Subjective Verification of Numerical Models as a Component of a Broader Interaction between Research and Operations

Abstract Systematic subjective verification of precipitation forecasts from two numerical models is presented and discussed. The subjective verification effort was carried out as part of the 2001 Spring Program, a seven-week collaborative experiment conducted at the NOAA/National Severe Storms Laboratory (NSSL) and the NWS/Storm Prediction Center, with participation from the NCEP/Environmental Modeling Center, the NOAA/Forecast Systems Laboratory, the Norman, Oklahoma, National Weather Service Forecast Office, and Iowa State University. This paper focuses on a comparison of the operational Eta Model and an experimental version of this model run at NSSL; results are limited to precipitation forecasts, although other models and model output fields were verified and evaluated during the program. By comparing forecaster confidence in model solutions to next-day assessments of model performance, this study yields unique information about the utility of models for human forecasters. It is shown that, when avera...

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

[2]  Charles A. Doswell,et al.  Examination of Derecho Environments Using Proximity Soundings , 2001 .

[3]  Neville Nicholls,et al.  commentary and analysis: The Insignificance of Significance Testing , 2001 .

[4]  Michael E. Baldwin,et al.  Properties of the Convection Scheme in NCEP's Eta Model that Affect Forecast Sounding Interpretation , 2002 .

[5]  Harold E. Brooks,et al.  Comparison between Observed Convective Cloud-Base Heights and Lifting Condensation Level for Two Different Lifted Parcels , 2002 .

[6]  S. Lakshmivarahan,et al.  8 . 3 VERIFICATION OF MESOSCALE FEATURES IN NWP MODELS , 2001 .

[7]  F. Mesinger.  Improvements in Quantitative Precipitation Forecasts with the Eta Regional Model at the National Centers for Environmental Prediction: The 48-km Upgrade , 1996 .

[8]  Michael E. Baldwin,et al.  Parameterized Updraft Mass Flux as a Predictor of Convective Intensity , 2003 .

[9]  Michael P. Kay,et al.  15.2 COMBINING OBJECTIVE AND SUBJECTIVE INFORMATION TO IMPROVE FORECAST EVALUATION , 2002 .

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

[11]  R. Johns,et al.  Severe Local Storms Forecasting , 1992 .

[12]  Stephen M. Goss,et al.  The melting effect as a factor in precipitation-type forecasting , 2000 .

[13]  Daniel S. Wilks,et al.  Statistical Methods in the Atmospheric Sciences: An Introduction , 1995 .

[14]  Jerome P. Charba,et al.  Comparative Verification of Recent Quantitative Precipitation Forecasts in the National Weather Service: A Simple Approach for Scoring Forecast Accuracy , 2003 .

[15]  S. J. Weiss,et al.  Mesoscale Model Ensemble Forecasts of the 3 May 1999 Tornado Outbreak , 2000 .

[16]  John S. Kain,et al.  Convective parameterization for mesoscale models : The Kain-Fritsch Scheme , 1993 .

[17]  T. Black.  The new NMC mesoscale Eta Model: description and forecast examples , 1994 .

[18]  S. Lakshmivarahan,et al.  7B.3 DEVELOPMENT OF AN “EVENTS-ORIENTED” APPROACH TO FORECAST VERIFICATION , 2001 .

[19]  Harold E. Brooks,et al.  COLLABORATION BETWEEN FORECASTERS AND RESEARCH SCIENTISTS AT THE NSSL AND SPC , 2003 .

[20]  Charles A. Doswell,et al.  Forecasting and Verifying in a Field Research Project: DOPLIGHT '87 , 1989 .

[21]  3.2 DETERMINING THE RESOLVED SPATIAL SCALES OF ETA MODEL PRECIPITATION FORECASTS , 2001 .

[22]  Alan R. Moller,et al.  The Operational Recognition of Supercell Thunderstorm Environments and Storm Structures , 1994 .

[23]  A. H. Murphy,et al.  What Is a Good Forecast? An Essay on the Nature of Goodness in Weather Forecasting , 1993 .