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1. Four decades of Antarctic Ice Sheet mass balance from 1979–2017

Author

Rignot, Eric, Mouginot, Jérémie, Scheuchl, Bernd, van den Broeke, Michiel, van Wessem, Melchior J, and Morlighem, Mathieu

Subjects
Climate Action, glaciology, Antarctica, remote sensing, climate change, sea-level rise
Abstract

We use updated drainage inventory, ice thickness, and ice velocity data to calculate the grounding line ice discharge of 176 basins draining the Antarctic Ice Sheet from 1979 to 2017. We compare the results with a surface mass balance model to deduce the ice sheet mass balance. The total mass loss increased from 40 ± 9 Gt/y in 1979-1990 to 50 ± 14 Gt/y in 1989-2000, 166 ± 18 Gt/y in 1999-2009, and 252 ± 26 Gt/y in 2009-2017. In 2009-2017, the mass loss was dominated by the Amundsen/Bellingshausen Sea sectors, in West Antarctica (159 ± 8 Gt/y), Wilkes Land, in East Antarctica (51 ± 13 Gt/y), and West and Northeast Peninsula (42 ± 5 Gt/y). The contribution to sea-level rise from Antarctica averaged 3.6 ± 0.5 mm per decade with a cumulative 14.0 ± 2.0 mm since 1979, including 6.9 ± 0.6 mm from West Antarctica, 4.4 ± 0.9 mm from East Antarctica, and 2.5 ± 0.4 mm from the Peninsula (i.e., East Antarctica is a major participant in the mass loss). During the entire period, the mass loss concentrated in areas closest to warm, salty, subsurface, circumpolar deep water (CDW), that is, consistent with enhanced polar westerlies pushing CDW toward Antarctica to melt its floating ice shelves, destabilize the glaciers, and raise sea level.

Published
2019

3. Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in sity observations and climate models

Author

van den Broeke, Michiel, Kuipers Munneke, Peter, Noël, Brice, Tijm - Reijmer, Carleen, Smeets, Paul, van de Berg, Willem Jan, van Wessem, Melchior, van den Broeke, Michiel, Kuipers Munneke, Peter, Noël, Brice, Tijm - Reijmer, Carleen, Smeets, Paul, van de Berg, Willem Jan, and van Wessem, Melchior

Abstract

Surface meltwater production impacts the mass balance of the Greenland and Antarctic ice sheets in several ways, both directly (e.g., through runoff in Greenland) and indirectly (e.g., through cryo-hydrologic warming and frontal melt of marine-terminating glaciers in Greenland and hydrofracturing of ice shelves in Antarctica). Despite its importance, the spatial and temporal patterns in melt rates on both ice sheets are still relatively poorly understood. In this contribution we review and contrast surface melt ‘weather ‘(i.e., short term, intra- and interdiurnal variability) and surface melt ‘climate’ (i.e., longer term, interannual variability and future melt) of both ice sheets. We find that in situ observations using suitably equipped (automatic or staffed) weather stations are invaluable for a complete understanding of the melt process, which represents the complex transport of energy by radiation, turbulence, and molecular conduction between the lower atmosphere, the ice/snow surface, and the subsurface ice/snow layers. We provide example time series of ice sheet melt ‘weather’ for the marginal Greenland ice sheet, where warm and humid air masses tend to increase surface melt rate, and for coastal East Antarctica, where the opposite happens. Apart from process understanding, these in situ observations, which especially in Antarctica are scarce in space and time, are also invaluable to validate, evaluate and calibrate satellite- and model-based estimates of ice sheet surface melt rate. We provide examples of modelled melt maps for both ice sheets, and melt projections for a high-warming, fossil-fuelled development scenario. Although important milestones in melt observations (both in-situ and remotely sensed) and melt models (both global and regional) have recently been reached, we identify multiple outstanding research questions pertaining to current and future ice sheet surface melt rates.

Published
2023

4. Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in sity observations and climate models

Author

Sub Dynamics Meteorology, Marine and Atmospheric Research, van den Broeke, Michiel, Kuipers Munneke, Peter, Noël, Brice, Tijm - Reijmer, Carleen, Smeets, Paul, van de Berg, Willem Jan, van Wessem, Melchior, Sub Dynamics Meteorology, Marine and Atmospheric Research, van den Broeke, Michiel, Kuipers Munneke, Peter, Noël, Brice, Tijm - Reijmer, Carleen, Smeets, Paul, van de Berg, Willem Jan, and van Wessem, Melchior

