Abstract

We present the official land uplift model NKG2016LU of the Nordic Commission of Geodesy (NKG) for northern Europe. The model was released in 2016 and covers an area from 49° to 75° latitude and 0° to 50° longitude. It shows a maximum absolute uplift of 10.3 mm/a near the city of Umeå in northern Sweden and a zero-line that follows the shores of Germany and Poland. The model replaces the NKG2005LU model from 2005. Since then, we have collected more data in the core areas of NKG2005LU, specifically in Norway, Sweden, Denmark and Finland, and included observations from the Baltic countries as well. Additionally, we have derived an underlying geophysical glacial isostatic adjustment (GIA) model within NKG as an integrated part of the NKG2016LU project. A major challenge is to estimate a realistic uncertainty grid for the model. We show how the errors in the observations and the underlying GIA model propagate through the calculations to the final uplift model. We find a standard error better than 0.25 mm/a for most of the area covered by precise levelling or uplift rates from Continuously Operating Reference Stations and up to 0.7 mm/a outside this area. As a check, we show that two different methods give approximately the same uncertainty estimates. We also estimate changes in the geoid and derive an alternative uplift model referring to this rising geoid. Using this latter model, the maximum uplift in Umeå reduces from 10.3 to 9.6 mm/a and with a similar reduction ratio elsewhere. When we compare this new NKG2016LU with the former NKG2005LU, we find the largest differences where the GIA model has the strongest influence, i.e. outside the area of geodetic observation. Here, the new model gives from − 3 to 4 mm/a larger values. Within the observation area, similar differences reach − 1.5 mm/a at the northernmost part of Norway and − 1.0 mm/a at the north-western coast of Denmark, but generally within the range of − 0.5 to 0.5 mm/a.

Highlights

  • The ongoing Fennoscandian postglacial rebound due to the last glaciation has been investigated in many ways and from different perspectives (e.g. Ekman 1996, 2009; Vestøl 2006; Steffen and Wu 2011)

  • Whenever we transform data referring to such global reference frames into national Earth-fixed reference frames, for instance European Terrestrial Reference System 1989 (ETRS 89) realizations, we must account for land uplift

  • NKG2016LU_abs are presented in Fig. 11 and Table 2, second row. The latter values are considerably larger than the residuals, which is because of the filtering effect in Least Square Collocation (LSC) and the fact that the empirical model is computed from both Global Navigation Satellite System (GNSS) and levelling observations and that the levelling sometimes has sufficient weight to overrule the GNSS observations

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Summary

Introduction

The ongoing Fennoscandian postglacial rebound due to the last glaciation has been investigated in many ways and from different perspectives (e.g. Ekman 1996, 2009; Vestøl 2006; Steffen and Wu 2011). The first uses geodetic observations (such as tide gauges, precise spirit levelling and/or GNSS) to calculate a model by some estimation method, such as Least Square Collocation (LSC) This method was successfully applied by, for instance, Danielsen (2001) and Vestøl (2006) and gives a strictly empirical model. The second method computes the model in a geophysical meaningful way based on the combination of an Earth model and geologically constrained ice thickness history, selected so that the model best fits selected land uplift observations such as GNSS-derived velocities and/or geological relative sealevel (RSL) changes. Our semi-empirical model gives the uplift expressed in a global reference frame, in this case the International Terrestrial Reference Frame 2008 (ITRF2008), since the uplift rates from the CORS are calculated and expressed in this frame We call this “absolute land uplift”, and the corresponding absolute model is NKG2016LU_abs.

The calculation of NKG2016LU
The empirical model
The GIA model
The combined model
Uncertainty estimation
Preliminary uncertainties for the empirical and semi‐empirical models
Uncertainty of the GIA model
Improved uncertainty estimates for the semi‐empirical model
Heterogeneous least square collocation in one step
Discussion and conclusions
The role of the tide gauges
Reference frame
One‐ or two‐step approach
Future developments
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