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J. L. Mcgregor and W. Bourke

Abstract

Vertical mode initialization (VMI) in a limited-area model is compared with normal mode initialization (NMI) as performed in a spectral model. Upon interpolating all datasets from the hemispheric spectral system, the greatest reduction of spurious oscillations in the limited-area system is found when its own VMI initialization scheme is used. The essential similarity of VMI and NMI is demonstrated by the close similarity of the vertical velocities and MSL pressure tendencies as derived in the respective systems. Reasonable agreement is found between regions of upward vertical velocity and cloudiness in the satellite imagery. The instantaneous mean-sea-level (MSL) pressure tendencies show qualitative agreement with time-averaged analysis tendencies over ocean areas, but disagree with tendencies over the land, seemingly as a result of diurnal heating effects.

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W. Bourke and J. L. Mcgregor

Abstract

A vertical mode initialization scheme for a limited area baroclinic primitive equations prediction model is proposed. The scheme is based on the approach employed in nonlinear normal mode initialization but incorporates a substantial simplification: the linearized equations with respect to which the model modes are defined admit only gravity modes. A variational constraint on induced increments is possible within the scheme. In the framework of the Australian Region Primitive Equations model the approach has been found to effectively control spurious model oscillations. A number of filtering conditions are considered and tested within the overall approach of this vertical mode scheme.

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J. L. McGregor and L. M. Leslie

Abstract

It is shown that semi-implicit time differencing on a nonstaggered grid using centered time and space derivatives leads to a decoupling into four separate solutions on different subgrids. This deficiency may be successfully overcome by combining weighted averages of Laplacian operators on the subgrids. However, a far more satisfactory approach is shown to be the use of a staggered grid which appears to be a natural choice for the semi-implicit scheme.

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G. A. Mills and J. L. McGregor

Abstract

A previously reported 9-day limited area data assimilation experiment has been reported, incorporating a recently developed nonlinear vertical mode initialization scheme. It is shown that the initialization scheme significantly reduces surfaces pressure oscillations during the model integration, producing more accurate guess fields for each analysis. It is demonstrated, by means of objective verification statistics and by means of a case study, that these more accurate guess fields result in improved analyses and a small increase in skill of 24 h prognoses based on these analyses.

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J. L. McGregor, L. M. Leslie, and D. J. Gauntlett

Abstract

The most recent version of the Australian Numerical Meteorology Research Centre limited-area primitive equations model is described in this paper. A staggered grid system has been introduced, the semi-implicit equations have been transformed with temperature as the primary variable, and an Arakawa-Schubert-type cumulus convection scheme included.

The model has been assessed, both objectively and subjectively, in a day-to-day operational trial for the Australian region extending over a period of four months. By comparison with the operational filtered equations model, the new model is found to be superior especially for tropospheric predictions. As a result of this trial, the model has been accepted as the new regional operational model by the Australian Bureau of Meteorology and was implemented during September 1977.

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H. Zhang, J. L. McGregor, A. Henderson-Sellers, and J. J. Katzfey

Abstract

A multimode Chameleon Surface Model (CHASM) with different levels of complexity in parameterizing surface energy balance is coupled to a limited-area model (DARLAM) to investigate the impacts of complexity in land surface representations on the model simulation of a tropical synoptic event. A low pressure system is examined in two sets of numerical experiments to discuss the following. (i) Does land surface parameterization influence regional numerical weather simulations? (ii) Can the complexity of land surface schemes in numerical models be represented by parameter tuning? The model-simulated tracks of the low pressure center do not, overall, show large sensitivity to the different CHASM modes coupled to the limited-area model. However, the landing position of the system, as one measurement of the track difference, can be influenced by several degrees in latitude and about one degree in longitude. Some of the track differences are larger than the intrinsic numerical noise in the model estimated from two sets of random perturbation runs. In addition, the landing time of the low pressure system can differ by about 14 h. The differences in the model-simulated central pressure exceed the model intrinsic numerical noise and such variations consistent with the differences seen in simulated surface fluxes. Furthermore, different complexity in the land surface scheme can significantly affect the model rainfall and temperature simulations associated with the low center, with differences in rainfall up to 20 mm day−1 and in surface temperature up to 2°C. Explicitly representing surface resistance and bare ground evaporation components in CHASM produces the most significant impacts on the surface processes. Results from the second set of experiments, in which the CHASM modes are calibrated by parameter tuning, demonstrate that the effects of the physical processes represented by extra complexity in some CHASM modes cannot be substituted for by parameter tuning in simplified land surface schemes.

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Terry L. Hart, William Bourke, Bryant J. McAvaney, Bruce W. Forgan, and John L. McGregor

Abstract

Results are presented for perpetual January and July general circulation simulations using the Australian Bureau of Meteorology Research Centre global spectral model. Particular emphasis is placed on the impact of changes in the physical parameterizations and horizontal resolution on the modeled fields. The results include variances and eddy transports as well as zonal means and geographical distributions. Of the experiments conducted the most satisfactory results were obtained using stability-dependent vertical diffusion and a combination of the Kuo scheme for deep convection and the Tiedtke shallow convection scheme.

