Development and Testing of an Advanced Hydrometeor-Phase Algorithm to Meet Emerging Needs in the Aviation Sector

Abstract

New regulations are being issued by the Federal Aviation Administration (FAA) that require three-dimensional hydrometeor-phase diagnosis, including discrimination between freezing rain (FZRA) and freezing drizzle (FZDZ), for all commercial airports in the United States. Herein, a novel hydrometeor-phase algorithm, the Spectral Bin Classifier (SBC), is adapted to meet these requirements. First, the SBC’s Particle Size Distribution (PSD) is upgraded to be variable rather than fixed. This, along with some changes to the logic, allows for drizzle (DZ)/FZDZ to be diagnosed. Second, the SBC is modified to provide a low-altitude (LA), above-ground diagnosis (SBC-LA). Last, necessary changes to account for resolution issues in NWP thermal profiles are presented. Adding a dynamic-PSD capability improves the Probability of Detection (POD) by about 12%, but adapting the algorithm to include DZ/FZDZ worsens the PODs. This is due to potentially-errant reports of rain (RA)/FZRA in environments more conducive to DZ/FZDZ. Assuming a diagnosis of DZ is a hit when RA is observed, and likewise for FZRA/FZDZ, increases the POD by between 35 and 60%. While performance statistics for SBC-LA cannot be computed, about one-third of all RA and DZ soundings herein have an elevated layer of FZRA/FZDZ, underscoring the importance of an above-ground diagnosis for the aviation sector. The comparatively-low vertical resolution of NWP profiles is found to degrade the SBC’s performance. Interpolating to a higher resolution helps mitigate this problem. Several case studies of mixed phases at different airports are presented to highlight the enhanced decision support made possible by the above modifications.