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1 17 April 2015
Apollonia Miola Institute for Environment and Sustainability, European Commission - Joint Research Centre (JRC)
Climate resilient development: theoretical framework, selection criteria and fit for purpose indicators
2 17 April 2015
10 issues to be considered when building an index: 1. Theoretical framework; 2. Variables selection; 3. Imputation of missing data; 4. Multivariate analysis; 5. Normalization; 6. Weighting and aggregation; 7. Robustness and sensitivity; 8. Links to other variables; 9. Back to the real data; 10. Presentation, and Visualization
Source:JRC/OECD,2008
3 17 April 2015
Core concepts of IPCC report “Climate Change 2014: Impacts, Adaptation, and Vulnerability”.
Source:IPCC,2014
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FINAL DRAFT IPCC WGII AR5 Technical Summary Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014
Subject to Final Copyedit 57 28 October 2013
Figure TS.1.
Development: Key Entry point for Climate resilience
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Source: OECD (2014), Climate Resilience in Development Planning: Experiences in Colombia and Ethiopia, OECD Publishing. DOI: 10.1787/9789264209503-en
6 17 April 2015
“ Vulnerability indicators define, quantify, and weight aspects of vulnerability across regional units, but methods of constructing indices are subjective, often lack transparency, and can be difficult to interpret. There are conflicting views on the choice of adaptation metrics, given differing values placed on needs and outcomes, many of which cannot be captured in a comparable way by metrics” . IPCC, 2014 (IPCC WG II AR5 -Technical summary: page 12
“The search for metrics for adaptation will remain contentious with many alternative uses competing for attention”. IPCC, 2014 (IPCC WGII AR5 Chapter 4:page 23
Miola, Simonet, 2014
7 17 April 2015
Mean Rank of the analysed indices
Mean Rank of the Vulnerability Component
8 17 April 2015
Miola, Simonet, 2014
Variance in the Rank of the Vulnerability component
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Miola, Simonet, 2014
10 17 April 2015
Source:http://www.un.org/en/development/desa/policy/cdp/ldc/ldc_criteria.shtml#hai
Mixing EVI and geography of Vulnerability
11 Miola, Simonet, 2015
Overall DAC with aid ac1vi1es marked adapta1on as significant or principal objec1ve and Vulnerability component of the analysed indexes
12 Miola, Simonet, 2015
Criteria
…..reliable and open-source, consistent, with global coverage and based on data which are in the public domain.
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Components Natural hazards. It refers to the occurrence of climate-related and weather-driven
hazards, like flooding, storms, droughts, heat waves, and sea level rise. Exposure. It refers to the consequences for people and assets of the occurrence of
such events. Vulnerability. It captures the socio-economic factors that are likely to influence
vulnerability. It includes also indicators on sensitivity, which can be considered as dependence on natural resource sensitive sectors such as agriculture.
Adaptive capacity. It encompasses the features that determine the ability to adapt of a local community including ecosystem services.
Coping capacity It captures the ability of a country to cope with disasters in terms of formal, organized activities.
Mitigation capacity. It refers to the factors that ease implementation of actions by reducing greenhouse gases.
Development. It recalls economic and social factors that make an economy more resilient to natural hazards, thereby reducing the impacts of climate related events. They also describe socio-economic conditions that should be met to ensure that development is climate resilient.
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Indicator name Defini1on Relevant Hazards Sectors affected Ra1onale References
Dependence on agriculture
Agricultural employees (% of total popula4on)
Drought, dry spells, stress on surface water resources and floods
Agriculture and macro-‐economic impacts
Brooks et al., 2005; Sub-‐indicator of Sensi4vity in ND-‐Gain
Popula1on with access to improved water supply
percentage of popula4on with reasonable access (within one km) to an adequate amount of water (20 litres per person) through a household connec4on, public standpipe well or spring, or rain water system
Drought, dry spells, stress on surface water resources
Households People without improved water sources are vulnerable to diseases caused by unclean water and could become more vulnerable in the aMermath of a hazard
Füssel, 2010; Shah et al 2013; "Suscep4bility in the World Risk Index; Adap4ve capacity in ND-‐Gain; Lack of coping capacity in INFORM-‐ INFORM names it as ""Improved water source (% of popula4on with access)"" and suggests as data sources: WHO; UNICEF h_p://www.wssinfo.org/data-‐es4mates/table/ ND Gain uses WB data h_p://data.worldbank.org/indicator/SH.H2O.SAFE.ZS "
Case Study
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Sample of Countries
Least Developed Countries (LDC), Small Islands Developing (SIDS), low income countries and lower middle income countries and territories from the DAC list of Official Development Assistance (ODA) Recipients (excluding Tokelau, Singapore, and Bahamas)
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Normalization of indicators and Aggregation at component level.
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FORMULA OF AGGREGATION
Geometrical CC-Risk = Hazard * [(Exposure*Vulnerability)/ (Capacity *Development)] Linear CC-linear= (Hazard+ Exposure + Vulnerability+ Capacity +Development)/ 5
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Index calculated with geometrical formula of aggregation
20 Miola, Paccagnan,Papadimitriou,Mandrici, 2015
Index calculated with linear formula of aggregation
21 Miola, Paccagnan,Papadimitriou,Mandrici, 2015
Highest Difference in ranking of the two aggregation
22 The lowest rank is the highest score for the objective of the indices.
Miola, Paccagnan,Papadimitriou,Mandrici, 2015
Conclusion
1. no agreement to build a fit for purpose index; 2. Open issues:
• Limits of Data sets on Natural Hazards • Including indicators on M&E
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Conclusion – way to forward Proposal of a platform
As an interface between science and policy in the domains of (1) climate change, (2) disaster risk, and (3)development should provide transparent and open source information on climate change, vulnerability, adaptive capacity, mitigation and resilience.
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Conclusion – way to forward Proposal of a platform
2) Each Domain will include indicators, data sets related to concepts and political objectives autonomously. Projections. The climate change domain will include projections on the basis of scenarios (in a second phase); 3) Choice of the indicators, weights, formula of aggregation as a political choice to build a index fit for purpose; 4) Identification of overlapping with mitigation /low carbon development
Some Characteristics: 1) Openness, Transparency, Global coverage
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2014
Apollonia Miola and Catherine Simonet
Concepts and Metrics for Climate Change Risk and Development - Towards an index for Climate Resilient Development
2 0 1 4
Report EUR 26587EN
Climate resilient development: theoretical framework, selection criteria and fit for purpose indicators
20 1 5
Report EUR 27126
A case study to build an index Apollonia Miola, Vania Paccagnan, Eleni Papadimitriou, Andrea Mandrici