Published
2023

6. Mass balance of the Greenland Ice Sheet from 1992 to 2018

Author

Shepherd, Andrew, Ivins, Erik, Rignot, Eric, Smith, Ben, van den Broeke, Michiel, Velicogna, Isabella, Whitehouse, Pippa, Briggs, Kate, Joughin, Ian, Krinner, Gerhard, Nowicki, Sophie, Payne, Tony, Scambos, Ted, Schlegel, Nicole, Geruo, A., Agosta, Cécile, Ahlstrøm, Andreas, Babonis, Greg, Barletta, Valentina R., Bjørk, Anders A., Blazquez, Alejandro, Bonin, Jennifer, Colgan, William, Csatho, Beata, Cullather, Richard, Engdahl, Marcus E., Felikson, Denis, Fettweis, Xavier, Forsberg, Rene, Hogg, Anna E., Gallee, Hubert, Gardner, Alex, Gilbert, Lin, Gourmelen, Noel, Groh, Andreas, Gunter, Brian, Hanna, Edward, Harig, Christopher, Helm, Veit, Horvath, Alexander, Horwath, Martin, Khan, Shfaqat, Kjeldsen, Kristian K., Konrad, Hannes, Langen, Peter L., Lecavalier, Benoit, Loomis, Bryant, Luthcke, Scott, McMillan, Malcolm, Melini, Daniele, Mernild, Sebastian, Mohajerani, Yara, Moore, Philip, Mottram, Ruth, Mouginot, Jeremie, Moyano, Gorka, Muir, Alan, Nagler, Thomas, Nield, Grace, Nilsson, Johan, Noël, Brice, Otosaka, Ines, Pattle, Mark E., Peltier, W. Richard, Pie, Nadège, Rietbroek, Roelof, Rott, Helmut, Sørensen, Louise Sandberg, Sasgen, Ingo, Save, Himanshu, Scheuchl, Bernd, Schrama, Ernst, Schröder, Ludwig, Seo, Ki-Weon, Simonsen, Sebastian B., Slater, Thomas, Spada, Giorgio, Sutterley, Tyler, Talpe, Matthieu, Tarasov, Lev, Jan van de Berg, Willem, van der Wal, Wouter, van Wessem, Melchior, Vishwakarma, Bramha Dutt, Wiese, David, Wilton, David, Wagner, Thomas, Wouters, Bert, Wuite, Jan, Team, The IMBIE, Marine and Atmospheric Research, Sub Dynamics Meteorology, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Andrew Shepherd, Erik Ivin, Eric Rignot, Ben Smith, Michiel van den Broeke, Isabella Velicogna, Pippa Whitehouse, Kate Brigg, Ian Joughin, Gerhard Krinner, Sophie Nowicki, Tony Payne, Ted Scambo, Nicole Schlegel, A Geruo, Cécile Agosta, Andreas Ahlstrøm, Greg Baboni, Valentina R. Barletta, Anders A. Bjørk, Alejandro Blazquez, Jennifer Bonin, William Colgan, Beata Csatho, Richard Cullather, Marcus E. Engdahl, Denis Felikson, Xavier Fettwei, Rene Forsberg, Anna E. Hogg, Hubert Gallee, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian Gunter, Edward Hanna, Christopher Harig, Veit Helm, Alexander Horvath, Martin Horwath, Shfaqat Khan, Kristian K. Kjeldsen, Hannes Konrad, Peter L. Langen, Benoit Lecavalier, Bryant Loomi, Scott Luthcke, Malcolm McMillan, Daniele Melini, Sebastian Mernild, Yara Mohajerani, Philip Moore, Ruth Mottram, Jeremie Mouginot, Gorka Moyano, Alan Muir, Thomas Nagler, Grace Nield, Johan Nilsson, Brice Noël, Ines Otosaka, Mark E. Pattle, W. Richard Peltier, Nadège Pie, Roelof Rietbroek, Helmut Rott, Louise Sandberg Sørensen, Ingo Sasgen, Himanshu Save, Bernd Scheuchl, Ernst Schrama, Ludwig Schröder, Ki-Weon Seo, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler Sutterley, Matthieu Talpe, Lev Tarasov, Willem Jan van de Berg, Wouter van der Wal, Melchior van Wessem, Bramha Dutt Vishwakarma, David Wiese, David Wilton, Thomas Wagner, Bert Wouter, Jan Wuite, Marine and Atmospheric Research, and Sub Dynamics Meteorology

Subjects
geography, Multidisciplinary, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Global warming, Greenland ice sheet, Climate change, Glacier, GLACIAL ISOSTATIC-ADJUSTMENT, RELATIVE SEA-LEVEL PETERMANN GLACIER, ELEVATION CHANGE, SURFACE, GRACE, CLIMATE, MODEL, ACCELERATION, ANTARCTICA, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, Glacier mass balance, 13. Climate action, Taverne, [SDE]Environmental Sciences, SDG 13 - Climate Action, Environmental science, Climate model, Ice sheet, F840 Physical Geography, Meltwater, 0105 earth and related environmental sciences
Abstract

ArticlePublished: 10 December 2019This is an unedited manuscript that has been accepted for publication. Nature Research are providing this early version of the manuscript as a service to our customers. The manuscript will undergo copyediting, typesetting and a proof review before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.Mass balance of the Greenland Ice Sheet from 1992 to 2018The IMBIE TeamNature (2019)Cite this article6914 Accesses1410 AltmetricMetricsdetailsAbstractIn recent decades, the Greenland Ice Sheet has been a major contributor to global sea-level rise1,2, and it is expected to be so in the future3. Although increases in glacier flow4–6 and surface melting7–9 have been driven by oceanic10–12 and atmospheric13,14 warming, the degree and trajectory of today’s imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. Although the ice sheet was close to a state of balance in the 1990s, annual losses have risen since then, peaking at 335 ± 62 billion tonnes per year in 2011. In all, Greenland lost 3,800 ± 339 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.6 ± 0.9 millimetres. Using three regional climate models, we show that reduced surface mass balance has driven 1,971 ± 555 billion tonnes (52%) of the ice loss owing to increased meltwater runoff. The remaining 1,827 ± 538 billion tonnes (48%) of ice loss was due to increased glacier discharge, which rose from 41 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. Between 2013 and 2017, the total rate of ice loss slowed to 217 ± 32 billion tonnes per year, on average, as atmospheric circulation favoured cooler conditions15 and as ocean temperatures fell at the terminus of Jakobshavn Isbræ16. Cumulative ice losses from Greenland as a whole have been close to the IPCC’s predicted rates for their high-end climate warming scenario17, which forecast an additional 50 to 120 millimetres of global sea-level rise by 2100 when compared to their central estimate.

