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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

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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FINAL DRAFT IPCC WGII AR5 Technical Summary Do Not Cite, Quote, or Distribute Prior to Public Release on 31 March 2014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

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“ 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

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Mean Rank of the analysed indices

Mean Rank of the Vulnerability Component

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Miola, Simonet, 2014

Variance in the Rank of the Vulnerability component

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Miola, Simonet, 2014

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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  

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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

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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