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VMF3/GPT3: refined discrete and empirical troposphere mapping functions

Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves fro...

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Autores principales: Landskron, Daniel, Böhm, Johannes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6566279/
https://www.ncbi.nlm.nih.gov/pubmed/31258259
http://dx.doi.org/10.1007/s00190-017-1066-2
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author Landskron, Daniel
Böhm, Johannes
author_facet Landskron, Daniel
Böhm, Johannes
author_sort Landskron, Daniel
collection PubMed
description Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of [Formula: see text] . Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a [Formula: see text] as well as a [Formula: see text] global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.
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spelling pubmed-65662792019-06-28 VMF3/GPT3: refined discrete and empirical troposphere mapping functions Landskron, Daniel Böhm, Johannes J Geod Original Article Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of [Formula: see text] . Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a [Formula: see text] as well as a [Formula: see text] global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3. Springer Berlin Heidelberg 2017-09-15 2018 /pmc/articles/PMC6566279/ /pubmed/31258259 http://dx.doi.org/10.1007/s00190-017-1066-2 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Landskron, Daniel
Böhm, Johannes
VMF3/GPT3: refined discrete and empirical troposphere mapping functions
title VMF3/GPT3: refined discrete and empirical troposphere mapping functions
title_full VMF3/GPT3: refined discrete and empirical troposphere mapping functions
title_fullStr VMF3/GPT3: refined discrete and empirical troposphere mapping functions
title_full_unstemmed VMF3/GPT3: refined discrete and empirical troposphere mapping functions
title_short VMF3/GPT3: refined discrete and empirical troposphere mapping functions
title_sort vmf3/gpt3: refined discrete and empirical troposphere mapping functions
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6566279/
https://www.ncbi.nlm.nih.gov/pubmed/31258259
http://dx.doi.org/10.1007/s00190-017-1066-2
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