7B.5 Further Improvements of Radial Wind Assimilation in the High-Resolution Rapid Refresh (HRRR) model

Tuesday, 5 June 2018: 2:30 PM
Colorado B (Grand Hyatt Denver)
Guoqing Ge, CIRES and NOAA/ESRL/GSD, Boulder, CO; and M. Hu, C. Zhou, J. Beck, S. Weygandt, 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 convective-scale 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 ingested into HRRR. To get best use of radial wind data, lots of fine tuning work are underway. We examined the impact of radar superob settings, the impact of decorrelation length scales and ensemble localization scales. One week long retrospective experiments showed that assimilating radial winds does not degrade synoptic forecast skills while slightly improve the prediction of individual storm cells. Further experiments will be conducted to assimilate radial wind data subhourly and repeatedly in a one-hour time window to check whether storm forecasts can be further improved. 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.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner