Uncertainty in regional climate projections isn’t going away, and that’s an inconvenient truth the development community will have to face, says Christoph Müller of the Potsdam Institute for Climate Impacts Research in Germany.
Müller recently authored a report on expected climate change impacts in sub-Saharan Africa, at the behest of the German Development Institute (GDI), a Bonn-based think tank. A top recommendation of the final report, published 24 April and presented at the IHDP conference last month, is that adaptation strategies should not be motivated by specific impact projections, but instead should work on reducing vulnerability to environmental change in general.
An expert on climate impacts on agriculture and land-use, Müller found while scoping the report for GDI that there was a mistaken assumption by development experts that many of the current uncertainties in predicting climate change will soon clear up. “In the adaptation community, they often have the feeling that if we wait for another five years, we will know exactly what the weather will be,” he says.
So he turned the focus of the report around from cataloging impacts to dealing with uncertainty. “This report basically is trying to raise awareness that you will never get very accurate projections of what you will have to adapt to. Don’t wait for that. You have to adapt to uncertainty,” says Müller.
I talked to Müller to find out more about what adaptation planners in sub-Saharan Africa are up against and how they might tackle changes they can’t forsee. What climate models agree on is that the continent will warm a bit more than the global average – roughly 2.0 to 4.5 degrees centigrade, according to three emissions scenarios of the Intergovernmental Panel on Climate Change.
“But that’s where the certainty stops,” he says. Precipitation projections, for example, are important for many impacts studies – of freshwater availability, agricultural production, and development of water-hungry industries – but global climate models differ wildly on precipitation in African locales. “There’s maybe only a few locations in sub-Saharan Africa where you don’t have a scenario that says it’s going to get significantly wetter and another scenario that says it’s going to get significantly drier,” Müller points out.
A particular problem for sub-Saharan Africa is that observational data from meteorological stations is sparse, and many stations formerly sending out data have stopped (‘historical’ stations on map, below) – making it hard to produce local projections. This is usually achieved through a technique called ‘downscaling’, which involves using weather statistics and interpolating data to add details between the distant grid points of a global climate model. But without recent observations to constrain the calculations, it becomes near impossible to fill in this extra information with any degree of accuracy.
In fact, possible climate change scenarios vary so widely that impacts researchers sometimes need to forget about trying to choose among them. The approach Müller considers “most practical” for adaptation studies is to simply make assumptions that fall somewhere within the range of model projections – for example, a 2-degree temperature rise and 20% less rain – when estimating consequences such as shifting crop yields.
And if you’re not sure what kind of change you’ll be facing, says Müller, the best adaptation options are the “classical approaches” of development aid, such as trying to diversify income sources and reducing dependence on a single factor like crop yields. “What climate change adds is extra uncertainty, and an extra challenge for politics to respond to,” he says.
Image: Robert A.
Rhode Rohde, based on Peterson and Vose, Bulletin of the American Meteorological Society 78, 2837-2849 (1997).