Examination of a real-time 3DVAR analysis system in the hazardous weather testbed

Travis M. Smith, Jidong Gao, Kristin M. Calhoun, David J. Stensrud, Kevin L. Manross, Kiel L. Ortega, Chenghao Fu, Darrel M. Kingfield, Kimberly L. Elmore, Valliappa Lakshmanan, Christopher Riedel

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Forecasters and research meteorologists tested a real-time three-dimensional variational data assimilation (3DVAR) system in the Hazardous Weather Testbed during the springs of 2010-12 to determine its capabilities to assist in the warning process for severe storms. This storm-scale system updates a dynamically consistent three-dimensional wind field every 5 min, with horizontal and average vertical grid spacings of 1 km and 400 m, respectively. The system analyzed the life cycles of 218 supercell thunderstorms on 27 event days during these experiments, producing multiple products such as vertical velocity, vertical vorticity, and updraft helicity. These data are compared to multiradar-multisensor data from the Warning Decision Support System-Integrated Information to document the performance characteristics of the system, such as how vertical vorticity values compare to azimuthal shear fields calculated directly from Doppler radial velocity. Data are stratified by range from the nearest radar, as well as by the number of radars entering into the analysis of a particular storm. The 3DVAR system shows physically realistic trends of updraft speed and vertical vorticity for a majority of cases. Improvements are needed to better estimate the near-surface winds when no radar is nearby and to improve the timeliness of the input data. However, the 3DVAR wind field information provides an integrated look at storm structure that may be of more use to forecasters than traditional radar-based proxies used to infer severe weather potential.

Original languageEnglish (US)
Pages (from-to)63-77
Number of pages15
JournalWeather and Forecasting
Volume29
Issue number1
DOIs
StatePublished - Feb 2014

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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