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

Abstract

[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 (P s ) and water-vapor-weighted atmospheric mean temperature (T m ), which are two key parameters for converting ZPD to PW. P s is derived from global, 3-hourly surface synoptic observations with temporal, vertical and horizontal adjustments. T m is calculated from NCEP/NCAR reanalysis with temporal, vertical and horizontal interpolations. The derived P s and T m 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, T m and P s 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.Citation: Wang, J., L. Zhang, A. Dai, T. Van Hove, and J. Van Baelen (2007), A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements,

A multi-site intercomparison of integrated water vapour observations for climate change analysis

“…Its accuracy depends thus mainly on errors in the pressure measurements, causing offsets in the IWV estimates of at most 0.8 mm when considering an error in the pressure of 2 hPa (Vey et al, 2010). Other surface pressure uncertainties reported in the literature are 1 hPa (Deblonde et al, 2005) and 1.65 hPa (Wang et al, 2007), corresponding respectively to 0.4 and 0.6 mm uncertainty in IWV. Only during extreme (and rare) events, the atmosphere departs from hydrostatic equilibrium and consequently, this assumption can lead to significant errors in the IWV estimation (Brenot et al, 2006).…”

“…In this paper, we will concentrate on this integrated water vapour (IWV) amount, also commonly known as precipitable water vapour (PW or PWV) or total column water vapour (TCWV), and we will express the IWV in units of mm. It is defined as the liquid equivalent of the total water vapour contained in an air column from the Earth's surface to the top of the atmosphere (Wang et al, 2007). This primary atmospheric variable can be measured by different devices, among which are ground-based, satellite-based and in situ instrumental techniques.…”

“…for GOME-2 there can be two overpasses per day with a time difference of about 1.5 h. a Deblonde et al (2005); Wang et al (2007); Vey et al (2010). b Miloshevich et al (2009);Smit et al (2013); Wang et al (2013).…”

“…By this approach, we neglect the small contribution of the atmospheric layers above 500 hPa to the total column water vapour. Wang et al (2007) pointed out that this introduces a dry bias of 2.44 % in IWV.…”

“…For 13 out of the 28 selected IGS stations in our selection, more than one WMO station lies within the imposed maximum horizontal distance of 50 km, allowing different strategies to be applied for the ZTD to IWV conversion. For instance, Wang et al (2007) propose to use the weighted average of the pressure observations (corrected for the altitude difference) of all selected synoptic stations to obtain the pressure at the GPS station height and location. However, different synoptic data sources of deviating quality and at sometimes diosonde and CIMEL sun photometer instruments is found in the Northern Hemisphere.…”