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The selection of methods for projecting future impacts of climate change starts with a determination of whether causal relationships between variables internal to the study unit and the external drivers of change can be formally represented as a computational model. In adaptation situations where models are not available, vulnerability indication approaches can be used to say something about possible future impacts based on data collected on the current state of the study unit. Alternatively, knowledge elicitation provides a means of surveying and classifying expert and lay opinions about climate change and its potential impacts.

Modelling future impacts involves the deployment of methods and tools drawn from a formidable and ever-expanding range of options. br>
Table 3-6 is a matrix of impact studies, divided by sector of analysis and geographical location. Symbols after each study indicate the methods employed by the study: various types of modelling, integrated assessment, participatory scenario development, expert judgment and indicators. Some of the studies—particularly those with a global focus—use historical data as analogues, or base their methods around existing literature reviews. On the whole, studies presented in this table are impact assessments looking to the future that use climate projections and provide analysis on how those projections will impact on the various sectors in the various locations.

Location	Europe	North America	South America	Africa and Middle East	Asia	Australasia	Global
Sector
Agriculture	Abildtrup et al, 2006 * ^ Falloon and Betts, 2010 !	Zhang et al, 2011b !	Jones and Thornton, 2003 % Meza et al, 2008 % @ Ruane et al, forthcoming %	Abraha and Savage, 2006 % Al Bakri et al, 2011 % Jones and Thornton, 2003 % Roudier et al, 2011 ! Thornton et al, 2010 %	Chavas et al, 2009 % Lioubimtseva and Henebry, 2009 @ Masutomi et al, 2009 % Srivastava et al, 2010 % Xiong et al, 2008 % Wei et al, 2009 % & Thomson et al, 2006 % Simelton et al, 2009 + @	Luo et al, 2003 % Pearson et al, 2011 ! ~	Berg et al, 2012 “ (tropics) Fraser, 2006 $ (famines) Jacxsens et al, 2010 (food safety supply chain) ! Kang et al, 2009 % & Mera et al, 2006 % (soybean and maize) Nardone et al, 2010 @ (livestock) Ramirez- Vallegas et al, forthcoming % ~ (sorghum) Sutherst et al, 2000 ! (pests) Thornton et al, 2009 @ (livestock developing countries)
Pollution	Alcamo et al, 2002 ^	McDonald et al, 2005 @
Coasts and Fisheries (marine)	Philippart et al, 2011 @						Badjeck et al, 2010 £ Brander, 2010 !
Ecosystems and/or biodiversity	De Chazal et al, 2008 ! * Lindner et al, 2010 ! ^ Van Minnen et al, 2002 ! + Schröter et al, 2005 ! Metzger et al, 2008 ! +	Andalo et al, 2005 ! Coops and Waring, 2011 ! Coops et al, 2012 ! Dale et al, 2010 ? Dalla Valle et al, 2007 ! Ehman et al, 2002 ? Ivits et al, 2012 ! MacRae et al, 2008 ? ! Nitschke and Innes, 2008 ? Taner et al, 2011 ?		Pettorrelli et al, 2012 “	Tanaka et al, 2012 !		Chakraborty et al, 2000 (plant diseases) ! Sekercioglu et al, 2012 ! @ (birds) Sietz et al, 2011 ^ (drylands) Stock et al, 2011 ! (living marine resources)
Urban	Bonazza et al, 2009 !	Hayhoe et al, 2010 ^ Wuebbles et al, 2010 ^	Romero Lankao et al, 2012 ^ @ (more adaptation, less quant)				Gasper et al, 2011 @ Li et al, 2012 ! (energy use in buildings) Romero Lankao and Qin, 2011 @ Willems et al, 2012 ! (urban drainage)
Water	Eckhardt and Ulbrich, 2003 & Falloon and Betts, 2010 !	Boyer et al, 2010 & Chang and Jung 2010 & Kienzle et al, 2012 & Zhang et al, 2011a &			De Silva et al, 2007 & Kelkar et al 2008 & # Lioubimtseva and Henebry, 2009 @ Park et al, 2010 @ Park et al, 2011 @ Varis et al, 2012 ! +		Green et al, 2011 @ (groundwater)
Transport							Koetse and Rietveld, 2009 @
Health		Patz et al, 2008 !	Romero Lankao et al, 2012 ^ @ (more adaptation, less quant)		Lioubimtseva and Henebry, 2009 @ Nelson, 2003 @ Vineis et al 2011 @
Energy		Burkett, 2011! @					Mideksa and Kallbekken, 2010 @
Coasts							Nicholls, 2002 ! (sea level flooding)

Key for methods:
* = participatory scenario development
~ = expert judgment
^ = integrated model/integrated assessment
% = crop simulation model
£ = livelihoods framework
“ = vegetation models
? = forest ecosystem models
! = modelling
& = water models
$ = landscape ecology
@ = literature review / analysis / historical data
# = participatory knowledge elicitation
+ = indicators


A large proportion of climate change impact assessments make use of predictive models that describe the causal relationships between climate and a study unit. However, modelling tools tend to be available only for certain sectors such as agriculture, water resources, coastal zones, and terrestrial ecosystems. Technical requirements for projecting climate change impacts are generally high and often difficult to meet, so in many cases it will be preferable to adopt an existing model and tailor it for the adaptation context or to meet specific assessment needs. Models vary enormously in their complexity, in the spatial and temporal scale of their application, and in their assumptions about adaptation, but the process of impact projection (Box 3-5) is generally the same: select climate and socio-economic scenarios, select adaptation options and strategies, then compute impacts. Each of these steps is described in detail in the following sub-sections.

Box 3 5: Overview of Impact Projection Theoretical assumptions Interaction between the study unit and drivers of change can be  formally represented as a computational model Adaptation can be formally represented as a computational model Question addressed What are the impacts of climate change? Data requirements Climate and socio-economic scenarios Information about adaptation options Typical result A list of propositions that map each scenario and strategy for adaptation to an impact. Generic steps 1. Select climate and socio-economic scenarios 2. Select adaptation strategies 3. Compute the impacts of the scenarios and adaptations

Representing adaptation
Projecting impacts of climate change depends not only on the climate and socio-economic scenarios that are selected, but also on the assumptions that are made about adaptation. It is therefore important to carefully consider whether to choose models that project potential impacts, which are those that “may occur without considering adaptation” (Parry et al. 2007: 876), in contrast to tools that project residual impacts, which include adaptation.

Most natural and human systems will undergo some form of autonomous adjustment in response to either gradual changes in climate or sudden shocks, so it is generally understood that potential impacts will almost certainly not occur. However, it is important to note that the purpose of representing adaptation in impact projection is not to compute an optimal adaptation policy, but to model how different assumptions about the kinds of adjustments that are possible translate into differences in impacts. In other words, the selection of adaptation strategies to represent in impact projection serves the same purpose as the selection of climate and socio-economic scenarios, i.e. to explore a range of possible futures.