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Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
CLIMAFRICA
Climate change predictions
in Sub-Saharan Africa:
impacts and
adaptations
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
CLIMAFRICA
Climate change predictions in Sub-Saharan Africa: impacts
and adaptations
European Commission – FP7
3.5 M€
48 months: 1 Oct 2010 – 30 Sep 2014
Key Words
Climate Predictions; Climate Impacts;
Vulnerabilities; Adaptation; Case Studies;
Agriculture and Water Resources;
Socio-economic analysis
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
ClimAfrica Rationale
Urgent international need for the most appropriate and up-to-date tools to better
understand and predict climate change in Africa, assess its impact on African
ecosystems and population, and develop the correct adaptation strategies.
ClimAfrica Objectives
1- Develop improved climate predictions on seasonal to decadal climatic scales,
especially relevant to SSA;
2- Assess climate impacts in key sectors of SSA livelihood and economy, especially
water resources and agriculture;
3- Evaluate the vulnerability of ecosystems and civil population to inter-annual
variations and longer trends (10 years) in climate;
4- Suggest and analyse new suited adaptation strategies;
5- Develop a new concept of medium term monitoring and forecasting warning
system (for food security, risk management, civil protection)
6- Analyse the economic impacts of climate change on agriculture and water
resources in SSA and the cost-effectiveness of potential adaptation measures.
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
1
2
Acronym
CMCC
ULUND
Participant organisation name
CENTRO EURO-MEDITERRANEO per i CAMBIAMENTI CLIMATICI
LUNDS UNIVERSITET
Country
Italy
Sweden
3
CEA
COMMISSARIAT A L’ENERGIE ATOMIQUE
France
4
5
MPG
VUA
6
CTFC
MAX PLANCK GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN
Germany
VERENIGING VOOR CHRISTELIJK HOGER ONDERWIJS WETENSCHAPPELIJK Netherlands
ONDERZOEK EN PATIENTEZORG
CENTRE TECNOLOGIC FORESTAL DE CATALUNYA
Spain
7
PIC
POTSDAM INSTITUTE FOR CLIMATE IMPACT RESEARCH
8
CIRAD
CENTRE DE COOPERATION INTERNATIONAL EN RECHERCHE AGRONOMIQUE France
POUR LE DEVELOPPEMENT
9
FAO – GTOS FOOD and AGRICULTURE ORGANISATION of the UNITED NATIONS
10
SOW – VU
11
UR2PI
12
UCT
STICHTING ONDERZOEK WERELDVOEDSELVOORZIENING VAN DE VRIJE Netherlands
UNIVERSITEIT
UNITE DE RECHERCHE SUR LA PRODUCTIVITE DES PLANTATIONS Congo
INDUSTRIELLES
UNIVERSITY OF CAPE TOWN
South Africa
13
BCA
UNIVERSITY OF MALAWI
Malawi
14
LBEV
UNIVERSITY OF LOMÉ
Togo
15
ARC
AGRICULTURAL RESEARCH CORPORATION
Sudan
16
ICPAC
IGAD CENTRE FOR CLIMATE PREDICTION APPLICATION
Kenya
17
CSIR-CRI
18
CERPINEDD
COUNCIL FOR SCIENTIFIC INDUSTRIAL RESEARCH – CROPS RESEARCH Ghana
INSTITUTE
CENTRE D’ETUDE DE RECHERCHE ET DE PRODUCTION EN INFORMATION Burkina Faso
POUR L’ENVIRONNEMENT ET LE DEVELOPPEMENT DURABLE
Germany
Partnership
18 institutions: 9
Europe
8 Africa
+ FAO
Project
coordinator: CMCC
– Italy
www.cmcc-org
Local
case studies:
1)Burkina Faso
2)Ghana
3)Togo
4)Sudan
5)Ethiopia
6)Congo
7)Tanzania
8)Kenya
9)Malawi
10) South Africa
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WORK PACKAGES
on
Partner
ecosystem MPG
WP1
Effects of past climate
productivity and water cycle
WP2
Feedbacks between climate variability / changes and the CMCC
land surface. Improving modelling seasonal to decadal
climate predictions
Analysis of climate impacts on key ecosystem services LU
(water, agriculture)
WP3
variability
Lead
WP4
Medium-term of Forecasting food and water vulnerabilities FAO
and recommending relevant adaptation measures
WP5
Socio-economic implications of climate change impacts CMCC
and adaptation measures in SSA
WP6
Regional case studies in SSA
CTFC
WP7
Project Management
CMCC
WP8
Dissemination and exploitation of project results
CMCC
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP1
past climate
variability
WP6
case studies
WP3
climate
impacts
WP5
Socioeconomic
implications
WP4
Medium-term
warning
system
vulnerability,
adaptation
WP8 dissemination
WP7 project management
WP2
climate
predictability
and forecasts
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP1 - Africa is a hotspot of interannual variability of the global land carbon cycle
Jung et al.
