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REVIEW OF SEASONAL CLIMATE FORECASTING FOR AGRICULTURE IN SUB-SAHARAN AFRICA

Published online by Cambridge University Press:  25 March 2011

JAMES W. HANSEN*
Affiliation:
Challenge Program on Climate Change, Agriculture and Food Security (CCAFS) International Research Institute for Climate and Society, The Earth Institute, Columbia University, Palisades, NY, USA
SIMON J. MASON
Affiliation:
International Research Institute for Climate and Society, The Earth Institute, Columbia University, Palisades, NY, USA
LIQIANG SUN
Affiliation:
International Research Institute for Climate and Society, The Earth Institute, Columbia University, Palisades, NY, USA
ARAME TALL
Affiliation:
African Studies/SAIS, The Johns Hopkins University, Baltimore, MD, USA
*
Corresponding author: jhansen@iri.columbia.edu

Summary

We review the use and value of seasonal climate forecasting for agriculture in sub-Saharan Africa (SSA), with a view to understanding and exploiting opportunities to realize more of its potential benefits. Interaction between the atmosphere and underlying oceans provides the basis for probabilistic forecasts of climate conditions at a seasonal lead-time, including during cropping seasons in parts of SSA. Regional climate outlook forums (RCOF) and national meteorological services (NMS) have been at the forefront of efforts to provide forecast information for agriculture. A survey showed that African NMS often go well beyond the RCOF process to improve seasonal forecast information and disseminate it to the agricultural sector. Evidence from a combination of understanding of how climatic uncertainty impacts agriculture, model-based ex-ante analyses, subjective expressions of demand or value, and the few well-documented evaluations of actual use and resulting benefit suggests that seasonal forecasts may have considerable potential to improve agricultural management and rural livelihoods. However, constraints related to legitimacy, salience, access, understanding, capacity to respond and data scarcity have so far limited the widespread use and benefit from seasonal prediction among smallholder farmers. Those constraints that reflect inadequate information products, policies or institutional process can potentially be overcome. Additional opportunities to benefit rural communities come from expanding the use of seasonal forecast information for coordinating input and credit supply, food crisis management, trade and agricultural insurance. The surge of activity surrounding seasonal forecasting in SSA following the 1997/98 El Niño has waned in recent years, but emerging initiatives, such as the Global Framework for Climate Services and ClimDev-Africa, are poised to reinvigorate support for seasonal forecast information services for agriculture. We conclude with a discussion of institutional and policy changes that we believe will greatly enhance the benefits of seasonal forecasting to agriculture in SSA.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2011

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References

REFERENCES

Abdulai, A., Barrett, C. B. and Hazell, P. (2004). Food aid for market development in Sub-Saharan Africa. DSGD Discussion Paper No. 5. Washington, DC: International Food Policy Research Institute.Google Scholar
AfDB (2009). Framework Document for the Establishment of the ClimDev-Africa Special Fund (CDSF). Tunis, Tunisia: African Development Bank.Google Scholar
Anderson, W. K. (1984). Plant populations for triticale in a Mediterranean environment. Field Crops Research 8: 281295.CrossRefGoogle Scholar
Archer, E., Mukhala, E., Walker, S., Dilley, M. and Masamvu, K. (2007). Sustaining agricultural production and food security in Southern Africa: an improved role for climate prediction? Climatic Change 83: 287300.CrossRefGoogle Scholar
Archer, E. R. M. (2003). Identifying underserved end-user groups in the provision of climate information. Bulletin of the American Meteorological Society 84: 15251532.CrossRefGoogle Scholar
Arndt, C. and Bacou, M. (2000). Economy wide effects of climate variability and prediction in Mozambique. American Journal of Agricultural Economics 82: 750754.CrossRefGoogle Scholar
Arndt, C., Bacou, M. and Cruz, A. (2003). Climate forecasts in Mozambique: an economic perspective. In Coping with Climate Variability: The Use of Seasonal Climate Forecasts in Southern Africa, 129152 (Eds O'Brien, K. and Vogel, C.). Abingdon, UK: Ashgate Publishing.Google Scholar
Barnston, A. G., Li, S., Mason, S. J., DeWitt, D. G., Goddard, L. and Gong, X. (2010). Verification of the first 11 years of IRI's seasonal climate forecasts. Journal of Applied Meteorology and Climatology 46: 493520.CrossRefGoogle Scholar
