Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign

Schwartz, M. Christian; Ghate, Virendra P.; Albrecht, Bruce. A.; Zuidema, Paquita; Cadeddu, Maria P.; Vivekanandan, Jothiram; Ellis, Scott M.; Tsai, Pei; Eloranta, Edwin W.; Mohrmann, Johannes; Wood, Robert; Bretherton, Christopher S.

doi:10.1175/JTECH-D-18-0111.1

Title: Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign

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Abstract

The Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR's High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved usingmore »« less

Authors:

Schwartz, M. Christian ^[1]; Ghate, Virendra P. ^[1]; Albrecht, Bruce. A. ^[2]; Zuidema, Paquita ^[2]; Cadeddu, Maria P. ^[1]; Vivekanandan, Jothiram ^[3]; Ellis, Scott M. ^[3]; Tsai, Pei ^[3]; Eloranta, Edwin W. ^[4]; Mohrmann, Johannes ^[5]; Wood, Robert ^[5]; Bretherton, Christopher S. ^[5]

Argonne National Lab. (ANL), Lemont, IL (United States)
Univ. of Miami, Miami, FL (United States)
National Center for Atmospheric Research, Boulder, CO (United States). Earth Observing Lab.
Univ. of Wisconsin, Madison, WI (United States)
Univ. of Washington, Seattle, WA (United States)

Publication Date:: Wed May 22 00:00:00 EDT 2019

Research Org.:: Argonne National Lab. (ANL), Argonne, IL (United States)

Sponsoring Org.:: National Science Foundation (NSF); USDOE Office of Science (SC), Biological and Environmental Research (BER)

OSTI Identifier:: 1542634

Grant/Contract Number:: AC02-06CH11357; AGS-1445831

Resource Type:: Accepted Manuscript

Journal Name:: Journal of Atmospheric and Oceanic Technology

Additional Journal Information:: Journal Volume: 36; Journal Issue: 6; Journal ID: ISSN 0739-0572

Publisher:: American Meteorological Society

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES; aircraft observations; clouds; lidar observations; lidars; radar observations; radars; remote sensing

Citation Formats


                    Schwartz, M. Christian, Ghate, Virendra P., Albrecht, Bruce. A., Zuidema, Paquita, Cadeddu, Maria P., Vivekanandan, Jothiram, Ellis, Scott M., Tsai, Pei, Eloranta, Edwin W., Mohrmann, Johannes, Wood, Robert, and Bretherton, Christopher S. Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign.  United States: N. p., 2019. 
Web.  doi:10.1175/JTECH-D-18-0111.1.

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                    Schwartz, M. Christian, Ghate, Virendra P., Albrecht, Bruce. A., Zuidema, Paquita, Cadeddu, Maria P., Vivekanandan, Jothiram, Ellis, Scott M., Tsai, Pei, Eloranta, Edwin W., Mohrmann, Johannes, Wood, Robert, & Bretherton, Christopher S. Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign.  United States.  https://doi.org/10.1175/JTECH-D-18-0111.1

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                    Schwartz, M. Christian, Ghate, Virendra P., Albrecht, Bruce. A., Zuidema, Paquita, Cadeddu, Maria P., Vivekanandan, Jothiram, Ellis, Scott M., Tsai, Pei, Eloranta, Edwin W., Mohrmann, Johannes, Wood, Robert, and Bretherton, Christopher S. Wed .  
"Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign".  United States.  https://doi.org/10.1175/JTECH-D-18-0111.1.  https://www.osti.gov/servlets/purl/1542634.

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@article{osti_1542634,

  title        = {Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign},

  author       = {Schwartz, M. Christian and Ghate, Virendra P. and Albrecht, Bruce. A. and Zuidema, Paquita and Cadeddu, Maria P. and Vivekanandan, Jothiram and Ellis, Scott M. and Tsai, Pei and Eloranta, Edwin W. and Mohrmann, Johannes and Wood, Robert and Bretherton, Christopher S.},

  abstractNote = {The Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR's High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved using the HCR reflectivity, HSRL backscatter, and the HCR Doppler spectrum width after it is corrected for the aircraft speed. These indicate that as the boundary layers deepen and cloud-top heights increase toward the equator, both the cloud and rain fractions decrease.},

  doi          = {10.1175/JTECH-D-18-0111.1},

  journal      = {Journal of Atmospheric and Oceanic Technology},

  number       = 6,

  volume       = 36,

  place        = {United States},

  year         = {Wed May 22 00:00:00 EDT 2019},

  month        = {Wed May 22 00:00:00 EDT 2019}

}

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