Climate change is expected to have severe physical, social, environmental and economic impacts on cities worldwide, both directly and indirectly. Although there are some uncertainties surrounding the understanding of earth’s complex systems, there is strong evidence in current literature and climatic measurements to demonstrate that, as a result of increasing green house gas emissions, atmospheric, land and sea surface temperatures are rising. Global model projections have demonstrated that temperature and rainfall changes throughout Africa, increased frequency of storms and sea-level rise in sub-tropical Oceans, will expose current vulnerabilities of coastal (and other) cities, whilst also potentially heightening risks associated with food security and water resources.
This report shows the results from applying a downscaling methodology developed at the University of Cape Town to nine GCMs and the observed rainfall and temperature data from stations near Maputo. The downscaling relates daily weather systems to the observed rainfall and temperature at each location on each day (to a point-scale). This report will outline impacts and vulnerabilities that the recently available model results typically imply for Maputo, as well as discuss constraints given the paucity of available climatological data and the limitations of the current methods.
Tadross, M.; Johnston, P. Sub-Saharan African Cities: A five-City Network to Pioneer Climate Adaptation through Participatory Research & Local Action. Climate Change Projections for Maputo: Adding value through downscaling. ICLEI &#8211; Local Governments for Sustainability &#8211; Africa, Cape Town, South Africa (2012) 25 pp. ISBN 978-0-9921802-0-1 [Annex 33 from "Adaptation to Climate Change: Stakeholder engagement and understanding impacts - International Council for Local Environment Initiatives (ICLEI)]
Sub-Saharan African Cities: A five-City Network to Pioneer Climate Adaptation through Participatory Research & Local Action. Climate Change Projections for Maputo: Adding value through downscaling