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UNIVERSITY OF BUCHAREST
FACULTY OF PHYSICS Guest
2024-11-22 2:31 |
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Conference: Bucharest University Faculty of Physics 2015 Meeting
Section: Atmosphere and Earth Science; Environment Protection
Title:
The impact of assimilation satellite observations in the ALARO numerical weather forecast
Authors:
Mirela PIETRISI(1,2), Simona TASCU(2)
Affiliation:
1) University of Bucharest, Faculty of Physics, P.O.BOX MG-11, Magurele, Romania
2) National Meteorological Administration, Bucharest, Romania
E-mail
mirela.niculae@meteoromania.ro
Keywords:
severe weather, variational data assimilation, satellite observations
Abstract:
Severe weather phenomena forecast require the best possible description of the model initial state. In such situations, the errors from the model initial state significantly affect the numerical weather prediction performance. One way to improve the numerical forecasts is the observations (as many as possible) assimilation. For this study, a variational data assimilation technique, which is the most often used for limited area models, allowing the complex observations to be assimilate, is applied (Courtier, 1997). Basically, a functional accounting for the departure between the model and observation is minimized throughout an iterative method.It is recognized that high-density observational data, particularly satellite and radar data can lead to a substantial improvement in numerical forecast having an important role in reducing the uncertainties from the initial conditions of the numerical model. The observations from polar-orbiting and geostationary satellites provide essential information on the vertical structure of the atmosphere (temperature, water vapor content of the atmosphere).It is analysed the important role that satellite observations play in data assimilation. For a chosen case, 11 September 2013, the satellite radiances from ATOVS/AMSU-A (Advanced Microwave Sounding Unit-A), ATOVS/AMSU-B (Advanced Microwave Sounding Unit-B) sounding and SEVIRI (Spinning Enhanced Visible and Infrared Imager) imager were assimilated and the impact of their assimilation was consequently analysed.
References:
Courtier, P., 1997: Variational methods, J. Meteorol. Soc. Jpn., 75, 211–218.
Acknowledgement:
The model specific data base used for data assimilation is a commonly exploit in operation by the members of RC-LACE (Regional Cooperation for Limited Area modelling in Central Europe) Consortium. The efforts of the Hungarian colleagues for maintain it operationally is acknowledged.
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