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A new approach for the development of grid models calculating tropospheric key parameters over China / Ge Zhu in Remote sensing, vol 13 n° 17 (September-1 2021)
[article]
Titre : A new approach for the development of grid models calculating tropospheric key parameters over China Type de document : Article/Communication Auteurs : Ge Zhu, Auteur ; Liangke Huang, Auteur ; Lilong Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 3546 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] Chine
[Termes IGN] données maillées
[Termes IGN] données météorologiques
[Termes IGN] MERRA
[Termes IGN] positionnement par GNSS
[Termes IGN] propagation troposphérique
[Termes IGN] retard troposphérique
[Termes IGN] série temporelle
[Termes IGN] teneur en vapeur d'eauRésumé : (auteur) Pressure, water vapor pressure, temperature, and weighted mean temperature (Tm) are tropospheric parameters that play an important role in high-precision global navigation satellite system navigation (GNSS). As accurate tropospheric parameters are obligatory in GNSS navigation and GNSS water vapor detection, high-precision modeling of tropospheric parameters has gained widespread attention in recent years. A new approach is introduced to develop an empirical tropospheric delay model named the China Tropospheric (CTrop) model, providing meteorological parameters based on the sliding window algorithm. The radiosonde data in 2017 are treated as reference values to validate the performance of the CTrop model, which is compared to the canonical Global Pressure and Temperature 3 (GPT3) model. The accuracy of the CTrop model in regards to pressure, water vapor pressure, temperature, and weighted mean temperature are 5.51 hPa, 2.60 hPa, 3.09 K, and 3.35 K, respectively, achieving an improvement of 6%, 9%, 10%, and 13%, respectively, when compared to the GPT3 model. Moreover, three different resolutions of the CTrop model based on the sliding window algorithm are also developed to reduce the amount of gridded data provided to the users, as well as to speed up the troposphere delay computation process, for which users can access model parameters of different resolutions for their requirements. With better accuracy of estimating the tropospheric parameters than that of the GPT3 model, the CTrop model is recommended to improve the performance of GNSS positioning and navigation. Numéro de notice : A2021-688 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.3390/rs13173546 Date de publication en ligne : 06/09/2021 En ligne : https://doi.org/10.3390/rs13173546 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98423
in Remote sensing > vol 13 n° 17 (September-1 2021) . - n° 3546[article]Comparative analysis of different atmospheric surface pressure models and their impacts on daily ITRF2014 GNSS residual time series / Zhao Li in Journal of geodesy, vol 94 n°4 (April 2020)
[article]
Titre : Comparative analysis of different atmospheric surface pressure models and their impacts on daily ITRF2014 GNSS residual time series Type de document : Article/Communication Auteurs : Zhao Li, Auteur ; Chen Wu, Auteur ; Tonie M. van Dam, Auteur ; Paul Rebischung , Auteur ; Zuheir Altamimi , Auteur Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : n° 42 Note générale : bibliographie
This research is supported by the National Key Research and Development Program of China (Project 2016YFB0502101), the European Commission/Research Grants Council (RGC) Collaboration Scheme sponsored by the Research Grants Council of Hong Kong Special Administrative Region, China (Project No. E-PolyU 501/16), and the National Science Foundation for Distinguished Young Scholars of China (Grant No. 41525014).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] analyse comparative
[Termes IGN] coefficient de corrélation
[Termes IGN] données GNSS
[Termes IGN] International Terrestrial Reference Frame
[Termes IGN] MERRA
[Termes IGN] modèle atmosphérique
[Termes IGN] pression atmosphérique
[Termes IGN] radar JPL
[Termes IGN] résidu
[Termes IGN] série temporelle
[Termes IGN] station GNSSRésumé : (auteur) To remove atmospheric pressure loading (ATML) effect from GNSS coordinate time series, surface pressure (SP) models are required to predict the displacements. In this paper, we modeled the 3D ATML surface displacements using the latest MERRA-2 SP grids, together with four other products (NCEP-R-1, NCEP-R-2, ERA-Interim and MERRA) for 596 globally distributed GNSS stations, and compared them with ITRF2014 residual time series. The five sets of ATML displacements are highly consistent with each other, particularly for those stations far away from coasts, of which the lowest correlations in the Up component for all the four models w.r.t MERRA-2 become larger than 0.91. ERA-Interim-derived ATML displacement performs best in reducing scatter of the GNSS height for 90.3% of the stations (89.3% for NCEP-R-1, 89.1% for NCEP-R-2, 86.4% for MERRA and 85.1% for MERRA-2). We think that this may be possibly due to the 4D variational data assimilation method applied. Considering inland stations only, more than 96% exhibit WRMS reduction in the Up direction for all five models, with an average improvement of 3–4% compared with the original ITRF2014 residual time series before ATML correction. Most stations (> 67%) also exhibit horizontal WRMS reductions based on the five models, but of small magnitudes, with most improvements (> 76%) less than 5%. In particular, most stations in South America, South Africa, Oceania and the Southern Oceans show larger WRMS reductions with MERRA-2, while all other four SP datasets lead to larger WRMS reduction for the Up component than MERRA-2 in Europe. Through comparison of the daily pressure variation from the five SP models, we conclude that the bigger model differences in the SP-induced surface displacements and their impacts on the ITRF2014 residuals for coastal/island stations are mainly due to the IB correction based on the different land–sea masks. A unique high spatial resolution land–sea mask should be applied in the future, so that model differences would come from only SP grids. Further research is also required to compare the ATML effect in ice-covered and high mountainous regions, for example the Qinghai–Tibet Plateau in China, the Andes in South America, etc., where larger pressure differences between models tend to occur. Numéro de notice : A2020-159 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01370-y Date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.1007/s00190-020-01370-y Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94813
in Journal of geodesy > vol 94 n°4 (April 2020) . - n° 42[article]