Barrett, C. B. (1998). The value of imperfect ENSO forecast information: Discussion. American Journal of Agricultural Economics 80: 11091112.CrossRefGoogle Scholar
Barrett, C. B. (2002). Food security and food assistance programs. In Handbook of Agricultural Economics (Eds Gardner, B. L. and Rausser, G. C.). Amsterdam: Elsevier Science.Google Scholar
Barrett, C. B., Barnett, B. J., Carter, M. R., Chantarat, S., Hansen, J. W., Mude, A. G., Osgood, D. E., Skees, J. R., Turvey, C. G. and Ward, M. N. (2007). Poverty traps and climate risk: limitations and opportunities of index-based risk financing. IRI Tech. Rep. No. 07–03. Palisades, New York: International Research Institute for Climate and Society.Google Scholar
Barrett, C. B., Moser, C. M., McHugh, O. V. and Barison, J. (2004). Better technology, better plots or better farmers? Identifying changes in productivity and risk among Malagasy rice farmers. American Journal of Agricultural Economics 86: 869888.CrossRefGoogle Scholar
Barrett, C. B. and Swallow, B. M. (2006). Fractal poverty traps. World Development 34: 115.CrossRefGoogle Scholar
Basher, R., Clark, C., Dilley, M., and Harrison, M. (Ed) (2001). Coping with Climate: A Way Forward. Summary and Proposals for Action. Palisades, New York: International Research Institute for Climate Prediction.Google Scholar
Blench, R. (1999). Seasonal climate forecasting: Who can use it and how should it be disseminated? Natural Resource Perspectives 47: 15.Google Scholar
Blench, R. (2003). Forecasts and farmers: exploring the limitations. In Coping with Climate Variability: The Use of Seasonal Climate Forecasts in Southern Africa, 5971 (Eds O'Brien, K. and Vogel, C.). Hampshire, UK: Ashgate.Google Scholar
Boulahya, M., Stewart-Cerda, M., Pratt, M. and Sponberg, K. (2005). Climate, communications, and innovative technologies: potential impacts and sustainability of new radio and internet linkages in rural African communities. Climatic Change 70: 299310.CrossRefGoogle Scholar
Broad, K. and Agrawala, S. (2000). The Ethiopia food crisis – uses and limits of climate forecasts. Science 289: 16931694.CrossRefGoogle ScholarPubMed
Buizer, J. L., Foster, J. and Lund, D. (2000). Global impacts and regional actions: Preparing for the 1997–98 El Nino. Bulletin of the American Meteorological Society 81: 21212139.2.3.CO;2>CrossRefGoogle Scholar
Byerlee, D., Jayne, T. S. and Myers, R. J. (2006). Managing food price risks and instability in a liberalizing market environment: Overview and policy options. Food Policy 31: 275287.CrossRefGoogle Scholar
Cane, M. A., Eshel, G. and Buckland, R. W. (1994). Forecasting Zimbabwean maize yield using eastern equatorial Pacific sea surface temperature. Nature 16: 30593071.Google Scholar
Carriquiry, M. and Osgood, D. (2008). Index insurance, production practices, and probabilistic climate forecasts. CARD working paper 08-WP 465.Google Scholar
Carter, M. R. and Barrett, C. B. (2006). The economics of poverty traps and persistent poverty: an asset-based approach. Journal of Development Studies 42: 178199.CrossRefGoogle Scholar
Cash, D. and Buizer, J. (2005). Knowledge-action systems for seasonal to interannual climate forecasting: Summary of a workshop report to the Roundtable on Science and Technology for Sustainability, Policy and Global Affairs. Washington, DC: National Academy Press.Google Scholar
Cash, D. W., Borck, J. C. and Patt, A. G. (2006). Countering the loading dock approach to linking science and decision making: comparative analysis of El Nino/Southern Oscillation (ENSO) forecasting systems. Science, Technology and Human Values 31: 465494.CrossRefGoogle Scholar
Cash, D. W., Clark, W. C., Alcock, F., Dickson, N. M., Eckley, N., Guston, D. H., Jager, J. and Mitchell, R. B. (2003). Knowledge systems for sustainable development. Proceedings of the National Academy of Sciences of the United States of America 100: 80868091.CrossRefGoogle ScholarPubMed
CCAFS (2009). Climate Change, Agriculture and Food Security. A CGIAR Challenge Program. CCAFS Report No. 1. Rome and Paris: The Alliance of the CGIAR Centres and ESSP.Google Scholar
Changnon, S. A. (2002). Impacts of the Midwestern drought forecasts of 2000. Journal of Applied Meteorology 41: 10421052.2.0.CO;2>CrossRefGoogle Scholar
Chen, C.-C., McCarl, B. A. and Chang, C.-C. (2008). Strong El Niño–Southern Oscillation events and the economics of the international rice market. Climate Research 36: 113122.CrossRefGoogle Scholar
Chidzambwa, S. and Mason, S. J. (2008). Report of the evaluation of Regional Climate Outlook Forecasts for Africa during the period 1997 to 2007. ACMAD Technical Report, 30.Google Scholar
