Scenario Types
Arbitrary, or synthetic, scenarios consider, for example, incremental changes in mean temperature and/or precipitation amount, usually combined with a baseline daily climate database. They are simple to apply, provide information on a range of possible changes and can readily be applied in a consistent way in different studies and regions, but they seldom represent a realistic set of changes that are physically plausible, particularly if uniform changes are applied over a very large area or if assumed changes in variables are not physically consistent with each other. Their main use is in the exploration of system sensitivity.
Analogue Scenarios
Analogue scenarios involve the use of past warm climates as scenarios of future climate (temporal analogue scenario), or the use of current climate in another location (usually warmer) as a scenario of future climate in the study area (spatial analogue scenario).
In temporal analogues, palaeoclimatic reconstructions of past climate from fossil evidence, or periods of observed global-scale warmth in the instrumental record, are used as analogues for the future climate. The advantage of using palaeoclimate data over instrumental data is that the temperature differences in the distant past compared to current climate tend to be greater than those within the instrumental record, and may, therefore, be more consistent with potential changes in average global temperature over the next 100 years. However, in addition to concerns about the quality and availability of palaeoclimate reconstructions, there are also concerns related to using data derived from time periods when the causes of climate change (e.g., orbital variations) were different from those resulting in the enhanced greenhouse effect, since the resulting regional and seasonal patterns of climate change may be quite different.
In spatial analogues, recorded climate regimes are identified which may resemble the future climate of a given region (e.g. Bergthusson et al. (1988) used northern Britain as a spatial analogue for the potential future climate over Iceland in order to determine future grass growth). Although such scenarios can be used to examine how social and natural systems have adapted to different climates, this approach is restricted since there is a frequent lack of correspondence between other important features (e.g., geography, soils etc.) of the two regions, meaning that the future climate of the study area is unlikely to be the same as the current climate of another location (Carter et al., 1994), even if the average annual temperature is similar. Because of the above problems, the climate change impacts assessment literature has generally recommended that these types of scenarios should not be used (IPCC, 1990; Carter et al., 1994; IPCC-TCGCIA, 1999).
Global Climate Model Scenarios
Climate models, particularly global climate models (GCMs), currently provide the major source of information for constructing scenarios of climate change. GCMs are considered to be the only credible tools currently available for simulating the response of the global climate system to increasing greenhouse gas concentrations, since they are based on mathematical representations of atmosphere, ocean, ice cap and land surface processes (IPCC-TGCIA, 1999). As they are based on physical laws and physically-based empirical relationships, GCMs are therefore the only tools that estimate changes in climate due to increased greenhouse gases for a large number of climate variables in a physically-consistent manner.
In the earlier equilibrium GCM experiments, climate was simulated in response to an instantaneous doubling or quadrupling of equivalent CO2 concentration. Scenarios from these experiments are not considered to be very realistic since they depict patterns of climate change which can be quite different to those occurring under the gradual change in atmospheric composition actually being observed. In the most recent transient GCM experiments, historical (since the nineteenth century) and future forcing due to greenhouse gases and sulphate aerosols has been included, thus enabling comparisons to be made between modelled and observed climate over the historical period. However, although GCMs accurately represent global climate, their simulations of current regional climate are often inaccurate (IPCC, 1996; Giorgi et al., 2001) and they do not produce output on a geographic and temporal scale fine enough for many impacts assessments. In addition, a single GCM, or even several GCMs, may not represent the full range of potential climate changes in a region.
From Global Climate Model to High Resolution Scenarios
Due to the limitations in GCM scenarios, other alternative methods or downscaling methodologies have been developed in recent years to obtain fine resolution (high spatial and temporal) climate change information. These downscaling processes include dynamical (RCM) and statistical methodologies. Results from the Canadian RCM (CRCM) runs are available through the CCCSN and include raw and derived/extreme variable datasets. Additional RCM products will be added to the CCCSN as they become available. The CRCM, driven by the CGCM, provides climate information at a higher spatial resolution, 45 km, than the CGCM. See Fine Resolution Scenarios for further details.
Additional background information on Constructing Scenarios is also available on the CCCSN.
References
Bergthusson, P., Bjurnsson, H., Dumundsson, O., Gudmundsson, B., Helgadutir, A. and J.V. Jumundsson (1988): The effects of climatic variations on agriculture in Iceland. In: The Impact of Climatic Variations on Agriculture: Volume 1: Assessments in Cool Temperate and Cold Regions, (Eds. Parry, M.L., Carter, T.R. & Konijn, N.T.), Kluwer, Dordrecht, The Netherlands, pp. 381-509.
Carter, T.R., Parry, M.L., Harasawa, H. and
Giorgi, F., Hewitson, B., Christensen, J., Hulme, M., von Storch, H., Whetton, P., Jones, R., Mearns, L. and C. Fu (2001): Regional climate information - evaluation and projections. In: Climate Change 2001: The Scientific Basis (Eds. Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P., Dai, X., Maskell, K. and C.A. Johnson). Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, pp. 583-638.
IPCC (1990): Climate Change: The IPCC Scientific Assessment, (Eds. Houghton, J.T., Jenkins, G. and J.J. Ephraums), Cambridge University Press, Cambridge, 364 pp.
IPCC (1996): Climate Change 1995: The Science of Climate Change, (Eds. Houghton, J.T., Meira Filho, L.G., Callander, B., Harris, N., Kattenberg, A. and K. Maskell), Cambridge University Press, Cambridge, 572 pp.
IPCC-TGCIA (1999): Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment. Version 1. Prepared by Carter, T.R., Hulme, M. and M. Lal, Intergovernmental Panel on Climate Change, Task Group on Scenarios for Climate Impact Assessment. 69 pp. (Available from: http://ipcc-ddc.cru.uea.ac.uk)
