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  • 1. Gastgifvars, Maria
    et al.
    Mueller-Navarra, Sylvin
    Funkquist, Lennart
    SMHI, Research Department, Oceanography.
    Huess, Vibeke
    Performance of operational systems with respect to water level forecasts in the Gulf of Finland2008In: Ocean Dynamics, ISSN 1616-7341, E-ISSN 1616-7228, Vol. 58, no 2, p. 139-153Article in journal (Refereed)
    Abstract [en]

    This paper is devoted to the validation of water level forecasts in the Gulf of Finland. Daily forecasts produced by four setups of operational, three-dimensional Baltic Sea oceanographic models are analyzed using statistical means and are compared with water level observations at three Finnish stations located on the northern coast of the Gulf of Finland. The overall conclusion is that the operational systems were skillful in forecasting water level variations during the study period from November 1, 2003, to January 31, 2005. The factors causing differences between the water level forecasts of different models are discussed as well. An important task of operational sea level forecasting services is to provide accurate and early information about extreme water levels, both positive and negative surges. During the study period, two major winter storms occurred which caused coastal flooding in the region. According to our analysis, the operational models forecast the rise of water levels during these events rather successfully. Nowadays, operational forecasts can provide early warnings of extreme water levels at least 1 day in advance, which may be regarded as a minimum requirement for an operational forecasting system. The paper concludes that the models generally performed very well, with over 93% of the hourly water level forecasts found to be within the range of +/- 15 cm of the observed water levels, and with the timing of the water level peaks accurately predicted. Further discussion and studies dealing with the assessment of the skills of both operational meteorological and oceanographic forecasts, especially in connection with rare surge events, will be necessary. Skill assessment of operational oceanographic models would be relatively easy if acceptable error limits or a quality system was developed for the Baltic Sea operational models.

  • 2. Golbeck, Inga
    et al.
    Li, Xin
    Janssen, Frank
    Bruening, Thorger
    Nielsen, Jacob W.
    Huess, Vibeke
    Soderkvist, Johan
    Buchmann, Bjarne
    Siiria, Simo-Matti
    Vaha-Piikkio, Olga
    Hackett, Bruce
    Kristensen, Nils M.
    Engedahl, Harald
    Blockley, Ed
    Sellar, Alistair
    Lagemaa, Priidik
    Ozer, Jose
    Legrand, Sebastien
    Ljungemyr, Patrik
    SMHI, Core Services.
    Axell, Lars
    SMHI, Research Department, Oceanography.
    Uncertainty estimation for operational ocean forecast products-a multi-model ensemble for the North Sea and the Baltic Sea2015In: Ocean Dynamics, ISSN 1616-7341, E-ISSN 1616-7228, Vol. 65, no 12, p. 1603-1631Article in journal (Refereed)
    Abstract [en]

    Multi-model ensembles for sea surface temperature (SST), sea surface salinity (SSS), sea surface currents (SSC), and water transports have been developed for the North Sea and the Baltic Sea using outputs from several operational ocean forecasting models provided by different institutes. The individual models differ in model code, resolution, boundary conditions, atmospheric forcing, and data assimilation. The ensembles are produced on a daily basis. Daily statistics are calculated for each parameter giving information about the spread of the forecasts with standard deviation, ensemble mean and median, and coefficient of variation. High forecast uncertainty, i.e., for SSS and SSC, was found in the Skagerrak, Kattegat (Transition Area between North Sea and Baltic Sea), and the Norwegian Channel. Based on the data collected, longer-term statistical analyses have been done, such as a comparison with satellite data for SST and evaluation of the deviation between forecasts in temporal and spatial scale. Regions of high forecast uncertainty for SSS and SSC have been detected in the Transition Area and the Norwegian Channel where a large spread between the models might evolve due to differences in simulating the frontal structures and their movements. A distinct seasonal pattern could be distinguished for SST with high uncertainty between the forecasts during summer. Forecasts with relatively high deviation from the multi-model ensemble (MME) products or the other individual forecasts were detected for each region and each parameter. The comparison with satellite data showed that the error of the MME products is lowest compared to those of the ensemble members.

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