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- Kaare Brandt Petersen, Michael Syskind Pedersen, +20 authors Vasile Sima
- 2004

Acknowledgements: We would like to thank the following for contributions and suggestions: Bill Baxter, Brian Templeton, Christian Rishøj, Christian Schröppel Douglas L. Theobald, Esben Hoegh-Rasmussen, Glynne Casteel, Jan Larsen, Jun Bin Gao, Jürgen Struckmeier, Kamil Dedecius, Korbinian Strimmer, Lars Christiansen, Lars Kai Hansen, Leland Wilkinson, Liguo… (More)

- PAVEL SAKOV, PETER R. OKE
- 2006

This paper considers implications of different forms of the ensemble transformation in the ensemble square root filters (ESRFs) for the performance of ESRF-based data assimilation systems. It highlights the importance of using mean-preserving solutions for the ensemble transform matrix (ETM). The paper shows that an arbitrary mean-preserving ETM can be… (More)

This study investigates the relation between two common localisation methods in ensemble Kalman filter (EnKF) systems: covariance localisation and local analysis. Both methods are popular in large-scale applications with the EnKF. The case of local observations with non-correlated errors is considered. Both methods are formulated in terms of tapering of… (More)

- PAVEL SAKOV, PETER R. OKE
- 2007

A simple, versatile, computationally efficient ensemble-based method for objectively designing an observation array is described. The method seeks to compute the observation array that minimizes the analysis error variance, according to Kalman filter theory. While most elements of the method have been described elsewhere, this paper attempts to present a… (More)

l rights reserved. network is also enhanced by a network of tide gauges around Australia that is managed by the National Tidal Centre (www.bom.gov.au/ oceanography/). In contrast to the open-ocean components of IMOS, the shelf and coastal observation platforms are flexible, and the specifications of their deployment are largely to be determined by those… (More)

- P. Sakov, F. Counillon, L. Bertino, K. A. Lisæter, P. R. Oke
- 2012

We present a detailed description of TOPAZ4, the latest version of TOPAZ – a coupled ocean-sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only operational, large-scale ocean data assimilation system that uses the ensemble Kalman filter. This means that TOPAZ features a time-evolving, state-dependent estimate of the state… (More)

- PETER R. OKE, PAVEL SAKOV
- 2007

A simple approach to the estimation of representation error (RE) of sea level ( ), temperature (T ), and salinity (S) observations for ocean data assimilation is described. It is assumed that the main source of RE is due to unresolved processes and scales in the model. Therefore, RE is calculated as a function of model resolution. The methods described here… (More)

The study considers an iterative formulation of the ensemble Kalman filter (EnKF) for strongly nonlinear systems in the perfect-model framework. In the first part, a scheme is introduced that is similar to the ensemble randomized maximal likelihood (EnRML) filter by Gu and Oliver. The two new elements in the scheme are the use of the ensemble square root… (More)

- Peter R. Oke, Pavel Sakov, +6 authors Andreas Schiller
- 2013

The generation and evolution of eddies in the ocean are largely due to instabilities that are unpredictable, even on short time-scales. As a result, eddy-resolving ocean reanalyses typically use data assimilation to regularly adjust the model state. In this study, we present results from a second-generation eddy-resolving ocean reanalysis that is shown to… (More)

- Pavel Sakov
- ArXiv
- 2014

EnKF-C provides a light-weight generic framework for off-line data assimilation into large-scale layered geophysical models with the ensemble Kalman filter (EnKF). It is coded in C for GNU/Linux platform and can work either in EnKF or ensemble optimal interpolation (EnOI) mode.