Childs, I. R. W., Hastings, P. A. and Auliciems, A. (1991). The acceptance of long-range weather forecasts: A question of perception? Australian Meteorological Magazine 39: 105112.Google Scholar
Christianson, C. B. and Vlek, P. L. G. (1991). Alleviating soil fertility constraints to food production in West Africa: efficiency of nitrogen fertilizers applied to food crops. Fertilizer Research 29: 2133.CrossRefGoogle Scholar
Coventry, W. (2001). Getting the odds across – A better way. Climag 5: 14, 16.Google Scholar
Crane, T. A., Roncoli, C., Paz, J., Breuer, N., Broad, K., Ingram, K. T. and Hoogenboom, G. (2010). Forecast skill and farmers’ skills: seasonal climate forecasts and agricultural risk management in the southeastern United States Weather, Climate, and Society 2: 4459.CrossRefGoogle Scholar
Da Silva, J., Garanganga, B., Teveredzi, V., Marx, S. M., Mason, S. J., and Connor, S. J. (2004). Improving epidemic malaria planning, preparedness and response in Southern Africa. Malaria Journal 3: 37.CrossRefGoogle ScholarPubMed
Dercon, S. (1996). Risk, crop choice, and savings: evidence from Tanzania. Economic Development and Cultural Change 44: 485513.CrossRefGoogle Scholar
Dercon, S. and Christiaensen, L. (2007). Consumption risk, technology adoption and poverty traps: evidence from Ethiopia. World Bank Policy Research Working Paper 4257. Washington, DC: World Bank.Google Scholar
Dilley, M. (2000). Reducing vulnerability to climate variability in Southern Africa: the growing role of climate information. Climatic Change 45: 6373.CrossRefGoogle Scholar
Dilley, M. (2001). Institutions and sustainability. In Coping with the Climate: A Way Forward. Preparatory Report and Full Workshop Report, 122131 (Eds Basher, R., Clark, C., Dilley, M. and Harrison, M.). Palisades, New York: International Research Institute for Climate Prediction.Google Scholar
Elbers, C., Gunning, J. W. and Kinsey, B. (2007). Growth and risk: methodology and micro evidence. World Bank Economic Review 21: 120.CrossRefGoogle Scholar
Fafchamps, M. (2003). Rural Poverty, Risk and Development. Cheltenham, UK: Edward Elgar Publishing.CrossRefGoogle Scholar
Fischhoff, B. (1994). What forecasts (seem to) mean. International Journal of Forecasting 10: 387403.CrossRefGoogle Scholar
Gigerenzer, G. and Hoffrage, U. (1995). How to improve Bayesian reasoning without instruction: Frequency formats. Psychological Review 102: 684704.CrossRefGoogle Scholar
Glantz, M. H. (1977). The value of a long-range weather forecast for the West African Sahel. Bulletin American Meteorological Society 58: 150158.2.0.CO;2>CrossRefGoogle Scholar
Glantz, M. H. (Ed) (2001). Once Burned, Twice Shy? Lessons Learned from the 1997/98 El Niño. Tokyo: United Nations University Press.Google Scholar
Glantz, M. H., Katz, R. W. and Nicholls, N. (1991). Teleconnections Linking Worldwide Climate Anomalies: Scientific Basis and Societal Impact. Cambridge: Cambridge University Press.Google Scholar
Goddard, L., Mason, S. J., Zebiak, S. E., Ropelewski, C. F., Basher, R. and Cane, M. A. (2001). Current approaches to seasonal to interannual climate predictions. International Journal of Climatology 21: 11111152.CrossRefGoogle Scholar
Gong, X. F., Barnston, A. G. and Ward, M. N. (2003). The effect of spatial aggregation on the skill of seasonal precipitation forecasts. Journal of Climate 16: 30593071.2.0.CO;2>CrossRefGoogle Scholar
Haile, M. (2005). Weather patterns, food security and humanitarian response in sub-Saharan Africa. Philosophical Transactions of the Royal Society B-Biological Sciences 360: 21692182.CrossRefGoogle ScholarPubMed
Hallstrom, D. G. (2004). Interannual climate variation, climate prediction, and agricultural trade: the costs of surprise versus variability. Review of International Economics 12: 441455.CrossRefGoogle Scholar
Hammer, G. L., Hansen, J., Phillips, J. G., Mjelde, J. W., Hill, H. S. J., Love, A. and Potgieter, A. (2001). Advances in application of climate prediction in agriculture. Agricultural Systems 70: 515553.CrossRefGoogle Scholar
Hansen, J. W., Baethgen, W., Osgood, D., Ceccato, P. and Ngugi, R. K. (2007). Innovations in climate risk management: protecting and building rural livelihoods in a variable and changing climate. Journal of Semi-Arid Tropical Agricultural Research 4 (1). Available from http://www.icrisat.org/Journal/specialproject.htm [accessed 15 November 2010].Google Scholar
Hansen, J. W. and Indeje, M. (2004). Linking dynamic seasonal climate forecasts with crop simulation for maize yield prediction in semi-arid Kenya. Agricultural and Forest Meteorology 125: 143157.CrossRefGoogle Scholar
