Trends in the Atmospheric Water Vapor Content From Ground-Based GPS: The Impact of the Elevation Cutoff Angle

We used 14 years of data from 12 GPS sites in Sweden and Finland to estimate trends in the atmospheric integrated water vapor (IWV) for 8 different elevation cutoff angles, from 5° to 40°, for the observations used in the analyses. These trends were compared to the corresponding trends obtained from radiosonde data at 7 nearby (<;120 km) sites. The results show a variation in the correlation of the trends between the two techniques for different elevation cutoff angles. The highest correlation coefficient of 0.88 is obtained for the 25^ solution, whereas the smallest root-mean-square (RMS) differences between the IWV estimates themselves are obtained mainly for elevation cutoff angles of 10° and 15°. The results show that elevation-angle-dependent systematic errors vary with time. Therefore the elevation cutoff angle giving the best agreement between radiosonde and GPS for individual IWV estimates is not necessarily the optimum when estimating linear trends. The correlation between the trends from the two completely independent techniques is strong evidence that the two techniques provide information on the IWV trends although the true individual values are too small to be uniquely detected. In addition, we found that the choice of mapping functions is not critical for the IWV trend estimation.

[1]  A. Niell Global mapping functions for the atmosphere delay at radio wavelengths , 1996 .

[2]  J. Saastamoinen,et al.  Contributions to the theory of atmospheric refraction , 1972 .

[3]  Richard B. Langley,et al.  Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water Vapor Radiometer, GPS, and VLBI , 2001 .

[4]  Jan M. Johansson,et al.  The impact of microwave absorber and radome geometries on GNSS measurements of station coordinates and atmospheric water vapour , 2011 .

[5]  Leopold Haimberger,et al.  Critically Reassessing Tropospheric Temperature Trends from Radiosondes Using Realistic Validation Experiments , 2009 .

[6]  Viju O. John,et al.  Recent developments in the line-by-line modeling of outgoing longwave radiation , 2006 .

[7]  Jung-Ho Cho,et al.  Trend Analysis of GPS Precipitable Water Vapor Above South Korea Over the Last 10 Years , 2010 .

[8]  Tobias Nilsson,et al.  Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data , 2008 .

[9]  J. Zumberge,et al.  Precise point positioning for the efficient and robust analysis of GPS data from large networks , 1997 .

[10]  Walter H. F. Smith,et al.  New, improved version of generic mapping tools released , 1998 .

[11]  H. Schuh,et al.  Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium‐Range Weather Forecasts operational analysis data , 2006 .

[12]  Michael Bevis,et al.  GPS meteorology: Reducing systematic errors in geodetic estimates for zenith delay , 1998 .

[13]  Gunnar Elgered,et al.  Climate monitoring using GPS , 2002 .

[14]  Steven Businger,et al.  The Promise of GPS in Atmospheric Monitoring , 1996 .

[15]  Galina Dick,et al.  Integrated water vapor from IGS ground-based GPS observations: initial results from a global 5-min data set , 2009 .

[16]  Jan M. Johansson,et al.  The Influence of Vegetation and Multipath on GNSS Signals , 2005 .

[17]  Ryuichi Ichikawa,et al.  Tsukuba GPS Dense Net Campaign Observation: Improvement in GPS Analysis of Slant Path Delay by Stacking One-way Postfit Phase Residuals , 2004 .

[18]  Shuanggen Jin,et al.  Variability and Climatology of PWV From Global 13-Year GPS Observations , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[19]  Valery U. Zavorotny,et al.  GPS Multipath and Its Relation to Near-Surface Soil Moisture Content , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[20]  Ragne Emardson,et al.  The systematic behavior of water vapor estimates using four years of GPS observations , 2000, IEEE Trans. Geosci. Remote. Sens..

[21]  Pedro Elosegui,et al.  Geodesy Using the Global Positioning System: The Effects of Signal Scattering , 1995 .

[22]  Christian Mätzler,et al.  Tropospheric water vapour above Switzerland over the last 12 years , 2009 .

[23]  Per Jarlemark,et al.  Ground‐based microwave radiometry and long‐term observations of atmospheric water vapor , 1998 .

[24]  J. Johansson,et al.  Continuous GPS measurements of postglacial adjustment in Fennoscandia 1. Geodetic results , 2002 .

[25]  R. Haas,et al.  Multi-Technique Comparisons of Ten Years of Wet Delay 1 Estimates on the West Coast of Sweden 2 , 2012 .

[26]  A. J. Miller,et al.  Factors affecting the detection of trends: Statistical considerations and applications to environmental data , 1998 .

[27]  Junhong Wang,et al.  Systematic Errors in Global Radiosonde Precipitable Water Data from Comparisons with Ground-Based GPS Measurements , 2008 .

[28]  Tobias Nilsson,et al.  Temporal correlations of atmospheric mapping function errors in GPS estimation , 2007 .

[29]  Peter Steigenberger,et al.  Generation of a consistent absolute phase-center correction model for GPS receiver and satellite antennas , 2007 .

[30]  Gunnar Elgered,et al.  Observation of long term trends in the amount of atmospheric water vapor by space geodesy and remote sensing techniques , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[31]  T. Emardson,et al.  On the relation between the wet delay and the integrated precipitable water vapour in the European atmosphere , 2000 .

[32]  F. Webb,et al.  An Introduction to the GIPSY/OASIS-II , 1993 .