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  • 1.
    Funquist, Lennart
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Ljungemyr, Patrik
    SMHI, Samhälle och säkerhet.
    Validation of HIROMB during 1995-961997Rapport (Övrigt vetenskapligt)
  • 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, Samhälle och säkerhet.
    Axell, Lars
    SMHI, Forskningsavdelningen, Oceanografi.
    Uncertainty estimation for operational ocean forecast products-a multi-model ensemble for the North Sea and the Baltic Sea2015Ingår i: Ocean Dynamics, ISSN 1616-7341, E-ISSN 1616-7228, Vol. 65, nr 12, s. 1603-1631Artikel i tidskrift (Refereegranskat)
    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.

  • 3.
    Hordoir, Robinson
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Axell, Lars
    SMHI, Forskningsavdelningen, Oceanografi.
    Höglund, Anders
    SMHI, Forskningsavdelningen, Oceanografi.
    Dieterich, Christian
    SMHI, Forskningsavdelningen, Oceanografi.
    Fransner, Filippa
    Groger, Matthias
    SMHI, Forskningsavdelningen, Oceanografi.
    Liu, Ye
    SMHI, Forskningsavdelningen, Oceanografi.
    Pemberton, Per
    SMHI, Forskningsavdelningen, Oceanografi.
    Schimanke, Semjon
    SMHI, Forskningsavdelningen, Oceanografi.
    Andersson, Helén
    SMHI, Forskningsavdelningen, Oceanografi.
    Ljungemyr, Patrik
    SMHI, Samhälle och säkerhet.
    Nygren, Petter
    SMHI, Samhälle och säkerhet.
    Falahat, Saeed
    SMHI, Samhälle och säkerhet.
    Nord, Adam
    SMHI, Samhälle och säkerhet.
    Jönsson, Anette
    SMHI, Samhälle och säkerhet.
    Lake, Irene
    SMHI, Samhälle och säkerhet. SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Doos, Kristofer
    Hieronymus, Magnus
    SMHI, Forskningsavdelningen, Oceanografi.
    Dietze, Heiner
    Loeptien, Ulrike
    Kuznetsov, Ivan
    Westerlund, Antti
    Tuomi, Laura
    Haapala, Jari
    Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas - research and operational applications2019Ingår i: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 12, nr 1, s. 363-386Artikel i tidskrift (Refereegranskat)
  • 4.
    Ljungemyr, Patrik
    et al.
    SMHI, Samhälle och säkerhet.
    Gustafsson, Nils
    SMHI, Forskningsavdelningen, Meteorologi.
    Omstedt, Anders
    SMHI, Forskningsavdelningen, Oceanografi.
    Parameterization of lake thermodynamics in a high-resolution weather forecasting model1996Ingår i: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 48, nr 5, s. 608-621Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A model for the parameterization of lake temperatures and lake ice thicknesses in atmospheric models is presented. The model is verified independently, and it is also tested within the framework of the High Resolution Limited Area Model(HIRLAM), applied operationally for short range weather forecasting at the Swedish Meteorological and Hydrological Institute (SMHI). The lake model is a slab model based upon energy conservation and treats the lakes as well mixed boxes with depths represented by the mean depths. The model is forced by near surface fluxes calculated from total cloudiness, air temperature, air humidity and low-level winds. A data base, describing 92000 Swedish lakes. provides the model with lake mean depths, areal sizes and locations. When the model is used for parameterization of lake effects in the atmospheric model, all the smaller lakes and the fractions of larger lakes within each horizontal grid square of the atmospheric model are parameterized by four model lakes, representing the lake size distribution. The verification of the lake model is done by comparing it with a more advanced, vertically resolved model, including parameterization of turbulent mixing processes, as well as by comparison with observations. A sensitivity test shows great interannual variations of the ice-covered season, which implies that lake models should be used instead of climate data. The results from an experiment with two-way coupling of the lake model to the atmospheric model are verified by comparing forecasted weather parameters with routine meteorological observations. These results show that the impact of lake effects can reach several degrees C in air temperatures close to the surface.

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