Published
2020
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7. What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates

Author

Mottram, Ruth H., Hansen, Nicolay, Kittel, Christoph, van Wessem, Melchior, Agosta, Cécile, Amory, Charles, Boberg, F., van de Berg, Willem Jan, Fettweis, Xavier, Gossart, Alexandra, van Lipzig, NPM, van Meijgaard, E., Orr, Andrew, Phillips, Tony, Webster, Stuart, Simonsen, S.B., Souverijns, Niels, Mottram, Ruth H., Hansen, Nicolay, Kittel, Christoph, van Wessem, Melchior, Agosta, Cécile, Amory, Charles, Boberg, F., van de Berg, Willem Jan, Fettweis, Xavier, Gossart, Alexandra, van Lipzig, NPM, van Meijgaard, E., Orr, Andrew, Phillips, Tony, Webster, Stuart, Simonsen, S.B., and Souverijns, Niels

Abstract

We compare the performance of five different regional climate models (RCMs) (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM, and RACMO2.3p2), forced by ERA-Interim reanalysis, in simulating the near-surface climate and surface mass balance (SMB) of Antarctica. All models simulate Antarctic climate well when compared with daily observed temperature and pressure, with nudged models matching daily observations slightly better than free-running models. The ensemble mean annual SMB over the Antarctic ice sheet (AIS) including ice shelves is 2329±94 Gt yr−1 over the common 1987–2015 period covered by all models. There is large interannual variability, consistent between models due to variability in the driving ERA-Interim reanalysis. Mean annual SMB is sensitive to the chosen period; over our 30-year climatological mean period (1980 to 2010), the ensemble mean is 2483 Gt yr−1. However, individual model estimates vary from 1961±70 to 2519±118 Gt yr−1. The largest spatial differences between model SMB estimates are in West Antarctica, the Antarctic Peninsula, and around the Transantarctic Mountains. We find no significant trend in Antarctic SMB over either period. Antarctic ice sheet (AIS) mass loss is currently equivalent to around 0.5 mm yr−1 of global mean sea level rise (Shepherd et al., 2020), but our results indicate some uncertainty in the SMB contribution based on RCMs. We compare modelled SMB with a large dataset of observations, which, though biased by undersampling, indicates that many of the biases in SMB are common between models. A drifting-snow scheme improves modelled SMB on ice sheet surface slopes with an elevation between 1000 and 2000 m, where strong katabatic winds form. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution are factored into our analysis. Targeting undersampled regions with high precipitation for observational campaigns will be key to improving future estimates of SMB in Antarctica.

Published
2021

8. What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates

Author

Sub Dynamics Meteorology, Marine and Atmospheric Research, Mottram, Ruth H., Hansen, Nicolay, Kittel, Christoph, van Wessem, Melchior, Agosta, Cécile, Amory, Charles, Boberg, F., van de Berg, Willem Jan, Fettweis, Xavier, Gossart, Alexandra, van Lipzig, NPM, van Meijgaard, E., Orr, Andrew, Phillips, Tony, Webster, Stuart, Simonsen, S.B., Souverijns, Niels, Sub Dynamics Meteorology, Marine and Atmospheric Research, Mottram, Ruth H., Hansen, Nicolay, Kittel, Christoph, van Wessem, Melchior, Agosta, Cécile, Amory, Charles, Boberg, F., van de Berg, Willem Jan, Fettweis, Xavier, Gossart, Alexandra, van Lipzig, NPM, van Meijgaard, E., Orr, Andrew, Phillips, Tony, Webster, Stuart, Simonsen, S.B., and Souverijns, Niels

Published
2021

11. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet

Author

Morlighem, Mathieu, Rignot, Eric, Binder, Tobias, Blankenship, Donald, Drews, Reinhard, Eagles, Graeme, Eisen, Olaf, Ferraccioli, Fausto, Forsberg, Rene, Fretwell, Peter, Goel, Vikram, Greenbaum, Jamin S., Gudmundsson, Hilmar, Guo, Jingxue, Helm, Veit, Hofstede, Coen, Howat, Ian, Humbert, Angelika, Jokat, Wilfried, Karlsson, Nanna B., Lee, Won Sang, Matsuoka, Kenichi, Millan, Romain, Mouginot, Jeremie, Paden, John, Pattyn, Frank, Roberts, Jason, Rosier, Sebastian, Ruppel, Antonia, Seroussi, Helene, Smith, Emma C., Steinhage, Daniel, Sun, Bo, van den Broeke, Michiel R., van Ommen, Tas D., van Wessem, Melchior, Young, Duncan A., Morlighem, Mathieu, Rignot, Eric, Binder, Tobias, Blankenship, Donald, Drews, Reinhard, Eagles, Graeme, Eisen, Olaf, Ferraccioli, Fausto, Forsberg, Rene, Fretwell, Peter, Goel, Vikram, Greenbaum, Jamin S., Gudmundsson, Hilmar, Guo, Jingxue, Helm, Veit, Hofstede, Coen, Howat, Ian, Humbert, Angelika, Jokat, Wilfried, Karlsson, Nanna B., Lee, Won Sang, Matsuoka, Kenichi, Millan, Romain, Mouginot, Jeremie, Paden, John, Pattyn, Frank, Roberts, Jason, Rosier, Sebastian, Ruppel, Antonia, Seroussi, Helene, Smith, Emma C., Steinhage, Daniel, Sun, Bo, van den Broeke, Michiel R., van Ommen, Tas D., van Wessem, Melchior, and Young, Duncan A.

