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  • Author or Editor: R. Michael Reynolds x
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Steven R. Hanna, Michael J. Brown, Fernando E. Camelli, Stevens T. Chan, William J. Coirier, Olav R. Hansen, Alan H. Huber, Sura Kim, and R. Michael Reynolds

Computational fluid dynamics (CFD) model simulations of urban boundary layers have improved in speed and accuracy so that they are useful in assisting in planning emergency response activities related to releases of chemical or biological agents into the atmosphere in large cities such as New York, New York. In this paper, five CFD models [CFD-Urban, Finite Element Flow (FEFLO), Finite Element Model in 3D and Massively-Parallel version (FEM3MP), FLACS, and FLUENT–Environmental Protection Agency (FLUENT-EPA)] have been applied to the same 3D building data and geographic domain in Manhattan, using approximately the same wind input conditions. Wind flow observations are available from the Madison Square Garden 2005 (MSG05) field experiment. Plots of the CFD models' simulations and the observations of near-surface wind fields lead to the qualitative conclusion that the models generally agree with each other and with field observations over most parts of the computational domain, within typical atmospheric uncertainties of a factor of 2. The results are useful to emergency responders, suggesting, for example, that transport of a release at street level in a large city could extend for a few blocks in the upwind and crosswind directions. There are still key differences among the models for certain parts of the domain. Further examination of the differences among the models and the observations are necessary in order to understand the causal relationships.

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David C. Fritts, Ronald B. Smith, Michael J. Taylor, James D. Doyle, Stephen D. Eckermann, Andreas Dörnbrack, Markus Rapp, Bifford P. Williams, P.-Dominique Pautet, Katrina Bossert, Neal R. Criddle, Carolyn A. Reynolds, P. Alex Reinecke, Michael Uddstrom, Michael J. Revell, Richard Turner, Bernd Kaifler, Johannes S. Wagner, Tyler Mixa, Christopher G. Kruse, Alison D. Nugent, Campbell D. Watson, Sonja Gisinger, Steven M. Smith, Ruth S. Lieberman, Brian Laughman, James J. Moore, William O. Brown, Julie A. Haggerty, Alison Rockwell, Gregory J. Stossmeister, Steven F. Williams, Gonzalo Hernandez, Damian J. Murphy, Andrew R. Klekociuk, Iain M. Reid, and Jun Ma


The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.

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