Geodesy by radio interferometry: Water vapor radiometry for estimation of the wet delay

Elgered, Gunnar; Davis, J. L.; Herring, Thomas A.; Shapiro, I. I.

doi:10.1029/90jb00834

Cited by 244 publications

(130 citation statements)

References 26 publications

(21 reference statements)

Supporting

Mentioning

128

Contrasting

Unclassified

Order By: Relevance

“…Assuming the hydrostatic equilibrium of the neutral atmosphere, the ZHD at a given GPS station can be modelled using the surface pressure (P s in hPa) and an estimation of the mean gravity (g m ) of the atmospheric column (Saastamoinen, 1972;Davis et al, 1985;Elgered et al, 1991), where g m depends on the latitude ϕ (in degrees) and the height h of the station above the Earth ellipsoid (in m):…”

Section: Ztd To Iwv Conversion Schemementioning

confidence: 99%

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

et al. 2014

View full text Add to dashboard Cite

Abstract. Water vapour plays a dominant role in the climate change debate. However, observing water vapour over a climatological time period in a consistent and homogeneous manner is challenging. On one hand, networks of groundbased instruments able to retrieve homogeneous integrated water vapour (IWV) data sets are being set up. Typical examples are Global Navigation Satellite System (GNSS) observation networks such as the International GNSS Service (IGS), with continuous GPS (Global Positioning System) observations spanning over the last 15+ years, and the AErosol RObotic NETwork (AERONET), providing long-term observations performed with standardized and well-calibrated sun photometers. On the other hand, satellite-based measurements of IWV already have a time span of over 10 years (e.g. AIRS) or are being merged to create long-term time series (e.g. GOME, SCIAMACHY, and GOME-2).This study performs an intercomparison of IWV measurements from satellite devices (in the visible, GOME/SCIAMACHY/GOME-2, and in the thermal infrared, AIRS), in situ measurements (radiosondes) and ground-based instruments (GPS, sun photometer), to assess their use in water vapour trends analysis. To this end, we selected 28 sites world-wide for which GPS observations can directly be compared with coincident satellite IWV observations, together with sun photometer and/or radiosonde measurements. The mean biases of the different techniques compared to the GPS estimates vary only between −0.3 to 0.5 mm of IWV. Nevertheless these small biases are accompanied by large standard deviations (SD), especially for the satellite instruments. In particular, we analysed the impact of clouds on the IWV agreement. The influence of specific issues for each instrument on the intercomparison is also investigated (e.g. the distance between the satellite ground pixel centre and the co-located ground-based station, the satellite scan angle, daytime/nighttime differences). Furthermore, we checked if the properties of the IWV scatter plots between these different instruments are dependent on the geography and/or altitude of the station. For all considered instruments, the only dependency clearly detected is with latitude: the SD of the IWV observations with respect to the GPS IWV retrievals decreases with increasing latitude and decreasing mean IWV.

show abstract

Section: Ztd To Iwv Conversion Schemementioning

confidence: 99%

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

et al. 2014

View full text Add to dashboard Cite

show abstract

“…One of the most commonly used methods to obtain the ZHD is using the Saastamoinen formula, which is a function of surface pressure (Saastamoinen, 1972;Elgered et al, 1991;Niell et al, 2001). Davis et al (1985) pointed out that the uncertainty in the ZHD obtained from the Saatamoinen formula was 0.5 mm, if uncertainties in the physical constants and the calculation of the mean value of gravity were taken into consideration.…”

Section: Computation Of Zhd and Iwvmentioning

confidence: 99%

“…Equations (6) and (7), developed by Elgered et al (1991) based on the Saastamoinen formula, are adopted in this study to obtain the ZHD (in mm). These formulae have been widely used in many studies (Bevis et al, 1992;Bock and Doerflinger, 2001;Bokoye et al, 2003;Kleijer, 2004;Musa et al, 2011;Kumar et al, 2013;Norazmi et al, 2015).…”

Section: Computation Of Zhd and Iwvmentioning

confidence: 99%

Determination of zenith hydrostatic delay and its impact on GNSS-derived integrated water vapor

Wang

Zhang

et al. 2017

Atmos. Meas. Tech.

