Climate Dynamics

, Volume 28, Issue 6, pp 581–597 | Cite as

Parameterisation of orographic cloud dynamics in a GCM

  • S. M. Dean
  • J. Flowerdew
  • B. N. Lawrence
  • S. D. Eckermann


A new parameterisation is described that predicts the temperature perturbations due to sub-grid scale orographic gravity waves in the atmosphere of the 19 level HadAM3 version of the United Kingdom Met Office Unified Model. The explicit calculation of the wave phase allows the sign of the temperature perturbation to be predicted. The scheme is used to create orographic clouds, including cirrus, that were previously absent in model simulations. A novel approach to the validation of this parameterisation makes use of both satellite observations of a case study, and a simulation in which the Unified Model is nudged towards ERA-40 assimilated winds, temperatures and humidities. It is demonstrated that this approach offers a feasible way of introducing large scale orographic cirrus clouds into GCMs.


  1. Bacmeister JT, Newman PA, Gray BL, Chan KR (1994) An algorithm for forecasting mountain wave-related turbulence in the stratosphere. Weather Forecast 9:241–253CrossRefGoogle Scholar
  2. Broutman D, Rottman JW, Eckermann SD (2004) Ray methods for internal waves in the atmosphere and ocean. Annu Rev Fluid Mech 36:233–253CrossRefGoogle Scholar
  3. Butchart N, Knight JR (1999) Estimates of sub-grid temperature perturbations from a gravity wave drag parameterization in a GCM. In: Carslaw KS, Amanatidis GT (eds) Mesoscale processes in the stratosphere—their effects on stratospheric chemistry and microphysics, no. 69 in European Commission air pollution research reportGoogle Scholar
  4. Carslaw KS, Peter T, Bacmeister JT, Eckermann SD (1999) Widespread solid particle formation by mountain waves in the Arctic stratosphere. J Geophys Res 104:1827–1836CrossRefGoogle Scholar
  5. Cusack S, Edwards JM, Kershaw R (1999) Estimating the subgrid variance of saturation and its parameterization for use in a GCM cloud scheme. Q J R Meteorol Soc 125:3057–3076CrossRefGoogle Scholar
  6. Dean SM, Lawrence BN, Grainger RG, Heuff DN (2005) Orographic cloud in a GCM: the missing cirrus. Clim Dyn 24:771–780CrossRefGoogle Scholar
  7. Eckermann SD, Preusse P (1999) Global measurements of stratospheric mountain waves from space. Science 286:1534–1537CrossRefGoogle Scholar
  8. Eckermann SD, Gibson-Wilde DE, Bacmeister JT (1998) Gravity wave perturbations of minor constituents: a parcel advection methodology. J Atmos Sci 55:3521–3539CrossRefGoogle Scholar
  9. ECMWF (1995) User Guide to ECMWF Products 2.1, European Centre for Medium-Range Weather ForecastingGoogle Scholar
  10. Feichter J, Lohmann U (1999) Can a relaxation technique be used to validate clouds and sulphur species in a gcm? Q J R Meteorol Soc 125:1277–1294CrossRefGoogle Scholar
  11. Fowler LD, Randall DA (1999) Simulation of upper tropospheric clouds with the Colorado State University general circulation model. J Geophys Res 104:6101–6121CrossRefGoogle Scholar
  12. Gregory D, Shutts GJ, Mitchell JR (1998) A new gravity-wave drag scheme incorporating anisotropic orography and low level wave breaking: impact upon the climate of the UK Meteorological Office Unified Model. Q J R Meteorol Soc 124:463–493CrossRefGoogle Scholar
  13. Höpfner M, Larsen N, Spang R, Luo BP, Ma J, Svendsen SH, Eckermann SD, Knudsen B, Massoli P, Cairo F, Stiller G, v Clarmann T, Fischer H (2005) Mipas detects antarctic stratospheric belt of nat pscs caused by mountain waves. Atmos Chem Phys Discuss 5:10723–10745CrossRefGoogle Scholar
  14. Jeuken ABM, Siegmund PC, Heijboer LC, Feichter J, Bengtsson L (1996) On the potential of assimilating meteorological analyses in a global climate model for the purposes of model validation. J Geophys Res 101:16939–16950CrossRefGoogle Scholar
