VACS Deliverables since SSG 14

1. VACS Deliverables since SSG 14 • Climate Prediction workshop, Dar es Salaam, July 06 – trained 30 operational scientists from NMS’s and ocean agencies from 20 African countries in the Climate Predictability Tool (CPT) software • Workshop funded by Royal Society / S A govt (NRF) on southern African programme – last week – GIRAFFE • Ongoing development of WCRP-CLIVAR African Climate Atlas • VACS East African programme • AMMA (former Co-Chair of VACS also Co-Chair of AMMA) – special issue of CLIVAR Exchanges • Africa breakout session organised at the WCRP Seasonal Prediction workshop, Barcelona, June 07 • Young African Scientists’ Day at JSC Zanzibar organised by VACS – outcomes include special issue of Int. J. Climatol. (10-12 papers) and entrainment of these young scientists in GIRAFFE and East African programmes • 2006 BAMS article – African climate change impacts need to be dealt with on S2D timescales • Africa sessions at conferences organised by VACS members – eg AMS Jan 08 New Orleans (Kerry Cook) • Hosted IOP4 at SA Weather Service to develop interactions with IOP

2. VACS Southern and Eastern African Climate Predictability Workshop Tanzania Meteorological Agency, Dar es Salaam 10-13th July 2006 Seasonal Climate Prediction Network for Africa • Attendees from NMS’s of each southern African country and 5 East African countries as well as from 6 operational ocean agencies • Climate Predictability Tool -IRI The Climate Predictability Tool (CPT) provides a Windows package for constructing a seasonal climate forecast model, performing model validation, and producing forecasts given updated data. Its design has been tailored for producing seasonal climate forecasts using model output statistic (MOS) corrections to climate predictions from general circulation model (GCM), or for producing forecasts using fields of sea-surface temperatures. Although the software is specifically tailored for these applications, it can be used in more general settings to perform canonical correlation analysis (CCA) or principal components regression (PCR) on any data, and for any application.

3. GIRAFFE reGionally IntegRated southern AFrican climate and Forecasting for sociEty Workshop sponsors – UK Royal Society / SA govt National Research Foundation

4. GIRAFFE reGionally IntegRated southern AFrican climate and Forecasting for sociEty

5. GIRAFFE DESIGN QUESTIONS • Research Themes • Basic state • Variability • Modelling • S2D Prediction • Climate Change • Observing System • Training • User Interface

6. BASIC STATE • Justifications: • Forcing of global circulation which originates from southern Africa is unknown (e.g. MJO, convectively forced waves) • Southern Africa is expected to be subjected to major desertification as a result of ACC but model simulation of the basic state and teleconnections are problematic

7. BASIC STATE • Justifications: • Examination of forcing of global circulation from African convection (e.g. MJO) • Detailed assessment of performance of climate models, individual and ensembles, for seasonal and climate change uses • Examination of forcing modes in atmosphere vs. models – modes produce higher-order statistics required by users • Enhanced information on potential climate predictability in the region through the year • Improved post-processing of model information for users • Major SADC input to work

8. BASIC STATE • Questions: • Dynamics of rain-bearing and other systems • Mechanisms of cloud band generation • Mechanisms of other convective systems • Dynamics of the flow at 5-20°S over Africa (Angola Low, easterly waves, ITCZ dynamics and uniqueness of meridional arm, why a standing wave with no propagation into Atlantic {Brazilian hurricane?} +?) • MJO initiation (NB: effects on global circulation) • Wave generation by African convection; effects on global circulation • Intraseasonal dynamics (semi-annual cycle) • Causes of winter dryness • Controls on surface temperatures • Affect of aerosols on dynamics • Forcing mechanisms; links to global circulation • Mechanisms by which ENSO affects African rainfall • Role and mechanisms of surrounding ocean basins on African rainfall • Mid to high latitude mechanisms on African rainfall variability (SAM, wave 3-4, sea ice) • Land surface mechanisms • Predictability • Of the SW Indian Ocean upper heat content and SSTs • Effect on land surface feedback; relevant space and time scales

