Working Group I: The Scientific Basis

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Executive Summary

Further work is required to improve the ability to detect, attribute, and understand climate change, to reduce uncertainties, and to project future climate changes. In particular, there is a need for additional systematic observations, modelling and process studies. A serious concern is the decline of observational networks. Further work is needed in eight broad areas:

  • Reverse the decline of observational networks in many parts of the world. Unless networks are significantly improved, it may be difficult or impossible to detect climate change over large parts of the globe.
  • Sustain and expand the observational foundation for climate studies by providing accurate, long-term, consistent data including implementation of a strategy for integrated global observations. Given the complexity of the climate system and the inherent multi-decadal time-scale, there is a need for long-term consistent data to support climate and environmental change investigations and projections. Data from the present and recent past, climate-relevant data for the last few centuries, and for the last several millennia are all needed. There is a particular shortage of data in polar regions and data for the quantitative assessment of extremes on the global scale.
  • Understand better the mechanisms and factors leading to changes in radiative forcing; in particular, improve the observations of the spatial distribution of greenhouse gases and aerosols. It is particularly important that improvements are realised in deriving concentrations from emissions of gases and particularly aerosols, and in addressing biogeochemical sequestration and cycling, and specifically, in determining the spatial-temporal distribution of carbon dioxide (CO2) sources and sinks, currently and in the future. Observations are needed that would decisively improve our ability to model the carbon cycle; in addition, a dense and well-calibrated network of stations for monitoring CO2 and oxygen (O2) concentrations will also be required for international verification of carbon sinks. Improvements in deriving concentrations from emissions of gases and in the prediction and assessment of direct and indirect aerosol forcing will require an integrated effort involving in situ observations, satellite remote sensing, field campaigns and modelling.
  • Understand and characterise the important unresolved processes and feedbacks, both physical and biogeochemical, in the climate system. Increased understanding is needed to improve prognostic capabilities generally. The interplay of observation and models will be the key for progress. The rapid forcing of a non-linear system has a high prospect of producing surprises.
  • Address more completely patterns of long-term climate variability including the occurrence of extreme events. This topic arises both in model calculations and in the climate system. In simulations, the issue of climate drift within model calculations needs to be clarified better in part because it compounds the difficulty of distinguishing signal and noise. With respect to the long-term natural variability in the climate system per se, it is important to understand this variability and to expand the emerging capability of predicting patterns of organised variability such as El Niño-Southern Oscillation (ENSO). This predictive capability is both a valuable test of model performance and a useful contribution in natural resource and economic management.
  • Improve methods to quantify uncertainties of climate projections and scenarios, including development and exploration of long-term ensemble simulations using complex models. The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible. Rather the focus must be upon the prediction of the probability distribution of the system´┐Żs future possible states by the generation of ensembles of model solutions. Addressing adequately the statistical nature of climate is computationally intensive and requires the application of new methods of model diagnosis, but such statistical information is essential.
  • Improve the integrated hierarchy of global and regional climate models with a focus on the simulation of climate variability, regional climate changes, and extreme events. There is the potential for increased understanding of extremes events by employing regional climate models; however, there are also challenges in realising this potential. It will require improvements in the understanding of the coupling between the major atmospheric, oceanic, and terrestrial systems, and extensive diagnostic modelling and observational studies that evaluate and improve simulation performance. A particularly important issue is the adequacy of data needed to attack the question of changes in extreme events.
  • Link models of the physical climate and the biogeochemical system more effectively, and in turn improve coupling with descriptions of human activities. At present, human influences generally are treated only through emission scenarios that provide external forcings to the climate system. In future more comprehensive models, human activities need to begin to interact with the dynamics of physical, chemical, and biological sub-systems through a diverse set of contributing activities, feedbacks, and responses.

Cutting across these foci are crucial needs associated with strengthening international co-operation and co-ordination in order to utilise better scientific, computational, and observational resources. This should also promote the free exchange of data among scientists. A special need is to increase the observational and research capacities in many regions, particularly in developing countries. Finally, as is the goal of this assessment, there is a continuing imperative to communicate research advances in terms that are relevant to decision making.

The challenges to understanding the Earth system, including the human component, are daunting, but these challenges simply must be met.

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