scholarly journals Glacier surface temperatures in the Canadian High Arctic, 2000–15

2016 ◽  
Vol 62 (235) ◽  
pp. 963-975 ◽  
Author(s):  
COLLEEN A. MORTIMER ◽  
MARTIN SHARP ◽  
BERT WOUTERS
Keyword(s):  
Mass Balance ◽  
Land Surface ◽  
Large Scale ◽  
Average Rate ◽  
Spatial And Temporal Variability ◽  
Surface Mass Balance ◽  
Glacier Surface ◽  
Near Surface ◽  
Surface Mass ◽  
Surface Temperatures

ABSTRACTCanada's Queen Elizabeth Islands (QEI) contain ~14% of the world's glacier and ice-cap area. Sparse in-situ measurements indicate that interannual variability in glacier surface mass balance in this region is driven primarily by variations in summer melt, and that the annual surface mass balance of four index glaciers has become increasingly negative since 2007. Here, we use a 16-a record of satellite-derived mean summer (June–August) land surface temperatures (LST) from NASA's Moderate Resolution Imaging Spectroradiometer to investigate large-scale spatial and temporal variability in the duration and intensity of summer melt across glaciated surfaces in the QEI from 2000 to 2015. During this period, QEI mean summer glacier surface temperatures increased at an average rate of 0.06 ± 0.04°C a−1, for a total of nearly 1°C. Most of this increase occurred between 2005 and 2012, when mean summer near-surface (2 m) and upper-air (700 hPa) temperatures were 1.0–1.2°C higher than the 1948–2015 mean. There is a strong correlation between the glacier LST and 700 hPa air temperature records (r> 0.8). The period 2005–12, when mean summer LSTs were anomalously high, was likely the warmest period in the region since at least 1948.

scholarly journals Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

2017 ◽  
Vol 11 (6) ◽  
pp. 2595-2609 ◽  
Author(s):  
Jeremy Fyke ◽  
Jan T. M. Lenaerts ◽  
Hailong Wang
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Model Simulation ◽  
Precipitation Variability ◽  
Spatial And Temporal Variability ◽  
Surface Mass Balance ◽  
Dominant Term ◽  
Surface Mass ◽  
Basin Scale ◽  
Antarctic Precipitation

Abstract. Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and ice core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.

scholarly journals Glacier Surface Mass Balance in the Suntar-Khayata Mountains, Northeastern Siberia

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1949 ◽  
Author(s):  
Yong Zhang ◽  
Xin Wang ◽  
Zongli Jiang ◽  
Junfeng Wei ◽  
Hiroyuki Enomoto ◽  
...  
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Surface Mass Balance ◽  
Negative Mass ◽  
Glacier Surface ◽  
Surface Mass ◽  
Northeastern Siberia ◽  
Response To Temperature ◽  
Rapid Mass

Arctic glaciers comprise a small fraction of the world’s land ice area, but their ongoing mass loss currently represents a large cryospheric contribution to the sea level rise. In the Suntar-Khayata Mountains (SKMs) of northeastern Siberia, in situ measurements of glacier surface mass balance (SMB) are relatively sparse, limiting our understanding of the spatiotemporal patterns of regional mass loss. Here, we present SMB time series for all glaciers in the SKMs, estimated through a glacier SMB model. Our results yielded an average SMB of −0.22 m water equivalents (w.e.) year−1 for the whole region during 1951–2011. We found that 77.4% of these glaciers had a negative mass balance and detected slightly negative mass balance prior to 1991 and significantly rapid mass loss since 1991. The analysis suggests that the rapidly accelerating mass loss was dominated by increased surface melting, while the importance of refreezing in the SMB progressively decreased over time. Projections under two future climate scenarios confirmed the sustained rapid shrinkage of these glaciers. In response to temperature rise, the total present glacier area is likely to decrease by around 50% during the period 2071–2100 under representative concentration pathway 8.5 (RCP8.5).

Impact of the choice of surface mass balance models and their calibration on large-scale glacier change projections

2021 ◽  
Author(s):  
Lilian Schuster ◽  
David Rounce ◽  
Fabien Maussion
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Model Complexity ◽  
Model Parameters ◽  
Glacier Change ◽  
Surface Mass Balance ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Mass Balance Models ◽  
Intercomparison Study

