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Abstract
A technique is presented for meteorological modeling in which all variables are held on an unstaggered grid, but the winds are transformed to a staggered C grid for the gravity wave calculations. An important feature is the use of a new reversible interpolation procedure for the staggering–unstaggering of the winds. This reversible procedure has excellent dispersion properties for geostrophic adjustment of the linearized shallow-water equations, being generally superior to those of the A, B, and C grids. Its dispersion behavior is generally similar to that of the unstaggered Z grid of Randall, which carries divergence and vorticity as primary variables. The scheme has fewer computational overheads than the Z grid.
Abstract
A technique is presented for meteorological modeling in which all variables are held on an unstaggered grid, but the winds are transformed to a staggered C grid for the gravity wave calculations. An important feature is the use of a new reversible interpolation procedure for the staggering–unstaggering of the winds. This reversible procedure has excellent dispersion properties for geostrophic adjustment of the linearized shallow-water equations, being generally superior to those of the A, B, and C grids. Its dispersion behavior is generally similar to that of the unstaggered Z grid of Randall, which carries divergence and vorticity as primary variables. The scheme has fewer computational overheads than the Z grid.
Abstract
It has been demonstrated by McGregor that semi-Lagrangian advection techniques may be efficiently applied to a cubic gnomonic grid on the sphere. Despite the nonorthogonal nature of that grid, the accuracy is superior to that of conventional latitude–longitude grids. The present paper demonstrates even greater accuracy by applying similar techniques to the related conformal-cubic grid devised by Rančić et al.; an important new feature is a simple iterative technique for the inverse calculation of grid coordinates. Advection over the vertices of the grid exhibits none of the problems that occur over the poles of a latitude–longitude grid. A stretched grid configuration is also presented showing further improvements. It is finally shown that the departure points may be interpolated onto a B-grid version and advection performed simply on the staggered grid without loss of accuracy.
Abstract
It has been demonstrated by McGregor that semi-Lagrangian advection techniques may be efficiently applied to a cubic gnomonic grid on the sphere. Despite the nonorthogonal nature of that grid, the accuracy is superior to that of conventional latitude–longitude grids. The present paper demonstrates even greater accuracy by applying similar techniques to the related conformal-cubic grid devised by Rančić et al.; an important new feature is a simple iterative technique for the inverse calculation of grid coordinates. Advection over the vertices of the grid exhibits none of the problems that occur over the poles of a latitude–longitude grid. A stretched grid configuration is also presented showing further improvements. It is finally shown that the departure points may be interpolated onto a B-grid version and advection performed simply on the staggered grid without loss of accuracy.
Abstract
An Eulerian procedure that avoids both interpolation and iteration is proposed for determining the departure points of trajectories. It is applicable to semi-Lagrangian models formulated either on the plane or on the sphere. The technique can achieve a high degree of accuracy; it is also simpler and more economical than other schemes, especially when applied on the sphere. The technique is applied to the cone advection test on the plane, as well as to a “Gaussian hill” problem on a rotating sphere.
Abstract
An Eulerian procedure that avoids both interpolation and iteration is proposed for determining the departure points of trajectories. It is applicable to semi-Lagrangian models formulated either on the plane or on the sphere. The technique can achieve a high degree of accuracy; it is also simpler and more economical than other schemes, especially when applied on the sphere. The technique is applied to the cone advection test on the plane, as well as to a “Gaussian hill” problem on a rotating sphere.
Abstract
In this paper the authors dynamically downscale daily-averaged general circulation model (GCM) datasets over Australia using the Conformal Cubic Atmospheric Model (CCAM). The technique can take advantage of the wider range of Coupled Model Intercomparison Project phase 3 (CMIP3) daily-averaged GCM datasets than is available using 3-hourly datasets. The daily-averaged host GCM atmospheric data are fitted to a time interpolation formula and then differentiated in time to produce a first-order estimate of the atmosphere at 0000 UTC on each simulation day. The processed GCM data are forced into CCAM using a scale-selective filter with an 18° radius. Since this procedure is unable to account for the diurnal cycle, the forcing data are only applied to winds and air temperatures once per day between 800 and 100 hPa. Lateral boundary conditions are not required since CCAM employs a variable-resolution global grid. The technique is evaluated by downscaling daily-averaged 2.5° NCEP reanalyses over Australia at 60-km resolution from 1971 to 2000 and comparing the results to downscaling the 6-hourly reanalyses and to simulating with sea surface temperature (SST)-only forcing. The results show that the daily-averaged downscaling technique can simulate average seasonal maximum and minimum screen temperatures and rainfall similar to those obtained downscaling 6-hourly reanalyses. Some implications for regional climate projections are considered by downscaling four daily-averaged GCM datasets from the twentieth-century climate in coupled models (20C3M) experiment over Australia.
