On the use of simple dynamical systems for climate predictions: A Bayesian prediction of the next glacial inception

Details On the use of simple dynamical systems for climate predictions: A Bayesian prediction of the next glacial inception On the use of simple dynamical systems for climate predictions: A Bayesian prediction of the next glacial inception

2009-06-19

arxiv.org/abs/0906.3625v2

Eur. Phys. J. Special Topics 174, 11-31 (2009)

Physics

Atmospheric and Oceanic Physics

superseeds the arXiv:0809.0632 (which was published in European Reviews). The Bayesian section has been significantly expanded

Scientific paper

10.1140/epjst/e2009-01087-5

Over the last few decades, climate scientists have devoted much effort to the development of large numerical models of the atmosphere and the ocean. While there is no question that such models provide important and useful information on complicated aspects of atmosphere and ocean dynamics, skillful prediction also requires a phenomenological approach, particularly for very slow processes, such as glacial-interglacial cycles. Phenomenological models are often represented as low-order dynamical systems. These are tractable, and a rich source of insights about climate dynamics, but they also ignore large bodies of information on the climate system, and their parameters are generally not operationally defined. Consequently, if they are to be used to predict actual climate system behaviour, then we must take very careful account of the uncertainty introduced by their limitations. In this paper we consider the problem of the timing of the next glacial inception, about which there is on-going debate. Our model is the three-dimensional stochastic system of Saltzman and Maasch (1991), and our inference takes place within a Bayesian framework that allows both for the limitations of the model as a description of the propagation of the climate state vector, and for parametric uncertainty. Our inference takes the form of a data assimilation with unknown static parameters, which we perform with a variant on a Sequential Monte Carlo technique (`particle filter'). Provisional results indicate peak glacial conditions in 60,000 years.

Affiliated with

Also associated with

No associations

Rating

On the use of simple dynamical systems for climate predictions: A Bayesian prediction of the next glacial inception does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with On the use of simple dynamical systems for climate predictions: A Bayesian prediction of the next glacial inception, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On the use of simple dynamical systems for climate predictions: A Bayesian prediction of the next glacial inception will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-401343