Four degrees and beyond: the potential for a global ... - Amper

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Temperature and precipitation change 87 In §2, the methodology is described. Next, the magnitudes and patterns of climate change from high-end model simulations are examined and compared with the remaining projections, to see whether the behaviour of these two classes of model is very different. We then identify areas experiencing the greatest impacts of high-end climate change, which are those regions where the largest changes in temperature and precipitation occur. 2. Methodology The AR4 ensemble of global climate model projections was forced with greenhouse gas concentrations inferred from several SRES emissions scenarios [7]. The emissions of greenhouse gases (and hence greenhouse gas concentrations in the atmosphere) are greatest in the A2 scenario. Gridded temperature and precipitation data from each model were obtained from the Programme for Climate Model Diagnosis and Intercomparison (PCMDI; http:// www-pcmdi.llnl.gov). The models use many different horizontal grids; to facilitate comparison and analysis, all model results were transformed to the same horizontal resolution (1.875 ◦ longitude by 1.25 ◦ latitude) as the HadGEM1 model [10]. Here, we focused on the set of projections for the A2 scenario, to allow investigation of the variations in climate model responses to a single scenario of greenhouse gas concentrations. Of the 24 models discussed in the AR4, 19 were forced with the A2 scenario. Multiple simulations using the A2 scenario were available for some models (which differed only in the initial conditions used), in which case each simulation was treated independently. Overall, 40 simulations using the A2 scenario were available for our analysis. The models and simulations are listed in table 1. Additionally, all models had been used to perform a preindustrial control experiment, where greenhouse gas concentrations were held at fixed levels throughout the simulation. We plotted time series of global annual mean temperatures calculated from the preindustrial simulations and examined them by eye. Any clear initial drift in the temperatures (resulting from the modelled climate adjusting from its initial state to that determined by the greenhouse gas concentrations) was identified, and that portion of the data was not included in the analysis. It was only necessary to exclude some of these data for a few of the models. Preindustrial mean temperatures were then calculated from the remaining years (which numbered between 180 and 940). The increase in global mean temperatures between the preindustrial and the period 2090–2099 was calculated for all 40 simulations and rounded to one decimal point. In order to separate the simulations into those that warm faster and those that warm slower under a given forcing, we used an increase in global mean temperature of 4 ◦ C relative to preindustrial as an indicator. We classed those simulations that projected 4 ◦ C or more as ‘high-end’. There are too few results to assign probabilities to the changes; although appropriate methods to calculate probabilities are available (e.g. [11]), they are outside the scope of this paper. Internal variability in the models will not have a significant impact on the analysis, because simulated climate change by the 2090s will be dominated by the modelled response to the increasing greenhouse gas concentrations. These simulations suggest that a warming of 4 ◦ C could be reached from the 2080s [12]. Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010
88 M. G. Sanderson et al. Table 1. AR4 models analysed. Only those models which were run using the SRES A2 scenario are listed. The columns headed ‘run no.’ contain the number of the simulation analysed. The change in annual mean temperature for each simulation between the preindustrial period and 2090–2099 is given in the columns headed ‘DT( ◦ C)’. Simulations classed as high-end (which are 4.0 ◦ Cor greater) are shown in italics. model run no. DT( ◦ C) model run no. DT( ◦ C) bccr_bcm_2 1 3.7 miub_echo_g 3 4.0 cccma_cgcm3_1 1 4.5 mpi_echam5 1 4.0 cccma_cgcm3_1 2 4.5 mpi_echam5 2 4.0 cccma_cgcm3_1 3 4.5 mpi_echam5 3 4.0 cccma_cgcm3_1 4 4.4 mri_cgcm2_3_2a 1 3.3 cccma_cgcm3_1 5 4.4 mri_cgcm2_3_2a 2 3.4 cnrm_cm3 1 4.9 mri_cgcm2_3_2a 3 3.3 csiro_mk3_0 1 3.4 mri_cgcm2_3_2a 4 3.4 csiro_mk3_5 1 4.4 mri_cgcm2_3_2a 5 3.4 gfdl_cm2_0 1 3.6 ncar_ccsm3_0 1 4.3 gfdl_cm2_1 1 3.6 ncar_ccsm3_0 2 4.2 giss_model_e_r 1 3.0 ncar_ccsm3_0 3 4.2 ingv_echam4 1 3.7 ncar_ccsm3_0 4 4.2 inmcm3_0 1 3.8 ncar_ccsm3_0 5 4.2 ipsl_cm4 1 4.5 ncar_pcm1 1 3.1 miroc3_2_medres 1 4.0 ncar_pcm1 2 3.0 miroc3_2_medres 2 3.9 ncar_pcm1 3 3.0 miroc3_2_medres 3 3.9 ncar_pcm1 4 3.1 miub_echo_g 1 3.8 ukmo_hadcm3 1 4.0 miub_echo_g 2 4.0 ukmo_hadgem1 1 4.8 3. Results Overall, 21 projections using the A2 scenario were classed as high-end, and 19 as non-high-end. Temperature increases in several of the non-high-end projections reached 4 ◦ C or more during the 2090s in individual years. However, their decadal average temperature increases for the 2090s were less than 4 ◦ C, and so those models were not classed as high-end. Temperature increases from all simulations are given in table 1, where those from the high-end projections are in italics. In a similar analysis to that of Räisänen [13], the correlation between the temperature change and the modelled preindustrial mean temperature for all projections was calculated. Only the models that simulate the large areas of ice in the polar regions, which will have the coldest temperatures for the preindustrial period, can produce a large warming as the ice sheets recede. However, no correlation was observed, indicating that any relationship between modelled preindustrial ice sheet extent and temperature increases is complex and nonlinear. Next, regional changes in temperature and precipitation in the high-end and non-high-end models are examined. To minimize any impacts of decadal variability, model results for 2070–2099 are analysed. The median changes in temperature and precipitation for December, January and February (DJF) Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010
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ISSN 1364-503X volume 369 number 19
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Phil. Trans. R. Soc. A (2011) 369,
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Editorial David Garner Phil. Trans.
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Four degrees and beyond: the potent
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Preface 5 commitments might give us
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8 M. New et al. In the final plenar
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12 M. New et al. Table 1. Impacts a
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16 M. New et al. as permanent crop
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18 M. New et al. 24 Boe, J. L., Hal
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Beyond 'dangerous' climate change:
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Beyond dangerous climate change 21
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(i) Energy and industrial process e
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(a) 50 (b) GtCO 2e yr -1 40 30 20 1
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Table 1. Summary of scenario pathwa
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REVIEW Phil. Trans. R. Soc. A (2011
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Review. Interactions in a 4 ◦ C w
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spread in mosquitoborne disease may
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[89,94,95] further acidification by
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Editorial Editorial 3 D. Garner Pre
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