Abstract

The Antarctic ice sheet has been losing mass over past decades through the accelerated flow of its glaciers, conditioned by ocean temperature and bed topography. Glaciers retreating along retrograde slopes (that is, the bed elevation drops in the inland direction) are potentially unstable, while subglacial ridges slow down the glacial retreat. Despite major advances in the mapping of subglacial bed topography, significant sectors of Antarctica remain poorly resolved and critical spatial details are missing. Here we present a novel, high-resolution and physically based description of Antarctic bed topography using mass conservation. Our results reveal previously unknown basal features with major implications for glacier response to climate change. For example, glaciers flowing across the Transantarctic Mountains are protected by broad, stabilizing ridges. Conversely, in the marine basin of Wilkes Land, East Antarctica, we find retrograde slopes along Ninnis and Denman glaciers, with stabilizing slopes beneath Moscow University, Totten and Lambert glacier system, despite corrections in bed elevation of up to 1 km for the latter. This transformative description of bed topography redefines the high- and lower-risk sectors for rapid sea level rise from Antarctica; it will also significantly impact model projections of sea level rise from Antarctica in the coming centuries.

Published
2020

12. Mass balance of the Greenland Ice Sheet from 1992 to 2018

Author

Marine and Atmospheric Research, Sub Dynamics Meteorology, Shepherd, Andrew, Ivins, Erik, Rignot, Eric, Smith, Ben, van den Broeke, Michiel, Velicogna, Isabella, Whitehouse, Pippa, Briggs, Kate, Joughin, Ian, Krinner, Gerhard, Nowicki, Sophie, Payne, Tony, Scambos, Ted, Schlegel, Nicole, Geruo, A., Agosta, Cécile, Ahlstrøm, Andreas, Babonis, Greg, Barletta, Valentina R., Bjørk, Anders A., Blazquez, Alejandro, Bonin, Jennifer, Colgan, William, Csatho, Beata, Cullather, Richard, Engdahl, Marcus E., Felikson, Denis, Fettweis, Xavier, Forsberg, Rene, Hogg, Anna E., Gallee, Hubert, Gardner, Alex, Gilbert, Lin, Gourmelen, Noel, Groh, Andreas, Gunter, Brian, Hanna, Edward, Harig, Christopher, Helm, Veit, Horvath, Alexander, Horwath, Martin, Khan, Shfaqat, Kjeldsen, Kristian K., Konrad, Hannes, Langen, Peter L., Lecavalier, Benoit, Loomis, Bryant, Luthcke, Scott, McMillan, Malcolm, Melini, Daniele, Mernild, Sebastian, Mohajerani, Yara, Moore, Philip, Mottram, Ruth, Mouginot, Jeremie, Moyano, Gorka, Muir, Alan, Nagler, Thomas, Nield, Grace, Nilsson, Johan, Noël, Brice, Otosaka, Ines, Pattle, Mark E., Peltier, W. Richard, Pie, Nadège, Rietbroek, Roelof, Rott, Helmut, Sørensen, Louise Sandberg, Sasgen, Ingo, Save, Himanshu, Scheuchl, Bernd, Schrama, Ernst, Schröder, Ludwig, Seo, Ki-Weon, Simonsen, Sebastian B., Slater, Thomas, Spada, Giorgio, Sutterley, Tyler, Talpe, Matthieu, Tarasov, Lev, Jan van de Berg, Willem, van der Wal, Wouter, van Wessem, Melchior, Vishwakarma, Bramha Dutt, Wiese, David, Wilton, David, Wagner, Thomas, Wouters, Bert, Wuite, Jan, Team, The IMBIE, Marine and Atmospheric Research, Sub Dynamics Meteorology, Shepherd, Andrew, Ivins, Erik, Rignot, Eric, Smith, Ben, van den Broeke, Michiel, Velicogna, Isabella, Whitehouse, Pippa, Briggs, Kate, Joughin, Ian, Krinner, Gerhard, Nowicki, Sophie, Payne, Tony, Scambos, Ted, Schlegel, Nicole, Geruo, A., Agosta, Cécile, Ahlstrøm, Andreas, Babonis, Greg, Barletta, Valentina R., Bjørk, Anders A., Blazquez, Alejandro, Bonin, Jennifer, Colgan, William, Csatho, Beata, Cullather, Richard, Engdahl, Marcus E., Felikson, Denis, Fettweis, Xavier, Forsberg, Rene, Hogg, Anna E., Gallee, Hubert, Gardner, Alex, Gilbert, Lin, Gourmelen, Noel, Groh, Andreas, Gunter, Brian, Hanna, Edward, Harig, Christopher, Helm, Veit, Horvath, Alexander, Horwath, Martin, Khan, Shfaqat, Kjeldsen, Kristian K., Konrad, Hannes, Langen, Peter L., Lecavalier, Benoit, Loomis, Bryant, Luthcke, Scott, McMillan, Malcolm, Melini, Daniele, Mernild, Sebastian, Mohajerani, Yara, Moore, Philip, Mottram, Ruth, Mouginot, Jeremie, Moyano, Gorka, Muir, Alan, Nagler, Thomas, Nield, Grace, Nilsson, Johan, Noël, Brice, Otosaka, Ines, Pattle, Mark E., Peltier, W. Richard, Pie, Nadège, Rietbroek, Roelof, Rott, Helmut, Sørensen, Louise Sandberg, Sasgen, Ingo, Save, Himanshu, Scheuchl, Bernd, Schrama, Ernst, Schröder, Ludwig, Seo, Ki-Weon, Simonsen, Sebastian B., Slater, Thomas, Spada, Giorgio, Sutterley, Tyler, Talpe, Matthieu, Tarasov, Lev, Jan van de Berg, Willem, van der Wal, Wouter, van Wessem, Melchior, Vishwakarma, Bramha Dutt, Wiese, David, Wilton, David, Wagner, Thomas, Wouters, Bert, Wuite, Jan, and Team, The IMBIE

