scholarly journals The SUMup Dataset: Compiled measurements of surface mass balance components over ice sheets and sea ice with preliminary analysis over Greenland

2018 ◽  
Author(s):  
Lynn Montgomery ◽  
Lora Koenig ◽  
Patrick Alexander
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Greenland Ice Sheet ◽  
Field Measurements ◽  
Strong Relationship ◽  
Snow Accumulation ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Density Measurements ◽  
Field Notes

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.

scholarly journals The SUMup dataset: compiled measurements of surface mass balance components over ice sheets and sea ice with analysis over Greenland

2018 ◽  
Vol 10 (4) ◽  
pp. 1959-1985 ◽  
Author(s):  
Lynn Montgomery ◽  
Lora Koenig ◽  
Patrick Alexander
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Greenland Ice Sheet ◽  
Strong Relationship ◽  
Snow Accumulation ◽  
Surface Mass Balance ◽  
Community Based ◽  
Surface Mass ◽  
Density Measurements ◽  
Field Notes

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.

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 ◽  
...  
Keyword(s):  
Mass Balance ◽  
Ground Penetrating Radar ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Surface Mass Balance ◽  
Snow Density ◽  
Surface Mass ◽  
Age Model ◽  
Ground Penetrating ◽  
Good Agreement

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.

scholarly journals Surface mass balance of the Greenland ice sheet from climate-analysis data and accumulation/runoff models

2002 ◽  
Vol 35 ◽  
pp. 67-72 ◽  
Author(s):  
Edward Hanna ◽  
Philippe Huybrechts ◽  
Thomas L. Mote
Keyword(s):  
Mass Balance ◽  
Satellite Data ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Snow Accumulation ◽  
Surface Elevation ◽  
Great Promise ◽  
Surface Mass Balance ◽  
Ice Dynamics ◽  
Surface Mass

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).

scholarly journals Annual Greenland accumulation rates (2009–2012) from airborne snow radar

2016 ◽  
Vol 10 (4) ◽  
pp. 1739-1752 ◽  
Author(s):  
Lora S. Koenig ◽  
Alvaro Ivanoff ◽  
Patrick M. Alexander ◽  
Joseph A. MacGregor ◽  
Xavier Fettweis ◽  
...  
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ice Cores ◽  
Snow Accumulation ◽  
Ultra Wideband ◽  
The Arctic ◽  
Surface Mass Balance ◽  
Accumulation Rates ◽  
Surface Mass

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.

Contemporary (1960–2012) Evolution of the Climate and Surface Mass Balance of the Greenland Ice Sheet

2013 ◽  
Vol 35 (5) ◽  
pp. 1155-1174 ◽  
Author(s):  
J. H. van Angelen ◽  
M. R. van den Broeke ◽  
B. Wouters ◽  
J. T. M. Lenaerts
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass

scholarly journals Simulation of the future sea level contribution of Greenland with a new glacial system model

2018 ◽  
Vol 12 (10) ◽  
pp. 3097-3121 ◽  
Author(s):  
Reinhard Calov ◽  
Sebastian Beyer ◽  
Ralf Greve ◽  
Johanna Beckmann ◽  
Matteo Willeit ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Surface Temperature ◽  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
System Model ◽  
Surface Mass Balance ◽  
Surface Mass

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.

scholarly journals Observationally constrained surface mass balance of Larsen C ice shelf, Antarctica

2017 ◽  
Vol 11 (6) ◽  
pp. 2411-2426 ◽  
Author(s):  
Peter Kuipers Munneke ◽  
Daniel McGrath ◽  
Brooke Medley ◽  
Adrian Luckman ◽  
Suzanne Bevan ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Snow Accumulation ◽  
Airborne Radar ◽  
Surface Mass Balance ◽  
Spatial And Temporal Patterns ◽  
Ice Shelf ◽  
The West ◽  
Surface Mass

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.

scholarly journals Seasonal mass variations show timing and magnitude of meltwater storage in the Greenland Ice Sheet

2018 ◽  
Vol 12 (9) ◽  
pp. 2981-2999 ◽  
Author(s):  
Jiangjun Ran ◽  
Miren Vizcaino ◽  
Pavel Ditmar ◽  
Michiel R. van den Broeke ◽  
Twila Moon ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Spatial Scales ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
High Accumulation ◽  
Outlet Glacier ◽  
Surface Mass ◽  
Meltwater Runoff

Abstract. The Greenland Ice Sheet (GrIS) is currently losing ice mass. In order to accurately predict future sea level rise, the mechanisms driving the observed mass loss must be better understood. Here, we combine data from the satellite gravimetry mission Gravity Recovery and Climate Experiment (GRACE), surface mass balance (SMB) output of the Regional Atmospheric Climate Model v. 2 (RACMO2), and ice discharge estimates to analyze the mass budget of Greenland at various temporal and spatial scales. We find that the mean rate of mass variations in Greenland observed by GRACE was between −277 and −269 Gt yr−1 in 2003–2012. This estimate is consistent with the sum (i.e., -304±126 Gt yr−1) of individual contributions – surface mass balance (SMB, 216±122 Gt yr−1) and ice discharge (520±31 Gt yr−1) – and with previous studies. We further identify a seasonal mass anomaly throughout the GRACE record that peaks in July at 80–120 Gt and which we interpret to be due to a combination of englacial and subglacial water storage generated by summer surface melting. The robustness of this estimate is demonstrated by using both different GRACE-based solutions and different meltwater runoff estimates (namely, RACMO2.3, SNOWPACK, and MAR3.9). Meltwater storage in the ice sheet occurs primarily due to storage in the high-accumulation regions of the southeast and northwest parts of Greenland. Analysis of seasonal variations in outlet glacier discharge shows that the contribution of ice discharge to the observed signal is minor (at the level of only a few gigatonnes) and does not explain the seasonal differences between the total mass and SMB signals. With the improved quantification of meltwater storage at the seasonal scale, we highlight its importance for understanding glacio-hydrological processes and their contributions to the ice sheet mass variability.

scholarly journals The impact of a seasonally ice free Arctic Ocean on the climate and surface mass balance of Svalbard

2011 ◽  
Vol 5 (4) ◽  
pp. 1887-1920
Author(s):  
J. J. Day ◽  
J. L. Bamber ◽  
P. J. Valdes ◽  
J. Kohler
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Mass Balance ◽  
21St Century ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Sea Ice Decline ◽  
Ice Edge ◽  
Sea Ice Edge ◽  
The Impact

Abstract. General circulation models (GCMs) predict a rapid decrease in Arctic sea ice extent in the 21st century. The decline of September sea ice is expected to continue until the Arctic Ocean is seasonally ice free, leading to a much perturbed Arctic climate with large changes in surface energy flux. Svalbard, located on the present day sea ice edge, contains many low lying ice caps and glaciers which are extremely sensitive to changes in climate. Records of past accumulation indicate that the surface mass balance (SMB) of Svalbard is also sensitive to changes in the position of the sea ice edge. To investigate the impact of 21st Century sea ice decline on the climate and surface mass balance of Svalbard a high resolution (25 km) regional climate model (RCM) was forced with a repeating cycle of sea surface temperatures (SSTs) and sea ice conditions for the periods 1961–1990 and 2061–2090. By prescribing 20th Century SSTs and 21st Century sea ice for one simulation, the impact of sea ice decline is isolated. This study shows that the coupled impact of sea ice decline and SST increase results in a decrease in SMB, whereas the impact of sea ice decline alone causes an increase in SMB of similar magnitude.

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