tools used in climate risk management policies
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Presentation by Philip Thornton, Theme Leader, CCAFS, at the CCAFS Workshop on Institutions and Policies to Scale out Climate Smart Agriculture held between 2-5 December 2013, in Colombo, Sri Lanka.TRANSCRIPT
Tools used in climate risk management policies
Philip Thornton
Institutions and Policies for Scaling Out Climate Smart Agriculture Colombo, 2-3 December 2013
Outline
• Importance of climate variability and the need for managing risk
• Types of risk, what CCAFS is doing
• Some tools that can help in policy formulation concerning risk management
• Summary and what’s needed in the future
How does climate variability affect food insecurity?
• Climate variability can have substantial effects on agricultural growth at the national level; at local level it can crush households
• We can show links from climate variability to food availability and then to food insecurity and poverty
• As climate variability increases in the future (though we don’t know how, exactly), more pressure on food insecurity and poverty, all other things being equal
Climate variability at the national level
12-month Weighted Anomaly of Standardized Precipitation (WASP) and growth in GDP and agricultural GDP (data from data.worldbank.org/indicator and the IRI data library, iridl.ldeo.columbia.edu/)
Climate variability at the household level Herd dynamics in a Kenyan pastoral landscape with increasing drought frequency
Thornton & Herrero (2009)
Some of the types of risk in agriculture
Risk management
in CCAFS
• Actions taken now can reduce vulnerability in the short term and enhance resilience in the long term
• Improving current climate risk management should reduce obstacles to making future structural adaptations
Local-level risk management
• Use of weather forecasts, seasonal forecasts
• Index-based insurance
• Designed diversification
• Integrating traditional risk management knowledge
1 January 2013
National / regional risk management
• Better food security early warning (e.g. crop yield forecasting)
• Informing earlier intervention
• Grain, fodder, seed banks
• Trade policies
• Improving national and regional climate information services (e.g. inputs to insurance indices)
Tools 1: Weather and climate information
Example: reconstructing historical weather data in Ethiopia
STATION BLENDED SATELLITE
weather records to use for crop forecasting, insurance indices, economic planning, …
Greatrex, 2013
http://ccafs-climate.org
Climate Analogues: finding tomorrow's
agriculture today
http://gismap.ciat.cgiar.org/Analogues/
Tools 1: Weather and climate information Example: downscaled future climate information
™
Daily generated data for future climates using Google Earth
http://gismap.ciat.cgiar.org/MarkSimGCM
Systems dynamics and mathematical programming models Household constraints, objectives, resources Impacts on income, food security, resource use, of different adaptation / mitigation options What are the local impacts of policy changes at national level?
Data collection
• Climate
• Family structure
• Land management
• Livestock management
• Labour allocation
• Family’s dietary pattern
• Farm’s sales and expenses
• Mitigation practices
Impact-household
Tools 2: Household modelling under uncertainty
Tools 2: Household modeling under uncertainty Sodo, Ethiopia (ILRI, 2010)
Introduction of cowpea
Current management
Tools 3: In-season crop production forecasting
Yield Forecasts
Tools 4: Scenarios to quantify uncertain futures
The way regional uncertainties play out will dramatically affect agriculture and food security development pathways
• Actors: governments, private sector, civil society, academia and media
• Scenarios being quantified using global agricultural economic models: IFRPI’s IMPACT, IIASA’s GLOBIOM
Using scenarios in South Asia • LEAD Pakistan organises policy
engagement • NAPA review Bangladesh funded
by ADB • YES Bank India, PANOS South Asia • Nepal adaptation policies
0
500
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3500
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2000 2010 2020 2030 2040 2050
SSP1EasternAf
SSP2EasternAf
SSP3EasternAf
SSP4EasternAf
SSP5EasternAf
CCAFS Scen1 Ants revisedEasternAf
CCAFS Scen2 Zebra revisedEasternAf
CCAFS Scen3 Leopards revisedEasternAf
CCAFS Scen4 Lions revisedEasternAf
CCAFS East Africa Scenarios to 2050 GDP per capita compared with the SSP scenarios to 2050, $ per capita (input)
Maize production in East Africa projected to 2030 under four scenarios: results from GLOBIOM (IIASA) and IMPACT (IFPRI). Historical data from FAO.
