Adaptation Task Navigator
appraising vulnerability and impacts
impact analysis
Task overview
Impact attribution methods explain observed impacts by either using process-based models or building statistical models of the relationship between observed impacts and a number of explanatory variables. Most scholarly work in the field of CCVIA focuses on the explanation of impact through biophysical variables and goes under the label of impact attribution. Some work also tries to explain impacts through socio-economic variables. These approaches are sometimes also called vulnerability or adaptive capacity indicators in the literature (Yohe and Tol 2002; Hinkel 2011a). In order to avoid confusion, we only use the term vulnerability indicator for those approaches that do not use data of observed impacts.
The attribution of impacts to social system variables, face two major challenges. First, in contrast to the case of natural systems, general simulation models of social system are not available and the development of statistical models is only promising when systems can be described by few variables and a lot of data is available. The systems considered in the context of climate change are, however, generally complex social-ecological systems, which means that in principle, they cannot be described using few variables and simple (or linear) statistical regression models (Barnett et al. 2008; Hinkel 2011a). Second, the time-series data records available for impacts caused by climate change are often not long enough for building reliable statistical models (e.g., Bouwer 2011)
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Question addressed
Which (combination of) variable(s) can explain observed changes in the study unit?
Conditions of applicability
Data on explanatory variables is available.
Data on observed impacts on the study unit is available.
Theoretical assumptions
Explanation of observed impacts through climate and non-climate variables
Steps taken
1. Selection of potential explanatory variables based on literature and theory.
2. Application of statistical methods
Results achieved
Statistical model explaining observed impacts.
Issues involved
A general issue for the complex social-ecological systems considered in CCVIA is that the amount of possible explanatory variables is thus very large and not conducive to building statistical models. Second, most impact data has only begun to be collected with respect to slow-onset changes, most impact data is on extreme events.
Example cases from literature
Checkley et al., (2000), for example, explain changes in daily hospital admissions in Lima through the stimuli variables temperature, humidity and rainfall. Singh et al., (2001) explain observed incidences of diarrhoea in Fiji based on variations in temperature and rainfall.
Tol and Yohe (2007) address the question whether national level socio-economic variables can explain observed impact data found in the EM-DAT database. An initial list of 34 variables was selected based on the IPCC 's eight determinants of adaptive capacity. Six alternative impact indicators such as number of people affected by natural disasters, infant mortality and life expectancy were selected for which data was available in the EM-DAT database. 24 of the 34 indicating variables were found to be statistically not significant. Amongst the statistical significant ones, different ones were found significant for different impact indicators. They conclude that there are no universal explanations; mechanisms that cause impact vary from case to case and hazard to hazard.
Criteria checklist
Overview on the criteria that lead you to the current task:
| 1. | You want to generate knowledge on vulnerability and impacts relevant for adaptation. | |
| 2. | Your focus is on impacts. | |
| 3. | Data is available on observed impacts |
Toolbox
As yet, no toolbox entries have been related to 'Impact attribution'.
Case steps
Use these links to browse the Meditation case studies for steps that have addressed adaptation task 'Impact attribution'.
| SE2 - Tuscan people is hot! | |
| What is the relationship between climate and tourism in Tuscany? | |
External resources
weADAPT case studies identidied for task 'Impact attribution' 1
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Climate change modelling and analyses for Mozambique
This report uses historical data and climate projections to assess how climate change may affect the operations of Mozambique's Instituto Nacional de Gestão de Calamidades (National Disaster Management Institute). The climate messages presented here are based on analysing: observed data collected from 32 weather stations across Mozambique since 1960... | |
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1 note that this does not imply that the Mediation Integrated Methodology was used in these cases. | |