Convective Storms & NWP Seminar Series presents...
Detection of Hazardous Weather Phenomena Using Data Assimilation Techniques
Robert Fritchie
Weather Decision Technologies (WDT), Norman, OK
06 March 2009, 2:00 PM
National Weather Center, Room 5600
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK
Directions to the NWC (.pdf, 60 kb)
Currently, the most widely used paradigm for the automated detection of tornadoes and other hazardous weather events involves identifying patterns in Doppler radar reflectivity and velocity data. The patterns include gate-to-gate shear, strong convergence oriented in lines, descending areas of high reflectivity, etc. The major limitation of this technique, however, is that new detection algorithms must be created, or existing ones adapted, each time a new observation system is deployed (e.g., TDWR). Further, they operate principally on data directly measured by the sensor (e.g., radial velocity and reflectivity) and thus cannot make use of fine-scale fields that are potentially available (e.g., pressure deviation and temperature fields within the storms). Finally, such systems are limited in their ability to synthesize data from other observing platforms in a dynamically consistent manner.
An alternative approach that has the potential to overcome these limitations involves using advanced data assimilation and retrieval techniques, applied to all available observations - especially those collected at fine scales by Doppler radar - to generate dynamically consistent, 3D gridded analyses of all key observed and unobserved meteorological quantities to which detection tools can be applied. The potential advantages include the ability to interrogate quantities not available from radar data alone and the use of geometrically simple 3D grids.
To examine the tradeoffs in hazardous weather detection between conventional sensor-based algorithms and the potential of applying algorithms to assimilated, gridded analyses, we compare detections produced by the Warning Decision Support System-Integrated Information (WDSS-II) to features in analyses that are generated using ensemble Kalman filtering for an observed tornadic storm that occurred on 29 May 2004 and that was observed at reasonably close range by NEXRAD radar.