scholarly journals Reconstruction of historical surface mass balance, 1984–2017 from GreenTrACS multi-offset ground-penetrating radar

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.

2010 ◽  
Vol 51 (55) ◽  
pp. 1-8 ◽  
Author(s):  
Karsten Müller ◽  
Anna Sinisalo ◽  
Helgard Anschütz ◽  
Svein-Erik Hamran ◽  
Jon-Ove Hagen ◽  
...  

AbstractSnow accumulation and its variability on the East Antarctic plateau are poorly understood due to sparse and regionally confined measurements. We present a 5.3 GHz (C-band) ground-penetrating radar (GPR) profile with a total length of 860 km recovered during the joint Norwegian–US International Polar Year traverse 2007/08. Mean surface mass balance (SMB) over the last 200 years was derived from the GPR data by identifying the volcanic deposition of the Tambora eruption in 1815. It varies between 9.1 and 37.7 kg m−2 a−1 over the profile, with a mean of 23.7 kg m−2 a−1 and a standard deviation of 4.7 kg m−2 a−1. The 200 year SMB estimated is significantly lower than most of the SMB estimates over shorter time periods in this region. This can be partly explained by a SMB minimum in the vicinity of the ice divide. However, it is more likely that a recent increase in SMB observed by several studies is largely responsible for the observed discrepancy.


2002 ◽  
Vol 35 ◽  
pp. 67-72 ◽  
Author(s):  
Edward Hanna ◽  
Philippe Huybrechts ◽  
Thomas L. Mote

AbstractWe used surface climate fields from high-resolution (~0.5660.56˚) European Centre for Medium-RangeWeather Forecasts (ECMWF) operational analyses (1992–98), together with meteorological and glaciological models of snow accumulation and surface meltwater runoff/retention, to produce novel maps of Greenland ice sheet (GIS) net accumulation, net runoff and surface mass balance (SMB). We compared our runoff maps with similar-scaled runoff (melt minus refreezing) maps based on passive-microwave satellite data. Our gross spatial/temporal patterns of runoff compared well with those from the satellite data, although amounts of modelled runoff are likely too low. Mean accumulation was 0.287 (0.307)ma–1, and mean runoff was 0.128 (0.151)ma–1, averaged across the W. Abdalati (T. L. Mote) GIS mask. Corresponding mean SMB was 0.159 (0.156)ma–1, with considerable interannual variability (standard deviation ~0.11ma–1) primarily due to variations in runoff. Considering best estimates of current iceberg calving, overall the GIS is probably currently losing mass. Our study shows great promise for meaningfully modelling SMB based on forthcoming ``second-generation’’ ECMWF re-analysis (ERA-40) data, and comparing the results with ongoing laser/radarmeasurements of surface elevation. This should help elucidate to what extent surface elevation changes are caused by short-term SMB variations or other factors (e.g. ice dynamics).


2016 ◽  
Vol 10 (4) ◽  
pp. 1739-1752 ◽  
Author(s):  
Lora S. Koenig ◽  
Alvaro Ivanoff ◽  
Patrick M. Alexander ◽  
Joseph A. MacGregor ◽  
Xavier Fettweis ◽  
...  

Abstract. Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor its surface mass balance in order to improve sea-level rise predictions. Snow accumulation is the largest component of the ice sheet's surface mass balance, but in situ observations thereof are inherently sparse and models are difficult to evaluate at large scales. Here, we quantify recent Greenland accumulation rates using ultra-wideband (2–6.5 GHz) airborne snow radar data collected as part of NASA's Operation IceBridge between 2009 and 2012. We use a semiautomated method to trace the observed radiostratigraphy and then derive annual net accumulation rates for 2009–2012. The uncertainty in these radar-derived accumulation rates is on average 14 %. A comparison of the radar-derived accumulation rates and contemporaneous ice cores shows that snow radar captures both the annual and long-term mean accumulation rate accurately. A comparison with outputs from a regional climate model (MAR) shows that this model matches radar-derived accumulation rates in the ice sheet interior but produces higher values over southeastern Greenland. Our results demonstrate that snow radar can efficiently and accurately map patterns of snow accumulation across an ice sheet and that it is valuable for evaluating the accuracy of surface mass balance models.


2018 ◽  
Vol 10 (4) ◽  
pp. 1959-1985 ◽  
Author(s):  
Lynn Montgomery ◽  
Lora Koenig ◽  
Patrick Alexander

Abstract. Increasing atmospheric temperatures over ice cover affect surface processes, including melt, snowfall, and snow density. Here, we present the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset, a standardized dataset of Arctic and Antarctic observations of surface mass balance components. The July 2018 SUMup dataset consists of three subdatasets, snow/firn density (https://doi.org/10.18739/A2JH3D23R), at least near-annually resolved snow accumulation on land ice (https://doi.org/10.18739/A2DR2P790), and snow depth on sea ice (https://doi.org/10.18739/A2WS8HK6X), to monitor change and improve estimates of surface mass balance. The measurements in this dataset were compiled from field notes, papers, technical reports, and digital files. SUMup is a compiled, community-based dataset that can be and has been used to evaluate modeling efforts and remote sensing retrievals. Active submission of new or past measurements is encouraged. Analysis of the dataset shows that Greenland Ice Sheet density measurements in the top 1 m do not show a strong relationship with annual temperature. At Summit Station, Greenland, accumulation and surface density measurements vary seasonally with lower values during summer months. The SUMup dataset is a dynamic, living dataset that will be updated and expanded for community use as new measurements are taken and new processes are discovered and quantified.