Published
2020

13. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet

Author

Morlighem, Mathieu, Rignot, Eric, Binder, Tobias, Blankenship, Donald, Drews, Reinhard, Eagles, Graeme, Eisen, Olaf, Ferraccioli, Fausto, Forsberg, Rene, Fretwell, Peter, Goel, Vikram, Greenbaum, Jamin S., Gudmundsson, Hilmar, Guo, Jinxue, Helm, Veit, Hofstede, Coen, Howat, Ian, Humbert, Angelika, Jokat, Wilfried, Karlsson, Nanna B., Matsuoka, Kenichi, Millan, Romain, Mouginot, Jeremie, Paden, John, Pattyn, Frank, Roberts, Jason, Rosier, Sebastian, Ruppel, Antonia, Seroussi, Helene, Smith, Emma C., Steinhage, Daniel, Sun, Bo, Van den Broeke, Michiel R., Van Ommen, Tas D., Van Wessem, Melchior, Young, Duncan, Morlighem, Mathieu, Rignot, Eric, Binder, Tobias, Blankenship, Donald, Drews, Reinhard, Eagles, Graeme, Eisen, Olaf, Ferraccioli, Fausto, Forsberg, Rene, Fretwell, Peter, Goel, Vikram, Greenbaum, Jamin S., Gudmundsson, Hilmar, Guo, Jinxue, Helm, Veit, Hofstede, Coen, Howat, Ian, Humbert, Angelika, Jokat, Wilfried, Karlsson, Nanna B., Matsuoka, Kenichi, Millan, Romain, Mouginot, Jeremie, Paden, John, Pattyn, Frank, Roberts, Jason, Rosier, Sebastian, Ruppel, Antonia, Seroussi, Helene, Smith, Emma C., Steinhage, Daniel, Sun, Bo, Van den Broeke, Michiel R., Van Ommen, Tas D., Van Wessem, Melchior, and Young, Duncan

Abstract

The Antarctic ice sheet has been losing mass over past decades through the accelerated flow of its glaciers, conditioned by ocean temperature and bed topography. Glaciers retreating along retrograde slopes (that is, the bed elevation drops in the inland direction) are potentially unstable, while subglacial ridges slow down the glacial retreat. Despite major advances in the mapping of subglacial bed topography, significant sectors of Antarctica remain poorly resolved and critical spatial details are missing. Here we present a novel, high-resolution and physically based description of Antarctic bed topography using mass conservation. Our results reveal previously unknown basal features with major implications for glacier response to climate change. For example, glaciers flowing across the Transantarctic Mountains are protected by broad, stabilizing ridges. Conversely, in the marine basin of Wilkes Land, East Antarctica, we find retrograde slopes along Ninnis and Denman glaciers, with stabilizing slopes beneath Moscow University, Totten and Lambert glacier system, despite corrections in bed elevation of up to 1 km for the latter. This transformative description of bed topography redefines the high- and lower-risk sectors for rapid sea level rise from Antarctica; it will also significantly impact model projections of sea level rise from Antarctica in the coming centuries.

Published
2019

14. Four decades of Antarctic Ice Sheet mass balance from 1979-2017

Author

Sub Dynamics Meteorology, Marine and Atmospheric Research, Rignot, Eric, Mouginot, Jeremie, Scheuchl, Bernd, van den Broeke, Michiel, van Wessem, Melchior J., Morlighem, Mathieu, Sub Dynamics Meteorology, Marine and Atmospheric Research, Rignot, Eric, Mouginot, Jeremie, Scheuchl, Bernd, van den Broeke, Michiel, van Wessem, Melchior J., and Morlighem, Mathieu

