Technical Policy Briefing Notes - 1
Summary of Methods and Case Study Examples from the MEDIATION Project
Adaptation Decision Support
Policy Briefs
Summary Methods and Case Study Examples
Adaptation Decision Support
With the increased focus in Europe towards
adaptation implementation, there is a greater need to consider the
approaches and methods for assessing adaptation. However, policy
analysts, consultants and researchers are currently confronted with a
large number of concepts, methods, frameworks, guidelines and toolboxes
to choose from.
The MEDIATION Briefing Note on ‘Choosing Salient Approaches and Methods for Adaptation’ provides an overview for the decision support structure used in the MEDIATION Adaptation Platform. This recognises that there are many types of adaptation challenges and problem types, and that there is little to no guidance on which approach is appropriate for each of these different challenges. In response, MEDIATION has developed a more precise and specific language for describing the various challenges and methods for adaptation, and developed a diagnostic framework for problem-oriented adaptation research that matches adaptation challenges to appropriate approaches and methods for addressing them, using a series of decision trees.
The MEDIATION framework identifies five general stages as high-level entry points for adaptation research and practice, shown in Figure 1 below. The approaches and methods salient within each stage, and the empirical and theoretical criteria for choosing them are explained on the Adaptation Platform, and in the overview briefing note.
Stage three relates to the appraisal of adaptation options. This recognises that faced with a list of potential options there is a need to determine the most suitable or best option, noting that this definition will vary with the objectives of the adaptation problem type and the particular application.
Of course the appraisal of options is a standard part of all policy and project analysis, and there are existing guidelines and decision support tools to help in the prioritisation and ranking of options, many of which are focused on economic assessment, especially as policies or projects move towards implementation.
However, the appraisal of adaptation options involves several methodological challenges (EEA, 2007: OECD, 2008: UNFCCC, 2009). These relate to the varied spatial and sector contexts, as well as the timing of adaptation, which raises questions such as how much adaptation is needed (if any) and when action is most appropriate (UKCIP, 2002).
Adaptation also involves a core methodological challenge of uncertainty (UNFCCC, 2009; Hallegatte, 2009). As described in Box 1, future climate outcomes are highly uncertainty, because of future alternative socio-economic scenarios, but also because of the differences between climate model outputs (or simulations) for key climate parameters. This uncertainty cascades through to a large range of potential impacts and damage costs, which in turn affect the amount of adaptation that could be needed.
As a result, the most common techniques used in appraisal (and decision support) have limitations in coping with the uncertainty associated with climate change (e.g. see Hunt and Watkiss, 2011). There is therefore a growing consensus that the appraisal of climate change adaptation should incorporate uncertainty, and that this requires extended analysis within existing elements in existing tools or new decision methods that more fully capture uncertainty.
The MEDIATION Briefing Note on ‘Choosing Salient Approaches and Methods for Adaptation’ provides an overview for the decision support structure used in the MEDIATION Adaptation Platform. This recognises that there are many types of adaptation challenges and problem types, and that there is little to no guidance on which approach is appropriate for each of these different challenges. In response, MEDIATION has developed a more precise and specific language for describing the various challenges and methods for adaptation, and developed a diagnostic framework for problem-oriented adaptation research that matches adaptation challenges to appropriate approaches and methods for addressing them, using a series of decision trees.
The MEDIATION framework identifies five general stages as high-level entry points for adaptation research and practice, shown in Figure 1 below. The approaches and methods salient within each stage, and the empirical and theoretical criteria for choosing them are explained on the Adaptation Platform, and in the overview briefing note.
Figure 1. The Stages of
Adaptation and the Entry Point for
Decision Support Tools.
Decision Support Tools.
Stage three relates to the appraisal of adaptation options. This recognises that faced with a list of potential options there is a need to determine the most suitable or best option, noting that this definition will vary with the objectives of the adaptation problem type and the particular application.
Of course the appraisal of options is a standard part of all policy and project analysis, and there are existing guidelines and decision support tools to help in the prioritisation and ranking of options, many of which are focused on economic assessment, especially as policies or projects move towards implementation.
However, the appraisal of adaptation options involves several methodological challenges (EEA, 2007: OECD, 2008: UNFCCC, 2009). These relate to the varied spatial and sector contexts, as well as the timing of adaptation, which raises questions such as how much adaptation is needed (if any) and when action is most appropriate (UKCIP, 2002).
Adaptation also involves a core methodological challenge of uncertainty (UNFCCC, 2009; Hallegatte, 2009). As described in Box 1, future climate outcomes are highly uncertainty, because of future alternative socio-economic scenarios, but also because of the differences between climate model outputs (or simulations) for key climate parameters. This uncertainty cascades through to a large range of potential impacts and damage costs, which in turn affect the amount of adaptation that could be needed.
