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Experiments with three-dimensional radar reflectivity data assimilation into the COAMPS model

100%
Jakubiak B., Szturc J., Osrodka K., Jurczyk A.
Meteorology Hydrology and Water Management. Research and Operational Applications
|
2014
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tom 02
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nr 1
High temporal and spatial resolution of radar measurements enables to continuously observe dynamically evolving meteorological phenomena. Three-dimensional (3D) weather radar reflectivity data assimilated into the numerical weather prediction model has the potential to improve initial description of the atmospheric model state. The paper is concentrated on the development of radar reflectivity assimilation technique into COAMPS mesoscale model using an Ensemble Kalman Filter (EnKF) type assimilation schemes available in Data Assimilation Research Testbed (DART) programming environment. Before weather radar data enter into the assimilation system, the measurement errors are eliminated through quality control procedures. At first artifacts associated with non-meteorological errors are removed using the algorithms based on analysis of reflectivity field pattern. Then procedures for correction of the reflectivity data are employed, especially due to radar beam blockage and attenuation in rain. Each of the correction algorithms is connected with generation of the data quality characteristic expressed quantitatively by so called quality index (QI). In order to avoid transformation of data uncertainty into assimilation scheme only the radar gates successfully verified by means of the quality algorithms were employed in the assimilation. The proposed methodology has been applied to simulate selected intense precipitation events in Poland in May and August 2010.
2

The choice of optimal lag for Kriging interpolation of NWP model forecast

84%
Katsalova L. M., Shpyg V. M.
Meteorology Hydrology and Water Management. Research and Operational Applications
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2016
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tom 04
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nr 2
In this paper a Kriging method is reviewed and a way of its application in numerical weather prediction is proposed. The basic principles of the Kriging are shown; the main advantage is its accuracy, but at the same time a disadvantage is its large computational complexity. The construction stage of the variographical model is highlighted, as it is the most important stage and has a significant impact on the accuracy of interpolation. The algorithm for the construction of the variographical model is described. Special attention is paid to averaging an experimental variogram by introducing a special interval, called “lag”. Precisely this issue, according to the authors has a significant impact on the effectiveness of the practical application of Kriging for the interpolation of meteorological parameters. The advantages of averaging an experimental variogram by the administration of lag are presented, and the error that arises in this case is estimated. A theoretical study for the determination of the optimal lag was conducted. The lag proposed for the determination is guided by the criteria of accuracy and the economy of computer time. The twocriteria problem is solved, and the formula, which makes it possible to determine the optimal lag on these criteria, is received. An example shown here is the application of the obtained results for solving the applied task associated with meteorological parameters forecast by the COS MO model.
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A comparison of ASCAT wind measurements and the HIRLAM model over the Baltic Sea

67%
Sluzenikina J., Mannik A.
Oceanologia
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2011
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tom 53
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nr (1-TI)
This paper presents a comparison of the wind data measured by the ASCAT polar-orbiting satellite scatterometer and winds forecast by the numerical weather prediction model HIRLAM in the Baltic Sea region during the stormy season in 2009. Two different resolution models were used in the comparison. Mutual quality and uncertainty characteristics of the measurements and predictions are determined. The results of the study show that the ASCAT wind data are well correlated with the HIRLAM predicted winds, which raises the credibility of both data sources in operational and hindcasting applications over the Baltic Sea. A case of phase error in a HIRLAM forecast of cyclonic activity over the Baltic Sea is discussed.
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