Applications of the Adjoint Technique to Short-Range Ensemble Forecasting of Mesoscale Convective Systems

The feasibility of applying a mesoscale adjoint model to the creation of an ensemble for short-range simulations of mesoscale convective systems (MCSs) is explored. Because past studies show that forecasters routinely improve upon numerical guidance and can identify mesoscale-sized areas of forecast concern with a high level of skill, it is clear that forecasters have insights into the daily weather forecast problems that exceed what can be provided by a numerical weather prediction model. Using an adjoint model, one could develop a system in which a forecaster identifies the area of forecast concern and then designs a set of rapidly produced sensitivity experiments that evaluate the influence of key atmospheric parameters on the model forecast. The output from these sensitivity experiments is then used to create ensemble members for a short-range operational ensemble forecast, which is specifically designed to investigate the forecast concern of the day. This adjoint ensemble approach is tested for the 48-h period beginning 1200 UTC 27 May 1985, in which a long-lived MCS developed underneath a large-scale ridge. A mesoscale adjoint model is used to define the alterations to the model initial conditions necessary to evaluate the influences of key mesoscale structures, which the authors believe have a large influence on later convective development in the model. Results indicate that the adjoint technique is effective in creating the proper directional response in the model simulation. When compared to initial condition and model physics ensembles of this event, the adjoint ensemble produces more variance than the initial condition ensemble and almost as much variance as the model physics ensemble. However, the values of the equitable threat score and the ranked probability score are better for the adjoint ensemble between 6 and 24 h than for either of the other two ensembles. These results suggest that further exploration of ensembles that incorporate the experience and expertise possessed by forecasters is warranted.

[1]  Ronald M. Errico,et al.  An Adjoint Examination of a Nudging Method for Data Assimilation , 1997 .

[2]  James S. Goerss,et al.  Assimilation of Synthetic Tropical Cyclone Observations into the Navy Operational Global Atmospheric Prediction System , 1994 .

[3]  Nelson L. Seaman,et al.  A Simple Scheme for Objective Analysis in Curved Flow , 1985 .

[4]  D. Stensrud,et al.  Mesoscale Convective Systems in Weakly Forced Large-Scale Environments. Part III: Numerical Simulations and Implications for Operational Forecasting , 1994 .

[5]  D. Deaven,et al.  The Regional Analysis System for the Operational “Early” Eta Model: Original 80-km Configuration and Recent Changes , 1995 .

[6]  Charles A. Doswell,et al.  New technology and numerical weather prediction — a wasted opportunity? , 1993 .

[7]  Ronald M. Errico,et al.  Sensitivity Analysis Using an Adjoint of the PSU-NCAR Mesoseale Model , 1992 .

[8]  T. Palmer,et al.  Singular Vectors, Metrics, and Adaptive Observations. , 1998 .

[9]  P. Courtier,et al.  Assimilation of Simulated Wind Lidar Data with a Kalman Filter , 1993 .

[10]  J. Eom.  Analysis of the Internal Gravity Wave Occurrence of 19 April 1970 in the Midwest , 1975 .

[11]  Ying-Hwa Kuo,et al.  Variational Assimilation of Precipitable Water Using a Nonhydrostatic Mesoscale Adjoint Model. Part I: Moisture Retrieval and Sensitivity Experiments , 1996 .

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

[13]  Tomislava Vukicevic,et al.  Nonlinear and Linear Evolution of Initial Forecast Errors , 1991 .

[14]  K. Tung,et al.  Banded Convective Activity and Ducted Gravity Waves , 1976 .

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

[16]  Roberto Buizza,et al.  Targeting Observations Using Singular Vectors , 1999 .

[17]  R. J. Reed,et al.  Numerical Simulation of the Large-Amplitude Mesoscale Gravity-Wave Event of 15 December 1987 in the Central United States , 1993 .

[18]  J. Barkmeijer,et al.  Singular vectors and estimates of the analysis‐error covariance metric , 1998 .

[19]  R. Errico.  What is an adjoint model , 1997 .

[20]  E. J. Harrison,et al.  An evaluation of the real-time tropical cyclone forecast skill of the Navy Operational Global Atmospheric Prediction System in the western North Pacific , 1993 .

[21]  L. Uccellini,et al.  A Case Study of Gravity Waves–Convective Storms Interaction: 9 May 1979 , 1983 .

[22]  Da‐Lin Zhang,et al.  A High-Resolution Model of the Planetary Boundary Layer—Sensitivity Tests and Comparisons with SESAME-79 Data , 1982 .

[23]  E. Lorenz.  A study of the predictability of a 28-variable atmospheric model , 1965 .

[24]  Ronald M. Errico,et al.  Singular-Vector Perturbation Growth in a Primitive Equation Model with Moist Physics , 1999 .

[25]  Ying-Hwa Kuo,et al.  Assimilation of Atmospheric Radio Refractivity Using a Nonhydrostatic Adjoint Model , 1995 .

[26]  L. L. Means,et al.  A Synoptic Study on the Formation of Squall Lines in the North Central United States , 1955 .

