Cloud Mask from Micropulse Lidar
Abstract
Lidar backscattered signal is a useful tool for identifying vertical cloud structure in the atmosphere in optically thin clouds. Cloud boundaries derived from lidar signals are a necessary input for popular ARM data products, such as the Active Remote Sensing of Clouds (ARSCL) product. An operational cloud boundary algorithm has been implemented for use with the ARM Micropulse Lidar (MPL) systems. In addition to retrieving cloud boundaries above 500 m, the value-added product (VAP) named Micropulse Lidar Cloud Mask (MPLCMASK) applies lidar-specific corrections (i.e., afterpulse, background, deadtime, and overlap)
- Authors:
- Publication Date:
- DOE Contract Number:
- DE-AC05-00OR22725
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Archive; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Collaborations:
- PNNL, BNL, ANL, ORNL
- Subject:
- 54 Environmental Sciences
- Keywords:
- Cloud mask, Cloud top height, cloud base height, backscatter, linear depolarization
- OSTI Identifier:
- 1508389
- DOI:
- https://doi.org/10.5439/1508389
Citation Formats
Sivaraman, Chitra, Flynn, Donna, Riihimaki, Laura, and Comstock, Jennifer. Cloud Mask from Micropulse Lidar. United States: N. p., 2019.
Web. doi:10.5439/1508389.
Sivaraman, Chitra, Flynn, Donna, Riihimaki, Laura, & Comstock, Jennifer. Cloud Mask from Micropulse Lidar. United States. doi:https://doi.org/10.5439/1508389
Sivaraman, Chitra, Flynn, Donna, Riihimaki, Laura, and Comstock, Jennifer. 2019.
"Cloud Mask from Micropulse Lidar". United States. doi:https://doi.org/10.5439/1508389. https://www.osti.gov/servlets/purl/1508389. Pub date:Mon Jul 15 00:00:00 EDT 2019
@article{osti_1508389,
title = {Cloud Mask from Micropulse Lidar},
author = {Sivaraman, Chitra and Flynn, Donna and Riihimaki, Laura and Comstock, Jennifer},
abstractNote = {Lidar backscattered signal is a useful tool for identifying vertical cloud structure in the atmosphere in optically thin clouds. Cloud boundaries derived from lidar signals are a necessary input for popular ARM data products, such as the Active Remote Sensing of Clouds (ARSCL) product. An operational cloud boundary algorithm has been implemented for use with the ARM Micropulse Lidar (MPL) systems. In addition to retrieving cloud boundaries above 500 m, the value-added product (VAP) named Micropulse Lidar Cloud Mask (MPLCMASK) applies lidar-specific corrections (i.e., afterpulse, background, deadtime, and overlap)},
doi = {10.5439/1508389},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {7}
}
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Works referenced in this record:
Deriving Arctic Cloud Microphysics at Barrow, Alaska: Algorithms, Results, and Radiative Closure
journal, July 2015
- Shupe, Matthew D.; Turner, David D.; Zwink, Alexander
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Effects of Dynamic Range and Sampling Rate of an Infrared Thermometer to the Accuracy of the Cloud Detection
journal, July 2018
- Won, Hye; Ahn, Myoung
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(GO) 2 -SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase
journal, January 2018
- Lamer, Katia; Fridlind, Ann M.; Ackerman, Andrew S.
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Works referencing / citing this record:
Deriving Arctic Cloud Microphysics at Barrow, Alaska: Algorithms, Results, and Radiative Closure
journal, July 2015
- Shupe, Matthew D.; Turner, David D.; Zwink, Alexander
- Journal of Applied Meteorology and Climatology, Vol. 54, Issue 7
(GO) 2 -SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase
journal, January 2018
- Lamer, Katia; Fridlind, Ann M.; Ackerman, Andrew S.
- Geoscientific Model Development, Vol. 11, Issue 10
Effects of Dynamic Range and Sampling Rate of an Infrared Thermometer to the Accuracy of the Cloud Detection
journal, July 2018
- Won, Hye; Ahn, Myoung
- Remote Sensing, Vol. 10, Issue 7