368191 Examining the Performance of Aviation Weather Center Traffic Flow Management Convective Forecast Products

Wednesday, 15 January 2020
Robert M. Hepper, CIRA/Colorado State Univ., NOAA/NWS/NCEP/AWC, Kansas City, MO; and A. Cross

The Traffic Flow Management (TFM) Convective Forecast (TCF) product, produced at the Aviation Weather Center (AWC), provides a high confidence graphical representation of forecast convection meeting specific criteria of coverage, intensity, and echo top height. TCF graphics are produced every 2 hours and valid at 4-, 6-, and 8- hours after issuance time and are intended to be used as the authoritative source of convective weather forecast information for TFM strategic planning. During the primary convective season from March 1st to October 31st, the TCF product is produced by AWC forecasters through collaboration with forecasters embedded at the Federal Aviation Administration (FAA) Air Traffic Control System Command Center (ATCSCC), Center Weather Service Units (CWSU) forecasters, airline meteorologists, and other authorized participants. At the beginning of each forecast cycle period, forecasters at AWC are provided with a first guess automated TCF product, created through a blend of high resolution model guidance. AWC Forecasters then build the final product based on the automated TCF output, other observational and model guidance, and collaboration with the aforementioned partners.

Objective verification metrics have been computed for both the first guess automated and final TCF products, with MRMS reflectivity and echo tops being used as observations, allowing for comparison between the automated and final products. This paper will examine the performance of both the final and first guess automated TCF products over the 2018 and 2019 convective seasons. Value added over the automated product by AWC forecasters and the collaborative forecast process will be detailed through comparison of objective verification scores, as well as subjective evaluation of individual cases. Additionally potential future improvements to the automated guidance product will be analyzed and discussed.

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