Search

Your search keyword '"Wouters, Bert"' showing total 12 results
Start Over Author "Wouters, Bert" Topic climate change
12 results on '"Wouters, Bert"'

3. Arctic glaciers record wavier circumpolar winds

Author

Sasgen, Ingo, Salles, Annette, Wegmann, Martin, Wouters, Bert, Fettweis, Xavier, Noël, Brice, and Beck, Christoph

Subjects
Cryospheric science, Atmospheric dynamics, glacier, 910 Geography & travel, Environmental Science (miscellaneous), Attribution, climate change, GRACE, SDG 13 - Climate Action, jetstream, Social Sciences (miscellaneous), ddc:910
Abstract

Glaciers in the Arctic respond sensitively to climate change, recording the polar amplification of global warming with increasing mass loss. Here, we use glacier mass balances in Svalbard and northern Arctic Canada to categorize tropospheric variability and the associated summer circulation over the Arctic. We establish a link between annual glacier mass balances and their respective atmospheric forcings since 1950 using GRACE/GRACE-FO satellite data (2002–2021), as well as regional climate models and reanalysis data (1950–2019). We find that asynchronous behaviour of mass balance between the regions has become very likely since the early 2000s, exceeding the range of previous decadal variability. Related tropospheric circulation exhibits more meridional patterns, a greater influence of meridional heat advection and a wavier summer circulation. The traceable impact on glacier mass balances emphasizes the importance of dynamic next to thermodynamic climate changes for the future of glacier mass loss, Arctic ecology and societal impacts.

