Precipitable water vapor estimates from homogeneously reprocessed GPS data: an intertechnique comparison in Antarctica

• Published in: Journal of Geophysical Research
• Main Authors: Thomas, ID, King, MA, Clarke, PJ, Penna, NT
• Format: Article in Journal/Newspaper
• Language: English
• Published: Amer Geophysical Union 2011
• Subjects: Engineering; Geomatic Engineering; Geodesy; Antarctic; Antarc*; Antarctica; Antarctica Journal
• Online Access: https://doi.org/10.1029/2010JD013889; http://ecite.utas.edu.au/89662

Homogeneously reprocessed GPS data offer the possibility of an accurate, stable,and increasingly long‐term record of integrated precipitable water vapor (PW) ofparticular value in data sparse regions. We present such a global reanalysis of GPS data,focusing on 12 Antarctic sites. We show stepwise improvements of GPS zenith totaldelay (ZTD) estimates upon adoption of each of (1) absolute antenna phase centrevariations, (2) VMF1 tropospheric mapping functions, and (3) an accurate model ofa priori zenith hydrostatic delay (ZHD) from observed surface meteorological data.The cumulative effect of these three additions to the analysis is a systematic decrease inthe magnitude of GPS estimates of ZTD by an average of ∼11 mm ZTD (∼1.8 mm PW).The resultant GPS PW data set for 2004 shows a mean bias to radiosonde measurementsof ‐0.48 mm PW. Our conclusion is that, in Antarctica at least, a proportion of thewidely observed bias between GPS and radiosonde measurements can be explained byearlier GPS analysis deficiencies. We also compare our GPS PW measurements with AIRSand MODIS level 2 PW products. The GPS agreements with AIRS and MODIS arecomparable. Reanalyzed GPS gives typically larger measurements than AIRS with amean site bias of 0.58 mm PW and a mean rms of 1.24 mm PW. By contrast, the GPSmeasurements are typically smaller than those from MODIS, with a mean site bias of‐0.35 mm PW and rms of 1.42 mm PW. PW estimates from reprocessed GPS solutionsusing state‐of‐the‐art models now have greater potential for assimilation into regionalor global numerical weather models.