). Summary for policymakers. In S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, et al. (Eds.), Climate change 2007 The physical science basis Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.

    Google Scholar 

  • IPCC. (2013). Climate Change 2013 The Physical Science Basis. In T. F. Stocker, D. Qin, G. K. Plattner, M. Tignor, S. K. Allen, J. Boschung, et al. (Eds.), Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (p. 1535). Cambridge: Cambridge University Press.

    Google Scholar 

  • IPCC. (2014). Climate Change 2014 Synthesis Report Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. In Core Writing Team, RK Pachauri, Meyer LA (Eds.), (pp. 151–152) IPCC, Geneva, Switzerland

  • Kisembe, J., Favre, A., Dosio, A., Lennard, C., Sabiiti, G., & imusiima, A. (2018). Evaluation of rainfall simulations over Uganda in CORDEX regional climate models. Theoretical and Applied Climatology. https://doi.org/10.1007/s00704-018-2643-x.

    Article  Google Scholar 

  • Klutse, N. A. B., Owusu, K., Adukpo, D. C., Nkrumah, F., Quagraine, K., Owusu, A., & Gutowski, W. J. (2013). Farmer’s observation on climate change impacts on maize (Zea mays) production in a selected agro-ecological zone in Ghana. Research Journal of Agriculture and Environmental Management, 2(12), 394–402.

    Google Scholar 

  • Knox, J. W., Hess, T.M., Daccache, A., & Perez Ortola, M. (2013). What Are the Projected Impacts of Climate Change on Food Crop Productivity in Africa and South Asia? Retrieved March 28, 2019, from http://r4d.dfid.gov.uk/Output/186428/.

  • Kolavalli, S., Robinson, E., Diao, X., Alpuerto, V., Folledo, R., Slavova, M., & Ngeleza, G. (2012). Economic transformation in Ghana: Where will the path lead? IFPRI Discussion Paper 01161. Washington: International Food Policy Research Institute.

    Google Scholar 

  • Koukidis, E. N., & Berg, A. A. (2009). Sensitivity of the Statistical downscaling Model (SDSM) to reanalysis products. Atmosphere-Ocean, 47, 1–18. https://doi.org/10.3137/AO924.2009.

    Article  Google Scholar 

  • Läderach, P., Martinez-Valle, A., Schroth, G., & Castro, N. (2013). Predicting the future climatic suitability for cocoa farming of the world´s leading producer countries. Ghana and Côte d’Ivoire. Climatic Change, 119, 841. https://doi.org/10.1007/s10584-013-0774-8.

    Article  Google Scholar 

  • Liepert, B. G., & Previdi, M. (2012). Inter-model variability and biases of the global water cycle in CMIP3 coupled climate models. Environmental Research Letters, 7, 1–13. https://doi.org/10.1088/1748-9326/7/1/014006.

    Article  Google Scholar 

  • Liu, Z., Xu, Z., Charles, S. P., Fu, G., & Liu, L. (2011). Evaluation of two statistical downscaling models for daily precipitation over an arid basin in China. International Journal of Climatology, 31, 2006–2020. https://doi.org/10.1002/joc.2211.

    Article  Google Scholar 

  • Lu, G. Y., & Wong, D. W. (2008). An adaptive inverse-distance weighting spatial interpolation technique. Computer Geosciences, 34(9), 1044–1055.

    Article  Google Scholar 

  • Mahmood, R., & Babel, M. S. (2013). Evaluation of SDSM developed by annual and monthly sub-models for downscaling temperature and precipitation in the Jhelum basin, Pakistan and India. Theoretical and Applied Climatology, 113(1–2), 27–44. https://doi.org/10.1007/s00704-012-0765-0.

    Article  Google Scholar 

  • Manzanas, R., Amekudzi, L. K., Preko, K., Herrera, S., & Gutierrez, J. M. (2014). Precipitation variability and trends in Ghana: An intercomparison of observational and reanalysis products. Climatic Change, 124, 805–819. https://doi.org/10.1007/s10584-014-1100-9.

    Article  Google Scholar 

  • McSweeney, C., New, M., Lizcano, G., & Lu, X. (2010). The UNDP climate change country profiles. American Meteorological Society, 91, 157–166.

    Article  Google Scholar 

  • Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J.-F., et al. (2011). The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109(1–2), 213–241. https://doi.org/10.1007/s10584-011-0156-z.

    Article  CAS  Google Scholar 

  • Mensah, C., Amekudzi, L. K., Klutse, N. A. B., Aryee, J. N. A., & Asare, K. (2016). Comparison of rainy season onset, cessation and duration for Ghana from RegCM4 and GMet datasets. Atmospheric and Climate Sciences, 6, 300–309.

    Article  Google Scholar 

  • MFA (2018. Climate Change Profile: Ghana. Ministry of Foreign Affairs (MFA), The Netherlands.

  • Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. American Society of Agricultural and Biological Engineers, 50(3), 885–900.

