Abstract
Today, climate models are widely discussed because of the climate projections they produce for the next century (see Chap. 31). The models used for climate prediction are developed first and foremost based on the data from observations of recent decades. Before being applied to forecasting, these models are evaluated to assess their ability to reproduce the present climate and its recent variations over the last decades. They represent our understanding of the current climate and of the mechanisms that intervene to play important roles in recent variations, but also our ability to translate this understanding into digital codes which is necessarily limited by computing capabilities. Thus, even though the most powerful computers are currently used to produce simulations with the most complex climate models, they are limited by computing power in terms of resolution and system complexity. This question of finding the best compromise between the desired timespan for a climate simulation and the complexity of the climate model used is crucial for modeling present and future climates, but is even more critical in paleoclimatology, where the time scales are much longer than for the IPCC predictions (which last a few centuries at most). In this chapter, we will show how models built for projecting future climate can be used for analysing past climate changes, but also that other types of models can be developed and used to understand past climatic changes.
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Kageyama, M., Paillard, D. (2021). Modeling and Paleoclimatology. In: Ramstein, G., Landais, A., Bouttes, N., Sepulchre, P., Govin, A. (eds) Paleoclimatology. Frontiers in Earth Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-24982-3_25
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