This chapter is a new addition compared with previous IPCC assessment reports. It stems from the increasing need to better understand the processes that determine regional climate and to evaluate regional climate change information for use in impact studies and policy planning. To date, a relatively high level of uncertainty has characterised regional climate change information. This is due to the complexity of the processes that determine regional climate change, which span a wide range of spatial and temporal scales, and to the difficulty in extracting fine-scale regional information from coarse resolution coupled Atmosphere-Ocean General Circulation Models (AOGCMs).

Coupled AOGCMs are the modelling tools traditionally used for generating projections of climatic changes due to anthropogenic forcings. The horizontal atmospheric resolution of present day AOGCMs is still relatively coarse, of the order of 300 to 500 km, due to the centennial to millennial time-scales associated with the ocean circulation and the computing requirements that these imply. However, regional climate is often affected by forcings and circulations that occur at the sub-AOGCM horizontal grid scale (e.g., Giorgi and Mearns, 1991). Consequently, AOGCMs cannot explicitly capture the fine-scale structure that characterises climatic variables in many regions of the world and that is needed for impact assessment studies (see Chapter 13).

Therefore, a number of techniques have been developed with the goal of enhancing the regional information provided by coupled AOGCMs and providing fine-scale climate information. Here these are referred to as “regionalisation” techniques and are classified into three categories:

• high resolution and variable resolution Atmosphere GCM (AGCM) experiments;
• nested limited area (or regional) climate models (RCMs);
• empirical/statistical and statistical/dynamical methods.

Since the IPCC WGI Second Assessment Report (IPCC, 1996) (hereafter SAR), a substantial development has been achieved in all these areas of research. This chapter has two fundamental objectives. The first is to assess whether the scientific community has been able to increase the confidence that can be placed in the projection of regional climate change caused by anthropogenic forcings since the SAR. The second is to evaluate progress in regional climate research. It is not the purpose of this chapter to provide actual regional climate change information for use in impact work, although the material discussed in this chapter serves most often for the formation of climate change scenarios (see Chapter 13).

The assessment is based on all the different modelling tools that are currently available to obtain regional climate information, and includes: (a) an evaluation of the performance, strengths and weaknesses of different techniques in reproducing present day climate characteristics and in simulating processes of importance for regional climate; and (b) an evaluation of simulations of climate change at the regional scale and associated uncertainties.

Evaluation of present day climate simulations is important because, even though a good simulation of present day climate does not necessarily imply a more accurate simulation of future climate change (see also Chapter 13), confidence in the realism of a model’s response to an anomalous climate forcing can be expected to be higher when the model is capable of reproducing observed climate. In addition, interpretation of the response is often facilitated by understanding the behaviour of the model in simulating the current climate. When possible, the capability of models to simulate climates different from the present, such as palaeoclimates, may also provide additional confidence in the predicted climatic changes.

The chapter is organised as follows. In the remainder of this section a summary is first presented of the conclusions reached in the SAR concerning regional climate change. This is followed by a brief discussion of the regional climate problem. Section 10.2 examines the principles behind different approaches to the generation of regional climate information. Regional attributes of coupled AOGCM simulations are discussed in Section 10.3. This discussion is important for different reasons: first, because AOGCMs are the starting point in the generation of regional climate change scenarios; second, because many climate impact assessment studies still make use of output from coupled AOGCM experiments without utilising any regionalisation tool; and third because AOGCMs provide the baseline against which to assess the added value of regionalisation techniques. Sections 10.4, 10.5 and 10.6 are devoted to the analysis of experiments using high resolution and variable resolution AGCMs, RCMs and empirical/statistical and statistical/dynamical methods, respectively. Section 10.7 analyses studies in which different regional-isation techniques have been intercompared and Section 10.8 presents a summary assessment.

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