2021 ◽  
Author(s):  
Marie G. P. Cavitte ◽  
Hugues Goosse ◽  
Sarah Wauthy ◽  
Jean-Louis Tison ◽  
Thore Kausch ◽  
...  

<p>Several studies have shown that there is often a poor match between surface mass balance (SMB, mass gain at the surface of the ice sheet) simulated by regional climate models and the one locally measured from ice cores in Antarctica. Models’ representation of the physical processes that affect SMB is known to be imperfect, while ice core records may be strongly influenced by local processes such as post-depositional wind redistribution and precipitation intermittency. These two sources of uncertainty likely both have a role to play in the discrepancy identified between modeled and observed ice core SMB estimates over the past centuries.</p><p>The goal here is to estimate the uncertainties associated with the difference between a point-wise measurement of SMB as provided by the ice core and the SMB averages over a grid of several square kilometers of the models. To do so, we use ground-penetrating radar (GPR) data, collected over several ice rises, located along the high accumulation Princess Ragnhild Coast (East Antarctica), to obtain a multi-year resolution record that goes back ∼30-40 years, representing SMB spatial and temporal variability at the scale of a few km<sup>2</sup> for each ice rise. Ice cores were collected during each radar field campaign, which allows us to place age constraints on the radar stratigraphy obtained and compare the GPR SMB estimates with the ice core SMB estimate.</p><p>Therefore, we are able to calculate an error of representativeness for each ice core SMB, estimated as the difference between the average GPR SMB over a few km<sup>2</sup> and the ice core SMB. This representativeness error can be split into two components: a systematic error (on the order of ∼0.1 m w.e. yr<sup>-1</sup>) and a random error (on the order of ±1 cm w.e. yr<sup>-1</sup>). Finally, we then compare our corrected ice core SMB records to regional SMB derived from a state-of-the-art polar-oriented regional climate model to quantify the impact of ice core uncertainties on the modeled-observed SMB discrepancy.</p>


2018 ◽  
Author(s):  
Lynn Montgomery ◽  
Lora Koenig ◽  
Patrick Alexander

Abstract. Increasing atmospheric temperatures over ice cover affects surface processes including melt, snowfall and snow density. Here, we present the SUMup dataset, a standardized dataset of Arctic and Antarctic observations of surface mass balance components. The July 2017 SUMup dataset consists of three subdatasets, snow/firn density (doi:10.18739/A26D6F), snow accumulation on land ice (doi:10.18739/A2XX0V), and snow depth on sea ice (doi:10.18739/A22Q35), to monitor change and improve estimates of surface mass balance. The measurements in this dataset were compiled from field notes, papers, technical reports, and digital files. SUMup is a compiled, community-based dataset that can be and has been used to evaluate modeling efforts and remote sensing retrievals. Measurements in the dataset are sporadic in time and have spatial gaps, however, they likely constitute the largest set of field measurements compiled, standardized and publicly available. Analysis of the dataset shows that Greenland ice sheet density measurements in the top 1 m do not show a strong relationship with annual temperature. At Summit Station, Greenland accumulation and surface density measurements vary seasonally with lower values during summer months. The SUMup dataset is a dynamic, living dataset that will be updated and expanded for community use as new measurements are taken and new processes are discovered and quantified.


2013 ◽  
Vol 35 (5) ◽  
pp. 1155-1174 ◽  
Author(s):  
J. H. van Angelen ◽  
M. R. van den Broeke ◽  
B. Wouters ◽  
J. T. M. Lenaerts

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.


2017 ◽  
Vol 11 (6) ◽  
pp. 2411-2426 ◽  
Author(s):  
Peter Kuipers Munneke ◽  
Daniel McGrath ◽  
Brooke Medley ◽  
Adrian Luckman ◽  
Suzanne Bevan ◽  
...  

Abstract. The surface mass balance (SMB) of the Larsen C ice shelf (LCIS), Antarctica, is poorly constrained due to a dearth of in situ observations. Combining several geophysical techniques, we reconstruct spatial and temporal patterns of SMB over the LCIS. Continuous time series of snow height (2.5–6 years) at five locations allow for multi-year estimates of seasonal and annual SMB over the LCIS. There is high interannual variability in SMB as well as spatial variability: in the north, SMB is 0.40 ± 0.06 to 0.41 ± 0.04 m w.e. year−1, while farther south, SMB is up to 0.50 ± 0.05 m w.e. year−1. This difference between north and south is corroborated by winter snow accumulation derived from an airborne radar survey from 2009, which showed an average snow thickness of 0.34 m w.e. north of 66° S, and 0.40 m w.e. south of 68° S. Analysis of ground-penetrating radar from several field campaigns allows for a longer-term perspective of spatial variations in SMB: a particularly strong and coherent reflection horizon below 25–44 m of water-equivalent ice and firn is observed in radargrams collected across the shelf. We propose that this horizon was formed synchronously across the ice shelf. Combining snow height observations, ground and airborne radar, and SMB output from a regional climate model yields a gridded estimate of SMB over the LCIS. It confirms that SMB increases from north to south, overprinted by a gradient of increasing SMB to the west, modulated in the west by föhn-induced sublimation. Previous observations show a strong decrease in firn air content toward the west, which we attribute to spatial patterns of melt, refreezing, and densification rather than SMB.


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