The dichotomous structure of the warm conveyor belt

The warm conveyor belt (WCB) of an extratropical cyclone generally splits into two branches. One branch (WCB1) turns anticyclonically into the downstream upper-level tropospheric ridge, while the second branch (WCB2) wraps cyclonically around the cyclone centre. Here, the WCB split in a typical North Atlantic cold-season cyclone is analysed using two numerical models: the Met Office Unified Model and the COSMO model. The WCB flow is defined using off-line trajectory analysis. The two models represent the WCB split consistently. The split occurs early in the evolution of the WCB with WCB1 experiencing maximum ascent at lower latitudes and with higher moisture content than WCB2. WCB1 ascends abruptly along the cold front where the resolved ascent rates are greatest and there is also line convection. In contrast, WCB2 remains at lower levels for longer before undergoing saturated large-scale ascent over the system's warm front. The greater moisture in WCB1 inflow results in greater net potential temperature change from latent heat release, which determines the final isentropic level of each branch. WCB1 also exhibits lower outflow potential vorticity values than WCB2. Complementary diagnostics in the two models are utilised to study the influence of individual diabatic processes on the WCB. Total diabatic heating rates along the WCB branches are comparable in the two models, with microphysical processes in the large-scale cloud schemes being the major contributor to this heating. However, the different convective parametrization schemes used by the models cause significantly different contributions to the total heating. These results have implications for studies on the influence of the WCB outflow in Rossby wave evolution and breaking. Key aspects are the net potential temperature change and the isentropic level of the outflow, which together will influence the relative mass going into each WCB branch and the associated negative PV anomalies at the tropopause-level flow.

[1]  R. Plant,et al.  Parametrized diabatic processes in numerical simulations of an extratropical cyclone , 2014 .

[2]  Peter H. Haynes,et al.  On the Evolution of Vorticity and Potential Vorticity in the Presence of Diabatic Heating and Frictional or Other Forces , 1987 .

[3]  S. Gray Mechanisms of midlatitude cross‐tropopause transport using a potential vorticity budget approach , 2006 .

[4]  John Methven,et al.  Diabatic processes modifying potential vorticity in a North Atlantic cyclone , 2013 .

[5]  S. Belcher,et al.  The Moist Boundary Layer under a Mid-latitude Weather System , 2010 .

[6]  Huw C. Davies,et al.  Diagnosis and Dynamics of Forecast Error Growth , 2013 .

[7]  Toby N. Carlson,et al.  Airflow Through Midlatitude Cyclones and the Comma Cloud Pattern , 1980 .

[8]  G. Mellor,et al.  Development of a turbulence closure model for geophysical fluid problems , 1982 .

[9]  M. Stoelinga A Potential Vorticity-Based Study of the Role of Diabatic Heating and Friction in a Numerically Simulated Baroclinic Cyclone , 1996 .

[10]  John S. Kain,et al.  The Kain–Fritsch Convective Parameterization: An Update , 2004 .

[11]  Keith A. Browning,et al.  Organization of Clouds and Precipitation in Extratropical Cyclones , 1990 .

[12]  T. W. Harrold Mechanisms influencing the distribution of precipitation within baroclinic disturbances , 1973 .

[13]  Heini Wernli,et al.  Influence of microphysical processes on the potential vorticity development in a warm conveyor belt: a case‐study with the limited‐area model COSMO , 2012 .

[14]  P. Hobbs,et al.  The cellular structure of narrow cold‐frontal rainbands , 1979 .

[15]  G. Vaughan,et al.  Occluded Fronts and the Occlusion Process: A Fresh Look at Conventional Wisdom , 2011 .

[16]  G. Martin,et al.  A New Boundary Layer Mixing Scheme. Part I: Scheme Description and Single-Column Model Tests , 2000 .

[17]  R. Plant,et al.  The dynamics of a midlatitude cyclone with very strong latent‐heat release , 2004 .

[18]  J. Steppeler,et al.  Meso-gamma scale forecasts using the nonhydrostatic model LM , 2003 .

[19]  T. Bracegirdle,et al.  The dynamics of a polar low assessed using potential vorticity inversion , 2009 .

[20]  John Methven,et al.  Potential vorticity in warm conveyor belt outflow , 2015 .