Published
2022

5. 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

6. Global sea-level budget 1993–present

Author

Group, WCRP Global Sea Level Budget, Cazenave, Anny, Meyssignac, Benoit, Ablain, Michael, Balmaseda, Magdalena, Bamber, Jonathan, Barletta, Valentina Roberta, Beckley, Brian, Benveniste, Jérôme, Berthier, Etienne, Blazquez, Alejandro, Boyer , Tim, Caceres , Denise, Chambers, Don P., Champollion, Nicolas, Chao , Ben, Chen , Jianli, Cheng , Lijing, Church , John A., Chuter, Stephen, Cogley , J. Graham, Dangendorf , Soenke, Desbruyères , Damien, Döll , Petra, Domingues, Catia, Falk , Ulrike, Famiglietti , James, Fenoglio-Marc, Luciana, Forsberg, René, Galassi , Gaia, Gardner, Alex, Groh, Andreas, Hamlington , Benjamin, Hogg, Anna, Horwath, Martin, Humphrey , Vincent, Husson , Laurent, Ishii , Masayoshi, Jaeggi , Adrian, Jevrejeva , Svetlana, Johnson , Gregory, Kolodziejczyk , Nicolas, Kusche , Jürgen, Lambeck , Kurt, Landerer , Felix, Leclercq , Paul, Legresy , Benoit, Leuliette , Eric, Llovel, William, Longuevergne , Laurent, Loomis , Bryant D., Luthcke, Scott B, Marcos, Marta, Marzeion , Ben, Merchant , Chris, Merrifield , Mark, Milne, Glenn, Mitchum , Gary, Mohajerani, Yara, Monier , Maeva, Monselesan , Didier, Nerem , Steve, Palanisamy , Hindumathi, Paul, Frank, Pérez, Begona, Piecuch , Christopher G., Ponte , Rui M., Purkey , Sarah G., Reager , John T., Rietbroek , Roelof, Rignot, Eric, Riva, Riccardo, Roemmich , Dean H., Sørensen, Louise Sandberg, Sasgen, Ingo, Schram, E.J.O., Seneviratne , Sonia I., Shum, C.K., Spada, Giorgio, Stammer, Detlef, van de Wal , Roderic, Velicogna, Isabella, von Schuckmann, Karina, Wada, Yoshihide, Wang , Yiguo, Watson, Christopher S., Wiese, David, Wijffels , Susan, Westaway , Richard, Woppelmann, Guy, Wouters, Bert, Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), International Space Science Institute [Bern] (ISSI), Géosciences Rennes (GR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Collecte Localisation Satellites (CLS), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National d'Études Spatiales [Toulouse] (CNES), European Centre for Medium-Range Weather Forecasts (ECMWF), University of New South Wales [Sydney] (UNSW), Universität Siegen [Siegen], Institut Français de Recherche pour l'Exploitation de la Mer - Brest (IFREMER Centre de Bretagne), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), National Oceanographic Centre [Liverpool] (NOC ), Australian National University (ANU), CSIRO Marine and Atmosphere Research [Hobart], Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Institut Mediterrani d'Estudis Avancats (IMEDEA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Universidad de las Islas Baleares (UIB), University of Tasmania [Hobart, Australia] (UTAS), LIttoral ENvironnement et Sociétés - UMRi 7266 (LIENSs), Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS), Hubrecht Institute [Utrecht, Netherlands], University Medical Center [Utrecht]-Royal Netherlands Academy of Arts and Sciences (KNAW), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Cazenave, Anny, Meyssignac, Benoit, Ablain, Michael, Balmaseda, Magdalena, Bamber, Jonathan, Barletta, Valentina, Beckley, Brian, Benveniste, Jérôme, Berthier, Etienne, Blazquez, Alejandro, Boyer, Tim, Caceres, Denise, Chambers, Don, Champollion, Nicola, Chao, Ben, Chen, Jianli, Cheng, Lijing, Church, John A., Chuter, S., Cogley, J., Dangendorf, Soenke, Desbruyères, Damien, Döll, Petra, Domingues, Catia, Falk, Ulrike, Famiglietti, Jame, Fenoglio-Marc, Luciana, Forsberg, Rene, Galassi, Gaia, Gardner, Alex, Groh, Andrea, Hamlington, Benjamin, Hogg, Anna, Horwath, Martin, Humphrey, Vincent, Husson, Laurent, Ishii, Masayoshi, Jaeggi, Adrian, Jevrejeva, Svetlana, Johnson, Gregory, Kolodziejczyk, Nicola, Kusche, Jürgen, Lambeck, Kurt, Landerer, Felix, Leclercq, Paul, Legresy, Benoit, Leuliette, Eric, Llovel, William, Longuevergne, Laurent, Loomis, Bryant D., Luthcke, Scott B., Marcos, Marta, Marzeion, Ben, Merchant, Chri, Merrifield, Mark, Milne, Glenn, Mitchum, Gary, Mohajerani, Yara, Monier, Maeva, Monselesan, Didier, Nerem, Steve, Palanisamy, Hindumathi, Paul, Frank, Perez, Begoña, Piecuch, Christopher G., Ponte, Rui M., Purkey, Sarah G., Reager, John T., Rietbroek, Roelof, Rignot, Eric, Riva, Riccardo, Roemmich, Dean H., Sandberg Sørensen, Louise, Sasgen, Ingo, Schrama, E. J. O., Seneviratne, Sonia I., Shum, C. K., Spada, Giorgio, Stammer, Detlef, van de Wal, Roderic, Velicogna, Isabella, von Schuckmann, Karina, Wada, Yoshihide, Wang, Yiguo, Watson, Christopher, Wiese, David, Wijffels, Susan, Westaway, Richard, Woppelmann, Guy, and Wouters, Bert

Subjects
010504 meteorology & atmospheric sciences, Climate change, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Context (language use), sea level, 010502 geochemistry & geophysics, 01 natural sciences, Deep sea, SDG 13 - Climate Action, sea level, sea level change, gauge records, 14. Life underwater, Altimeter, Sea level, ComputingMilieux_MISCELLANEOUS, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, geography, geography.geographical_feature_category, 520 Astronomy, Global warming, lcsh:QE1-996.5, Glacier, lcsh:Geology, 13. Climate action, Climatology, gauge records, General Earth and Planetary Sciences, Environmental science, GlobalMass, Ice sheet, sea level change
Abstract

Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows changes (e.g., acceleration) to be detected in one or more components. Study of the sea-level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitledRegional Sea Level and Coastal Impacts, an international effort involving the sea-level community worldwide has been recently initiated with the objective of assessing the various datasets used to estimate components of the sea-level budget during the altimetry era (1993 to present). These datasets are based on the combination of a broad range of space-based and in situ observations, model estimates, and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about 50 research teams/institutions worldwide (www.wcrp-climate.org/grand-challenges/gc-sea-level, last access: 22 August 2018). The results presented in this paper are a synthesis of the first assessment performed during 2017–2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 ± 0.3 mm yr−1and acceleration of 0.1 mm yr−2over 1993–present), as well as of the different components of the sea-level budget (http://doi.org/10.17882/54854, last access: 22 August 2018). We further examine closure of the sea-level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute 42 %, 21 %, 15 % and 8 % to the global mean sea level over the 1993–present period. We also study the sea-level budget over 2005–present, using GRACE-based ocean mass estimates instead of the sum of individual mass components. Our results demonstrate that the global mean sea level can be closed to within 0.3 mm yr−1(1σ). Substantial uncertainty remains for the land water storage component, as shown when examining individual mass contributions to sea level.

Published
2018

7. Glacier surface temperatures in the Canadian High Arctic, 2000–15

Author

Mortimer, Colleen, Sharp, Martin, Wouters, Bert, Sub Dynamics Meteorology, Marine and Atmospheric Research, Sub Dynamics Meteorology, and Marine and Atmospheric Research

Subjects
geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Climate change, Glacier, 010502 geochemistry & geophysics, 01 natural sciences, Glacier mass balance, Arctic, 13. Climate action, Climatology, Air temperature, Moderate-resolution imaging spectroradiometer, Geology, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract

Canada'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.

Published
2016

8. Geodetic measurements reveal similarities between posttextendashLast Glacial Maximum and present-day mass loss from the Greenland ice sheet

Author

Khan, Shfaqat A., Sasgen, Ingo, Bevis, Michael, van Dam, Tonie, Bamber, Jonathan L., Wahr, John, Willis, Michael, Kjær, Kurt H., Wouters, Bert, Helm, Veit, Csatho, Beata, Fleming, Kevin, Bjørk, Anders A., Aschwanden, Andy, Knudsen, Per, Munneke, Peter Kuipers, Sub Dynamics Meteorology, Marine and Atmospheric Research, and 2.6 Seismic Hazard and Stress Field, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum

Subjects
010504 meteorology & atmospheric sciences, Meteorology, Greenland Ice Sheet, GPS, Climate change, Greenland ice sheet, Present day, 010502 geochemistry & geophysics, 01 natural sciences, Sea level rise, Deglaciation, SDG 13 - Climate Action, glacial isostatic adjustment, 14. Life underwater, SDG 14 - Life Below Water, Sea level, Research Articles, 0105 earth and related environmental sciences, Multidisciplinary, Last Glacial Maximum, Geodetic datum, SciAdv r-articles, Post-glacial rebound, climate change, 13. Climate action, Environmental Science, Physical geography, Geology, Research Article
Abstract

Present destabilization of marine-based sectors in Greenland may increase sea level for centuries to come., Accurate quantification of the millennial-scale mass balance of the Greenland ice sheet (GrIS) and its contribution to global sea-level rise remain challenging because of sparse in situ observations in key regions. Glacial isostatic adjustment (GIA) is the ongoing response of the solid Earth to ice and ocean load changes occurring since the Last Glacial Maximum (LGM; ~21 thousand years ago) and may be used to constrain the GrIS deglaciation history. We use data from the Greenland Global Positioning System network to directly measure GIA and estimate basin-wide mass changes since the LGM. Unpredicted, large GIA uplift rates of +12 mm/year are found in southeast Greenland. These rates are due to low upper mantle viscosity in the region, from when Greenland passed over the Iceland hot spot about 40 million years ago. This region of concentrated soft rheology has a profound influence on reconstructing the deglaciation history of Greenland. We reevaluate the evolution of the GrIS since LGM and obtain a loss of 1.5-m sea-level equivalent from the northwest and southeast. These same sectors are dominating modern mass loss. We suggest that the present destabilization of these marine-based sectors may increase sea level for centuries to come. Our new deglaciation history and GIA uplift estimates suggest that studies that use the Gravity Recovery and Climate Experiment satellite mission to infer present-day changes in the GrIS may have erroneously corrected for GIA and underestimated the mass loss by about 20 gigatons/year.

