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A stochastic operational forecasting system of the Black Sea: Technique and validation
Institution:1. Jailoo SRL, seamod.ro, Valea Iepii nr. 1, Com. Salatrucu, Jud. Arges, Romania;2. GeoHydrodynamics and Environment Research, University of Liege, Belgium;1. Department of Astronautic Science and Mechanics, Harbin Institute of Technology, Harbin, 150001 China;2. LSEC, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190 China;1. Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 54–918, 77 Massachusetts Avenue, Cambridge, MA 02139–4307, USA;2. NASA Goddard Institute for Space Studies, 2880 Broadway, New York, NY10025, USA;1. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven 27515, Germany;2. A. M. Obukhov Institute of Atmospheric Physics RAS, Moscow, Russia;1. Institute for Coastal Research, HZG Geesthacht, Max-Planck-Straße 1, 21502 Geesthacht, Germany;2. Department of Atmospheric Sciences, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou 510275, PR China
Abstract:In this article, we present the latest version of an ensemble forecasting system of the hydrodynamics of the Black Sea, based on the GHER model. The system includes the Weakly Constrained Ensembles algorithm to generate random, but physically balanced perturbations to initialize members of the ensemble. On top of initial conditions, the ensemble accounts also for uncertainty on the atmospheric forcing fields, and on some scalar parameters such as river flows or model diffusion coefficients. The forecasting system also includes the Ocean Assimilation Kit, a sequential data assimilation package implementing the SEEK and Ensemble Kalman filters. A novel aspect of the forecasting system is that not only our best estimate of the future ocean state is provided, but also the associated error estimated from the ensemble of models. The primary goal of this paper is to quantitatively show that the ensemble variability is a good estimation of the model error, regardless of the magnitude of the forecast errors themselves. In order for this estimation to be meaningful, the model itself should also be well validated. Therefore, we describe the model validation against general circulation patterns. Some particular aspects critical for the Black Sea circulation are validated as well: the mixed layer depth and the shelfopen sea exchanges. The model forecasts are also compared with observed sea surface temperature, and errors are compared to those of another operational model as well.
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