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Ionospheric tomographic common clock model of undifferenced uncombined GNSS measurements / German Olivares-Pulido in Journal of geodesy, vol 95 n° 11 (November 2021)
[article]
Titre : Ionospheric tomographic common clock model of undifferenced uncombined GNSS measurements Type de document : Article/Communication Auteurs : German Olivares-Pulido, Auteur ; Manuel Hernández-Pajares, Auteur ; Haixia Lyu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 122 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] correction ionosphérique
[Termes IGN] horloge du satellite
[Termes IGN] mesurage par GNSS
[Termes IGN] modèle ionosphérique
[Termes IGN] phase
[Termes IGN] positionnement ponctuel précis
[Termes IGN] teneur totale en électrons
[Termes IGN] tomographie par GPS
[Termes IGN] voxel
[Termes IGN] Wide Area Augmentation System
[Vedettes matières IGN] Traitement de données GNSSRésumé : (auteur) In this manuscript, we introduce the Ionospheric Tomographic Common Clock (ITCC) model of undifferenced uncombined GNSS measurements. It is intended for improving the Wide Area precise positioning in a consistent and simple way in the multi-GNSS context, and without the need of external precise real-time products. This is the case, in particular, of the satellite clocks, which are estimated at the Wide Area GNSS network Central Processing Facility (CPF) referred to the reference receiver one; and the precise realtime ionospheric corrections, simultaneously computed under a voxel-based tomographic model with satellite clocks and other geodetic unknowns, from the uncombined and undifferenced pseudoranges and carrier phase measurements at the CPF from the Wide Area GNSS network area. The model, without fixing the carrier phase ambiguities for the time being (just constraining them by the simultaneous solution of both ionospheric and geometric components of the uncombined GNSS model), has been successfully applied and assessed against previous precise positioning techniques. This has been done by emulating real-time conditions for Wide Area GPS users during 2018 in Poland. Numéro de notice : A2021-776 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01568-8 Date de publication en ligne : 13/10/2021 En ligne : https://doi.org/10.1007/s00190-021-01568-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98839
in Journal of geodesy > vol 95 n° 11 (November 2021) . - n° 122[article]A parameterization of the cloud scattering polarization signal derived from GPM observations for microwave fast radative transfer models / Victoria Sol Galligani in IEEE Transactions on geoscience and remote sensing, vol 59 n° 11 (November 2021)
[article]
Titre : A parameterization of the cloud scattering polarization signal derived from GPM observations for microwave fast radative transfer models Type de document : Article/Communication Auteurs : Victoria Sol Galligani, Auteur ; Die Wang, Auteur ; Paola Belen Corales, Auteur ; Catherine Prigent, Auteur Année de publication : 2021 Article en page(s) : pp 8968 - 8977 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] image GPM
[Termes IGN] image radar
[Termes IGN] latitude
[Termes IGN] modèle atmosphérique
[Termes IGN] modèle de transfert radiatif
[Termes IGN] nuage
[Termes IGN] polarisation
[Termes IGN] prévision météorologique
[Termes IGN] radiomètre à hyperfréquence
[Termes IGN] reconstruction du signal
[Termes IGN] variation saisonnièreRésumé : (auteur) Microwave cloud polarized observations have shown the potential to improve precipitation retrievals since they are linked to the orientation and shape of ice habits. Stratiform clouds show larger brightness temperature (TB) polarization differences (PDs), defined as the vertically polarized TB (TBV) minus the horizontally polarized TB (TBH), with ~10 K PD values at 89 GHz due to the presence of horizontally aligned snowflakes, while convective regions show smaller PD signals, as graupel and/or hail in the updraft tend to become randomly oriented. The launch of the global precipitation measurement (GPM) microwave imager (GMI) has extended the availability of microwave polarized observations to higher frequencies (166 GHz) in the tropics and midlatitudes, previously only available up to 89 GHz. This study analyzes one year of GMI observations to explore further the previously reported stable relationship between the PD and the observed TBs at 89 and 166 GHz, respectively. The latitudinal and seasonal variability is analyzed to propose a cloud scattering polarization parameterization of the PD-TB relationship, capable of reconstructing the PD signal from simulated TBs. Given that operational radiative transfer (RT) models do not currently simulate the cloud polarized signals, this is an alternative and simple solution to exploit the large number of cloud polarized observations available. The atmospheric radiative transfer simulator (ARTS) is coupled with the weather research and forecasting (WRF) model, in order to apply the proposed parameterization to the RT simulated TBs and hence infer the corresponding PD values, which show to reproduce the observed GMI PDs well. Numéro de notice : A2021-886 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3049921 Date de publication en ligne : 02/02/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3049921 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98871
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 11 (November 2021) . - pp 8968 - 8977[article]On the TEC bias of altimeter satellites / Francisco Azpilicueta in Journal of geodesy, vol 95 n° 10 (October 2021)
[article]
Titre : On the TEC bias of altimeter satellites Type de document : Article/Communication Auteurs : Francisco Azpilicueta, Auteur ; Bruno Nava, Auteur Année de publication : 2021 Article en page(s) : n° 114 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] altimétrie satellitaire par radar
