Skip to main content
Log in

The hypohydrostatic rescaling and its impacts on modeling of atmospheric convection

  • Original Article
  • Published:
Theoretical and Computational Fluid Dynamics Aims and scope Submit manuscript

Abstract

The atmospheric circulation spans a wide range of spatial scales, including the planetary scale (~10,000 km), synoptic scale (~2,000 km), mesoscale (~200 km), and convective scales (< 20 km). The wide scale separation between convective motions, responsible for the vertical energy transport, and the planetary circulation, responsible for the meridional energy transport, has prevented explicit representation of convective motions in global atmospheric models. Kuang et al. (Geophys. Res. Lett. 32: L02809, 2005) have suggested a way to circumvent this limitation through a rescaling that they refer to as Diabatic Acceleration and REscaling (DARE). We focus here on a modified version of the procedure that we refer to as hypohydrostatic rescaling. These two strategies are equivalent for inviscid and adiabatic flow in the traditional meteorological setting in which the vertical component of the Coriolis acceleration is ignored, but they differ when atmospheric physics is taken into account. It is argued here that, while the hypohydrostatic rescaling preserves the dynamics of the planetary scale circulation, it increases the horizontal scale of convective motions. This drastically reduces the computational cost for explicit simulation of hypohydrostatic convection in a global atmospheric model. A key question is whether explicit simulations of hypohydrostatic convection could offer a valid alternative to convective parameterization in global models. To do so, radiative–convective equilibrium is simulated with a high-resolution non-hydrostatic model using different model resolutions and values of the rescaling parameter. When the behavior of hypohydrostatic convection is compared with coarse-resolution simulations of convection, the latter set of simulations reproduce more accurately the result from a reference high-resolution simulation. This is particularly true for the convective velocity and cloud ice distributions. Scaling arguments show that hypohydrostatic rescaling increases the convective overturning time. In particular, this convective slowdown associated with the hypohydrostatic rescaling is more significant than the slowdown resulting from under-resolving the convective elements. These results cast doubt on the practical value of the hypohydrostatic rescaling as an alternative to convective parameterization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Anderson J.L., Balaji V., Broccoli A.J., Cooke W.F., Delworth T.L., Dixon K.W., Donner L.J., Dunne K.A., Freidenreich S.M., Garner S.T., Gudgel R.G., Gordon C.T., Held I.M., Hemler R.S., Horowitz L.W., Klein S.A., Knutson T.R., Kushner P.J., Langenhorst A.R., Lau N.-C., Liang Z., Malyshev S.L., Milly P.C.D., Nath M.J., Ploshay J.J., Ramaswamy V., Schwarzkopf M.D., Shevliakova E., Sirutis J.J., Soden B.J., Stern W.F., Thompson L.A., Wilson R.J., Wittenberg A.T., Wyman B.L. (2004): The new GFDL global atmosphere and land model AM2/LM2: evaluation with prescribed SST simulations. J. Atmos. Sci 17, 4641–4673

    Google Scholar 

  2. Colella P., Woodward P.R. (1984): The piecewise parabolic method (PPM) for gas-dynamical simulations. J. Comput. Phys. 54, 174–201

    Article  MATH  MathSciNet  ADS  Google Scholar 

  3. Davies-Jones R. (2003): An expression for effective buoyancy in surroundings with horizontal density gradients. J. Atmos. Sci. 60, 2922–2925

    Article  MathSciNet  ADS  Google Scholar 

  4. Freidenreich, S.M., Ramaswamy, V.: A new multiple-band solar radiative parameterization for general circulation models. J. Geophys. Res. 104, 31, 389–31, 409 (1999)

    Google Scholar 

  5. Garner, S.G., Frierson, D., Held, I., Pauluis, O., Vallis, G.: Resolving convection in a global hypohydrostatic model. J. Atmos. Sci (2006) (submitted)

  6. Grabowski W., Wu X., Moncrieff M.W. (1996): Cloud-resolving modeling of tropical cloud systems during phase III of GATE. Part I: Two-dimensional experiments. J. Atmos. Sci. 53, 3684–3709

