1. AF07: Climate Change Scenarios

2. Distributed team Host Institution: University of Cape Town Bruce HewitsonSouth Africa Mark Tadross (project coordinator)South Africa Ernest Afiesiemama Nigeria Suman Jain Zambia Joseph Intsiful Ghana Abdoulaye Sarr Senegal Brad Garangara Zimbabwe Hannes RautenbachSouth Africa Ruwani WalawegeSouth Africa Chris JackSouth Africa William GutowskiIowa State University Robert Crane, Penn State University Richard JonesHadley Center, UK Project Objectives Climate change scenario information at spatial and temporal scales appropriate to the vulnerabilities of Africa. Emphasis on development of multi-institutional capacity within Africa in the use and application of regional climate models (RCMs), empirical downscaling, and analysis of the climate system processes.

3. GCM Skill: Average precipitation anomaly (mm/day) for DJF 6 GCMs, A2 scenario, 2070-2099 – 1970-1999

4. GCM Skill: Grid cells where 4 out of 6 models agree on the sign of the change

5. User requirement RCM or empirical downscaling translates (in principle) from GCM to user requirements

6. Southern Africa RCM domain “Pan equatorial” RCM domain

7. GCM Simulations Assess skill & uncertainty GCM-based regional scenarios Observational Data Quality Control Formatting Dissemination User Needs AIACC projects Other? Common GCM / Observational data sets for participants usage Availibility via internet and CD- ROM Regional Climate Model Simulations Control simulations with reanalysis Skill & uncertainty GCM boundary forcing Long-term for sub-continental Short-term high resolution foci Empirical downscaling Downscaling from reanalysis data Skill & uncertainty Downscaling of GCM simulation data Initial downscaling of ppt and T Integration and Analysis ( ) Project activities = significant progress

8. a)Input to Norwich regional scenario workshop: recommendation that Africa AIACC-projects emphasize sensitivity studies b)DDC GCM monthly data collated, subset, with support graphics and software – initial CD for distribution c)Historical station data partly collated – initial CD distributed d)GCM data appropriate for downscaling acquired (high temporal resolution), and initial assessment of model performance completed (see later talk) e)New empirical downscaling methodology developed f)RCM tests with MM5 (perturbation and sensitivity to land surface) g)RCM (MM5) climatology for southern Africa domain complete h)PRECIS training workshop completed – climatology still to be assessed Project progress and status

9. Perturbation simulations: Experiment: 20% change in land surface albedo (within natural variability), can generate a temperature anomaly of 1°C

10. Perturbation simulations: Experiment: Desiccation of soil moisture – temperature increases up to 4°C

11. Continued validation of GCMs and assessment of skill. Evaluation of GCMs in terms of characteristics for RCM forcing Empirical downscaling of GCM data. Climatology simulation with MM5 RCM pan-equatorial domain Initial climate change simulations with MM5 Climatology simulation with PRECIS Data product time Frames: 2002/3: Dissemination of GCM + observational data 2003: GCM skill assessment and uncertainty envelope 2003/4: Empirical downscaling products 2004: RCM-based products Next steps:

12. Continuous Assessment: Questions of Integration and Analysis Inter-GCM comparison – spread as function of GCM and SRES scenario Downscaling comparison – Inter-RCM comparison / RCM vs Empirical downscaling Downscaling skill – Stationarity, representation of control climate, convergence? Confidence levels and uncertainty of regional scenarios Tailoring of results to user needs Journal papers / workshops and training / inter-institutional visits / internships