As a result, the most common techniques used in appraisal (and decision support) have limitations in coping with the uncertainty associated with climate change (e.g. see Hunt and Watkiss, 2011). There is therefore a growing consensus that the appraisal of climate change adaptation should incorporate uncertainty, and that this requires extended analysis within existing elements in existing tools or new decision methods that more fully capture uncertainty.
Box 1. Climate Projection
Uncertainty
While the appraisal of adaptation involves several difficult aspects, the most challenging is that of uncertainty (UNFCCC, 2009). There are many uncertainties that influence adaptation options, including the climate system, future socio-economic change, impacts, and issues that drive adaptation process such as human and institutional systems, however, the main focus to date has been on climate change uncertainty, which has two key components.
First, climate models require scenarios of future greenhouse gas emissions over time, which are generated from future socio-economic scenarios. These involve very wide ranges of future emission paths, ranging from global stabilisation scenarios consistent with the 2 degree goal, through to high emission scenarios that would lead to 4 to 5 degrees of global temperature change by 2100. At the current time, it is not clear which emission scenario is likely, and this affects future temperature, precipitation and other climate variables, though major differences between scenarios are only likely to emerge after 2035, when the scenarios start to diverge. Second, there are large variations in results from different climate models, even for outputs of the same future emission scenarios. This arises because of structural uncertainty in the models, the level of climate sensitivity (the warming associated with given emission increases), the exact regional and seasonal changes associated with certain changes in global temperature, and the difficulty in projecting complex effects such as precipitation. As a result, different climate models often give very different results even for the same scenario.
These two effects lead to very wide ranges of plausible changes in temperature and precipitation. Indeed, for the latter, different simulations can even differ in the sign of change. Examples are shown in the Figures below. This uncertainty is magnified as subsequent impacts are assessed, leading to an extremely wide range of possibilities for adaptation.
Note: Top: Change in surface air temperature (°C) for summer (JJA) (2070-2099 A1B).
Bottom: Change in summer precipitation (%) for summer (JJA) (2070-2099 for A1B). Source of plots, Christensen et al, 2011.
The range of outputs from 11 regional climate model projections for Europe from the ENSEMBLES project (with plots from Christensen et al, 2011), comparing projections for a single SRES scenario (A1B) for late century.
The top two figures show the minimum and maximum temperature projected from the models. This shows the level of temperature across Europe varies enormously between cooler (left, top) and warmer (right, top) models, particularly for the warming level in Southern Europe. The bottom two figures show the projections for precipitation, with drier (left, bottom) and wetter (right, bottom) models. In this case, even the sign of change is different in many locations, with different models indicating decreases (left) or increases (right) in precipitation from the UK in the northwest to Romania in the east.
While the appraisal of adaptation involves several difficult aspects, the most challenging is that of uncertainty (UNFCCC, 2009). There are many uncertainties that influence adaptation options, including the climate system, future socio-economic change, impacts, and issues that drive adaptation process such as human and institutional systems, however, the main focus to date has been on climate change uncertainty, which has two key components.
First, climate models require scenarios of future greenhouse gas emissions over time, which are generated from future socio-economic scenarios. These involve very wide ranges of future emission paths, ranging from global stabilisation scenarios consistent with the 2 degree goal, through to high emission scenarios that would lead to 4 to 5 degrees of global temperature change by 2100. At the current time, it is not clear which emission scenario is likely, and this affects future temperature, precipitation and other climate variables, though major differences between scenarios are only likely to emerge after 2035, when the scenarios start to diverge. Second, there are large variations in results from different climate models, even for outputs of the same future emission scenarios. This arises because of structural uncertainty in the models, the level of climate sensitivity (the warming associated with given emission increases), the exact regional and seasonal changes associated with certain changes in global temperature, and the difficulty in projecting complex effects such as precipitation. As a result, different climate models often give very different results even for the same scenario.
These two effects lead to very wide ranges of plausible changes in temperature and precipitation. Indeed, for the latter, different simulations can even differ in the sign of change. Examples are shown in the Figures below. This uncertainty is magnified as subsequent impacts are assessed, leading to an extremely wide range of possibilities for adaptation.
Note: Top: Change in surface air temperature (°C) for summer (JJA) (2070-2099 A1B).
Bottom: Change in summer precipitation (%) for summer (JJA) (2070-2099 for A1B). Source of plots, Christensen et al, 2011.
The range of outputs from 11 regional climate model projections for Europe from the ENSEMBLES project (with plots from Christensen et al, 2011), comparing projections for a single SRES scenario (A1B) for late century.
The top two figures show the minimum and maximum temperature projected from the models. This shows the level of temperature across Europe varies enormously between cooler (left, top) and warmer (right, top) models, particularly for the warming level in Southern Europe. The bottom two figures show the projections for precipitation, with drier (left, bottom) and wetter (right, bottom) models. In this case, even the sign of change is different in many locations, with different models indicating decreases (left) or increases (right) in precipitation from the UK in the northwest to Romania in the east.
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