The simulation of the polar night region of the stratosphere in January was much more realistic than in results obtained using an earlier version of the model. The improvement is attributed to the revised radiation code, supporting the conclusions of Ramanathan et al. on the sensitivity of simulations of this region of the atmosphere to the treatment of radiative processes.

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H. Zhang, A. Henderson-Sellers, A. J. Pitman, C. E. Desborough, J. L. McGregor, and J. J. Katzfey

Abstract

By coupling a multimode land surface scheme with a regional climate model, three scientific issues are addressed in this paper: (i) the regional model's sensitivity to the different levels of complexity presented by the land surface parameterization, (ii) relative model sensitivity to the land surface parameterization as compared with that to other model physical representations, and, (iii) following offline calibration, whether different complexity in the land surface representation leads to different model performance in the coupled experiments. In this study, a version of a regional model [Division of Atmospheric Research Limited Area Model (DARLAM)] is coupled with the Chameleon Surface Model (CHASM). Three sets of experiments are analyzed in this paper, employing six different complexity modes of CHASM. Model results from these coupled experiments show that the regional model is sensitive overall to different complexities represented in the CHASM modes. Moreover, these model sensitivities are larger than the model's intrinsic sensitivity to the perturbation of its initial conditions. The sensitivity is retained in a series of model configurations employing different vertical resolutions and convection schemes. Different complexities in the land surface representation lead to 10–30 W m−2 changes in surface evaporation and 0.5–2.5-K changes in surface temperature. In comparing different sets of coupled experiments, it is noted that, because of the complex feedbacks involved in air–land interactions, land surface parameterizations can induce quantitatively similar model sensitivity to that from changing other model aspects such as vertical resolution and convection parameterization. Although different CHASM modes can be calibrated to show similar offline results, when coupled with DARLAM these similarities between different complexity modes are significantly reduced. The sensitivity revealed in the coupled model simulations underlines the importance of understanding the feedbacks between model land surface parameterization and other physical components. More important, these results show that complexity in land surface representation cannot be substituted by tuning of parameters such as the surface or stomatal resistance, because offline agreement is not maintained in coupled simulations.

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Faye T. Cruz, Andrew J. Pitman, John L. McGregor, and Jason P. Evans

Abstract

Using a coupled atmosphere–land surface model, simulations were conducted to characterize the regional climate changes that result from the response of stomates to increases in leaf-level carbon dioxide (CO2) under differing conditions of moisture availability over Australia. Multiple realizations for multiple Januarys corresponding to dry and wet years were run, where only the leaf-level CO2 was varied at 280, 375, 500, 650, 840, and 1000 ppmv and the atmospheric CO2 was fixed at 375 ppmv. The results show the clear effect of increasing leaf-level CO2 on the transpiration via the stomatal response, particularly when sufficient moisture is available. Statistically significant reductions in transpiration generally lead to a significantly warmer land surface with decreases in rainfall. Increases in CO2 lead to increases in the magnitude and areal extent of the statistically significant mean changes in the surface climate. However, the results also show that the availability of moisture substantially affects the effect of increases in the leaf-level CO2, particularly for a moisture-limited region. The physiological feedback can indirectly lead to more rainfall via changes in the low-level moisture convergence and vertical velocity, which result in a cooling simulated over Western Australia. The significant changes in the surface climate presented in the results suggest that it is still important to incorporate these feedbacks in future climate assessments and projections for Australia. The influence of moisture availability also indicates that the capacity of the physiological feedback to affect the future climate may be affected by uncertainties in rainfall projections, particularly for water-stressed regions such as Australia.

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J. D. Price, S. Lane, I. A. Boutle, D. K. E. Smith, T. Bergot, C. Lac, L. Duconge, J. McGregor, A. Kerr-Munslow, M. Pickering, and R. Clark

Abstract

Fog is a high-impact weather phenomenon affecting human activity, including aviation, transport, and health. Its prediction is a longstanding issue for weather forecast models. The success of a forecast depends on complex interactions among various meteorological and topographical parameters; even very small changes in some of these can determine the difference between thick fog and good visibility. This makes prediction of fog one of the most challenging goals for numerical weather prediction. The Local and Nonlocal Fog Experiment (LANFEX) is an attempt to improve our understanding of radiation fog formation through a combined field and numerical study. The 18-month field trial was deployed in the United Kingdom with an extensive range of equipment, including some novel measurements (e.g., dew measurement and thermal imaging). In a hilly area we instrumented flux towers in four adjacent valleys to observe the evolution of similar, but crucially different, meteorological conditions at the different sites. We correlated these with the formation and evolution of fog. The results indicate new quantitative insight into the subtle turbulent conditions required for the formation of radiation fog within a stable boundary layer. Modeling studies have also been conducted, concentrating on high-resolution forecast models and research models from 1.5-km to 100-m resolution. Early results show that models with a resolution of around 100 m are capable of reproducing the local-scale variability that can lead to the onset and development of radiation fog, and also have identified deficiencies in aerosol activation, turbulence, and cloud micro- and macrophysics, in model parameterizations.

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