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Parameterisation of the GNSS troposphere tomography domain with optimisation of the nodes’ distribution / Estera Trzcina in Journal of geodesy, vol 97 n° 1 (January 2023)  

Public [article]  inJournal of geodesy > vol 97 n° 1 (January 2023) . - n° 2 Titre : Parameterisation of the GNSS troposphere tomography domain with optimisation of the nodes’ distribution Type de document : Article/Communication Auteurs : Estera Trzcina, Auteur ; Witold Rohm, Auteur ; Kamil Smolak, Auteur Année de publication : 2023 Article en page(s) : n° 2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] données GNSS [Termes IGN] interpolation bilinéaire [Termes IGN] modèle météorologique [Termes IGN] optimisation (mathématiques) [Termes IGN] radiosondage [Termes IGN] récepteur GNSS [Termes IGN] retard troposphérique [Termes IGN] retard troposphérique zénithal [Termes IGN] système de grille globale discrète [Termes IGN] teneur en vapeur d'eau [Termes IGN] tomographie [Termes IGN] troposphère Résumé : (auteur) Water vapour is a highly variable constituent of the troposphere; thus, its high-resolution measurements are of great importance to weather prediction systems. The Global Navigation Satellite Systems (GNSS) are operationally used in the estimation of the tropospheric state and assimilation of the results into the weather models. One of the GNSS techniques of troposphere sensing is tomography which provides 3-D fields of wet refractivity. The tomographic results have been successfully assimilated into the numerical weather models, showing the great potential of this technique. The GNSS tomography can be based on two different approaches to the parameterisation of the model’s domain, i.e. block (voxel-based) or grid (node-based) approach. Regardless of the parameterisation approach, the tomographic domain should be discretised, which is usually performed in a regular manner, with a grid resolution depending on the mean distance between the GNSS receivers. In this work, we propose a new parameterisation approach based on the optimisation of the tomographic nodes’ location, taking into account the non-uniform distribution of the GNSS information in the troposphere. The experiment was performed using a dense network of 16 low-cost multi-GNSS receivers located in Wrocław and its suburbs, with a mean distance of 3 km. Cross-validation of four different parameterisation approaches is presented. The validation is performed based on the Weather Research and Forecasting model as well as radiosonde observations. The new approach improves the results of wet refractivity estimation by 0.5–2 ppm in terms of RMSE, especially for altitudes of 0.5–2.0 km. Numéro de notice : A2023-044 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1007/s00190-022-01691-0 Date de publication en ligne : 30/12/2022 En ligne : https://doi.org/10.1007/s00190-022-01691-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102343 [article]

Assessing ZWD models in delay and height domains using data from stations in different climate regions / Thainara Munhoz Alexandre de Lima in Applied geomatics, vol 14 n° 1 (March 2022)  

Public [article]  inApplied geomatics > vol 14 n° 1 (March 2022) . - pp 93 - 103 Titre : Assessing ZWD models in delay and height domains using data from stations in different climate regions Type de document : Article/Communication Auteurs : Thainara Munhoz Alexandre de Lima, Auteur ; Marcelo Santos, Auteur ; Daniele Barroca Marra Alves, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 93 - 103 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] climat [Termes IGN] correction du signal [Termes IGN] données GNSS [Termes IGN] modèle atmosphérique [Termes IGN] modèle empirique [Termes IGN] modèle météorologique [Termes IGN] positionnement ponctuel précis [Termes IGN] prévision météorologique [Termes IGN] radiosondage [Termes IGN] retard troposphérique zénithal Résumé : (auteur) Global Navigation Satellite System (GNSS) has revolutionized activities involving geodetic positioning. To achieve a desired accuracy, it is essential to model the atmosphere in an appropriate way. With respect to the neutral atmosphere, the signal sent by the satellite suffers a delay when crossing this layer during its travel to the receiver on the surface, the so-called neutral atmospheric delay. Although empirical models exist, they may not be suitable to represent microclimatic variations in different regions of the globe due to peculiarities that exist in diverse areas. To minimize this limitation, correction models based on numerical weather prediction (NWP) emerge. They allow the assessment of the delay from local atmospheric parameters and the evaluation of atmospheric particularities of each region. In addition, another way to obtain neutral atmosphere delay is by making use of data from radiosondes, which measure atmospheric data at various altitude levels. The main objective of this article is to investigate the performance of different models using GNSS data collected in countries with different climatic conditions. Assessment is performed on the positioning domain using the precise point positioning (PPP) technique. The results show that the proximity between the NWP-based models and radiosondes was approximately 3 cm, and that between empirical models was 5 cm, with variations that depended on the model and the region. Regarding the impact on the height component, the difference between the accuracy of the empirical and NWP models was approximately 16 cm. Numéro de notice : A2022-219 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s12518-021-00414-y En ligne : https://doi.org/10.1007/s12518-021-00414-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100088 [article]

