EGU22-4471, updated on 27 Sep 2023
https://doi.org/10.5194/egusphere-egu22-4471
EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Relative tropospheric delay fields by GNSS, InSAR and NWP models in an Alpine Region

Endrit Shehaj1, Othmar Frey2,3, Gregor Moeller1, Matthias Aichinger-Rosenberger1, Alain Geiger1, and Markus Rothacher1
Endrit Shehaj et al.
  • 1Institute of Geodesy and Photogrammetry, ETH Zürich, Zürich, Switzerland, eshehaj@ethz.ch
  • 2Institute of Environmental Engineering, ETH Zürich, Zürich, Switzerland, frey@ifu.baug.ethz.ch
  • 3Gamma Remote Sensing, Gümligen, Switzerland, frey@ifu.baug.ethz.ch

Atmospheric interaction with microwaves causes refraction as well as delays of electromagnetic signals. Although the effects are the same for all microwave signals including GNSS and radar, different spatio-temporal sampling of the tropospheric delays, different frequencies resulting in different phase sensitivity to path delays changes, as well as different processing strategies, assumptions and algorithms may lead to differences in the quantified tropospheric estimates. In case of GNSS, the most typical troposphere-related product is the zenith total delay - quantified after the mapping of all GNSS slant delays in the zenith direction. On the other side, double-difference tropospheric slant delays in persistent scatterer interferometry can be obtained in an iterative manner by isolating and subsequently adding the unwrapped low spatial frequency components of the phase residuals to update the estimate of the tropospheric phase. The updated tropospheric phase is then subtracted before the next iteration of point-wise regression-based estimations of topographic corrections and surface displacements. This iterative process is repeated for all scatterers with acceptable standard deviation of the phase residuals until convergence is reached. For comparison of the different tropospheric delays, the spatio-temporal characteristics of GNSS and InSAR observations must be considered. In this work, we use statistical interpolation methods to collocate the GNSS ZTDs with the InSAR measurements. Moreover, as another external (independent) observation we consider 3D fields of numerical weather models, which are integrated in the slant direction to produce (relative) tropospheric delay maps.

As a case study, an alpine region in the Valais area, Switzerland has been selected, which is an interesting scenario due to the high variability of the refractive index over complex terrain. A relatively dense GNSS network, as well as an interferometric time series of Synthetic Aperture Radar (SAR) images are available for the time span of 2008-2013. After introducing the available observations into the collocation approach, we perform the comparison and evaluation of the different tropospheric delays. In addition, we address the following two questions: How should the correct signal part be considered when modeling tropospheric delays using collocation? What is the effect of the GNSS network in terms of size and resolution? This work is an effort in understanding the different estimated/modeled delays, and it aims to set a baseline and a framework for the fusion of GNSS and InSAR tropospheric delays for the monitoring of the atmospheric state over complex terrain.

How to cite: Shehaj, E., Frey, O., Moeller, G., Aichinger-Rosenberger, M., Geiger, A., and Rothacher, M.: Relative tropospheric delay fields by GNSS, InSAR and NWP models in an Alpine Region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4471, https://doi.org/10.5194/egusphere-egu22-4471, 2022.

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