Hansen, J. W., Marx, S. and Weber, E. (2004a).The role of climate perceptions, expectations, and forecasts in farmer decision making: The Argentine Pampas and South Florida. IRI Technical Report. Palisades, New York: International Research Institute for Climate and Society.Google Scholar
Hansen, J. W., Mishra, A., Rao, K. P. C., Indeje, M. and Ngugi, R. K. (2009). Potential value of GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya. Agricultural Systems 101: 8090.CrossRefGoogle Scholar
Hansen, J. W., Potgieter, A. and Tippett, M. (2004b). Using a general circulation model to forecast regional wheat yields in Northeast Australia. Agricultural and Forest Meteorology 127: 7792.CrossRefGoogle Scholar
Harrison, M. S. J. (2005). The development of seasonal and inter-annual climate forecasting. Climatic Change 70: 201220.CrossRefGoogle Scholar
Hellmuth, M. E., Moorhead, A., Thomson, M. C. and Williams, J. (Eds) (2007). Climate Risk Management in Africa: Learning from Practice. New York: International Research Institute for Climate and Society, Columbia University.Google Scholar
Hellmuth, M. E., Osgood, D. E., Hess, U., Moorhead, A. and Bhojwani, H. (Eds) (2009). Index Insurance and Climate Risk: Prospects for Development and Disaster Management. Climate and Society No. 2. Palisades, New York, USA: International Research Institute for Climate and Society.Google Scholar
Hess, U. and Syroka, J. (2005). Weather-based Insurance in Southern Africa: The Case of Malawi. Washington, D. C: The International Bank for Reconstruction and Development/The World Bank.Google Scholar
Hill, H. S. J., Mjelde, J. W., Love, H. A., Rubas, D. J., Fuller, S. W., Rosenthal, W. and Hammer, G. (2004). Implications of seasonal climate forecasts on world wheat trade: a stochastic, dynamic analysis. Canadian Journal of Agricultural Economics 52: 289312.CrossRefGoogle Scholar
Hudson, J. and Vogel, C. (2003). The use of seasonal forecasts by livestock farmers in South Africa. In Coping with Climate Variability: the Use of Seasonal Climate Forecasts in Southern Africa, 7596 (Eds O'Brien, K. and Vogel, C.). Aldershot: Ashgate Press.Google Scholar
Hulme, M., Biot, Y., Borton, J., Buchanan-Smith, M., Davies, S., Folland, C., Nicholds, N., Seddon, D. and Ward, N. (1992). Seasonal rainfall forecasting for Africa part II – application and impact assessment. International Journal of Environmental Studies 40: 103121.CrossRefGoogle Scholar
Husak, G. J., Michaelsen, J., Kyriakidis, P., Verdin, J. P., Funk, C. and Galu, G. (In press). The Forecast Interpretation Tool – a Monte Carlo technique for blending climatic distributions with probabilistic forecasts. International Journal of Climatology. DOI: 10.1002/joc.2074.CrossRefGoogle Scholar
Indeje, M., Ward, M. N., Ogallo, L. J., Davies, G., Dilley, M. and Anyamba, A. (2006). Predictability of the Normalized Difference Vegetation Index. Journal of Climate 19: 16731687.CrossRefGoogle Scholar
Ingram, K. T., Roncoli, M. C. and Kirshen, P. H. (2002). Opportunities and constraints for farmers of West Africa to use seasonal precipitation forecasts with Burkina Faso as a case study. Agricultural Systems 74: 331349.CrossRefGoogle Scholar
IRI (2005). Mitigating the Effects of Hydro-Climatic Extremes in Southern Africa. Final Report to the USAID Office of Foreign Disaster Assistance. Palisades, NY, USA: International Research Institute for Climate and Society.Google Scholar
IRI (2006). A gap analysis for the implementation of the global climate observing system programme in africa. IRI Tech. Rep. 06–01. Palisades, New York: International Research Institute for Climate and Society.Google Scholar
Jayne, T. S., Zulu, B. and Nijhoff, J. J. (2006). Stabilizing food markets in eastern and southern Africa. Food Policy 31: 328341.CrossRefGoogle Scholar
Jochec, K. G., Mjelde, J. W., Lee, A. C. and Conner, J. R. (2001). Use of seasonal climate forecasts in rangeland-based livestock operations in West Texas. Journal of Applied Meteorology 40: 16291630.2.0.CO;2>CrossRefGoogle Scholar
Jones, J. W., Hansen, J. W., Royce, F. S. and Messina, C. D. (2000). Potential benefits of climate forecasting to agriculture. Agriculture, Ecosystems and Environment 82: 169184.CrossRefGoogle Scholar
Kebede, Y. (1992). Risk behavior and new agricultural technologies: the case of producers in the central highlands of Ethiopia. Quarterly Journal of International Agriculture 31: 269284.Google Scholar
Kelly, V., Adesina, A. A. and Gordon, A. (2003). Expanding access to agricultural inputs in Africa: a review of recent market development experience. Food Policy 28: 379404.CrossRefGoogle Scholar
