Incorporating data from GOES and POES platforms into an integrated in-flight icing diagnostic algorithm for Alaska
Jeffrey S. Tilley, Univ. of Alaska, Fairbanks, AK; and J. Long
Though the aviation safety record in Alaska has improved somewhat in recent years, several general aviation accidents per year continue to occur which are related to mesoscale in-flight icing conditions that are not well forecast with existing operational models and algorithms available to aviation forecasters. As part of efforts by the FAA's In-flight Icing Product Development Team, we have been developing a version of NCAR/RAP's Integrated Icing Diagnostic Algorithm (IIDA) suitable for Alaskan application and utilizing the Penn State/NCAR MM5 mesoscale modeling system.
The NCAR/RAP IIDA utilizes not only numerical model data, but also surface observations, radar observations and information derived from the GOES-8 instrumentation on cloud location, cloud top temperatures and cloud top heights. Our development of an Alaskan version of the IIDA has had to take into account not only a relative lack of useful radar information but a relative wealth of satellite information available through both GOES and POES instrumentation due to our high latitude area of interest.
In this paper we present the methodology behind and sample products of the Alaska IIDA we have developed at UAF, with a strong emphasis on satellite aspects. We will describe the procedures used in incorporating data from not only GOES but POES platforms, the latter of which requires a blending of data from the two sources along the appropriate POES swath at the time of interest. We will also briefly discuss other potential satellite data inputs into future versions of the IIDA.
Extended Abstract (76K)
Poster Session 1, Environmental Applications
Monday, 15 October 2001, 9:45 AM-11:15 AM
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