Articles | Volume 11, issue 3
https://doi.org/10.5194/amt-11-1615-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-1615-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Mar 2018
Research article |
| 22 Mar 2018
| 22 Mar 2018
A prototype method for diagnosing high ice water content probability using satellite imager data
Christopher R. Yost
Science Systems and Applications, Inc., Hampton, VA 23666, USA
Kristopher M. Bedka
CORRESPONDING AUTHOR
NASA Langley Research Center, Hampton, VA 23681, USA
Patrick Minnis
Science Systems and Applications, Inc., Hampton, VA 23666, USA
Louis Nguyen
NASA Langley Research Center, Hampton, VA 23681, USA
J. Walter Strapp
Met Analytics Inc., Aurora, Ontario, Canada
Rabindra Palikonda
Science Systems and Applications, Inc., Hampton, VA 23666, USA
Konstantin Khlopenkov
Science Systems and Applications, Inc., Hampton, VA 23666, USA
Douglas Spangenberg
Science Systems and Applications, Inc., Hampton, VA 23666, USA
William L. Smith Jr.
NASA Langley Research Center, Hampton, VA 23681, USA
Alain Protat
Australian Bureau of Meteorology, Melbourne, Australia
Julien Delanoe
Laboratoire Atmosphere, Milieux, et Observations Spatiales,
Guyancourt, France
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21 citations as recorded by crossref.
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- Detecting Clouds Associated with Jet Engine Ice Crystal Icing J. Haggerty et al. 10.1175/BAMS-D-17-0252.1
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- Relationship between airborne electrical and total water content measurements in ice clouds A. Bouchard et al. 10.1016/j.atmosres.2019.104836
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- Evaluation of a high‐resolution numerical weather prediction model's simulated clouds using observations from CloudSat, GOES‐13 and in situ aircraft Z. Qu et al. 10.1002/qj.3318
- Analysis and Automated Detection of Ice Crystal Icing Conditions Using Geostationary Satellite Datasets and In Situ Ice Water Content Measurements K. Bedka et al. 10.4271/2019-01-1953
- Demonstration of a Nowcasting Service for High Ice Water Content (HIWC) Conditions R. Potts et al. 10.3390/atmos14050786
- Evaluation of the AROME model's ability to represent ice crystal icing using in situ observations from the HAIC 2015 field campaign J. Wurtz et al. 10.1002/qj.4100
- An Evaluation of the GOES-16 Rapid Scan for Nowcasting in Southeastern Brazil: Analysis of a Severe Hailstorm Case B. Ribeiro et al. 10.1175/WAF-D-19-0070.1
- Satellites See the World’s Atmosphere S. Ackerman et al. 10.1175/AMSMONOGRAPHS-D-18-0009.1
- A Long-Term Overshooting Convective Cloud-Top Detection Database over Australia Derived from MTSAT Japanese Advanced Meteorological Imager Observations K. Bedka et al. 10.1175/JAMC-D-17-0056.1
- The Above-Anvil Cirrus Plume: An Important Severe Weather Indicator in Visible and Infrared Satellite Imagery K. Bedka et al. 10.1175/WAF-D-18-0040.1
- High ice water content in tropical mesoscale convective systems (a conceptual model) A. Korolev et al. 10.5194/acp-24-11849-2024
- Dependence of Ice Microphysical Properties On Environmental Parameters: Results from HAIC-HIWC Cayenne Field Campaign Y. Hu et al. 10.1175/JAS-D-21-0015.1
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Discussed (preprint)
Latest update: 20 Nov 2024
Short summary
Accretion of cloud ice particles upon engine or instrument probe surfaces can cause engine malfunction or even power loss, and therefore it is important for aircraft to avoid flight through clouds that may have produced large quantities of ice particles. This study introduces a method by which potentially hazardous conditions can be detected using satellite imagery. It was found that potentially hazardous conditions were often located near or beneath very cold clouds and thunderstorm updrafts.
Accretion of cloud ice particles upon engine or instrument probe surfaces can cause engine...
