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Article
Article Type:
Research Article

A Real-Time Weather-Adaptive 3DVAR Analysis System for Severe Weather Detections and Warnings

Jidong Gao * NOAA/National Severe Storms Laboratory, Norman, Oklahoma

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Travis M. Smith NOAA/National Severe Storms Laboratory, and Cooperate Institute for Mesoscale Meteorological Studies, Norman, Oklahoma

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David J. Stensrud * NOAA/National Severe Storms Laboratory, Norman, Oklahoma

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Chenghao Fu Cooperate Institute for Mesoscale Meteorological Studies, Norman, Oklahoma, and Hunan Meteorological Bureau, Changsa, Hunan, China

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Kristin Calhoun NOAA/National Severe Storms Laboratory, and Cooperate Institute for Mesoscale Meteorological Studies, Norman, Oklahoma

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Kevin L. Manross NOAA/National Severe Storms Laboratory, and Cooperate Institute for Mesoscale Meteorological Studies, Norman, Oklahoma

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Jeffrey Brogden NOAA/National Severe Storms Laboratory, and Cooperate Institute for Mesoscale Meteorological Studies, Norman, Oklahoma

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Valliappa Lakshmanan NOAA/National Severe Storms Laboratory, and Cooperate Institute for Mesoscale Meteorological Studies, Norman, Oklahoma

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Yunheng Wang Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Kevin W. Thomas Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Keith Brewster Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Ming Xue Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

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Print Publication:
01 Jun 2013
DOI:
https://doi.org/10.1175/WAF-D-12-00093.1
Page(s):
727–745
Restricted access

Abstract

A real-time, weather-adaptive three-dimensional variational data assimilation (3DVAR) system has been adapted for the NOAA Warn-on-Forecast (WoF) project to incorporate all available radar observations within a moveable analysis domain. The key features of the system include 1) incorporating radar observations from multiple Weather Surveillance Radars-1988 Doppler (WSR-88Ds) with NCEP forecast products as a background state, 2) the ability to automatically detect and analyze severe local hazardous weather events at 1-km horizontal resolution every 5 min in real time based on the current weather situation, and 3) the identification of strong circulation patterns embedded in thunderstorms. Although still in the early development stage, the system performed very well within the NOAA's Hazardous Weather Testbed (HWT) Experimental Warning Program during preliminary testing in spring 2010 when many severe weather events were successfully detected and analyzed. This study represents a first step in the assessment of this type of 3DVAR analysis for use in severe weather warnings. The eventual goal of this real-time 3DVAR system is to help meteorologists better track severe weather events and eventually provide better warning information to the public, ultimately saving lives and reducing property damage.

Corresponding author address: Jidong Gao, NOAA/National Severe Storm Laboratory, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: jidong.gao@noaa.gov

Abstract

A real-time, weather-adaptive three-dimensional variational data assimilation (3DVAR) system has been adapted for the NOAA Warn-on-Forecast (WoF) project to incorporate all available radar observations within a moveable analysis domain. The key features of the system include 1) incorporating radar observations from multiple Weather Surveillance Radars-1988 Doppler (WSR-88Ds) with NCEP forecast products as a background state, 2) the ability to automatically detect and analyze severe local hazardous weather events at 1-km horizontal resolution every 5 min in real time based on the current weather situation, and 3) the identification of strong circulation patterns embedded in thunderstorms. Although still in the early development stage, the system performed very well within the NOAA's Hazardous Weather Testbed (HWT) Experimental Warning Program during preliminary testing in spring 2010 when many severe weather events were successfully detected and analyzed. This study represents a first step in the assessment of this type of 3DVAR analysis for use in severe weather warnings. The eventual goal of this real-time 3DVAR system is to help meteorologists better track severe weather events and eventually provide better warning information to the public, ultimately saving lives and reducing property damage.

Corresponding author address: Jidong Gao, NOAA/National Severe Storm Laboratory, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: jidong.gao@noaa.gov
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