Development of a method to analyze the error factor of GNSS-A system using SGO-A data
- 1University of Tokyo, Institute of Industrial Science, Center for Integrated Underwater Observation Technology, Tokyo, Japan (yyokota@iis.u-tokyo.ac.jp)
- 2Hydrographic and Oceanographic department, Japan Coast Guard
The GNSS-A seafloor geodetic observation array (SGO-A) has been operated in about 20 years by the Japan Coast Guard [Ishikawa et al., 2020]. It has become possible to measure interplate coupling condition and shallow slow slip events along the Nankai Trough in recent years [Yokota et al., 2016; Yokota and Ishikawa, 2020], and it has become possible to interpret the time change of postseismic deformation following the 2011 Tohoku-oki earthquake [Watanabe et al., 2021]. For understanding the detail physical process of the plate boundary (e.g., SSE), it is necessary to understand the accuracy of the GNSS-A system and study the quantification and attenuation of the error source.
SGO-A data is very useful for this purpose. This dataset is located in the SGO-A site, and basic analysis software GARPOS is also open to the public [Watanabe et al., 2020]. The format is also defined, and a lot of information necessary for error analysis is published.
For example, using the estimation result of SGO-A data by GARPOS, the relationship between the vertical movement and the sound speed structure’s disturbance can be investigated from the residual of the vertical movement and the estimated sound speed structure. In addition, the existence of unexpected errors and their effects can be considered by examining the correlation with the position of the seafloor station.
It is also possible to understand the disturbance in the ocean from the estimated disturbance of the sound speed structure. Recently, the theoretical background for this estimation has been organized and made easier to handle. Considering this result and the comparison of the ocean fields that are likely to occur in reality, it was also found that the observation accuracy is expected to be improved depending on the observation points. In this presentation, we introduce the interpretation method of GNSS-A data that is being developed in recent years.
SGO-A data: https://www1.kaiho.mlit.go.jp/KOHO/chikaku/kaitei/sgs/datalist_e.html
GARPOS: https://doi.org/10.5281/zenodo.4522027
How to cite: Yokota, Y., Ishikawa, T., Watanabe, S., and Nakamura, Y.: Development of a method to analyze the error factor of GNSS-A system using SGO-A data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1564, https://doi.org/10.5194/egusphere-egu22-1564, 2022.
