Editorial Type:
Article
Article Type:
Research Article

Determining the Flight Icing Threat to Aircraft with Single-Layer Cloud Parameters Derived from Operational Satellite Data

William L. Smith Jr. NASA Langley Research Center, Hampton, Virginia

Search for other papers by William L. Smith Jr. in
Current site
Google Scholar
PubMed Close
,
Patrick Minnis NASA Langley Research Center, Hampton, Virginia

Search for other papers by Patrick Minnis in
Current site
Google Scholar
PubMed Close
,
Cecilia Fleeger Science Systems and Applications, Inc., Hampton, Virginia

Search for other papers by Cecilia Fleeger in
Current site
Google Scholar
PubMed Close
,
Douglas Spangenberg Science Systems and Applications, Inc., Hampton, Virginia

Search for other papers by Douglas Spangenberg in
Current site
Google Scholar
PubMed Close
,
Rabindra Palikonda Science Systems and Applications, Inc., Hampton, Virginia

Search for other papers by Rabindra Palikonda in
Current site
Google Scholar
PubMed Close
, and
Louis Nguyen NASA Langley Research Center, Hampton, Virginia

Search for other papers by Louis Nguyen in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Oct 2012
DOI:
https://doi.org/10.1175/JAMC-D-12-057.1
Page(s):
1794–1810
Restricted access

Abstract

An algorithm is developed to determine the flight icing threat to aircraft utilizing quantitative information on clouds derived from meteorological satellite data as input. Algorithm inputs include the satellite-derived cloud-top temperature, thermodynamic phase, water path, and effective droplet size. The icing-top and -base altitude boundaries are estimated from the satellite-derived cloud-top and -base altitudes using the freezing level obtained from numerical weather analyses or a lapse-rate approach. The product is available at the nominal resolution of the satellite pixel. Aircraft pilot reports (PIREPs) over the United States and southern Canada provide direct observations of icing and are used extensively in the algorithm development and validation on the basis of correlations with Geostationary Operational Environmental Satellite imager data. Verification studies using PIREPs, Tropospheric Airborne Meteorological Data Reporting, and NASA Icing Remote Sensing System data indicate that the satellite algorithm performs reasonably well, particularly during the daytime. The algorithm is currently being run routinely using data taken from a variety of satellites across the globe and is providing useful information on icing conditions at high spatial and temporal resolutions that are unavailable from any other source.

Corresponding author address: William L. Smith Jr., NASA Langley Research Center, MS 420, Hampton, VA 23681. E-mail: william.l.smith@nasa.gov

Abstract

An algorithm is developed to determine the flight icing threat to aircraft utilizing quantitative information on clouds derived from meteorological satellite data as input. Algorithm inputs include the satellite-derived cloud-top temperature, thermodynamic phase, water path, and effective droplet size. The icing-top and -base altitude boundaries are estimated from the satellite-derived cloud-top and -base altitudes using the freezing level obtained from numerical weather analyses or a lapse-rate approach. The product is available at the nominal resolution of the satellite pixel. Aircraft pilot reports (PIREPs) over the United States and southern Canada provide direct observations of icing and are used extensively in the algorithm development and validation on the basis of correlations with Geostationary Operational Environmental Satellite imager data. Verification studies using PIREPs, Tropospheric Airborne Meteorological Data Reporting, and NASA Icing Remote Sensing System data indicate that the satellite algorithm performs reasonably well, particularly during the daytime. The algorithm is currently being run routinely using data taken from a variety of satellites across the globe and is providing useful information on icing conditions at high spatial and temporal resolutions that are unavailable from any other source.

Corresponding author address: William L. Smith Jr., NASA Langley Research Center, MS 420, Hampton, VA 23681. E-mail: william.l.smith@nasa.gov
Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Bernstein, B. C., F. McDonough, M. Politovich, B. Brown, T. Ratvasky, D. Miller, C. Wolff, and G. Cunning, 2005: Current icing potential: Algorithm description and comparison with aircraft observations. J. Appl. Meteor., 44, 969–986.

    • Search Google Scholar
    • Export Citation

  • Bernstein, B. C., C. A. Wolff, and P. Minnis, 2006: Practical application of NASA-Langley advanced satellite products to in-flight icing nowcasts. Proc. 44th AIAA Aerospace Science Meeting and Exhibit, Reno, NV, AIAA-2006-1220.