  15. Karcher B, Lohmann U (2002) A parameterization of cirrus cloud formation: homogeneous freezing of supercooled aerosols. J Geophys Res 107:ACL4–9,ACL4–10Google Scholar
  16. Leung LR, Ghan S (1995) A subgrid parameterisation of orographic precipitation. Theor Appl Climatol 53:95–118CrossRefGoogle Scholar
  17. Leung LR, Ghan S (1998) Parameterising subgrid orographic precipitation and surface cover in climate models. Mon Weather Rev 126:3271–3291CrossRefGoogle Scholar
  18. Lindzen RS (1981) Turbulence and stress owing to gravity wave and tidal breakdown. J Geophys Res 86,NO.C10:9707–9714Google Scholar
  19. Lohmann U, Feichter J, Chuang CC, Penner JE (1999) Prediction of the number of cloud droplets in the ECHAM GCM. J Geophys Res 104:9169–9198CrossRefGoogle Scholar
  20. Mann GW, Carslaw KS, Chipperfield MP, Davies S, Eckermann SD (2005) Large nat particles and dentrification caused by mountain waves in the arctic stratosphere. J Geophys Res 110Google Scholar
  21. McFarlane NA (1987) The effect of orographically excited gravity wave drag on the general circulation of the lower stratosphere and troposphere. J Atmos Sci 44:1775–1800CrossRefGoogle Scholar
  22. Nilson ED, Pirjola L, Kulmala M (2000) The effect of atmospheric waves on aerosol nucleation and size distribution. J Geophys Res 105:19917–19926CrossRefGoogle Scholar
  23. Palmer TN, Shutts GJ, Swinbank R (1986) Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parameterisation. Q J R Meteorol Soc 112:1001–1039CrossRefGoogle Scholar
  24. Pope VD, Gallani ML, Rowntree PR, Stratton RA (2000) The impact of new physical parameterizations in the Hadley Centre climate model HadAM3. Clim Dyn 16:123–146CrossRefGoogle Scholar
  25. Queney P (1948) The problem of airflow over mountains: a summary of theoretical studies. Bull Am Met Soc 29:16–26Google Scholar
  26. Ridley RN (1991) Observations and numerical modelling of air flows over New Zealand, Ph.D. thesis, Monash UniversityGoogle Scholar
  27. Tan K, Eckermann SD (2000) Numerical simulations of mountain waves in the middle atmosphere over the southern Andes. In: Siskind DE, Summers ME, Eckermann SD (eds) Atmospheric science across the stratopause. Geophysical Monograph, AGU, Washington pp 123:311–318Google Scholar
  28. Watts PD (1995) Potential use of along track scanning radiometer data for cloud parameter retrieval, no. 2578 in Proc Spie Int Soc Opt EngGoogle Scholar
  29. Webster S, Brown AR, Cameron DR, Jones CP (2003) Improvements to the representation of orography in the Met Office Unified Model. Q J R Meteorol Soc 129:1989–2010CrossRefGoogle Scholar
  30. Wilson DR, Ballard SP (1999) A microphysically based precipitation scheme for the UK Meteorological Office Unified Model. Q J R Meteorol Soc 125:1607–1636CrossRefGoogle Scholar
  31. Wilson D, Gregory D (2003) The behavior of large-scale model cloud schemes under idealized forcing scenarios. Q J R Meteorol Soc 129:967–986CrossRefGoogle Scholar
  32. Xu KM, Randall DA (1996) A semiempirical cloudiness parameterization for use in climate models. J Atmos Sci 53:3084–3102CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • S. M. Dean
    • 1
  • J. Flowerdew
    • 2
  • B. N. Lawrence
    • 3
  • S. D. Eckermann
    • 4
  1. 1.National Institute of Water and Atmospheric Research LtdWellingtonNew Zealand
  2. 2.Atmospheric Oceanic and Planetary Physics, Clarendon LaboratoryUniversity of OxfordOxfordUK
  3. 3.British Atmospheric Data Centre, Rutherford Appleton LaboratoryChiltonUK
  4. 4.E. O. Hulburt Center for Space Research, Code 7646Naval Research LaboratoryWashington, DCUSA

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