Several developments have especially pushed the capabilities in modelling forward over recent years (see Figure 1.13 and a more detailed discussion in Chapters 6, 7 and 9).
There has been a continuing increase in horizontal and vertical resolution. This is especially seen in how the ocean grids have been refined, and sophisticated grids are now used in the ocean and atmosphere models making optimal use of parallel computer architectures. More models with higher resolution are available for more regions. Figure 1.14a and 1.14b show the large effect on surface representation from a horizontal grid spacing of 87.5 km (higher resolution than most current global models and similar to that used in today’s highly resolved models) to a grid spacing of 30.0 km (similar to the current regional climate models).
Representations of Earth system processes are much more extensive and improved, particularly for the radiation and the aerosol cloud interactions and for the treatment of the cryosphere. The representation of the carbon cycle was added to a larger number of models and has been improved since AR4. A high-resolution stratosphere is now included in many models. Other ongoing process development in climate models includes the enhanced representation of nitrogen effects on the carbon cycle. As new processes or treatments are added to the models, they are also evaluated and tested relative to available observations (see Chapter 9 for more detailed discussion).
Ensemble techniques (multiple calculations to increase the statistical sample, to account for natural variability, and to account for uncertainty in model formulations) are being used more frequently, with larger samples and with different methods to generate the samples (different models, different physics, different initial conditions). Coordinated projects have been set up to generate and distribute large samples (ENSEMBLES, climateprediction.net, Program for Climate Model Diagnosis and Intercomparison).
The model comparisons with observations have pushed the analysis and development of the models. CMIP5, an important input to the AR5, has produced a multi-model data set that is designed to advance our understanding of climate variability and climate change. Building on previous CMIP efforts, such as the CMIP3 model analysis reported in AR4, CMIP5 includes ‘long-term’ simulations of 20th century climate and projections for the 21st century and beyond. See Chapters 9, 10, 11 and 12 for more details on the results derived from the CMIP5 archive.
Since AR4, the incorporation of ‘long-term’ paleoclimate simulations in the CMIP5 framework has allowed incorporation of information from paleoclimate data to inform projections. Within uncertainties associated with reconstructions of past climate variables from proxy records and forcings, paleoclimate information from the Mid Holocene, Last Glacial Maximum and Last Millennium have been used to test the ability of models to simulate realistically the magnitude and large scale patterns of past changes (Section 5.3, Box 5.1 and 9.4).
The capabilities of ESMs continue to be enhanced. For example, there are currently extensive efforts towards developing advanced treatments for the processes affecting ice sheet dynamics. Other enhancements are being aimed at land surface hydrology, and the effects of agriculture and urban environments.
As part of the process of getting model analyses for a range of alternative assumptions about how the future may unfold, scenarios for future emissions of important gases and aerosols have been generated for the IPCC assessments (e.g., see the SRES scenarios used in TAR and AR4). The emissions scenarios represent various development pathways based on well-defined assumptions. The scenarios are used to calculate future changes in climate, and are then archived in the Climate Model Intercomparison Project (e.g., CMIP3 for AR4; CMIP5 for AR5). For CMIP5, four new scenarios, referred to as Representative Concentration Pathways (RCPs) were developed (Section 12.3; Moss et al., 2010). See Box 1.1 for a more thorough discussion of the RCP scenarios. Because results from both CMIP3 and CMIP5 will be presented in the later chapters (e.g., Chapters 8, 9, 11 and 12), it is worthwhile considering the differences and similarities between the SRES and the RCP scenarios. Figure 1.15, acting as a prelude to the discussion in Box 1.1, shows that the RF for several of the SRES and RCP scenarios are similar over time and thus should provide results that can be used to compare climate modelling studies.
ES 1.1 1.2.1 1.2.2 1.2.3 1.3 1.3.1 1.3.2 1.3.3 1.3.4 184.108.40.206 220.127.116.11 18.104.22.168 1.4.1 1.4.2 1.4.3 1.4.4 1.5 1.5.1 1.5.2 1.6 Box 1 FAQ Refs