19/09/20151 climate change data analysis, risks assessments on agric/water resources and adaptation...
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Climate Change Data Analysis,
Risks Assessments On agric/Water
Resources and Adaptation Strategies
In Some AAP-CountriesSeyni Salack
(UNOPS-IRTSC, Consultant)
Contributors: Intsiful J., Obuabie E., Moufouma W.
Email: [email protected]
AAP Countries Meeting, Dakar, Senegal, 12-16 November 2012
Overall objective of our team
Help AAP countries build upon their local knowledge and capabilities.
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“Strengthen the strengths and make weaknesses irrelevant in CC info
use and applications”
Focus on few to help many !19/04/23 3
How ?
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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
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…..GCM outputs…
Hundreds of km
tens of km
km
point
Impacts needs…
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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
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 dataa) Classical Methods: Baron et al, (2005), Hansen et al, (2006),
Schmidli et al. (2006) , Ines & Hansen (2006)
Statistical
Dowscalling
???
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The challenges (3): Climate & CC data archiving, formatting (NetCDF), QC
technics
1 ni
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)
Methods and tools provided (1): open source tools
19/04/23 8New_locClim (FAO, 2006): to solve problem of data scarcity, data interpolation/spatialisation
Methods and tools provided (2): open source tools
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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.
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 !
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Methods and tools provided (3): open source data
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
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The achievements (1): Strengthened & sustained capacity
MZ CG NE BF GH Mauritius
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AAP-Mozambique (23 participants)
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AAP-Niger (22 participants)
AAP-Congo (2x25 participants)
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Results (1): Example of Natl report on CC in Congo
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…and output oriented… useful to any other decision making project
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…
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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.
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Impacts on agric & water resources
Results 2: Example of Natl report on agric in Congo
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…and output oriented… useful to any other decision making project
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
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Results 3: Example of Natl report on agric in Congo
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…and output oriented… useful to any other decision making project
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).
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Thank you
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