ing as the climate modeling community keeps pace with the information needs of a changing climate system, while at the same time improving climate model capabilities and skill.

In this chapter specific scientific targets for advancing climate science and climate modeling in the coming decades are identified. They require modeling efforts at both global and regional scales, or a fusion of these efforts. This chapter emphasizes problems where (i) progress is likely, given appropriate strategic/scientific investment, and (ii) progress would directly benefit societal needs with respect to weather and/or climate impacts and investments in climate change mitigation and adaptation.

STRENGTHS OF CLIMATE MODELS

Bader et al. (2008) provide a detailed discussion of strengths and weaknesses of the current generation of global climate models. Current models have demonstrable skill in many aspects of climate dynamics, including their ability to simulate large-scale features of ocean and atmospheric circulation, planetary Rossby waves, extratropical cyclone dynamics and storm tracks, radiative transfer, and global temperatures (Chapter 1). Climate models conserve energy, mass, and momentum; can be integrated for multiple centuries; and have demonstrated the ability to simulate the broad features of 20th-century climate, both the mean state and historical climate change. The rich array of models and expertise, nationally as well as internationally, allows for extensive testing and model intercomparison activities. This cooperation within the global community provides further insight and confidence into the capabilities of climate models. No other global scientific endeavor enjoys this level of international cooperation, or is subject to the same degree of scientific and public scrutiny; although this presents some challenges, this has helped to drive climate modeling forward.

Several considerations underlie the reliability of climate models for many aspects of climate change. It is important to recognize that climate projections are not forecasts of the specific state of the climate system at a particular place and time; rather, they should be interpreted as a realization of the mean statistics of weather for a period of time in the future (commonly taken as the average over multiple decades). Constructing the statistics of future climate conditions is a different problem from predicting what the weather will be like on a given day or month in the future; it is less sensitive to nonlinear dynamics and initial conditions, as the statistics of short-lived weather systems average out over many years. The average climate of a location depends on the relative frequency of different weather systems, which is governed by large-scale features of atmospheric circulation that are reasonably robust in climate models.



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