87th AMS Annual Meeting

Tuesday, 16 January 2007: 4:00 PM
Monitoring the quality of global radiosonde humidity record using ground-based GPS measurements
207A (Henry B. Gonzalez Convention Center)
Junhong Wang, NCAR, Boulder, CO; and L. Zhang
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 Global Positioning System (GPS) data and more importantly its long-term stability, and use it to monitor the quality of global radiosonde data and potentially improve the long-term radiosonde climate records. A global, 9-year (1997-2005), 2-hourly data set of atmospheric precipitable water (PW) has been produced from ground-based GPS measurements of zenith path delay (ZPD) and will be updated frequently when the ZPD becomes available. The GPS PW data are available every two hours at about 350 International GPS Service (IGS) ground stations. We found total 102 stations, where radiosonde and GPS stations are within 50 km in distance and within 100 m in elevations. The PW comparison at 102 stations around the globe shows mean difference of -1.53 mm (drier radiosonde PW) with a mean rms difference of 1.95 mm. The comparison reveals systematic and significant biases in three widely-used radiosonde types, dry biases in Vaisala sondes (both RS80 and RS90) and wet biases in MRZ and IM-MK3 radiosondes. The dry bias in Vaisala sondes has larger magnitudes during the day than at night, especially for RS90, and increases with PW. The wet bias does not vary significantly with PW for MRZ, but prevails at PW < 30 mm for IM-MK3. The radiosonde type change from VIZ to Vaisala at a U.S. station was detected by the time series of PW differences between radiosonde and GPS. Such change would have significant impact on the long-term trend estimate. Seasonal mean diurnal sampling errors of twice-daily radiosonde data are within 2% at more than 87% of stations, but can be as much as 20% at some stations for once-daily sounding at 00 UTC. The diurnal sampling error reaches the maximum in winter, and mean absolute values are larger than 2% at 60% of stations for once-daily sounding in winter.

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