Klopper, E. and Bartman, A. (2003). Forecasts and commercial agriculture: a survey of user needs in South Africa. In Coping with Climate Variability: The Use of Seasonal Climate Forecasts in Southern Africa, 170182 (Eds O'Brien, K. and Vogel, C.). Abingdon, UK: Ashgate Publishing.Google Scholar
Klopper, E., Vogel, C. H. and Landman, W. A. (2006). Seasonal climate forecasts – Potential agricultural risk management tools? Climatic Change 76: 7390.CrossRefGoogle Scholar
Lemos, M. C. and Dilling, L. (2007). Equity in forecasting climate: can science save the world's poor? Science Public Policy 34: 109116.CrossRefGoogle Scholar
Lemos, M. C., Finan, T. J., Fox, R. W., Nelson, D. R. and Tucker, J. (2002). The use of seasonal climate forecasting in policymaking: lessons from Northeast Brazil. Climate Change 55: 479507.CrossRefGoogle Scholar
Letson, D., Llovet, I., Podesta, G., Royce, F., Brescia, V., Lema, D. and Parellada, G. (2001). User perspectives of climate forecasts: crop producers in Pergamino, Argentina. Climate Research 19: 5767.CrossRefGoogle Scholar
Luo, H., Skees, J. R. and Marchant, M. A. (1994). Weather information and the potential for intertemporal adverse selection in crop insurance. Review of Agricultural Economics 16: 441451.CrossRefGoogle Scholar
Luseno, W. K., McPeak, J. G., Barret, C., Little, P. D. and Gebru, G. (2003). Assessing the value of climate forecast information for pastoralists: evidence from southern Ethiopia and northern Kenya. World Development 31: 14771494.CrossRefGoogle Scholar
Lybbert, T. J., Barrett, C., McPeak, J. G. and Luseno, W. K. (2007). Bayesian herders: asymmetric updating of rainfall beliefs in response to external forecasts. World Development 35: 480497.CrossRefGoogle Scholar
Lyon, B. and Mason, S. J. (2009). The 1997–98 summer rainfall season in Southern Africa. Part II: model simulations and coupled model forecasts. Journal of Climate 22: 38023818.CrossRefGoogle Scholar
Madden, B. and Hayes, G. (2000). Building dairy farmer demand for climate information. In Proceedings of the Conference on Managing Australian Climate Variability. Albury, NSW, Australia, 23–25 October 2000.Google Scholar
Malusalila, P. M. (2000). Experiences of an agricultural input supplier. In Proceedings of the International Forum on Climate Prediction, Agriculture and Development, 8286 Palisades, New York, USA: International Research Institute for Climate and Society.Google Scholar
Marra, M., Pannell, D. J. and Ghadim, A. K. A. (2003). The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: where are we on the learning curve? Agricultural Systems 75: 215234.CrossRefGoogle Scholar
Marx, S. M., Weber, E. U., Orlove, B. S., Leiserowitz, A., Krantz, D. H., Roncolia, C. and Phillips, J. (2007). Communication and mental processes: Experiential and analytic processing of uncertain climate information. Global Environmental Change 17: 4758.CrossRefGoogle Scholar
Mason, S. J. (2008). ‘Flowering walnuts in the wood’ and other bases for seasonal climate forecasting. In Seasonal Forecasts, Climatic Change and Human Health, 1329 (Eds Thomson, M. C., Garcia-Herrera, R. and Beniston, M.). Dordrecht: Springer.CrossRefGoogle Scholar
Mason, S. J. and Jury, M. R. (1997). Climatic change and inter-annual variability over southern Africa: a reflection on underlying processes. Progress in Physical Geography 21: 2350.CrossRefGoogle Scholar
McCrea, R., Dalgleish, L. and Coventry, W. (2005). Encouraging use of seasonal climate forecasts by farmers. International Journal of Climatology 25: 11271137.CrossRefGoogle Scholar
Meinke, H., Nelson, R., Kokic, P., Stone, R., Selvaraju, R. and Baethgen, W. (2006). Actionable climate knowledge: from analysis to synthesis. Climate Research 33: 101110.CrossRefGoogle Scholar
Meza, F. J., Hansen, J. W. and Osgood, D. (2008). Economic value of seasonal climate forecasts for agriculture: review of ex ante assessments and recommendations for future research. Journal of Applied Meteorology and Climatology 47: 12691286.CrossRefGoogle Scholar
Miranda, M. J. and Glauber, J. W. (1997). Systemic risk, reinsurance, and the failure of crop insurance markets. American Journal of Agricultural Economics 79: 206215.CrossRefGoogle Scholar
Mishra, A., Hansen, J. W., Dingkuhn, M., Baron, C., Traoré, S. B., Ndiaye, O. and Ward, M. N. (2008). Sorghum yield prediction from seasonal rainfall forecasts in Burkina Faso. Agricultural and Forestry Meteorology 148: 17981814.CrossRefGoogle Scholar
Moron, V., Robertson, A. W. and Ward, M. N. (2006). Seasonal predictability and spatial coherence of rainfall characteristics in the tropical setting of Senegal. Monthly Weather Review 134: 32483262.CrossRefGoogle Scholar
