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Abstract
Global mean sea level has been rising about 3 mm/yr since 1993 due to global warming. Today, Greenland is the largest mass contributor to global mean sea level rise and has been so since the early 2000s. In order to study the movement of the bedrock in response to ice mass loss a network of permanent GNSS stations was developed along the coast of Greenland in 2007-2009. The network (GNET) gives valuable insights into the dynamics and mass loss of nearby glaciers as the uplift decreases rapidly with the distance to the station.
During the last decade or so a method called GNSS interferometric reflectometry (GNSSIR) has been developed using GNSS data to study the surrounding environment. It utilizes the interference between the direct signals and the signals reaching the antenna after being reflected off a surface. In the first study of this thesis we test the use of GNSS-IR for studies of inter annual sea level variations in Thule, Greenland, using the existing THU2 GNSS station from 2008 - 2019. We find that the two methods show much of the same sea level variations but also that there are differences significantly larger than the estimated errors. We suggest that the difference are likely a result of a combination of factors; sea ice will affect the two measurements differently and induce an error which is not accounted for, the tide gauge is not datum controlled and the tide gauge was moved to a new location in 2015.
For the second study we use a GNSS station which was installed at the PROMICE automatic weather station, NUK-K, in March-August 2020. The aim of the installation was to test if the setup could be used for high precision positioning with the goal of tracking glacier flow. We use the GNSS data from the station to extract snow heights using GNSSIR and compare the results to a sonic ranger mounted on the weather station. Though the data is limited, we find a good correspondence between the GNSS-IR results and the sonic ranger. We suggest that the deviations during some of the melt period is due to the much larger footprint of GNSS-IR and an uneven snow and melt distribution.
In the third paper we study the draining cycles of the ice dammed Lake Tininnilik. We use a combined set of observations of lake water level since 1940. The lake has been known to drain periodically about every 10 years at approximately the same water level up until 2003. At this point it starts to drain at continuously lower water levels and at shorter time intervals. The decreasing water level at drainage coincides with a thinning of the damming glacier. Measurements from a nearby GNSS station show an uplift in 2020 of about half of the uplift during the 2010 event, confirming the reduction in drained water volume. Using the trend in maximum lake level and an infill rate based on the last three cycles we suggest that the lake will drain again in 2024. If no continuous spillways are formed and the trend in maximum water level continues, we estimate that the quasi periodic drainage events will cease in 2053 where the water level at drainage reaches the level of the drained lake.
During the last decade or so a method called GNSS interferometric reflectometry (GNSSIR) has been developed using GNSS data to study the surrounding environment. It utilizes the interference between the direct signals and the signals reaching the antenna after being reflected off a surface. In the first study of this thesis we test the use of GNSS-IR for studies of inter annual sea level variations in Thule, Greenland, using the existing THU2 GNSS station from 2008 - 2019. We find that the two methods show much of the same sea level variations but also that there are differences significantly larger than the estimated errors. We suggest that the difference are likely a result of a combination of factors; sea ice will affect the two measurements differently and induce an error which is not accounted for, the tide gauge is not datum controlled and the tide gauge was moved to a new location in 2015.
For the second study we use a GNSS station which was installed at the PROMICE automatic weather station, NUK-K, in March-August 2020. The aim of the installation was to test if the setup could be used for high precision positioning with the goal of tracking glacier flow. We use the GNSS data from the station to extract snow heights using GNSSIR and compare the results to a sonic ranger mounted on the weather station. Though the data is limited, we find a good correspondence between the GNSS-IR results and the sonic ranger. We suggest that the deviations during some of the melt period is due to the much larger footprint of GNSS-IR and an uneven snow and melt distribution.
In the third paper we study the draining cycles of the ice dammed Lake Tininnilik. We use a combined set of observations of lake water level since 1940. The lake has been known to drain periodically about every 10 years at approximately the same water level up until 2003. At this point it starts to drain at continuously lower water levels and at shorter time intervals. The decreasing water level at drainage coincides with a thinning of the damming glacier. Measurements from a nearby GNSS station show an uplift in 2020 of about half of the uplift during the 2010 event, confirming the reduction in drained water volume. Using the trend in maximum lake level and an infill rate based on the last three cycles we suggest that the lake will drain again in 2024. If no continuous spillways are formed and the trend in maximum water level continues, we estimate that the quasi periodic drainage events will cease in 2053 where the water level at drainage reaches the level of the drained lake.
Original language | English |
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Place of Publication | Kgs. Lyngby |
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Publisher | Technical University of Denmark |
Number of pages | 95 |
Publication status | Published - 2022 |
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Dive into the research topics of 'Geodetic measurements of present-day climate changes in Greenland'. Together they form a unique fingerprint.Projects
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Geodetic measurements of present-day climate changes in Greenland
Dahl-Jensen, T. S. (PhD Student), Kierulf, H. P. (Examiner), Voss, P. H. (Examiner), Khan, S. A. (Main Supervisor), Andersen, O. B. (Supervisor) & Knudsen, P. (Supervisor)
01/01/2018 → 16/01/2023
Project: PhD