Demystifying long-term changes observed by GNSS: comparison with GRACE observations and hydrological models


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Mikocki J., Klos A., Güneş Ö., Lenczuk A., Bogusz J.

EGU General Assembly 2023, Vienna, Avusturya, 23 - 28 Nisan 2023, ss.1

  • Yayın Türü: Bildiri / Özet Bildiri
  • Doi Numarası: 10.5194/egusphere-egu23-5537
  • Basıldığı Şehir: Vienna
  • Basıldığı Ülke: Avusturya
  • Sayfa Sayıları: ss.1
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Hydrogeodesy is an applied scientific field that uses precise geodetic observations to measure or infer hydrological quantities and their changes over time. Recently, modern geodesy supplies hydrology with a very powerful tools based on the Earth’s artificial satellites, notably GRACE (Gravity Recovery and Climate Experiment) and GNSS (Global Navigation Satellite System). The long-term changes of periods higher than 1 year present in the time series of GNSS station displacements may be due to real geophysical effects, but may also be coupled to effects resulting from the superposition of GNSS systematic errors as well as numerical artefacts. As a result, it is often difficult to use the aforementioned changes to study, for example, long-term changes in the hydrosphere for specific GNSS station locations. Consequently, it is impossible to exploit the main advantage of GNSS over other measurement techniques, in the sense of dense spatial distribution in some parts of the world. In this study, we use wavelet analysis to determine long-term changes from GNSS station displacement time series and displacement time series determined from GRACE data and data from GRACE-assimilating high-resolution hydrological model GLWS v2.0 (Global Land Water Storage) provided by the University of Bonn. Global GNSS time series set was processed by the International GNSS Service (IGS) in the form of the latest reprocessing repro3.We correct the GNSS displacement time series for non-hydrospheric effects, such as non-tidal atmospheric effect, non-tidal oceanic effect, draconic period, post-glacial rebound and ground thermal expansion effects. We use a range of statistical analyses, such as correlation coefficient analysis and dynamic time warping (DTW) distance to assess the similarity of long-term changes between the three data sets. On this basis, we identify GNSS stations for which long-term changes can be analyzed in terms of changes in the terrestrial hydrosphere and those for which the long-term nature of the series is not due to changes in the hydrosphere, but to other effects.