Relationship between singular vectors and transient features in the background flow

The relationships between singular vectors (SVs) and transient features in the background flow are examined through both composite techniques and case-studies. The SVs are derived using the NOGAPS forward and adjoint tangent models based on 48-hour forecasts during the NORPEX period. Composite results and case-studies both reveal significant spatial relationships between the SVs and transient features in the background flow. The SV perturbations often occur below distinctive high potential-vorticity (PV) features in the middle-to-upper troposphere. Case-studies reveal that the SVs propagate upward rapidly and have an impact on these PV features through the end of the optimization interval. In order to investigate how these small, initial perturbations have such a large impact on future development, the relationship between SVs and the quasi-geostrophic forcing is examined through the use of Q-vectors. The SV perturbations, while scaled to have a very small impact on the temperature and wind fields, have a very large impact on the mid-tropospheric Q-vectors. In contrast, the impact of the SV on the Q-vectors is negligible when added to an analysis field for which it is not optimal (e.g. the analysis field from another day). These findings establish a significant relationship between the SV perturbations and dynamically active regions in the middle troposphere, and point toward an integral link between SVs and upper-level PV precursors in synoptic development.

[1]  Brian F. Farrell,et al.  Small Error Dynamics and the Predictability of Atmospheric Flows. , 1990 .

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

[3]  H. Davies,et al.  Misforecasts of Synoptic Systems: Diagnosis via PV Retrodiction , 1997 .

[4]  Brian F. Farrell,et al.  Optimal Excitation of Baroclinic Waves , 1989 .

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

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

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

[8]  Brian F. Farrell,et al.  Optimal Excitation of Neutral Rossby Waves , 1988 .

[9]  B. Hoskins,et al.  Simple Initial Value Problems and Mechanisms for Baroclinic Growth , 2001 .

[10]  Paul J. Valdes,et al.  On the Existence of Storm-Tracks. , 1990 .

[11]  Roberto Buizza,et al.  Singular Vectors: The Effect of Spatial Scale on Linear Growth of Disturbances. , 1995 .

[12]  R. Atlas,et al.  Diagnostic evaluation of vertical motion forcing mechanisms by using Q-vector partitioning , 1998 .

[13]  Da‐Lin Zhang,et al.  Interaction of Potential Vorticity Anomalies in Extratropical Cyclogenesis. Part II: Sensitivity to Initial Perturbations , 1999 .

[14]  Timothy F. Hogan,et al.  Sensitivity Studies of the Navy's Global Forecast Model Parameterizations and Evaluation of Improvements to NOGAPS , 1993 .

[15]  Ronald M. Errico,et al.  Mesoscale Predictability and the Spectrum of Optimal Perturbations , 1995 .

[16]  Michael C. Morgan Using Piecewise Potential Vorticity Inversion to Diagnose Frontogenesis. Part I: A Partitioning of the Q Vector Applied to Diagnosing Surface Frontogenesis and Vertical Motion , 1999 .

[17]  Dennis L. Hartmann,et al.  Barotropic Instability and Optimal Perturbations of Observed Nonzonal Flows , 1992 .

[18]  B. Pouponneau,et al.  The Impact of Aircraft Data on an Atlantic Cyclone Analyzed in Terms of Sensitivities and Trajectories , 1999 .

[19]  A. Krueger,et al.  The Arctic Tropopause Fold , 1987 .

[20]  Michael C. Morgan A Potential Vorticity and Wave Activity Diagnosis of Optimal Perturbation Evolution , 2001 .

[21]  B. Farrell The initial growth of disturbances in a baroclinic flow , 1982 .

[22]  Brian F. Farrell,et al.  Modal and Non-Modal Baroclinic Waves , 1984 .

[23]  Meral Demirtas,et al.  Sensitivity of Short-Range Weather Forecasts to Local Potential Vorticity Modifications , 1999 .

[24]  B. Hoskins,et al.  The diagnosis of middle latitude synoptic development , 1980 .

[25]  M. Shapiro,et al.  A Review of the Structure and Dynamics of Upper-Level Frontal Zones , 1986 .

[26]  C. Appenzeller,et al.  Structure of stratospheric intrusions into the troposphere , 1992, Nature.

[27]  H. Davies,et al.  PV Frontogenesis and Upper-Tropospheric Fronts , 1998 .

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

[29]  Baroclinic Eady wave and fronts. Part II : Geostrophic potential vorticity dynamics in semigeostrophic space , 2000 .

[30]  Roberto Buizza,et al.  The Singular-Vector Structure of the Atmospheric Global Circulation , 1995 .

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

[32]  Franco Molteni,et al.  Predictability and finite‐time instability of the northern winter circulation , 1993 .

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

[34]  Thierry Bergot,et al.  Adaptive observations during FASTEX: A systematic survey of upstream flights , 1999 .

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

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

[37]  Brian F. Farrell,et al.  A Simple Approximate Result for the Maximum Growth Rate of Baroclinic Instabilities , 1980 .

[38]  Jean-Noël Thépaut,et al.  Combined use of sensitivity information and observations to improve meteorological forecasts: A feasibility study applied to the 'Christmas storm' case , 2000 .

[39]  Ronald Gelaro,et al.  A Predictability Study Using Geostationary Satellite Wind Observations during NORPEX , 2000 .

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

[41]  J. S. Sawyer The vertical circulation at meteorological fronts and its relation to frontogenesis , 1956, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[42]  L. Bosart,et al.  Cyclone–Anticyclone Couplets over North America. Part II: Analysis of a Major Cyclone Event over the Eastern United States , 1986 .

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

[44]  Leonard A. Smith,et al.  Accountability and internal consistency in ensemble formation , 1997 .

[45]  Jonathan E. Martin Quasigeostrophic Forcing of Ascent in the Occluded Sector of Cyclones and the Trowal Airstream , 1999 .

[46]  R. Buizza Impact of horizontal diffusion on T21, T42, and T63 singular vectors , 1998 .

[47]  Roberto Buizza,et al.  The nature of singular vector growth and structure , 2000 .

[48]  R. Buizza Localization of optimal perturbations using a projection operator , 1994 .

[49]  S. Petterssen,et al.  On the development of extratropical cyclones , 1971 .

[50]  Da‐Lin Zhang,et al.  Interaction of Potential Vorticity Anomalies in Extratropical Cyclogenesis. Part I: Static Piecewise Inversion , 1999 .

[51]  Tim N. Palmer,et al.  Decaying Singular Vectors and Their Impact on Analysis and Forecast Correction , 1998 .