scholarly journals Representative surface snow density on the East Antarctic Plateau

2020 ◽  
Author(s):  
Alexander H. Weinhart ◽  
Johannes Freitag ◽  
Maria Hörhold ◽  
Sepp Kipfstuhl ◽  
Olaf Eisen

Abstract. Surface mass balance estimates of polar ice sheets are essential to estimate the contribution of ice sheets to sea level rise, in response global warming. One of the largest uncertainties in the interior regions of the ice sheets, such as the East Antarctic Plateau (EAP), is the determination of a precise surface snow density. Wrong estimates of snow and firn density can lead to significant underestimations of the surface mass balance. We present density data from snow profiles taken along an overland traverse in austral summer 2016/17 covering over 2000 km on the Dronning Maud Land plateau. The sampling strategy included investigation on various spatial scales, from regional to local, with sampling locations 100 km apart as well as a high-resolution study in a trench at 30° E 79° S with thirty 3 m deep snow profiles. Density of the surface snow profiles has been measured volumetrically as well as using μ-computer tomography. With an error of less than 2 %, the volumetric liner density provides higher precision than other sampling devices of smaller volume. With four spatially independent snow profiles per location we derive a representative and precise 1 m mean snow density with an error of less than 1.5 %. The average liner density along the traverse across the EAP is 355 kg m−3, which we identify as representative surface snow density between Kohnen station and Dome Fuji. The highest horizontal variability in density can be seen in the upper 0.3 m. Therefore, we do not recommend vertical sampling in intervals of less than several decimeters, as this does neither adequately cover seasonal variations in high accumulation areas nor the annual accumulation in low accumulation areas. From statistical analysis of the liner density on regional scale we identify representative spatial distributions of density based on geographical and thus climatic conditions. Our representative density of 355 kg m−3 is considerably different from the density of 320 kg m−3 provided by a regional climate model. This difference of more than 10 % indicates the necessity for further calibration of density parameterizations. The difference in the total mass equivalent of measured and modelled density yields a 3 % underestimation by models, which translates into 5 cm sea level equivalent. We do not find a statistically significant temporal trend in density changes over the last two decades. Our data provide a solid baseline for tuning parameterizations of the surface snow density for regions with low accumulation and low temperatures like the EAP to improve surface mass balance estimates of polar ice sheets.

2020 ◽  
Vol 14 (11) ◽  
pp. 3663-3685
Author(s):  
Alexander H. Weinhart ◽  
Johannes Freitag ◽  
Maria Hörhold ◽  
Sepp Kipfstuhl ◽  
Olaf Eisen

Abstract. Surface mass balances of polar ice sheets are essential to estimate the contribution of ice sheets to sea level rise. Uncertain snow and firn densities lead to significant uncertainties in surface mass balances, especially in the interior regions of the ice sheets, such as the East Antarctic Plateau (EAP). Robust field measurements of surface snow density are sparse and challenging due to local noise. Here, we present a snow density dataset from an overland traverse in austral summer 2016/17 on the Dronning Maud Land plateau. The sampling strategy using 1 m carbon fiber tubes covered various spatial scales, as well as a high-resolution study in a trench at 79∘ S, 30∘ E. The 1 m snow density has been derived volumetrically, and vertical snow profiles have been measured using a core-scale microfocus X-ray computer tomograph. With an error of less than 2 %, our method provides higher precision than other sampling devices of smaller volume. With four spatially independent snow profiles per location, we reduce the local noise and derive a representative 1 m snow density with an error of the mean of less than 1.5 %. Assessing sampling methods used in previous studies, we find the highest horizontal variability in density in the upper 0.3 m and therefore recommend the 1 m snow density as a robust measure of surface snow density in future studies. The average 1 m snow density across the EAP is 355 kg m−3, which we identify as representative surface snow density between Kohnen Station and Dome Fuji. We cannot detect a temporal trend caused by the temperature increase over the last 2 decades. A difference of more than 10 % to the density of 320 kg m−3 suggested by a semiempirical firn model for the same region indicates the necessity for further calibration of surface snow density parameterizations. Our data provide a solid baseline for tuning the surface snow density parameterizations for regions with low accumulation and low temperatures like the EAP.


Nature ◽  
2001 ◽  
Vol 409 (6823) ◽  
pp. 1026-1029 ◽  
Author(s):  
Jerry X. Mitrovica ◽  
Mark E. Tamisiea ◽  
James L. Davis ◽  
Glenn A. Milne

2018 ◽  
Vol 12 (4) ◽  
pp. 1433-1460 ◽  
Author(s):  
Heiko Goelzer ◽  
Sophie Nowicki ◽  
Tamsin Edwards ◽  
Matthew Beckley ◽  
Ayako Abe-Ouchi ◽  
...  

Abstract. Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. The goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within the Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises.


2020 ◽  
pp. 1-10
Author(s):  
Tate G. Meehan ◽  
H. P. Marshall ◽  
John H. Bradford ◽  
Robert L. Hawley ◽  
Thomas B. Overly ◽  
...  

