Vulnerability indication approaches attempt to say something about possible future impacts based on data collected on the current state of the exposure unit, often combined with social system variables representing capacity.
Vulnerability indication approaches face the challenge that the aggregation of indicating variables into a vulnerability index can hardly be supported by theory nor can the results be validated empirically (Hinkel 2011a). Due to the lack of theory, some approaches seek to validate through data generated in interviews and focus groups against the "narratives" of vulnerability present in the literature (e.g. Mustafa et al. 2008). Other approaches use expert judgement, but different experts usually rank dimensions differently (Brooks and Adger 2005). Nonetheless, current work on developing and improving vulnerability indicators to address these issues is ongoing (see e.g. Regions 2020, ClimWatAdapt Project and ESPON project). The difference between impact attribution and vulnerability indication approaches is that the former require data on observed impacts while the latter are only applied in the absence of such data.
Which (combination of) variable(s) give an indication on how climate change may impact the study unit?
Data on indicating variables is available.
Data on observed impacts is NOT available.
Future impacts cannot be reliably simulated using computational models.
Variables related to both capacity and climate drivers (or exposure) are responsible for impacts on study unity.
1. Selection of variables of interest
2. Application of statistical methods
A function that maps the current state of the entity to a measure of possible future impacts. The measure is often called adaptive capacity.
[text to be added]
Hahn et al. (2009) develop a Livelihood Vulnerability Index based on surveying 220 household in Mozambique. The indicating variables describing aspects such as demographics, social networks, resource availability and past exposure to climate variability were selected based on the literature and then aggregated using equal weights.
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. | Either no data is available on observed impacts, or trend detection / impact attribution have already been performed. | |
4. | Either no knowledge on future impacts is available, or a representative range of uncertainty has not been explored. | |
5. | Impact models are not available. |
Browse the toolbox to learn more on methods and tools related to adaptation task 'Vulnerability indication'.
Indicator mapping | |
UNDP Scenario Guidance |
Use these links to browse the Meditation case studies for steps that have addressed adaptation task 'Vulnerability indication'.
NE1 - Vulnerability of the elderly | |
In which regions are elderly likely to be vulnerable to the future impacts of climate change? |
weADAPT case studies identidied for task 'Vulnerability indication' 1
Mapping vulnerability of the elderly to climate change in Northern Europe
The elderly population is growing rapidly across the Nordic region. Within this group many individuals are potentially vulnerable to the impacts... | |
Indicators for assessing the vulnerability of Ujung Kulon National Park
Climate change will increase the pressure on the park’s biodiversity, and especially the Javan rhino. Socio-economic threats will also increase ... | |
Socio-economic indicators of vulnerability to climate hazards in Nepal
This work on socio-economic indices was supporting research for a pilot action that was part of the larger ACCCA project to increase... | |
Building Capacity in the Colombian coastal area
NCAP Colombia evaluates the vulnerability of key economic sectors to climate change effects in the coastal area and identifies strategies to... | |
1 note that this does not imply that the Mediation Integrated Methodology was used in these cases. |