  • Bernstein, B. C., C. A. Wolff, and F. McDonough, 2007: An inferred climatology of icing conditions aloft, including supercooled large drops. Part I: Canada and the continental United States. J. Appl. Meteor. Climatol., 46, 1857–1878.

    • Search Google Scholar
    • Export Citation

  • Brown, B. G., and G. S. Young, 2000: Verification of icing and turbulence forecasts: Why some verification statistics can’t be computed using PIREPs. Preprints, Ninth Conf. on Aviation, Range, and Aerospace Meteorology, Orlando, FL, Amer. Meteor. Soc., 393–398.

  • Chang, F.-L., and Z. Li, 2005: A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J. Atmos. Sci., 62, 3993–4009.

    • Search Google Scholar
    • Export Citation

  • Chang, F.-L., P. Minnis, B. Lin, M. M. Khaiyer, R. Palikonda, and D. A. Spangenberg, 2010: A modified method for inferring upper troposphere cloud top height using the GOES 12 imager 10.7 and 13.3μm data. J. Geophys. Res., 115, D06208, doi:10.1029/2009JD012304.

    • Search Google Scholar
    • Export Citation

  • Curry, J. A., and G. Liu, 1992: Assessment of aircraft icing potential using satellite data. J. Appl. Meteor., 31, 605–621.

  • Daniels, T. S., 2002: Tropospheric airborne meteorological data reporting (TAMDAR) sensor development. SAE General Aviation Technology Conf. and Exposition, Wichita, KS, SAE International, 2002-02-153. [Available online at http://papers.sae.org/2002-01-1523.]

  • Dong, X., P. Minnis, G. G. Mace, W. L. Smith Jr., M. Poellot, R. T. Marchand, and A. D. Rapp, 2002: Comparison of stratus cloud properties deduced from surface, GOES, and aircraft data during the March 2000 ARM Cloud IOP. J. Atmos. Sci., 59, 3256–3284.

    • Search Google Scholar
    • Export Citation

  • Dong, X., P. Minnis, B. Xi, S. Sun-Mack, and Y. Chen, 2008: Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site. J. Geophys. Res., 113, D03204, doi:10.1029/2007JD008438.

    • Search Google Scholar
    • Export Citation

  • Ellrod, G., and J. P. Nelson, 1996: Remote sensing of aircraft icing regions using GOES multispectral imager data. Preprints, 15th Conf. on Weather Analysis and Forecasting, Norfolk, VA, Amer. Meteor. Soc., 9–12.

  • Ellrod, G., and A. P. Bailey, 2007: Assessment of aircraft icing potential and maximum icing altitude from geostationary meteorological satellite data. Wea. Forecasting, 22, 160–174.

    • Search Google Scholar
    • Export Citation

  • Haggerty, J., F. McDonough, J. Black, S. Landolt, C. Wolff, S. Mueller, P. Minnis, and W. L. Smith Jr., 2008: Integration of satellite-derived cloud phase, cloud-top height, and liquid water path into an operational aircraft icing nowcasting system. Preprints, 13th Conf. on Aviation, Range, and Aerospace Meteorology, New Orleans, LA, Amer. Meteor. Soc., 3.13. [Available online at http://ams.confex.com/ams/pdfpapers/131893.pdf.]

  • Kane, T. L., B. G. Brown, and R. Bruintjes, 1998: Characteristics of pilot reports of icing. Preprints, 14th Conf. on Probability and Statistics, Phoenix, AZ, Amer. Meteor. Soc., 90–95.

  • Mason, J. G., J. W. Strapp, and P. Chow, 2006: The ice particle threat to engines in flight. Proc. 44th AIAA Aerospace Science Meeting and Exhibit, Reno, NV, AIAA-2006-206.

  • Minnis, P., and Coauthors, 1995: Cloud Optical Property Retrieval (subsystem 4.3). Clouds and the Earth’s Radiant Energy System (CERES) Algorithm Theoretical Basis Document: Cloud Analyses and Radiance Inversions (Subsystem 4), NASA RP 1376, Vol. 3, 135–176.

  • Minnis, P., and Coauthors, 2004: Real-time cloud, radiation, and aircraft icing parameters from GOES over the USA. Preprints, 13th Conf. on Satellite Oceanography and Meteorolology, Norfolk, VA, Amer. Meteor. Soc., P7.1. [Available online at http://ams.confex.com/ams/pdfpapers/79179.pdf.]

