Evaluation of physical processes in an idealized extratropical cyclone using adjoint sensitivity

An adjoint model is used to examine the sensitivity of an idealized dry extratropical cyclogenesis simulation to perturbations of predictive variables and parameters during the cyclone life cycle. the adjoint sensitivity indicates how small perturbations of model variables or parameters anywhere in the model domain can influence cyclone central pressure. Largest sensitivity for both temperature and wind perturbations is located between 600 and 900 hPa in the baroclinic zone above the developing cyclone. Perturbations of a given size have more influence on cyclone intensity when located in high-sensitivity regions (the middle and lower troposphere in this simulation). the effects of physical processes can be interpreted with adjoint sensitivity by considering perturbations that are proportional to temperature and wind tendencies in the basic state (nonlinear forecast). In the early phase of the cyclone life cycle, temperature advection near the steering level in the lower troposphere (about 800 hPa) is strongly cyclogenetic and resembles a Charney mode of baroclinic instability. During the phase of most rapid deepening, temperature advection in the lower troposphere remains important, while interpretation of sensitivity to wind perturbations suggests that increased vorticity in the middle and upper troposphere above the surface low-pressure centre may also be significant for cyclone intensification. Adjoint techniques can provide insight into spatial and temporal sensitivity not easily obtained from other methods. Higher sea surface temperature (SST) has a cyclogenetic effect mainly in a localized region corresponding to the cyclone warm sector. Outside the areas of high sensitivity, small perturbations of SST have very little effect on central pressure of the forecast cyclone. When strong upward sensible-heat flux, Fs, exists, it can have a cyclogenetic (preconditioning) influence early in the cyclone life cycle, although downward Fs in the cyclone warm sector is anticyclogenetic during the phase of most rapid deepening. the sensitivity indicates that Fs can be cyclogenetic in one location and anticyclogenetic at the same time in another location, so that Fs effects on cyclone intensity are partially self-cancelling. Surface momentum stress is anticyclogenetic, with sensitivity highly localized in the cyclone warm sector.

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

[2]  L. Uccellini Processes Contributing to the Rapid Development of Extratropical Cyclones , 1990 .

[3]  Y. Kuo,et al.  Description of the Penn State/NCAR Mesoscale Model: Version 4 (MM4) , 1987 .

[4]  M. C. Hall,et al.  Application of adjoint sensitivity theory to an atmospheric general circulation model , 1986 .

[5]  O. Talagrand,et al.  Short-range evolution of small perturbations in a barotropic model , 1988 .

[6]  R. Anthes,et al.  A Numerical Investigation of Low-Level Processes in Rapid Cyclogenesis , 1987 .

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

[8]  Roberto Buizza,et al.  Sensitivity of optimal unstable structures , 1994 .

[9]  M. Shapiro,et al.  The Life Cycle of an Extratropical Marine Cyclone. Part I: Frontal-Cyclone Evolution and Thermodynamic Air-Sea Interaction , 1993 .

[10]  J. Bane,et al.  Wintertime air‐sea interaction processes across the Gulf Stream , 1989 .

[11]  Paul Roebber,et al.  The Role of Antecedent Surface Vorticity Development as a Conditioning Process in Explosive Cyclone Intensification , 1992 .

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

[13]  B. Hoskins,et al.  Baroclinic Instability of the Zonally Averaged Flow with Boundary Layer Damping , 1988 .

[14]  M. Shapiro,et al.  Fronts, Jet Streams and the Tropopause , 1990 .

[15]  Sensitivity and uncertainty analysis of a short‐term sea ice motion model , 1990 .

[16]  R. V. Madala Efficient Time Integration Schemes for Atmosphere and Ocean Models , 1981 .

[17]  F. Sanders,et al.  Synoptic-Dynamic Climatology of the “Bomb” , 1980 .

[18]  B. Hoskins,et al.  The Life Cycles of Some Nonlinear Baroclinic Waves , 1978 .

[19]  A. Hollingsworth,et al.  The response of numerical weather prediction systems to fgge level iib data. Part I: Analyses , 1985 .

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

[21]  Philippe Courtier,et al.  Four‐Dimensional Assimilation In the Presence of Baroclinic Instability , 1992 .

[22]  C. Mechoso,et al.  Influence of Surface Drag on the Evolution of Fronts , 1993 .

