Notes and correspondence

An automated algorithm for detection of hydrometeor returns in micropulse lidar data

Eugene Edmund Clothiaux, G. G. Mace, T. P. Ackerman, Timothy Joseph Kane, J. D. Spinhirne, V. S. Scott

Research output: Contribution to journalArticle

42 Citations (Scopus)

Abstract

A cloud detection algorithm for a low power micropulse lidar is presented that attempts to identify all of the significant power returns from the vertical column above the lidar at all times. The main feature of the algorithm is construction of lidar power return profiles during periods of clear sky against which cloudy-sky power returns are compared. This algorithm supplements algorithms designed to detect cloud-base height in that the tops of optically thin clouds are identified and it provides an alternative approach to algorithms that identify significant power returns by analysis of changes in the slope of the backscattered powers with height. The cloud-base heights produced by the current algorithm during nonprecipitating periods are comparable with the results of a cloud-base height algorithm applied to the same data. Although an objective validation of algorithm performance on high, thin cirrus is lacking because of no truth data, the current algorithm produces few false positive and false negative classifications as determined through manual comparison of the original photoelectron count data to the final cloud mask image.

Original languageEnglish (US)
Pages (from-to)1035-1042
Number of pages8
JournalJournal of Atmospheric and Oceanic Technology
Volume15
Issue number4
DOIs
StatePublished - Jan 1 1998

Fingerprint

Optical radar
lidar
detection
cirrus
clear sky
Photoelectrons
Masks

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Atmospheric Science

Cite this

@article{66a7fdf4647a4f198492549692397bf3,
title = "Notes and correspondence: An automated algorithm for detection of hydrometeor returns in micropulse lidar data",
abstract = "A cloud detection algorithm for a low power micropulse lidar is presented that attempts to identify all of the significant power returns from the vertical column above the lidar at all times. The main feature of the algorithm is construction of lidar power return profiles during periods of clear sky against which cloudy-sky power returns are compared. This algorithm supplements algorithms designed to detect cloud-base height in that the tops of optically thin clouds are identified and it provides an alternative approach to algorithms that identify significant power returns by analysis of changes in the slope of the backscattered powers with height. The cloud-base heights produced by the current algorithm during nonprecipitating periods are comparable with the results of a cloud-base height algorithm applied to the same data. Although an objective validation of algorithm performance on high, thin cirrus is lacking because of no truth data, the current algorithm produces few false positive and false negative classifications as determined through manual comparison of the original photoelectron count data to the final cloud mask image.",
author = "Clothiaux, {Eugene Edmund} and Mace, {G. G.} and Ackerman, {T. P.} and Kane, {Timothy Joseph} and Spinhirne, {J. D.} and Scott, {V. S.}",
year = "1998",
month = "1",
day = "1",
doi = "10.1175/1520-0426(1998)015<1035:AAAFDO>2.0.CO;2",
language = "English (US)",
volume = "15",
pages = "1035--1042",
journal = "Journal of Atmospheric and Oceanic Technology",
issn = "0739-0572",
publisher = "American Meteorological Society",
number = "4",

}

Notes and correspondence : An automated algorithm for detection of hydrometeor returns in micropulse lidar data. / Clothiaux, Eugene Edmund; Mace, G. G.; Ackerman, T. P.; Kane, Timothy Joseph; Spinhirne, J. D.; Scott, V. S.

In: Journal of Atmospheric and Oceanic Technology, Vol. 15, No. 4, 01.01.1998, p. 1035-1042.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Notes and correspondence

T2 - An automated algorithm for detection of hydrometeor returns in micropulse lidar data

AU - Clothiaux, Eugene Edmund

AU - Mace, G. G.

AU - Ackerman, T. P.

AU - Kane, Timothy Joseph

AU - Spinhirne, J. D.

AU - Scott, V. S.

PY - 1998/1/1

Y1 - 1998/1/1

N2 - A cloud detection algorithm for a low power micropulse lidar is presented that attempts to identify all of the significant power returns from the vertical column above the lidar at all times. The main feature of the algorithm is construction of lidar power return profiles during periods of clear sky against which cloudy-sky power returns are compared. This algorithm supplements algorithms designed to detect cloud-base height in that the tops of optically thin clouds are identified and it provides an alternative approach to algorithms that identify significant power returns by analysis of changes in the slope of the backscattered powers with height. The cloud-base heights produced by the current algorithm during nonprecipitating periods are comparable with the results of a cloud-base height algorithm applied to the same data. Although an objective validation of algorithm performance on high, thin cirrus is lacking because of no truth data, the current algorithm produces few false positive and false negative classifications as determined through manual comparison of the original photoelectron count data to the final cloud mask image.

AB - A cloud detection algorithm for a low power micropulse lidar is presented that attempts to identify all of the significant power returns from the vertical column above the lidar at all times. The main feature of the algorithm is construction of lidar power return profiles during periods of clear sky against which cloudy-sky power returns are compared. This algorithm supplements algorithms designed to detect cloud-base height in that the tops of optically thin clouds are identified and it provides an alternative approach to algorithms that identify significant power returns by analysis of changes in the slope of the backscattered powers with height. The cloud-base heights produced by the current algorithm during nonprecipitating periods are comparable with the results of a cloud-base height algorithm applied to the same data. Although an objective validation of algorithm performance on high, thin cirrus is lacking because of no truth data, the current algorithm produces few false positive and false negative classifications as determined through manual comparison of the original photoelectron count data to the final cloud mask image.

UR - http://www.scopus.com/inward/record.url?scp=0032449852&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032449852&partnerID=8YFLogxK

U2 - 10.1175/1520-0426(1998)015<1035:AAAFDO>2.0.CO;2

DO - 10.1175/1520-0426(1998)015<1035:AAAFDO>2.0.CO;2

M3 - Article

VL - 15

SP - 1035

EP - 1042

JO - Journal of Atmospheric and Oceanic Technology

JF - Journal of Atmospheric and Oceanic Technology

SN - 0739-0572

IS - 4

ER -