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Elastic lidar measurements of summer nocturnal low level jet events over Baltimore, Maryland

Abstract

Elastic lidar (532 nm) measurements were carried out by the Atmospheric Lidar Group at the University of Maryland, Baltimore County (UMBC, 39.25° N, 76.70° W) during meteorological conditions that favored the formation of the nocturnal low level jet (NLLJ) over the United States Mid-Atlantic region. The lidar timeseries from three case studies showed the intrusion of the NLLJ air mass into the nocturnal boundary layer (NBL) and the subsequent displacement of aerosols that were used for tracing atmospheric motion. Three distinctive regions were identified in the timeseries: 1) a wedging zone within the residual layer, that was heavily laden with aerosols, at the onset of the NLLJ, 2) a lofted layer of particulates above the “clean” jet core, and 3) a region where the lofted layer collapsed that was conterminous with the diminishing NLLJ below, and characterized by downward mixing analogous to turbulent wake regions. The National Oceanic and Atmospheric Administration’s (NOAA) Rapid Update Cycle (RUC, grid 252) model was used to analyze the horizontal extent and vertical structure of the NLLJ and to compare with observations acquired during these events. A conceptual model is proposed to highlight the role of the NLLJ, during similar weather patterns, in the regional transport of pollutants and their impact on poor air quality episodes in the Mid-Atlantic United States.

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Acknowledgments

The authors wish gratefully to acknowledge support for this study provided by the Maryland Department of the Environment (Contract U00P7201032), and NOAA-CREST CCNY Foundation CREST Grant (Contract NA11SEC481004).

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Correspondence to Ruben Delgado.

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Delgado, R., Rabenhorst, S.D., Demoz, B.B. et al. Elastic lidar measurements of summer nocturnal low level jet events over Baltimore, Maryland. J Atmos Chem 72, 311–333 (2015). https://doi.org/10.1007/s10874-013-9277-2

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Keywords

  • Lidar
  • Air quality
  • Low level jets
  • Ozone
  • Particulate matter
  • Remote sensing