9. VARIABILITY • Modulation of ENSO modes, and their interactions with southern African climate (rainfall and temperature), on decadal and multi-decadal timescales • Stability of teleconnections (ENSO plus others) • Combination effects of teleconnections on southern African climate • What is the influence of the PSA on southern African climate

10. MODELLING • Quality of simulations of the basic state (rainfall and temperature) (q.v.) • Quality of simulations of the modes of variability (q.v.) • What are the limits to our ability to model regional climate systems? • Mechanistic examination of regional climate dynamics • What are the benefits of high resolution over low resolution modelling in simulating regional climate? • What is the sensitivity of the simulation of regional climate to various parameterisation schemes? • Does high resolution modelling of the neighbouring oceans assist in simulating regional climate? • What is the sensitivity in models of regional rainfall systems to variations in aerosol concentrations?

11. PREDICTION • What are the implications and limitations introduced for prediction of the ability of the current models to simulate the basic state (rainfall and temperature) and variability, as determined in earlier sections • Do coupled models add value/quality/operational performance over and above other modelling approaches • What is the predictability of predictability – forecasting uncertainty? • What is needed in order to make land surface assimilations over southern Africa? • What is the predictability of variations in intra-seasonal rainfall? • What is the optimal ensemble prediction system for the region (resolution, number of models, number of members, weighting, post-processing, etc.)? • What is the optimal approach for generating forecast variables for inclusion in application models?

12. CLIMATE CHANGE • What are the implications and limitations introduced for climate change prediction of the ability of the current models to simulate the basic state (rainfall and temperature) and variability, as determined in earlier sections • How will the basic state (rainfall and temperature) (q.v.) and variability (q.v.) of southern African climate change in future climates? • How well are high impact events simulated in climate models, how will these change, and how well are these likely to be simulated for future climates? • What will be the future dynamic structures of southern African rain bearing systems? • How will teleconnections to southern Africa, including ENSO, change under future climates? • What are the potential impacts of future predicted climates on society, what uncertainties are involved, and what are the limitations to this knowledge? • How do the uncertainties of climate change predictions affect planning?

13. OBSERVING SYSTEMS • Climate systems: • Target Angola Benguela Frontal Zone/south-east Atlantic and Indian Ocean thermocline ridge – AIP/IOP • Land surface: lack of data • How do we link this to?: • ClimDev • INDOOS • PIRATA • GCOS • TIGER, etc. • Observations for applications: • How do we access existing data? • How do we encourage creation of quality data sets? • How do we encourage use of accompanying data and metadata? • How do we promote QA? • How do we link to training activities? • Database management (climate and applications-relevant): • How to connect to ClimDev (see Roger Stern contribution)? • How might it be developed across SADC? • How best to handle in SAGRADEX? • How to ensure access to all relevant data bases for SAGRADEX participants?

14. IMPROVED SOCIETAL USES FOR CLIMATE INFORMATION • What is the current usage of climate information and prediction in decision making? • List of sectors/institutes/levels • List of information currently used • What empirical underpinning is required to further develop application models? • What are the societal consequences of rainfall variability in the region • What defines a high impact event? • What climate information is required for societal use? • Role of near-real time observation products • Level of model skill required • Timing of delivery of information • How might society be conditioned to expecting longer-range predictions only at times of relatively high predictability? • How should uncertainty be conveyed to society? • What is required to action the use of climate information and forecasting (including ensemble prediction) systems for society? • Data availability • Linking information to decision processes; understanding decision processes • Post processing (downscaling; bias correction) • Verification of probabilistic output • Is there a need for selected pilot studies? • What are the main issues preventing data use • Others as above • How are these issues to be addressed

15. TRAINING • How to incorporate pilot studies and RCOFs for training? • How to produce training materials, including workshops, web sites, wikis, blogs? • Centrally controlled? • Overall management? • Brand image? • How do we train climate scientists? • How to attract from other disciplines (ACCESS)? • How to include relevant climate science in other curricula? • What is the best strategy to include governmental, NGO and social sector officers in forecasting systems? • What level of involvement works best, and at what stage of the process? • How do advise the general public of climate risk and the use of climate information (ACCESS)? • How to involve the media?

