Progress toward characterization of the atmospheric boundary layer over northern Alabama using observations by a vertically pointing, S-band profiling radar during VORTEX-Southeast

During spring 2016 and spring 2017, a vertically pointing, S-band FMCW radar (UMass FMCW) was deployed in northern Alabama under the auspices of the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) – Southeast. In total, ~14 weeks’ worth of data were collected, in conditions...

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Detalles Bibliográficos
Autores: Tanamachi, Robin, Frasier, Steve, Waldinger, Joseph, LaFleur, Allison T., Turner, David Dave, Rocadenbosch Burillo, Francisco|||0000-0001-8614-4408
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/171479
Acceso en línea:https://hdl.handle.net/2117/171479
https://dx.doi.org/10.1175/JTECH-D-18-0224.1
Access Level:acceso abierto
Palabra clave:Remote sensing
Teledetecció
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció
Descripción
Sumario:During spring 2016 and spring 2017, a vertically pointing, S-band FMCW radar (UMass FMCW) was deployed in northern Alabama under the auspices of the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) – Southeast. In total, ~14 weeks’ worth of data were collected, in conditions ranging from quiescent clear skies to severe thunderstorms. The principal objective of these deployments was to characterize the boundary layer evolution near the VORTEX-Southeast domain. In this paper, we describe intermediate results in service of this objective. Specifically, we describe updates to the UMass FMCW system, document its deployments for VORTEX-Southeast, and apply three automated algorithms: (1) an dealiasing algorithm to the Doppler velocities, (2) a fuzzy logic scatterer classification scheme to separate precipitation from non-precipitation observations, (3) a bright band / melting layer identification algorithm for stratiform precipitation, and (4) an extended Kalman filter-based convective boundary layer depth (mixing height) measurement algorithm for non-precipitation observations. Results from the latter two applications are qualitatively verified against retrieved soundings from a collocated thermodynamic profiling system.