Articles | Volume 12, issue 1
https://doi.org/10.5194/asr-12-207-2015
https://doi.org/10.5194/asr-12-207-2015
27 Oct 2015
 | 27 Oct 2015

Methodologies to characterize uncertainties in regional reanalyses

M. Borsche, A. K. Kaiser-Weiss, P. Undén, and F. Kaspar

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Cited articles

Berre, L.: Estimation of Synoptic and Mesoscale Forecast Error Covariances in a Limited-Area Model, Mon. Weather Rev., 128, 644–667, https://doi.org/10.1175/1520-0493(2000)128<0644:EOSAMF>2.0.CO;2, 2000.
Bollmeyer, C., Keller, J. D., Ohlwein, C., Wahl, S., Crewell, S., Friederichs, P., Hense, A., Keune, J., Kneifel, S., Pscheidt, I., Redl, S., and Steinke, S.: Towards a high-resolution regional reanalysis for the European CORDEX domain, Q. J. Roy. Meteorol. Soc., 141, 1–15, https://doi.org/10.1002/qj.2486, 2015.
Brier, G. W.: Verification of forecasts expressed in terms of probability, Mon. Weather Rev., 78, 1–3 , 1950.
Brunet, M., Jones, P. D., Jourdain, S., Efthymiadis, D., Kerrouche, M., and Boroneant, C.: Data sources for rescuing the rich heritage of Mediterranean historical surface climate data, Geosci. Data J., 1, 61–73, https://doi.org/10.1002/gdj3.4, 2013.
Bubnova, R., Hello, G., Benard, P., and Geleyn, J.-F.: Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following in the framework of the ARPEGE/ALADIN NWP system, Mon. Weather Rev., 123, 515–535, 1995.
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Within the European Union’s seventh Framework Programme project Uncertainties in Ensembles of Regional Re-Analyses (UERRA), ensembles of RRAs covering the European area are produced and their uncertainties are quantified. In this study, we discuss different methods for quantifying the uncertainty of RRAs in order to answer the question to which extent the smaller scale information (or resulting statistics) provided by the RRAs can be relied on.