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Title: Atmospheric Boundary Layer Classification With Doppler Lidar

Abstract

We present a method using Doppler lidar data for identifying the main sources of turbulent mixing within the atmospheric boundary layer. The method identifies the presence of turbulence and then assigns a turbulent source by combining several lidar quantities: attenuated backscatter coefficient, vertical velocity skewness, dissipation rate of turbulent kinetic energy, and vector wind shear. Both buoyancy-driven and shear-driven situations are identified, and the method operates in both clear-sky and cloud-topped conditions, with some reservations in precipitation. To capture the full seasonal cycle, the classification method was applied to more than 1 year of data from two sites, Hyytiälä, Finland, and Jülich, Germany. Analysis showed seasonal variation in the diurnal cycle at both sites; a clear diurnal cycle was observed in spring, summer, and autumn seasons, but due to their respective latitudes, a weaker cycle in winter at Jülich, and almost non-existent at Hyytiälä. Additionally, there are significant contributions from sources other than convective mixing, with cloud-driven mixing being observed even within the first 500 m above ground. Also evident is the considerable amount of nocturnal mixing within the lowest 500 m at both sites, especially during the winter. The presence of a low-level jet was often detected when sourcesmore » of nocturnal mixing were diagnosed as wind shear. The classification scheme and the climatology extracted from the classification provide insight into the processes responsible for mixing within the atmospheric boundary layer, how variable in space and time these can be, and how they vary with location.« less

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [4]
  1. Univ. of Helsinki (Finland)
  2. Institute for Geophysics and Meteorology, University of Cologne, Cologne Germany
  3. Univ. of Helsinki (Finland); Vaisala Oyj, Vantaa (Finland); Finnish Meteorological Inst. (FMI), Helsinki (Finland)
  4. Finnish Meteorological Inst. (FMI), Helsinki (Finland); Univ. of Reading (United Kingdom)
Publication Date:
Research Org.:
Univ. of Helsinki (Finland)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1539731
Alternate Identifier(s):
OSTI ID: 1463196
Grant/Contract Number:  
SC0017338
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research: Atmospheres
Additional Journal Information:
Journal Volume: 123; Journal Issue: 15; Journal ID: ISSN 2169-897X
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Meteorology & Atmospheric Sciences

Citation Formats

Manninen, A. J., Marke, T., Tuononen, M., and O'Connor, E. J. Atmospheric Boundary Layer Classification With Doppler Lidar. United States: N. p., 2018. Web. doi:10.1029/2017jd028169.
Manninen, A. J., Marke, T., Tuononen, M., & O'Connor, E. J. Atmospheric Boundary Layer Classification With Doppler Lidar. United States. doi:10.1029/2017jd028169.
Manninen, A. J., Marke, T., Tuononen, M., and O'Connor, E. J. Fri . "Atmospheric Boundary Layer Classification With Doppler Lidar". United States. doi:10.1029/2017jd028169. https://www.osti.gov/servlets/purl/1539731.
@article{osti_1539731,
title = {Atmospheric Boundary Layer Classification With Doppler Lidar},
author = {Manninen, A. J. and Marke, T. and Tuononen, M. and O'Connor, E. J.},
abstractNote = {We present a method using Doppler lidar data for identifying the main sources of turbulent mixing within the atmospheric boundary layer. The method identifies the presence of turbulence and then assigns a turbulent source by combining several lidar quantities: attenuated backscatter coefficient, vertical velocity skewness, dissipation rate of turbulent kinetic energy, and vector wind shear. Both buoyancy-driven and shear-driven situations are identified, and the method operates in both clear-sky and cloud-topped conditions, with some reservations in precipitation. To capture the full seasonal cycle, the classification method was applied to more than 1 year of data from two sites, Hyytiälä, Finland, and Jülich, Germany. Analysis showed seasonal variation in the diurnal cycle at both sites; a clear diurnal cycle was observed in spring, summer, and autumn seasons, but due to their respective latitudes, a weaker cycle in winter at Jülich, and almost non-existent at Hyytiälä. Additionally, there are significant contributions from sources other than convective mixing, with cloud-driven mixing being observed even within the first 500 m above ground. Also evident is the considerable amount of nocturnal mixing within the lowest 500 m at both sites, especially during the winter. The presence of a low-level jet was often detected when sources of nocturnal mixing were diagnosed as wind shear. The classification scheme and the climatology extracted from the classification provide insight into the processes responsible for mixing within the atmospheric boundary layer, how variable in space and time these can be, and how they vary with location.},
doi = {10.1029/2017jd028169},
journal = {Journal of Geophysical Research: Atmospheres},
number = 15,
volume = 123,
place = {United States},
year = {2018},
month = {6}
}

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