Characterization of satellite cloud products for application in an aircraft icing prediction system

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Wednesday, 1 February 2006
Characterization of satellite cloud products for application in an aircraft icing prediction system
Exhibit Hall A2 (Georgia World Congress Center)
Julie A. Haggerty, NCAR, Boulder, CO; and S. Landolt, J. Simard, C. Wolff, B. Bernstein, and P. Minnis

The NCAR Current Icing Potential (CIP) algorithm combines basic satellite-derived information with multiple other data sources to produce a gridded, three-dimensional, hourly depiction of icing potential and intensity. Satellite data from the GOES Imagers are used in CIP to create a cloud mask and estimate cloud top temperature. Advanced satellite-derived cloud products developed at the NASA Langley Research Center (LaRC) provide a more detailed description of cloud properties (primarily at cloud top) compared to the basic satellite-derived information currently used. A goal of the NASA Advanced Satellite Aviation-weather Products (ASAP) program is to improve icing diagnosis and forecasting products by integrating advanced cloud products into CIP. In support of the integration efforts, assessment of satellite product accuracy in varying conditions is required.

The NASA LaRC cloud products have been used by forecasters for detection of probable icing conditions in support of icing research flights during the past three winter seasons. Forecasters generally found them useful, and developed “rules of thumb” for when specific products are of value. For example, cases with uniform values of phase, liquid water path (LWP), and/or effective radius (Re) over large areas are usually more reliable than cases with high spatial variability. Gradients in LWP are often found to be qualitatively accurate. Sharp transitions in values are sometimes problematic. Phase estimates are typically accurate, and higher Re estimates tend to correlate positively with in situ observations of larger drops. Such observations provide direction for more systematic evaluation of the products and for developing logic to integrate the products with the CIP algorithm.

In this paper, we translate the forecasters' anecdotal guidance into hypotheses that can be verified statistically. A data set over the Great Lakes region from the winters of 2003-2005, including satellite products, research aircraft data, and pilot reports, has been assembled for this purpose. Results from this study will be used to confirm that satellite-derived phase, LWP, and Re products are of value for detection of potential icing, to determine conditions under which these products are likely to improve CIP output, and to develop methods for effectively combining this new data source with existing CIP input data sources.