Conventional and neural network-based water vapor density model for GNSS troposphere tomography / Chen Liu in GPS solutions, vol 26 n° 1 (January 2022)  

Public [article]  inGPS solutions > vol 26 n° 1 (January 2022) . - n° 4 Titre : Conventional and neural network-based water vapor density model for GNSS troposphere tomography Type de document : Article/Communication Auteurs : Chen Liu, Auteur ; Yibin Yao, Auteur ; Chaoqian Xu, Auteur Année de publication : 2022 Article en page(s) : n° 4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] classification par réseau neuronal [Termes IGN] erreur absolue [Termes IGN] étalonnage de modèle [Termes IGN] modèle météorologique [Termes IGN] propagation troposphérique [Termes IGN] tomographie par GPS [Termes IGN] vapeur d'eau [Termes IGN] voxel Résumé : (auteur) Global navigation satellite system (GNSS) water vapor (WV) tomography is a promising technique to reconstruct the three-dimensional (3D) WV field. However, this technique usually suffers from the ill-posed problem caused by the poor geometry of GNSS rays, resulting in underdetermined tomographic equations. Such equations often rely on iterative methods for solving, but conventional iterative approaches require accurate initial WV density. To address this demand, we proposed two models for WV density estimation. One is the conventional model (CO model) that consists of an exponential model and a linear least-squares model, which are used to describe the spatial and temporal variability of the WV density, respectively. The other is a neural network model (NN model) that uses a backpropagation neural network (BPNN) to fit the nonlinear variation of WV density in both spatial and temporal domains. WV density derived from a Hong Kong (HK) radiosonde station (RS) during 2020 was used to validate the proposed models. Validation results show that both models well describe the spatial and temporal distribution of the WV density. The NN model exhibits better prediction performance than the CO model in terms of root mean square error (RMSE) and bias. We also applied the proposed models to GNSS WV tomography to test their performance in extreme weather conditions. Test results show that the proposed model-based GNSS tomography can correct the content of WV density but cannot accurately sense its irregular distribution. Numéro de notice : A2022-005 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-021-01188-x Date de publication en ligne : 23/10/2021 En ligne : https://doi.org/10.1007/s10291-021-01188-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98920 [article]

Hourly rainfall forecast model using supervised learning algorithm / Qingzhi Zhao in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 60 n° 1 (January 2022) . - n° 4100509 Titre : Hourly rainfall forecast model using supervised learning algorithm Type de document : Article/Communication Auteurs : Qingzhi Zhao, Auteur ; Yang Liu, Auteur ; Wanqiang Yao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4100509 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] autocorrélation [Termes IGN] classification dirigée [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] données GNSS [Termes IGN] heure [Termes IGN] modèle de simulation [Termes IGN] modèle météorologique [Termes IGN] précipitation [Termes IGN] série temporelle [Termes IGN] station GNSS [Termes IGN] Taïwan [Termes IGN] vapeur d'eau Résumé : (auteur) Previous studies on short-term rainfall forecast using precipitable water vapor (PWV) and meteorological parameters mainly focus on rain occurrence, while the rainfall forecast is rarely investigated. Therefore, an hourly rainfall forecast (HRF) model based on a supervised learning algorithm is proposed in this study to predict rainfall with high accuracy and time resolution. Hourly PWV derived from Global Navigation Satellite System (GNSS) and temperature data are used as input parameters of the HRF model, and a support vector machine is introduced to train the proposed model. In addition, this model also considers the time autocorrelation of rainfall in the previous epoch. Hourly PWV data of 21 GNSS stations and collocated meteorological parameters (temperature and rainfall) for five years in Taiwan Province are selected to validate the proposed model. Internal and external validation experiments have been performed under the cases of slight, moderate, and heavy rainfall. Average root-mean-square error (RMSE) and relative RMSE of the proposed HRF model are 1.36/1.39 mm/h and 1.00/0.67, respectively. In addition, the proposed HRF model is compared with the similar works in previous studies. Compared results reveal the satisfactory performance and superiority of the proposed HRF model in terms of time resolution and forecast accuracy. Numéro de notice : A2022-024 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3054582 Date de publication en ligne : 09/02/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3054582 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99253 [article]