View full text Add to dashboard Cite

Abstract. Surface pressure is a necessary meteorological variable for the accurate determination of integrated water vapor (IWV) using Global Navigation Satellite System (GNSS). The lack of pressure observations is a big issue for the conversion of historical GNSS observations, which is a relatively new area of GNSS applications in climatology. Hence the use of the surface pressure derived from either a blind model (e.g., Global Pressure and Temperature 2 wet, GPT2w) or a global atmospheric reanalysis (e.g., ERAInterim) becomes an important alternative solution. In this study, pressure derived from these two methods is compared against the pressure observed at 108 global GNSS stations at four epochs (00:00, 06:00, 12:00 and 18:00 UTC) each day for the period 2000-2013. Results show that a good accuracy is achieved from the GPT2w-derived pressure in the latitude band between −30 and 30 • and the average value of 6 h root-mean-square errors (RMSEs) across all the stations in this region is 2.5 hPa. Correspondingly, an error of 5.8 mm and 0.9 kg m −2 in its resultant zenith hydrostatic delay (ZHD) and IWV is expected. However, for the stations located in the mid-latitude bands between −30 and −60 • and between 30 and 60 • , the mean value of the RMSEs is 7.3 hPa, and for the stations located in the high-latitude bands from −60 to −90 • and from 60 to 90 • , the mean value of the RMSEs is 9.9 hPa. The mean of the RMSEs of the ERAInterim-derived pressure across at the selected 100 stations is 0.9 hPa, which will lead to an equivalent error of 2.1 mm and 0.3 kg m −2 in the ZHD and IWV, respectively, determined from this ERA-Interim-derived pressure. Results also show that the monthly IWV determined using pressure from ERAInterim has a good accuracy − with a relative error of better than 3 % on a global scale; thus, the monthly IWV resulting from ERA-Interim-derived pressure has the potential to be used for climate studies, whilst the monthly IWV resulting from GPT2w-derived pressure has a relative error of 6.7 % in the mid-latitude regions and even reaches 20.8 % in the highlatitude regions. The comparison between GPT2w and seasonal models of pressure-ZHD derived from ERA-Interim and pressure observations indicates that GPT2w captures the seasonal variations in pressure-ZHD very well.

show abstract

“…For example, the zenith total delay (ZTD) estimated from a GPS analysis represents the vertically integrated value of the refractive index of the atmosphere; it can be split into the zenith hydrostatic delay (ZHD) and the zenith wet delay (ZWD). The former is mainly driven by the neutral gas content of the atmosphere and can be accurately estimated using ground pressure measurements (Elgered et al 1991), while the latter is directly related to the vertically integrated water vapor contents (precipitable water vapor (PWV)).…”

Section: Introductionmentioning

confidence: 99%

A Study of Near Real-time Water Vapor Analysis Using a Nationwide Dense GPS Network of Japan

Shoji¹

2009

Journal of the Meteorological Society of Japan

View full text Add to dashboard Cite

In order to use the nationwide dense receiver network of the Global Positioning System (GPS) in Japan to contribute to water vapor monitoring and numerical weather prediction, a near real-time (NRT) analysis trial was performed at the Meteorological Research Institute. In this paper, the NRT analysis procedure is described along with some validation results.In view of the computational load involved in analyzing more than 1,300 GPS stations in Japan, the precise point positioning (PPP) procedure was adopted. The PPP procedure requires accurate information of GPS satellites' positions and clock o¤sets. International GNSS Service (IGS) has been routinely providing ultra rapid ephemeris (IGU) that includes satellite orbits and clock o¤sets with latency of about 3 hours. We found the accuracy of satellite clock o¤sets in IGU was insu‰cient for the retrieval of precipitable water vapor (PWV) through the PPP procedure. Therefore, we applied correction to the IGU clock using the predicted clock o¤set at an IGS station ''USUD''. The hydrogen maser atomic clock at USUD also had some di¤erences with GPS time. However, we found it could be fitted and predicted by a linear equation for a period of several days.The resulting satellite clock o¤sets exhibited some biases toward the IGS final ephemeris, but the time constant biases of satellite clock o¤sets did not a¤ect the PWV retrieval at all. The retrieved PWV data agreed well with those obtained from radio-sonde observations. The root mean square di¤erences in summer and in winter were around 3.4 mm and 1.6 mm, respectively. The results were comparable with those obtained by preceding studies using the final ephemeris. The Retrieved spatial and temporal variation of PWV in a heavy rainfall case demonstrated the usefulness of the NRT PWV retrieval for weather monitoring. We could capture the water vapor increase that preceded torrential rain.

show abstract

Geodesy by radio interferometry: Water vapor radiometry for estimation of the wet delay

Cited by 244 publications

References 26 publications

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

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

Determination of zenith hydrostatic delay and its impact on GNSS-derived integrated water vapor

A Study of Near Real-time Water Vapor Analysis Using a Nationwide Dense GPS Network of Japan

Contact Info

Product

Resources

About