Abstract

This paper comprehensively analyzes the effect of surface mass loading on GPS height time series in terms of weighted root mean square (WRMS), annual timescale, velocity and noise properties. Considering the complexity of the hydrological process, we adopt the same atmospheric loading and nontidal ocean loading estimated from the TUGO-m barotropic model (ATMMO) and different hydrological loadings estimated from the Global Land Data Assimilation System (GLDAS) and the Global Land Surface Discharge Model (LSDM). The results indicate that the combined ATMMO & GLDAS outperforms the combined ATMMO & LSDM in reducing the WRMS of GPS height times series due to the annual phase asynchrony between GPS height and ATMMO & LSDM. Furthermore, cross-wavelet transform-based (XWT-based) semblance analysis is adopted to quantitatively express the annual phase relationship between GPS height time series and different loading model combinations. The results show that (1) mass loading is the main driving force for the annual fluctuation in GPS height, and (2) the annual term of ATMMO & GLDAS better matches the GPS height time series than ATMMO & LSDM. Consequently, it is concluded that the LSDM may not work well in Eurasia with its current accuracy. Finally, we investigate the impacts of the mass loading correction on site velocity and noise properties. For most sites, the velocity change can reach 0.1 mm/year after the loading correction, indicating that the influence of mass loading should not be ignored in the construction of millimeter-level earth reference frames. However, for some sites, the velocity uncertainty is increased due to undesirable changes in noise properties, suggesting that using the mass loading model to correct GPS height time series is potentially feasible but not sufficient.

Highlights

  • With the enormous advances in GPS technology and in GPS postprocessing software (i.e., GAMIT and GIPSY) over the past three decades, the effects of various factors, such as ionospheric delay and satellite and receiver clock errors, have been greatly reduced or efficiently removed [1,2,3,4]

  • In this paper, we focus on the effects of mass loading deformation on GPS height time series using different hydrological loading models

  • Solutions of 38 GPS stations over Eurasia are used to quantify the performance of ATMMO & Global Land Data Assimilation System (GLDAS) and ATMMO & Land Surface Discharge Model (LSDM)

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Summary

INTRODUCTION

With the enormous advances in GPS technology (i.e., optimized processing strategies and error correction models) and in GPS postprocessing software (i.e., GAMIT and GIPSY) over the past three decades, the effects of various factors, such as ionospheric delay and satellite and receiver clock errors, have been greatly reduced or efficiently removed [1,2,3,4] Apart from these random and systematic errors, the GPS signal shows seasonal variations that are mainly driven by surface mass redistribution [5,6,7]. We revisit the idea of comparing mass loading models, especially the hydrological model, and discuss their correction effects on GPS station time series. We further investigate the effects of mass loading correction on GPS station velocity and noise properties

DATA AND METHODS
RESULTS AND ANALYSIS
CONCLUSION
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