<p>A recent large model intercomparison study (GlacierMIP) showed that differences between the glacier models is a dominant source of uncertainty for future glacier change projections, in particular in the first half of the century.  Each glacier model has their own unique set of process representations and climate forcing methodology, which makes it impossible to determine the model components that contribute most to the projection uncertainty. This study aims to improve our understanding of the sources of large scale glacier model uncertainty using the Open Global Glacier Model (OGGM), focussing on the surface mass balance (SMB) in a first step. We calibrate and run a set of interchangeable SMB model parameterizations (e.g. monthly vs. daily, constant vs. variable lapse rates, albedo, snowpack evolution and refreezing) under controlled boundary conditions. Based on ensemble approaches, we explore the influence of (i) the parameter calibration strategy and (ii) SMB model complexity on regional to global glacier change. These uncertainties are then put in relation to a qualitative selection of other model design choices, such as the forcing climate dataset and ice dynamics model parameters. </p>

scholarly journals Characteristics of the Antarctic surface mass balance, 1958–2002, using a regional atmospheric climate model

2005 ◽  
Vol 41 ◽  
pp. 97-104 ◽  
Author(s):  
W.J. Van De Berg ◽  
M.R. Van Den Broeke ◽  
C.H. Reijmer ◽  
E. Van Meijgaard
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Solid Precipitation ◽  
Temporal And Spatial Characteristics ◽  
The Antarctic ◽  
Regional Atmospheric Climate Model

AbstractTemporal and spatial characteristics of the Antarctic specific surface mass balance (SSMB) are presented, including its components solid precipitation, sublimation/deposition and melt. For this purpose, we use the output of a regional atmospheric climate model (RACMO2/ANT, horizontal resolution of ~55 km) for the period 1958–2002. RACMO2/ANT uses European Centre for Medium-Range Weather Forecasts (ECMWF) 40 year re-analysis (ERA-40) fields as forcing at the lateral boundaries. RACMO2/ANT underestimates SSMB in the high interior of East and West Antarctica and overestimates SSMB on the steep coastal slopes. Otherwise, the modeled spatial pattern of SSMB is in good qualitative agreement with recent compilations of in situ observations. Large-scale patterns, like the precipitation shadow effect of the Antarctic Peninsula, are well reproduced, and mesoscale SSMB patterns, such as the strong precipitation gradients on Law Dome, are well represented in the model. The integrated SSMB over the grounded ice sheet is 153mmw.e. a–1 for the period 1958–2002, which agrees within 5% with the latest measurement compilations. Sublimation and melt remove 7% and <1% respectively of the solid precipitation. We found significant seasonality of solid precipitation, with a maximum in autumn and a minimum in summer. No meaningful trend was identified for the SSMB, because the time series of solid precipitation and SSMB are affected by an inhomogeneity in 1980 within the ERA-40 fields that drive RACMO2/ANT. Sublimation, melt and liquid precipitation increase in time, which is related to a modeled increase in 2m temperature.

scholarly journals Temporally stable surface mass balance asymmetry across an ice rise derived from radar internal reflection horizons through inverse modeling

2016 ◽  
Vol 62 (233) ◽  
pp. 525-534 ◽  
Author(s):  
DENIS CALLENS ◽  
REINHARD DREWS ◽  
EMMANUEL WITRANT ◽  
MORGANE PHILIPPE ◽  
FRANK PATTYN
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Optimization Technique ◽  
Internal Reflection ◽  
Asymmetric Distribution ◽  
Surface Mass Balance ◽  
Ice Flow ◽  
Atmospheric Flow ◽  
Surface Mass ◽  
Ice Shelves

ABSTRACTIce rises are locally grounded parts of Antarctic ice shelves that play an important role in regulating ice flow from the continent towards the ocean. Because they protrude out of the otherwise horizontal ice shelves, ice rises induce an orographic uplift of the atmospheric flow, resulting in an asymmetric distribution of the surface mass balance (SMB). Here, we combine younger and older internal reflection horizons (IRHs) from radar to quantify this distribution in time and space across Derwael Ice Rise (DIR), Dronning Maud Land, Antarctica. We employ two methods depending on the age of the IRHs, i.e. the shallow layer approximation for the younger IRHs near the surface and an optimization technique based on an ice flow model for the older IRHs. We identify an SMB ratio of 2.5 between the flanks and the ice divide with the SMB ranging between 300 and 750 kg m−2 a−1. The SMB maximum is located on the upwind side, ~4 km offset to today's topographic divide. The large-scale asymmetry is consistently observed in time until 1966. The SMB from older IRHs is less-well constrained, but the asymmetry has likely persisted for >ka, indicating that DIR has been a stable features over long time spans.

scholarly journals An Evaluation of Surface Climatology in State-of-the-Art Reanalyses over the Antarctic Ice Sheet