[21]  A. Slingo,et al.  Studies with a flexible new radiation code. I: Choosing a configuration for a large-scale model , 1996 .

[22]  Heini Wernli,et al.  A 15-Year Climatology of Warm Conveyor Belts , 2004 .

[23]  S. Belcher,et al.  Boundary‐layer friction in midlatitude cyclones , 2006 .

[24]  Damian R. Wilson,et al.  A microphysically based precipitation scheme for the UK meteorological office unified model , 1999 .

[25]  Alan J. Thorpe,et al.  The Evolution and Dynamical Role of Reduced Upper-Tropospheric Potential Vorticity in Intensive Observing Period One of FASTEX , 2000 .

[26]  E. Lorenz Energy and Numerical Weather Prediction , 1960 .

[27]  P. Rowntree,et al.  A Mass Flux Convection Scheme with Representation of Cloud Ensemble Characteristics and Stability-Dependent Closure , 1990 .

[28]  S. Gray,et al.  Horizontal potential vorticity dipoles on the convective storm scale , 2009 .

[29]  H. Wernli,et al.  Warm Conveyor Belts in Idealized Moist Baroclinic Wave Simulations , 2013 .

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

[31]  B. Hoskins,et al.  On the use and significance of isentropic potential vorticity maps , 2007 .

[32]  J. Kain,et al.  A One-Dimensional Entraining/Detraining Plume Model and Its Application in Convective Parameterization , 1990 .

[33]  Ying-Hwa Kuo,et al.  The Integrated Effect of Condensation in Numerical Simulations of Extratropical Cyclogenesis , 1993 .

[34]  M. Tiedtke A Comprehensive Mass Flux Scheme for Cumulus Parameterization in Large-Scale Models , 1989 .

[35]  Heini Wernli,et al.  A Lagrangian‐based analysis of extratropical cyclones. II: A detailed case‐study , 1997 .

[36]  S. Belcher,et al.  Numerical Simulation of Baroclinic Waves with a Parameterized Boundary Layer , 2007 .

[37]  P. Knippertz,et al.  Research flight observations of a prefrontal gravity wave near the southwestern UK , 2010 .

[38]  M. Blackburn,et al.  The importance of moisture distribution for the growth and energetics of mid-latitude systems , 1999 .

[39]  N. Phillips,et al.  NUMERICAL INTEGRATION OF THE QUASI-GEOSTROPHIC EQUATIONS FOR BAROTROPIC AND SIMPLE BAROCLINIC FLOWS , 1953 .

[40]  Heini Wernli,et al.  A Lagrangian‐based analysis of extratropical cyclones. I: The method and some applications , 1997 .

[41]  J. Namias The Use of Isentropic Analysis in Short Term Forecasting , 1939 .

[42]  S. Belcher,et al.  Synoptic Controls on Boundary-Layer Characteristics , 2010 .

[43]  J. Whitaker,et al.  Cyclogenesis in a Saturated Environment , 1994 .

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

[45]  K. Browning,et al.  Structure of a frontal cyclone , 1994 .

[46]  D. Schultz Reexamining the Cold Conveyor Belt , 2001 .

[47]  K. Browning,et al.  Interpretation of Satellite Imagery of A Rapidly Deepening Cyclone , 2007 .

[48]  Akio Arakawa,et al.  Computational Design of the Basic Dynamical Processes of the UCLA General Circulation Model , 1977 .

[49]  A. Staniforth,et al.  A new dynamical core for the Met Office's global and regional modelling of the atmosphere , 2005 .

[50]  Jonathan E. Martin The Structure and Evolution of a Continental Winter Cyclone. Part I: Frontal Structure and the Occlusion Process , 1998 .

[51]  J. Louis A parametric model of vertical eddy fluxes in the atmosphere , 1979 .

[52]  David Abend Images In Weather Forecasting A Practical Guide For Interpreting Satellite And Radar Imagery , 2016 .

[53]  K. A. Browning,et al.  RADAR MEASUREMENTS OF AIR MOTION NEAR FRONTS , 1971 .

[54]  Diagnosis of “forecast‐analysis” differences of a weather prediction system , 2003 .

[55]  B. Ritter,et al.  A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations , 1992 .

[56]  M. Rodwell,et al.  Characteristics of occasional poor medium-range weather forecasts for Europe , 2013 .