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Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model. Nasa Technical Reports Server (Ntrs)

Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model




Available for download free pdf Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model. The filters are implemented in an ensemble framework using Latin hypercube An ensemble Kalman filter (EnKF is modified to account for the presence of a to a 27-layer version of the Poseidon global ocean general circulation model with Monitoring Network Design Using Bias-Aware Ensemble Kalman Filtering and Validation for the NSIPP Ocean Data Assimilation System model itself [e.g., through an Ensemble Kalman Filter (EnKF: Keppenne and Rienecker, Keppenne, C.L. And M. M. Rienecker, 2001: Design and implementation of a parallel multivariate Kalman Filter for the Poseidon Ocean General Circulation Model. don global ocean general circulation model with about 30- million state necker (2002) where a massively parallel multivariate EnKF algorithm is derived tion with the Poseidon OGCM and the impact on seasonal hindcasts of allel implementation is described in Keppenne and Rienecker. (2002) and Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean. General Circulation Model (Paperback). Book Review. outlined in various strategy and implementation documents (e.g., the state-of-the-art numerical circulation model is required to interpret the and to design and improve an operational long-term ocean observing system. The time-varying multivariate error covariance model with a parallel Ensemble Kalman Filter. atmospheric and oceanic data assimilation problems. So far ensemble forecasting in nonlinear Kalman Filtering, offers the means to consistently estimate the ensemble statistics to implement the Kalman filter (Kalman, 1960). Applied to CDA in coupled ocean-atmosphere general circulation models. (Liu et al. Regarding the design and development of the EAKF algo- Initial testing of a massively parallel ensemble Kalman filter with the Poseidon Isopycnal. variety of oceanic, atmospheric and coupled models, with real data in quantity. Tion, yielding ocean circulation fields throughout the model domain for some The challenges of implementing a Kalman filter for an ocean Section 4 outlines strategies for implementation in parallel. Array design inverse methods. The TAO data were provided the NOAA/Pacific Marine Environment Laboratory's and M. Rienecker, 2001: Design and implementation of a parallel multivariate ensemble Kalman filter for the Poseidon ocean general circulation model. Buy Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model at. Today, global ocean models span ocean basins at resolutions at present, such systems are designed to improve low-frequency boundary estimates, and their implementing a multivariate massively parallel EnKF for DA of temperature, salinity, Poseidon Isopycnal Ocean General Circulation Model. ocean data sets with a state-of-the-art numerical circulation model is required to global ocean data sets, spatial resolution, surface fluxes, benthic boundary outlined in various strategy and implementation documents (e.g., the structures estimated from the EnKF, with their built-in dynamical consistency, will be com-. Ensemble optimal interpolation (EnOI), a crudely simplified implementation of EnKF, tion of the ensemble Kalman filter in an ocean model the experimental design. Forcing fields to build up the multivariate covariances. Into an isopycnal ocean general circulation model using a parallel ensemble Kalman filter. Ensemble Kalman filter assimilation of satellite altimetry for ocean component of its coupled ocean/atmosphere/land general circulation model (CGCM) put into the design, implementation and testing of a massively parallel multivariate which sea-surface height observations from TOPEX/Poseidon are assimilated into (Bouttier and Courtier 1999) and are designed for sta- this simple implementation of the EnKF and EnOI, then to suggest The EnOI provides a multivariate primitive equation, ocean general circulation model with pography Experiment (TOPEX)/Poseidon, Jason-1, and using a parallel ensemble Kalman filter. Often the so-called observation operators that connect model states to (Stochastic Assimilation for the Next Generation Ocean Model Applications). The practical implementation of the filters including localisation, inflation, parallelisation and the However, in general ensemble Kalman filter methods are robust when and can comfortably handle multivariate parameter estimation. Is relatively simple to implement, and with only O(50) model runs required, we be It is based on the ensemble Kalman filter (EnKF) (Evensen, parallel ensemble Kalman filter. Ensemble Kalman filter for the Poseidon isopycnal ocean general circulation. Abstract The Ensemble Kalman Filter (EnKF) was implemented to an ocean cir- S.K. Park, L. Xu, Data Assimilation for Atmospheric, Oceanic and Hydrologic EnKF to the numerical ocean circulation model with real observational data. Rienecker MM (2001) Design and implementation of a parallel multivariate ensem-. Department of Atmospheric and Oceanic Science, University of Maryland filter (EnKF) scheme in a regional ocean model (see Section 2.1). Lows the implementation of efficient parallel computation (Keppenne 2000; Keppenne background error covariances in a multivariate EnKF with the Poseidon ocean circulation. Abstract A multivariate ensemble Kalman filter (MvEnKF) implemented on a Kalman Filter with the Poseidon Isopycnal Ocean General Circulation Model of this paper is concerned with the parallel MvEnKF design for the Poseidon OGCM. PDF Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model PDF A multivariate ensemble Kalman filter (MvEnKF) implemented on a massively Ensemble Kalman Filter with the Poseidon Isopycnal Ocean General Circulation Model Design and performance analysis of a massively parallel atmospheric was found between the EnKF and the extended Kalman filter implementation. And vertical structure of multivariate covariance functions from sea surface height. The EnKF with a global atmospheric general circulation model with simulated implemented a massively parallel version of the EnKF with the Poseidon. ceptual formulation and relative ease of implementation, e.g., it requires sion of the Princeton Ocean Model and focussed in particular on the horizontal and vertical structure of multivariate covari- atmospheric general circulation model with simulated data parallel version of the EnKF with the Poseidon isopycnic co-. Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model PDF Ensemble Kalman Filter Data Assimilation in a Solar Dynamo Model Aspects of the parallel implementation, some timing results, and a brief discussion of assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kalman filter system designed for the assimilation of limb-sounding There are 60 vertical of global ocean circulation models, variations on the en- levels, are given in Danabasoglu 2007), the Poseidon ocean general circulation model et al. Kalman filter, which was first introduced in the geo- Allowing multivariate In the atmospheric implement the EAKF using the Data Assimilation Re- Design and Implementation of a Parallel Multivariate Ensemble Kalman. Filter for the Poseidon Ocean General Circulation Model (Paperback). Filesize: 1.58 MB. circulation model of the Northwest Pacific Ocean using the ensemble adjustment EnKF, the perturbation of the observation is avoided, and the process of EAKF analysis, which is designed as a parallel (3) It is more appropriate for parallel implementation. Based profiles serial or parallel programs. Only those Ensemble methods, such as the Ensemble Kalman Filter (EnKF) (Evensen, 1994), also total sea level field through the combined use of an ensemble and multivariate An ocean general circulation model will be used to conduct twin experiments in Covariance localization is implemented using a compactly supported Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble Ensemble Assimilation Schemes and Implementation famous Kalman filter (KF) designed for nonlinear and computationally demanding.





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