16. NEXT STEPS/SCHEDULE • Meeting Report (2 pages) – Richard/Chris – end 09/07 – send to RS, NRF • Andy to set up a blog or wiki – end 09/07 • Core Group to review consistency of design (spreadsheet – Andy to set up on Google) – end first week 10/07 • Group at SAGRADEX meeting to review – coordination by Chris – mid 11/07 • Preparations for Flier and White Paper – end 11/07: • Programme logo – Andy • Budget estimate – Chris/Richard/Andy • Organisational diagram – Andy • Create extended list of potential collaborators – Chris/Willem for Africa; Richard/Andy/Mike for elsewhere • Time line (for programme spin-up) – Core Group • Interrelationship in time for project components – Mike • Brief status review – Willem/Chris • A4/A5 Flier and stock powerpoint slides – Andy end 11/07 • Web site initialisation – Willem/Chris – mid 11/07 • White Paper (10-12 pages with executive summary) - Richard/Chris lead – end 11/07 • gain endorsement (CLIVAR, ESSP) – Richard/Chris • approach potential collaborators (see list) – Core Group • approach funders (RS, NRF, DST, NERC, funders slide, plus others – check UK/David King) – Core Group • identify champions primarily, but not necessarily uniquely, for societal link – Core Group • confirm identify of gate keepers – in-region responsibilities • examine data and data base issues – Juliet/Chris (see under Observing Systems) • Consider interactions with ClimDev, INCLUDE, ENSEMBLES, AMMA etc. – Mike/Andy – end 11/08 • Draft programme document – Richard/Chris lead – 02/08 • Use proposal opportunities that arise

17. GIRAFFE – reGionally IntegRated southern AFrican climate and Forecasting for sociEty – a 5-year programme with vision!

18. WCRP-CLIVAR African Climate Atlas • Part I - Climatology • Part II - Anomalies • Part III - TOMS Absorbing Aerosol Index (interactive visualization) • Part IV ERA-40 interactive plotting tool • Part V African Climate FAQs • Part VI IPCC AR4 data portal Part VI Thanks to WCRP: secured funds from GEO IPCC AR4 coupled simulation data and plotting tool Interactive Data and maps for download

19. Young African Scientists’ Day – JSC Zanzibar March 2007 Kenya, Tanzania, Uganda, Rwanda, Senegal, Botswana, Mozambique, South Africa, Zambia – Int. J. Climatol. Special Issue – submissions now Young African Scientists’ Day – JSC Zanzibar March 2007 Sunset at Stone Town beach, Zanzibar, March 30, 2007

20. VACS Lake Victoria project 1961-62 IO Warming 97-98 El Nino “no trend” pre-1961 lake levels Observed lake level drop due to hydroelectric dam water over release at source of the Nile? AND/OR Is lake level drop dueto 2005-6 record drought/temperatures of eastern Africa? Goal: Verification & Prediction Satellite NCEP reanalysis Nile Outflow & Lake Level RegCM3 RCM RegCM3 RCM VACS Modeling Research (surface temperature and winds)

21. Prediction of Lake Victoria Levels Lake Victoria levels validation based on preliminary results using our version of the modified Tate et al (2004) modified water balance model (diamond - blue), and observed lake levels (square - pink). Input is six rain-gauge station data around lake. Next step is to use input from the RegCM3 regional climate model.

