Modelling extreme climatic events and their economic ...€¦ · Modelling extreme climatic events...
Transcript of Modelling extreme climatic events and their economic ...€¦ · Modelling extreme climatic events...
Modelling extreme climatic events and their economic impacts:
Managing global supply chain risk for sustainable intensification of food production
Aspen Institute 2nd Dialogue of the Food Security Strategy Group
Rome 5-7 February 2014, Aspen Institute Italia
Erik Chavez [email protected]
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D. Coumou and S. Rahmstorf (2012)
A decade of weather extremes. Nature Climate Change
More frequent extreme weather events: heat waves
Years highlighted are record breaking summer maximum (red) and minimum (blue) average temperature in Western Europe over the past 105 years data records
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• The index is crafted as a proxy of production based on one weather parameter (rainfall) • Most indexes developed are based on precipitation data. Contracts have been
structured on maximum temperatures (Anhui, China), wind speed (Ukraine) • Basis risk, the most important potential shortcoming of weather index programmes, is
the difference between actual production loss and index variation
Emergence of weather index-based insurance DRAFT – NOT FOR CIRCULATION
“Weather-within-climate” index and machine learning-based modelling framework
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Experimental results: Precipitation Variability Indices Selection
Three Technological Scenarios (Shandong province, maize)
Local rainfed variety Local irrigated variety
Switched rainfed variety
Pixel colours refer to the period of crop growth highest vulnerability to precipitation variability - Green/yellow: start of season - Red: middle of season - Blue: end of season
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Prov
ince
Lev
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Grid
Lev
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Province/country-level production risk profile under different climate & tech scenarios
Irrigated rice expected production under 2020’s climate scenario – 10 year return period heat wave event
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Index distribution under best and worst climate scenario
Weighted sum 2020’s decade
Rice yield response as function of heat wave index
Expected rice distribution in 2020’s driven by heat wave
Province/country-level production risk profile under different climate & tech scenarios
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Smoothing and decreasing weather risk costs: risk mitigation & transfer
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Global retailing and manufacturing industry:
• 71% see supply chain as strategic
• Over 50 % have not mapped top 10 suppliers
Supply chain risk management of global retailers and manufacturers
Supply chain risk costs 1-4 % revenue loss (100-400 mUSD for 10 bUSD rev) PWC/Zurich
Operational supply chain risk management
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Increasing climate robustness of supply-chain streams through risk mitigation and transfer
Global Financial and Reinsurance Market
Global retailing and manufacturing sector
Local producers (in Africa)
Increased production and climate-robust supply
Firm-level supply chain “climate” risk transfer
Access to investment finance
Access to risk mitigating and production increasing technology
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Increasing climate robustness of supply-chain streams through risk mitigation and transfer
Global Financial and Reinsurance Market
Global retailing and manufacturing sector
Local producers (in Africa)
Manufacturing & trading
Imperial College London Civil Engineering Department Finance Department Reading University Meteorology Department Satellite Observation Group Ecole Polytechnique Economics Department Hamburg University Climate Research Centre
Funding: European Institute of Technology European Union Project start: 2nd semester 2014
Technology firms NGO
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Increasing climate robustness of country-level food security and financial preparedness
World Bank • 1st preliminary results: April 2014 • Report to Ministry of Finance &
Ministry of Agriculture • Risk profiles of country-level direct
and indirect economic costs under different climate and technological scenarios
Mozambique maize production suitability index
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