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Data Assimilation, Climate Modelling and Ensemble Generation

Activity Leader: Terry O’Kane  

Staff and associates

Dr Richard Matear                              Dr Russell Fiedler

Dr Mark Collier                                   Dr Vassili Kitsios

Dr Matt Chamberlain                         Dr Paul Sandery

Ms Lauren Stevens                              Dr Pavel Sakov

Dr Ian Watterson



combines coupled modelling with ensemble data assimilation and prediction to provide the core of the Climate Analysis and Forecast Ensemble (CAFE) System.  The CAFE system is configured as a research tool to characterise the climate state over the recent past, to investigate the predictability of the climate system and in time to provide skilful multi-year climate forecasts.

Utilizing multi-year forecasts of the relevant climate observables relies on the development of coupled ocean atmosphere climate models in combination with advanced initialization schemes underpinned by modern data assimilation methods and a rigorous mathematical framework. The factors that enable these advances at this point in time are:

  • the availability of modern satellite and in situ ocean observations
  • knowledge of the relevant climate modes of variability that are predictable on a range of spatio-temporal scales,
  • the technical means to track the growth of predictable modes and reduce forecast errors, and
  • a rigorous mathematical framework to underpin and guide system development.

Advances in our understanding of the climate system, based on theoretical and observational studies, have highlighted some of the key processes, particularly in the ocean, upon which multi-year predictability depends. Importantly, climate models now feature high enough spatial resolution to simulate many of these processes with sufficiently realistic fidelity to resolve key processes.

Further, advances in computational power and storage now makes feasible ensemble forecasts of sufficient size that estimates of not only the mean future climatic state but also the uncertainty in the climate system are possible.

The goal is to develop a predictive framework that enables informed strategic decisions that exploit knowledge of climate variability over multiyear to decadal scale.


View transcript for video here


Risbey, James; O’Kane, Terry; Monselesan, Didier; Franzke, Christian; Horenko, Illia (2018) On the dynamics of Austral heat waves Journal of Geophysical, Atmospheres 123 (1) 38-57 
Matear, Richard; Lenton, Andrew (2018) Carbon-Climate feedbacks accelerate ocean acidification Biogeosciences 15 1721-1732
Crucifix, Michael; Lenoir, Guillaume; Mitsui, Takahito; Ditlevsen, Peter; Feldstein, Steven; Franzke, Christian; Straus, David; Franco, Molteni; Corti, Susanna; Nadiga, Balu; O’Kane, Terrence; Donner, Reik; Wiedermann, Marc; Donges, Jonathan; Horenko, Illia; Gerber, Susanne; Risbey, James; Monselesan, Didier; Gottwald, Georg; Crommelin, Daan; Frederiksen, Jorgen; Kitsios, Vassili; Zidikheri, Meelis; Harlim, John; Bunde, Armin; Ludescher, Josef; Watkins, Nicholas; Ribatet, Mathieu; Bodai, Tamas (2017) Nonlinear and Stochastic Climate Dynamics NonLinear and Stochastic Climate Dynamics
O’Kane, Terry; Monselesan, Didier; Risbey, James; Horenko, Illia; Franzke, Christian (2017) On memory, dimension and atmospheric teleconnections Mathematics of Climate and Weather Forecasting 3 (1) 1-27