32 Development and Applications of a Long-term, Global Tropical Cyclone Dropsonde Dataset

Tuesday, 17 April 2018
Champions DEFGH (Sawgrass Marriott)
Jonathan Zawislak, Univ. of Miami/Cooperative Institute for Marine and Atmospheric Studies and NOAA/AOML/HRD, Miami, FL; and L. Nguyen, E. Paltz, K. Young, H. Voemel, and T. Hock

Since 1996, GPS dropsondes have served as a key observing platform for reconnaissance, synoptic surveillance, and research missions into tropical cyclones (TCs) across multiple agencies, most notably on NOAA, U.S. Air Force Reserve, NASA, NRL, and NCAR/NSF aircraft. These observations have covered extensively the inner core, near-, and far-environments throughout the lifecycle of TCs. The needs of the TC research community require dropsonde datasets be organized in such a way that can easily facilitate individual case studies and composite analyses. The most significant challenge to meeting these needs is that dropsonde datasets are spread across multiple agencies and can have varying data quality. Leveraging NCAR’s Long-term NOAA Dropsonde Hurricane Archive (DHA), which established the methods for a commonly formatted and carefully quality controlled hurricane dropsonde dataset, this presentation describes the effort towards the development of the complete, long-term DHA that extends the archive to observations from all agencies. On one level of service, the quality controlled dropsonde observations are organized by individual aircraft missions for each storm. On a higher-level, each observation is averaged to similar vertical levels, located in storm-, motion-, and vertical wind shear-relative reference frames, and include value-added information, such as vertical wind shear magnitude and direction, SST, maximum sustained wind speed, MSLP, and intensity change near the observation time. This information facilitates the users’ ability for science question driven exploration of the dataset. In addition to the dataset description, this presentation will offer results from some applications of the dataset, most notably the composite TC structure at various intensities and stages within the lifecycle, including during intensity change periods.
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