Higher Resolution in an Operational Ensemble Kalman Filter

P. L. Houtekamer Data Assimilation and Satellite Meteorology Research Section, Environment Canada, Dorval, Québec, Canada

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Xingxiu Deng Meteorological Service of Canada, Environment Canada, Dorval, Québec, Canada

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Herschel L. Mitchell Data Assimilation and Satellite Meteorology Research Section, Environment Canada, Dorval, Québec, Canada

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Seung-Jong Baek Data Assimilation and Satellite Meteorology Research Section, Environment Canada, Dorval, Québec, Canada

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Normand Gagnon Meteorological Service of Canada, Environment Canada, Dorval, Québec, Canada

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Abstract

Recently, the computing facilities available to the Meteorological Service of Canada were significantly upgraded. This provided an opportunity to improve the resolution of the global ensemble Kalman filter (EnKF) and the medium-range Global Ensemble Prediction System (GEPS). In the EnKF, the main upgrades include improved horizontal, vertical, and temporal resolution. With the introduction of the higher horizontal resolution, it was decided to use a filtered topography in order to address an occasional instability problem. At the same time, the number of assimilated radiance observations was increased via a relaxation of the data-thinning procedures. In the medium-range GEPS, which already used the higher horizontal resolution, the filtered topography was also adopted. Likewise, the temporal resolution was increased to be the same as in the short-range integrations of the EnKF. With these changes, the grid used by the Canadian EnKF has 600 × 300 points in the horizontal and 74 vertical levels. The forecast model uses a 20-min time step and, for time interpolation of the model trajectories, model states are stored every hour. The EnKF uses an ensemble having 192 members. This paper sequentially examines the impact of these implemented changes. The upgraded EnKF became operational at the Canadian Meteorological Centre in mid-February 2013.

Corresponding author address: P. L. Houtekamer, Section de la Recherche en Assimilation des Données et en Météorologie Satellitaire, 2121 Route Trans-Canadienne, Dorval, QC H9P 1J3, Canada. E-mail: peter.houtekamer@ec.gc.ca

Abstract

Recently, the computing facilities available to the Meteorological Service of Canada were significantly upgraded. This provided an opportunity to improve the resolution of the global ensemble Kalman filter (EnKF) and the medium-range Global Ensemble Prediction System (GEPS). In the EnKF, the main upgrades include improved horizontal, vertical, and temporal resolution. With the introduction of the higher horizontal resolution, it was decided to use a filtered topography in order to address an occasional instability problem. At the same time, the number of assimilated radiance observations was increased via a relaxation of the data-thinning procedures. In the medium-range GEPS, which already used the higher horizontal resolution, the filtered topography was also adopted. Likewise, the temporal resolution was increased to be the same as in the short-range integrations of the EnKF. With these changes, the grid used by the Canadian EnKF has 600 × 300 points in the horizontal and 74 vertical levels. The forecast model uses a 20-min time step and, for time interpolation of the model trajectories, model states are stored every hour. The EnKF uses an ensemble having 192 members. This paper sequentially examines the impact of these implemented changes. The upgraded EnKF became operational at the Canadian Meteorological Centre in mid-February 2013.

Corresponding author address: P. L. Houtekamer, Section de la Recherche en Assimilation des Données et en Météorologie Satellitaire, 2121 Route Trans-Canadienne, Dorval, QC H9P 1J3, Canada. E-mail: peter.houtekamer@ec.gc.ca
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