In press
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP1 – Past Climate Variability
Collection and synthesis of various
data streams that diagnose the
variability of the climate, in
particular the water cycle, and the
productivity of ecosystems in the
past decades.
The data streams range from ground
based observations and satellite
remote sensing to model
simulations.
WP1 aims at providing consolidated
data to other WPs in ClimAfrica, and
at analyzing the interactions
between climate variability, water
availability, and ecosystem
productivity of Sub-Saharan Africa.
Jung et al. 2010
Recent trends in the water cycle of Africa
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP1 – data already available internally to the project
(from Martin Jung and Uli Weber, MPI)
•
•
•
•
•
daily meteorology from 1901-2010
soil texture
historical land cover/use from 1901 till 2007
albedo for 2000-2010 based on MODIS
latent and sensible heat fluxes derived from upscaling eddy covariance
data (1982-2008, monthly)
• monthly FAPAR from 1982-2010 based on AVHRR, SeaWiFS, MERIS
Expected data (soon):
• Land use data (by PIK)
• digital elevation model
• meteo data update until 2030 based on Echam5 A2
• soil moisture data set (by VUA)
• MODIS land surface temperatures and LAI
(all data are 0.5° and gap-filled if based on remote sensing)
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP2 - CMCC seasonal forecast and decadal prediction system
• Seasonal retrospective forecast for 22 years (1989-2010). Four six-monthforecasts per year, start dates 1st Feb, 1st May, 1st Aug, 1st Nov.
• Decadal predictions. Twenty-year-simulations, start dates 1990-1995-20002005-2010, November 1st.
• Simulations are performed by means of a global climate model initialized
with the best observational products of ocean, land and atmosphere.
Outputs provided:
• surface temperature
• Precipitation
• heat fluxes
• winds
• etc.
East Africa
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP2
Will the weather
be favourable
this summer?
Warm
Hot and Dry
Cool and Wet
Hot and Wet
Cold
and
Wet
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP2
CMCC Seasonal Prediction System
Coupled Model component
Off line Initialization Tools
Radiative forcings
GHGs & SO4
Atmospheric IC from ERAInterim Reanalysis
Land Surface
SILVA
(Alessandri 2006, 2007)
Atmosphere
ECHAM5 (T63 ≈ 1.87°x1.87°)
(Roeckner et al 1996, 2003)
Spectral & Time interpolation
INTERA
(Kirchner, 2001)
Coupler
OASIS3
(Valcke et al, 2000)
Ocean initial condition production
Sea Ice
LIM (ORCA2)
Ocean
OPA 8.2 (ORCA2)
(Timmerman et al, 2005)
(Madec et al, 1998)
T & S - OI assimilation
SOFA 3.0
(De Mey and Benkiran 2002)
Bellucci, Masina, Di Pietro &
Navarra, 2007. MWR
Coupling Daily
No flux adjustment
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP2
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP2 - Observations and global model skill for Eastern Africa
Rainfall is most important climate element to model and prediction in Sub-Saharan
Africa (SSA) food security and water resources.
Studies on rainfall patterns are already ongoing in many areas of Africa.
Seasonal rainfall as percentage of annual total amounts for some seasons within Eastern Africa
(from ICPAC, Kenya).
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP2 - Observations and global model skill for Eastern Africa
Examples from several Global models:
“Skill” basis for use of Global model in multi-model downscaling is quite high for
East Africa sub-domain of ClimAfrica analysis and applications.
Regional model: Regional model skill is reasonably good also
PRECIS model will be a reliable source of detailed future projections within time
window 2010-2090s.
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP3 - Climate impacts on key ecosystem services
Quantifying sensitivity of vegetation productivity and water resources to
seasonal, interannual and decadal variability in weather and climate
Current
models in
combination
recently
Land Use
Change
CO2 emissions
Climate
Change with
developed datasets of land use and climate (from
WP2) will be used to simulate crop yield and
water resources.
Simulations using short-term scenarios of future
climate change (5-10 years) will be used to
identify regional differences in the climate
sensitivity of crop production etc.
Crop Model
Scenarios for the African agricultural/pastoral
sectors will also be made using longer model
Water use
Crop yield
runs.
Identify tradeoffs and areas of
risk and vulnerability related to:
a) water related hazards
b) agricultural and pastoral
performance
c) soil degradation
…using an agroDVM
Work in progress:
Model development and
input data processing.
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP3 - Preliminary output
GUESS with crop module:
Hadley A2 scenario
Potential NPP
a. Maize
b. Maniok
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP4 - Medium-term of Forecasting food and water vulnerabilities and
adaptation mesures
Establish a monitoring and forecasting warning system (based on ClimAfrica
data) that produces prospective analyses about food insecurity and water
crisis for at least the next 10 years.