  • Minnis, P., and Coauthors, 2008a: Near-real time cloud retrievals from operational and research meteorological satellites. Remote Sensing of Clouds and the Atmosphere XIII, R. H. Picard et al., Eds., International Society for Optical Engineering (SPIE Proceedings Vol. 7107), 710703, doi:10.1117/12.800344.

  • Minnis, P., and Coauthors, 2008b: Cloud detection in non-polar regions for CERES using TRMM VIRS and Terra and Aqua MODIS data. IEEE Trans. Geosci. Remote Sens., 46, 3857–3884.

    • Search Google Scholar
    • Export Citation

  • Minnis, P., C. R. Yost, S. Sun-Mack, and Y. Chen, 2008c: Estimating the physical top altitude of optically thick ice clouds from thermal infrared satellite observations using CALIPSO data. Geophys. Res. Lett., 35, L12801, doi:10.1029/2008GL033947.

    • Search Google Scholar
    • Export Citation

  • Minnis, P., and Coauthors, 2011a: CERES edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data, Part I: Algorithms. IEEE Trans. Geosci. Remote Sens., 49, 4374–4400.

    • Search Google Scholar
    • Export Citation

  • Minnis, P., and Coauthors, 2011b: CERES edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data, Part II: Examples of average results and comparisons with other data. IEEE Trans. Geosci. Remote Sens., 49, 4401–4430.

    • Search Google Scholar
    • Export Citation

  • National Aviation Safety Data Analysis Center, 2005: National Transportation Safety Board weather related accident study: 1994–2003. Federal Aviation Administration Study Rep. [Available online at http://www.asias.faa.gov/aviation_studies/weather_study/studyindex.html.]

  • Pavolonis, M. J., 2010: Advances in extracting cloud composition information from spaceborne infrared radiances—A robust alternative to brightness temperatures. Part I: Theory. J. Appl. Meteor. Climatol., 49, 1992–2012.

    • Search Google Scholar
    • Export Citation

  • Platnick, S., 2000: Vertical photon transport in cloud remote sensing problems. J. Geophys. Res., 105, 22919–22935.

  • Politovich, M. K., 2003: Predicting inflight aircraft icing intensity. J. Aircr., 40, 639–644.

  • Rasmussen, R., and Coauthors, 1992: Winter Icing and Storms Project (WISP). Bull. Amer. Meteor. Soc., 73, 951–974.

  • Rauber, R., and A. Tokay, 1991: An explanation for the existence of supercooled water at the top of cold clouds. J. Atmos. Sci., 48, 1005–1023.

    • Search Google Scholar
    • Export Citation

  • Reehorst, A., D. Brinker, M. Politovich, D. Serke, C. Ryerson, A. Pazmany, and F. Solheim, 2009: Progress towards the remote sensing of aircraft icing hazards. NASA Tech. Rep. NASA/TM-2009-215828, 12 pp. [Available online at http://icebox-esn.grc.nasa.gov/RSData/70880J.pdf.]

  • Smith, W. L., Jr., P. Minnis, and D. F. Young, 2000: An icing product derived from operational satellite data. Preprints, Ninth Conf. on Aviation, Range, and Aerospace Meteorology, Orlando, FL, Amer. Meteor. Soc., 256–259.

  • Smith, W. L., Jr., P. Minnis, B. C. Bernstein, F. McDonough, and M. M. Khaiyer, 2003: Comparison of super-cooled liquid water cloud properties derived from satellite and aircraft measurements. Proc. In-Flight Icing/De-icing Int. Conf., Chicago, IL, Federal Aviation Administration 2003-01-2156.

  • Smith, W. L., Jr., P. Minnis, H. Finney, R. Palikonda, and M. M. Khaiyer, 2008: An evaluation of operational GOES derived single-layer cloud top heights with ARSCL over the ARM Southern Great Plains site. Geophys. Res. Lett., 35, L13820, doi:10.1029/2008GL034275.

    • Search Google Scholar
    • Export Citation

  • Thompson, G., R. Bullock, and T. F. Lee, 1997: Using satellite data to reduce spatial extent of diagnosed icing. Wea. Forecasting, 12, 185–190.

    • Search Google Scholar
    • Export Citation

  • Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. Academic Press, 627 pp.

  • Xi, B., X. Dong, P. Minnis, and M. M. Khaiyer, 2010: A 10-year climatology of cloud cover and vertical distribution derived from both surface and GOES observations over the DOE ARM SGP site. J. Geophys. Res., 115, D12124, doi:10.1029/2009JD012800.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2065 800 36
PDF Downloads 816 147 7