[Termes IGN] données DORIS
[Termes IGN] données Jason
[Termes IGN] données Topex-Poseidon
[Termes IGN] erreur systématique
[Termes IGN] teneur totale en électrons
[Termes IGN] traitement de données GNSSRésumé : (auteur) TOPEX/Poseidon, Jason-1, Jason-2 and Jason-3 altimeter missions have provided 27 + years of uninterrupted Total Electron Content (TEC) measurements since 1992, with unprecedented precision. Nevertheless, the issue of a possible systematic bias in the data was identified immediately after first TOPEX measurements were compared with measurements from other sources. The bias issue has remained open for decades, and it has increased in complexity because each new mission had its different bias. The purpose of this paper is to assess the problem of TEC bias of altimeters. Two approaches have been followed. The first one relied on the TEC data series of the four altimeters to determine inter-mission systematic biases using the last available data versions for each mission. The second approach consisted of inspecting the missions’ official reports to trace changes of the inter-mission and inter-version biases, including biases relative to DORIS ionospheric measurements. Both approaches have converged and resulted in the determination of a reference frame where missions, instruments and ionospheric reference levels could be compared. This reference frame was also used to analyze results published in representative papers during the last decades, including ionospheric data from the ENVISAT mission. This reference frame could help to assess TEC levels of the announced new data version of Jason-2, Jason-3 and the imminent Jason-CS/Sentinel missions. The main conclusion of this work is that Jason-1, ‘E’ data version, defines a TEC reference level which is compatible with most of the results found in the literature. Numéro de notice : A2021-747 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-021-01564-y Date de publication en ligne : 04/10/2021 En ligne : https://doi.org/10.1007/s00190-021-01564-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98706
in Journal of geodesy > vol 95 n° 10 (October 2021) . - n° 114[article]Predicting total electron content in ionosphere using vector autoregression model during geomagnetic storm / Sumitra Iyer in Journal of applied geodesy, vol 15 n° 4 (October 2021)
[article]
Titre : Predicting total electron content in ionosphere using vector autoregression model during geomagnetic storm Type de document : Article/Communication Auteurs : Sumitra Iyer, Auteur ; Alka Mahajan, Auteur Année de publication : 2021 Article en page(s) : pp 279 - 291 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] auto-régression
[Termes IGN] déformation temporelle dynamique (algorithme)
[Termes IGN] format RINEX
[Termes IGN] Inde
[Termes IGN] modèle de simulation
[Termes IGN] modèle ionosphérique
[Termes IGN] série temporelle
[Termes IGN] signal GPS
[Termes IGN] tempête magnétique
[Termes IGN] teneur totale en électrons
[Termes IGN] teneur verticale totale en électronsRésumé : (auteur) The ionospheric total electron content (TEC) severely impacts the positional accuracy of a single frequency Global Positioning System (GPS) receiver at the equatorial latitudes. The ionosphere causes a frequency-dependent group delay in the GPS-ranging signals, which reduces the receiver’s accuracy. Further, the variations in TEC due to various space weather phenomena make the ionosphere’s behaviour nonhomogeneous and complex. Hence, developing an accurate forecast model that can track the dynamic behaviour of the ionosphere remains a challenge. However, advances in emerging data-driven algorithms have been found helpful in tracking non-stationary behavior in TEC. These models help forecast the delays in advance. The multivariate Vector Autoregression model (VAR) predicts the Ionospheric TEC in the proposed model. The prediction model uses input data compiled in real-time from the lag values of incoming TEC data and features extracted from TEC. The TEC is predicted in real-time and tested for different prediction intervals. The metrics – Mean Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) are used for testing and validating the accuracy of the model statistically. Testing the predicted output accuracy is also done with the dynamic time warping (DTW) algorithm by comparing it with the actual value obtained from the dual-frequency receiver. The model is tested for storm days of the year 2015 for Bangalore and Hyderabad stations and found to be reliable and accurate. A prediction interval of twenty-minute shows the highest accuracy with an error within 10 TECU for all the storm days. Numéro de notice : A2021-745 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2021-0015 Date de publication en ligne : 23/06/2021 En ligne : https://doi.org/10.1515/jag-2021-0015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98717
in Journal of applied geodesy > vol 15 n° 4 (October 2021) . - pp 279 - 291[article]Stochastic super-resolution for downscaling time-evolving atmospheric fields with a generative adversarial network / Jussi Leinonen in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)
[article]
Titre : Stochastic super-resolution for downscaling time-evolving atmospheric fields with a generative adversarial network Type de document : Article/Communication Auteurs : Jussi Leinonen, Auteur ; Daniele Nerini, Auteur ; Alexis Berne, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7211 - 7223 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] données météorologiques
[Termes IGN] épaisseur de nuage
[Termes IGN] image à basse résolution
[Termes IGN] image GOES
[Termes IGN] modèle atmosphérique
