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

1000

1500

2000

2500

3000

3500

4000

4500

5000

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

p.thornton@cgiar.org