Assessment of several moist adiabatic processes associated with convective energy calculation

  • Li YaodongEmail author
  • Gao Shouting
  • Liu Jianwen


Several methods dealing with the moist adiabatic process are described in this paper. They are based on static energy conservation, pseudo-equivalent potential temperature conservation, the strict pseudo-adiabatic equation, and the reversible moist adiabatic process, respectively. Convective energy parameters, which are closely related to the moist adiabatic process and which reflect the gravitational effects of condensed liquid water, are reintroduced or defined, including MCAPE [Modified-CAPE (convective available potential energy)], DCAPE (Downdraft-CAPE), and MDCAPE (Modified-Downdraft-CAPE). Two real case analyses with special attention given to condensed liquid water show that the selection of moist adiabatic process does affect the calculated results of CAPE and the gravitational effects of condensed liquid water are not negligible in severe storms. Intercomparisons of these methods show that static energy conservation is consistent with pseudo-equivalent potential temperature conservation not only in physical properties but also in calculated results, and both are good approximations to the strict pseudo-adiabatic equation. The lapse rate linked with the reversible moist adiabatic process is relatively smaller than that linked with other moist adiabatic processes, especially when considering solidification of liquid water in the reversible adiabatic process.

Key words

moist adiabatic processes modified convective available potential energy downdraft convective available potential energy modified downdraft convective available potential energy reversible moist adiabatic process liquid water 


  1. Andrew, J. M., and G. S. Michael, 2001: Models for stratiform instability and convectively coupled waves.J. Atmos. Sci.,58, 1567–1584.CrossRefGoogle Scholar
  2. Bolton, D., 1980: The computation of equivalent potential temperature.Mon. Wea. Rev.,108, 1046–1052.CrossRefGoogle Scholar
  3. Desautels, G., and R. Verret, 1996: Canadian Meteorological Center summer severe weather ypackage.18th Conf. on Severe Local Storms. San Francisco, CA., Amer. Meteor. Soc., 689–692.Google Scholar
  4. Doswell, C. A. III, 1987: The distinction between largescale and mesoscale contribution to severe convection: A case study example.Wea. Forecasting,2, 3–16.CrossRefGoogle Scholar
  5. Durran, D. R., and J. B. Klemp, 1982: On the effects of moisture on the Brunt-Vaisala frequency.J. Atmos. Sci.,9, 2152–2158.CrossRefGoogle Scholar
  6. Emanuel, K. A., 1994: Atmospheric Convection. Oxford University Press, New York, 580pp.Google Scholar
  7. Galway, J. G., 1956: The lifted index as a predictor of latent instability.Bull. Amer. Meteor. Soc.,37, 528–529.Google Scholar
  8. Gilmore, M. S., and L. J. Wicker, 1998: The influence of midtropospheric dryness on supercell morphology and evolution.Mon. Wea. Rev.,126, 943–958.CrossRefGoogle Scholar
  9. Huntrieser, H., H. H. Schiesser, and W. A. Schmid, 1997: Comparison of traditional and newly developed thunderstorm indices for Switzerland.Wea. Forecasting,12, 108–125.CrossRefGoogle Scholar
  10. Li Yaodong, Liu Jianwen, Liu Yuling, Zhang Fangyou, and Wu Baojun, 1998: Drawing emagram with microcomputer and calculating convective available potential energy.Meteorological Monthly,24(5), 23–27. (in Chinese)Google Scholar
  11. Liu Liping, Feng Jinming, Chu Rongzhong, Zhou Yunjun, and K. Ueno, 2002: The diurnal variation of precipitation in monsoon season in the Tibetan Plateau.Adv. Atmos. Sci.,19, 365–378.CrossRefGoogle Scholar
  12. McNulty, R. P., 1978: On upper tropospheric kinematics and severe weather occurrence.Mon. Wea. Rev.,106, 662–672.CrossRefGoogle Scholar
  13. McNulty, R. P., 1995: Severe and convective weather: A central region forecasting challenge.Wea. Forecasting,10, 187–202.CrossRefGoogle Scholar
  14. Moncrieff, M. W., and M. J. Miller, 1976: The dynamics and simulation of tropical cumulonimbus and squall lines.Quart. J. Roy. Meteor. Soc.,102, 373–394.CrossRefGoogle Scholar
  15. Rochette, S. M., 1999: The importance of parcel choice in elevated CAPE computations.National Weather Digest,23, 20–32.Google Scholar
  16. Saunders, P. M., 1957: The thermodynamics of saturated air: A contribution to the classical theory.Quart. J. Roy. Meteor. Soc.,83, 342–350.CrossRefGoogle Scholar
  17. Schultz, D. M., and P. N. Schumacher, 1999: The use and misuse of conditional symmetric instability.Mon. Wea. Rev.,127, 2709–2732.CrossRefGoogle Scholar
  18. Schultz, D. M., P. N. Schumacher, and C. A. Doswell, 2000: The intricacies of instabilities.Mon. Wea. Rev.,128, 4143–4148.CrossRefGoogle Scholar
  19. Sherwood, S. C., 2000: On moist instability.Mon. Wea. Rev.,128, 4139–4142.CrossRefGoogle Scholar
  20. Showalter, A. K., 1953: A stability index for thunderstorm forecasting.Bull. Amer. Meteor. Soc.,34, 250–252.Google Scholar
  21. Showalter, A. K., and J. R. Fulks, 1943: Preliminary report on tornadoes. U.S. Weather Bureau, Washington, 162pp.Google Scholar
  22. Tian Shengchun, 1991: Effect of merging of the convective cloud clusters on occurrence of heavy rainfall.Adv. Atmos. Sci.,8, 499–504.CrossRefGoogle Scholar
  23. Williams, E., and N. Renno, 1993: An analysis of the conditional instability of the tropical atmosphere.Mon. Wea. Rev.,121, 21–36.CrossRefGoogle Scholar
  24. Xie Shaocheng, 2002: Intercomparison and evaluation of cumulus parameterizations for midlatitude intense organized convection.Proc. Summer Workshop on Severe Storms and Torrential Rain, Chengdu China, Institute of Atmospheric Physics, Chinese Academy of Sciences, 86–90.Google Scholar

Copyright information

© Advances in Atmospheric Sciences 2004

Authors and Affiliations

  1. 1.Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing
  2. 2.Beijing Aviation Meteorological InstituteBeijing

Personalised recommendations