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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 3
Atmos. Meas. Tech., 11, 1615–1637, 2018
https://doi.org/10.5194/amt-11-1615-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 11, 1615–1637, 2018
https://doi.org/10.5194/amt-11-1615-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 22 Mar 2018

Research article | 22 Mar 2018

A prototype method for diagnosing high ice water content probability using satellite imager data

Christopher R. Yost1, Kristopher M. Bedka2, Patrick Minnis1, Louis Nguyen2, J. Walter Strapp3, Rabindra Palikonda1, Konstantin Khlopenkov1, Douglas Spangenberg1, William L. Smith Jr.2, Alain Protat4, and Julien Delanoe5 Christopher R. Yost et al.
  • 1Science Systems and Applications, Inc., Hampton, VA 23666, USA
  • 2NASA Langley Research Center, Hampton, VA 23681, USA
  • 3Met Analytics Inc., Aurora, Ontario, Canada
  • 4Australian Bureau of Meteorology, Melbourne, Australia
  • 5Laboratoire Atmosphere, Milieux, et Observations Spatiales, Guyancourt, France

Abstract. Recent studies have found that ingestion of high mass concentrations of ice particles in regions of deep convective storms, with radar reflectivity considered safe for aircraft penetration, can adversely impact aircraft engine performance. Previous aviation industry studies have used the term high ice water content (HIWC) to define such conditions. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: (1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, (2) tropopause-relative infrared brightness temperature, and (3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite–aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC  ≥  0.5 g m−3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.

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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...
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