Journal metrics

Journal metrics

  • IF value: 3.248 IF 3.248
  • IF 5-year value: 3.650 IF 5-year 3.650
  • CiteScore value: 3.37 CiteScore 3.37
  • SNIP value: 1.253 SNIP 1.253
  • SJR value: 1.869 SJR 1.869
  • IPP value: 3.29 IPP 3.29
  • h5-index value: 47 h5-index 47
  • Scimago H index value: 60 Scimago H index 60
Discussion papers | Copyright
https://doi.org/10.5194/amt-2018-80
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 12 Apr 2018

Research article | 12 Apr 2018

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Atmospheric Measurement Techniques (AMT) and is expected to appear here in due course.

Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign

Nicola Bodini1, Julie K. Lundquist1,2, and Rob K. Newsom3 Nicola Bodini et al.
  • 1Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado, USA
  • 2National Renewable Energy Laboratory, Golden, Colorado, USA
  • 3Pacific Northwest National Laboratory, Richland, Washington, USA

Abstract. Despite turbulence being a fundamental transport process in the boundary layer, the capability of current numerical models to represent it is undermined by the limits of the adopted assumptions, notably that of local equilibrium. Here we leverage the potential of extensive observations in determining the variability of turbulence dissipation rate (ε). These observations can provide insights towards the understanding of the scales at which the major assumption of local equilibrium between generation and dissipation of turbulence is invalid. Typically, observations of ε require time- and labor-intensive measurements from sonic and/or hot-wire anemometers. We explore the capability of wind Doppler lidars to provide measurements of ε. We refine and extend an existing method to accommodate different atmospheric stability conditions. To validate our approach, we estimate ε from four wind Doppler lidars during the 3-month XPIA campaign at the Boulder Atmospheric Observatory (Colorado), and we assess the uncertainty of the proposed method by data inter-comparison with sonic anemometer measurements of ε. Our analysis of this extensive dataset provides understanding of the climatology of turbulence dissipation over the course of the campaign. Further, the variability of ε with atmospheric stability, height, and wind speed is also assessed. Finally, we present how ε increases as nocturnal turbulence is generated during low-level jet events.

Download & links
Nicola Bodini et al.
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Nicola Bodini et al.
Data sets

XPIA, Sonic Anemometer, BAO Tower, All levels L. Bianco https://doi.org/10.21947/1328878

Nicola Bodini et al.
Viewed
Total article views: 315 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
231 79 5 315 15 4 6
  • HTML: 231
  • PDF: 79
  • XML: 5
  • Total: 315
  • Supplement: 15
  • BibTeX: 4
  • EndNote: 6
Views and downloads (calculated since 12 Apr 2018)
Cumulative views and downloads (calculated since 12 Apr 2018)
Viewed (geographical distribution)
Total article views: 315 (including HTML, PDF, and XML) Thereof 311 with geography defined and 4 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited
Saved
No saved metrics found.
Discussed
No discussed metrics found.
Latest update: 17 Jul 2018
Publications Copernicus
Download
Short summary
Turbulence within the atmospheric boundary layer is critically important to transfer heat, momentum and moisture. Currently, improved turubulence parametrizations are crucially needed to refine the accuracy of model results at fine horizontal scales. In this study, we calculate turbulence dissipation rate from sonic anemometers and discuss a novel approach to derive turbulence dissipation from profiling lidar measurements.
Turbulence within the atmospheric boundary layer is critically important to transfer heat,...
Citation
Share