|عنوان فارسی مقاله:||نظرات در مورد توسعه سناریوی تغییرات آب و هوایی|
|عنوان انگلیسی مقاله:||Comments on Climate Change Scenario Development|
|رشته های مرتبط:||جغرافیا، تغییرات آب و هوایی اقلیمی، آب و هواشناسی و مخاطرات آب و هوایی|
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|نشریه||الزویر – Elsevier|
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There has been a marked increase in the concentrations of infrared-absorbing gases in the atmosphere since the beginning of the industrial revolution. Their expected warming effect on the surface climate has led to a widespread demand for “predictions” of possible future climate change for use in impact and policy studies. However, various sources of uncertainty prohibit the issuing of confident predictions. Rather, “scenarios” of possible climate change are being developed for use in sensitivity studies, and as an aid to decision making regarding policies to limit greenhouse gas emissions, the adoption of adaptive strategies, and forward planning. In so far as the uncertainties regarding future climate are related to uncertain future rates of anthropogenic emissions of greenhouse gases, these uncertainties demonstrate that human decision-making may influence future climate change.
2. SOURCES OF UNCERTAINTY
Major sources of uncertainty about future climates arise from: 6) (ii) (iii) (iv) uncertainties about future greenhouse gas emissions and concentrations; limitations on the physical representations of processes in global climate models (GCMs), which lead to uncertainty regarding the global temperature sensitivity to increasing greenhouse gas concentrations; differences between models as to the spatial patterns of local climate change for a given global warming; and other less quantifiable uncertainties, such as the effect of changes in the ocean circulations (including El Niiio), natural climate variability, and changes due to other pollutants such es sulfate particles. Emissions of carbon dioxide, the most important anthropogenic greenhouse gas, are uncertain at 2100AD by a factor of about seven, according to the Intergovernmental Panel on Climate Change, known as IPCC [l]. The global climate sensitivity is usually expressed as the global average surface warming, at equilibrium, due to an effective doubling of CO2 concentration, and lies in the range 1.5 to 4.5”C. IPCC, in its 1992 supplementary report [l], repeats the view that at present GCMs do not give good agreement on the regional details of climate change, even for the same global average warmings.
3. PROGRESS TOWARDS CREDIBLE SCENARIOS
The first two sources of uncertainty above are now readily quantifiable using IPCC emission scenarios and ranges of global climate sensitivity, together with highly parameterised transient (time transgressive) models of the global ocean-atmosphere system. Regarding differences between GCMs at the regional scale, considerable progress has now been made by focusing on results from the more recent and improved GCM simulations. We have taken the view that results from different GCMs should only be considered for climate change scenarios if they can be shown to perform acceptably well in simulating the present climate. While “acceptance” is somewhat subjective, objective statistical tests can be applied to various simulated fields in comparing them with observed fields. In 1991, we did this for seven different GCM simulations of the present Australian climate, and were forced to reject five as completely unsatisfactory, accepting only two, with reservations, for scenario development . However, in 1993, a similar test of five newer GCM simulations found that the worst of the newer five was better than the best of the earlier seven . More recently, we have carried out statistical tests on the measure of agreement between these five more “acceptable” GCMs, in their predictions of the direction of change in precipitation between the present climate (1 x CO2) and an enhanced greenhouse climate (the 2 x CO2 simulations). All five GCMs, like others, agree on a global average increase in precipitation, and on increases preferentially at high latitudes (polewards of 60N or S). In our statistical tests, we have eliminated both these factors, and reduced the degrees of freedom to take account of spatial correlations in the climate changes at neighbouring gridpoints. We derived a frequency distribution of numbers of gridpoints, between 60 S and 60 N, to determine how many models would be expected to agree on an increase (or on a decrease) if there were no skill in the models at the regional scale. We then compared this with the frequency distribution of levels of agreement from the five simulations. We found that there were many more gridpoints at which all five GCMs agreed on the direction of precipitation change than would be expected by chance. According to our tests, the differences between actual numbers of agreements and those expected by chance were generally significant at better than the 99% probability level, showing that the patterns of regional increases and decreases in precipitation simulated by the GCMs are not random. This result gives us some confidence that there is meaning in the regional climate change patterns, at least at the coarse spatial scale of the existing GCMs, which have gridpoints several hundred kilometers apart (although agreement between models does not guarantee that the models are correct). Consequently, we have felt justified in using the range of results at particular gridpoints, between the five different GCMs, to estimate a range of possible regional climate changes per degree of global warming. These estimates can be converted to regional climate change scenarios for any time in the future using transient global warming projections.