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  • 1.
    Bengtsson, Lisa K.
    et al.
    Sveriges meteorologiska och hydrologiska institut (SMHI), Norrköping.
    Magnusson, Linus
    Stockholm University, Faculty of Science, Department of Meteorology .
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology .
    Independent Estimations of the Asymptotic Variability in an Ensemble Forecast System2008In: Monthly Weather Review, ISSN 0027-0644, E-ISSN 1520-0493, Vol. 136, no 11, p. 4105-4112Article in journal (Refereed)
    Abstract [en]

    One desirable property within an ensemble forecast system is to have a one-to-one ratio between the root-mean-square error (rmse) of the ensemble mean and the standard deviation of the ensemble (spread). The ensemble spread and forecast error within the ECMWF ensemble prediction system has been extrapolated beyond 10 forecast days using a simple model for error growth. The behavior of the ensemble spread and the rmse at the time of the deterministic predictability are compared with derived relations of rmse at the infinite forecast length and the characteristic variability of the atmosphere in the limit of deterministic predictability. Utilizing this methodology suggests that the forecast model and the atmosphere do not have the same variability, which raises the question of how to obtain a perfect ensemble.

  • 2.
    Graversen, Rune Grand
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology.
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology.
    Tjernström, Michael
    Stockholm University, Faculty of Science, Department of Meteorology.
    Körnich, Heiner
    Stockholm University, Faculty of Science, Department of Meteorology.
    Atmospheric mass-budget inconsistency in the ERA-40 reanalysis2007In: Quarterly Journal of the Royal Meteorological society, ISSN 0035-9009, Vol. 133, p. 673-680Article in journal (Refereed)
  • 3.
    Graversen, Rune Grand
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology.
    Mauritsen, Thorsten
    Stockholm University, Faculty of Science, Department of Meteorology.
    Tjernström, Michael
    Stockholm University, Faculty of Science, Department of Meteorology.
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology.
    Svensson, Gunilla
    Stockholm University, Faculty of Science, Department of Meteorology.
    Reply: Communications arising2008In: Nature, Vol. 455, p. E4-E5Article in journal (Refereed)
  • 4.
    Kleman, Johan
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology.
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology .
    Rodhe, Henning
    Stockholm University, Faculty of Science, Department of Meteorology .
    Bern förnekar fysikens grunder2008Other (Other (popular science, discussion, etc.))
  • 5.
    Körnich, Heiner
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology .
    Climate sensitivity and variability examined in a global climate model2009In: Multiscale Modeling and Simulation in Science., Berlin: Springer Verlag , 2009, p. 299-302Chapter in book (Other academic)
  • 6.
    Körnich, Heiner
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology.
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology.
    Combining the mid-latitudinal and equatorial mass/wind balance relationships in global data assimilation2008In: Tellus. Series A: Dynamic Meteorology and Oceanography, Vol. 60, no 2, p. 261-272Article in journal (Refereed)
  • 7.
    Magnusson, Linus
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology.
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology.
    Nycander, Jonas
    Stockholm University, Faculty of Science, Department of Meteorology.
    Initial state perturbations in ensemble forecasting2008In: Nonlinear processes in geophysics, ISSN 1023-5809, E-ISSN 1607-7946, Vol. 15, no 5, p. 751-759Article in journal (Refereed)
    Abstract [en]

    Due to the chaotic nature of atmospheric dynamics, numerical weather prediction systems are sensitive to errors in the initial conditions. To estimate the forecast uncertainty, forecast centres produce ensemble forecasts based on perturbed initial conditions. How to optimally perturb the initial conditions remains an open question and different methods are in use. One is the singular vector (SV) method, adapted by ECMWF, and another is the breeding vector (BV) method (previously used by NCEP). In this study we compare the two methods with a modified version of breeding vectors in a low-order dynamical system (Lorenz-63). We calculate the Empirical Orthogonal Functions (EOF) of the subspace spanned by the breeding vectors to obtain an orthogonal set of initial perturbations for the model. We will also use Normal Mode perturbations. Evaluating the results, we focus on the fastest growth of a perturbation. The results show a large improvement for the BV-EOF perturbations compared to the non-orthogonalised BV. The BV-EOF technique also shows a larger perturbation growth than the SVs of this system, except for short time-scales. The highest growth rate is found for the second BV-EOF for the long-time scale. The differences between orthogonal and non-orthogonal breeding vectors are also investigated using the ECMWF IFS-model. These results confirm the results from the Loernz-63 model regarding the dependency on orthogonalisation

  • 8.
    Magnusson, Linus
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology.
    Leutbecher, Martin
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology.
    Comparison between Singular Vectors and Breeding Vectors as Initial Perturbations for the ECMWF Ensemble Prediction System2008In: Monthly Weather Review, ISSN 0027-0644, E-ISSN 1520-0493, Vol. 136, no 11, p. 4092-4104Article in journal (Refereed)
    Abstract [en]

    In this paper a study aimed at comparing the perturbation methodologies based on the singular vector ensemble prediction system (SV-EPS) and the breeding vector ensemble prediction system (BV-EPS) in the same model environment is presented. A simple breeding system (simple BV-EPS) as well as one with regional rescaling dependent on an estimate of the analysis error variance (masked BV-EPS) were used. The ECMWF Integrated Forecast System has been used and the three experiments are compared for 46 forecast cases between 1 December 2005 and 15 January 2006. By studying the distribution of the perturbation energy it was possible to see large differences between the experiments initially, but after 48 h the distributions have converged. Using probabilistic scores, these results show that SV-EPS has a somewhat better performance for the Northern Hemisphere compared to BV-EPS. For the Southern Hemisphere masked BV-EPS and SV-EPS yield almost equal results. For the tropics the masked breeding ensemble shows the best performance during the first 6 days. One reason for this is the current setup of the singular vector ensemble at ECMWF yielding in general very low initial perturbation amplitudes in the tropics.

