Seasonal and Diurnal Patterns of Temperature Inversion Formation and Breakup in a Topographically Complex Urban Environment

Abstract

Measuring air temperatures and winds at several heights in a dense urban area over a nine-month period reveals important seasonal differences in patterns of atmospheric stability, boundary-layer circulation, and other important factors that affect concentrations of air pollutants. The study site in Portland, Oregon includes natural topographic variations from 5 meters above sea level at the shore of a heavily industrialized stretch of the Willamette River, up to 50 meters above sea level atop a nearby bluff where residents often complain of poor air quality. This study installed, and continues to maintain, a network of remote automated weather stations ranging in altitude from river-level to the rooftops of buildings up to eight stories high, spanning a range of 70 m in the vertical from the lowest to highest station altitude, within an area of only 0.25 square km. Prior to this study, the density of weather observations in this area was often insufficient for resolving the conditions relevant to analyzing and monitoring air pollution events, but the significantly higher resolution of meteorological data now available for the area shows promise for addressing these issues. Station measurements include air temperatures and humidities at multiple heights per station, wind direction, wind speed, gust speed, solar radiation in multiple wavelength ranges, direct-diffuse ratios of solar radiation, air pressure, precipitation rates, leaf wetness, soil moisture, thermal-infrared radiant temperatures, kinetic temperatures, and boundary layer fluxes. This study also designed new tethersonde sampling methods to complement the ground-based stations with high-resolution data on vertical profiles of air temperatures, humidity, and winds within the boundary layer. Results show strong, low-level temperature inversions that are often more diurnally-constant in winter than in other seasons, with important implications for local air pollutant concentrations. Applications include improved understanding of local atmospheric patterns, which could help to inform better policies for addressing air quality issues

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