Thursday, 23 June 2005: 11:30 AM
South Ballroom (Hilton DeSoto)
Global radiosonde data represent an increasingly valuable resource for studies of climate change. Unfortunately, the usefulness of radiosonde data for long-term climate monitoring is limited by errors and biases associated with instrument and data processing procedures and by radiosonde changes among stations and with time. The primary goal of this study is to take advantage of increasing volume and maturity of GPS data and more importantly its long-term stability, and use it to monitor the quality of global radiosonde data. An analysis technique is under-developing to derive and continuously update a near real-time, global, 2-hourly data set of atmospheric precipitable water (PW) obtained from ground-based GPS measurements of zenith path delay (ZPD). The GPS ZPD data are currently available every two hours at about 360 GPS ground stations as part of the International GPS Service (IGS) products. This number has been increasing and is expected to continue to increase. Global radiosonde humidity data are compared with GPS-derived PW data to quantify spatial and temporal inhomogeneity and biases in radiosonde data. Preliminary analysis of PW differences between GPS and radiosonde data at 21 stations around the globe shows that radiosonde data at most of stations have dry biases, which is consistent with the conclusion based on analysis of WMO radiosonde inter-comparison data. This type of comparisons will be applied to global and multi-year data. The GPS-PW data have been used to monitor the quality of radiosonde humidity data, which are employed to initialize NWP models. The preliminary work on why there are sometimes large PW differences between GPS and radiosonde data at one station show that the near-surface inversion, which is unique for radiosonde station but not able to be measured by GPS, contributes to the large differences. Therefore, we suggest that cautions have to be taken for such comparison, and call for co-locating GPS and radiosonde stations in the future for climate monitoring.
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