22. Greater Horn of Africa Regional Model Inter-comparison Project(ARMIP) Objectives • Inter-compare regional climate simulations of the GHA climate based on different state-of-the-art RCMs to explore and evaluate uncertainties in the present skill of these models over the region. Participating Models (so far: NCEP-RSM; PRECIS, RAMS, RegCM3, WRF/MM5) • Develop criteria for modifying and improving the parameterizations of various physical processes (e.g., convection, boundary layer, radiation) as appropriate for improving the performance of regional climate models over the GHA sub-region • Develop a regional seasonal climate dynamical prediction system • Develop high-resolution regional climate change scenarios to assess the impacts of climate change on regional hydro-climates, including fluctuations of Lake Victoria surface elevation and the hydrology of the entire Nile River Basin NOTE: The ARMIP Project is an initiative of Richard Anyah, currently funded (limited) by NSF:2007-2009. It would be great if CLIVAR-VACS panel members who are currently running Regional Models would come forward to participate by donating their models, time and computing facilities.

23. Predictability of East African short rains based on regional model simulations NEK NUG NUG NEK CEK CTZ CTZ CEK Figure 3: Regional Model (RegCM3) simulated interannual rainfall variability in different homogeneous climate zones over East Africa (Anyah and Semazzi, 2007)

24. AMMA - WG1Scientific objectives (1) • Integrative view of the variability/impact/predictability of the WAM • Consider processes operating at global and regional scales • Variability and Predictability of the WAM • Key-SST anomaly patterns linked to WAM variability and associated teleconnection mechanisms; Impact of other monsoon regions and the rest of African continent; To what extent this is predictable ? • What mechanisms determine the observed intraseasonal variability over West Africa ? Roles of intra-continental continental teleconnections and equatorial waves; • Mechanisms that control the annual cycle of the WAM including monsoon onset • To what extent the key modes of variability of the WAM are predictable ? To highlight the predictable aspects of the WAM

25. SST-WAM coupled modes at interannual scale (obs) Joly et al. 2006

26. SST-WAM coupled modes at interannual scale (IPCC4) Coupled models do not simulate accurately the teleconnections at interannual scale Joly et al. 2006

27. AMMA - WG1Scientific objectives (2) • Integrative view of the variability/impact/predictability of the WAM • Consider processes operating at global and regional scales • Impacts of the WAM on the global scale • Variability and Predictability of Atlantic tropical cyclone activity : role of WAM heating and teleconnections that impact the environment where the cyclones develop; Variability of the weather systems that trigger many of the tropical cyclones • Aerosol variability : Improve our knowledge of the aerosol physical, chemical and radiative properties (Sahara dust, biomass burning, sulfates); sign of (in-)direct radiative effect; modification of aerosol properties during long-range transport; effect on cloud properties • Atmospheric chemistry : trace constituents uplifted by convection in the free atmosphere, then transported over large distances ; What is the extent of this long-range transport and their impact on the global oxydizing capacity and global radiative forcing ?

28. Monitoring of African easterly waves • Hovmoller space-time diagram of 700 hPa curvature vorticity averaged between 5°N and 15°N based on GFS analysis. The numbers refer to synoptic systems that meet the tracking criteria used by Berry et al. (2007). Those in red became tropical cyclones in the Atlantic basin. These were Chris (6), Ernesto (13), Debby (14), Florence (18), Gordon (19), Helene (21), Isaac (23).On the vertical axis time is expressed as month-day/hour. Berry et al. 2007

29. Issues for SSG • Africa tends to be just viewed as a monsoon system rather than a vast continent with distinct regional climate processes and impacts that include monsoons • Despite very limited resources, VACS has made significant progress • For Africa, adaptation to climate change and variability is vital: info gap on decadal timescales • Progress largely depends on the enthusiasm of a small group of individuals, crucial help from WCRP and external funding • The challenge is to extend this enthusiastic small group to a much larger network throughout Africa and worldwide

30. SUMMARY • Despite very limited resources, VACS has made significant progress • For Africa, adaptation to climate change and variability is vital • Progress largely depends on the enthusiasm of a small group of individuals, crucial help from WCRP and external funding • The challenge is to extend this enthusiastic small group to a much larger network throughout Africa and worldwide