Accounting for initial condition uncertainties in COSMO‐DE‐EPS

[1] This study describes the experimental setup of an atmospheric ensemble prediction system (EPS) based on a high resolution numerical weather prediction model developed at Deutscher Wetterdienst (DWD). The focus is set on uncertainties of initial conditions, and how to combine them with perturbations of the boundary conditions and model physics variations, discussed in a previous investigation. Two ensemble setups are constructed: one with model physics diversity and variations of boundaries (BP ensemble) and one which also includes perturbations of initial conditions (IBP ensemble). Experimental ensemble forecasts of precipitation with a lead time of 24 hours, for a period of 29 days in the summer of 2009, are generated. Deterministic verification shows that the inclusion of the initial perturbations does not decrease the quality of the forecast, with individual members of the IBP and BP ensembles being statistically similar. The probabilistic scores of the IBP ensemble are better than those of the BP ensemble during the first 12 hours of the forecast, and afterwards both have similar performances. Similarly, the IBP ensemble provides more spread during the first 12 hours of the forecast, decreasing to levels comparable to the BP ensemble afterwards.

[1]  G. Brier.  VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY , 1950 .

[2]  T. A. Zang,et al.  Spectral Methods for Partial Differential Equations , 1984 .

[3]  J. Schaefer.  The critical success index as an indicator of Warning skill , 1990 .

[4]  J. Dudhia.  A Nonhydrostatic Version of the Penn State–NCAR Mesoscale Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front , 1993 .

[5]  Chen Jiabin,et al.  A global spectral model and test of its performance , 1995 .

[6]  F. Molteni,et al.  The ECMWF Ensemble Prediction System: Methodology and validation , 1996 .

[7]  Jun Du,et al.  Short-Range Ensemble Forecasting of Quantitative Precipitation , 1997 .

[8]  E. Kalnay,et al.  Ensemble Forecasting at NCEP and the Breeding Method , 1997 .

[9]  A. Staniforth,et al.  The Operational CMC–MRB Global Environmental Multiscale (GEM) Model. Part II: Results , 1998 .

[10]  M. Desgagné,et al.  The Canadian MC2: A Semi-Lagrangian, Semi-Implicit Wideband Atmospheric Model Suited for Finescale Process Studies and Simulation , 1997 .

[11]  A. Staniforth,et al.  The Operational CMC–MRB Global Environmental Multiscale (GEM) Model. Part I: Design Considerations and Formulation , 1998 .

[12]  David J. Stensrud,et al.  The Correspondence Ratio in Forecast Evaluation , 2000 .

[13]  David J. Stensrud,et al.  Using Initial Condition and Model Physics Perturbations in Short-Range Ensemble Simulations of Mesoscale Convective Systems , 2000 .

[14]  Michael Buchhold,et al.  The Operational Global Icosahedral-Hexagonal Gridpoint Model GME: Description and High-Resolution Tests , 2002 .

[15]  J. Steppeler,et al.  Meso-gamma scale forecasts using the nonhydrostatic model LM , 2003 .

[16]  Simon J. Mason,et al.  On Using ``Climatology'' as a Reference Strategy in the Brier and Ranked Probability Skill Scores , 2004 .

[17]  Christoph Schär,et al.  Predictability of Precipitation in a Cloud-Resolving Model , 2004 .

[18]  David J. Stensrud,et al.  Surface Data Assimilation Using an Ensemble Kalman Filter Approach with Initial Condition and Model Physics Uncertainties , 2005 .

[19]  Ryan D. Torn,et al.  Boundary Conditions for Limited-Area Ensemble Kalman Filters , 2006 .

[20]  Fanyou Kong,et al.  Multiresolution Ensemble Forecasts of an Observed Tornadic Thunderstorm System. Part II: Storm-Scale Experiments , 2007 .

[21]  Neill E. Bowler,et al.  The MOGREPS short‐range ensemble prediction system , 2008 .

[22]  N. Roberts,et al.  Scale-Selective Verification of Rainfall Accumulations from High-Resolution Forecasts of Convective Events , 2008 .

[23]  C. Schär,et al.  Cloud‐resolving ensemble simulations of the August 2005 Alpine flood , 2008 .

[24]  C. Schraff,et al.  Assimilation of radar‐derived rain rates into the convective‐scale model COSMO‐DE at DWD , 2008 .

[25]  Jimy Dudhia,et al.  Four-Dimensional Variational Data Assimilation for WRF : Formulation and Preliminary Results , 2009 .

[26]  M. Xue,et al.  A Comparison of Precipitation Forecast Skill between Small Convection-Allowing and Large Convection-Parameterizing Ensembles , 2009 .

[27]  P. A. Clark,et al.  Perturbation growth at the convective scale for CSIP IOP18 , 2010 .

[28]  Yong Wang,et al.  A strategy for perturbing surface initial conditions in LAMEPS , 2010 .

[29]  S. J. Weiss,et al.  Toward Improved Convection-Allowing Ensembles: Model Physics Sensitivities and Optimizing Probabilistic Guidance with Small Ensemble Membership , 2010 .

[30]  Felix Ament,et al.  Assessing the Benefits of Convection-Permitting Models by Neighborhood Verification: Examples from MAP D-PHASE , 2010 .

[31]  Z. Pu,et al.  Beating the Uncertainties: Ensemble Forecasting and Ensemble-Based Data Assimilation in Modern Numerical Weather Prediction , 2010 .

[32]  C. Keil,et al.  Regime-dependent forecast uncertainty of convective precipitation , 2011 .

[33]  Andreas Rhodin,et al.  LETKF for the nonhydrostatic regional model COSMO-DE , 2011 .

[34]  Tiziana Paccagnella,et al.  Seven years of activity in the field of mesoscale ensemble forecasting by the COSMO-LEPS system: main achievements and open challenges , 2011 .

[35]  Véronique Ducrocq,et al.  Cloud-Resolving Ensemble Simulations of Mediterranean Heavy Precipitating Events: Uncertainty on Initial Conditions and Lateral Boundary Conditions , 2011 .

[36]  Z. B. Bouallègue,et al.  Uncertainties in COSMO-DE precipitation forecasts introduced by model perturbations and variation of lateral boundaries , 2011 .

[37]  Dusanka Zupanski,et al.  A Prototype WRF-Based Ensemble Data Assimilation System for Dynamically Downscaling Satellite Precipitation Observations , 2011 .

[38]  M. Baldauf,et al.  Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities , 2011 .