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  • 101. Van den Dool, H. M.
    et al.
    Peng, Peitao
    Johansson, Åke
    SMHI, Research Department, Meteorology.
    Chelliah, Muthuvel
    Shabbar, Amir
    Saha, Suranjana
    Seasonal-to-decadal predictability and prediction of North American climate - The Atlantic influence2006In: Journal of Climate, ISSN 0894-8755, E-ISSN 1520-0442, Vol. 19, no 23, p. 6005-6024Article in journal (Refereed)
    Abstract [en]

    The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP-NCAR reanalysis data. The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub) tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found. In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere-ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to. There are several signs of enthusiasm in the community about using "trends" (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years' averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in "explaining" variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century.

  • 102. van den Dool, H M
    et al.
    Saha, S
    Johansson, Åke
    SMHI, Research Department, Meteorology.
    Empirical orthogonal teleconnections2000In: Journal of Climate, ISSN 0894-8755, E-ISSN 1520-0442, Vol. 13, no 8, p. 1421-1435Article in journal (Refereed)
    Abstract [en]

    A new variant is proposed for calculating functions empirically and orthogonally from a given space-time dataset. The method is rooted in multiple linear regression and yields solutions that are orthogonal in one direction, either space or time. In normal setup, one searches for that point in space, the base point (predictor). which, by linear regression, explains the most of the variance at all other points (predictands) combined. The first spatial pattern is the regression coefficient between the base point and all other points, and the first time series is taken to be the time series of the raw data at the base point. The original dataset is next reduced; that is, what has been accounted for by the first mode is subtracted out. The procedure is repeated exactly as before for the second, third, etc., modes. These new functions are named empirical orthogonal teleconnections (EOTs). This is to emphasize the similarity of EOT to both teleconnections and (biorthogonal) empirical orthogonal functions (EOFs). One has to choose the orthogonal direction for EOT. In the above description of the normal space-time setup, picking successive base points in space, the time series are orthogonal. One can reverse the role of time and space-in this case one picks base points in time, and the spatial maps will be orthogonal. If the dataset contains biorthogonal modes, the EOTs are the same for both setups and are equal to the EOFs. When applied to four commonly used datasets, the procedure was found to work well in terms of explained variance (EV) and in terms of extracting familiar patterns. In all examples the EV for EOTs was only slightly less than the optimum obtained by EOF. A numerical recipe was given to calculate EOF, starting from EOT as an initial guess. When subjected to cross validation the EOTs seem to fare well in terms of explained variance on independent data las good as EOF). The EOT procedure can be implemented very easily and has, for some (but not all) applications, advantages over EOFs. These novelties, advantages, and applications include the following. 1) One can pick certain modes (or base point) first-the order of the EOTs is free, and there is a near-infinite set of EOTs. 2) EOTs are linked to specific points in space or moments in time. 3) When linked to Row at specific moments in time, the EOT modes have undeniable physical reality. 4) When linked to flow at specific moments in time, EOTs appear to be building blocks for empirical forecast methods because one can naturally access the time derivative. 5) When linked to specific points in space, one has a rational basis to define strategically chosen points such that an analysis of the whole domain would benefit maximally from observations at these locations.

  • 103. van Meijgaard, E
    et al.
    Andrae, Ulf
    SMHI, Research Department, Meteorology.
    Rockel, B
    Comparison of model predicted cloud parameters and surface radiative fluxes with observations on the 100 km scale2001In: Meteorology and atmospheric physics (Print), ISSN 0177-7971, E-ISSN 1436-5065, Vol. 77, no 1-4, p. 109-130Article in journal (Refereed)
    Abstract [en]

    Cloud parameters and surface radiative fluxes predicted by regional atmospheric models are directly compared with observations for a 10-day period in late summer 1995 characterized by predominantly large-scale synoptic conditions. Observations of total cloud cover and Vertical cloud structure are inferred from measurements with a groundbased network of Lidar ceilometers and IR-radiometers and from satellite observations on a 100 kilometer scale. Groundbased observations show that at altitudes below 3 km, implying liquid water clouds, there is a considerable portion of optically non-opaque clouds. Vertical distributions of cloud temperatures simultaneously inferred from the groundbased infrared radiometer network and from satellite can only be reconciled if the occurrence of optically thin cloud structures at mid- and high tropospheric levels is assumed to be frequent. Results of three regional atmospheric models, i.e. the GKSS-REMO, SMHI-HIRLAM. and KNMI-RACMO, are quantitatively compared with the observations. The main finding is that all models predict too much cloud amount at low altitude below 900 hPa, which is then compensated by an underestimation of cloud amount around 800 hPa. This is likely to be related with the finding that all models tend to underestimate the planetary boundary layer height. All models overpredict the high-level cloud amount albeit it is difficult to quantify to what extent due to the frequent presence of optically thin clouds. Whereas reasonably alike in cloud parameters, the models differ considerably in radiative fluxes. One model links a well matching incoming solar radiation to a radiatively transparent atmosphere over a too cool surface, another model underpredicts incoming solar radiation at the surface due to a too strong cloud feedback to radiation, the last model represents all surface radiative fluxes quite well on average: but underestimates the sensitivity of atmospheric transmissivity to cloud amount.

  • 104. Wolters, L
    et al.
    Cats, G
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    Wilhelmsson, T
    Data-parallel numerical methods in a weather forecast model1995In: Applied Numerical Mathematics, ISSN 0168-9274, E-ISSN 1873-5460, Vol. 19, no 1-2, p. 159-171Article in journal (Refereed)
    Abstract [en]

    The results presented in this paper are part of a research project to investigate the possibilities to apply massively parallel architectures for numerical weather forecasting. Within numerical weather forecasting several numerical techniques are used to solve the model equations. This paper compares the performance of implementations on a MasPar system of two techniques, finite difference and spectral, that are adopted in the numerical weather forecasting model HIRLAM. The operational HIRLAM model is based on finite difference methods, while the spectral model is still in a research phase. Also the differences in relative performance of these methods on the MasPar and vector architectures will be discussed.

  • 105. Zaplotnik, Ziga
    et al.
    Zagar, Nedjeljka
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    An intermediate-complexity model for four-dimensional variational data assimilation including moist processes2018In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 144, no 715, p. 1772-1787Article in journal (Refereed)
  • 106. Zilitinkevich, S S
    et al.
    Perov, Veniamin
    SMHI, Research Department, Meteorology.
    King, J C
    Near-surface turbulent fluxes in stable stratification: Calculation techniques for use in general-circulation models2002In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 128, no 583, p. 1571-1587Article in journal (Refereed)
    Abstract [en]

    Practically oriented flux-calculation techniques based on correction functions to the neutral drag and heat/mass transfer coefficients are further developed. In the traditional formulation, the correction functions depend only on the bulk Richardson number. However, data from measurements of turbulent fluxes and mean profiles in stable stratification over different sites exhibit too strong variability in this type of dependencies. Indirect evidence from climate and weather prediction modelling also shows that the traditional flux-calculation technique is not sufficiently advanced. It is conceivable that other mechanisms besides the surface-layer stratification and, therefore, other arguments besides the bulk Richardson number must be considered. The proposed technique includes a newly discovered effect of the static stability in the free atmosphere on the surface-layer scaling and accounts for the general essential difference between the roughness lengths for momentum and scalars. Besides bulk Richardson number, recommended correction functions depend oil one more stability parameter. involving the Brunt-Vaisala frequency in the free atmosphere, and on the roughness lengths.

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