Published
2019

15. Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet

Author

Morlighem, M., Rignot, Eric, Binder, Tobias, Blankenship, Donald, Drews, Reinhard, Eagles, Graeme, Eisen, Olaf, Ferraccioli, Fausto, Forsberg, René, Fretwell, Peter, Goel, Vikram, Greenbaum, Jamin Stevens, Gudmundsson, Hilmar, Guo, Jingxue, Helm, Veit, Hofstede, Coen, Howat, Ian, Humbert, A., Jokat, Wilfried, Karlsson, Nanna N.B., Lee, Won Sang, Matsuoka, Kenichi, Millan, Romain, Mouginot, Jeremie, Paden, John, Pattyn, Frank, Roberts, Jason J.L., Rosier, Sebastian, Ruppel, Antonia, Seroussi, Helene, Smith, Emma, Steinhage, Daniel, Sun, Bo, Broeke, Michiel Rvan Den M.R.v.d., Ommen, Tas Dvan T.D.v., Wessem, Melchior van, Young, Duncan D.A., Morlighem, M., Rignot, Eric, Binder, Tobias, Blankenship, Donald, Drews, Reinhard, Eagles, Graeme, Eisen, Olaf, Ferraccioli, Fausto, Forsberg, René, Fretwell, Peter, Goel, Vikram, Greenbaum, Jamin Stevens, Gudmundsson, Hilmar, Guo, Jingxue, Helm, Veit, Hofstede, Coen, Howat, Ian, Humbert, A., Jokat, Wilfried, Karlsson, Nanna N.B., Lee, Won Sang, Matsuoka, Kenichi, Millan, Romain, Mouginot, Jeremie, Paden, John, Pattyn, Frank, Roberts, Jason J.L., Rosier, Sebastian, Ruppel, Antonia, Seroussi, Helene, Smith, Emma, Steinhage, Daniel, Sun, Bo, Broeke, Michiel Rvan Den M.R.v.d., Ommen, Tas Dvan T.D.v., Wessem, Melchior van, and Young, Duncan D.A.

Abstract

The Antarctic ice sheet has been losing mass over past decades through the accelerated flow of its glaciers, conditioned by ocean temperature and bed topography. Glaciers retreating along retrograde slopes (that is, the bed elevation drops in the inland direction) are potentially unstable, while subglacial ridges slow down the glacial retreat. Despite major advances in the mapping of subglacial bed topography, significant sectors of Antarctica remain poorly resolved and critical spatial details are missing. Here we present a novel, high-resolution and physically based description of Antarctic bed topography using mass conservation. Our results reveal previously unknown basal features with major implications for glacier response to climate change. For example, glaciers flowing across the Transantarctic Mountains are protected by broad, stabilizing ridges. Conversely, in the marine basin of Wilkes Land, East Antarctica, we find retrograde slopes along Ninnis and Denman glaciers, with stabilizing slopes beneath Moscow University, Totten and Lambert glacier system, despite corrections in bed elevation of up to 1 km for the latter. This transformative description of bed topography redefines the high- and lower-risk sectors for rapid sea level rise from Antarctica; it will also significantly impact model projections of sea level rise from Antarctica in the coming centuries., SCOPUS: ar.j, info:eu-repo/semantics/published

Published
2019

16. Mass balance of the Antarctic Ice Sheet from 1992 to 2017

Author

Shepherd, Andrew, Ivins, Erik, Rignot, Eric, Smith, Ben, van den Broeke, Michiel, Velicogna, Isabella, Whitehouse, Pippa, Briggs, Kate, Joughin, Ian, Krinner, Gerhard, Nowicki, Sophie, Payne, Tony, Scambos, Ted, Schlegel, Nicole, Geruo, A., Agosta, Cecile, Ahlstrom, Andreas, Babonis, Greg, Barletta, Valentina, Blazquez, Alejandro, Bonin, Jennifer, Csatho, Beata, Cullather, Richard, Felikson, Denis, Fettweis, Xavier, Forsberg, Rene, Gallee, Hubert, Gardner, Alex, Gilbert, Lin, Groh, Andreas, Gunter, Brian, Hanna, Edward, Harig, Christopher, Helm, Veit, Horvath, Alexander, Horwath, Martin, Khan, Shfaqat, Kjeldsen, Kristian K., Konrad, Hannes, Langen, Peter, Lecavalier, Benoit, Loomis, Bryant, Luthcke, Scott, McMillan, Malcolm, Melini, Daniele, Noel, Brice, van de Berg, Willem Jan, van der Wal, Wouter, van Wessem, Melchior, Wouters, Bert, Marine and Atmospheric Research, and Sub Dynamics Meteorology

Subjects
Taverne
Abstract

The Antarctic Ice Sheet is an important indicator of climate change and driver of sea-level rise. Here we combine satellite observations of its changing volume, flow and gravitational attraction with modelling of its surface mass balance to show that it lost 2,720 ± 1,390 billion tonnes of ice between 1992 and 2017, which corresponds to an increase in mean sea level of 7.6 ± 3.9 millimetres (errors are one standard deviation). Over this period, ocean-driven melting has caused rates of ice loss from West Antarctica to increase from 53 ± 29 billion to 159 ± 26 billion tonnes per year; ice-shelf collapse has increased the rate of ice loss from the Antarctic Peninsula from 7 ± 13 billion to 33 ± 16 billion tonnes per year. We find large variations in and among model estimates of surface mass balance and glacial isostatic adjustment for East Antarctica, with its average rate of mass gain over the period 1992–2017 (5 ± 46 billion tonnes per year) being the least certain.

