12.4 Assimilating Radar Radial Winds into the High-Resolution Rapid Refresh (HRRR) Model and Its Impact on Storm Forecasts

Thursday, 11 January 2018: 2:15 PM
Room 14 (ACC) (Austin, Texas)
Guoqing Ge, CIRES and NOAA/ESRL/GSD, Boulder, CO; and M. Hu, J. Beck, C. Zhou, H. Shao, S. Weygandt, S. Benjamin, and C. Alexander

The High-Resolution Rapid Refresh (HRRR) system is a NOAA operational convective allowing atmospheric model. It is hourly-updated, assimilates all available meteorological observations, such as surface, radiosonde, radar, satellite, aircraft and other observations, at a 3km high resolution and launches forecasts up to 36 hours. It provides very valuable convective forecast guidance for operational forecasters, meteorologists and disaster planners. It greatly helps improve storm forecasts.

Weather radar network is the only data source which can routinely provide storm-scale observations of the atmosphere at a very high time frequency. Utilizing this kind of precious radar data is vital for successful convective weather predictions. Currently, radar reflectivity data plays an import role in HRRR as it evidently improves forecasts. Its impact has been being examined. Radar radial winds are also used into HRRR analysis. To get best use of radial wind data, lots of fine tuning work are underway. For example, the super-obing of radial winds needs to be compatible with the 3km grid mesh and the shock to the model due to the assimilation of a great amount of radial winds data should be carefully addressed. The background error covariance matrix (BE) should also be correctly specified since at the 3km resolution, the BE is very different from that at a lower-resolution. Tests, evaluations as well as the enhancing development work on the improvement of radial winds data assimilation into HRRR will be reported at the meeting.

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