Tuesday, 24 January 2017: 9:00 AM
Conference Center: Skagit 2 (Washington State Convention Center )
Turbulence is a significant aviation hazard that impacts air travel from flight safety to route planning and air traffic management. Turbulence observations can give researchers insights into causes of turbulence that occur on scales that impact aircraft as well as inform new ways to forecast such phenomenon. Turbulence observations from aircraft consist mostly of reports called in by pilots in flight (PIREPs) or automated in situ
reports from select commercial aircraft. Both of these have signisficant limitations, not the least of which is intentional pilot avoidance of turbulence regions. The NEXRAD Turbulence Detection Algorithm (NTDA) is a ground-based algorithm that produces estimates of in-cloud turbulence routinely over much of the continental United States. This algorithm uses spectrum width information as well as dual-polarimetric and radial velocity information from the nation’s network of NEXRAD radars to produce a 3-D gridded mosaic of the Energy Dissipation Rate (EDR) associated with the in-cloud turbulence across the U.S. every 5 minutes. To gain a better quantitative understanding of the nature, frequency, and spatial distribution of in-cloud turbulence we use NTDA EDR data to derive climatological information of in-cloud turbulence over the United States, with a focus on convectively induced turbulence at upper levels. Regional and seasonal variability are explored, as well as comparisons of the data with other convective parameters. These analyses are a necessary first step in developing in-cloud turbulence diaganostics to be used in aviation turbulence nowcast and forecast systems.
“This research is in response to requirements and funding by the Federal Aviation Administration (FAA). The views expressed are those of the authors and do not necessarily represent the official policy or position of the FAA.”
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