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Title: Aerial Assessment of Liquid in Clouds at Oliktok Field Campaign Report

Abstract

The Aerial Assessment of Liquid in Clouds at Oliktok (AALCO) Intensive Operation Period (IOP) began in October 2016 and ended in October 2017 at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) third Mobile Facility (AMF3) at Oliktok Point, Alaska (https://www.arm.gov/research/campaigns/amf2016aalco). The operations tested super-cooled liquid water sensors (SLWCs), leaf-wetness sensors, radiosondes, and a distributed temperature sensor (DTS) on tethered balloon system (TBS) platforms throughout the period. An auto-reeler system, a helikite, and an aerostat were tested. When conditions were optimal, the aerostat was preferred to the helikite and the auto-reeler. It was found that the SLWCs had better transmission and sensitivity to relay information about the near-surface cloudy boundary layer than the leaf-wetness sensors. The DTS was also found to give useful information about the atmospheric column and deployment is condition-dependent. Results from the SLWCs and DTS are being compared with high-resolution large-eddy simulations (LES) in the System for Atmospheric Modeling (SAM) (Khairoutdinov and Randall, 2003).

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
DOE Office of Science Atmospheric Radiation Measurement (ARM) Program (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1459557
Report Number(s):
DOE/SC-ARM-18-024
DOE Contract Number:  
ACO5-7601830
Resource Type:
Program Document
Country of Publication:
United States
Language:
English
Subject:
North Slope of Alaska, Oliktok Point, aerosols, Arctic processes, tethered balloon system, clouds, boundary layer

Citation Formats

Roesler, Erika L, Dexheimer, Dari, Longbottom, Casey, Helsel, Fred, Apple, Monty, Hillman, Ben, Hardesty, Joe, and Ivey, Mark. Aerial Assessment of Liquid in Clouds at Oliktok Field Campaign Report. United States: N. p., 2018. Web.
Roesler, Erika L, Dexheimer, Dari, Longbottom, Casey, Helsel, Fred, Apple, Monty, Hillman, Ben, Hardesty, Joe, & Ivey, Mark. Aerial Assessment of Liquid in Clouds at Oliktok Field Campaign Report. United States.
Roesler, Erika L, Dexheimer, Dari, Longbottom, Casey, Helsel, Fred, Apple, Monty, Hillman, Ben, Hardesty, Joe, and Ivey, Mark. Tue . "Aerial Assessment of Liquid in Clouds at Oliktok Field Campaign Report". United States. https://www.osti.gov/servlets/purl/1459557.
@article{osti_1459557,
title = {Aerial Assessment of Liquid in Clouds at Oliktok Field Campaign Report},
author = {Roesler, Erika L and Dexheimer, Dari and Longbottom, Casey and Helsel, Fred and Apple, Monty and Hillman, Ben and Hardesty, Joe and Ivey, Mark},
abstractNote = {The Aerial Assessment of Liquid in Clouds at Oliktok (AALCO) Intensive Operation Period (IOP) began in October 2016 and ended in October 2017 at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) third Mobile Facility (AMF3) at Oliktok Point, Alaska (https://www.arm.gov/research/campaigns/amf2016aalco). The operations tested super-cooled liquid water sensors (SLWCs), leaf-wetness sensors, radiosondes, and a distributed temperature sensor (DTS) on tethered balloon system (TBS) platforms throughout the period. An auto-reeler system, a helikite, and an aerostat were tested. When conditions were optimal, the aerostat was preferred to the helikite and the auto-reeler. It was found that the SLWCs had better transmission and sensitivity to relay information about the near-surface cloudy boundary layer than the leaf-wetness sensors. The DTS was also found to give useful information about the atmospheric column and deployment is condition-dependent. Results from the SLWCs and DTS are being compared with high-resolution large-eddy simulations (LES) in the System for Atmospheric Modeling (SAM) (Khairoutdinov and Randall, 2003).},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {7}
}

Program Document:
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