Moron, V., Robertson, A. W. and Ward, M. N. (2007). Spatial coherence of tropical rainfall at regional scale. Journal of Climate 20: 52445263.CrossRefGoogle Scholar
Moron, V., Lucero, A., Hilario, F., Lyon, B., Robertson, A. W. and DeWitt, D. (2009). Spatio-temporal variability and predictability of summer monsoon onset over the Philippines. Climate Dynamics. 33: 11591177.CrossRefGoogle Scholar
Moron, V., Robertson, A. W. and Qian, J.-H. (2010). Local versus large-scale characteristics of monsoon onset and post-onset rainfall over Indonesia. Climate Dynamics 34: 281291.CrossRefGoogle Scholar
Morris, M., Kelly, V. A., Kopicki, R. and Byerlee, D. (2007). Fertilizer Use in African Agriculture: Lessons Learned and Good Practice Guidelines. Washington, DC: World Bank.CrossRefGoogle Scholar
Mutai, C. C., Ward, M. N. and Colman, A. W. (1998). Towards the prediction of the East Africa short rains based on sea-surface temperature-atmosphere coupling. International Journal of Climatology 18: 975997.3.0.CO;2-U>CrossRefGoogle Scholar
Mwinamo, J. M. (2001). Investigation on Utility of Weather and Climate Forecasts on Farming Activities in Kwale District, Kenya. Silver Springs, MD, USA: NOAA Office of Global Programs.Google Scholar
Myers, R. J. K. and Foale, M. A. (1981). Row spacing and population density in grain sorghum – a simple analysis. Field Crops Research 4: 147154.CrossRefGoogle Scholar
Ndiaye, O., Goddard, L. and Ward, M. N. (2009). Using regional wind fields to improve general circulation model forecasts of July–September Sahel rainfall. International Journal of Climatology 29: 12621275.CrossRefGoogle Scholar
Ndiaye, O., Hansen, J. W. and Robertson, A. (2008). Prediction of rainfall frequency and related quantities in West Africa. Report prepared for the International Federation of the Red Cross – West Africa. International Research Institute for Climate and Society.Google Scholar
Ndiaye, O., Ward, M. N. and Thiaw, W. (In press). Predictability of seasonal Sahel rainfall using GCMs and lead-time improvements through a coupled model. Journal of Climate. doi:10.1175/2010JCLI3557.1CrossRefGoogle Scholar
Nelson, D. and Finan, T. (2000). The emergence of a climate anthropology in Northeast Brazil. Practicing Anthropologist 22: 610.CrossRefGoogle Scholar
Ngugi, R. K. (2002). Climate forecast information: the status, needs and expectations among smallholder agro-pastoralists in Machakos District, Kenya. IRI Technical Report 31. Palisades, NY: IRI, Columbia Earth Institute, Columbia University.Google Scholar
Nicholls, N. and Kestin, T. (1998). Communicating climate. Climatic Change 40: 417420.CrossRefGoogle Scholar
O'Brien, K., Sygna, L., Otto Naess, L., Kingamkono, R. and Hochobeb, B. (2000). Is Information Enough? User Responses to Seasonal Climate Forecasts in Southern Africa. Oslo, Norway: Center for International Climate and Environment Research (CICERO)Google Scholar
Ogallo, L., Bessemoulin, P., Ceron, J. P., Mason, S. and Connor, S. J. (2008). Adapting to climate variability and change: The climate outlook forum process. WMO Bulletin 57: 93102.Google Scholar
Omamo, S. W. and Lynam, J. K. (2003). Agricultural science and technology policy in Africa. Research Policy 32: 16811694.CrossRefGoogle Scholar
Orlove, B. S. and Roncoli, C. (2006). Integration of Climate Information from Multiple Sources through Group Discussion in Ugandan Farm Communities. New York: Center for Research on Environmental Decisions, Columbia University.Google Scholar
Orlove, B. S. and Tosteson, J. L. (1999). The application of seasonal to interannual climate forecasts based on El Niño-Southern Oscillation (ENSO) events: Lessons from Australia, Brazil, Ethiopia, Peru and Zimbabwe. Berkeley Workshop on Environmental Politics Working Paper WP 99–3. Institute of International Studies, University of California, Berkeley.Google Scholar
Osgood, D. E., Suarez, P., Hansen, J. W., Carriquiry, M. and Mishra, A. (2008). Integrating seasonal forecasts and insurance for adaptation among subsistence farmers: the case of malawi. World Bank Policy Research Working Paper No. 4651. Washington, DC: World Bank.Google Scholar
Pala, M., Matar, A. and Mazid, A. (1996). Assessment of the effects of environmental factors on the response of wheat to fertilizer in on-farm trials in Northern Syria. Experimental Agriculture 32: 339349.CrossRefGoogle Scholar
Palmer, T. N. and Anderson, D. L. T. (1994). The prospect for seasonal forecasting – a review paper. Quarterly Journal of the Royal Meteorological Society 120: 755793.Google Scholar
Patt, A., Suarez, P. and Gwata, C. (2005). Effects of seasonal climate forecasts and participatory workshops among subsistence farmers in Zimbabwe. Proceedings of the National Academy of Sciences 102: 1262312628.CrossRefGoogle ScholarPubMed
