developing improved climate products for effective climate risk management c. f. ropelewski...
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Developing Improved Climate Products for Effective Climate Risk Management
C. F. Ropelewski International Research Institute for Climate and Society
The Earth Institute, Columbia University
31st Climate Diagnostics and Prediction Workshop23-27 October 2006Boulder, CO
Development of new climate productsfor Effective Climate Risk Management
“Involve the Users from the start”
Considerations:
Be aware of the other factors effecting the system.
Understand the limiting factors (Internal and External)
Encourage flexibility in decision making and understandhow much flexibility resides in the system.
Be aware that there may be alternatives to those offered inthe use of climate information.
Institutions and Policies Research
• Methodologies for mapping institutions and policy process
•Methodologies to analyze policy responses and development outcomes
• Methodologies to analyze institutional utilityof climate information
Epidemic Preparedness and Response (EPR)
An example of how climate information can influence decisions in a real-world setting.
Example 1 - Health
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Why EPR Planning: Outbreak Detection and Response Without Preparedness
Delayed Response
DAY
CASESOpportunity for control
Late Detection
First Cases
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Why EPR Planning: Outbreak Detection and Response Without Preparedness
Rapid Response
DAY
CASES
Early Detection
Potential Cases Prevented
Case Study: Public Health, Botswana
Dec-Feb RAINFALL and Jan-May MALARIA incidence
5115N =
Detrended Malaria Anomoly Quartiles
Upper quartileMid quartilesLower quartile
Rain
fall
from
CM
AP
for
DJF
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1993
2000
(Thomson et al, 2006; Nature)
Environmental monitoring
ENV monitoring enables opportunities to mobilize more localized response >>
Example in Botswana …
Seasonal Forecasting…..
SCF offers opportunities for planning and preparedness …….
NMCP strengthen vector control measures and prepare emergency containers with mobile treatment centers
Example 2 – Agriculture
Using climate information to inform decisions inagriculture.
Maize Yield (kg/ha)
0 2500 5000 7500 10000 12500
Cu
mu
lati
ve F
req
uen
cy (
%)
0
10
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100La Niña (15 Sep)El Niño (15 Sep)
Adjusting crop management practices to ENSO phases
Maize Yield (kg/ha)
0 2500 5000 7500 10000 12500
Cu
mu
lati
ve F
req
uen
cy (
%)
0
10
20
30
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La Niña (15 Dec)El Niño (15 Sep)
Case Study: Agricultural production, SE S.America
Maize: Changing sowing date and hybrid typeLa Niña years: shorter season hybrid, late sowing date
Márgenes Brutos (US $/ha) para Riego de Maíz en Secano(Ciclo Corto, Siembra de Setiembre, 1968 - 1999)
Modelo CERES-Maize
1965 1970 1975 1980 1985 1990 1995 2000
Má
rgen
Bru
to (
US
$ /
ha)
-400
-200
0
200
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800
CV = 128%9 years in 30: results ( 0)60% of Total Income in 6 years
Gross Margins for Rainfed Maize (1960 – 2001) CERES Model
Márgenes Brutos (US $/ha) para Riego de Maíz Regado y en Secano(Ciclo Corto, Siembra de Setiembre, 1968 - 1999)
Modelo CERES-Maize
1965 1970 1975 1980 1985 1990 1995 2000
Má
rgen
Bru
to (
US
$ /
ha)
-400
-200
0
200
400
600
800
IrrigadoSecano
Gross Margins for Rainfed vs Irrigated Maize (1960 – 2001) CERES Model
Irrigated
Rainfed
Example 3 – Reservoir Management
Using climate information to inform decisions inWater Resources.
Case Study: Angat Reservoir, PhilippinesAssume that the current priority in water allocation is honored: 1st Manila water supply; 2nd Irrigation;
3rd Hydropower
Oct-Feb performance of the reservoir
Index insurance
• Insurance is a key tool to allow use of information in decisionmaking
• Problems with traditional crop insurance– Moral hazard– Adverse selection
• The index innovation– Insure weather index (such as seasonal rainfall), not
crop– Only partial protection (basis risk), should not overuse– Cheap, easy to implement, good incentives
• Minimum possible price (easy to determine): – aver insurance payout + admin + risk finance costs– This price must < value to client for market to exist
• In Malawi, smallholder farmers report they cannot currently obtain inputs necessary to address climate variability
• New contracts provide for a package of loans, groundnut and maize inputs
• Working toward packages including price incentives, risk protection to take advantage of forecasts
–Partners include Malawi farmers and financing associations (NASFAM, OIBM MRFC, Malawi Insurance Association), the World Bank CRMG, Malawi Met Service, CUCRED
Case Study: Index Insurance, Southern Africa
Summary of current activities in Africa
• Ethiopia– Drought famine relief (client: national government, pilot
2006)– Crop loss micro-insurance (client: farmers, pilot 2006)
• Morocco– Crop loss micro-insurance, climate change problems
• South Africa: Relatively developed financial markets– Apple grower cooperatives and freeze coverage
• Malawi– Drought relief (client: national government, pilot 2006)– Farm level crop loss, bundled contracts (~900 farmers,
transacted 2005)• Scoping: Tanzania, Uganda, Kenya, more on the way• India: BASIX, thousands of farmer transactions completed
World Bank CRMG, Re-insurers, WFP highly involved
SUMMARY
Climate Risk Management provides:
More resilient systems for management of seasonal climate variability. andA mechanism for building management systems to cope with climate variability on longer time scales
Tailoring climate information to risk management problems is key methodological issue
Early and effective engagement with stakeholders is essential
For most effective and timely implementation, institutional mapping is key
Summary (continued)
Be aware of the other factors effecting the system.
Understand the limiting factors (Internal and External)
Encourage flexibility in decision making and understandhow much flexibility resides in the system.
Be aware that there may be alternatives to those offered inthe use of climate information.
“Involve the Users from the start”