Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length

Davis, J. L.; Herring, T. A.; Shapiro, I. I.; Rogers, A. E. E.; Elgered, Gunnar

doi:10.1029/rs020i006p01593

Cited by 1,119 publications

(832 citation statements)

References 15 publications

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“…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

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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.

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Section: Ztd To Iwv Conversion Schemementioning

confidence: 99%

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

et al. 2014

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“…The standard atmospheric product is the zenith tropospheric delay (ZTD). This quantity is the vertical projection of the delay of the electromagnetic wave that has travelled between a satellite (at 20 200 km altitude) and a ground-based receiver with respect to propagation in a vacuum (Davis et al, 1985). The standard procedure for GPS data analysis assumes that the delay in any direction can be mapped from the delay at zenith.…”

Section: Description Of the Datasetmentioning

confidence: 99%

Water vapour variability induced by urban/rural surface heterogeneities during convective conditions

Champollion

Drobinski

Haeffelin

et al. 2009

Quart J Royal Meteoro Soc

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Scientific interest in urban meteorology has increased because highly populated areas experience high vulnerability to pollution or heavy rain. However, compared to urban air quality or urban heat island (UHI) processes, the urban water vapour cycle is poorly understood because it has been investigated less due to the lack of upper-air measurements and the high sensitivity of surface measurements to local heterogeneities. In this paper, surface measurements of wind, temperature, pressure and humidity, as well as integrated water vapour (IWV) from GPS and MODIS and numerical simulations, have been used to investigate the urban cycle of water vapour in May and June 2004 during the VAPIC field experiment in the Paris area.The surface data show the typical characteristics of an urban area with the absence of water vapour sources and a UHI of about 6 • C at night. The urban IWV distribution differs completely, with an urban IWV excess on average between 1600 and 0600 UTC (with a maximum of about 1.5 kg m −2 at 0600 and 1700 UTC). No IWV difference between the urban and rural areas is found in the middle of the day. The numerical simulations reproduce accurately the urban IWV anomaly.Shallow surface wind convergence associated with the UHI during nighttime provides moisture from the rural areas. Urban areas are therefore under wind convergence for most of the time. The rural water vapour sources and the depth of the convergence control the amplitude of the urban IWV excess. At about 1200 UTC, entrainment at the top of the urban boundary layer is the key process that inhibits the urban IWV excess observed at night.

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“…First, it is normal to assume that in the vicinity of the GPS receiver the atmosphere has azimuthal symmetry. Second, the delay is usually estimated in the zenith direction only, exploiting the dependence of the delay on the elevation angle via the use of a mapping function [e.g., Davis et al, 1985;Niell, 1996]. Bar-Sever et al…”

Section: Gps Zenith Delay Observationsmentioning

confidence: 99%

“…Variations in pressure, temperature, and water vapor content cause changes in the effective refractive index along the ray path and therefore corrupt any geometric delay or phase change measurement and degrade any parameters or products estimated from such measurements. We seek to understand the nature and effect The atmospheric delay is usually divided into two components' the hydrostatic and wet components (see Davis et al [1985] for a thorough description). The wet component results from the permanent dipole moment of water molecules.…”

Section: Introductionmentioning

confidence: 99%

Integrated satellite interferometry: Tropospheric noise, GPS estimates and implications for interferometric synthetic aperture radar products

Williams¹,

Bock²,

Fang³

1998

J. Geophys. Res.

260

204

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Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length

Cited by 1,119 publications

References 15 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

Water vapour variability induced by urban/rural surface heterogeneities during convective conditions

Integrated satellite interferometry: Tropospheric noise, GPS estimates and implications for interferometric synthetic aperture radar products

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