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| Titel |
Implementation of a 3D-Var system for atmospheric profiling data assimilation into the RAMS model: initial results |
| VerfasserIn |
S. Federico |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 6, no. 12 ; Nr. 6, no. 12 (2013-12-17), S.3563-3576 |
| Datensatznummer |
250085137
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| Publikation (Nr.) |
 copernicus.org/amt-6-3563-2013.pdf |
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| Zusammenfassung |
This paper presents the current status of development of a three-dimensional
variational data assimilation system (3D-Var). The system can be used with different
numerical weather prediction models, but it is mainly designed to be coupled
with the Regional Atmospheric Modelling System (RAMS). Analyses are given for
the following parameters: zonal and meridional wind components, temperature,
relative humidity, and geopotential height.
Important features of the data assimilation system are the use of incremental
formulation of the cost function, and the representation of the background
error by recursive filters and the eigenmodes of the vertical component of
the background error covariance matrix. This matrix is estimated by the
National Meteorological Center (NMC) method.
The data assimilation and forecasting system is applied to the real context
of atmospheric profiling data assimilation, and in particular to the
short-term wind prediction. The analyses are produced at 20 km horizontal
resolution over central Europe and extend over the whole troposphere.
Assimilated data are vertical soundings of wind, temperature, and relative
humidity from radiosondes, and wind measurements of the European wind
profiler network.
Results show the validity of the analyses because they are closer to the
observations (lower root mean square error (RMSE)) compared to the background (higher RMSE), and the
differences of the RMSEs are in agreement with the data assimilation
settings.
To quantify the impact of improved initial conditions on the short-term
forecast, the analyses are used as initial conditions of three-hours
forecasts of the RAMS model. In particular two sets of forecasts are
produced: (a) the first uses the ECMWF analysis/forecast cycle as initial and
boundary conditions; (b) the second uses the analyses produced by the 3D-Var
as initial conditions, then it is driven by the ECMWF forecast.
The improvement is quantified by considering the horizontal components of the
wind, which are measured at asynoptic times by the European wind profiler
network. The results show that the RMSE is effectively reduced at the short
range. The results are in agreement with the set-up of the numerical
experiment. |
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