Fill the gap between
seasonal scale
predictions and longterm impact scenarios
Identify the future Areas
of Concerns (AoCs) and
likely hotspots of
vulnerabilities and food
insecurity
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP4 - Natural Resources and Food Security – Systems at Risk (NaF-SAR)
Integrate and harmonize ClimAfrica data with existing data and information to be used as
inputs to develop improved vulnerability assessment and optimal adaptation options. A Risk
framework is being used to provide a strategic context for the data and tools generated. The
framework consists of 4 key stages:
1- Physiographic data related to hazard or environmental pressure;
2- Socio-economic data (people)
3- Risk assessment hot spotting based on (1) & (2) and the development of scenarios
4- Decision support.
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP5 – Socio-economic implications
The social economic research group within CLIMAFRICA aims to provide a
throughout economic assessment of agriculture and water sector, using, among
others, a computable general equilibrium model, ICES, developed at the CMCC.
The main advantage of this
Nested tree Structure
Output
Output
for the supply
demandside
side
investigation approach is to
Utility
Utility
ICES
model
V.A. + Energy
Other Inputs
depict the economy as a
system where goods and
Private
Public
Savings
factor markets interacts
Consumption
Consumption
domestically and
internationally. Price effects,
competitiveness effects,
demand and supply
adjustments triggered by
impacts on the agricultural
sector can thus be properly
captured.
Natural
Resources
Land
Domestic
Capital
+
Energy
Labour
Foreign
Region 1
Capital
Item 1
Item m
Item …
Energy
Non Electric
Item 1
Region n
Region ...
Electric
Item m
Item …
Domestic
Non Coal
Foreign
Coal
Reg n
Reg 1
Domestic
Foreign
Gas1
Region
Region n
Region ...
Domestic
Domestic
Domestic
Region ...
Domestic
Domestic
Reg n
Region
n
Reg ..
Oil
Foreign
Reg 1
Foreign
Foreign
Reg 1
Petroleum
Region 1
Products
Foreign
Foreign
Reg n
Reg 1
Reg ..
Reg n
Reg ..
Reg 1
Reg n
Reg ..
Reg ..
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP5
Number of people exposed to
climate-change induced water stress
(IPCC AR4, 2007)
Climate Change impacts on crops’ yields.
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP5
Climate change impacts by category and region (Bosello et al. 2009)
Climate Change Impacts: Summary
4.0
3.0
USA
Med_Europe
2.0
North_Europe
% of GDP
1.0
East_Europe
FSU
0.0
KOSAU
CAJANZ
-1.0
NAF
-2.0
MDE
SSA
-3.0
SASIA
-4.0
CHINA
EASIA
-5.0
1.2 °C 3.1 °C
1.2 °C 3.1 °C
1.2 °C 3.1 °C
1.2 °C 3.1 °C
1.2 °C 3.1 °C
1.2 °C 3.1 °C
LACA
Agriculture
Energy
Demand
Health
Sea Level
Rise
Tourism
All Impacts
World
Tem perature increase
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
WP6 – Case Studies
Characterize the environmental and socioeconomic conditions of 9 different SubSaharan African regions distributed along a
wide climate gradient (Ghana, Burkina Faso,
Togo, Malawi, Republic of Congo, Sudan,
Kenya, Ethiopia and Tanzania).
The studies carried out in these regions will
provide field data to other work packages for
empirical model development and mechanistic
model parametrization.
In addition, the synergies developed with the existing actors (managers and policymakers, NGO’s, local farmer’s organizations, women’s associations, etc.) during these
studies will allow to test and validate both the individual model outputs and the
Medium Term Warning System in these regions.
Tchizalamou site, Congo
Climate change predictions in Sub-Saharan
Africa: impacts and adaptation
Case Studies
The countries to be considered for the choice of the case studies have been
identified by an analysis of the Sub-Saharan region based on the following five
data sets, as indicators of environmental, climatic, agricultural and socioeconomic conditions:
•Global Ecological Zones (2001) - as indicator of ecologic conditions
•Major farming systems of SSA(2001) (as indicator of farming systems)
•GLC-2000 Based 1 km Global Land Cover - Africa (2004) - as indicator of land
cover
•Prevalence of stunting among children under five (2007) - as indicator of
malnutrition, under nutrition, and poverty
•Total renewable water per capita (actual) (1960-2007) - as indicator of water
scarcity
The analysis has produced the following list of eligible countries:
1) Burkina Faso, 2) Ghana, 3) Togo, 4) Sudan, 5) Ethiopia, 6) Congo,
7) Tanzania, 8) Kenya, 9) Malawi, 10) South Africa