Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction?
Andy Majda discussed a methodology for forecasting low frequency teleconnection patterns, such as the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO). By applying a fluctuation-dissipation theorem (FDT), the climate response to small external forcing can be estimated from well-chosen st...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.674.9699 2023-05-15T15:05:10+02:00 Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction? Paul Williams Marek Wlasak The Pennsylvania State University CiteSeerX Archives 2009 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.674.9699 http://www.met.reading.ac.uk/%7Ewilliams/publications/UKMO2009_BreakoutSession1.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.674.9699 http://www.met.reading.ac.uk/%7Ewilliams/publications/UKMO2009_BreakoutSession1.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.met.reading.ac.uk/%7Ewilliams/publications/UKMO2009_BreakoutSession1.pdf text 2009 ftciteseerx 2016-01-08T17:33:33Z Andy Majda discussed a methodology for forecasting low frequency teleconnection patterns, such as the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO). By applying a fluctuation-dissipation theorem (FDT), the climate response to small external forcing can be estimated from well-chosen statistics of the present climate. FDTs centre on identifying the appropriate response function, using an ergodic assumption and assuming that the evolution is in statistical equilibrium. The technique may be generalised to calculate accurate variance and mean estimates. Sensitivity information can also be obtained such that the forcing can be readily determined from a given response. We may also use FDTs to infer the regional perturbations that contain the most information. FDTs require strong mixing. They have been shown to work in the Lorenz (1996) model with 40 modes and in other simple climate models. They are also expected to work in more complex climate models. The validity of the response function is limited by the fidelity of the climate model from which it is generated. Climate models are numerical discretisations with finite Text Arctic North Atlantic North Atlantic oscillation Unknown Arctic |
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Andy Majda discussed a methodology for forecasting low frequency teleconnection patterns, such as the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO). By applying a fluctuation-dissipation theorem (FDT), the climate response to small external forcing can be estimated from well-chosen statistics of the present climate. FDTs centre on identifying the appropriate response function, using an ergodic assumption and assuming that the evolution is in statistical equilibrium. The technique may be generalised to calculate accurate variance and mean estimates. Sensitivity information can also be obtained such that the forcing can be readily determined from a given response. We may also use FDTs to infer the regional perturbations that contain the most information. FDTs require strong mixing. They have been shown to work in the Lorenz (1996) model with 40 modes and in other simple climate models. They are also expected to work in more complex climate models. The validity of the response function is limited by the fidelity of the climate model from which it is generated. Climate models are numerical discretisations with finite |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Paul Williams Marek Wlasak |
spellingShingle |
Paul Williams Marek Wlasak Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction? |
author_facet |
Paul Williams Marek Wlasak |
author_sort |
Paul Williams |
title |
Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction? |
title_short |
Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction? |
title_full |
Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction? |
title_fullStr |
Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction? |
title_full_unstemmed |
Report from breakout group 1: How can work in nonlinear PDEs most benefit climate prediction? |
title_sort |
report from breakout group 1: how can work in nonlinear pdes most benefit climate prediction? |
publishDate |
2009 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.674.9699 http://www.met.reading.ac.uk/%7Ewilliams/publications/UKMO2009_BreakoutSession1.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic North Atlantic North Atlantic oscillation |
genre_facet |
Arctic North Atlantic North Atlantic oscillation |
op_source |
http://www.met.reading.ac.uk/%7Ewilliams/publications/UKMO2009_BreakoutSession1.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.674.9699 http://www.met.reading.ac.uk/%7Ewilliams/publications/UKMO2009_BreakoutSession1.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766336917763260416 |