Patt, A. G. (2001). Understanding uncertainty: forecasting seasonal climate for farmers in Zimbabwe. Risk Decision and Policy 6: 105119.CrossRefGoogle Scholar
Patt, A. G. and Gwata, C. (2002). Effective seasonal climate forecasts applications: examining constraints for subsistence farmers in Zimbabwe. Global Environmental Change-Human and Policy Dimensions 12: 185195.CrossRefGoogle Scholar
Patt, A. G., Ogallo, L. J. and Hellmuth, M. (2007). Learning from 10 years of climate outlook forums in Africa. Science 318: 4950.CrossRefGoogle ScholarPubMed
Patt, A. G. and Schrag, D. P. (2003). Using specific language to describe risk and probability. Climatic Change 61: 1730.CrossRefGoogle Scholar
Phillips, J. (2003). Determinants of forecast use among communal farmers in Zimbabwe. In Coping with Climate Variability: The Use of Seasonal Climate Forecasts in Southern Africa, 110126 (Eds O'Brien, K. and Vogel, C.). Abingdon, UK: Ashgate Publishing.Google Scholar
Phillips, J. and Orlove, B. S. (2004). Improving climate forecast communications for farm management in Uganda. Final Report to NOAA Office of Global Programs.Google Scholar
Phillips, J. G., Deane, D., Unganai, L. and Chimeli, A. (2002). Implications of farm-level response to seasonal climate forecasts for aggregate grain production in Zimbabwe. Agricultural Systems 74: 351369.CrossRefGoogle Scholar
Phillips, J. G., Unganai, L. and Makaudze, E. (2001). Current and potential use of seasonal climate forecasts for resource-poor farmers in Zimbabwe. In Impacts of El Niño and Climate Variability on Agriculture. ASA Special Publication no. 63, 87100 (Eds Rosenzweig, C., Boote, K. J., Hollinger, S., Iglesias, A. and Phillips, J.). Madison, Wis., USA American Society of AgronomyGoogle Scholar
Piha, M. I. (1993). Optimising fertiliser use and practical rainfall capture in a semi-arid environment with variable rainfall. Experimental Agriculture 29: 405415.CrossRefGoogle Scholar
Podestá, G. P., Letson, D., Messina, C. D., Royce, F. S., Ferreyra, R. A., Jones, J. W., Hansen, J. W., Llovet, I., Grondona, M. O. and O'Brien, J. J. (2002). Use of ENSO-related climate information in agricultural decision making in Argentina: A pilot experience. Agricultural Systems 74: 371392.CrossRefGoogle Scholar
Poulton, C., Kydd, J. and Dorward, A. (2006a). Overcoming market constraints on pro-poor agricultural growth in sub-Saharan Africa. Development Policy Review 24: 243277.CrossRefGoogle Scholar
Poulton, P. L., Kydd, J., Wiggins, S. and Dorward, A. (2006b). State intervention for food price stabilisation in Africa: Can it work? Food Policy 31: 342356.CrossRefGoogle Scholar
Quan, X. W., Webster, P. J., Moore, A. M. and Chang, H. R. (2004). Seasonality in SST-forced atmospheric short-term climate predictability. Journal of Climate 17: 30903108.2.0.CO;2>CrossRefGoogle Scholar
Rengalakshmi, R. (2007). Localized climate forecasting system: seasonal climate and weather prediction for farm level decision-making. In Climate Prediction and Agriculture: Advances and Challenges, 129134 (Eds Sivakumar, M. V. K. and Hansen, J. W.). Berlin: Springer.CrossRefGoogle Scholar
Robertson, A. W., Moron, V. and Swarinoto, Y. (2009). Seasonal predictability of daily rainfall statistics over Indramayu district, Indonesia. International Journal of Climatology 29: 14491462.CrossRefGoogle Scholar
Rockefeller Foundation (2010). African Agriculture and Climate Change Resilience Strategy. New York: Rockefeller Foundation.Google Scholar
Roncoli, C., Jost, C., Kirshen, P. and Hoogenboom, G. (2005). Risk management and social learning in farmers’ responses to seasonal climate forecasts in three agro-ecological zones of Burkina Faso. In American Association of Geographers Annual Meeting. Denver, Colorado.Google Scholar
Roncoli, C., Jost, C., Kirshen, P., Sanon, M., Ingram, K. T., Woodin, M., Somé, L., Ouattara, F., Sanfo, B. J., Sia, C., Yaka, P. and Hoogenboom, G. (2009). From accessing to assessing forecasts: an end-to-end study of participatory climate forecast dissemination in Burkina Faso (West Africa). Climatic Change 92: 433460.CrossRefGoogle Scholar
Rose, E. (2001). Ex ante and ex post labor supply response to risk in a low-income area. Journal of Development Economics 64: 371388.CrossRefGoogle Scholar
Rosenzweig, C. (1994). Maize suffers a sea-change. Nature 370: 175176.CrossRefGoogle Scholar
Rosenzweig, M. R. and Binswanger, H. P. (1993). Wealth, weather risk and the composition and profitability of agricultural investments. The Economic Journal 103: 5678.CrossRefGoogle Scholar
Rosenzweig, M. R. and Stark, O. (1989). Consumption smoothing, migration and marriage. Journal of Political Economy 97: 905926.CrossRefGoogle Scholar