Abstract We present continuous estimates of snow and firn density, layer depth and accumulation from a multi-channel, multi-offset, ground-penetrating radar traverse. Our method uses the electromagnetic velocity, estimated from waveform travel-times measured at common-midpoints between sources and receivers. Previously, common-midpoint radar experiments on ice sheets have been limited to point observations. We completed radar velocity analysis in the upper ~2 m to estimate the surface and average snow density of the Greenland Ice Sheet. We parameterized the Herron and Langway (1980) firn density and age model using the radar-derived snow density, radar-derived surface mass balance (2015–2017) and reanalysis-derived temperature data. We applied structure-oriented filtering to the radar image along constant age horizons and increased the depth at which horizons could be reliably interpreted. We reconstructed the historical instantaneous surface mass balance, which we averaged into annual and multidecadal products along a 78 km traverse for the period 1984–2017. We found good agreement between our physically constrained parameterization and a firn core collected from the dry snow accumulation zone, and gained insights into the spatial correlation of surface snow density.


2018 ◽  
Vol 12 (10) ◽  
pp. 3097-3121 ◽  
Author(s):  
Reinhard Calov ◽  
Sebastian Beyer ◽  
Ralf Greve ◽  
Johanna Beckmann ◽  
Matteo Willeit ◽  
...  

Abstract. We introduce the coupled model of the Greenland glacial system IGLOO 1.0, including the polythermal ice sheet model SICOPOLIS (version 3.3) with hybrid dynamics, the model of basal hydrology HYDRO and a parameterization of submarine melt for marine-terminated outlet glaciers. The aim of this glacial system model is to gain a better understanding of the processes important for the future contribution of the Greenland ice sheet to sea level rise under future climate change scenarios. The ice sheet is initialized via a relaxation towards observed surface elevation, imposing the palaeo-surface temperature over the last glacial cycle. As a present-day reference, we use the 1961–1990 standard climatology derived from simulations of the regional atmosphere model MAR with ERA reanalysis boundary conditions. For the palaeo-part of the spin-up, we add the temperature anomaly derived from the GRIP ice core to the years 1961–1990 average surface temperature field. For our projections, we apply surface temperature and surface mass balance anomalies derived from RCP 4.5 and RCP 8.5 scenarios created by MAR with boundary conditions from simulations with three CMIP5 models. The hybrid ice sheet model is fully coupled with the model of basal hydrology. With this model and the MAR scenarios, we perform simulations to estimate the contribution of the Greenland ice sheet to future sea level rise until the end of the 21st and 23rd centuries. Further on, the impact of elevation–surface mass balance feedback, introduced via the MAR data, on future sea level rise is inspected. In our projections, we found the Greenland ice sheet to contribute between 1.9 and 13.0 cm to global sea level rise until the year 2100 and between 3.5 and 76.4 cm until the year 2300, including our simulated additional sea level rise due to elevation–surface mass balance feedback. Translated into additional sea level rise, the strength of this feedback in the year 2100 varies from 0.4 to 1.7 cm, and in the year 2300 it ranges from 1.7 to 21.8 cm. Additionally, taking the Helheim and Store glaciers as examples, we investigate the role of ocean warming and surface runoff change for the melting of outlet glaciers. It shows that ocean temperature and subglacial discharge are about equally important for the melting of the examined outlet glaciers.


2021 ◽  
Author(s):  
Zhitong Yu ◽  
Luojia Hu ◽  
Yan Huang ◽  
Rong Ma ◽  
Peng Xiao ◽  
...  

<p>Quantifying changes in Earth’s ice sheets and identifying the climate drivers are central to improving sea level projections. But it is a pity that the future sea level is difficult to predicted. Space observation can provide global multiscale long-term continuous monitoring data. And it is very important for understanding intrinsic mechanisms, improve models and projections and analyze the impacts on human civilization.</p><p>Several satellites are applied for Global Cryosphere Watch, including sea ice extent and concentration, ice sheet elevation, glacier area and velocity. Although there are many variable can be measured by satellite sensors. But several variables need to improve the observing capability and developing new methods. Such as snow depth on ice, ice sheets thickness, and permafrost parameters. China has established high-resolution earth observation system to realize stereopsis and dynamic monitoring of the lands, the oceans and the atmosphere.</p><p>Currently, Qian Xuesen Laboratory working together with Sun Yat-sen University, is trying to design a new space observation system to support Three Poles Environment and Climate Changes project. We are conceptualizing two series satellites including FluxSats and BingSats for carbon/water cycle and cryosphere observations, respectively. To clarify the mechanism of the cryosphere carbon release and carbon sink effects of the oceans and ecosystems. We are developing a new lidar system for detecting the concentration and wind speed, and then atmospheric boundary layer flux exchange can be estimated. To understand the rapid change of the sea ice, such as drift, fragmentation and freeze. We need a short revisit and wide swath system capabilities. InSAR technology gives the digitial elevation of the ice surface. And temporal difference InSAR (DInSAR) shows the changes of elevation. BingSAT-Tomographic Observation of Polar Ice Sheets (TOPIS) achieves the tomographic observation of polar ice sheets with a wide swath and short revisit time. Over the polar regions, the CubeSats form a large cross-track baseline with the master satellite to realize the high two-dimensional spatial resolution with the along-track synthetic aperture. The MirrorSAR technology is utilized in BingSat-TOPIS to achieve time and phase synchronization more economically than the traditional bistatic radar. Sparse array and digital beamforming are also considered to significantly reduce the number of microsatellites, and achieve tomographic images of polar ice sheets.</p>


2016 ◽  
Vol 37 (7) ◽  
pp. 3154-3174 ◽  
Author(s):  
Sebastian H. Mernild ◽  
Glen E. Liston ◽  
Christopher Hiemstra ◽  
Ryan Wilson

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