[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,

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Global Positioning System (GPS) receivers, water vapor radiometers (WVRs), and surface meteorological equipment were operated at both ends of a 50‐km baseline in Colorado to measure the precipitable water vapor (PWV) and wet delay in the line‐of‐sight to GPS satellites. Using high precision orbits, WVR‐measured and GPS‐inferred PWV differences between the two sites usually agreed to better than 1 mm. Using less precise on‐line broadcast orbits increased the discrepancy by 30%. Data simulations show that GPS measurements can provide mm‐level separate PWV estimates for the two sites, as opposed to just their difference, if baselines exceed 500 km and the highest accuracy GPS orbits are used.

[1] Diurnal variations in atmospheric water vapor are studied by analyzing 30-min-averaged data of atmospheric precipitable water (PW) for 1996-2000 derived from Global Position System (GPS) observations from 54 North America stations. Vertical structures in the diurnal cycle of atmospheric water vapor are examined using 3-hourly radiosonde data from Lamont, Oklahoma, during the 1994 -2000 period. Significant diurnal variations of PW are found over most of the stations. The diurnal (24 hour) cycle, S 1 , which explains over 50% of the subdaily variance, has an amplitude of 1.0 -1.8 mm over most of the central and eastern United States during summer and is weaker in other seasons. The S 1 peaks around noon in winter and from midafternoon to midnight in summer. The semidiurnal (12 hour) cycle is generally weak, with an amplitude of a few tenths of 1 mm. At Lamont, specific humidity in the free troposphere is significantly higher in the early morning (0000 -0008 local solar time (LST)) than during the day (0800 -1800 LST). This diurnal variation changes little from $4 to 16 km above the ground. Near the surface, specific humidity tends to be lower in the morning than in the afternoon and evening in all seasons except summer. This near-surface diurnal cycle propagates upward through the lower troposphere (up to $4 km). Errors in seasonal mean humidity due to undersampling the diurnal cycle with twice-daily synoptic soundings (at 0000 and 1200 UTC) are generally small (within ±3% or ±0.5 mm for PW), but it can easily reach 5 -10% if there is only one random sounding per day. Several physical processes are proposed that could contribute to the diurnal variations in atmospheric water vapor.

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The upper-air sounding network for Dynamics of the Madden-Julian Oscillation (DYNAMO) has provided an unprecedented set of observations for studying the MJO over the Indian Ocean, where coupling of this oscillation with deep convection first occurs. With 72 rawinsonde sites and dropsonde data from 13 aircraft missions, the sounding network covers the tropics from eastern Africa to the western Pacific. In total nearly 26 000 soundings were collected from this network during the experiment's 6-month extended observing period (from October 2011 to March 2012). Slightly more than half of the soundings, collected from 33 sites, are at high vertical resolution. Rigorous post-field phase processing of the sonde data included several levels of quality checks and a variety of corrections that address a number of issues (e.g., daytime dry bias, baseline surface data errors, ship deck heating effects, and artificial dry spikes in slow-ascent soundings).Because of the importance of an accurate description of the moisture field in meeting the scientific goals of the experiment, particular attention is given to humidity correction and its validation. The humidity corrections, though small relative to some previous field campaigns, produced high-fidelity moisture analyses in which sonde precipitable water compared well with independent estimates. An assessment of operational model moisture analyses using corrected sonde data shows an overall good agreement with the exception at upper levels, where model moisture and clouds are more abundant than the sonde data would indicate.

Abstract. We describe sensing of atmospheric column water min. The Yellowstone site transmits GPS data to Boulder every 30 vapor in near real-time using the Global Positioning System sec via satellite link. This site is operated primarily to monitor (GPS). We use predicted GPS orbits for automated computation of geodetic deformation of the volcanic caldera and does not provide vertical column water vapor within 30 minutes of GPS data col-surface meteorological data. lecfion. Based on a 4 month comparison, near real-time GPS col-The real-time GPS network extends more than 1,500 km from umn water vapor agrees with radiosondes and radiometers within the Mississippi Gulf coast to Yellowstone. A network of this size 2 mm rms. Our near real-time column water vapor data are posted hourly at www. unavco. ucar. edu. They are available for assimilation in numerical weather models and for other applications.

The sensing of precipitable water (PW) using the Global Positioning System (GPS) in the near Tropics is investigated. GPS data acquired from the Central Weather Bureau's Taipei weather station in Banchao (Taipei), Taiwan, and each of nine International GPS Service (IGS) stations were utilized to determine independently the PW at the Taipei site from 18 to 24 March 1998. Baselines between Taipei and the other nine stations range from 676 to 3009 km. The PW determined from GPS observations for the nine baseline cases are compared with measurements by a dual-channel water vapor radiometer (WVR) and radiosondes at the Taipei site. Although previous results from other locations show that the variability in the rms difference between GPS-and WVRobserved PW ranges from 1 to 2 mm, a variability of 2.2 mm is found. The increase is consistent with scaling of the variability with the total water vapor burden (PW). In addition, accurate absolute PW estimates from GPS data for baseline lengths between 1500 and 3000 km were obtained. Previously, 500 and 2000 km have been recommended in the literature as the minimum baseline length needed for accurate absolute PW estimation. An exception occurs when GPS data acquired in Guam, one of the nine IGS stations, were utilized. This result is a possible further indication that the rms difference between GPS-and WVR-measured PW is dependent on the total water vapor burden, because both Taipei and Guam are located in more humid regions than the other stations.