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Francis S. Binkowski
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Jack H. Shreffler and Francis S. Binkowski

Abstract

Strong thunderstorm activity over Iowa on two successive afternoons was the apparent source of pressure-jump lines (PJL's) which moved SSE at 50 km h−1 through the nocturnal boundary layer and were detected by National Weather Service (NWS) stations as far away as Paducah, Kentucky. Rainshowers and thunder were reported at many NWS stations as the PJL's passed.

The Regional Air Monitoring System (RAMS) network at St. Louis provided detailed information on the PJL'S. Arrival there was indicated by an abrupt pressure rise of 1.5 mb, a near reversal of the surface flow, and a vertical displacement of 750 m extending through the lower 4 km of the atmosphere. The passage of each PJL was coincident with the turbulent collapse of the nocturnal jet. The observations of the PJL events seem indicative of an internal bore and are similar to those of the Morning Glory seen in northern Australia. We speculate that the bore originates from a late afternoon convergence produced by thunderstorm outflow and opposing low-level winds involving the nocturnal jet.

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David R. Stauffer, Nelson L. Seaman, and Francis S. Binkowski

Abstract

A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or nudging has been developed and evaluated in the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Limited-Area Mesoscale Model. It was shown in Part I of this study that continuous assimilation of standard-resolution rawinsonde observations throughout a model integration, rather than at only the initial time, can successfully limit large model error growth (amplitude and phase errors) while the model maintains intervariable consistency and generates realistic mesoscale structures not resolved by the data. The purpose of this paper is to further refine the previously reported FDDA strategy used to produce “dynamic analyses” of the atmosphere by investigating the effects of data assimilation within the planetary boundary layer (PBL).

The data used for assimilation include conventional synoptic-scale rawinsonde data and mesoalpha-scale surface data. The main objective of this study is to determine how to effectively utilize the combined strength of these two simple data systems while avoiding their individual weaknesses. Ten experiments, which use a 15-layer version of the model, are evaluated for two midlatitude, real-data cases.

It is found that the homogenizing effect of vertical mixing during free convective conditions allows the three-hourly surface-layer wind and mixing ratio observations to be applied throughout the model PBL according to an idealized conceptual model of boundary-layer structure. Single-level surface temperature observations, however, are often poorly representative of the boundary layer as a whole (e.g., shallow superadiabatic layers, nocturnal inversions), and are more attractive for FDDA applications when additional vertical profile information is available. Assimilation of surface wind and moisture data throughout the model PBL generally showed a positive impact on the simulated precipitation by better reserving the low-level structure and movement of systems (e.g., cyclones, fronts) during the 12-h periods bracketed by the standard rawinsonde data. Improved precipitation simulations due to assimilation of surface data are also possible even in cases with weak large-scale forcing, because a significant portion of the vertically integrated moisture convergence often occurs in the boundary layer. Overall, the best dynamic analyses of precipitation, PBL depth, surface-layer temperature and tropospheric mass and wind fields were obtained by nudging to analyses of rawinsonde wind, temperature, and moisture above the model PBL and to analyses of surface-layer wind and moisture within the model PBL.

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Francis S. Binkowski, Saravanan Arunachalam, Zachariah Adelman, and Joseph P. Pinto

Abstract

A prototype online photolysis module has been developed for the Community Multiscale Air Quality (CMAQ) modeling system. The module calculates actinic fluxes and photolysis rates (j values) at every vertical level in each of seven wavelength intervals from 291 to 850 nm, as well as the total surface irradiance and aerosol optical depth within each interval. The module incorporates updated opacity at each time step, based on changes in local ozone, nitrogen dioxide, and particle concentrations. The module is computationally efficient and requires less than 5% more central processing unit time than using the existing CMAQ “lookup” table method for calculating j values. The main focus of the work presented here is to describe the new online module as well as to highlight the differences between the effective cross sections from the lookup-table method currently being used and the updated effective cross sections from the new online approach. Comparisons of the vertical profiles for the photolysis rates for nitrogen dioxide (NO2) and ozone (O3) from the new online module with those using the effective cross sections from a standard CMAQ simulation show increases in the rates of both NO2 and O3 photolysis.

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Robert E. Eskridge, Francis S. Binkowski, J. C. R. Hunt, Terry L. Clark, and Kenneth L. Demerjian

Abstract

A finite-difference highway model is presented which uses surface layer similarity theory and a vehicle wake theory to determine the atmospheric structure along a roadway. Surface similarity is used to determine the wind profile and eddy diffusion profiles in the ambient atmosphere. The ambient atmosphere is treated as a basic-state atmosphere on which the disturbances due to vehicle wakes are added. A conservation of species equation is then solved using an upstream-flux corrected technique which insures positive concentrations. Simulation results from the highway model are compared with 58 half-hour periods of data (meteorological and SF6 tracer) taken by General Motors. The results show that the predictions of this model are closer to the observations than those of the Gaussian-formulated EPA highway model (HIWAY).

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