Data Assimilation, Climate Modelling and Ensemble Generation
Activity Leader: Terry O’Kane
Staff and associates
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.
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 https://doi.org/10.1002/2017JD027222
Matear, Richard; Lenton, Andrew (2018) “Carbon-Climate feedbacks accelerate ocean acidification”, Biogeosciences 15 1721-1732 https://doi.org/10.5194/bg-15-1721-2018 .
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 http://www.cambridge.org/au/academic/subjects/earth-and-environmental-science/climatology-and-climate-change/nonlinear-and-stochastic-climate-dynamics#lMbmjFpXXiYdFBpC.99 .
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 https://doi.org/10.1515/mcwf-2017-0001.
Sandery, P., 2018: “Data assimilation cycle length and observation impact in mesoscale ocean forecasting”, Model Dev., 11, 4011–4019, https://doi.org/10.5194/gmd-11-4011-2018.
Kitsios, V. & Frederiksen, J.S., 2019, “Subgrid parameterizations of eddy-eddy, eddy-meanfield, eddy-topographic, meanfield-meanfield and meanfield-topographic interactions in atmospheric models”, Journal of the Atmospheric Sciences, Vol. 76, pp 457-477.
T.J. O’Kane, P.A. Sandery, D.P. Monselesan, P. Sakov, M.A. Chamberlain, R.J. Matear, M.A. Collier, D.T. Squire & L. Stevens (2019) “Coupled data assimilation and ensemble initialization with application to multi-year ENSO prediction”, J. Climate, 32, 997—1024.
M.A. Chamberlain, R.J. Matear, M. Holzer, D. Bi and S.J. Marsland (2019) “Transport matrices from standard ocean-model output and quantifying circulation response to climate change”, Ocean Modelling 135, 1—13, doi.org/10.1016/j.ocemod.2019.01.005.
I.G. Watterson (2019) “Indices of climate change based on patterns from CMIP5 models, and the range of projections”, Climate Dynamics, 52, 2451-2466, doi 10.1007/s00382-018-4260 .
Quinn, C., Sieber, J., & von der Heydt, A. S. (2019). “Effects of periodic forcing on a Paleoclimate delay model”, SIAM Journal on Applied Dynamical Systems, arXiv:1808.02310. https://epubs.siam.org/doi/pdf/10.1137/18M1203079.
Alkhayuon, H., Ashwin, P., Jackson, L., Quinn, C., & Wood, R. (2019). “Basin bifurcations, oscillatory instability and rate-induced thresholds in a global oceanic box model for AMOC”, Proceedings of the Royal Society of London A. arXiv:1901.10111. https://doi.org/10.1098/rspa.2019.005 .
J.S. Frederiksen & T.J. O’Kane (2018) “Markovian inhomogeneous closures for Rossby waves and turbulence over topography”, J. Fluid Mech. (2019), vol. 858, pp. 45–70 .
D.E. Gwyther, T.J. O’Kane, B.K. Galton-Fenzi & D.P. Monselesan (2018) “Intrinsic processes drive variability in basal melting of the Totten Glacier Ice Shelf”, Nature Communications, 9:3141 DOI: 10.1038/s41467-018-05618-2.
J.S. Risbey, D.P. Monselesan, T.J. O’Kane, C.R. Tozer, M.J. Pook and P.T. Haymen (2019) “Synoptic and large scale determinants of extreme Austral frost events”, J. Applied Meteorology and Climatology .
C. Tozer, J.S. Risbey, T.J. O’Kane, D.P. Monselesan and M. Pook (2018) “The relationship between waveguide mode forms in the Southern Hemisphere storm track and precipitation extremes over Tasmania”, Monthly Weather Review (2018), 146, pp4201—4230 .
Allen, K. J. Anchukaitis, M. G. Grose, E. R. Cook, J. S. Risbey, P. J. Baker, G. Lee, T. J. O’Kane, D. Monselesan, A. O’Grady, S. Larsen (2019) “Tree-ring reconstructions of cool season temperature for far southeastern Australia”, Climate Dynamics .
Y. Kushnir and A. A. Scaife, R. Arritt, G. Balsamo, G. Boer, F. Doblas-Reyes, E. Hawkins, M. Kimoto, R.K. Kolli, A. Kumar, D. Matei, K. Matthes, W. A. Müller, T.J. O’Kane, J. Perlwitz, S. Power, M. Raphael, A. Shimpo, D. Smith, M. Tuma, and B. Wu (2019) “Towards operational predictions of near term climate”, Nature Climate Change doi.org/10.1038/s41558-018-0359-7.
P.K. Dunstan, S.D. Foster, E. King, J.S. Risbey, T.J. O’Kane, D.P. Monselesan, A. Hobday, J. Hartog, and P. Thompson, (2018) “Interactions in Global patterns of variation in Sea Surface Temperature and Chlorophyll A produce mesoscale unique states”, Scientific Reports (2018) 8:14624 | DOI:10.1038/s41598-018-33057-.
Kitsios, V., O’Kane, T.J., & Zagar, N., 2019, “A reduced order theory of the Madden-Julian oscillation based on reanalysis normal mode coherences”, Journal of the Atmospheric Sciences, Vol 76, pp 2463 – 2480.
S.G. Penny, S. Akella, M.A. Balmaseda, P. Browne, J.A. Carton,M. Chevallier, F. Counillon, C. Domingues, S. Frolov, P. Heimbach, P. Hogan, I. Hoteit, D. Iovino, Patrick Laloyaux, Matthew J. MarMtin, Simona Masina, Andrew M. Moore, P. D. Rosnay, D. Schepers, B.M. Sloyan, A. Storto, A. Subramanian, S.-H. Nam, F. Vitart, C. Yang, Y. Fujii, H. Zuo, T.J. O’Kane, P.A. Sandery, T. Moore, C.C. Chapman (2019) “Observational Needs for improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction”, Frontiers in Marine Science , 11 July 2019.