Seminar/workshop 1984 Data Assimilation Systems and Observing System Experiments with Particular Emphasis on Fgge
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System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies
A fully coupled data assimilation (CDA) system, consisting of an ensemble filter applied to the Geophysical Fluid Dynamics Laboratory’s global fully coupled climate model (CM2), has been developed to facilitate the detection and prediction of seasonal-to-multidecadal climate variability and climate trends. The assimilation provides a self-consistent, temporally continuous estimate of the couple...
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Many methods have been used to undertake observing system design and assessment studies for oceanic and atmospheric applications most of which borrow tools from data assimilation [14, 4, 9]. To date, only a limited number of model-based studies have been undertaken to specifically assess the design and assessment of the Integrated Marine Observing System (IMOS) [11, 8]. These studies have used ...
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A one dimensional non-linear magnetohydrodynamic (MHD) system has been introduced to test a sequential optimal interpolation assimilation technique that uses a Monte-Carlo method to calculate the forecast error covariance. An ensemble of 100 model runs with perturbed initial conditions are used to construct the covariance, and the assimilation algorithm is tested using Observation Simulation Ex...
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Gary Brassington is first introducing this newsletter with a paper telling us about the international summer school for “observing, assimilating and forecasting the ocean” which will be held in Perth, Western Australia in 11-22 January 2010 (http://www.bom.gov.au/bluelink/summerschool/). The course curriculum will include topics covering the leading edge science in ocean observing systems, as w...
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Predicting the quality of water and air is a particular challenge for forecasting systems that support them. In order to represent the small-scale phenomena, a high-resolution model needs accurate capture of air and sea circulations, significant for forecasting environmental pollution. Data assimilation is one of the state of the art methods to be used for this purpose. Due to the importance of...
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