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This paper describes the development and first results of the ''Community Integrated Assessment System'' (CIAS), a unique multi-institutional modular and flexible integrated assessment system for modelling climate change. Key to this development is the supporting software infrastructure, SoftIAM. Through it, CIAS is distributed between the communities of institutions which has each contributed modules to the CIAS system. At the heart of SoftIAM is the Bespoke Framework Generator (BFG) which enables flexibility in the assembly and composition of individual modules from a pool to form coupled models within CIAS, and flexibility in their deployment onto the available software and hardware resources. Such flexibility greatly enhances modellers' ability to re-configure the CIAS coupled models to answer different questions, thus tracking evolving policy needs. It also allows rigorous testing of the robustness of IA modelling results to the use of different component modules representing the same processes (for example, the economy). Such processes are often modelled in very different ways, using different paradigms, at the participating institutions. An illustrative application to the study of the relationship between the economy and the earth's climate system is provided.

Increased melting of glaciers and ice caps, excluding Greenland and Antarctica, will probably represent the second largest contribution to global sea level rise by 2100. The temperature sensitivity of sea level rise depends upon the global distribution of glacier areas, the temperature sensitivity of glacier mass balance in each region, the expected change of climate in each region, and changes in glacier geometry resulting from climate change. None of these are particularly well known at present. Improvements in global climate models should eventually give better information about expected climate changes in regions where glaciers occur but there is also much work for glaciologists. For example, glacier areas, altitudes, shape characteristics and mass balance sensitivity are still not known for many glacierized regions and ways must be found to fill gaps.

Global-mean temperature and sea-level implications are calculated for four preliminary emissions scenarios presented elsewhere in this issue. Total anthropogenic temperature change in the year 2100 ranges from 1.3–4.0°C using the four scenarios for upper and lower bounds on emissions and high and low values for the climate sensitivity. The lower bound is higher than that given in the IPCC Second Assessment Report, due mainly to lower future sulfur dioxide emissions. These lower emissions also have the effect of reducing uncertainties associated with sulfate aerosol forcing. Significant future climate changes occur in all scenarios, indicating that adaptation policies need to be considered as an important component of climate-change policy.

ESCAPE (the Evaluation of Strategies to address Climate change by Adapting to and Preventing Emissions) is an integrated climate change assessment model constructed between 1990 and 1992 for DG XI of the Commission of the European Community by a consortium of research institutes headed by the Climatic Research Unit (CRU). It has been designed to enable the user to generate future scenarios of greenhouse gas emissions (through an energy-economic model), examine their impact on global climate and sea level (through two independent global climate models), and illustrate some of the consequences of this global climate change at a regional scale for the European Community (through a regional climate scenario generator and impact models). We provide a very brief overview of the ESCAPE model which, although innovative, suffers from a number of major limitations. Subsequent work in the CRU has concentrated on improvements to the global climate module and work has also commenced on an improved regional climate scenario generating module. These improvements will lead to a new integrated climate change assessment model, MAGICC (Model for the Assessment of Greenhouse gas Induced Climate Change) which can easily be incorporated into new larger integrated frameworks developed by other institutes.

This paper outlines the different methods which may be used for the construction of regional climate change scenarios. The main focus of the paper is the construction of regional climate change scenarios from climate change experiments carried out using General Circulation Models (GCMs). An introduction to some GCM climate change experiments highlights the difference between model types and experiments (e.g. equilibrium or transient). The latest generation of climate change experiments have been performed using fully coupled ocean-atmosphere GCMs. These allow transient simulations of climate change to be performed with respect to a given greenhouse gas forcing scenario. There are, however, a number of problems with these simulations which pose difficulties for the construction of climate change scenarios for use in climate change impacts assessment. The characteristics of the transient climate change experiments which pose difficulties for the construction of climate change scenarios are discussed. Three examples of these problems are: different climate change experiments use different greenhouse gas concentration scenarios; the “cold-start” problem which makes it hard to link future projections of climate change a given calendar year; and the drift of the climate is noticeable in the control simulations. In order to construct climate change scenarios for impacts assessment a method has therefore to be employed which addresses these problems. At present the climate modelling and climate change impacts communities are somewhat polarised in their approach to spatial scales. Current GCMs model the climate at resolutions larger than 2.5° × 3.75°, while the majority of impacts assessment studies are undertaken at scales below 50 km (or 0.5°). This paper concludes by addressing the problems in bringing together these two different modelling perspectives by presenting a number of regional climate change scenarios.