Synoptic Classification and Physical Model Experiments to Guide Field Studies in Complex Terrain

Neil S. Berman Environmental Fluid Dynamics Program, Arizona State University, Tempe, Arizona

Search for other papers by Neil S. Berman in
Current site
Google Scholar
PubMed
Close
,
Don L. Boyer Environmental Fluid Dynamics Program, Arizona State University, Tempe, Arizona

Search for other papers by Don L. Boyer in
Current site
Google Scholar
PubMed
Close
,
Anthony J. Brazel Environmental Fluid Dynamics Program, Arizona State University, Tempe, Arizona

Search for other papers by Anthony J. Brazel in
Current site
Google Scholar
PubMed
Close
,
Sandra W. Brazel Environmental Fluid Dynamics Program, Arizona State University, Tempe, Arizona

Search for other papers by Sandra W. Brazel in
Current site
Google Scholar
PubMed
Close
,
Rui-Rong Chen Environmental Fluid Dynamics Program, Arizona State University, Tempe, Arizona

Search for other papers by Rui-Rong Chen in
Current site
Google Scholar
PubMed
Close
,
Harindra J. S. Fernando Environmental Fluid Dynamics Program, Arizona State University, Tempe, Arizona

Search for other papers by Harindra J. S. Fernando in
Current site
Google Scholar
PubMed
Close
, and
Mark J. Fitch Environmental Fluid Dynamics Program, Arizona State University, Tempe, Arizona

Search for other papers by Mark J. Fitch in
Current site
Google Scholar
PubMed
Close
Full access

Abstract

Synoptic classification is used to identify meteorological conditions characteristic of high-pollution periods at Nogales, Arizona. Low surface winds determined by local surface cooling at night with little vertical mixing were found to be most important. This condition was simulated in a 0.79-m-square box filled with water with the lower surface made to model a 12-km-square region of the surface topography of the United States-Mexico border at Nogales. The aluminum base was cooled to induce the downslope flows. Photographs of dye initially placed on the surface at many locations were used to obtain a set of surface velocities that formed the input to the Diagnostic Wind Model (DWM). The DWM provided hourly velocity data with grids of 500- and 250-m spacings.

The similarity arguments used to analyze the relationship of the physical model to the atmosphere are discussed. Although the magnitude of the wind vectors in the physical model cannot be matched to the atmosphere, the directions can be used to assess the accuracy of the wind field obtained from a sparse set of field sites. A range of locations of these sites is analyzed to determine a strategy for obtaining sufficient wind data to depict satisfactory wind fields in this complex terrain.

Abstract

Synoptic classification is used to identify meteorological conditions characteristic of high-pollution periods at Nogales, Arizona. Low surface winds determined by local surface cooling at night with little vertical mixing were found to be most important. This condition was simulated in a 0.79-m-square box filled with water with the lower surface made to model a 12-km-square region of the surface topography of the United States-Mexico border at Nogales. The aluminum base was cooled to induce the downslope flows. Photographs of dye initially placed on the surface at many locations were used to obtain a set of surface velocities that formed the input to the Diagnostic Wind Model (DWM). The DWM provided hourly velocity data with grids of 500- and 250-m spacings.

The similarity arguments used to analyze the relationship of the physical model to the atmosphere are discussed. Although the magnitude of the wind vectors in the physical model cannot be matched to the atmosphere, the directions can be used to assess the accuracy of the wind field obtained from a sparse set of field sites. A range of locations of these sites is analyzed to determine a strategy for obtaining sufficient wind data to depict satisfactory wind fields in this complex terrain.

Save