Published
2016

9. Seasonal mass variations show timing and magnitude of meltwater storage in the Greenland Ice Sheet.

Author

Ran, Jiangjun, Vizcaino, Miren, Ditmar, Pavel, van den Broeke, Michiel R., Moon, Twila, Steger, Christian R., Enderlin, Ellyn M., Wouters, Bert, Noël, Brice, Reijmer, Catharina H., Klees, Roland, Zhong, Min, Liu, Lin, and Fettweis, Xavier

Subjects
MELTWATER, CLIMATE change, MASS budget (Geophysics), WATER storage, MELTING, SEA level
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 glaciohydrological processes and their contributions to the ice sheet mass variability. [ABSTRACT FROM AUTHOR]

Published
2018
Full Text
View/download PDF

10. Modelling the climate and surface mass balance of polar ice sheets using RACMO2 - Part 2: Antarctica (1979-2016).

Author

van Wessem, Jan Melchior, van de Berg, Willem Jan, Noël, Brice P. Y., van Meijgaard, Erik, Amory, Charles, Birnbaum, Gerit, Jakobs, Constantijn L., Krüger, Konstantin, Lenaerts, Jan T. M., Lhermitte, Stef, Ligtenberg, Stefan R. M., Medley, Brooke, Reijmer, Carleen H., van Tricht, Kristof, Trusel, Luke D., van Ulft, Lambertus H., Wouters, Bert, Wuite, Jan, and van den Broeke, Michiel R.

Subjects
ICE sheets, SURFACE analysis, CLIMATE change, METEOROLOGICAL precipitation, ICE shelves
Abstract

We evaluate modelled Antarctic ice sheet (AIS) near-surface climate, surface mass balance (SMB) and surface energy balance (SEB) from the updated polar version of the regional atmospheric climate model, RACMO2 (1979-2016). The updated model, referred to as RACMO2.3p2, incorporates upper-air relaxation, a revised topography, tuned parameters in the cloud scheme to generate more precipitation towards the AIS interior and modified snow properties reducing drifting snow sublimation and increasing surface snowmelt. Comparisons of RACMO2 model output with several independent observational data show that the existing biases in AIS temperature, radiative fluxes and SMB components are further reduced with respect to the previous model version. The model-integrated annual average SMB for the ice sheet including ice shelves (minus the Antarctic Peninsula, AP) now amounts to 2229 Gt with an interannual variability of 109 Gt y-1. The largest improvement is found in modelled surface snowmelt, which now compares well with satellite and weather station observations. For the high-resolution (~5.5 km) AP simulation, results remain comparable to earlier studies. The updated model provides a new, high-resolution data set of the contemporary near-surface climate and SMB of the AIS; this model version will be used for future climate scenario projections in a forthcoming study. [ABSTRACT FROM AUTHOR]

Published
2018
Full Text
View/download PDF

11. A multi-model comparison of Atlantic multidecadal variability.

Author

Ba, Jin, Keenlyside, Noel, Latif, Mojib, Park, Wonsun, Ding, Hui, Lohmann, Katja, Mignot, Juliette, Menary, Matthew, Otterå, Odd, Wouters, Bert, Salas y Melia, David, Oka, Akira, Bellucci, Alessio, and Volodin, Evgeny

Subjects
GENERAL circulation model, OCEAN temperature, CLIMATE change, CLIMATOLOGY, COMPARATIVE studies
Abstract

