• Beljaars, A. C. M., 1995: The impact of some aspects of the boundary layer scheme in the ECMWF model. Proc. Parametrization of Sub-Grid Scale Physical Processes, Reading, United Kingdom, ECMWF, 125–161.

  • Bintanja, R., and M. R. van den Broeke, 1995: The surface energy balance of Antarctic snow and blue ice. J. Appl. Meteor.,34, 902–926.

  • ——, ——, and M. J. Portanger, 1993: A meteorological and glaciological experiment on a blue ice area in the Heimefront Range, Queen Maud Land, Antarctica. Svea Field Report, Institute for Marine and Atmospheric Research Utrecht, Utrecht University, 29 pp. [Available from IMAU, P. O. Box 80005, 3508 TA Utrecht, Netherlands.].

  • Bromwich, D. H., F. M. Robasky, R. I. Cullather, and M. L. Woert, 1995: The atmospheric hydrological cycle over the Southern Ocean and Antarctica from operational numerical analyses. Mon. Wea. Rev.,123, 3518–3538.

  • Budd, W. F., P. A. Reid, and L. J. Minty, 1995: Antarctic moisture flux and net accumulation from global atmospheric analyses. Ann. Glaciol.,21, 149–156.

  • Christensen, J. H., O. B. Christensen, P. Lopez, E. van Meijgaard, and M. Botzet, 1996: The HIRHAM4 regional atmospheric climate model. DMI Scientific Rep. 96-4, Copenhagen, Denmark, 51 pp. [Available from DMI, Lyngbyvej 100, DK-2100 Copenhagen, Denmark.].

  • ——, B. Machenhauer, R. G. Jones, C. Schär, P. M. Ruti, M. Castro, and G. Visconti, 1997: Validation of present-day regional climate simulations over Europe: LAM simulations with observed boundary conditions. Climate Dyn.,31, 489–506.

  • Connolley, W. M., and H. Cattle, 1994: The Antarctic climate of the UKMO unified model. Antarct. Sci.,6, 115–122.

  • Cullather, R. I., D. H. Bromwich, and R. W. Grumbine, 1997: Validation of operational numerical analyses in Antarctic latitudes. J. Geophys. Res.,102 (D12), 13 761–13 784.

  • Dethloff, K., A. Rinke, R. Lehmann, J. H. Christensen, M. Botzet, and B. Machenhauer, 1996: Regional climate model of the Arctic atmosphere. J. Geophys. Res.,101, 23 401–23 422.

  • Dickinson, R. E., R. M. Errico, F. Giorgi, and G. T. Bates, 1989: A regional climate model for the western United States. Climate Change,15, 383–422.

  • Drewry, D. J., 1983: Antarctica: Glaciological and Geophysical Folio. Scott Polar Research Institute, 9 maps.

  • Engels, R., and G. Heinemann, 1996: Three-dimensional structures of summertime Antarctic mesoscale cyclones: Part II: Numerical simulations with a limited area model. Global Atmos. Ocean Syst.,4, 181–208.

  • Fouquart, Y., and B. Bonnel, 1980: Computation of solar heating of the earth’s atmosphere: A new parameterization. Beitr. Phys. Atmos.,53, 35–62.

  • Genthon, C., 1994: Antarctic climate modeling with general circulation models of the atmosphere. J. Geophys. Res.,99 (D6), 12 953–12 961.

  • ——, and A. Braun, 1995: ECMWF analyses and predictions of the surface climate of Greenland and Antarctica. J. Climate,8, 2324–2332.

  • Gibson, R., P. Kållberg, S. Uppala, A. Hernandez, A. Nomura, and E. Serrano, 1997: ERA description. ECMWF Re-Analysis Project Rep. Series 1, Reading, United Kingdom, 72 pp.

  • Gustafsson, N., 1993: HIRLAM 2 final report. HIRLAM Tech. Rep. 9, SMHI, Norrköping, Sweden, 126 pp. [Available from SMHI, S-60176 Norrköping, Sweden.].

  • Heinemann, G., 1997: Idealized simulations of the Antarctic katabatic wind system with a three-dimensional mesoscale model. J. Geophys. Res.,102 (D12), 13 825–13 834.

