GPS-IPW observations and their assimilation into the 20-km RUC during severe weather season

GPS-IPW observations and their assimilation into the 20-km RUC during severe weather season

Tracy Lorraine Smith, Stephen S. Weygandt, Stanley G. Benjamin, Seth I. Gutman, and Susan Sahm

Analyzing the rapidly evolving moisture field is an essential component of severe weather forecasting. GPS-IPW observations are a new and important asynoptic data source of moisture information for data assimilation. At present, the NOAA GPS-Met network has nearly 300 sites across the United States providing continuous half hourly observations of integrated precipitable water (IPW) in near real time and under all weather conditions.

For over a year, 20-km RUC analyses and forecasts with and without GPS-IPW data have been compared hourly to the GPS-IPW observations. Studies have shown the GPS-IPW data to have comparable quality to integrated (total column) RAOB observations, and using hourly GPS-IPW data allows for the verification of many more analyses and forecasts from all cycles.

Investigation into the impact of the data shows that GPS-IPW improves the RUC analysis fit to the observations by approximately 1.5 mm. In RUC forecasts the improvement due to the inclusion of GPS-IPW is around 1 mm for the 3-h forecast, with a slight impact persisting into the 6-h (~.4 mm) and 9-h (~.2 mm) forecasts. Stratification of the statistics by season reveals that for more volatile, fast moving spring weather, the RMS error in PW in the model increases, making the GPS-IPW data even more important in correcting the analysis moisture field. The location and migration of features such as drylines and rapidly returning Gulf moisture can be tracked by GPS-IPW and is vital for updating the hourly RUC.

We will also investigate the role of GPS-IPW in the forecasts for several individual severe weather situations from spring 2004. Observations of GPS-IPW in the area will be examined, along with their impact on the 20-km RUC forecasts. The temporal and spatial density of the network also allows for interesting in situ storm observations.

Both statistical and individual impacts will be presented at the conference.

Real time comparisons of the two versions of RUC can be viewed at http://gpsmet.noaa.gov/cgi-bin/ruc20/ruc20.cgi