The NOAA Forecast Systems Laboratory in Boulder, Colorado has developed operational techniques to retrieve integrated precipitable water vapor (IPW) from Global Positioning System (GPS) signal delays. We have demonstrated that it is possible to make these observations in near real-time under all weather conditions with high reliability and accuracy using commercial off-the-shelf geodetic quality GPS receivers. Techniques to assimilate GPS meteorological (GPS-Met) retrievals into mesoscale numerical weather prediction models such as the Rapid Update Cycle (RUC) have also been developed and tested, and continuous improvements in short-range moisture and precipitation forecast accuracy have been observed since parallel (i.e. with and without GPS-Met) runs began in 1997 (Benjamin et al., 1998; Smith et al., 1999, 2000, 2002; Gutman et al., 2001). One of the most definitive results is that the impact increases as the network of GPS-Met observing systems expands. This result is both reasonable and obvious, given the temporal and spatial variability of water vapor in the lower atmosphere, and the fact that water vapor is under-observed in both time and space at meso-alpha and smaller scales, especially during active weather. In recent years, state and local government agencies, universities, and even the private sector have started to operate a large number of CORS/DGPS receivers for high accuracy positioning and navigation applications. The GPS data from these sites can usually be made available with little effort or expense in near real-time, and their proliferation provides NOAA with an extraordinary opportunity to quickly and cost-effectively densify the GPS-Met network. We noted that many of these sites are being established in “close proximity” to airports, many of which are equipped with automated surface meteorological systems such as ASOS. The question is, what is the definition of “close proximity” when it comes to separating the wet and dry components of the GPS signal delay with “sufficient accuracy” to make the retrievals useful for objective and subjective weather forecasting? This paper reviews IPW retrieval accuracy issues, and compares NWP precipitable water vapor analysis and forecast accuracy with and without GPS observations. We have determined that a bias-corrected ASOS pressure observation can be used to parse a tropospheric GPS signal delay into its wet and dry components with sufficient accuracy if the ASOS is located within a radius of 50 kilometers and a vertical distance of less than 100 meters. The method of estimating and bias correcting ASOS pressure measurements is discussed.

References

Smith, T.L., S.G. Benjamin, B.E. Schwartz, B.E., and S.I. Gutman, 2002. Impact of GPS water vapor data on RUC severe weather forecasts. 21st Conference on Severe Local Storms, paper J5.3 (joint session with the NWP/WAF conference) San Antonio, TX Aug. 12-16.

Gutman, S.I., S.G. Benjamin, 2001. The Role of Ground-Based GPS Meteorological Observations in Numerical Weather Prediction, GPS Solutions, Volume 4, No. 4, pp. 16-24.

Smith, T.L., S.G. Benjamin, B.E. Schwartz, B.E., and S.I. Gutman, 2000. Using GPS-IPW in a 4-D data assimilation system. Earth, Planets and Space, 52, 921-926.

Smith, T.L., S.G Benjamin, B.E. Schwartz, and S.I. Gutman, 1999. Using GPS-IPW in a 4D Data Assimilation System, The International Symposium on GPS Application to Earth Sciences (GPS'99 in Tsukuba), October 18-22, Tsukuba, Ibaraki, Japan.

Benjamin, S., T. Smith, B. Schwartz, S. Gutman, and D. Kim, 1998: Precipitation forecast sensitivity to GPS precipitable water observations combined with GOES using RUC-2. 2nd Symp. on Int. Obs. Sys., AMS, Phoenix.