    Google Scholar 

  • Mullan, D., Fealy, R., & Favis-Mortlock, D. (2012). Developing site-specific future temperature scenarios for Northern Ireland: addressing key issues employing a statistical downscaling approach. International Journal of Climatology. https://doi.org/10.1002/joc.2414.

    Article  Google Scholar 

  • Musah, A. I., Du, J., Udimal, T. B., & Sadick, M. A. (2018). The nexus of weather extremes to agriculture production indexes and the future risk in Ghana. Climate, 6(86), 1–24. https://doi.org/10.3390/cli6040086.

    Article  Google Scholar 

  • Niang, I., Ruppel, O. C., Abdrabo, M. A., Essel, A., Lennard, C., Padgham, J., & Urquhart, P. (2014). Africa. In V. R. Barros, C. B. Field, D. J. Dokken, M. D. Mastrandrea, K. J. Mach, T. E. Bilir, et al. (Eds.), Climate Change 2014 Impacts, Adaptation, and Vulnerability Part B Regional Aspects Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1199–1265). Cambridge, New York: Cambridge University Press.

    Google Scholar 

  • Nutsukpo, D. K., Jalloh, A., Zougmore, R., Nelson, G. C., & Thomas, T. S. (2013). Ghana. In A. Jalloh, H. Roy-Macauley, P. Sereme, R. Zougmore, T. S. Thomas, & G. C. Nelson (Eds.), Assessing the vulnerability of West African agriculture to climate change: a comprehensive analysis. IFPRI Research Monograph. Washington DC: International Food Policy Research Institute (IFPRI). https://doi.org/10.2499/9780896292048.

    Chapter  Google Scholar 

  • Okafor, G., Annor, T., Odai, S., & Agyekum, J. (2019). Volta basin precipitation and temperature climatology: Evaluation of CORDEX-Africa regional climate model simulations. Theoretical and Applied Climatology. https://doi.org/10.1007/s00704-018-2746-4.

    Article  Google Scholar 

  • Osman, Y. Z., & Abdellatif, M. E. (2016). Improving accuracy of downscaling rainfall by combining predictions of different statistical downscale models. Water Science, 30(2), 61–75. https://doi.org/10.1016/j.wsj.2016.10.002.

    Article  Google Scholar 

  • Owusu, K. (2017). Rainfall changes in the savannah zone of northern Ghana 1961–2010. Weather, 99(99), 1–5. https://doi.org/10.1002/wea.2999.

    Article  Google Scholar 

  • Owusu, K., & Kluste, N. A. B. (2013). Simulation of the rainfall regime over Ghana from CORDEX. International Journal of Geosciences, 4, 785–791. https://doi.org/10.4236/ijg.2013.44072.

    Article  Google Scholar 

  • Owusu, K., & Waylen, P. R. (2009). Trends in spatio-temporal rainfall variability in Ghana (1951–2000). Weather, 64, 115–120.

    Article  Google Scholar 

  • Salon, S., Cossarini, G., Libralato, S., Gao Solidoro, X. C., & Giorgi, F. (2008). Downscaling experiment for the Venice lagoon I Validation of the present-day precipitation climatology. Journal of Climate Research, 38(1), 31–41. https://doi.org/10.3354/cr00757.

    Article  Google Scholar 

  • Shongwe, M. E., Van Oldenborgh, G. J., Van Den Hurk, B. J. J. M., De Boer, B., Coelho, C. A. S., & Van Aalst, M. K. (2009). Projected changes in mean and extreme precipitation in Africa under global warming Part I Southern Africa. Journal of Climate, 22(13), 3819–3837.

    Article  Google Scholar 

  • Souvignet, M., Gaese, H., Ribbe, L., Kretschmer, N., & Oyarzún, R. (2010). Statistical downscaling of precipitation and temperature in north-central Chile: An assessment of possible climate change impacts in an arid Andean watershed. Hydrological Sciences Journal, 55(1), 41–57.

    Article  CAS  Google Scholar 

  • Stanturf, J. A., Warren, M. L., Charnley, S., Jr., Polasky, S. C., Goodrick, S. L., Armah, F., & Nyako, Y. A. (2011). Ghana climate change vulnerability and adaptation assessment. Washington: US Agency for International Development.

    Google Scholar 

  • Stennett-Brown, R. K., Jones, J. J. P., Stephenson, T. S., & Taylor, M. A. (2017). Future Caribbean temperature and rainfall extremes from statistical downscaling. International Journal of Climatology, 37, 4828–4845. https://doi.org/10.1002/joc.5126.

    Article  Google Scholar 

  • Sultan, B., & Janicot, S. (2003). The west African monsoon dynamics part ii: Preonset and onset of the summer monsoon. Journal of Climatology, 16, 3407–3427.