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

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

[25]  R. Dole,et al.  The Dynamics of Large-Scale Cyclogenesis over the North Pacific Ocean , 1993 .

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

[27]  Brian J. Hoskins,et al.  The Shape, Propagation and Mean-Flow Interaction of Large-Scale Weather Systems , 1983 .

[28]  B. Hoskins,et al.  Two paradigms of baroclinic‐wave life‐cycle behaviour , 1993 .

[29]  Xiang-Yu Huang,et al.  The influence of isolated observations on short‐range numerical weather forecasts , 1988 .

[30]  Ying-Hwa Kuo,et al.  Prediction of Nine Explosive Cyclones over the Western Atlantic Ocean with a Regional Model , 1990 .

[31]  B. Farrell,et al.  The Concept of Wave Overreflection and Its Application to Baroclinic Instability , 1980 .

[32]  Franco Molteni,et al.  Ensemble prediction using dynamically conditioned perturbations , 1993 .

[33]  Ying-Hwa Kuo,et al.  Numerical Simulation of an Explosively Deepening Cyclone in the Eastern Pacific , 1988 .

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

[35]  M. Danard,et al.  Physical influences on east coast cyclogenesis , 1980 .

[36]  David P. Baumhefner,et al.  The Impact of Initial Condition Uncertainty on Numerical Simulations of Large-scale Explosive Cyclogenesis , 1989 .

[37]  Ying-Hwa Kuo,et al.  Effects of Surface Energy Fluxes during the Early Development and Rapid Intensification Stages of Seven Explosive Cyclones in the Western Atlantic , 1991 .

[38]  P. Courtier,et al.  A strategy for operational implementation of 4D‐Var, using an incremental approach , 1994 .

[39]  Philippe Courtier,et al.  A comparison between four-dimensional variational assimilation and simplified sequential assimilation relying on three-dimensional variational analysis , 1993 .

[40]  B. Hoskins,et al.  Barotropic Influences on the Growth and Decay of Nonlinear Baroclinic Waves , 1980 .

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

[42]  B. Farrell,et al.  An Adjoint Method for Obtaining the Most Rapidly Growing Perturbation to Oceanic Flows , 1992 .

[43]  K. Emanuel,et al.  Potential Vorticity Diagnostics of Cyclogenesis , 1991 .

[44]  J. Whitaker,et al.  Type B Cyclogenesis in a Zonally Varying Flow , 1992 .

[45]  W. Robinson On the structure of potential vorticity in baroclinic instability , 1989 .

[46]  Yong Li,et al.  Four-Dimensional Variational Data Assimilation Experiments with a Multilevel Semi-Lagrangian Semi-Implicit General Circulation Model , 1994 .

[47]  Dan G. Cacuci,et al.  Sensitivity Analysis of a Radiative-Convective Model by the Adjoint Method , 1982 .

[48]  Paul Roebber Statistical analysis and updated climatology of explosive cyclones , 1984 .

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

[50]  F. Sanders Explosive Cyclogenesis in the West-Central North Atlantic Ocean, 1981–84. Part I: Composite Structure and Mean Behavior , 1986 .

[51]  C. Chouinard,et al.  Numerical Forecasts of Explosive Winter Storms: Sensitivity Experiments with a Meso‐α scale Model , 1989 .

[52]  Philippe Courtier,et al.  Interactions of Dynamics and Observations in a Four-Dimensional Variational Assimilation , 1993 .

[53]  Milija Zupanski,et al.  Regional Four-Dimensional Variational Data Assimilation in a Quasi-Operational Forecasting Environment , 1993 .

[54]  Thomas T. Warner,et al.  A Real-Time, Mesoscale Numerical Weather-Prediction System Used for Research, Teaching, and Public Service at The Pennsylvania State University , 1990 .

[55]  Y. Kuo,et al.  Climatology of explosive cyclones off the East Asian Coast , 1992 .

[56]  B. Hoskins,et al.  Eliassen-Palm Cross Sections for the Troposphere , 1980 .

[57]  L. E. Branscome,et al.  Effect of Surface Fluxes on the Nonlinear Development of Baroclinic Waves , 1989 .

[58]  L. Bosart,et al.  A Diagnostic Analysis of the Presidents' Day Storm Of February 1979 , 1984 .

[59]  R. G. Fleagle,et al.  The Distribution of Surface Fluxes and Boundary Layer Divergence in Midlatitude Ocean Storms , 1985 .