Development of a Nested Grid, Second Moment Turbulence Closure Model and Application to the 1982 ASCOT Brush Creek Data Simulation

Yamada, Tetsuji; Bunker, S.

doi:10.1175/1520-0450(1988)027<0562:doangs>2.0.co;2

Cited by 118 publications

(47 citation statements)

References 12 publications

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“…This correction to the Lagrangian model is important when the turbulence intensity is highly non-uniform. Ground level time-integrated concentration is calculated at each computational node by summing the contribution from all particles in the domain multiplied by the sampling interval t. The contribution to a location is calculated using a three-dimensional Gaussian kernel (Yamada and Bunker, 1988). For this study, the particles were representing neutral tracers and no decay, deposition or buoyancy effects were considered.…”

Section: Lagrangian Particle Dispersion Model (Lpdm)mentioning

confidence: 99%

Numerical simulation of particle trajectory and atmospheric dispersion of airborne releases

Raza

Ávila

2009

Meteorological Applications

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Numerical simulation of particle trajectory and atmospheric dispersion has been performed for an airborne accidental release from a nuclear power plant site. A Long-range Particle transport and Dispersion Model (LPDM) based on a Lagrangian approach is developed and tested in this work. The Lagrangian transport/dispersion model is directly coupled with an atmospheric prediction model, RAMS (Regional Atmospheric Modeling System), to provide necessary meteorological fields in a three-dimensional domain. An advantage of this direct coupling is that the meteorological data generated by RAMS can be used directly for trajectory calculations without storage, thus reducing the CPU time consumed in the data storage and retrieval. This effort was done to be able to use this directly coupled modelling system for real-time predictions in case of an accidental release from a potential site.The simulated Lagrangian trajectories were compared with those obtained using observed hourly weather data obtained from an on-site meteorological tower. The results indicated that this one-way coupling between LPDM-RAMS provided almost identical trajectories when compared with those obtained using LPDM alone driven by hourly observed wind data. The comparison demonstrated the reliability of the RAMS meteorological predictions for the site under consideration. The comparison also indicated that LPDM (run in a stand alone mode), with hourly-observed wind data, could also be used for trajectory calculations over flat terrain.The model was developed on a parallel processing computer (SGI workstation, ORIGIN 2000 computer with eight processors) for use in real-time forecast mode. The computational time was about one-third of the simulation time, while using four processors. The model options need to be explored to reduce the computational time further and test its performance for real-time atmospheric dispersion applications.

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Section: Lagrangian Particle Dispersion Model (Lpdm)mentioning

confidence: 99%

Numerical simulation of particle trajectory and atmospheric dispersion of airborne releases

Raza

Ávila

2009

Meteorological Applications

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“…The pair of models used in this study was developed by Yamada Science and Art Inc. to simulate the turbulent transport of airborne materials based on the work of Yamada (1982) and Yamada and Bunker (1988). The models were tested against (a) nocturnal drainage flow in the California Geysers area (Yamada, 1981) with tree canopy effects (Yamada, 1982); (b) pollutant transport in Brush Creek, Colorado (Yamada and Bunker, 1988); (c) dispersion of airborne materials at Vandenberg Air Force Base, California (Yamada et al, 1992); and (d) tracer gas dispersion in southern Nevada to northwestern Arizona (Yamada, 2000).…”

Section: Introductionmentioning

confidence: 99%

“…The models were tested against (a) nocturnal drainage flow in the California Geysers area (Yamada, 1981) with tree canopy effects (Yamada, 1982); (b) pollutant transport in Brush Creek, Colorado (Yamada and Bunker, 1988); (c) dispersion of airborne materials at Vandenberg Air Force Base, California (Yamada et al, 1992); and (d) tracer gas dispersion in southern Nevada to northwestern Arizona (Yamada, 2000). The approach provided satisfactory results in these instances.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional prediction of maize pollen dispersal and cross-pollination, and the effects of windbreaks

Ushiyama

Inoue

et al. 2009

Environ. Biosafety Res.

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With the extensive adoption of transgenic crops, an understanding of transgene flow is essential to manage gene flow to non-GM crops. Thus, a flexible and accurate numerical model is required to assess gene flow through pollen dispersal. A three-dimensional atmospheric model combined with a diffusion transport model would be a useful tool for predicting pollen dispersal since it would be flexible enough to incorporate the effects of factors such as the spatial arrangement of crop combinations, land use, topography, windbreaks, and buildings. We applied such a model to field measurements of gene flow between two adjacent maize (Zea mays) cultivars, with suppression effects due to windbreaks, in an experimental cornfield in Japan. This combined model reproduced the measured cross-pollination distribution quite well in the case of maize plots with plant windbreaks slightly taller than the maize and without windbreaks, but the model underestimated the effect of a 6-m-tall windbreak net beyond 25 m from the donor pollen source on cross-pollination. The underestimation was most probably due to the problem of assimilated wind data. The model showed that the 6-m-tall windbreak and the plant wind break suppressed average cross-pollination rate by about 60% and 30%, respectively. Halftall and coarser mesh windbreak net suppressed cross-pollination rates by 40% by reducing the swirl of donor pollen by reduced wind speed.

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“…These models usually take the topography of the study area into consideration and are able to simulate the L&SB features over an area of several hundred kilometers square at a time (Mahrer and Pielke, 1978;Estoque and Gross, 1981;Kikuchi et al, 1981;Ookouchi and Wakata, 1984;Yamada and Bunker, 1988;Papageorgiou,1988;Kondo,1990;Itoh,1995).…”

Section: Introductionmentioning

confidence: 99%

General Aspects of Land and Sea Breezes in Osaka Bay and Surrounding Area

Mizuma

1995

Journal of the Meteorological Society of Japan

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The general aspects of land and sea breezes in the Osaka Bay area and its environment are revealed from an analysis of the wind data obtained by the AMeDAS. The study area consists of a complex land-sea configuration and a complex topography which includes plains, hilly terrain, and mountainous regions. The land and sea breezes are classified into five types according to the behavior of the sea breeze at several locations in the study area.The most frequently occurring type is characterized in the following. Along the southern coast of Osaka Bay, the sea breeze from Osaka Bay changes with time into that from the Kui Channel. At the same time, along the coast of the Seto Inland Sea the sea breeze contains a predominant easterly component. For this type, several interesting features are further elucidated: (1) the simultaneous onset of the coastal sea breeze and the valley or upslope wind in the mountainous region is clearly seen, especially in the eastern Chugoku area, (2) the meeting of the southerly sea breeze from the Seto Inland Sea and the northerly breeze from the Sea of Japan occurs around the region of the mountain ridges in eastern Chugoku, (3) the alternation of converging sea breezes from surrounding seas forms a uniform southerly sea breeze from the Kui Channel at Awaji Island, (4) the southerly sea breeze continues until the late afternoon in the coastal area of the Kui Channel and Osaka Bay.Other types are discussed and compared with the above type for the mature stage of the sea breeze. The relationships between the occurrence of the land and sea breeze and general meteorological conditions are also analyzed.

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Development of a Nested Grid, Second Moment Turbulence Closure Model and Application to the 1982 ASCOT Brush Creek Data Simulation

Cited by 118 publications

References 12 publications

Numerical simulation of particle trajectory and atmospheric dispersion of airborne releases

Numerical simulation of particle trajectory and atmospheric dispersion of airborne releases

Three-dimensional prediction of maize pollen dispersal and cross-pollination, and the effects of windbreaks

General Aspects of Land and Sea Breezes in Osaka Bay and Surrounding Area

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