A multi-model analysis of Atlantic multidecadal variability is performed with the following aims: to investigate the similarities to observations; to assess the strength and relative importance of the different elements of the mechanism proposed by Delworth et al. (J Clim 6:1993-2011, 1993) (hereafter D93) among coupled general circulation models (CGCMs); and to relate model differences to mean systematic error. The analysis is performed with long control simulations from ten CGCMs, with lengths ranging between 500 and 3600 years. In most models the variations of sea surface temperature (SST) averaged over North Atlantic show considerable power on multidecadal time scales, but with different periodicity. The SST variations are largest in the mid-latitude region, consistent with the short instrumental record. Despite large differences in model configurations, we find quite some consistency among the models in terms of processes. In eight of the ten models the mid-latitude SST variations are significantly correlated with fluctuations in the Atlantic meridional overturning circulation (AMOC), suggesting a link to northward heat transport changes. Consistent with this link, the three models with the weakest AMOC have the largest cold SST bias in the North Atlantic. There is no linear relationship on decadal timescales between AMOC and North Atlantic Oscillation in the models. Analysis of the key elements of the D93 mechanisms revealed the following: Most models present strong evidence that high-latitude winter mixing precede AMOC changes. However, the regions of wintertime convection differ among models. In most models salinity-induced density anomalies in the convective region tend to lead AMOC, while temperature-induced density anomalies lead AMOC only in one model. However, analysis shows that salinity may play an overly important role in most models, because of cold temperature biases in their relevant convective regions. In most models subpolar gyre variations tend to lead AMOC changes, and this relation is strong in more than half of the models. [ABSTRACT FROM AUTHOR]

Published
2014
Full Text
View/download PDF

12. Decadal prediction skill in a multi-model ensemble.

Author

Oldenborgh, Geert, Doblas-Reyes, Francisco, Wouters, Bert, and Hazeleger, Wilco

Subjects
ATMOSPHERIC models, PREDICTION theory, CLIMATE change, BOUNDARY value problems, GREENHOUSE gases, STRATOSPHERIC aerosols, TROPOSPHERIC aerosols, OCEAN-atmosphere interaction, OCEAN temperature, WEATHER forecasting
Abstract

Decadal climate predictions may have skill due to predictable components in boundary conditions (mainly greenhouse gas concentrations but also tropospheric and stratospheric aerosol distributions) and initial conditions (mainly the ocean state). We investigate the skill of temperature and precipitation hindcasts from a multi-model ensemble of four climate forecast systems based on coupled ocean-atmosphere models. Regional variations in skill with and without trend are compared with similarly analysed uninitialised experiments to separate the trend due to monotonically increasing forcings from fluctuations around the trend due to the ocean initial state and aerosol forcings. In temperature most of the skill in both multi-model ensembles comes from the externally forced trends. The rise of the global mean temperature is represented well in the initialised hindcasts, but variations around the trend show little skill beyond the first year due to the absence of volcanic aerosols in the hindcasts and the unpredictability of ENSO. The models have non-trivial skill in hindcasts of North Atlantic sea surface temperature beyond the trend. This skill is highest in the northern North Atlantic in initialised experiments and in the subtropical North Atlantic in uninitialised simulations. A similar result is found in the Pacific Ocean, although the signal is less clear. The uninitialised simulations have good skill beyond the trend in the western North Pacific. The initialised experiments show some skill in the decadal ENSO region in the eastern Pacific, in agreement with previous studies. However, the results in this study are not statistically significant ( p ≈ 0.1) by themselves. The initialised models also show some skill in forecasting 4-year mean Sahel rainfall at lead times of 1 and 5 years, in agreement with the observed teleconnection from the Atlantic Ocean. Again, the skill is not statistically significant ( p ≈ 0.2). Furthermore, uninitialised simulations that include volcanic aerosols have similar skill. It is therefore still an open question whether initialisation improves predictions of Sahel rainfall. We conclude that the main source of skill in forecasting temperature is the trend forced by rising greenhouse gas concentrations. The ocean initial state contributes to skill in some regions, but variations in boundary forcings such as aerosols are as important in decadal forecasting. [ABSTRACT FROM AUTHOR]

Published
2012
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results