[Termes IGN] précipitation
[Termes IGN] processus stochastique
[Termes IGN] réduction d'échelle
[Termes IGN] réseau antagoniste génératif
[Termes IGN] réseau neuronal convolutif
[Termes IGN] SuisseRésumé : (auteur) Generative adversarial networks (GANs) have been recently adopted for super-resolution, an application closely related to what is referred to as “downscaling” in the atmospheric sciences: improving the spatial resolution of low-resolution images. The ability of conditional GANs to generate an ensemble of solutions for a given input lends itself naturally to stochastic downscaling, but the stochastic nature of GANs is not usually considered in super-resolution applications. Here, we introduce a recurrent, stochastic super-resolution GAN that can generate ensembles of time-evolving high-resolution atmospheric fields for an input consisting of a low-resolution sequence of images of the same field. We test the GAN using two data sets: one consisting of radar-measured precipitation from Switzerland; the other of cloud optical thickness derived from the Geostationary Earth Observing Satellite 16 (GOES-16). We find that the GAN can generate realistic, temporally consistent super-resolution sequences for both data sets. The statistical properties of the generated ensemble are analyzed using rank statistics, a method adapted from ensemble weather forecasting; these analyses indicate that the GAN produces close to the correct amount of variability in its outputs. As the GAN generator is fully convolutional, it can be applied after training to input images larger than the images used to train it. It is also able to generate time series much longer than the training sequences, as demonstrated by applying the generator to a three-month data set of the precipitation radar data. The source code to our GAN is available at https://github.com/jleinonen/downscaling-rnn-gan. Numéro de notice : A2021-645 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3032790 Date de publication en ligne : 02/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3032790 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98349
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7211 - 7223[article]Estimation of code observation-specific biases (OSBs) for the modernized multi-frequency and multi-GNSS signals: an undifferenced and uncombined approach / Teng Liu in Journal of geodesy, vol 95 n° 8 (August 2021)PermalinkAtmospheric correction to passive microwave brightness temperature in snow cover mapping over china / Yubao Qiu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkOrdered subsets-constrained ART algorithm for ionospheric tomography by combining VTEC data / Dunyong Zheng in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkGPS satellite differential code bias estimation with current eleven low earth orbit satellites / Xingxing Li in Journal of geodesy, vol 95 n° 7 (July 2021)PermalinkThree-dimensional reconstruction of seismo-traveling ionospheric disturbances after March 11, 2011, Japan Tohoku earthquake / Changzhi Zhai in Journal of geodesy, vol 95 n° 7 (July 2021)PermalinkComparison of polar ionospheric behavior at Arctic and Antarctic regions for improved satellite-based positioning / Arun Kumar Singh in Journal of applied geodesy, vol 15 n° 3 (July 2021)PermalinkIonospheric irregularity layer height and thickness estimation with a GNSS receiver array / Seebany Datta-Barua in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)PermalinkAdaptive regularization method for 3-D GNSS ionospheric tomography based on the U-curve / Jun Tang in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)PermalinkGNSS-based statistical analysis of ionospheric anomalies during typhoon landings in Taiwan/Japan / Hai Peng in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)PermalinkMulti-GNSS PPP/INS tightly coupled integration with atmospheric augmentation and its application in urban vehicle navigation / Shengfeng Gu in Journal of geodesy, vol 95 n° 6 (June 2021)PermalinkAn improved computerized ionospheric tomography model fusing 3-D multisource ionospheric data enabled quantifying the evolution of magnetic storm / Jian Kong in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)PermalinkObservable quality assessment of broadband very long baseline interferometry system / Ming H. Xu in Journal of geodesy, vol 95 n° 5 (May 2021)PermalinkCloud detection from paired CrIS water vapor and CO₂ channels using machine learning techniques / Miao Tian in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkApplication of a multi-layer artificial neural network in a 3-D global electron density model using the long-term observations of COSMIC, Fengyun-3C, and Digisonde / Li Wang in Space weather, vol 19 n° 3 (March 2021)PermalinkIntegrity investigation of global ionospheric TEC maps for high-precision positioning / Jiaojiao Zhao in Journal of geodesy, vol 95 n° 3 (March 2021)PermalinkModélisation des délais ionosphériques appliquée au traitement PPP-RTK centimétrique avec ambiguïtés entières de phase / Camille Parra in XYZ, n° 166 (mars 2021)PermalinkON GLONASS pseudo-range inter-frequency bias solution with ionospheric delay modeling and the undifferenced uncombined PPP / Zheng Zhang in Journal of geodesy, vol 95 n° 3 (March 2021)PermalinkG-band radar for humidity and cloud remote sensing / Ken B. Cooper in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)PermalinkReceiver DCB analysis and calibration in geomagnetic storm-time using IGS products / Jianfeng Li in Survey review, Vol 53 n° 377 (February 2021)PermalinkCopula-based modeling of dependence structure in geodesy and GNSS applications: case study for zenith tropospheric delay in complex terrain / Roya Mousavian in GPS solutions, vol 25 n° 1 (January 2021)Permalink