HR: 0800h
AN: G21B-1282    [Abstracts]
TI: A new improvement of ZTD estimation by modeling GPS systematic residuals
AU: * PARK, J
EM: jupark@kasi.re.kr
AF: Korea Astronomy and Space Science Institute, 61-1, Whaam-Dong, Yuseong-Gu, Daejeon, 305348 Korea, Republic of
AU: JIN, S
EM: sgjin@kasi.re.kr
AF: Korea Astronomy and Space Science Institute, 61-1, Whaam-Dong, Yuseong-Gu, Daejeon, 305348 Korea, Republic of
AU: JIN, S
EM: sgjin@kasi.re.kr
AF: Shanghai Astronomical Observatory, No 80, Shanghai, Shanghai, 200030 China
AU: PARK, P
EM: phpark@kasi.re.kr
AF: Korea Astronomy and Space Science Institute, 61-1, Whaam-Dong, Yuseong-Gu, Daejeon, 305348 Korea, Republic of
AB: The GPS-derived ZTD (Zenith Tropospheric Delay) with a high accuracy and a high resolution plays a key role in near real-time weather forecasting and improvement of Numeric Weather prediction (NWP) model. Traditionally, the GPS ZTD estimations were obtained based on the least squares (LS) principle, where the functional and stochastic models of GPS measurements need to be defined. The functional models for GPS measurements have been investigated in considerable detail in the past two decades. However, in all current GPS processing software programs, e.g. GAMIT, BERNESE or GIPSY, the stochastic models of GPS observation data are simplified, assuming that all the GPS measurements have the same variance, and that they are statistically independent in time and space. Such assumptions are unrealistic and will result in unreliable ZTD estimations. This paper aims to improve the GPS ZTD estimations by modeling GPS systematic residuals into the stochastic model. The results show that the GPS ZTD estimation can be obviously improved through stochastic models, which is certainly critical for reliable Numeric Weather prediction (NWP).
DE: 1220 Atmosphere monitoring with geodetic techniques (6952)
DE: 1240 Satellite geodesy: results (6929, 7215, 7230, 7240)
SC: Geodesy [G]
MN: Fall Meeting 2005