Abstract
COSMO model is a non-hydrostatic limited-area model mainly used by National Meteorological Services for operational applications. In the present study operational forecasts over Switzerland for the entire year 2013 have been compared with forecasts in which no observational data are used for the assimilation. The numerical weather prediction model COSMO is applied at 2.2 horizontal resolution and variables used for everyday operational forecast, such as 2 m temperature, total precipitation and total cloud coverage are evaluated against observations in both cases. A small improvement is evident in 2 m temperature while for precipitation the use of observational data slightly affects POD during dry seasons.
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References
Baldauf M, Seifert A, Förstner J, Majewski D, Raschendorfer M, Reinhardt T (2011) Operational convective-scale numerical weather prediction with the COSMO model: description and sensitivities. Mon Weather Rev 139:3887–3905
Barker DM, Huang W, Guo YR, Bourgeois AJ, Xiao QN (2004) A three-dimensional variational data assimilation system for MM5: implementation and initial results. Mon Weather Rev 132:897–914
Courtier P, Thépaut JN, Hollingsworth A (1994) A strategy for operational implementation of 4D-Var, using an incremental approach. Q J R Meteorol Soc 120:519, 1367–1387, Part B
Doms G, Foerstner J, Heise E, Herzog HJ, Mironov D, Raschendorfer M, Reinhardt T, Ritter B, Schrodin R, Schultz JP, Vogel G (2011) A description of the nonhydrostatic regional COSMO model. Part II: physical parameterization. http://www.cosmo-model.org
Kaufmann P (2005) Verification of aLMo with SYNOP and GPS data over Europe. COSMO Newsl 5:113–117
Lopez P (2013) Experimental 4D-Var assimilation of SYNOP rain gauge data at ECMWF. Mon Weather Rev 141:1527–1544
Schraff C (1996) Data assimilation and mesoscale weather prediction: a study with a forecast model for the Alpine region. Publication 56, Swiss Meteorological Institute, Zurich
Schraff C (1997) Mesoscale data assimilation and prediction of low stratus in the Alpine region. Meteorol Atmos Phys 64:21–50
Stephan K, Klink S, Schraff C (2008) Assimilation of radar-derived rain rates into the convective-scale model COSMO-DE at DWD. Q J R Meteorol Soc 134:1315–1326
Wilks DS (1995) Statistical methods in the atmospheric sciences. Academic Press, 467 pp
Acknowledgments
The authors would like to acknowledge CSCS for providing computer resources. The present study is performed within the framework of CALMO project of COSMO.
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Voudouri, A., Avgoustoglou, E., Kaufmann, P. (2017). Impacts of Observational Data Assimilation on Operational Forecasts. In: Karacostas, T., Bais, A., Nastos, P. (eds) Perspectives on Atmospheric Sciences. Springer Atmospheric Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-35095-0_21
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DOI: https://doi.org/10.1007/978-3-319-35095-0_21
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