    Article  Google Scholar 

  • Sylla, B. M., Nikiema, P. M., Gibba, P., Kebe, I., & Klutse, N. A. B. (2016). Climate change over West Africa Recent trends and future projections. In J. A. Yaro & J. Hesselberg (Eds.), Adaptation to Climate Change and Variability in Rural West Africa (pp. 25–40). Switzerland: Springer International. https://doi.org/10.1007/978-3-319-31499-0_3.

    Chapter  Google Scholar 

  • Tachie-Obeng, E., Hewitson, B., Gyasi, E. A., Abekoe, M. K., & Owusu, G. (2014). Downscaled climate change projections for Wa District in the Savanna Zone of Ghana. Journal of Disaster Research, 9, 4.

    Article  Google Scholar 

  • Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of America Meteorological Society, 93(4), 485–498. https://doi.org/10.1175/BAMS-D-11-000941.

    Article  Google Scholar 

  • Tschakert, P., Sagoe, R., Ofori-Darko, G., & Codjoe, S. N. (2010). Floods in the Sahel: an analysis of anomalies, memory, and anticipatory learning. Climatic Change, 103, 471–502. https://doi.org/10.1007/s10584-009-9776-y.

    Article  Google Scholar 

  • UNEP (2017). Country level impacts of climate change (CLICC) pilot project – Ghana. United Nations Environment Programme (UNEP). Retrieved March 15, 2019, fromhttps://uneplive.unep.org/media/docs/theme/13/clicc_pilot_ghana.pdf.

  • UPEI (2018). Island Database. Climate Records for the Day, and Other Database Information. Retrieved March 15, 2018, fromhttps://climate.upei.ca.

  • Wilby, R.L. (2008). Dealing with uncertainties of future climate: the special challenge of semi-arid regions. Proceedings of the Water Tribune, Expo Zaragoza, Spain.

  • Wilby, R. L., & Dawson, C. W. (2013). The statistical downscaling model (SDSM): Insight from one decade of application. International Journal of Climatology, 33, 1707–1719.

    Article  Google Scholar 

  • Wilby, R. L., & Harris, I. (2006). A framework for assessing uncertainties in climate change impacts: Low flow scenarios for the River Thames. UK. Water Resources Research, 42, W02419. https://doi.org/10.1029/2005WR004065.

    Article  Google Scholar 

  • Wilby, R. L., & Wigley, T. M. L. (1997). Downscaling general circulation model output: a review of methods and limitations. Progress in Physical Geography, 21(4), 530–548. https://doi.org/10.1177/030913339702100403.

    Article  Google Scholar 

  • Wilby, R. L., & Yu, D. (2013). Rainfall and temperature estimation for a data sparse region. Hydrology and Earth System Science, 17, 3937–3955. https://doi.org/10.5194/hess-17-3937-2013.

    Article  Google Scholar 

  • Wilby, R. L., Dawson, C. W., & Barrow, E. M. (2002). SDSM–a decision support tool for the assessment of regional climate impacts. Environmental and Modelling Software, 17, 145–157.

    Article  Google Scholar 

  • Wilby, R. L., Dawson, C. W., Murphy, C., O’Conner, P., & Hawkins, E. (2014). The statistical downscaling model -decision centric (SDSM-DC): Conceptual basis and applications. Climate Research, 61, 251–268.

    Article  Google Scholar 

  • World Bank. (2010). Economics of adaptation to climate change (p. 2010). Ghana Country Study; World Bank: Washington, DC, USA.

    Google Scholar 

  • World Bank Databank (2017). World development indicators. Retrieved June 22, 2017, fromhttp://databank.worldbank.org/data/reports.aspx?source=world-development-indicators.

  • Yates, D. N., Miller, K. A., Wilby, R. L., & Kaatz, L. (2015). Decision-centric adaptation appraisal for water management across Colorado’s Continental Divide. Climate Risk Management: In Press.

    Book  Google Scholar 

  • Yengoh, G. T., Armah, F. A., Onumah, E. E., & Odoi, J. O. (2010). Trends in agriculturally-relevant rainfall characteristics for small-scale agriculture in Northern Ghana. Journal of Agricultural Science, 2(3), 3–16.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the developers of SDSM and the Loughborough University for making the software and NCEP dataset freely available. The authors are sincerely grateful to Professor Robert L. Wilby who helped to improve the scientific message of the manuscript for clarity. Finally, the authors thank the editor and the anonymous reviewers for their constructive comments that have improved the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Enoch Bessah.

Additional information

Publisher's Note

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

Appendix

Appendix

See Table

Table 5 Projected changes (%) in seasonal rainfall in the for the period 2020s 92011–2040), 2050s (2041–2070) and 2080s (2071–2100) from observed records (1981–2010) under the RCP 4.5 and 8.5 emission scenario.

5

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bessah, E., Boakye, E.A., Agodzo, S.K. et al. Increased seasonal rainfall in the twenty-first century over Ghana and its potential implications for agriculture productivity. Environ Dev Sustain 23, 12342–12365 (2021). https://doi.org/10.1007/s10668-020-01171-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10668-020-01171-5

Keywords

Navigation