Abstract

The scientific understanding of Earth's climate system is now sufficiently developed to show that climate change from anthropogenic greenhouse gas forcing is already upon us, and the rate of change as projected exceeds anything seen in nature in the past 10,000 years. The indisputable evidence of... Show moreThe scientific understanding of Earth's climate system is now sufficiently developed to show that climate change from anthropogenic greenhouse gas forcing is already upon us, and the rate of change as projected exceeds anything seen in nature in the past 10,000 years. The indisputable evidence of global warming and the knowledge that surface temperatures will continue to rise over the next several decades under any plausible emission scenario is now a factor in the planning of many governments, businesses, and socio-economic sectors for which climate sensitivity and vulnerability is high. It does not imply, however, that future changes will be uniform around the globe. On the time scale of a few years to a few decades ahead, regional and seasonal variations in weather patterns and climate, and their corresponding impacts, will be strongly influenced by natural, internal variability [1]. Decision makers in diverse arenas thus need to know the extent to which the climate events they are seeing are the product of this natural variability, and hence can be expected to reverse at some point, or are the result of potentially irreversible, forced anthropogenic climate change. Efforts to predict the evolution of climate over the next several decades that take into account both forced climate change and natural decadal-scale climate variability are in their infancy [2]. Many formidable challenges exist. For example, climate system predictions on the decadal time scale will require initialization of coupled general circulation models with the best estimates of the current observed state of the atmosphere, oceans, cryosphere, and land surface - a state influenced both by the current phases of modes of natural variability and by the accumulated impacts to date of anthropogenic radiative forcing. However, given imperfect observations and systematic errors in models, the best method of initialization has not yet been established, and it is not known what effect initialization has on climate predictions. It is also not clear what predictions should be attempted or how will they be verified. The brevity of most instrumental records furthermore means that even the basic characteristics and mechanisms of decadal variations in climate are relatively poorly documented and understood. As a consequence, the representation of natural variability arising from the slowly-varying components of the climate system differs considerably among models, so the inherent predictability of the climate system on the decadal time scale is also not well established. Demands will therefore be made on observations, particularly ocean observations, not only to describe the state of the climate system and improve knowledge of the mechanisms that give rise to decadal fluctuations in climate, but also to provide the optimal observations for decadal climate predictions and their verification. The purpose of this paper is to outline the most significant issues and the challenges of producing skillful predictions of the evolution of the climate system on the time scale of years to decades ahead. A very brief overview of observed decadal variability and its associated impacts is presented in the following section, while a concise description of the processes that give rise to such variability is presented in Section 3 (see also [3]). Different sources of predictability on decadal time scales are described in Section 4, while Section 5 describes issues associated with initializing coupled climate models (see also [4]). First attempts at initialized, decadal predictions and the challenge of verifying such predictions are summarized in Sections 6 and 7, while the paper concludes with some brief comments on the particular importance of ocean observations for emerging decadal prediction systems. Show less