Published
2018

17. Mass balance of the Antarctic Ice Sheet from 1992 to 2017

Author

Marine and Atmospheric Research, Sub Dynamics Meteorology, Shepherd, Andrew, Ivins, Erik, Rignot, Eric, Smith, Ben, van den Broeke, Michiel, Velicogna, Isabella, Whitehouse, Pippa, Briggs, Kate, Joughin, Ian, Krinner, Gerhard, Nowicki, Sophie, Payne, Tony, Scambos, Ted, Schlegel, Nicole, Geruo, A., Agosta, Cecile, Ahlstrom, Andreas, Babonis, Greg, Barletta, Valentina, Blazquez, Alejandro, Bonin, Jennifer, Csatho, Beata, Cullather, Richard, Felikson, Denis, Fettweis, Xavier, Forsberg, Rene, Gallee, Hubert, Gardner, Alex, Gilbert, Lin, Groh, Andreas, Gunter, Brian, Hanna, Edward, Harig, Christopher, Helm, Veit, Horvath, Alexander, Horwath, Martin, Khan, Shfaqat, Kjeldsen, Kristian K., Konrad, Hannes, Langen, Peter, Lecavalier, Benoit, Loomis, Bryant, Luthcke, Scott, McMillan, Malcolm, Melini, Daniele, Noel, Brice, van de Berg, Willem Jan, van der Wal, Wouter, van Wessem, Melchior, Wouters, Bert, Marine and Atmospheric Research, Sub Dynamics Meteorology, Shepherd, Andrew, Ivins, Erik, Rignot, Eric, Smith, Ben, van den Broeke, Michiel, Velicogna, Isabella, Whitehouse, Pippa, Briggs, Kate, Joughin, Ian, Krinner, Gerhard, Nowicki, Sophie, Payne, Tony, Scambos, Ted, Schlegel, Nicole, Geruo, A., Agosta, Cecile, Ahlstrom, Andreas, Babonis, Greg, Barletta, Valentina, Blazquez, Alejandro, Bonin, Jennifer, Csatho, Beata, Cullather, Richard, Felikson, Denis, Fettweis, Xavier, Forsberg, Rene, Gallee, Hubert, Gardner, Alex, Gilbert, Lin, Groh, Andreas, Gunter, Brian, Hanna, Edward, Harig, Christopher, Helm, Veit, Horvath, Alexander, Horwath, Martin, Khan, Shfaqat, Kjeldsen, Kristian K., Konrad, Hannes, Langen, Peter, Lecavalier, Benoit, Loomis, Bryant, Luthcke, Scott, McMillan, Malcolm, Melini, Daniele, Noel, Brice, van de Berg, Willem Jan, van der Wal, Wouter, van Wessem, Melchior, and Wouters, Bert

Published
2018

18. Regional climate of the Larsen B embayment 1980-2014

Author

Leeson, Amber Alexandra, van Wessem, Melchior, Ligtenberg, Stefan, Shepherd, A., van den broeke, Michiel, Killick, Rebecca Claire, Skvarca, Pedro, Marinsek, Sebastien, Colwell, Steve, Leeson, Amber Alexandra, van Wessem, Melchior, Ligtenberg, Stefan, Shepherd, A., van den broeke, Michiel, Killick, Rebecca Claire, Skvarca, Pedro, Marinsek, Sebastien, and Colwell, Steve

Abstract

Understanding the climate response of the Antarctic Peninsula ice sheet is vital for accurate predictions of sea level rise. However, since climate models are typically too coarse to capture spatial variability in local scale meteorological processes, our ability to study specific sectors has been limited by the local fidelity of such models and the (often sparse) availability of observations. We show that a high-resolution (5.5 km x 5.5 km) version of a regional climate model (RACMO2.3) can reproduce observed inter-annual variability in the Larsen B embayment sufficiently to enable its use in investigating long-term changes in this sector. Using the model, together with AWS data, we confirm previous findings that the year of the Larsen B ice shelf collapse (2001/2002) was a strong melt year, but discover that total annual melt production was in fact ~30% lower than two years prior. While the year before collapse exhibited the lowest melting and highest snowfall during 1980-2014, the ice shelf was likely pre-conditioned for collapse by a series of strong melt years in the 1990s. Melt energy has since returned to pre-1990s levels, which likely explains the lack of further significant collapse in the region (e.g. of SCAR Inlet).

