Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 3.668
IF3.668
IF 5-year value: 3.707
IF 5-year
3.707
CiteScore value: 6.3
CiteScore
6.3
SNIP value: 1.383
SNIP1.383
IPP value: 3.75
IPP3.75
SJR value: 1.525
SJR1.525
Scimago H <br class='widget-line-break'>index value: 77
Scimago H
index
77
h5-index value: 49
h5-index49
Preprints
https://doi.org/10.5194/amt-2020-227
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-227
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  31 Aug 2020

31 Aug 2020

Review status
This preprint is currently under review for the journal AMT.

LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part I: Theoretical framework

Stefano Letizia, Lu Zhan, and Giacomo Valerio Iungo Stefano Letizia et al.
  • Wind Fluids and Experiments (WindFluX) Laboratory, Mechanical Engineering Department, The University of Texas at Dallas, 800 W Campbell Rd, 75080 Richardson, TX, USA

Abstract. A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for optimal design of LiDAR scans and retrieval of the velocity statistical moments is proposed. The LiSBOA represents an adaptation of the classical Barnes scheme for the statistical analysis of unstructured experimental data in N-dimensional spaces and it is a suitable technique for the evaluation over a structured Cartesian grid of the statistics of scalar fields sampled through scanning LiDARs. The LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. This revisited theoretical framework for the Barnes objective analysis enables the formulation of guidelines for optimal design of LiDAR experiments and efficient application of the LiSBOA for the post-processing of LiDAR measurements. The optimal design of LiDAR scans is formulated as a two cost-function optimization problem including the minimization of the percentage of the measurement volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field. The optimal design of the LiDAR scans also guides the selection of the smoothing parameter and the total number of iterations to use for the Barnes scheme.

Stefano Letizia et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Stefano Letizia et al.

Stefano Letizia et al.

Viewed

Total article views: 177 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
131 41 5 177 7 5
  • HTML: 131
  • PDF: 41
  • XML: 5
  • Total: 177
  • BibTeX: 7
  • EndNote: 5
Views and downloads (calculated since 31 Aug 2020)
Cumulative views and downloads (calculated since 31 Aug 2020)

Viewed (geographical distribution)

Total article views: 101 (including HTML, PDF, and XML) Thereof 101 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 22 Nov 2020
Publications Copernicus
Download
Short summary
A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of LiDAR scans and retrieval of the velocity statistics is proposed.The LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. The optimal design of LiDAR scans is formulated as a two cost-function optimization problem including the minimization of the volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field.
A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of LiDAR scans and...
Citation