A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements

[1] A 2-hourly data set of atmospheric precipitable water (PW) has been produced from the zenith path delay (ZPD) derived from ground-based Global Positioning System (GPS) measurements. The PW data are available every 2 hours from 80 to 268 International GNSS Service (IGS, formally International GPS Service) ground stations from 1997 to 2004. The accuracy of the IGS ZPD product is roughly 4 mm. An analysis technique is developed to convert ZPD to PW on a global scale. Special efforts are made on deriving surface pressure (Ps) and water-vapor-weighted atmospheric mean temperature (Tm), which are two key parameters for converting ZPD to PW. Ps is derived from global, 3-hourly surface synoptic observations with temporal, vertical and horizontal adjustments. Tm is calculated from NCEP/NCAR reanalysis with temporal, vertical and horizontal interpolations. The derived Ps and Tm at the GPS location and height have root-mean-square (rms) errors of 1.65 hPa and 1.3 K, respectively. A theoretical error analysis concludes that typical PW error associated with the errors in ZPD, Tm and Ps is on the order of 1.5 mm. The PW data set is compared with radiosonde, microwave radiometer (MWR) and satellite data. The GPS and radiosonde PW comparisons at 98 stations around the globe show a mean difference of 1.08 mm (drier for radiosonde data) with a standard deviation of differences of 2.68 mm, which corresponds to mean percentage difference and standard deviation of 5.5% and 10.6%, respectively. The bias is primarily due to known dry biases in the Vaisala radiosonde data. The RMS difference between GPS and radiosonde/MWR data ranges from 1.2 mm to 2.83 mm. The latitudinal and seasonal variations of PW derived from the GPS data agree well with that from International Satellite Cloud Climatology Project (ISCCP) data if the ISCCP data are sampled only at grid boxes containing GPS stations. The large difference between GPS and ISCCP data in the subtropics is interesting, but is not easily explained. The comparisons did not reveal any systematic bias in GPS PW data and show that a RMS difference of less than 3 mm between GPS-derived PW and other data sets is achieved. The comparison study also illustrates the value of GPS-estimated PW for examining the quality of other data sets, such as those from radiosondes and MWR. Preliminary analysis of this data set shows interesting and significant diurnal variations in PW in four different regions.

[1]  Paul W. Stackhouse,et al.  Comparison of different global information sources used in surface radiative flux calculation: Radiative properties of the near‐surface atmosphere , 2006 .

[2]  Russell S. Vose,et al.  Overview of the Integrated Global Radiosonde Archive , 2006 .

[3]  T. Humphreys,et al.  The semidiurnal variation in GPS‐derived zenith neutral delay , 2005 .

[4]  Junhong Wang,et al.  Global estimates of water‐vapor‐weighted mean temperature of the atmosphere for GPS applications , 2005 .

[5]  Gerd Gendt,et al.  The New Tropospheric Product of the International GNSS Service , 2005 .

[6]  A Comparison of Total Precipitable Water between Reanalyses and NVAP , 2005 .

[7]  Shepard A. Clough,et al.  The effect of the half-width of the 22-GHz water vapor line on retrievals of temperature and water vapor profiles with a 12-channel microwave radiometer , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Kevin E. Trenberth,et al.  Trends and variability in column-integrated atmospheric water vapor , 2005 .

[9]  Jean-Pierre Aubagnac,et al.  Comparison of Near–Real Time Estimates of Integrated Water Vapor Derived with GPS, Radiosondes, and Microwave Radiometer , 2005 .

[10]  Geremew G. Amenu,et al.  NVAP and Reanalysis-2 Global Precipitable Water Products : Intercomparison and Variability Studies , 2005 .

[11]  G. Deblonde,et al.  Evaluation of GPS precipitable water over canada and the IGS network , 2005 .

[12]  A. Lacis,et al.  Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data , 2004 .

[13]  Bo-Cai Gao,et al.  A global water vapor data set obtained by merging the SSMI and MODIS data , 2004 .

[14]  Galina Dick,et al.  Near Real Time GPS Water Vapor Monitoring for Numerical Weather Prediction in Germany , 2004 .

[15]  Henrik Vedel,et al.  Impact of Ground Based GPS Data on Numerical Weather Prediction , 2004 .

[16]  Reinhard Dietrich,et al.  Comparison of Tropospheric Water Vapour over Antarctica Derived from AMSU-B Data, Ground-Based GPS Data and the NCEP/NCAR Reanalysis , 2004 .

[17]  Barry E. Schwartz,et al.  Rapid retrieval and assimilation of ground based GPS precipitable water observations at the NOAA Forecast Systems Laboratory: Impact on weather forecasts , 2004 .

[18]  Henrik Vedel,et al.  Impact of GPS Zenith Tropospheric Delay data on precipitation forecasts in Mediterranean France and Spain , 2004 .

[19]  J. Braun Remote Sensing of Atmospheric Water Vapor with the Global Positioning System , 2004 .