[27]  Walter H. Hoecker,et al.  THREE SOUTHERLY LOW-LEVEL JET SYSTEMS DELINEATED BY THE WEATHER BUREAU SPECIAL PIBAL NETWORK OF 1961 , 1963 .

[28]  François Bouttier,et al.  The dynamics of error covariances in a barotropic model , 1993 .

[29]  K. Emanuel,et al.  Report from a Workshop on Cumulus Parameterization Key Biscayne, Florida, 3–5 May 1991 , 1992 .

[30]  Ronald M. Errico,et al.  Evaluation of physical processes in an idealized extratropical cyclone using adjoint sensitivity , 1995 .

[31]  F. Baer,et al.  On Complete Filtering of Gravity Modes Through Nonlinear Initialization , 1977 .

[32]  Charles A. Doswell,et al.  The Distinction between Large-Scale and Mesoscale Contribution to Severe Convection: A Case Study Example , 1987 .

[33]  Rudolph W. Preisendorfer,et al.  Numerical Model-Reality Intercomparison Tests Using Small-Sample Statistics , 1983 .

[34]  J. Dudhia,et al.  Nonhydrostatic, mesobeta-scale, real-data simulations with the Penn State University/National Center for Atmospheric Research mesoscale model , 1992 .

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

[36]  N. Seaman,et al.  A Comparison Study of Convective Parameterization Schemes in a Mesoscale Model , 1997 .

[37]  R. Maddox,et al.  Mesoscale and Synoptic Scale Interactions Leading to Intense Convection: The Case of 7 June 1982 , 1988 .

[38]  D. Baumhefner,et al.  Predictability Experiments Using a High-Resolution Limited-Area Model , 1987 .

[39]  Philippe Courtier,et al.  An application of adjoint models to sensitivity analysis , 1992 .

[40]  R. Buizza.  Potential Forecast Skill of Ensemble Prediction and Spread and Skill Distributions of the ECMWF Ensemble Prediction System , 1997 .

[41]  A. Blackadar,et al.  High resolution models of the planetary boundary layer , 1979 .

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

[43]  P. L. Houtekamer,et al.  Methods for Ensemble Prediction , 1995 .

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

[45]  Tim N. Palmer,et al.  Examination of targeting methods in a simplified setting , 2000 .

[46]  X. Zou,et al.  Rainfall Assimilation through an Optimal Control of Initial and Boundary Conditions in a Limited-Area Mesoscale Model , 1996 .

[47]  Roberto Buizza,et al.  Forecast skill of the ECMWF model using targeted observations during FASTEX , 1999 .

[48]  Theodore W. Funk,et al.  Forecasting Techniques Utilized by the Forecast Branch of the National Meteorological Center During a Major Convective Rainfall Event , 1991 .

[49]  X. Zou,et al.  Introduction to Adjoint Techniques and the MM5 Adjoint Modeling System. , 1997 .

[50]  Louis W. Uccelini.  A Case Study of Apparent Gravity Wave Initiation of Severe Convective Storms , 1975 .

[51]  J. Dudhia.  Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model , 1989 .

[52]  Rolf H. Langland,et al.  As assessment of the singular‐vector approach to targeted observing using the FASTEX dataset , 1999 .

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

[54]  Philippe Courtier,et al.  Sensitivity of forecast errors to initial conditions , 1996 .

[55]  Roger Daley.  The application of non‐linear normal mode initialization to an operational forecast model , 1979 .

[56]  Ronald M. Errico,et al.  Examination of the accuracy of a tangent linear model , 1993 .

[57]  Alan K. Betts,et al.  The Betts-Miller Scheme , 1993 .

[58]  K. Mitchell,et al.  Importance of Cold Pools to NCEP Mesoscale Eta Model Forecasts , 1999 .

[59]  Roberto Buizza,et al.  Sensitivity Analysis of Forecast Errors and the Construction of Optimal Perturbations Using Singular Vectors , 1998 .

[60]  G. Grell,et al.  A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5) , 1994 .

[61]  Ronald Gelaro,et al.  Targeted observations in FASTEX: Adjoint‐based targeting procedures and data impact experiments in IOP17 and IOP18 , 1999 .

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

[63]  J. Barkmeijer.  Local error growth in a barotropic model , 1992 .

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

[65]  J. M. Fritsch,et al.  Preliminary Numerical Tests of the Modification of Mesoscale Convective Systems , 1981 .

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

[67]  P. L. Houtekamer,et al.  Using ensemble forecasts for model validation , 1997 .

[68]  Jeffrey L. Anderson,et al.  The Impact of Dynamical Constraints on the Selection of Initial Conditions for Ensemble Predictions: Low-Order Perfect Model Results , 1997 .

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

[70]  Ronald M. Errico,et al.  Interpretations of the total energy and rotational energy norms applied to determination of singular vectors , 2000 .

[71]  Ying-Hwa Kuo,et al.  The impact of Global Positioning System data on the prediction of an extratropical cyclone: an observing system simulation experiment , 1997 .

[72]  J. Fritsch,et al.  Forcing Mechanisms and Other Characteristics of Significant Summertime Precipitation , 1988 .