  • Herron, M. M., and C. C. Langway Jr., 1980: Firn densification: An empirical model. J. Glaciol.,25, 373–385.

  • Hines, K. M., D. H. Bromwich, and T. R. Parish, 1995: A mesoscale modeling study of the atmospheric circulation at high latitudes. Mon. Wea. Rev.,123, 1146–1165.

  • ——, ——, and Z. Liu, 1997: Combined global climate model and mesoscale model simulation of Antarctic climate. J. Geophys. Res.,102 (D12), 13 747–13 760.

  • Jonsson, S., 1992: Local climate and mass balance of a blue-ice area in western Dronning Maud Land, Antarctica. Z. Gletscherk. Glazialgeol.,26, 11–29.

  • King, J. C., and W. M. Connolley, 1997: Validation of the surface energy balance over the Antarctic ice sheets in the U.K. Meteorological Office Unified Climate Model. J. Climate,10, 1273–1287.

  • ——, and J. Turner, 1997: Antarctic Meteorology and Climatology. University Press, 409 pp.

  • Krinner, G., C. Genthon, Z.-X. Li, and P. Le Van, 1997: Studies of the Antarctic climate with a stretched-grid GCM. J. Geophys. Res.,102 (D12), 13 731–13 746.

  • Louis, J. F., 1979: A parametric model of vertical eddy fluxes in the atmosphere. Bound.-Layer Meteor.,17, 187–202.

  • Mellor, M., 1977: Engineering properties of snow. J. Glaciol.,19, 15–66.

  • Miller, M. J., T. N. Palmer, and R. Swinbank, 1989: Parameterization and influence of sub-grid scale orography in general circulation and numerical weather prediction models. Meteor. Atmos. Phys.,40, 84–109.

  • Morcrette, J.-J., L. Smith, and Y. Fouquart, 1986: Pressure and temperature dependence of the absorption in longwave radiation parameterizations. Beitr. Phys. Atmos.,59, 455–469.

  • Nomura, A., 1995: Global sea ice concentration data set for use with the ECMWF re-analysis system. ECMWF Tech. Rep. 76, Reading, United Kingdom, 25 pp.

  • Roeckner, E., and Coauthors, 1996: The atmospheric general circulation model ECHAM-4: Model description and simulation of present-day climate. Max-Planck-Institut für Meteorologie Rep. 218, 90 pp. [Available from Max Planck Institute for Meteorology, Bundesstrasse 55, D-20146 Hamburg, Germany.].

  • Sundqvist, H., 1978: A parameterization scheme for non-convective condensation including prediction of cloud water content. Quart. J. Roy. Meteor. Soc.,104, 677–690.

  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev.,117, 1779–1800.

  • Turner, J., and Coauthors, 1996: The Antarctic First Regional Observing Study of the Troposphere (FROST) project. Bull. Amer. Meteor. Soc.,77, 2007–2032.

  • Tzeng, R.-Y., D. H. Bromwich, T. R. Parish, and B. Chen, 1994: NCAR CCM2 simulation of the modern Antarctic climate. J. Geophys. Res.,99 (D11), 23 131–23 148.

  • van den Broeke, M. R., 1997: Spatial and temporal variation of sublimation on Antarctica: Results of a high-resolution general circulation model. J. Geophys. Res.,102 (D25), 29 765–29 777.

  • ——, and R. Bintanja, 1995: Summertime atmospheric circulation in the vicinity of a blue ice area in East Queen Maud Land, Antarctica. Bound.-Layer Meteor.,72, 411–438.

  • van Lipzig, N. P. M., E. van Meijgaard, and J. Oerlemans, 1998: Evaluation of a regional atmospheric model for January 1993 using in-situ measurements from the Antarctic. Ann. Glaciol.,27, 507–514.

  • Walsh, K., and J. L. McGregor, 1996: Simulations of Antarctic climate using a limited area model. J. Geophys. Res.,101, 19 093–19 108.

