A Performance Comparison between Multiphysics and Stochastic Approaches within a North American RAP Ensemble

AbstractA stochastic parameter perturbation (SPP) scheme consisting of spatially and temporally varying perturbations of uncertain parameters in the Grell–Freitas convective scheme and the Mellor–Yamada–Nakanishi–Niino planetary boundary scheme was developed within the Rapid Refresh ensemble system based on the Weather Research and Forecasting Model. Alone the stochastic parameter perturbations generate insufficient spread to be an alternative to the operational configuration that utilizes combinations of multiple parameterization schemes. However, when combined with other stochastic parameterization schemes, such as the stochastic kinetic energy backscatter (SKEB) scheme or the stochastic perturbation of physics tendencies (SPPT) scheme, the stochastic ensemble system has comparable forecast performance. An additional analysis quantifies the added value of combining SPP and SPPT over an ensemble that uses SPPT only, which is generally beneficial, especially for surface variables. The ensemble combining a...

[1]  Charles R. Sampson,et al.  Impact of Resolution and Design on the U.S. Navy Global Ensemble Performance in the Tropics , 2011 .

[2]  Thomas M. Hamill,et al.  Hypothesis Tests for Evaluating Numerical Precipitation Forecasts , 1999 .

[3]  Brian A. Colle,et al.  Verification of Extratropical Cyclones within the NCEP Operational Models. Part II: The Short-Range Ensemble Forecast System , 2009 .

[4]  Laure Raynaud,et al.  Impact of Stochastic Physics in a Convection-Permitting Ensemble , 2012 .

[5]  R. Buizza,et al.  A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems , 2005 .

[6]  H. Niino,et al.  An Improved Mellor–Yamada Level-3 Model with Condensation Physics: Its Design and Verification , 2004 .

[7]  D. Thomson,et al.  Stochastic backscatter in large-eddy simulations of boundary layers , 1992, Journal of Fluid Mechanics.

[8]  C. Snyder,et al.  Linear and non-linear response to parameter variations in a mesoscale model , 2009 .

[9]  P. Lacarrére,et al.  Parameterization of Orography-Induced Turbulence in a Mesobeta--Scale Model , 1989 .

[10]  Francisco J. Doblas-Reyes,et al.  A Debiased Ranked Probability Skill Score to Evaluate Probabilistic Ensemble Forecasts with Small Ensemble Sizes , 2005 .

[11]  W. Briggs Statistical Methods in the Atmospheric Sciences , 2007 .

[12]  P. Courtier,et al.  Correlation modelling on the sphere using a generalized diffusion equation , 2001 .

[13]  G. Grell,et al.  A generalized approach to parameterizing convection combining ensemble and data assimilation techniques , 2002 .

[14]  G. Shutts A kinetic energy backscatter algorithm for use in ensemble prediction systems , 2005 .

[15]  H. Niino,et al.  An Improved Mellor–Yamada Level-3 Model: Its Numerical Stability and Application to a Regional Prediction of Advection Fog , 2006 .

[16]  Chris Snyder,et al.  The U.S. Air ForceWeather Agency’s mesoscale ensemble: scientific description and performance results , 2011 .

[17]  Thomas Jung,et al.  Systematic Model Error: The Impact of Increased Horizontal Resolution versus Improved Stochastic and Deterministic Parameterizations , 2012 .

[18]  Irene M. Moroz,et al.  Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization , 2015 .

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

[20]  T. Hamill Interpretation of Rank Histograms for Verifying Ensemble Forecasts , 2001 .

[21]  Neill E. Bowler,et al.  The local ETKF and SKEB: Upgrades to the MOGREPS short‐range ensemble prediction system , 2009 .

[22]  Harold E. Brooks,et al.  Using Ensembles for Short-Range Forecasting , 1999 .

[23]  Z. Janjic The Step-Mountain Eta Coordinate Model: Further Developments of the Convection, Viscous Sublayer, and Turbulence Closure Schemes , 1994 .

[24]  Chris Snyder,et al.  Increasing the Skill of Probabilistic Forecasts: Understanding Performance Improvements from Model-Error Representations , 2015 .

[25]  Chris Snyder,et al.  Model Uncertainty in a Mesoscale Ensemble Prediction System: Stochastic versus Multiphysics Representations , 2011 .

[26]  Martin Leutbecher,et al.  A Spectral Stochastic Kinetic Energy Backscatter Scheme and Its Impact on Flow-Dependent Predictability in the ECMWF Ensemble Prediction System , 2009 .

[27]  J. Dudhia,et al.  A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes , 2006 .

[28]  G. Grell,et al.  A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh , 2016 .

[29]  H. Hersbach Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems , 2000 .

[30]  T. Palmer A nonlinear dynamical perspective on model error: A proposal for non‐local stochastic‐dynamic parametrization in weather and climate prediction models , 2001 .

[31]  M. Webb,et al.  Quantification of modelling uncertainties in a large ensemble of climate change simulations , 2004, Nature.

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

[33]  H. Pan,et al.  Revision of Convection and Vertical Diffusion Schemes in the NCEP Global Forecast System , 2011 .

[34]  Eugenia Kalnay,et al.  Ensemble Forecasting at NMC: The Generation of Perturbations , 1993 .

[35]  S. Freitas,et al.  A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling , 2013 .

[36]  Yuejian Zhu,et al.  Improvement of Statistical Postprocessing Using GEFS Reforecast Information , 2015 .

[37]  Stanley G. Benjamin,et al.  Modifications to the Rapid Update Cycle Land Surface Model (RUC LSM) Available in the Weather Research and Forecasting (WRF) Model , 2016 .

[38]  Jeffrey L. Anderson,et al.  Representing forecast error in a convection-permitting ensemble system , 2014 .

[39]  Clifford F. Mass,et al.  Aspects of Effective Mesoscale, Short-Range Ensemble Forecasting , 2005 .

[40]  Matthew D. Collins,et al.  Improved stochastic physics schemes for global weather and climate models , 2016 .

[41]  Retracted and replaced:Impact of observational error on the validation of ensemble prediction systems , 2008 .

[42]  A. Betts A new convective adjustment scheme. Part I: Observational and theoretical basis , 1986 .

[43]  T. Palmer,et al.  Stochastic representation of model uncertainties in the ECMWF ensemble prediction system , 2007 .

[44]  O. Talagrand,et al.  Evaluation of probabilistic prediction systems for a scalar variable , 2005 .

[45]  Reto Knutti,et al.  Climate model genealogy: Generation CMIP5 and how we got there , 2013 .