2019 ◽  
Vol 32 (20) ◽  
pp. 6899-6915 ◽  
Author(s):  
A. Gossart ◽  
S. Helsen ◽  
J. T. M. Lenaerts ◽  
S. Vanden Broucke ◽  
N. P. M. van Lipzig ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Surface Temperature ◽  
Mass Balance ◽  
Ice Sheet ◽  
Surface Mass Balance ◽  
Antarctic Ice Sheet ◽  
Near Surface ◽  
Surface Mass ◽  
Atmospheric Rivers ◽  
The Antarctic

Abstract In this study, we evaluate output of near-surface atmospheric variables over the Antarctic Ice Sheet from four reanalyses: the new European Centre for Medium-Range Weather Forecasts ERA-5 and its predecessor ERA-Interim, the Climate Forecast System Reanalysis (CFSR), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The near-surface temperature, wind speed, and relative humidity are compared with datasets of in situ observations, together with an assessment of the simulated surface mass balance (approximated by precipitation minus evaporation). No reanalysis clearly stands out as the best performing for all areas, seasons, and variables, and each of the reanalyses displays different biases. CFSR strongly overestimates the relative humidity during all seasons whereas ERA-5 and MERRA-2 (and, to a lesser extent, ERA-Interim) strongly underestimate relative humidity during winter. ERA-5 captures the seasonal cycle of near-surface temperature best and shows the smallest bias relative to the observations. The other reanalyses show a general temperature underestimation during the winter months in the Antarctic interior and overestimation in the coastal areas. All reanalyses underestimate the mean near-surface winds in the interior (except MERRA-2) and along the coast during the entire year. The winds at the Antarctic Peninsula are overestimated by all reanalyses except MERRA-2. All models are able to capture snowfall patterns related to atmospheric rivers, with varying accuracy. Accumulation is best represented by ERA-5, although it underestimates observed surface mass balance and there is some variability in the accumulation over the different elevation classes, for all reanalyses.

The Andes Cordillera. Part III: glacier surface mass balance and contribution to sea level rise (1979-2014)

2016 ◽  
Vol 37 (7) ◽  
pp. 3154-3174 ◽  
Author(s):  
Sebastian H. Mernild ◽  
Glen E. Liston ◽  
Christopher Hiemstra ◽  
Ryan Wilson
Keyword(s):  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Surface Mass Balance ◽  
Glacier Surface ◽  
Surface Mass ◽  
The Andes ◽  
Andes Cordillera

scholarly journals Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation

2021 ◽  
Author(s):  
Nicolaj Hansen ◽  
Peter L. Langen ◽  
Fredrik Boberg ◽  
Rene Forsberg ◽  
Sebastian B. Simonsen ◽  
...  
Keyword(s):  
Mass Balance ◽  
Total Mass ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Lagrangian Framework ◽  
Basin Scale ◽  
The Antarctic

Abstract. Antarctic surface mass balance (SMB) is largely determined by precipitation over the continent and subject to regional climate variability related to the Southern Annular Mode (SAM) and other climatic drivers at the large scale. Locally however, firn and snow pack processes are important in determining SMB and the total mass balance of Antarctica and global sea level. Here, we examine factors that influence Antarctic SMB and attempt to reconcile the outcome with estimates for total mass balance determined from the GRACE satellites. This is done by having the regional climate model HIRHAM5 forcing two versions of an offline subsurface model, to estimate Antarctic ice sheet (AIS) SMB from 1980 to 2017. The Lagrangian subsurface model estimates AIS SMB of 2473.5 ± 114.4 Gt per year, while the Eulerian subsurface model variant results in slightly higher modelled SMB of 2564.8 ± 113.7 Gt per year. The majority of this difference in modelled SMB is due to melt and refreezing over ice shelves and demonstrates the importance of firn modelling in areas with substantial melt. Both the Eulerian and the Lagrangian SMB estimates are within uncertainty ranges of each other and within the range of other SMB studies. However, the Lagrangian version has better statistics when modelling the densities. There is a mean bias in modelled density of −24.0 ± 18.4 kg m−3 and −8.2 ± 15.3 kg m−3 for layers less than 550 kg m−3 for the Eulerian and Lagrangian framework, respectively. For layers with a density above 550 kg m−3 the bias is −31.7 ± 23.4 kg m−3 and −35.0 ± 23.7 kg m−3 for the Eulerian and Lagrangian framework, respectively. The mean firn 10 m temperature bias is 0.42–0.52 °C. Further, analysis of the relationship between SMB in individual drainage basins and the SAM, is carried out using a bootstrapping approach. This shows a robust relationship between SAM and SMB in half of the basins (13 out of 27). In general, when SAM is positive there is a lower SMB over the Plateau and a higher SMB on the westerly side of the Antarctic Peninsula, and vice versa when the SAM is negative. Finally, we compare the modelled SMB to GRACE data by subtracting the solid ice discharge, and find that there is a good agreement in East Antarctica, but large disagreements over the Antarctic Peninsula.There is a large difference between published estimates of discharge that make it challenging to use mass reconciliation in evaluating SMB models on the basin scale.

