1. Slide 1EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 M. Troller (1), E. Brockmann (2), D. Ineichen (2), S. Lutz (1), A. Geiger (1), H.-G. Kahle (1) (1) Institute of Geodesy and Photogrammetry, Swiss Federal Institute of Technology, Zuerich, Switzerland (2) Swiss Federal Office of Topography, Geodetic bases and permanent networks, Wabern, Switzerland Determination of the 3D Water Vapor Distribution in the Troposphere on a Continuous Basis Using GPS

2. Slide 2EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Swiss AGNES-Network (operated by swisstopo) 30 AGNES stations 48 additional stations AGNES height range: 400 m (FHBB) - 3‘600 m (JUJO) AGNES stations Other stations

3. Slide 3EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 GPS-tomography – Voxel model  3x6 mesh elements, open elements at the boundaries  15 levels between 0 and 8000 meters; 1 more level alof  Hourly profiles

4. Slide 4EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 GPS-Tomography: Real Measurements and Pseudo-Measurements GPS Double Difference Delays: Main Measurements: Further Measurements: GPS Zenith Delays Inter-Voxel Constraints (C) Ground Meteorological Measurements (P) Time Constraints (T) Radiosondes (R) Pseudo- Measurements:

5. Slide 5EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Comparison of Refractivity Profiles C: Inter-voxel constraints P: Ground meteorlogical data T: Time constraints R: Radiosondes

6. Slide 6EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Comparison of Refractivity Profiles FALE ZIMM PAYE C: Inter-voxel constraints P: Ground meteorlogical data T: Time constraints R: Radiosondes

7. Slide 7EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Time Series of rms compared to aLMo C: Inter-voxel constraints P: Ground meteorlogical data T: Time constraints R: Radiosondes

8. Slide 8EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 rms compared to aLMo of the different GPS stations C: Inter-voxel constraints P: Ground meteorlogical data T: Time constraints R: Radiosondes

9. Slide 9EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Mean rms of the individual layers compared to aLMo C: Inter-voxel constraints P: Ground meteorlogical data T: Time constraints R: Radiosondes

10. Slide 10EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Statistical rms of all profiles over the entire period [ppm] (refractivity unit) mean offsetmean rmsmean std. AWATOS C-2.37.36.0 AWATOS CP0.65.04.0 AWATOS CPT0.34.83.8 AWATOS CPTR0.64.73.7 29 stations 336 time periods Mean of: 9744 profiles in total C: Inter-voxel constraints P: Ground meteorlogical data T: Time constraints R: Radiosondes

11. Slide 11EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Conclusions GPS-Tomography has been successfully developed An application using the Swiss National GPS reference network AGNES was demonstrated, the software is running routinely at swisstopo Tomography is a promising method for regions with dense GPS network: a ll weather, high spatial and temporal resolution Compared with the aLMo/7 analysis, a consistent accuracy of about 1mm water vapor was reached (calculated over voxel elements) The method has the tendency to introduce too much smoothing in the vertical

12. Slide 12EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Outlook – New field campaign Region with complex topography (400 - 4000 m) 20 GPS receivers 1 week, early July 2005 Tomography solution: 6x6 profiles, 5km mesh Radiosondes and aLMo/7 for validation – currently under way

13. Slide 13EGU 2005, Vienna, Austria, 24-29 April 2005Tuesday, 26 April 2005 Outlook – Further developments Incorporate additional sources of humidity information in tomography software –GPS occultation (transverse data) –Satellite aloft cloud cover (profiles in upper troposhere) –Cloud location (saturated regions) –Lidar and other Use aLMo short range forecast (3h) as first guess –Weight should be derived from error statistic Systematic verification within a longer period Ingest humidity profiles in aLMo –Tune structure functions Impact study with aLMo/2