  • 9.
    Magnusson, Linus
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Nycander, Jonas
    Stockholm University, Faculty of Science, Department of Meteorology .
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology .
    Flow-dependent versus flow-independent initial perturbations for ensemble forecasting2009In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 61A, no 2, p. 194-209Article in journal (Refereed)
  • 10.
    Mauritsen, Thorsten
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology.
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology.
    Blocking prediction in an ensemble forecasting system2004In: Tellus, Vol. 56A, p. 218-228Article in journal (Refereed)
    Abstract [en]

    The predictability of the atmospheric blocking phenomenon is investigated using the output of the high-resolution ensemble prediction system of the European Centre for Medium-Range Weather Forecasts.

    The output from the model is analysed using an objective blocking index. This is compared with the theory of Charney and DeVore that blocking is a large-scale non-linear phenomenon. A consequence of the non-linearity is that in some cases multiple quasi-stationary atmospheric states can exist for the same set of boundary conditions.

    It is found that the model in general produces too few blocks. Good agreement is found between the models lacking ability to predict blocking frequency and the systematic errors of 500-hPa geopotential height. It is found that there exists a limit, in the middle of the medium range, beyond which forecasts of blocking onset should be considered as probabilistic rather than dynamical. Inspection of individual blocking events adds new support to the idea that atmospheric blocking can be explained using the Charney–DeVore model.

  • 11.
    Žagar, Nedjeljka
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Gustafsson, Nils
    Stockholm University, Faculty of Science, Department of Meteorology .
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology .
    Dynamical response of equatorial waves in variational data assimilation2004In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 56A, no 1, p. 29-46Article in journal (Refereed)
    Abstract [en]

    In this study we question the relative importance of direct wind measurements in the tropics by investigating limits of four-dimensional variational assimilation (4D-Var) in the tropics when only wind or mass field observations are available. Typically observed equatorial wave motion fields (Kelvin, mixed Rossby-gravity and n= 1 equatorial Rossby waves) are assimilated in a non-linear shallow water model. Perfect observations on the full model grid are utilized and no background error term is used. The results illustrate limits of 4D-Var with only one type of information, in particular mass field information. First, there is a limit of information available through the internal model dynamics. This limit is defined by the length of the assimilation window, in relation to the characteristics of the motion being assimilated. Secondly, there is a limit related to the type of observations used. In all cases of assimilation of wind field data, two or three time instants with observations are sufficient to recover the mass field, independent of the length of the assimilation time window. Assimilation of mass field data, on the other hand, although capable of wind field reconstruction, is much more dependent on the dynamical properties of the assimilated motion system. Assimilating height information is less efficient, and the divergent part of the wind field is always recovered first and more completely than its rotational part.

  • 12.
    Žagar, Nedjeljka
    et al.
    Stockholm University, Faculty of Science, Department of Meteorology .
    Gustafsson, Nils
    Stockholm University, Faculty of Science, Department of Meteorology .
    Källén, Erland
    Stockholm University, Faculty of Science, Department of Meteorology .
    Variational data assimilation in the tropics: the impact of a background error constraint2004In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 130, p. 103-125Article in journal (Refereed)
    Abstract [en]

    Geostrophic adjustment theory predicts that wind information is a primary information source in the tropics. We ask whether this is true when variational data assimilation including a background-error constraint is applied. The question is investigated by carrying out three- and four-dimensional variational (4D-Var) data assimilation experiments with nonlinear shallow-water equations and idealized waves. The contribution to the analysis from mass and wind field observations is contrasted to that of spectral characteristics and multivariate relationships of equatorial waves built into a background-error covariance matrix. A background-error term for the analysis is built by using the tropical eigenmodes and the observed variability is used to determine the relative weights for different modes.

    Single observation sensitivity experiments illustrate an important impact of Kelvin and mixed Rossby-gravity waves in reducing the coupling between the mass and wind fields, found when only equatorial Rossby waves are utilized in the background-error constraint.

    The assimilation experiments demonstrate two main features. First, the wind field information is of greater value than the mass field information, in spite of the known error statistics. A second intriguing feature is that the assimilation of wind observations better resolves smaller-scale features of the height field than the assimilation of height data. When height data are used, a somewhat different analysis response is obtained for the zonal and meridional wind components, due to the strong projection onto the Kelvin wave structure for height observations. Finally, a comparison of different time windows for 4D-Var illuminates the sensitivity of height field assimilation to the length of the assimilation window.

1 - 12 of 12
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