Ground-based GNSS ZTD/IWV estimation system for numerical weather prediction in challenging weather conditions

Rohm, Witold; Yuan, Yubin; Biadeglgne, Bertukan; Zhang, Kefei; Marshall, J. Le

doi:10.1016/j.atmosres.2013.11.026

Cited by 68 publications

(47 citation statements)

References 24 publications

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“…Accurate knowledge of water vapor is not only vital for weather forecasting but also an important independent data source for global climate studies. For the last decade, the Global Navigation Satellite System (GNSS) has been used as an emerging and robust tool for remotely sensing integrated water vapor (IWV) for the monitoring of the real-time IWV variations in the atmosphere (Schneider et al, 2010;Rohm et al, 2014;Zhang et al, 2015;Li et al, 2014Li et al, , 2015Guerova et al, 2016) or the studies of climate (Nilsson and Elgered, 2008;Jin and Luo, 2009;Vonder Haar et al, 2012;Ning and Elgered, 2012) due to its 24 h availability, high accuracy, global coverage, high resolution and low cost. The atmospheric parameter directly estimated from GNSS measurements is the GNSS signal's tropospheric zenith total delay (ZTD) which can be effectively divided into the zenith hydrostatic delay (ZHD) and the zenith wet delay (ZWD).…”

Section: Introductionmentioning

confidence: 99%

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

Wang

Zhang

et al. 2017

Atmos. Meas. Tech.

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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.

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Section: Introductionmentioning

confidence: 99%

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

Wang

Zhang

et al. 2017

Atmos. Meas. Tech.

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“…Part of these delays, accumulated by the signal along its propagation path, can be associated to the water vapor. Considering the growing employment of ground-based GNSS receivers for the estimation of integrated precipitable water vapor (IPWV), time series of IPWV become available with high temporal and spatial resolution, taking into account that GNSS can be considered an all-weather system (Bevis et al, 1992(Bevis et al, , 1994Koulali et al, 2012;Rohm et al, 2014). Concerning the impact of the rain on the GNSS signal, Solheim et al (1999) proposed theoretical results on the microwave propagation delays induced by rain and other atmospheric constituents, while Champollion et al (2004) and Brenot et al (2006) analyzed the sensitivity of the total delay in the presence of severe precipitation events.…”

Section: Introductionmentioning

confidence: 99%

The usefulness of the Global Navigation Satellite Systems (GNSS) in the analysis of precipitation events

Bonafoni

Biondi

2016

Atmospheric Research

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“…Ground-based GPS meteorology has been proven to be a very effective method for AWV retrievals with high spatial and temporal resolutions in earlier studies (Bevis et al 1992;Rohm et al 2014;Yeh et al 2014;Yuan et al 2014). However, the oceanic AWV retrievals using a platform (ship or buoy) over sea regions have been confronted with some challenges, such as the dynamic nature of the platforms and the variability in the coordinate parameters for GPS receivers.…”

Section: Introductionmentioning

confidence: 99%

Validation of Atmospheric Water Vapor Derived from Ship-Borne GPS Measurements in the Chinese Bohai Sea

Fan¹,

Zang²,

Peng³

et al. 2016

Terr. Atmos. Ocean. Sci.

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Atmospheric water vapor (AWV) was investigated for the first time in the Chinese Bohai Sea using a Global Positioning System (GPS) receiver aboard a lightweight (300-ton) ship. An experiment was conducted to retrieve the AWV using the state-of-the-art GPS precise point positioning (PPP) technique. The effects of atmospheric weighted mean temperature model and zenith wet delay constraint on GPS AWV estimates were discussed in the PPP estimation system. The GPS-derived precipitable water vapor (PWV) and slant-path water vapor (SWV) were assessed by comparing with those derived from the Fifth Generation NCAR/Penn State Mesoscale Model (MM5). The results showed the PWV and SWV differences between those derived from both GPS and MM5 are 1.5 mm root mean square (RMS) with a bias of 0.2 and 3.9 mm RMS with a bias of -0.7 mm respectively. These good agreements indicate that the GPS-derived AWV in dynamic environments has a comparable accuracy with that of the MM5 model. This suggests that high accuracy and high spatio-temporal resolution humidity fields can be obtained using GPS in the Chinese Bohai Sea, which offers significant potential for meteorological applications and climate studies in this region.

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Ground-based GNSS ZTD/IWV estimation system for numerical weather prediction in challenging weather conditions

Cited by 68 publications

References 24 publications

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

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

The usefulness of the Global Navigation Satellite Systems (GNSS) in the analysis of precipitation events

Validation of Atmospheric Water Vapor Derived from Ship-Borne GPS Measurements in the Chinese Bohai Sea

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