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Evaluation of a Regional Atmospheric Model Using Measurements of Surface Heat Exchange Processes from a Site in Antarctica

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  • 1 Royal Netherlands Meteorological Institute, de Bilt, the Netherlands, and Institute for Marine and Atmospheric Research Utrecht, Utrecht, the Netherlands
  • | 2 Royal Netherlands Meteorological Institute, de Bilt, the Netherlands
  • | 3 Institute for Marine and Atmospheric Research Utrecht, Utrecht, the Netherlands
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Abstract

A regional atmospheric climate model with a horizontal grid spacing of 55 km has been used to simulate the Antarctic atmosphere during an austral summer period. ECMWF reanalyses were used to force the atmospheric prognostic variables from the lateral boundaries. Sea surface temperatures and the sea ice mask in the model were prescribed from observations. Parameterizations of the physical processes were taken from the ECHAM4 general circulation model. Before applying the model to Antarctic conditions, several adjustments had been made to the original code. In particular, a better correspondence between model output and measurements was accomplished by 1) the use of a fixed value of 0.8 for the surface albedo rather than applying an albedo that linearly rises with surface temperature and 2) the use of the volumetric heat capacity and the thermal diffusivity of snow rather than employing the values for ice.

The model is evaluated for the period 14–19 January 1993 (P1) on the basis of an extensive dataset compiled from measurements made at a site (Svea) in Dronning Maud Land. This dataset contains boundary layer temperature and specific humidity profiles, snow temperatures, and surface heat fluxes. The surface fluxes were obtained from direct measurements combined with an energy balance model. The atmospheric temperature profiles simulated at the grid points corresponding most closely to Svea are in good agreement with the measured profiles, although the model slightly overestimates the vertical temperature gradient. The model probably underestimates the turbulent transport of heat and moisture to atmospheric layers above roughly 200 m. At Svea a cloud cover of less than 0.5 octas was observed during P1. The model overestimates the cloud cover, which results in an underestimation of shortwave and an overestimation of longwave radiative fluxes at the surface. The simulated values for the net radiative fluxes, the heat flux into the snow, and the turbulent heat fluxes correspond within 4 W m−2 to the fluxes that were inferred from measurements.

Corresponding author address: Dr. Nicole P. M. van Lipzig, KNMI, P.O. Box 201, 3730 AE de Bilt, the Netherlands.

Email: lipzig@knmi.nl

Abstract

A regional atmospheric climate model with a horizontal grid spacing of 55 km has been used to simulate the Antarctic atmosphere during an austral summer period. ECMWF reanalyses were used to force the atmospheric prognostic variables from the lateral boundaries. Sea surface temperatures and the sea ice mask in the model were prescribed from observations. Parameterizations of the physical processes were taken from the ECHAM4 general circulation model. Before applying the model to Antarctic conditions, several adjustments had been made to the original code. In particular, a better correspondence between model output and measurements was accomplished by 1) the use of a fixed value of 0.8 for the surface albedo rather than applying an albedo that linearly rises with surface temperature and 2) the use of the volumetric heat capacity and the thermal diffusivity of snow rather than employing the values for ice.

The model is evaluated for the period 14–19 January 1993 (P1) on the basis of an extensive dataset compiled from measurements made at a site (Svea) in Dronning Maud Land. This dataset contains boundary layer temperature and specific humidity profiles, snow temperatures, and surface heat fluxes. The surface fluxes were obtained from direct measurements combined with an energy balance model. The atmospheric temperature profiles simulated at the grid points corresponding most closely to Svea are in good agreement with the measured profiles, although the model slightly overestimates the vertical temperature gradient. The model probably underestimates the turbulent transport of heat and moisture to atmospheric layers above roughly 200 m. At Svea a cloud cover of less than 0.5 octas was observed during P1. The model overestimates the cloud cover, which results in an underestimation of shortwave and an overestimation of longwave radiative fluxes at the surface. The simulated values for the net radiative fluxes, the heat flux into the snow, and the turbulent heat fluxes correspond within 4 W m−2 to the fluxes that were inferred from measurements.

Corresponding author address: Dr. Nicole P. M. van Lipzig, KNMI, P.O. Box 201, 3730 AE de Bilt, the Netherlands.

Email: lipzig@knmi.nl

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