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Title: Predictability of a laboratory analogue for planetary atmospheres
Author: Young, Roland Michael Brendon
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2009
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The thermally-driven rotating annulus is a laboratory experiment used to study the dynamics of planetary atmospheres under controlled and reproducible conditions. The predictability of this experiment is studied by applying the same principles used to predict the atmosphere. A forecasting system for the annulus is built using the analysis correction method for data assimilation and the breeding method for ensemble generation. The results show that a range of flow regimes with varying complexity can be accurately assimilated, predicted, and studied in this experiment. This framework is also intended to demonstrate a proof-of-concept: that the annulus could be used as a testbed for meteorological techniques under laboratory conditions. First, a regime diagram is created using numerical simulations in order to select points in parameter space to forecast, and a new chaotic flow regime is discovered within it. The two components of the framework are then used as standalone algorithms to measure predictability in the perfect model scenario and to demonstrate data assimilation. With a perfect model, regular flow regimes are found to be predictable until the end of the forecasts, and chaotic regimes are predictable over hundreds of seconds. There is a difference in the way predictability is lost between low-order chaotic regimes and high-order chaos. Analysis correction is shown to be accurate in both regular and chaotic regimes, with residual velocity errors about 3-8 times the observational error. Specific assimilation scenarios studied include information propagation from data-rich to data-poor areas, assimilation of vortex shedding observations, and assimilation over regime and rotation rate transitions. The full framework is used to predict regular and chaotic flow, verifying the forecasts against laboratory data. The steady wave forecasts perform well, and are predictable until the end of the available data. The amplitude and structural vacillation forecasts lose quality and skill by a combination of wave drift and wavenumber transition. Amplitude vacillation is predictable up to several hundred seconds ahead, and structural vacillation is predictable for a few hundred seconds.
Supervisor: Read, Peter L. Sponsor: Natural Environment Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Dynamical systems and ergodic theory (mathematics) ; Fluid mechanics (mathematics) ; Geophysics (mathematics) ; Atmospheric,Oceanic,and Planetary physics ; Physics ; Meteorology ; Chaos ; baroclinic ; instability ; data assimilation ; ensemble prediction ; breeding ; rotating annulus ; predictability ; forecast ; perfect model ; imperfect model ; vacillation ; ; 47.11.Bc ; 47.20.-k ; 47.32.Ef ; 47.52.+j ; 47.55.pb ; 92.60.Bh ; 92.60.Wc ; 96.12.Jt