GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water

Bevis, Michael; Businger, Steven; Chiswell, Stephen M.; Herring, Thomas A.; Anthes, Richard A.; Rocken, Christian; Ware, Randolph

doi:10.1175/1520-0450(1994)033<0379:gmmzwd>2.0.co;2

Cited by 1,083 publications

(897 citation statements)

References 13 publications

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“…Determination of the empirical coefficients is reviewed by Bevis, et al (1994) and Elgered, et al (2005). Despite the fact that ZHD dominates over ZWD in the computation of ZTD, it is the effect of IWV on ZWD that makes the ZTD observations potentially valuable for NWP applications.…”

Section: Gps Ztd Observing Systemmentioning

confidence: 99%

An observing‐system experiment with ground‐based GPS zenith total delay data using HIRLAM 3D‐Var in the absence of satellite data

Eresmaa

Salonen

Järvinen

2010

Quart J Royal Meteoro Soc

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Ground-based receiver networks of the Global Positioning System (GPS) provide observations of atmospheric water vapour with a high temporal and horizontal resolution. Variational data assimilation allows researchers to make use of zenith total delay (ZTD) observations, which comprise the atmospheric effects on microwave signal propagation. An observing-system experiment (OSE) is performed to demonstrate the impact of GPS ZTD observations on the output of the High Resolution Limited Area Model (HIRLAM). The GPS ZTD observations for the OSE are provided by the EUMETNET GPS Water Vapour Programme, and they are assimilated using three-dimensional variational data assimilation (3D-Var).The OSE covers a five-week period during the late summer of 2008. In parallel with GPS ZTD data assimilation in the regular mode, the impact of a static bias-correction algorithm for the GPS ZTD data is also assessed.Assimilation of GPS ZTD data, without bias correction of any kind, results in a systematic increase in the forecast water-vapour content, temperature and tropospheric relative topography. A slightly positive impact is shown in terms of decreased forecast-error standard deviation of lower and middle tropospheric humidity and lower tropospheric geopotential height. Moreover, verification of categorical forecasts of 12 h accumulated precipitation shows a positive impact. The application of the static bias-correction scheme is positively verified in the case of the mean forecast error of lower tropospheric humidity and when relatively high precipitation accumulations are considered.

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Section: Gps Ztd Observing Systemmentioning

confidence: 99%

An observing‐system experiment with ground‐based GPS zenith total delay data using HIRLAM 3D‐Var in the absence of satellite data

Eresmaa

Salonen

Järvinen

2010

Quart J Royal Meteoro Soc

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“…The observations from Global Navigation Satellite System (GNSS) systems can be used to study the state of the troposphere at a given location and time by estimating the respective amount of zenith total delay (ZTD) and converting this to integrated water vapor (IWV) using surface meteorological data (Bevis et al 1994). Both of these GNSS-derived tropospheric parameters (ZTD and IWV) can further be assimilated into numerical weather prediction (NWP) models having a positive impact on the quality of weather forecasts (Bennitt and Levick 2011;de Haan 2011;Gutman et al 2004;Vedel et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of real-time precise point positioning zenith total delay estimates

et al. 2014

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The continuous evolution of global navigation satellite systems (GNSS) meteorology has led to an increased use of associated observations for operational modern low-latency numerical weather prediction (NWP) models, which assimilate GNSS-derived zenith total delay (ZTD) estimates. The development of NWP models with faster assimilation cycles, e.g., 1-h assimilation cycle in the rapid update cycle NWP model, has increased the interest of the meteorological community toward sub-hour ZTD estimates. The suitability of real-time ZTD estimates obtained from three different precise point positioning software packages has been assessed by comparing them with the state-of-the-art IGS final troposphere product as well as collocated radiosonde (RS) observations. The ZTD estimates obtained by BNC2.7 show a mean bias of 0.21 cm, and those obtained by the G-Nut/Tefnut software library show a mean bias of 1.09 cm to the IGS final troposphere product. In comparison with the RS-based ZTD, the BNC2.7 solutions show mean biases between 1 and 2 cm, whereas the G-Nut/Tefnut solutions show mean biases between 2 and 3 cm with the RS-based ZTD, and the ambiguity float and ambiguity fixed solutions obtained by PPP-Wizard have mean biases between 6 and 7 cm with the references. The large biases in the time series from PPP-Wizard are due to the fact that this software has been developed for kinematic applications and hence does not apply receiver antenna eccentricity and phase center offset (PCO) corrections on the observations. Application of the eccentricity and PCO corrections to the a priori coordinates has resulted in a 66 % reduction of bias in the PPP-Wizard solutions. The biases are found to be stable over the whole period of the comparison, which are criteria (rather than the magnitude of the bias) for the suitability of ZTD estimates for use in NWP nowcasting. A millimeter-level impact on the ZTD estimates has also been observed in relation to ambiguity resolution. As a result of a comparison with the established user requirements for NWP nowcasting, it was found that both the G-Nut/Tefnut solutions and one of the BNC2.7 solutions meet the threshold requirements, whereas one of the BNC2.7 solution and both the PPPWizard solutions currently exceed this threshold.

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“…For , since the temperature and humidity profiles are very difficult to obtain, particularly in a near-real-time mode, has to be calculated from a model. An empirical model dependent on surface temperature ( ) (Bevis et al, 1994) or a blind model developed from atmospheric reanalysis products (Böhm et al, 2015;Yao et al, 2013;Zhang et al, 2017) is often employed. 25…”

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confidence: 99%

Constructing Precipitable Water Vapor Map from Regional GNSS Network Observations without Collocated Meteorological Data

Chen

Dai

Liu

et al. 2018

Preprint

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Abstract. Surface pressure ( ) and weighted mean temperature ( ) are two necessary variables for the accurate retrieval of precipitable water vapor (PWV) from global navigation satellite system (GNSS) data. The lack of or information is a concern for those GNSS sites that are not collocated with meteorological sensors. This paper investigates an alternative method of inferring accurate and at the GNSS station using nearby synoptic observations. and obtained at the 15 nearby synoptic sites are interpolated onto the location of GNSS station by performing both vertical and horizontal adjustments, in which the parameters involved in and calculation are estimated from ERA-Interim reanalysis profiles.In addition, we present a method of constructing high quality PWV map through vertical reduction and horizontal interpolation of the retrieved GNSS PWVs. To evaluate the performances of the and retrieval and the PWV map construction, GNSS data collected from 58 stations of the Hunan GNSS network and synoptic observations from 20 nearby 20 sites in 2015 were processed to extract the PWV so as to subsequently generate PWV map. The retrieved and and constructed PWV maps were assessed by the results derived from radiosonde and ERA-Interim reanalysis. The results show that (1) accuracies of and derived by synoptic interpolation are within the range of 1.7-3.0 hPa and 2.5-3.0 K, respectively, which are much better than the GPT2w model; (2) the constructed PWV maps have good agreements with radiosonde and ERA reanalysis data with overall accuracy better than 3 mm; and (3) PWV maps can well reveal the moisture 25 advection, transportation and convergence during heavy rainfall.

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GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water

Cited by 1,083 publications

References 13 publications

An observing‐system experiment with ground‐based GPS zenith total delay data using HIRLAM 3D‐Var in the absence of satellite data

An observing‐system experiment with ground‐based GPS zenith total delay data using HIRLAM 3D‐Var in the absence of satellite data

Comparative analysis of real-time precise point positioning zenith total delay estimates

Constructing Precipitable Water Vapor Map from Regional GNSS Network Observations without Collocated Meteorological Data

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