Convective, Moist, and Dynamic Vorticity Vectors

As one of the most important dynamic/thermodynamic parameters, potential vorticity (PV) has been studied to enhance the understanding of the genesis and development of weather systems for more than six decades since it was first introduced by Ertel (1942). PV is conserved in a frictionless, adiabatic flow in a dry atmosphere. Later, moist PV was introduced by replacing potential temperature with the equivalent potential temperature. Moist PV is conserved in frictionless, moist adiabatic processes. Many studies have contributed to understanding the dry and moist PV associated with dynamic and thermodynamic processes in the genesis and development of weather systems (e.g., Bennetts and Hoskins 1979; Emanuel 1979; Danielsen and Hipskind 1980; Thorpe 1985; Hoskins and Berrisford 1988; Xu 1992; Montgomery and Farrell 1993; Cao and Cho 1995; Cho and Cao 1998; Gao et al. 2002). Helicity, as an important dynamic concept, has been applied to the study of convective storms in recent decades (e.g., Lilly 1986; Droegemeier et al. 1993; Tan and Wu 1994) since it was introduced by Betchov (1961). However, PV and helicity cannot be applied to the analysis in the 2D framework.

Convective (CVV), moist (MVV), and dynamic (DVV) vorticity vectors are introduced in the 2D framework by Gao et al. (2004, 2005) and are further studied in the 3D framework by Gao et al. (2007) and Gao (2007). How well do these vorticity vectors represent convective signals? What dominant physical processes determine the variations of these vorticity vectors? What are the differences between the 2D and 3D vorticity vectors? What are the differences between CVV and moist PV and between DVV and helicity in the study of 3D convection? These questions will be discussed in this chapter based on Gao et al. (2004, 2005, 2007) and Gao (2007).

Keywords

Vortex Convection Covariance Radar Vorticity 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bennetts DA, Hoskins BJ (1979) Conditional symmetric instability - a possible explanation for frontal rainbands. Quart J Roy Meteor Soc 105:945–962CrossRefGoogle Scholar
  2. Betchov R (1961) Semi-isotropic turbulence and helicoidal flows. Phys Fuilds 4:925–926CrossRefGoogle Scholar
  3. Cao Z, Cho H (1995) Generation of moist vorticity in extratropical cyclones. J Atmos Sci 52: 3263–3281CrossRefGoogle Scholar
  4. Cho H, Cao Z (1998) Generation of moist vorticity in extratropical cyclones. Part II: Sensitivity to moisture distribution. J Atmos Sci 55:595–610CrossRefGoogle Scholar
  5. Danielsen EF, Hipskind RS (1980) Stratospheric-tropospheric exchange at polar latitudes in summer. J Geophys Res 85:393–400CrossRefGoogle Scholar
  6. Droegemeier KK, Lazarus SM (1993) The influence of helicity on numerically simulated convective storms. Mon Wea Rev 121:2005–2029CrossRefGoogle Scholar
  7. Emanuel KA (1979) Inertial instability and mesoscale convective systems. Part I: Linear theory of inertial instability in rotating viscous fluids. J Atmos Sci 36:2425–2449CrossRefGoogle Scholar
  8. Ertel H (1942) Ein neuer hydrodynamischer wirbelsatz. Meteorology Zeitschr Braunschweigs 6:277–281Google Scholar
  9. Gao S (2007) A three-dimensional dynamic vorticity vector associated with tropical oceanic convection. J Geophys Res, doi:10.1029/2007JD008247Google Scholar
  10. Gao S, Lei T, Zhou Y (2002) Moist potential vorticity anomaly with heat and mass forcings in torrential rain system. Chin Phys Lett 19:878–880CrossRefGoogle Scholar
  11. Gao S, Ping F, Li X, Tao WK (2004) A convective vorticity vector associated with tropical convection: A 2D cloud-resolving modeling study. J Geophys Res, doi:10.1029/2004JD004807Google Scholar
  12. Gao S, Cui X, Zhou Y, Li X, Tao WK (2005) A modeling study of moist and dynamic vorticity vectors associated with 2D tropical convection. J Geophys Res, doi:10.1029/2004JD005675Google Scholar
  13. Gao S, Li X, Tao WK, Shie CL, Lang S (2007) Convective and moist vorticity vectors associated with three-dimensional tropical oceanic convection during KWAJEX, J Geophys Res, doi:10.1029/2006JD007179Google Scholar
  14. Hoskins BJ, Berrisford P (1988) A potential vorticity perspective of the storm of 15–16 October 1987. Weather 43:122–129Google Scholar
  15. Li X, Sui CH, Lau KM (2002) Dominant cloud microphysical processes in a tropical oceanic convective system: A 2-D cloud resolving modeling study. Mon Wea Rev 130:2481–2491CrossRefGoogle Scholar
  16. Lilly DK (1986) The structure, energetics and propagation of rotating convective storms. Part II: Helicity and storm stabilization. J Atmos Sci 43:126–140CrossRefGoogle Scholar
  17. Montgomery MT, Farrell BF (1993) Tropical cyclone formation. J Atmos Sci 50:285–310CrossRefGoogle Scholar
  18. Shie CL, Tao WK, Simpson J (2003) Simulated KWAJEX convective systems using a 2D and 3D cloud resolving model and their comparisons with radar observations. 31st Conference on Radar Meteorology, Seattle, Washington, 6–12 August 2003Google Scholar
  19. Tan Z, Wu R (1994) Helicity dynamics of atmospheric flow. Adv Atmos Sci 11:175–188CrossRefGoogle Scholar
  20. Thorpe AJ (1985) Diagnosis of balanced vortex structure using potential vorticity. J Atmos Sci 42:397–406CrossRefGoogle Scholar
  21. Xu Q (1992) Formation and evolution of frontal rainbands and geostrophic potential vorticity anomalies. J Atmos Sci 49:629–648CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media B.V 2008

Personalised recommendations