Abstract
In this paper the authors dynamically downscale daily-averaged general circulation model (GCM) datasets over Australia using the Conformal Cubic Atmospheric Model (CCAM). The technique can take advantage of the wider range of Coupled Model Intercomparison Project phase 3 (CMIP3) daily-averaged GCM datasets than is available using 3-hourly datasets. The daily-averaged host GCM atmospheric data are fitted to a time interpolation formula and then differentiated in time to produce a first-order estimate of the atmosphere at 0000 UTC on each simulation day. The processed GCM data are forced into CCAM using a scale-selective filter with an 18° radius. Since this procedure is unable to account for the diurnal cycle, the forcing data are only applied to winds and air temperatures once per day between 800 and 100 hPa. Lateral boundary conditions are not required since CCAM employs a variable-resolution global grid. The technique is evaluated by downscaling daily-averaged 2.5° NCEP reanalyses over Australia at 60-km resolution from 1971 to 2000 and comparing the results to downscaling the 6-hourly reanalyses and to simulating with sea surface temperature (SST)-only forcing. The results show that the daily-averaged downscaling technique can simulate average seasonal maximum and minimum screen temperatures and rainfall similar to those obtained downscaling 6-hourly reanalyses. Some implications for regional climate projections are considered by downscaling four daily-averaged GCM datasets from the twentieth-century climate in coupled models (20C3M) experiment over Australia.
Abstract
This article examines dynamical downscaling with a scale-selective filter in the Conformal Cubic Atmospheric Model (CCAM). In this study, 1D and 2D scale-selective filters have been implemented using a convolution-based scheme, since a convolution can be readily evaluated in terms of CCAM’s native conformal cubic coordinates. The downscaling accuracy of 1D and 2D scale-selective filters is evaluated after downscaling NCEP Global Forecast System analyses for 2006 from 200-km resolution to 60-km resolution over Australia. The 1D scale-selective filter scheme was found to downscale the analyses with similar accuracy to a 2D filter but required significantly fewer computations. The 1D and 2D scale-selective filters were also found to downscale the analyses more accurately than a far-field nudging scheme (i.e., analogous to a boundary-value nudging approach). It is concluded that when the model is required to reproduce the host model behavior above a specified length scale then the use of an appropriately designed 1D scale-selective filter can be a computationally efficient approach to dynamical downscaling for models having a cube-based geometry.
Abstract
This article examines dynamical downscaling with a scale-selective filter in the Conformal Cubic Atmospheric Model (CCAM). In this study, 1D and 2D scale-selective filters have been implemented using a convolution-based scheme, since a convolution can be readily evaluated in terms of CCAM’s native conformal cubic coordinates. The downscaling accuracy of 1D and 2D scale-selective filters is evaluated after downscaling NCEP Global Forecast System analyses for 2006 from 200-km resolution to 60-km resolution over Australia. The 1D scale-selective filter scheme was found to downscale the analyses with similar accuracy to a 2D filter but required significantly fewer computations. The 1D and 2D scale-selective filters were also found to downscale the analyses more accurately than a far-field nudging scheme (i.e., analogous to a boundary-value nudging approach). It is concluded that when the model is required to reproduce the host model behavior above a specified length scale then the use of an appropriately designed 1D scale-selective filter can be a computationally efficient approach to dynamical downscaling for models having a cube-based geometry.
Abstract
A mesoscale wind field model is used to simulate a cyclonic nocturnal eddy which may form over Melbourne under stable conditions with light synoptic winds. Two types of eddy (Mel-I and Mel-II) are identified, with separate formation mechanisms. Mel-I is generated by vorticity shed from the upstream mountain ranges. Daytime anabatic effects enhance the strength of the eddy. When surface heat fluxes are suppressed, the numerical simulations are found to parallel previous to laboratory experiments, but with a somewhat relaxed Froude number formation criterion. The second type of eddy, Mel-II, is generated by interaction of the sea breeze front with the synoptic flow. The eddies are compared with the Kanto plain eddy modeled by Kimura.
Abstract
A mesoscale wind field model is used to simulate a cyclonic nocturnal eddy which may form over Melbourne under stable conditions with light synoptic winds. Two types of eddy (Mel-I and Mel-II) are identified, with separate formation mechanisms. Mel-I is generated by vorticity shed from the upstream mountain ranges. Daytime anabatic effects enhance the strength of the eddy. When surface heat fluxes are suppressed, the numerical simulations are found to parallel previous to laboratory experiments, but with a somewhat relaxed Froude number formation criterion. The second type of eddy, Mel-II, is generated by interaction of the sea breeze front with the synoptic flow. The eddies are compared with the Kanto plain eddy modeled by Kimura.