[20]  Gerd Gendt,et al.  On the determination of atmospheric water vapor from GPS measurements , 2003 .

[21]  Henrik Vedel,et al.  Accuracy and Variability of GPS Tropospheric Delay Measurements of Water Vapor in the Western Mediterranean , 2003 .

[22]  Jan-Peter Muller,et al.  Comparison of precipitable water vapor derived from radiosonde, GPS, and Moderate‐Resolution Imaging Spectroradiometer measurements , 2003 .

[23]  Fujio Kimura,et al.  Diurnal Variation of Precipitable Water over a Mountainous Area of Sumatra Island , 2003 .

[24]  Guergana Guerova,et al.  Validation of NWP Mesoscale Models with Swiss GPS Network AGNES , 2003 .

[25]  Douglas Hunt,et al.  REAL-TIME WATER VAPOR SENSING WITH SUOMINET -- TODAY AND TOMORROW , 2003 .

[26]  David Carlson,et al.  Corrections of Humidity Measurement Errors from the Vaisala RS80 Radiosonde—Application to TOGA COARE Data , 2002 .

[27]  Junhong Wang,et al.  Diurnal variation in water vapor over North America and its implications for sampling errors in radiosonde humidity , 2002 .

[28]  A NEW COMPOSITE OBSERVING SYSTEM STRATEGY FOR GROUND-BASED GPS METEOROLOGY , 2002 .

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

[30]  Water Vapor Variability in the Tropical Western Pacific from 20-year Radiosonde Data , 2001 .

[31]  W. Elliott,et al.  Radiosonde-Based Northern Hemisphere Tropospheric Water Vapor Trends , 2001 .

[32]  James J. Simpson,et al.  The NVAP global water vapor data set: independent cross-comparison and multiyear variability , 2001 .

[33]  Antonio Rius,et al.  The contributions of the MAGIC project to the COST 716 objectives of assessing the operational potential of ground-based GPS meteorology on an international scale , 2001 .

[34]  Yuei-An Liou,et al.  Comparison of Precipitable Water Observations in the Near Tropics by GPS, Microwave Radiometer, and Radiosondes , 2001 .

[35]  Isao Naito,et al.  Comparisons of GPS‐derived precipitable water vapors with radiosonde observations in Japan , 2000 .

[36]  Soroosh Sorooshian,et al.  SuomiNet: A Real-Time National GPS Network for Atmospheric Research and Education. , 2000 .

[37]  C. Deser,et al.  Diurnal and semidiurnal variations in global surface wind and divergence fields , 1999 .

[38]  Junhong Wang,et al.  Diurnal and Semidiurnal Tides in Global Surface Pressure Fields , 1999 .

[39]  W. Rossow,et al.  Advances in understanding clouds from ISCCP , 1999 .

[40]  Gunnar Elgered,et al.  A Comparison of Precipitable Water Vapor Estimates by an NWP Simulation and GPS Observations , 1999 .

[41]  Kevin E. Trenberth,et al.  Observed and model‐simulated diurnal cycles of precipitation over the contiguous United States , 1999 .

[42]  Markus Rothacher,et al.  The International GPS Service (IGS): An interdisciplinary service in support of Earth sciences , 1999 .

[43]  Paul Tregoning,et al.  Accuracy of absolute precipitable water vapor estimates from GPS observations , 1998 .

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

[45]  Jan M. Johansson,et al.  Three months of continuous monitoring of atmospheric water vapor with a network of Global Positioning System receivers , 1998 .

[46]  Christian Rocken,et al.  Near real‐time GPS sensing of atmospheric water vapor , 1997 .

[47]  Panmao Zhai,et al.  Atmospheric Water Vapor over China. , 1997 .

[48]  W. Elliott,et al.  Tropospheric Water Vapor Climatology and Trends over North America: 1973–93 , 1996 .

[49]  John R. Lanzante,et al.  An Assessment of Satellite and Radiosonde Climatologies of Upper-Tropospheric Water Vapor. , 1996 .

[50]  G. Stephens,et al.  A new global water vapor dataset , 1996 .

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

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

[53]  Steven Businger,et al.  GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water , 1994 .

[54]  Steven Businger,et al.  Sensing atmospheric water vapor with the global positioning system , 1993 .

[55]  Ying-Hwa Kuo,et al.  Assimilation of Precipitable Water Measurements into a Mesoscale Numerical Model , 1993 .

[56]  T. Herring,et al.  GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System , 1992 .

[57]  T. Barnett,et al.  Space and Time Scales of Global Tropospheric Moisture , 1991 .

[58]  Gunnar Elgered,et al.  Geodesy by radio interferometry - Water vapor radiometry for estimation of the wet delay , 1991 .

[59]  Jan Askne,et al.  Estimation of tropospheric delay for microwaves from surface weather data , 1987 .

[60]  I. Shapiro,et al.  Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length , 1985 .

[61]  Harold D. Black,et al.  The use of artificial satellites for geodesy , 1973 .