Measurement report: Can zenith wet delay from GNSS “see” atmospheric turbulence? Insights from case studies across diverse climate zones

Research output: Contribution to journalArticleResearchpeer review

Authors

External Research Organisations

  • State Meteorological Agency (AEMET)
  • GFZ Helmholtz Centre for Geosciences
  • Freie Universität Berlin (FU Berlin)
View graph of relations

Details

Original languageEnglish
Pages (from-to)3567-3581
Number of pages15
JournalAtmospheric chemistry and physics
Volume25
Issue number6
Publication statusPublished - 26 Mar 2025

Abstract

Global navigation satellite system (GNSS) microwave signals are nearly unaffected by clouds but are delayed as they travel the troposphere. The hydrostatic delay accounts for approximately 90 % of the total delay and can be modelled well as a function of temperature, pressure, and humidity. On the other hand, the wet delay is highly variable in space and time, making it difficult to model accurately. A zenith wet delay (ZWD) can be estimated as part of the GNSS positioning adjustment and is proportional to the specific humidity in the atmospheric boundary layer (ABL). While its average term can describe mesoscale events, its small-scale component is associated with turbulent processes in the ABL and is the focus of the present contribution. We introduce a new filtering and estimation strategy to analyse small-scale ZWD variations, addressing questions related to daily or periodic variations in some turbulent parameters and to the dependence of these parameters on climate zones. Five GNSS stations were selected for case studies, revealing promising specific daily and seasonal patterns depending on the estimated turbulence at the GNSS station (buoyancy or shear). This research lays the groundwork for more accurate models and prediction strategies for integrated water vapour, WV (and potentially liquid water clouds), turbulence. It has far-reaching applications, from nowcasting uncertainty assessments to the stochastic modelling for very large baseline interferometry or GNSS.

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

Measurement report: Can zenith wet delay from GNSS “see” atmospheric turbulence? Insights from case studies across diverse climate zones. / Kermarrec, Gaël; Calbet, Xavier; Deng, Zhiguo et al.
In: Atmospheric chemistry and physics, Vol. 25, No. 6, 26.03.2025, p. 3567-3581.

Research output: Contribution to journalArticleResearchpeer review

Download
@article{8807c4f775f04aceaa675acdcd8d01e7,
title = "Measurement report: Can zenith wet delay from GNSS “see” atmospheric turbulence? Insights from case studies across diverse climate zones",
abstract = "Global navigation satellite system (GNSS) microwave signals are nearly unaffected by clouds but are delayed as they travel the troposphere. The hydrostatic delay accounts for approximately 90 % of the total delay and can be modelled well as a function of temperature, pressure, and humidity. On the other hand, the wet delay is highly variable in space and time, making it difficult to model accurately. A zenith wet delay (ZWD) can be estimated as part of the GNSS positioning adjustment and is proportional to the specific humidity in the atmospheric boundary layer (ABL). While its average term can describe mesoscale events, its small-scale component is associated with turbulent processes in the ABL and is the focus of the present contribution. We introduce a new filtering and estimation strategy to analyse small-scale ZWD variations, addressing questions related to daily or periodic variations in some turbulent parameters and to the dependence of these parameters on climate zones. Five GNSS stations were selected for case studies, revealing promising specific daily and seasonal patterns depending on the estimated turbulence at the GNSS station (buoyancy or shear). This research lays the groundwork for more accurate models and prediction strategies for integrated water vapour, WV (and potentially liquid water clouds), turbulence. It has far-reaching applications, from nowcasting uncertainty assessments to the stochastic modelling for very large baseline interferometry or GNSS.",
author = "Ga{\"e}l Kermarrec and Xavier Calbet and Zhiguo Deng and Henken, {Cintia Carbajal}",
note = "Publisher Copyright: {\textcopyright} Author(s) 2025.",
year = "2025",
month = mar,
day = "26",
doi = "10.5194/acp-25-3567-2025",
language = "English",
volume = "25",
pages = "3567--3581",
journal = "Atmospheric chemistry and physics",
issn = "1680-7316",
publisher = "Copernicus Publications",
number = "6",

}

Download

TY - JOUR

T1 - Measurement report

T2 - Can zenith wet delay from GNSS “see” atmospheric turbulence? Insights from case studies across diverse climate zones

AU - Kermarrec, Gaël

AU - Calbet, Xavier

AU - Deng, Zhiguo

AU - Henken, Cintia Carbajal

N1 - Publisher Copyright: © Author(s) 2025.

PY - 2025/3/26

Y1 - 2025/3/26

N2 - Global navigation satellite system (GNSS) microwave signals are nearly unaffected by clouds but are delayed as they travel the troposphere. The hydrostatic delay accounts for approximately 90 % of the total delay and can be modelled well as a function of temperature, pressure, and humidity. On the other hand, the wet delay is highly variable in space and time, making it difficult to model accurately. A zenith wet delay (ZWD) can be estimated as part of the GNSS positioning adjustment and is proportional to the specific humidity in the atmospheric boundary layer (ABL). While its average term can describe mesoscale events, its small-scale component is associated with turbulent processes in the ABL and is the focus of the present contribution. We introduce a new filtering and estimation strategy to analyse small-scale ZWD variations, addressing questions related to daily or periodic variations in some turbulent parameters and to the dependence of these parameters on climate zones. Five GNSS stations were selected for case studies, revealing promising specific daily and seasonal patterns depending on the estimated turbulence at the GNSS station (buoyancy or shear). This research lays the groundwork for more accurate models and prediction strategies for integrated water vapour, WV (and potentially liquid water clouds), turbulence. It has far-reaching applications, from nowcasting uncertainty assessments to the stochastic modelling for very large baseline interferometry or GNSS.

AB - Global navigation satellite system (GNSS) microwave signals are nearly unaffected by clouds but are delayed as they travel the troposphere. The hydrostatic delay accounts for approximately 90 % of the total delay and can be modelled well as a function of temperature, pressure, and humidity. On the other hand, the wet delay is highly variable in space and time, making it difficult to model accurately. A zenith wet delay (ZWD) can be estimated as part of the GNSS positioning adjustment and is proportional to the specific humidity in the atmospheric boundary layer (ABL). While its average term can describe mesoscale events, its small-scale component is associated with turbulent processes in the ABL and is the focus of the present contribution. We introduce a new filtering and estimation strategy to analyse small-scale ZWD variations, addressing questions related to daily or periodic variations in some turbulent parameters and to the dependence of these parameters on climate zones. Five GNSS stations were selected for case studies, revealing promising specific daily and seasonal patterns depending on the estimated turbulence at the GNSS station (buoyancy or shear). This research lays the groundwork for more accurate models and prediction strategies for integrated water vapour, WV (and potentially liquid water clouds), turbulence. It has far-reaching applications, from nowcasting uncertainty assessments to the stochastic modelling for very large baseline interferometry or GNSS.

UR - http://www.scopus.com/inward/record.url?scp=105001273177&partnerID=8YFLogxK

U2 - 10.5194/acp-25-3567-2025

DO - 10.5194/acp-25-3567-2025

M3 - Article

AN - SCOPUS:105001273177

VL - 25

SP - 3567

EP - 3581

JO - Atmospheric chemistry and physics

JF - Atmospheric chemistry and physics

SN - 1680-7316

IS - 6

ER -

By the same author(s)