1. 19/09/20151 Climate Change Data Analysis, Risks Assessments On agric/Water Resources and Adaptation Strategies In Some AAP-Countries Seyni Salack (UNOPS-IRTSC, Consultant) Contributors: Intsiful J., Obuabie E., Moufouma W. Email: seyni.salack@ucad.edu.snseyni.salack@ucad.edu.sn AAP Countries Meeting, Dakar, Senegal, 12-16 November 2012

2. Overall objective of our team Help AAP countries build upon their local knowledge and capabilities. 19/09/20152 “Strengthen the strengths and make weaknesses irrelevant in CC info use and applications”

3. Focus on few to help many ! 19/09/20153 How ?

4. 19/09/20154 The challenges (1): Understanding the Complex climate system… The atmosphere and the chemical components are linked with other components of the Earth system: oceans; land; terrestrial; plants and animals

5. 19/09/20155 …..GCM outputs… Hundreds of km tens of km km point Impacts needs…

6. 19/09/20156 The challenges (2): End users handling the methods in dynamical and/or statistical downscaling technics Source: S. Salack (2007) RMC are used to downscale GCM outputs: Capture the sub-grid processes (orgaphic effects, local convection …) GCM scale RCM Stat Station data Statistical link Zoom 1 Zoom 2 b) Dynamical-statistical methods GCM scale Gamma Distribution, EOF, Transform. mul. Gauss. etc., Mark. Ch. Station data a) Classical Methods: Baron et al, (2005), Hansen et al, (2006), Schmidli et al. (2006), Ines & Hansen (2006) Statistical Dowscalling ???

7. 19/09/20157 The challenges (3): Climate & CC data archiving, formatting (NetCDF), QC technics 1ni nj → lon(ni), lat(nj) and time(nj,ni) for different levels (nk) Note: in Netcdf files, lon and lat are often both dimensions (ni and nj) and name of longitude and latitude vectors → lon(lon), lat(lat), level (nk) and time (lat, lon)

8. Methods and tools provided (1): open source tools 19/09/20158 New_locClim (FAO, 2006): to solve problem of data scarcity, data interpolation/spatialisation

9. Methods and tools provided (2): open source tools 19/09/20159 NCO: NetCDF Command Operators for managing NetCDF data format CDO: Same as NCO + extraction of climate extremes R packages and scripts: browse_NCDF.r (for handling NetCDF files by Salack et al., 2012), Rclimdex.r (for climate extremes extraction by ETCCM/WMO, 2006) Stochastic weather generator for downscaling: LARS- WG, EOFs and their limitations in CC info.

10. AMMA-ENSEMBLES & CORDEX data: RCM outputs IRI data library: Observations, re-analysis NOAA (GHCN), CRU, GPCP, TRMM Climate information portal of the CSAG-UCT FAO database, including CLIMWAT Other data sources such estimated, interpolated, self-owned data etc. >>> Because Good and true information is power ! 19/09/201510 Methods and tools provided (3): open source data

11. Workshops successfully organized (feedbacks & reports) Public conference in Congo (special) National average CC and extremes scenarios reports National average and local CC risks on agric & water resources and adaptation measures 19/09/201511 The achievements (1): Strengthened & sustained capacity MZ CG NE BF GH Mauritius

12. 19/09/201512 AAP-Mozambique (23 participants)

13. 19/09/201513 AAP-Niger (22 participants)

14. AAP-Congo (2x25 participants) 19/09/201514

15. Results (1): Example of Natl report on CC in Congo 19/09/201515 …and output oriented… useful to any other decision making project

16. Impacts on agric & water resources Major challenges: Managing uncertainties in CC info. Local information to parametrize & validation of crop models (DSSAT, CROPWAT, SARRAH) Information on local water levels and runoff Water basin metadata and evaporation data Etc… 19/09/201516

17. Implementations in AAP countries Deploy crop models: DSSAT, CROPWAT, SARRAH Deploy hydrological models: SWAT, WEAP Deploy GIS tools: ARCGIS, IDV The parameterizations and validations are done using mostly the FAO parameters and data in most cases but also local data. 19/09/201517 Impacts on agric & water resources

18. Results 2: Example of Natl report on agric in Congo 19/09/201518 …and output oriented… useful to any other decision making project

19. Adaptation Measures in agric sector The “Where” to adapt Adaptation is local. Case to case approach. The “how” to adapt Technical Adaptation measures have been suggested. Easy to use, to implement and sustained Low cost (financially and in manpower) Do not oppose indigenous knowledge and practices 19/09/201519

20. Results 3: Example of Natl report on agric in Congo 19/09/201520 …and output oriented… useful to any other decision making project

21. Lessons learnt (Recommendations) Open source data sets are very useful (support it) Open source tools provide precise and good quality results (Build on the acquired skills). AAP experiences can increase knowledge of climate science and can provide breakthrough ideas for follow up projects (per-review papers) Strong relationship between AAP and the national Met. Off. or Agency helps reduce the problem of local data availability (build on it). Strong links between AAP and the local Universities is a long term solution to research- end-users relationship (sustain this process). 19/09/201521

22. Thank you 19/09/201522