1 / 15

Integration of Advanced Satellite Cloud Products into an Icing Nowcasting System

Integration of Advanced Satellite Cloud Products into an Icing Nowcasting System. Julie Haggerty, Gary Cunning, Ben Bernstein, Michael Chapman, David Johnson, Marcia Politovich, Cory Wolff National Center for Atmospheric Research Boulder, Colorado USA Patrick Minnis and Rabindra Palikonda

gerik
Download Presentation

Integration of Advanced Satellite Cloud Products into an Icing Nowcasting System

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Integration of Advanced Satellite Cloud Products into an Icing Nowcasting System Julie Haggerty, Gary Cunning, Ben Bernstein, Michael Chapman, David Johnson, Marcia Politovich, Cory Wolff National Center for Atmospheric Research Boulder, Colorado USA Patrick Minnis and Rabindra Palikonda NASA Langley Research Center, Hampton, Virginia USA WWRP Symposium on Nowcasting and Very Short Range Forecasting, 5-9 September 2005

  2. The NCARCurrent Icing Potential (CIP) System:A Basic Description Hourly diagnosis of icing potential and the potential for supercooled large drops over a three-dimensional domain over the continental United States Experimental version estimates icing severity Data sources include surface observations, pilot reports, model forecasts, radars, and lightning sensors Limited satellite data currently used (cloud mask and cloud top temperature) CIP Icing Potential at 825 mb 16 February 2005 at 1600 UTC

  3. NASA Langley Satellite-derived Cloud Products • GOES Imager visible, near-infrared, and infrared channels • Products include cloud droplet phase, liquid water path, particle size • These variables can indicate possible icing conditions  potential improvement to CIP products • Represent conditions primarily near cloud top Liquid water path at 1615 UTC on 16 February 2005 as derived from GOES-12 imagery.

  4. Integration PlanCIP-Satellite Cloud Products • Forecasters’ experience using satellite products • Selection of satellite products likely to improve icing detection, i.e., phase, liquid water path, particle size • Objective assessment of satellite products • Modification of CIP algorithms to include satellite products • Case studies using modified version of CIP • Refinement of integration methods

  5. Satellite Product Validation • Case studies – comparison of phase, LWP, cloud top height, particle size with research aircraft and ground-based radiometer data • Long-term intercomparison of satellite and CIP products with pilot reports • Statistical characterization of satellite products to verify forecasters’ guidelines

  6. Satellite-Aircraft Comparisons from AIRS-II • Aircraft cloud-top penetrations • 13 aircraft-detected liquid cases • 10 classified correctly by satellite • 2 classified as ice (overlying cirrus?) • 1 as clear (varied conditions) • 2 aircraft-detected mixed phase cases • both classified as ice by satellite • 4 aircraft-detected ice cases • 3 classified correctly by satellite • 1 classified as clear

  7. Comparison of Satellite Product with Ground-based Microwave Radiometer MWR Mean = 238.5 GOES Mean = 264.0 MWR Stddev = 156.6 GOES Stddev = 169.2 Correlation coefficient = 0.72

  8. CIP Icing Severity Index • Severity product intended to characterize rate of ice accumulation • Current data sources are model estimates (vertical velocity, liquid water, temperature), pilot reports, and CIP icing potential • Good candidate for improvement by advanced satellite products because of liquid water and particle size dependence

  9. Case StudiesNortheastern United States • Six cases identified with icing conditions and in situ measurements by a research aircraft • 16 February 2005; non-precipitating, single layer stratus cloud; cloud top temperature -10 to -15 ºC • 19 January 2005; widespread liquid cloud with high liquid water content; cloud top temperature -10 ºC

  10. Adjustment of CIP Severity Index with Satellite Products Phase product locates pixels with liquid or supercooled liquid at cloud top Cloud drop phase, 16 February 2005, 1545 UTC

  11. Adjustment of CIP Severity Index with Satellite Products LWP product assumed to represent liquid water content in highest cloud layer Liquid Water Path, 16 February 2005, 1545 UTC

  12. Adjustment of CIP Severity Index with Satellite Products • Empirical scaling factor used to estimate liquid water content (LWC) in cloud layer using LWP estimate • New severity index calculated from LWC estimate for pixels with positive icing potential • Original CIP severity index adjusted upward or downward by half the difference

  13. Areas of high LWP Modified by inclusion of satellite-derived phase and liquid water path products Original estimate CIP Icing Severity Index 16 February 2005 at 1600 UTC

  14. CIP Icing Severity Index 19 January 2005 at 1915 UTC Modified by inclusion of satellite-derived phase and liquid water path products Original estimate

  15. Interim Conclusions and Future Work • Advanced satellite products appear to have skill in estimating icing-related cloud variables • Integration of phase and LWP products for adjustment of CIP severity index produces results consistent with aircraft measurements • Analysis of additional, more complex cases • Refinement of integration methods and use of additional products such as particle size

More Related