    Article  ADS  Google Scholar 

  7. Grabowski W., Yano J.-I., Moncrieff M.W. (2000): Cloud resolving modeling of tropical circulations driven by large-scale SST gradients. J. Atmos. Sci. 57, 2022–2040

    Article  ADS  Google Scholar 

  8. Held I.M., Hemler R.S., Ramaswamy V. (1993): Radiative-convective equilibrium with explicit two-dimensional moist convection. J. Atmos. Sci. 50, 3909–3927

    Article  ADS  Google Scholar 

  9. Klemp J.B., Wilhelmson R.B. (1978): The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci. 35, 1070–1096

    Article  ADS  Google Scholar 

  10. Krueger S.K., Fu Q., Liou K.N., Schin H.-N. (1995): Improvements of an ice-phase microphysics parameterization for use in numerical simulations of tropical convection. J. Appl. Meteorol. 34, 281–287

    Article  ADS  Google Scholar 

  11. Kuang Z., Blossey P.N., Bretherton C.S. (2005): A new approach for 3D cloud resolving simulations of large scale atmospheric circulation. Geophys. Res. Lett. 32: L02809

    Article  Google Scholar 

  12. Lin Y.-L., Farley R.D., Orville H.D. (1983): Bulk parameterization of the snow field in a cloud model. J. Appl. Meteorol. 22, 1065–1092

    Article  ADS  Google Scholar 

  13. Lipps F.B., Hemler R.S. (2004): Scale analysis of deep, moist convection and some related numerical calculations. J. Atmos. Sci. 39, 2192–2210

    Article  ADS  Google Scholar 

  14. Lord S.J., Willoughby H.E., Piotrowicz J.M. (1984): Role of a parameterized ice-phase microphysics in an axisymmetric, nonhydrostatic tropical cyclone model. J. Atmos. Sci. 41, 2836–2848

    Article  ADS  Google Scholar 

  15. Pauluis O., Garner S. (2006): Sensitivity of radiative-convective equilibrium simulations to horizontal resolution. J. Atmos. Sci. 63, 1910–1923

    Article  ADS  Google Scholar 

  16. Pedlosky J. (1979): Geophysical Fluid Dynamics. Springer, Berlin Heidelberg New York, p. 728,

    MATH  Google Scholar 

  17. Randall D., Krueger S., Bretherton C., Curry J., Duynkerke P., Moncrieff M., Ryan B., Starr D., Miller M., Rossow W., Tselioudis G., Wielicki B. (2003a): Confronting models with Data: the GEWEX cloud systems study. Bull. Am. Meteorol. Soc. 84, 455–469

    Article  ADS  Google Scholar 

  18. Randall D.A., Khairoutdinov M., Arakawa A., Grabowski W. (2003b): Breaking the cloud parameterization deadlock. Bull. Am. Meteorol. Soc. 84, 1547–1564

    Article  ADS  Google Scholar 

  19. Tomita H., Miura H., Iga S., Nasuno T., Satoh M. (2005): A global cloud-resolving simulation: preliminary results from an aqua planet experiment. Geophys. Res. Lett. 32:P L08805, DOI:10.1029/2005GL022459

    Google Scholar 

  20. Tompkins A, Craig G.C. (1998): Radiative-convective equilibrium in a three-dimensional cloud-ensemble model. Q. J. R. Meteorol. Soc. 124, 2073–2097

    Article  ADS  Google Scholar 

  21. Xu K.-M., Randall D. (1996): Explicit simulation of cumulus ensembles with the GATE phase III data: comparison with observations. J. Atmos. Sci. 53, 3710–3736

    Article  ADS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Olivier Pauluis.

Additional information

Communicated by R. Klein

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pauluis, O., Frierson, D.M.W., Garner, S.T. et al. The hypohydrostatic rescaling and its impacts on modeling of atmospheric convection. Theor. Comput. Fluid Dyn. 20, 485–499 (2006). https://doi.org/10.1007/s00162-006-0026-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00162-006-0026-x

Keywords

PACS

Navigation