Simtowe, F. P. (2006). Can risk-aversion towards fertilizer explain part of the non-adoption puzzle for hybrid maize? Empirical evidence from Malawi. Journal of Applied Sciences 6: 14901498.CrossRefGoogle Scholar
Suarez, P. and Patt, A. (2004). Caution, cognition, and credibility: the risks of climate forecast application. Risk, Decision and Policy 9: 7589.CrossRefGoogle Scholar
Sun, L., Li, H., Ward, M. N. and Moncunill, D. F. (2007). Climate variability and corn yields in semiarid Ceará, Brazil. Journal of Applied Meteorology and Climatology 46: 226240.CrossRefGoogle Scholar
Sun, L., Moncunill, D. F., Li, H., Moura, A. D. and De Assis De Souza Filho, F. (2005). Climate downscaling over Nordeste, Brazil, Using the NCEP RSM97. Journal of Climate 18: 551567.CrossRefGoogle Scholar
Sun, L., Semazzi, F. H. M., Giorgi, F. and Ogallo, L. (1999). Application of NCAR regional climate model to eastern Africa: Part II: Simulations of interannual variability of precipitation. Journal of Geophysical Research 104: 65496562.CrossRefGoogle Scholar
Sylla, M. B., Gaye, A. T., Pal, J. S., Jenkins, G. S. and Bi, X. Q. (2009). High-resolution simulations of West African climate using regional climate model (RegCM3) with different lateral boundary conditions. Theoretical and Applied Climatology 98: 293314.CrossRefGoogle Scholar
Tall, A., Mason, S. J., Suarez, P., Ait-Chellouche, Y., Diallo, A. A., Braman, L. and van Aalst, M. (In press). Seasonal forecasts to guide disaster management: The experience of the Red Cross during the 2008 floods in West Africa. Weather, Climate and SocietyGoogle Scholar
Tarhule, A. and Lamb, P. J. (2003). Climate Research and Seasonal Forecasting for West Africans. Bulletin of the American Meteorological Society 84: 17411759.CrossRefGoogle Scholar
Thornton, P. K., Fawcett, R. H., Galvin, K. A., Boone, R. B., Hudson, J. W. and Vogel, C. H. (2004). Evaluating management options that use climate forecasts: modelling livestock production systems in the semi-arid zone of South Africa. Climate Research 26: 3342.CrossRefGoogle Scholar
Traoré, P. C. S., Kouressy, M., Vaksmann, M., Tabo, R., Maikano, I., Traoré, S. B. and Cooper, P. (2007). Climate prediction and agriculture: what is different about Sudano-Sahelian West Africa? In Climate Prediction and Agriculture: Advances and Challenges (Eds Sivakumar, M. V. K. and Hansen, J. W.). Berlin: Springer.Google Scholar
Troccoli, A. (2010). Seasonal climate forecasting: a review. Meteorological Applications DOI: 10.1002/met.184.CrossRefGoogle Scholar
UNDP/WMO (2000). Coping with Drought in Sub-Saharan Africa: Better Use of Climate Information. In WMO/TD 1035 Geneva: UN Development Programme and World Meteorological Organization.Google Scholar
Vogel, C. (2000). Useable science: An assessment of long-term seasonal forecasts amongst farmers in rural areas of South Africa. South African Geographical Journal 82: 107116.CrossRefGoogle Scholar
Ward, M. N. (1998). Diagnosis and short-lead time prediction of summer rainfall in tropical North Africa at interannual and multidecadal timescales. Journal of Climate 11: 31673191.2.0.CO;2>CrossRefGoogle Scholar
Washington, R., Harrison, M., Conway, D., Black, E., Challinor, A., Grimes, D., Jones, R., Morse, A., Kay, G. and Todd, M. (2006). African climate change: taking the shorter route. Bull. Amer. Meteor. Soc. 87: 13551366.CrossRefGoogle Scholar
Wilks, D. S. (2000). Diagnostic verification of the Climate Prediction Center long-lead outlooks, 1995–98. Journal of Climate 13: 23892403.2.0.CO;2>CrossRefGoogle Scholar
Wilks, D. S. and Godfrey, (2002). Diagnostic verification of the IRI Net Assessment forecasts, 1997–2000. Journal of Climate 15: 13691377.2.0.CO;2>CrossRefGoogle Scholar
WMO (2009). Report of the World Climate Conference–3: Better climate information for a better future, Geneva, Switzerland, 31 August–4 September 2009. WMO No. 1048. Geneva: World Meteorological Organization.Google Scholar
Zebiak, S. E. (1999). El Niño and the science of climate prediction. Consequences 5: 315.Google Scholar
Ziervogel, G. (2004). Targeting seasonal climate forecasts for integration into household level decisions: the case of small farmers in Lesotho. The Geographical Journal 170: 621.CrossRefGoogle Scholar
Ziervogel, G. and Downing, T. E. (2004). Stakeholder networks: improving seasonal climate forecasts. Climatic Change 65: 73101.CrossRefGoogle Scholar
Zimmerman, F. J. and Carter, M. R. (2003). Asset smoothing, consumption smoothing and the reproduction of inequality under risk and subsistence constraints. Journal of Development Economics 71: 233260.CrossRefGoogle Scholar