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  • 1.
    Dahlgren, Per
    et al.
    SMHI, Research Department, Meteorology.
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    Assimilating host model information into a limited area model2012In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 64, article id 15836Article in journal (Refereed)
    Abstract [en]

    We propose to add an extra source of information to the data-assimilation of the regional HIgh Resolution Limited Area Model (HIRLAM) model, constraining larger scales to the host model providing the lateral boundary conditions. An extra term, J(k), measuring the distance to the large-scale vorticity of the host model, is added to the cost-function of the variational data-assimilation. Vorticity is chosen because it is a good representative of the large-scale flow and because vorticity is a basic control variable of the HIRLAM variational data-assimilation. Furthermore, by choosing only vorticity, the remaining model variables, divergence, temperature, surface pressure and specific humidity will be allowed to adapt to the modified vorticity field in accordance with the internal balance constraints of the regional model. The error characteristics of the J(k) term are described by the horizontal spectral densities and the vertical eigenmodes (eigenvectors and eigenvalues) of the host model vorticity forecast error fields, expressed in the regional model geometry. The vorticity field, provided by the European Centre for Medium-range Weather Forecasts (ECMWF) operational model, was assimilated into the HIRLAM model during an experiment period of 33 d in winter with positive impact on forecast verification statistics for upper air variables and mean sea level pressure.

  • 2.
    Dahlgren, Per
    et al.
    SMHI, Research Department, Meteorology.
    Landelius, Tomas
    SMHI, Research Department, Atmospheric remote sensing.
    Kållberg, Per
    SMHI, Research Department, Meteorology.
    Gollvik, Stefan
    SMHI, Research Department, Meteorology.
    A high-resolution regional reanalysis for Europe. Part 1: Three-dimensional reanalysis with the regional HIgh-Resolution Limited-Area Model (HIRLAM)2016In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 142, no 698, p. 2119-2131Article in journal (Refereed)
  • 3. Heygster, Georg
    et al.
    Melsheimer, Christian
    Mathew, Nizy
    Toudal, Leif
    Saldo, Roberto
    Andersen, Soren
    Tonboe, Rasmus
    Schyberg, Harald
    Tveter, Frank Thomas
    Thyness, Vibeke
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    Landelius, Tomas
    SMHI, Research Department, Atmospheric remote sensing.
    Dahlgren, Per
    SMHI, Research Department, Meteorology.
    Integrated Observation and Modeling of the Arctic Sea Ice and Atmosphere2009In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 90, no 3, p. 293-297Article in journal (Refereed)
  • 4.
    Landelius, Tomas
    et al.
    SMHI, Research Department, Atmospheric remote sensing.
    Dahlgren, Per
    SMHI, Research Department, Meteorology.
    Gollvik, Stefan
    SMHI, Research Department, Meteorology.
    Jansson, A.
    Olsson, Esbjörn
    SMHI, Research Department, Meteorology.
    A high-resolution regional reanalysis for Europe. Part 2: 2D analysis of surface temperature, precipitation and wind2016In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 142, no 698, p. 2132-2142Article in journal (Refereed)
  • 5. Stengel, M.
    et al.
    Undén, Per
    SMHI, Research Department, Meteorology.
    Lindskog, Magnus
    SMHI, Research Department, Meteorology.
    Dahlgren, Per
    SMHI, Research Department, Meteorology.
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    Bennartz, R.
    Assimilation of SEVIRI infrared radiances with HIRLAM 4D-Var2009In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 135, no 645, p. 2100-2109Article in journal (Refereed)
    Abstract [en]

    Four-dimensional variational data assimilation (4D-Var) systems are ideally suited to obtain the best possible initial model state by utilizing information about the dynamical evolution of the. atmospheric state from observations, such as satellite measurements, distributed over a certain period of time. In recent years, 4D-Var systems have been developed for several global and limited-area models. At the same time, spatially and temporally highly resolved satellite observations, as for example performed by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board the Meteosat Second Generation satellites, have become available. Here we demonstrate the benefit of a regional NWP model's analyses and forecasts gained by the assimilation of those radiances. The 4D-Var system of the High Resolution Limited Area Model (HIRLAM) has been adjusted to utilize three of SEVIRI's infrared channels (located around 6.2 mu m, 7.3 mu m, and 13.4 mu m, respectively) under clear-sky and low-level cloud conditions. Extended assimilation and forecast experiments show that the main direct impact of assimilated SEVIRI radiances on the atmospheric analysis were additional tropospheric humidity and wind increments. Forecast verification reveals a positive impact for almost all upper-air variables throughout the troposphere. Largest improvements are found for humidity and geopotential height in the middle troposphere. The observations in regions of low-level clouds provide especially beneficial information to the NWP system, which highlights the importance of satellite observations in cloudy areas for further improvements in the accuracy of weather forecasts. Copyright (C) 2009 Royal Meteorological Society

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