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21.
We carry out model studies of turbulence quantities for flow over two-dimensional hills using a non-hydrostatic version of the Regional Atmospheric Modeling System (RAMS). We test two turbulence closure models: the first one is an explicit Algebraic Reynolds Stress Model (ARSM) and the second one is a combination of the ARSM and a transport equation for the shear stress {ovuw}. Model predictions for the turbulent stresses are compared with data from a wind-tunnel experiment containing isolated two-dimensional hills of varying slope. From the comparison, it is concluded that the first model can only predict the normal stresses adequately while the second model provides satisfactory predictions for the normal stresses as well as giving an improved result for the shear stress {ovuw}.  相似文献   
22.
We study turbulent flow over two-dimensional hills. The Reynolds stresses are represented by a second-order closure model, where advection, diffusion, production and dissipation processes are all accounted for. We solve a full set of primitive non-hydrostatic dynamic equations for mean flow quantities using a finite-difference numerical method. The model predictions for the mean velocity and Reynolds stresses are compared with the measured data from a wind-tunnel experiment that simulates the atmospheric boundary layer. The agreement is good. The performance of the second-order closure model is also compared withthat of lower level turbulence models, including the eddy-viscositymodel and algebraic Reynolds stress models. It is concluded that thepresent closure is a considerable improvement over the other modelsin representing various physical effects in flow over hills. Thefeasibility of running a finite-difference numerical simulationincorporating a full second-order closure model on an IBM workstationis also demonstrated.  相似文献   
23.
We carry out climate simulations for 1880–2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880–2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.  相似文献   
24.
Why a variableG?     
Since a possible time variability ofG has received renewed attention (Wesson and Goodson, 1981), we think it is important to stress a conceptual aspect so far not sufficiently appreciated and which puts the variability ofG in a much wider context. VariableG is a popular but incomplete representation of a much deeper problem:Is the Strong Equivalence Principle (SEP) valid?  相似文献   
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