Abstract
AbstractUnderstanding the causes of regional climate projection uncertainty is a critical component toward establishing reliability of these projections. Here, four complementary experimental and decomposition techniques are synthesized to begin to understand which mechanisms differ most between models. These tools include a variety of multimodel ensembles, a decomposition of rainfall into tropics-wide or region-specific processes, and a separation of within-domain versus remote contributions to regional model projection uncertainty. Three East African regions are identified and characterized by spatially coherent intermodel projection behavior, which interestingly differs from previously identified regions of coherent interannual behavior. For the “Short Rains” regions, uncertainty in projected seasonal mean rainfall change is primarily due to uncertainties in the regional response to both the uniform and pattern components of SST warming (but not uncertainties in the global mean warming itself) and a small direct CO2 impact. These primarily derive from uncertain regional dynamics over both African and remote regions, rather than globally coherent (thermo)dynamics. For the “Long Rains” region, results are similar, except that uncertain atmospheric responses to a fixed SST pattern change are a little less important, and some key regional uncertainties are primarily located beyond Africa. The latter reflects the behavior of two outlying models that experience exceptional warming in the southern subtropical oceans, from which large lower-tropospheric moisture anomalies are advected by the mean flow to contribute to exceptional increases in the Long Rains totals. Further research could lead to a useful assessment of the reliability of these exceptional projections.
Highlights
Extremes of tropical rainfall, whether they are droughts or floods, can be catastrophic in developing countries
Our focus has been on East Africa’s two wet seasons, but the synthesis of techniques employed here may prove useful for understanding projection uncertainty for other tropical terrestrial regions
It has been common practice to date to discount or downweight models that perform poorly against standard metrics, but Rowell et al (2016) have shown that for East Africa, this is ineffectual for reducing projection spread
Summary
Whether they are droughts or floods, can be catastrophic in developing countries. Five criteria are used to define these averaging regions: 1) preference for large spatial extent; 2) inclusion of Lake Victoria, where the high population density is predicted to continue rising rapidly (Seto et al 2012) and because our study contributes to a project aiming to assist stakeholders in the Lake Victoria basin make climate-resilient development decisions (Marsham et al 2015; https://hycristal.wordpress.com/); 3) all points within the region must have at least 50% common crossensemble variance with at least 50% of the other points; 4) all grid points experience their wettest month during one of the transition seasons using Nicholson’s (2014) analysis, which is used to exclude large areas of North Africa during the Short Rains; and 5) the region is contiguous, such that all grid boxes are adjacent to another on at least two edges. These fairly low values imply large interregional and interseasonal differences in the dominant processes that drive projection uncertainty, more so than the interregional commonality, requiring that these regions and seasons should be examined separately
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