The future-climate, current-policy framework: towards an approach linking climate science to sector policy development

That global climate is being altered by human activities is well-established; for specific locations, however, the details of how and when many aspects of the changes will become manifest remains somewhat uncertain. For many policy makers there is a gap between recognising a long-term change and implementing short-term practical responses; therefore many countries are failing to implement changes needed for long-term adaptation. Traditional planning approaches are often closely aligned with near- term political cycles and perform poorly in terms of prioritising interventions that address multi-decadal climate impacts. We propose a novel approach that builds on adaptive planning and lessons from the business sector. The Future-Climate, Current-Policy (FCCP) Framework is based on plausible medium-term future climate scenarios, linked 'backwards' to identify short-term 'no regrets' actions. The approach was designed by a team of climate scientists and policy practitioners in East Africa and tested in national and regional fora. Initial trials of the FCCP Framework has proved it to be popular and effective as a way of linking climate science with policy. Its use shows promise as a way of initiating discussions that can enable long-term climate change information to feed effectively into the policy and planning process

Evaluation of uncertainties in regional climate change simulations

We have run two regional climate models (RCMs) forced by three sets of initial and boundary conditions to form a 2×3 suite of 10-year climate simulations for the continental United States at approximately 50 km horizontal resolution. The three sets of driving boundary conditions are a reanalysis, an atmosphere-ocean coupled general circulation model (GCM) current climate, and a future scenario of transient climate change. Common precipitation climatology features simulated by both models included realistic orographic precipitation, east-west transcontinental gradients, and reasonable annual cycles over different geographic locations. However, both models missed heavy cool-season precipitation in the lower Mississippi River basin, a seemingly common model defect. Various simulation biases (differences) produced by the RCMs are evaluated based on the 2×3 experiment set in addition to comparisons with the GCM simulation. The RCM performance bias is smallest, whereas the GCM-RCM downscaling bias (difference between GCM and RCM) is largest. The boundary forcing bias (difference between GCM current climate driven run and reanalysis-driven run) and intermodel bias are both largest in summer, possibly due to different subgrid scale processes in individual models. The ratio of climate change to biases, which we use as one measure of confidence in projected climate changes, is substantially larger than 1 in several seasons and regions while the ratios are always less than 1 in summer. The largest ratios among all regions are in California. Spatial correlation coefficients of precipitation were computed between simulation pairs in the 2×3 set. The climate change correlation is highest and the RCM performance correlation is lowest while boundary forcing and intermodel correlations are intermediate. The high spatial correlation for climate change suggests that even though future precipitation is projected to increase, its overall continental-scale spatial pattern is expected to remain relatively constant. The low RCM performance correlation shows a modeling challenge to reproduce observed spatial precipitation patterns

Scientific understanding of East African climate change from the HyCRISTAL project

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic

Scientific understanding of East African climate change from the HyCRISTAL project

Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL) is a Future Climate for Africa (FCFA) project funded to deliver new understanding of East African climate change and its impacts, and to demonstrate use of climate change information in long-term decision-making in the region. Here, we briefly summarise key findings from HyCRISTAL so far on climate change, as well as key findings from the pan-African FCFA project “IMPALA” relevant to East Africa, both in the context of previous literature on the topic

The Development of a Customization Framework for the WRF Model over the Lake Victoria Basin, Eastern Africa on Seasonal Timescales

Lake Victoria, Africa, supports millions of people. To produce reliable climate projections, it is desirable to successfully model the rainfall over the lake accurately. An initial step is taken here with customization of the Weather, Research, and Forecast (WRF) model. Of particular interest is an asymmetrical rainfall pattern across the lake basin, due to a diurnal land-lake breeze. The main aim is to present a customization framework for use over the lake. This framework is developed by conducting several series of model runs to investigate aspects of the customization. The runs are analyzed using Tropical Rainfall Measuring Mission rainfall data and Climatic Research Unit temperature data. The study shows that the choice of parameters and lake surface temperature initialization can significantly alter the results. Also, the optimal physics combinations for the climatology may not necessarily be suitable for all circumstances, such as extreme years. The study concludes that WRF is unable to reproduce the pattern across the lake. The temperature of the lake is too cold and this prevents the diurnal land-lake breeze reversal. Overall, this study highlights the importance of customizing a model to the region of research and presents a framework through which this may be achieved