New 3D velocity model of Estonia from GNSS measurements

Kall, Tarmo; Kruusla, Kätlin; Liibusk, Aive; Oja, Tõnis

doi:10.3176/earth.2021.08

Cited by 5 publications

(3 citation statements)

References 30 publications

(38 reference statements)

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“…The post-glacial land uplift has been studied in Estonia for over 50 years using various data, such as repeated leveling data [58,74,75], sea-level observations [76,77], and global navigation satellite system (GNSS) data, obtained from either continuously operating GNSS stations (CORS) or campaign data [78,79]. There are no significant differences between these studies.…”

Section: Land Uplift Modelsmentioning

confidence: 99%

Sea Level Rise and Future Projections in the Baltic Sea

Kapsi,

Kall,

Liibusk

2023

JMSE

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This article aimed to provide an overview of relative and absolute sea level rise in the Baltic Sea based on different studies, where researchers have used data from tide gauges, satellite altimetry, sea level rise, and land uplift models. These results provide an opportunity to get an overview of the sea level rise in the Baltic Sea. However, to better understand the impact of sea level rise on the coastal area of the Baltic Sea, and especially in Estonia, two post-glacial land uplift models, the latest land uplift model NKG2016LU of the Nordic Commission of Geodesy (NKG) and Estonian land uplift model EST2020VEL, were used. These models enabled to eliminate post-glacial land uplift from absolute sea level rise. To determine the relative sea level rise in the coastal area of the Baltic Sea, the rates from land uplift models were compared to ESA’s BalticSEAL absolute sea level rise model. It was found that the relative sea level rise between 1995–2019 was −5 to 4.5 mm/yr (based on NKG2016LU) in the Baltic Sea. In addition, the southern area is more affected by relative sea level rise than the northern part. During the research, it was also found that the IPCC AR5 sea level projections predict a maximum relative sea level rise in the Baltic Sea by the year 2100 of between 0.3 to 0.7 m. As coastal areas in the southern part of the Baltic Sea are predominantly flat, the sea level may reach the real estate properties by the end of the 21st century. In the coastal area of Estonia, the relative sea level rise in the period 1995–2019 was −1.1 to 3.1 mm/yr (based on NKG2016LU) and −0.3 to 3.4 mm/yr (based on EST2020VEL), the difference between the land uplift models is −0.9 to 0.1 mm/y. In Estonia, the west and southwest area are most threatened by sea level rise, where the coast is quite flat. One of the largest cities in Estonia, Pärnu, is also located there. Using the ESA’s sea level and EST2020VEL land uplift models, it was found that the relative sea level rise will be 0.28 m by the year 2100. Based on the large spatial resolution IPCC AR5 sea level projections, the relative sea level rise will be on the same scale: 0.2–0.4 m.

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Section: Land Uplift Modelsmentioning

confidence: 99%

Sea Level Rise and Future Projections in the Baltic Sea

Kapsi,

Kall,

Liibusk

2023

JMSE

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“…As was mentioned in the introduction, the GNSS stations are often used to estimate GNSS velocities, for example, to remove VLM from the relative TG-based sea level time series. The GNSS-CORS that belong to the national networks have relatedly been included in relevant research to estimate GNSS velocities and compile VLM models [22,[74][75][76]. However, as further discussed in the introduction, the GNSS records/measurements may similarly require consideration for VLM in marine applications since the measurements are forced to the reference epoch t 0 (i.e., the coordinates of CORS are fixed to the defining epoch).…”

Section: Treatment Of Marine Gnss Measurements For Vertical Land Motionmentioning

confidence: 99%

Treatment of Tide Gauge Time Series and Marine GNSS Measurements for Vertical Land Motion with Relevance to the Implementation of the Baltic Sea Chart Datum 2000

et al. 2022

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Tide gauge (TG) time series and GNSS measurements have become standard datasets for various scientific and practical applications. However, the TG and geodetic networks in the Baltic Sea region are deforming due to vertical land motion (VLM), the primary cause of which is the glacial isostatic adjustment. Consequently, a correction for VLM, either obtained from a suitable VLM model or by utilizing space-geodetic techniques, must be applied to ensure compatibility of various data sources. It is common to consider the VLM rate relative to an arbitrary reference epoch, but this also yields that the resulting datasets may not be directly comparable. The common height reference, Baltic Sea Chart Datum 2000 (BSCD2000), has been initiated to facilitate the effective use of GNSS methods for accurate navigation and offshore surveying. The BSCD2000 agrees with the current national height realizations of the Baltic Sea countries. As TGs managed by national authorities are rigorously connected to the national height systems, the TG data can also be used in a common system. Hence, this contribution aims to review the treatment of TG time series for VLM and outline potential error sources for utilizing TG data relative to a common reference. Similar consideration is given for marine GNSS measurements that likewise require VLM correction for some marine applications (such as validating marine geoid models). The described principles are illustrated by analyzing and discussing numerical examples. These include investigations of TG time series and validation of shipborne GNSS determined sea surface heights. The latter employs a high-resolution geoid model and hydrodynamic model-based dynamic topography, which is linked to the height reference using VLM corrected TG data. Validation of the presented VLM corrected marine GNSS measurements yields a 1.7 cm standard deviation and –2.7 cm mean residual. The estimates are 1.9 cm and –10.2 cm, respectively, by neglecting VLM correction. The inclusion of VLM correction thus demonstrates significant improvement toward data consistency. Although the focus is on the Baltic Sea region, the principles described here are also applicable elsewhere.

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“…This study also highlights the use of GPS data in identify a possible counter-clockwise rotational motion of the Indian Plate. Furthermore, Kall et al (2021) determined the new velocity model of Estonia by processing the position time series of 10 CORS stations and 12 GNSS campaign stations. The resulting model, called EST2020VEL, has an accuracy of less than ±0.5mm/year.…”

Section: Introductionmentioning

confidence: 99%

Crustal displacement in Vietnam using CORS data during 2018 - 2021

Dinh¹,

Nguyen

et al. 2023

Earth sci. res. j.

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Continuously Operation Reference Stations (CORS) networks provide surveying, mapping, and positioning services and play a crucial role in determining crustal displacement. This study processed the continuous Global Navigation Satellite System (GNSS) data collected from 55 CORS stations in the TAST’s CORS in Vietnam to determine the crustal displacement in Vietnam from 2018 to 2021. The processing was performed using online Precise Point Positioning (PPP) services and the displacement model to estimate the velocity of the position time series. The result showed that the horizontal velocity field of all CORS stations is uniform in magnitude and direction, ranging from 25.3 to 42.6 mm/year with accuracy from ±0.1 to ±1.0 mm/year in the south-east direction in the International Terrestrial Reference Frame 2014 (ITRF2014). This study confirms the stability and accuracy of GNSS data from the TAST’s CORS network for crustal displacement analysis.

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New 3D velocity model of Estonia from GNSS measurements

Cited by 5 publications

References 30 publications

Sea Level Rise and Future Projections in the Baltic Sea

Sea Level Rise and Future Projections in the Baltic Sea

Treatment of Tide Gauge Time Series and Marine GNSS Measurements for Vertical Land Motion with Relevance to the Implementation of the Baltic Sea Chart Datum 2000

Crustal displacement in Vietnam using CORS data during 2018 - 2021

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