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High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland / Karina Wilgan in Journal of geodesy, vol 93 n°6 (June 2019)

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inJournal of geodesy > vol 93 n°6 (June 2019) . - pp 819 - 835

Titre :	High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland
Type de document :	Article/Communication
Auteurs :	Karina Wilgan, Auteur ; Alain Geiger, Auteur
Année de publication :	2019
Article en page(s) :	pp 819 - 835
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] Alpes [Termes IGN] collocation par moindres carrés [Termes IGN] correction troposphérique [Termes IGN] données GNSS [Termes IGN] données météorologiques [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] modèle mathématique [Termes IGN] précision de l'estimation [Termes IGN] prévision météorologique [Termes IGN] réfraction [Termes IGN] retard troposphérique [Termes IGN] retard troposphérique zénithal [Termes IGN] Suisse
Résumé :	(auteur) The tropospheric delay of a microwave signal affects all space geodetic techniques. One possibility of modeling the delay is by introducing tropospheric models from external data sources. In this study, we present high-resolution models of tropospheric total refractivity and zenith total delay (ZTD) for the alpine area in Switzerland. The troposphere models are based on different combinations of data sources, including numerical weather prediction (NWP) model COSMO-1 with high spatial resolution of 1.1 km × 1.1 km, GNSS data from permanent geodetic stations and GPS L1-only data from low-cost permanent stations. The tropospheric parameters are interpolated to the arbitrary locations by the least-squares collocation method using the in-house developed software package COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays). The first goal of this study is to validate the obtained models with the reference radiosonde and GNSS data to show the improvement w.r.t. the previous studies that used lower resolution input data. In case of total refractivity, the profiles reconstructed from COSMO-1 model show the best agreement with the reference radiosonde measurements, with an average bias of 1.1 ppm (0.6% of the total refractivity value along a vertical profile) and standard deviation of 2.6 ppm (1.6%) averaged from the whole profile. The radiosondes are assimilated into COSMO-1 model; thus, a high correlation is expected, and this comparison is not independent. In case of ZTD, the GNSS-based model shows the highest agreement with the reference GNSS data, with an average bias of 0.2 mm (0.01%) and standard deviation of 4.3 mm (0.2%). For COSMO-based model, the agreement is also very high, especially compared to our previous studies with lower resolution NWPs. The average bias is equal to − 2.5 mm (0.1%) with standard deviation of 9.2 mm (0.5%). The second goal of this study is to test the feasibility of calculating high-resolution troposphere models over a limited area from coarser data sets. We calculate the ZTD models with spatial resolution of 20 m for a test area in Matter Valley. We include the information from the low-cost GPS stations (X-Sense), to also assess the performance and future usability of such stations. We validate the models based on three data sources w.r.t. the reference GNSS data. For the station located inside the area of the study, the models have an agreement of few mm with the reference data. For stations located further away from the study area, the agreement for X-Sense is smaller, but the standard deviations of residuals are still below 15 mm. We consider also another factor of evaluating the high-resolution models, i.e., spatial variability of the data. For designing a GNSS network, also for the tropospheric estimates, the height variability of the network may be as important as the horizontal distribution. The GNSS-based models are built from the coarsest network; thus, their variability is the lowest. The variability of X-Sense-based stations is the highest; thus, such data may be suitable for building troposphere models for very high-resolution applications.
Numéro de notice :	A2019-350
Affiliation des auteurs :	non IGN
Thématique :	POSITIONNEMENT
Nature :	Article
nature-HAL :	ArtAvecCL-RevueIntern
DOI :	10.1007/s00190-018-1203-6
Date de publication en ligne :	01/10/2018
En ligne :	https://doi.org/10.1007/s00190-018-1203-6
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=93394

$High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland$

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