Published
2017

19. What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates

Author

Mottram, Ruth H., Hansen, Nicolay, Kittel, Christoph, van Wessem, Melchior, Agosta, Cécile, Amory, Charles, Boberg, F., van de Berg, Willem Jan, Fettweis, Xavier, Gossart, Alexandra, van Lipzig, NPM, van Meijgaard, E., Orr, Andrew, Phillips, Tony, Webster, Stuart, Simonsen, S.B., Souverijns, Niels, Sub Dynamics Meteorology, Marine and Atmospheric Research, Danish Meteorological Institute (DMI), Université de Liège, Utrecht University [Utrecht], Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Glaces et Continents, Climats et Isotopes Stables (GLACCIOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Royal Netherlands Meteorological Institute (KNMI), British Antarctic Survey (BAS), Natural Environment Research Council (NERC), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Danmarks Tekniske Universitet = Technical University of Denmark (DTU), This publication was supported by PROTECT. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 869304 and PROTECT contribution number 19.Acquisition of meteorological data in Adélie Land has been made with the financial and logistical support of the French Polar Institute IPEV (programme CALVA-1013). The authors appreciate the support of the University of Wisconsin-Madison Automatic Weather Station programme for the dataset, data display, and information (NSF grant no. 1924730).The COSMO-CLM2 integrations were supported by the Belgian Science Policy Office (BELSPO, grant no. 747 BR/143/A2/AEROCLOUD) and the Research Foundation Flanders (FWO, grant nos. 748 G0C2215N and GOF5318N, EOS ID: 30454083). Computational resources and services were provided by the Flemish Supercomputer Center, funded by the FWO and the Flemish Government, EWI department. Matthias Demuzere, Jan Lenaerts, Irina Gorodetskaya, and Sam Vanden Broucke are gratefully acknowledged for supporting the COSMO-CLM2 integrations. COSMO-CLM2 is the community model of the German regional climate research jointly further developed by the CLM community. Computational resources for MAR simulations have been provided by the Consortium des Équipements de Calcul Intensif (CÉCI), funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S. – FNRS) under grant no. 2.5020.11 and the Tier-1 supercomputer (Zenobe) of the Fédération Wallonie Bruxelles infrastructure funded by the Walloon Region under grant agreement no. 1117545. Christoph Kittel's work was supported by the Fonds de la Recherche Scientifique – FNRS under grant no. T.0002.16.Melchior van Wessen, Willem Jan van de Berg, and Erik van Meijgaard acknowledge the ECMWF for the use of their computing and archive facilities for the RACMO2 simulations.Ruth Mottram, Nicolaj Hansen, and Sebastian B. Simonsen acknowledge the ESA Climate Change Initiative for the Greenland ice sheet funded via ESA-ESRIN contract no. 4000104815/11/I-NB and the Sea Level Budget Closure CCI project funded via ESA-ESRIN contract no. 4000119910/17/I-NB. HIRHAM5 regional climate model simulations were carried out by Ruth Mottram and Fredrik Boberg as part of the ice2ice project, a European Research Council project under the European Community’s Seventh Framework Programme (FP7/ 2007–2013)/ ERC grant agreement 610055. Data analysis was supported by the Danish state through the National Centre for Climate Research (NCKF)., Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Technical University of Denmark [Lyngby] (DTU), Sub Dynamics Meteorology, and Marine and Atmospheric Research

Subjects
LAND, REPRESENTATION, Katabatic wind, 010504 meteorology & atmospheric sciences, IMPACT, 0207 environmental engineering, Antarctic ice sheet, 02 engineering and technology, 010502 geochemistry & geophysics, 01 natural sciences, Glacier mass balance, DRIFTING-SNOW, SDG 13 - Climate Action, GE1-350, Precipitation, [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology, Geosciences, Multidisciplinary, 020701 environmental engineering, ACCUMULATION, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, QE1-996.5, geography, Science & Technology, geography.geographical_feature_category, Geology, WIND, GREENLAND, Snow, SIMULATIONS, Iceberg, Environmental sciences, Geography, Physical, Physical Geography, RESOLUTION, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Physical Sciences, Environmental science, Climate model, Ice sheet, DIGITAL ELEVATION MODEL
Abstract

Antarctic ice sheet mass loss is currently equivalent to around 1 mm year−1 of global mean sea level rise. Most mass is lost due to sub-ice shelf melting and calving of icebergs. Ice sheet models of the Antarctic ice sheet have thus largely concentrated on parameterising sub-shelf and calving processes. However, surface mass balance (SMB) is also of crucial importance in controlling the stability and evolution of the vast Antarctic ice sheet. In this paper we compare the performance of five different regional climate models (COSMO-CLM2, HIRHAM5, MAR3.10, MetUM and RACMO2.3p2) in simulating the near surface climate and SMB of Antarctica. Our results show that, when regional climate models (RCMs) are forced by the ERA-Interim reanalysis, the integrated Antarctic ice sheet ensemble mean annual SMB is 2329 ± 94 Gigatonnes (Gt) year−1 over the common 1987 to 2015 period. However, individual model estimates vary from 1961 ± 70 to 2519 ± 118 Gt year−1. The large differences are mostly explained by different SMB estimates in West Antarctica and the peninsula as well as around the Transantarctic mountains. The calculated annual average SMB is very sensitive to the period chosen but over the climatological mean period of 1980 to 2010 the ensemble mean is 2486 Gt year−1. The interannual variability in SMB is consistent between the models and dominated by variability in the driving ERA-Interim reanalysis. The declining trend in Antarctic SMB reported in other studies is also very sensitive to period chosen and models disagree on the sign and magnitude of the trend in Antarctic SMB over the ERA-Interim period. Evaluation of models shows that they simulate Antarctic climate well when compared with daily observed temperature (Pearson correlation of 0.85 and higher) and pressure (bias ranges from −0.39 hPa in HIRHAM5 to −6.01 hPa in MAR with a mean of −3.49 hPa over all models) and nudged models, constrained within the domain as well as at lateral boundaries, perform better than un-nudged models. We compare modelled surface mass balance with a large dataset of observations which, though biased by undersampling in some regions, indicates that many of the biases in modelled SMB are common between models. The inclusion of drifting snow schemes improves modelled SMB on ice sheet slopes between 1000 and 2000 m where strong katabatic winds form but other regions where precipitation rates are high lack observations needed for the evaluation of different SMB estimates. Different ice masks have a substantial impact on the integrated total SMB and along with model resolution is therefore factored into our analysis. The majority of the different values for continental SMB are due to differences in modelled precipitation at relatively few grid points in coastal areas. Our analysis suggests that targeting coastal areas for observational campaigns will be key to improving and refining estimates of the total surface mass balance of Antarctica.

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