Climate predictions: the influence of nonlinearity and randomness

J. Michael T. Thompson, Jan Sieber

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The current threat of global warming and the public demand for confident projections of climate change pose the ultimate challenge to science: predicting the future behaviour of a system of such overwhelming complexity as the Earth's climate. This Theme Issue addresses two practical problems that make even prediction of the statistical properties of the climate, when treated as the attractor of a chaotic system (the weather), so challenging. The first is that even for the most detailed models, these statistical properties of the attractor show systematic biases. The second is that the attractor may undergo sudden large-scale changes on a time scale that is fast compared with the gradual change of the forcing (the so-called climate tipping).
Original languageEnglish
Pages (from-to)1007-1011
Number of pages5
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences
Volume370
Issue number1962
Early online date30 Jan 2012
DOIs
Publication statusPublished - 13 Mar 2012

Keywords

  • stochastic closure
  • climate tipping
  • statistical modelling
  • time-series analysis
  • thermodynamics

Fingerprint Dive into the research topics of 'Climate predictions: the influence of nonlinearity and randomness'. Together they form a unique fingerprint.

  • Cite this