Temporal and spatial analogues are applied in a range of CCIAV studies. The most common of recently reported temporal analogues are historical extreme weather events. These types of event may recur more frequently under anthropogenic climate change, requiring some form of adaptation measure. The suitability of a given climate condition for use as an analogue requires specialist judgement of its utility (i.e., how well it represents the key weather variables affecting vulnerability) and its meteorological plausibility (i.e., how well it replicates anticipated future climate conditions). Examples of extreme events judged likely or very likely by the end of the century (see Table 2.2) that might serve as analogues include the European 2003 heatwave (see Chapter 12, Section 12.6.1) and flooding events related to intense summer precipitation in Bangladesh (Mirza, 2003a) and Norway (Næss et al., 2005). Other extreme events suggested as potential analogues, but about which the likelihood of future changes is poorly known (Christensen et al., 2007a), include El Niño-Southern Oscillation (ENSO)-related events (Glantz, 2001; Heslop-Thomas et al., 2006) and intense precipitation and flooding events in central Europe (Kundzewicz et al., 2005). Note also that the suitability of such analogue events should normally be considered along with information on accompanying changes in mean climate, which may ease or exacerbate vulnerability to extreme events.
Spatial analogues have also been applied in CCIAV analysis. For example, model-simulated climates for 2071 to 2100 have been analysed for selected European cities (Hallegatte et al., 2007). Model grid boxes in Europe showing the closest match between their present-day mean temperatures and seasonal precipitation and those projected for the cities in the future were identified as spatial analogues. These ‘displaced’ cities were then used as a heuristic device for analysing economic impacts and adaptation needs under a changing climate. A related approach is to seek projected climates (e.g., using climate model simulations) that have no present-day climatic analogues on Earth (‘novel’ climates) or regions where present-day climates are no longer to be found in the future (‘disappearing’ climates: see Ohlemüller et al., 2006; Williams et al., 2007). Results from such studies have been linked to risks to ecological systems and biodiversity.