HR: 09:30h
AN: G51D-07    [Abstracts]
TI: Tropospheric Signal Delay Estimates Derived from Numerical Weather Prediction Models and Their Impact on Real-Time GNSS Positioning Accuracy
AU: * Gutman, S I
EM: Seth.I.Gutman@noaa.gov
AF: NOAA Earth System Research Laboratory, 325 Broadway R/GSD7, Boulder, CO 80305-3328, United States
AU: Bock, Y
EM: ybock@ucsd.edu
AF: Institute of Geophysics and Planetary Physics, University of California San Diego, 9500 Gilman Drive DEPT 0225, La Jolla, CA 92093-0225, United States
AB: The accurate characterization of atmospheric moisture fields (including water vapor and clouds) is essential for improved weather forecasting and climate monitoring. Despite its importance, the ability to do so under all weather conditions has been a continuing problem for atmospheric scientists. The principle reason why this problem has been so difficult to solve is related to the high temporal and spatial variability of water in the free atmosphere. Under certain circumstances the distribution of moisture in the atmosphere can change abruptly over short distances, and this causes it to be under-observed using conventional weather observing systems. As water vapor, temperature and pressure change in the atmosphere, the refractivity of the troposphere changes accordingly and GNSS accuracy can suffer if the hydrostatic and wet signal delays are mismodeled. Recognizing this, the geodetic community developed techniques to treat the signal delays caused by the neutral atmosphere as nuisance parameters and remove them for high accuracy positioning applications. In ground-based GNSS/GPS Meteorology at NOAA, the tropospheric signal delay is estimated in near real-time from a network of about 400 continuously operating reference stations distributed across the U.S. using an 8-hr sliding window technique. Estimates of tropospheric refractivity (and/or integrated precipitable water vapor retrieved from these delays) have been assimilated into numerical weather prediction models in the U.S., Canada, Europe and Japan with exceptionally good results. Based on these and other findings, GNSS/GPS-Met is scheduled to transition from NOAA Research into operational use in NOAA's National Weather Service starting in 2009. Recognizing the need for improved ways to mitigate tropospheric effects on GNSS accuracy, especially for applications requiring low-latency measurements of height, scientists at NOAA's Earth System Research Laboratory began to investigate the feasibility of using operational numerical weather prediction (NWP) models to estimate the wet and dry refractivity of the troposphere to assist in integer-cycle ambiguity resolution and improve vertical position accuracy. The NOAA Tropospheric Signal Delay Model (NOAATrop) uses the state variables derived from NOAA's Rapid Update Cycle NWP model that assimilated GPS along with all other available atmospheric measurements to provide real-time zenith hydrostatic and wet signal delays, and their horizontal gradients, with a 2D RMS error of < 2.5 cm in the cool season and < 5 cm in the warm season. In this presentation, we will take a look "under the hood" of the NOAATrop model, explain how it works, give some examples from real-time GPS networks, and present some possible applications to the Earth System Science community.
UR: http://gpsmet.noaa.gov
DE: 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE
DE: 0365 Troposphere: composition and chemistry
DE: 1241 Satellite geodesy: technical issues (6994, 7969)
DE: 1295 Integrations of techniques
SC: Geodesy [G]
MN: 2007 Fall Meeting