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  • 1. Hansson, M
    et al.
    Michelson, Daniel
    SMHI, Core Services.
    Integration of radar with analysis fields - Bringing distant radar observations "down to Earth"2000In: Physics and chemistry of the earth. Part B: Hydrology, oceans and atmosphere, ISSN 1464-1909, E-ISSN 1873-4677, Vol. 25, no 10-12, p. 1033-1036Article in journal (Refereed)
    Abstract [en]

    Normal refraction of radar waves through the atmosphere prevents radar data at distant ranges from being quantitatively representative for the Earth's surface unless precipitation-related processes taking place between the radar echo and the surface are taken into account. A one-dimensional model is presented which uses a physical description of the processes involved in obtaining surface precipitation rate from a radar echo aloft, comprising local production, coalescence and evaporation. One or two cloud layers are assumed depending on the cloud base height. Input data are operationally analysed cloud base height, temperature, and humidity along with radar observations and their altitudes. At the moment, only precipitation as liquid water is assumed in the model. The method and results using it will be presented and discussed. (C) 2000 Elsevier Science Ltd. All rights reserved.

  • 2.
    Lindskog, Magnus
    et al.
    SMHI, Research Department, Meteorology.
    Jarvinen, H
    Michelson, Daniel
    SMHI, Core Services.
    Assimilation of radar radial winds in the HIRLAM 3D-Var2000In: Physics and chemistry of the earth. Part B: Hydrology, oceans and atmosphere, ISSN 1464-1909, E-ISSN 1873-4677, Vol. 25, no 10-12, p. 1243-1249Article in journal (Refereed)
    Abstract [en]

    During the last decade several attempts of assimilating radar wind data into atmospheric models have been reported by various research groups. Some of these are briefly reviewed here. A three-dimensional variational data assimilation (3D-Var) scheme for the High Resolution Limited Area Model (HIRLAM) forecasting system has been developed and prepared for assimilation of low elevation angle radar radial wind superobservations. The HIRLAM 3D-Var is based on a minimization of a cost function that consists of one term measuring the distance between the resulting analysis and a background field, which is a short-range forecast, and another term measuring the distance between the analysis and the observations. The development required for assimilating the radial wind data includes software for generating and managing the superobservations from polar volume data, a quality control algorithm and an observation operator for providing the model counterpart of the observation. The functionality of the components have been evaluated through assimilation experiments using data from Finnish and Swedish radars and further studies are underway. (C) 2000 Elsevier Science Ltd. All rights reserved.

  • 3.
    Michelson, Daniel
    et al.
    SMHI, Core Services.
    Koistinen, J
    Gauge-radar network adjustment for the Baltic Sea Experiment2000In: Physics and chemistry of the earth. Part B: Hydrology, oceans and atmosphere, ISSN 1464-1909, E-ISSN 1873-4677, Vol. 25, no 10-12, p. 915-920Article in journal (Refereed)
    Abstract [en]

    The gauge adjustment technique used to produce 2 x 2 km 3- and 12-hour radar-based accumulated precipitation datasets for the Baltic Sea Experiment is presented. The gauge adjustment technique is based on the gauge-to-radar ratio. A distance-dependent adjustment factor is derived and it is weighted against a spatially analyzed adjustment factor according to the local observation density and estimated spatial decorrelation distance. A preliminary adjustment strategy is applied in order to normalize data from many radars to a common level and to minimize the bias with gauges. The final adjustment field applied to radar accumulations is shown, through validation against independent gauge data, to minimize the bias between radar and gauge sums while raising the explained variance, compared to unadjusted radar sums. Areas not covered by radar are subjected to an optimal interpolation of systematically corrected gauge sums, and this field is merged with the gauge adjusted radar field in order to cover the entire Baltic Sea Experiment region. (C) 2000 Elsevier Science Ltd. All rights reserved.

  • 4.
    Persson, Tomas
    SMHI, Research Department, Oceanography.
    Solar radiation climate in Sweden1999In: Physics and chemistry of the earth. Part B: Hydrology, oceans and atmosphere, ISSN 1464-1909, E-ISSN 1873-4677, Vol. 24, no 3, p. 275-279Article in journal (Refereed)
    Abstract [en]

    Since 1983 a Swedish network of 12 solar radiation stations, measuring global radiation, G, and direct normal irradiance, EN, is Operated by SMHI. All stations are sited within the BALTEX area. During the fifteen years 1983-1997, for which a homogeneous radiation database has been built up, some clear features in the radiation climate show up. The largest difference in G on annular basis is between the stations Visby, located on the island of Gotland in the Baltic Sea, and Kiruna, the northernmost station. The mean annual total of G in Kiruna (2822 MJm(-2)) is 25 % less than in Visby (3758 MJm(-2)). This is due to both latitudinal effects and differing cloud conditions. The effect of different cloudiness is clearly seen when comparing the stations Vaxjo and Visby, which are only separated by 0.74 degrees in latitude. At the cloudier site in Vaixjo, G is on the average 12 % less than in Visby. At all stations there is a large year to year variation of 15 %, or more. During the period analysed there is a clear increasing trend in both G, EN and duration of bright sunshine at all stations. The trend in G averaged over all stations is + 7.2 %/decade. This is mainly caused by decreasing cloudiness, especially during the summer months. Taking the atmospheric water vapour into account, the (A) over circle ngstrom turbidity coefficient, beta, have been estimated from the measurements of EN Mean values of beta during 1983-1997 are 0.082 in Lund (station with highest turbidity) and 0.056 in Kiruna (station with lowest turbidity). These values are strongly affected, approximately to the same extent, by the major volcanic eruptions of El Chichon and Mt. Pinatubo. (C) 1999 Elsevier Science Ltd. All rights reserved.

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