Stockholm Environment Institute
Gina Ziervogel, Anton Cartwright, Adriaan Tas, James Adejuwon, Fernanda Zermoglio, Moliehi Shale and Ben Smith
This study, commissioned by the Rockefeller Foundation, set out to identify and understand the extent to which, and ways in which, information from climate change models is being integrated into agricultural development practice and decision making in Africa.
The development of climate projections for Africa is evolving rapidly. The science of climate modeling is complex and efforts to communicate this science to agricultural users remain rudimentary and fraught with what are perceived to be contradictory and unreliable messages. Within the climate science community there is an emerging effort to make findings more suitable for decision making, but as yet there is very little consensus as to how data may be relied on for decision making.
While awareness of and references to climate change are both increasing, this is mainly based on highly aggregated data from the IPCC Data Distribution Centre and GCMs. The climate data that are used within African agriculture are generated by a few key international organizations. The use of these data is based on their accessibility and familiarity to the users, rather than their suitability to the specific problem or research question being addressed.
As such there is very little discernment of the relative merits of different climate models for specific regions or purposes, even though models differ markedly in their utility for specific regions and parameters.
Modeling of African climate is limited from within Africa. The only African institution that is generating empirical downscaled climate data based on multiple models is CSAG at the University of Cape Town, but applications and further analysis based on this data remain limited. National Meteorological Services Climate Change and Adaptation in African Agriculture have previously not been mandated to work on climate change but in many countries they are starting to explore these issues.
Whilst African agriculture has always had to, and continues to, adapt to changing environmental circumstances (including climate), there is a danger that this adaptation with its focus on climate variability, will not take cognizance of the trends imposed by anthropogenic climate change.
Amongst farmers, applications of the existing downscaled data in decision making is limited to a few progressive and long-term farming schemes and agribusinesses. This is unsurprising as there is currently very little evidence that short-rotation crop farmers stand to benefit from using the available climate data in their decision making due to the temporal and spatial scale at which this data are reported.
What is conspicuous is that very few agricultural policy makers, crop breeders and donor agencies - whom one might expect to adopt a longer-term and more strategic focus - apply the available climate data in their program formulation.
There are currently very few “proofs of concept” – that is examples of agricultural decision makers that have successfully drawn on climate change projection data to take decisions that have improved agricultural productivity or human well-being. This is a function of the temporal and spatial at which climate data are provided as well as the way in which they are reported, perceived in terms of the reliability of the data, questions of their relevance to agriculture, and difficulty in accessing and understanding the data.
To address this “disconnect” between climate science and African agriculture, capacity capable of linking existing climate data and agricultural decision making needs to be created. This is as much an institutional challenge as it is a technical and human resource challenge.
The nature of climate change adaptation demands that efforts to support African agriculture in the face of climate change incorporate a multi-disciplinary set of stakeholders including climate science experts, agricultural practitioners and technicians, local communities/civil society, donors and policy makers. A key challenge involves extending the capacity that currently exists in agro-meteorological disciplines to include agro-climatic competency.
Local “climate change adaptation platforms” have been proposed by a number of development agencies, as a means of promoting collaboration between scientists and practitioners, and enhancing local adaptation capacity including the ability to draw on climate data. It is essential that these institutions design their activities around local needs and not the funding or reporting requirements of the international climate change community.
Climate change adaptation is, at its best, a social learning process that equips local decision makers to respond to a wide range of difficult to predict contingencies brought on by perturbed climates. Although once-off projects are capable of delivering technical capacity and social learning, experience has shown that creating the capacity to apply climate information is a resource intensive process that takes time. Therefore it is important that funding for climate change adaptation goes beyond pilot projects and once-off interventions, and instead allows local institutions to explore the relevant issues and develop the broad set of institutional capacity and technical skills that will equip them for the challenge. Developing the necessary independence and stability will require a lot of inputs from different stakeholders. For donors this presents the challenge of ensuring that funding for processes, which is more difficult to monitor than funding for projects, still delivers robust benefits and value for money.
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