Ensemble-based data assimilation for the climate of the past millennium

Matsikaris, Anastasios (2016). Ensemble-based data assimilation for the climate of the past millennium. University of Birmingham. Ph.D.

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Data assimilation (DA) is an emerging research area in palaeoclimatology. Here, ensemble-based DA schemes are implemented and evaluated for the reconstruction of the climate of some of the key periods from the past millennium. The study is among the first to employ a General Circulation Model for palaeoclimate DA. An off-line and an on-line DA method are first compared, assimilating continental proxy-based temperature reconstructions and using the 17th century as testing period. Both schemes provide simulations that follow the assimilated targets on large scales better than without DA. The on-line scheme has the advantage of temporal consistency of the analysis, and is subsequently used to reconstruct the climate for 1750-1850 AD. The assimilation performs well on large-scale temperatures, but there is no agreement between the DA analysis and reconstructions for regional temperature patterns. Evidence is presented to suggest that this lack of information propagation to smaller spatial scales is likely due to the fact that the Northern Hemisphere continental mean temperatures are not the best predictors for large-scale circulation anomalies, or that the assimilated reconstructions include noise. The lack of regional skill is again found when instrumental data for 1850-1949 AD are assimilated. Based on these results, it is argued that a potential way of improving the performance of DA is the assimilation of temperature reconstructions with higher spatial resolution.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
College/Faculty: Colleges (2008 onwards) > College of Life & Environmental Sciences
School or Department: School of Geography, Earth and Environmental Sciences
Funders: Natural Environment Research Council, Other
Other Funders: The University of Birmingham
Subjects: G Geography. Anthropology. Recreation > GB Physical geography
G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QC Physics
URI: http://etheses.bham.ac.uk/id/eprint/6876


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