Validation of water vapour profiles from GPS radio occultations in the Arctic

The relevance of water vapour in atmospheric physics and climate research contrasts strongly with the availability of humidity data in the Arctic. The most extensive humidity data set is based on approx. 80 radiosonde stations north of 60°N, but suffers from two major problems: Sensor diversity and sensor limitations under Arctic conditions, on the one hand, and lacking radiosonde launch sites in the Arctic Ocean and the Greenland iceshield, on the other hand. Calibration free satellite borne instruments like the GPS receiver onboard CHAMP prevent from both handicaps. Comparisons between radiosonde data and GPS-based humidity profiles are presented for single occultations as well as averaged data from the proof-of-concept experiment GPS/MET and the recent CHAMP satellite mission. The effects of low absolute humidity and uncertain meteorological analyses are examined using additional information from a regional climate model. For the observations of CHAMP in summer 2001, a general dry bias has been found if compared with radiosonde data, apparent both in single and mean profile intercomparisons. In contrast, during February 1997 GPS/MET data show slightly higher humidity in the mid-troposphere, if compared with model data and objective analyses

A case study of using Raman lidar measurements in high-accuracy GPS applications

International audienceThis paper investigates the impact of rapid small-scale water vapor fluctuations on GPS height determination. Water vapor measurements from a Raman lidar are used for documenting the water vapor heterogeneities and correcting GPS signal propagation delays in clear sky conditions. We use data from four short observing sessions (6 h) during the VAPIC experiment (15 May–15 June 2004). The retrieval of wet delays from our Raman lidar is shown to agree well with radiosonde retrievals (bias and standard deviation (SD) were smaller than 1 and 2.8 mm, respectively) and microwave radiometers (from two different instruments, bias was 6.0/−6.6 mm and SD 1.3/3.8 mm). A standard GPS data analysis is shown to fail in accurately reproducing fast zenith wet delay (ZWD) variations. The ZWD estimates could be improved when mean post-fit phase residuals were removed. Several methodologies for integrating zenith lidar observations into the GPS data processing are also presented. The final method consists in using lidar wet delays for correcting a priori the GPS phase observations and estimating a scale factor for the lidar wet delays jointly with the GPS station position. The estimation of this scale factor allows correcting for a mis-calibration in the lidar data and provides in the same way an estimate of the Raman lidar instrument constant. The agreement of this constant with an independent determination using radiosonde data is at the level of 1–4%. The lidar wet delays were derived by ray-tracing from zenith pointing measurements: further improvement in GPS positioning is expected from slant path lidar measurements that would properly account for water vapor anisotropy