Extended Abstract

skill of the best respective component and even improves them in the time around thecross-over point. One promising possiblity to reduce variabiltity in the results and likewiseimprove their reliability would be the consideration of synoptic regimes in the derivation ofthe calibration and weighting functions (Done et al. 2006). The performance of the modelcould be improved through the usage of a time-lagged ensemble including dataassimilation.Fig.4: Development of Brier Score, CSRR, and area under ROC curve with lead time for blendedprobabilities from 8 to 16 August 2007.ReferencesDone, J., Craig, G.C., Gray, S., Clark, P. and Gray, M.: 2006, Mesoscale simulations oforganized convection: Importance of convective equilibrium, Quart. J. Roy.Meteor. Soc. 132, 737-756.Gebhardt, C., Theis, S., Paulat, M. and Bouallegue, Z. B.: 2010, Uncertainties inCOSMO-DE precipitation forecasts introduced by model perturbations andvariation of lateral boundaries, submitted to Atmos. Res. .Germann, U. and Zawadzki, I.: 2004, Scale Dependence of the Predictability of Precipitationfrom Continental Radar Images. Part II: Probability Forecasts, J. Appl. Met.43, 74-89.Kober, K. and Tafferner, A.: 2009, Tracking and nowcasting of convective cells using remotesensing data from radar and satellite, Meteor. Z. 1, 75-84.Kober, K., Craig, G.C., Keil, C. and Dörnbrack, A.: Blending a probabilistic nowcastingmethod with a high resolution ensemble for convective precipitation forecasts,submitted to Quart. J. Roy. Meteor. Soc..Theis, S., Hense, A. and Damrath, U.: 2005, Probabilistic precipitation forecasts from adeterministic model: a pragmatic approach, Meteorol. Appl. 12, 257-268.-306-