13.3 Comparison of Radiosonde and Sodar/RASS Temperature Measurements in the Lowest Level of the ABL in Complex Terrain

Thursday, 16 January 2020: 9:00 AM
211 (Boston Convention and Exhibition Center)
Anthony J. Sadar, Allegheny County Health Department, Pittsburgh, PA; and D. J. Tauriello

Comparison of Radiosonde and Sodar/RASS Temperature Measurements in the Lowest Level of the ABL in Complex Terrain

Anthony J. Sadar, CCM, Allegheny County Health Department, Air Quality Program, Pittsburgh, PA

Daniel J. Tauriello, MPH Candidate, Northeastern University, Boston, MA

A better understanding of the lowest level of the atmospheric boundary layer (ABL) is important to improved air pollution forecasting, deciphering air quality trends, more-realistic dispersion models, and public health protection. Various equipment is used to sense the lowest level. Here we examine the simultaneous measurements made by a U.S. National Weather Service (NWS) radiosonde and a sodar/RASS unit. Included are observations from a 10 m meteorological tower used to supplement the sodar/RASS measurements.

The area examined is the complex terrain of Allegheny County, Pennsylvania. Analysis is based on radiosonde data collected from the Pittsburgh NWS field office (PIT) in western Allegheny County and sodar/RASS/10 m tower data collected from an industrial site located in Clairton, PA in southern Allegheny County.

Readings taken during the spring of 2019 are evaluated. The PIT radiosonde data are 12Z (7 am EST) readings, while the Clairton sodar/RASS/10 m tower values are measurements made at 11:00Z – 11:15Z (6 am – 6:15 am EST) -- the time of the initiation of the radiosonde launch.

Results reveal differences in topography and suburban (PIT) versus more-urban (Clairton) settings along with differences in the measurement techniques. The impact of synoptic conditions and the urban heat island effect are apparent.

Recommendations are given for siting of equipment and interpretation of results with respect to understanding the ABL, improving air pollution forecasting, deciphering air quality trends, developing more-realistic dispersion models, and protecting public health.

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