• Help organize strategic planning at the regional level
• Help to guide and develop agricultural, adaptation and mitigation policies at the national level
• Help to guide investments into agriculture and food security
• Help provide a context for research
• Provide a regional context for local decision-making
Exposure of
populations to
the impacts of
climate change
(hi, lo)
Sensitivity of
food systems
to these
impacts
(hi, lo)
Coping
capacity of
populations to
address these
impacts (hi, lo)
x x
• Areas in which food security is vulnerable to climate change using three key thresholds
• A way to pinpoint areas for targeting of interventions
Exposure 1: Areas where there is greater than 5% change in Length of Growing Period (LGP)
Ericksen et al. (2010)
Tools 5: Vulnerability mapping for priority setting
Areas with more dependence on crop agriculture assumed more sensitive : cropping <>16%
Chronic food insecurity a proxy for coping capacity (institutional, economic problems): stunting prevalence <>40%
Exposure of
populations to
the impacts of
climate change
(hi, lo)
Sensitivity of
food systems
to these
impacts
(hi, lo)
Coping
capacity of
populations to
address these
impacts (hi, lo)
x x
• Areas in which food security is vulnerable to climate change using three key thresholds
• A way to pinpoint areas for targeting of interventions Ericksen et al. (2010)
Tools 5: Vulnerability mapping for priority setting
Model Main exogenous drivers Main output variables
Computable General Equilibrium (CGE)
e.g. MIRAGE
Population, Total Factor Productivity, bioenergy demand, (carbon) taxes
Supply or demand volumes, prices, capital stock, GDP, GHG emissions
Partial Equilibrium (PE)
e.g. IMPACT
Population, GDP, input prices, bioenergy demand, yield and area trends
Supply or demand volumes, prices, GHG emissions
Tools 6: Integrated assessment: PE and GCE models
Tools 6: PE and CGE models MIRAGE Modeling International Relationships in Applied General Equilibrium
Trade Policy Analysis
• Export taxes • WTO Negotiations / Framework
• MIRAGE CGE model with Household Disaggregation
Trade and Climate Change
• Mitigation
• Biofuels, land use, and food prices
• Adaptation • Climate Change, trade consequences and trade policy
options
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Laborde, 2013
Tool Purpose Scale Weather data tools (reconstruction, infilling, generation)
• Improve data quality and availability for decision making and for use in other tools
Local national
Household modelling
• Evaluating options under uncertainty for effects on income, labour requirements, food security, GHG emissions, …
Local
Production forecasting
• Within-season projection of crop yields Local national
Scenarios (qualitative, quantitative)
• Facilitate discussions among stakeholders of plausible future development pathways
• Identify robust alternatives under uncertainty for attaining agreed objectives
Local Global
Priority setting tools, processes (qualitative, quantitative)
• Identify “hot spots” and “cold spots” of exposure / risk / vulnerability where interventions could be targeted
Local Global
Integrated assessment models (PE, CGE)
• Future supply and demand, land-use patterns, trade policy evaluation under uncertain economic development pathways
Regional global
Some of the tools that can inform policy making at different scales concerning risk management
1 Managing risk for sustainable agricultural growth • Approaches that consider different sources of risk and their
changing profiles • Relative benefits & costs of insurance, diversification, safety nets • More emphasis on building adaptive capacity and innovation • Integrating climate change effects on rainfall, temperature, pest /
disease patterns
2 Promoting policy coordination
• Holistic approaches to addressing food security, agriculture, climate change
• Involve multiple stakeholders, sectors, policy areas, time horizons, levels of governance
• Need to face up to complexity, uncertainty, volatility/shocks
3 Linking policy and research under uncertain futures
• Scenarios for looking at tradeoffs / synergies between multiple objectives of multiple stressors on human & biophysical systems
Achieving coordinated and science-informed policies