100 research outputs found
Elastic uplift in southeast Greenland due to rapid ice mass loss
This is the publisher's version, also available electronically from "http://onlinelibrary.wiley.com".[1] The rapid unloading of ice from the southeastern sector of the Greenland ice sheet between 2001 and 2006 caused an elastic uplift of ∼35 mm at a GPS site in Kulusuk. Most of the uplift results from ice dynamic-induced volume losses on two nearby outlet glaciers. Volume loss from Helheim Glacier, calculated from sequential digital elevation models, contributes about ∼16 mm of the observed uplift, with an additional ∼5 mm from volume loss of Kangerdlugssuaq Glacier. The remaining uplift signal is attributed to significant melt-induced ice volume loss from the ice sheet margin along the southeast coast between 62°N and 66°N
A new global GPS dataset for testing and improving modelled GIA uplift rates
We have produced a global dataset of ~4000 GPS vertical velocities that can be used as observational estimates of glacial isostatic adjustment (GIA) uplift rates. GIA is the response of the solid Earth to past ice loading, primarily, since the Last Glacial Maximum, about 20 K yrs BP. Modelling GIA is challenging because of large uncertainties in ice loading history and also the viscosity of the upper and lower mantle. GPS data contain the signature of GIA in their uplift rates but these also contain other sources of vertical land motion (VLM) such as tectonics, human and natural influences on water storage that can mask the underlying GIA signal.
A novel fully-automatic strategy was developed to post-process the GPS time series and to correct for non-GIA artefacts. Before estimating vertical velocities and uncertainties, we detected outliers and jumps and corrected for atmospheric mass loading displacements. We corrected the resulting velocities for the elastic response of the solid Earth to global changes in ice sheets, glaciers, and ocean loading, as well as for changes in the Earth's rotational pole relative to the 20th century average. We then applied a spatial median filter to remove sites where local effects were dominant to leave approximately 4000 GPS sites.
The resulting novel global GPS dataset shows a clean GIA signal at all post-processed stations and is suitable to investigate the behaviour of global GIA forward models. The results are transformed from a frame with its origin in the centre of mass of the total Earth's system (CM) into a frame with its origin in the centre of mass of the solid Earth (CE) before comparison with 13 global GIA forward model solutions, with best fits with Pur-6-VM5 and ICE-6G predictions. The largest discrepancies for all models were identified for Antarctica and Greenland, which may be due to either uncertain mantle rheology, ice loading history/magnitude and/or GPS errors
A new global GPS dataset for testing and improving modelled GIA uplift rates
We have produced a global dataset of ~4000 GPS vertical velocities that can be used as observational estimates of glacial isostatic adjustment (GIA) uplift rates. GIA is the response of the solid Earth to past ice loading, primarily, since the Last Glacial Maximum, about 20 K yrs BP. Modelling GIA is challenging because of large uncertainties in ice loading history and also the viscosity of the upper and lower mantle. GPS data contain the signature of GIA in their uplift rates but these also contain other sources of vertical land motion (VLM) such as tectonics, human and natural influences on water storage that can mask the underlying GIA signal.
A novel fully-automatic strategy was developed to post-process the GPS time series and to correct for non-GIA artefacts. Before estimating vertical velocities and uncertainties, we detected outliers and jumps and corrected for atmospheric mass loading displacements. We corrected the resulting velocities for the elastic response of the solid Earth to global changes in ice sheets, glaciers, and ocean loading, as well as for changes in the Earth's rotational pole relative to the 20th century average. We then applied a spatial median filter to remove sites where local effects were dominant to leave approximately 4000 GPS sites.
The resulting novel global GPS dataset shows a clean GIA signal at all post-processed stations and is suitable to investigate the behaviour of global GIA forward models. The results are transformed from a frame with its origin in the centre of mass of the total Earth's system (CM) into a frame with its origin in the centre of mass of the solid Earth (CE) before comparison with 13 global GIA forward model solutions, with best fits with Pur-6-VM5 and ICE-6G predictions. The largest discrepancies for all models were identified for Antarctica and Greenland, which may be due to either uncertain mantle rheology, ice loading history/magnitude and/or GPS errors
GNSS-IR Measurements of Inter Annual Sea Level Variations in Thule, Greenland from 2008–2019
Studies of global sea level often exclude Tide Gauges (TGs) in glaciated regions due to vertical land movement. Recent studies show that geodetic GNSS stations can be used to estimate sea level by taking advantage of the reflections from the ocean surface using GNSS Interferometric Reflectometry (GNSS-IR). This method has the immediate benefit that one can directly correct for bedrock movements as measured by the GNSS station. Here we test whether GNSS-IR can be used for measurements of inter annual sea level variations in Thule, Greenland, which is affected by sea ice and icebergs during much of the year. We do this by comparing annual average sea level variations using the two methods from 2008–2019. Comparing the individual sea level measurements over short timescales we find a root mean square deviation (RMSD) of 13 cm, which is similar to other studies using spectral methods. The RMSD for the annual average sea level variations between TG and GNSS-IR is large (18 mm) compared to the estimated uncertainties concerning the measurements. We expect that this is in part due to the TG not being datum controlled. We find sea level trends from GNSS-IR and TG of −4 and −7 mm/year, respectively. The negative trend can be partly explained by a gravimetric decrease in sea level as a result of ice mass changes. We model the gravimetric sea level from 2008–2017 and find a trend of −3 mm/year
Modelled glacier dynamics over the last quarter of a century at Jakobshavn Isbræ
Observations over the past 2 decades show substantial ice loss associated
with the speed-up of marine-terminating glaciers in Greenland. Here we use a
regional three-dimensional outlet glacier model to simulate the behaviour of Jakobshavn
Isbræ (JI) located in western Greenland. Our approach is to model and
understand the recent behaviour of JI with a physical process-based model.
Using atmospheric forcing and an ocean parametrization we tune our model to
reproduce observed frontal changes of JI during 1990–2014. In our
simulations, most of the JI retreat during 1990–2014 is driven by the ocean
parametrization used and the glacier's subsequent response, which is largely
governed by bed geometry. In general, the study shows significant progress in
modelling the temporal variability of the flow at JI. Our results suggest
that the overall variability in modelled horizontal velocities is a response
to variations in terminus position. The model simulates two major
accelerations that are consistent with observations of changes in glacier
terminus. The first event occurred in 1998 and was triggered by a retreat of
the front and moderate thinning of JI prior to 1998. The second event, which
started in 2003 and peaked in the summer 2004, was triggered by the final
break-up of the floating tongue. This break-up reduced the buttressing at the
JI terminus that resulted in further thinning. As the terminus retreated over
a reverse bed slope into deeper water, sustained high velocities over the
last decade have been observed at JI. Our model provides evidence that the
1998 and 2003 flow accelerations are most likely initiated by the ocean
parametrization used but JI's subsequent dynamic response was governed by its
own bed geometry. We are unable to reproduce the observed 2010–2012 terminus
retreat in our simulations. We attribute this limitation to either
inaccuracies in basal topography or to misrepresentations of the climatic
forcings that were applied. Nevertheless, the model is able to simulate the
previously observed increase in mass loss through 2014
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