Seven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs / Ann E. Gibbs in Remote sensing, vol 13 n° 21 (November-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 21 (November-1 2021) . - n° 4420 Titre : Seven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs Type de document : Article/Communication Auteurs : Ann E. Gibbs, Auteur ; Li H. Erikson, Auteur ; Benjamin M. Jones, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4420 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Alaska (Etats-Unis) [Termes IGN] analyse diachronique [Termes IGN] Beaufort, mer de [Termes IGN] détection de changement [Termes IGN] données météorologiques [Termes IGN] ERA5 [Termes IGN] érosion côtière [Termes IGN] modèle météorologique [Termes IGN] pergélisol [Termes IGN] série temporelle [Termes IGN] température de l'air [Termes IGN] température de surface de la mer [Termes IGN] trait de côte [Termes IGN] vague Résumé : (auteur) Observational data of coastal change over much of the Arctic are limited largely due to its immensity, remoteness, harsh environment, and restricted periods of sunlight and ice-free conditions. Barter Island, Alaska, is one of the few locations where an extensive, observational dataset exists, which enables a detailed assessment of the trends and patterns of coastal change over decadal to annual time scales. Coastal bluff and shoreline positions were delineated from maps, aerial photographs, and satellite imagery acquired between 1947 and 2020, and at a nearly annual rate since 2004. Rates and patterns of shoreline and bluff change varied widely over the observational period. Shorelines showed a consistent trend of southerly erosion and westerly extension of the western termini of Barter Island and Bernard Spit, which has accelerated since at least 2000. The 3.2 km long stretch of ocean-exposed coastal permafrost bluffs retreated on average 114 m and at a maximum of 163 m at an average long-term rate (70 year) of 1.6 ± 0.1 m/yr. The long-term retreat rate was punctuated by individual years with retreat rates up to four times higher (6.6 ± 1.9 m/yr; 2012–2013) and both long-term (multidecadal) and short-term (annual to semiannual) rates showed a steady increase in retreat rates through time, with consistently high rates since 2015. A best-fit polynomial trend indicated acceleration in retreat rates that was independent of the large spatial and temporal variations observed on an annual basis. Rates and patterns of bluff retreat were correlated to incident wave energy and air and water temperatures. Wave energy was found to be the dominant driver of bluff retreat, followed by sea surface temperatures and warming air temperatures that are considered proxies for evaluating thermo-erosion and denudation. Normalized anomalies of cumulative wave energy, duration of open water, and air and sea temperature showed at least three distinct phases since 1979: a negative phase prior to 1987, a mixed phase between 1987 and the early to late 2000s, followed by a positive phase extending to 2020. The duration of the open-water season has tripled since 1979, increasing from approximately 40 to 140 days. Acceleration in retreat rates at Barter Island may be related to increases in both thermodenudation, associated with increasing air temperature, and the number of niche-forming and block-collapsing episodes associated with higher air and water temperature, more frequent storms, and longer ice-free conditions in the Beaufort Sea. Numéro de notice : A2021-822 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13214420 Date de publication en ligne : 04/11/2021 En ligne : https://doi.org/10.3390/rs13214420 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98936 [article]

Attribution of the Australian bushfire risk to anthropogenic climate change / Geert Jan Van Oldenborgh in Natural Hazards and Earth System Sciences, vol 21 n° 3 (March 2021)  

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Climate change adaptation in coastal cities / David Major (2021)  

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Remote sensing of snow and its applications / Ali Nadir Arslan (2021)  

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An advanced residual error model for tropospheric delay estimation / Szabolcs Rózsa in GPS solutions, Vol 24 n° 4 (October 2020)  

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A two-stage tropospheric correction model combining data from GNSS and numerical weather model / Jan Douša in GPS solutions, vol 22 n° 3 (July 2018)  

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Spatial–temporal variations of water vapor content over Ethiopia: a study using GPS observations and the ECMWF model / Kibrom Ebuy Abraha in GPS solutions, vol 21 n° 1 (January 2017)  

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Multi-technique comparison of atmospheric parameters at the DORIS co-location sites during CONT14 / Robert Heinkelmann in Advances in space research, vol 58 n° 12 (15 December 2016)  

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Review of the state of the art and future prospects of the ground-based GNSS meteorology in Europe / Guergana Guerova in Atmospheric measurement techniques, vol 9 n° 11 (November 2016)  

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Using a regional numerical weather prediction model for GNSS positioning over Brazil / Daniele Barroca Marra Alves in GPS solutions, vol 20 n° 4 (October 2016)  

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A high-quality reprocessed ground-based GPS dataset for atmospheric process studies, radiosonde and model evaluation, and reanalysis of HyMeX Special Observing Period / Olivier Bock in Quarterly Journal of the Royal Meteorological Society, vol 142 n° S1 (August 2016)  

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