scholarly journals High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram

2013 ◽  
Vol 7 (1) ◽  
pp. 103-144 ◽  
Author(s):  
E. Collier ◽  
T. Mölg ◽  
F. Maussion ◽  
D. Scherer ◽  
C. Mayer ◽  
...  
Keyword(s):  
High Resolution ◽  
Mass Balance ◽  
Land Surface ◽  
Traditional Approach ◽  
Coupled Model ◽  
Glacier Mass Balance ◽  
Glacier Surface ◽  
Mountain Glacier ◽  
Near Surface ◽  
Basin Scale

Abstract. The traditional approach to simulations of alpine glacier mass balance (MB) has been one-way, or offline, thus precluding feedbacks from changing glacier surface conditions on the atmospheric forcing. In addition, alpine glaciers have been only simply, if at all, represented in atmospheric models to date. Here, we extend a recently presented, novel technique for simulating glacier–atmosphere interactions without the need for statistical downscaling, through the use of a coupled high-resolution mesoscale atmospheric and physically-based mass balance modelling system that includes glacier MB and energy balance feedbacks to the atmosphere. We compare the model results over the Karakoram region of the northwestern Himalaya with both remote sensing data and in situ glaciological and meteorological measurements for the ablation season of 2004. We find that interactive coupling has a localized but appreciable impact on the near-surface meteorological forcing data and that incorporation of MB processes improves the simulation of variables such as land surface temperature and snow albedo. Furthermore, including feedbacks from the MB model has a non-negligible effect on simulated mass balance, reducing modelled ablation, on average, by 0.1 m w.e. (−6.0%) to a total of −1.5 m w.e. between 25 June–31 August 2004. The interactively coupled model shows promise as a new, multi-scale tool for explicitly resolving atmospheric-MB processes of mountain glaciers at the basin scale.

scholarly journals Reconciling the surface temperature–surface mass balance relationship in models and ice cores in Antarctica over the last two centuries

2020 ◽  
Author(s):  
Marie G. P. Cavitte ◽  
Quentin Dalaiden ◽  
Hugues Goosse ◽  
Jan T. M. Lenaerts ◽  
Elizabeth R. Thomas
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Ice Core ◽  
Ice Sheets ◽  
Ice Cores ◽  
Surface Mass Balance ◽  
Weak Correlation ◽  
Surface Mass ◽  
The Past ◽  
Ice Core Records

Abstract. Ice cores are an important record of the past surface mass balance (SMB) of ice sheets, with SMB mitigating the ice sheets’ sea level impact over the recent decades. For the Antarctic Ice Sheet (AIS), SMB is dominated by large-scale atmospheric circulation, which collects warm moist air from further north and releases it in the form of snow as widespread accumulation or focused atmospheric rivers on the continent. This implies that the snow deposited at the surface of the AIS should record strongly coupled SMB and surface air temperature (SAT) variations. Ice cores use δ18O as a proxy for SAT as they do not record SAT directly. Here, using isotope-enabled global climate models and the RACMO2.3 regional climate model, we calculate positive SMB-SAT and δ18O-SMB correlations over ∼90 % of the AIS. The high spatial resolution of the RACMO2.3 model allows us to highlight a number of areas where SMB and SAT are not correlated, and show that wind-driven processes acting locally, such as Foehn and katabatic effects, can overwhelm the large-scale atmospheric input in SMB and SAT responsible for the positive SMB-SAT correlations. We focus in particular on Dronning Maud Land, East Antarctica, where the ice promontories clearly show these wind-induced effects. However, using the PAGES2k ice core compilations of SMB and δ18O of Thomas et al. (2017) and Stenni et al. (2017), we obtain a weak correlation, on the order of 0.1, between SMB and δ18O over the past ~150 years. We obtain an equivalently weak correlation between ice core SMB and the SAT reconstruction of Nicolas and Bromwich (2014) over the past ~50 years, although the ice core sites are not spatially co-located with the areas displaying a low SMB-SAT correlation in the models. To resolve the discrepancy between the measured and modeled signals, we show that averaging the ice core records in close spatial proximity increases their SMB-SAT correlation. This increase shows that the weak measured correlation likely results from random noise present in the ice core records, but is not large enough to match the correlation calculated in the models. Our results indicate thus a positive correlation between SAT and SMB in models and ice core reconstructions but with a weaker value in observations that may be due to missing processes in models or some systematic biases in ice core data that are not removed by a simple average.

Sign in / Sign up

Export Citation Format

Share Document