Articles | Volume 17, issue 9
https://doi.org/10.5194/tc-17-3803-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-3803-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Exploring the ability of the variable-resolution Community Earth System Model to simulate cryospheric–hydrological variables in High Mountain Asia
René R. Wijngaard
CORRESPONDING AUTHOR
Irreversible Climate Change Research Center, Yonsei University, Seoul, South Korea
now at: Institute for Marine and Atmospheric Research Utrecht,
Utrecht University, Utrecht, the Netherlands
Adam R. Herrington
Climate and Global Dynamics Laboratory, National Center for
Atmospheric Research, Boulder, CO, USA
William H. Lipscomb
Climate and Global Dynamics Laboratory, National Center for
Atmospheric Research, Boulder, CO, USA
Gunter R. Leguy
Climate and Global Dynamics Laboratory, National Center for
Atmospheric Research, Boulder, CO, USA
Irreversible Climate Change Research Center, Yonsei University, Seoul, South Korea
Climate Theory Lab, Department of Atmospheric Sciences, Yonsei
University, Seoul, South Korea
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We used the variable-resolution CESM to simulate present-day and future temperature and precipitation extremes in the Arctic by applying global grids (~111 km) with and without regional refinement (~28 km) and following a storyline approach. We found that global grids with (without) regional refinement generally perform better in simulating present-day precipitation (temperature) extremes, and that future high (low) temperature and wet precipitation extremes are projected to increase (decrease).
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The Antarctic Ice Sheet is currently thinning, especially at major outlet glaciers. Including present-day thinning rates in models is a modeller's choice and can affect future projections. This study quantifies the impact of current imbalance on forced future projections, revealing strong regional and short-term (up to 2100) effects when these mass change rates are included.
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Zhi-Bo Li, Chao Liu, Cesar Azorin-Molina, Soon-Il An, Yang Zhao, Yang Xu, Jongsoo Shin, Deliang Chen, and Cheng Shen
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Our research explores how European wind speeds respond to the removal of carbon dioxide from the atmosphere, focusing on their importance for wind energy. Using advanced climate models, we discovered that wind speeds react differently during periods of increased and decreased carbon dioxide levels. This study not only advances our understanding of climate dynamics but also aids in optimizing strategies for wind energy, crucial for future planning and policy-making in response to climate change.
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Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Willem Jan van de Berg, and Roderik S. W. van de Wal
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Ice sheet models to simulate future sea level rise require parameterizations, like for the friction at the bedrock. Studies have quantified the effect of using different parameterizations, and some have concluded that projections are sensitive to the choice of the specific parameterization. In this study, we show that you can make an ice sheet model sensitive to the basal friction parameterization, and that for equally defendable modellers choices you can also make the model insensitive to this.
William H. Lipscomb, David Behar, and Monica Ainhorn Morrison
The Cryosphere, 19, 793–803, https://doi.org/10.5194/tc-19-793-2025, https://doi.org/10.5194/tc-19-793-2025, 2025
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As communities try to adapt to climate change, they look for "actionable science" that can inform decision-making. There are risks in relying on novel results that are not yet accepted by the science community. We propose a practical criterion for determining which scientific claims are actionable. We show how premature acceptance of sea-level-rise predictions can lead to confusion and backtracking, and we suggest best practices for communication between scientists and adaptation planners.
Samar Minallah, William Lipscomb, Gunter Leguy, and Harry Zekollari
EGUsphere, https://doi.org/10.5194/egusphere-2024-4152, https://doi.org/10.5194/egusphere-2024-4152, 2025
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We implemented a new modeling framework within an Earth system model to study the evolution of mountain glaciers under different climate scenarios and applied it to the European Alps. Alpine glaciers will lose a large volume fraction under current temperatures, with near complete ice loss under warmer scenarios. This is the first use of a 3D, higher-order ice flow model for regional-scale glacier simulations that will enable assessments of coupled land ice and Earth system processes.
Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Jorjo Bernales, Constantijn J. Berends, Willem Jan van de Berg, and Roderik S. W. van de Wal
The Cryosphere, 19, 283–301, https://doi.org/10.5194/tc-19-283-2025, https://doi.org/10.5194/tc-19-283-2025, 2025
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In this study, we present an improved way of representing ice thickness change rates in an ice sheet model. We apply this method using two ice sheet models of the Antarctic Ice Sheet. We found that the two largest outlet glaciers on the Antarctic Ice Sheet, Thwaites Glacier and Pine Island Glacier, will collapse without further warming on a timescale of centuries. This would cause a sea level rise of about 1.2 m globally.
Michele Petrini, Meike D. W. Scherrenberg, Laura Muntjewerf, Miren Vizcaino, Raymond Sellevold, Gunter R. Leguy, William H. Lipscomb, and Heiko Goelzer
The Cryosphere, 19, 63–81, https://doi.org/10.5194/tc-19-63-2025, https://doi.org/10.5194/tc-19-63-2025, 2025
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Anthropogenic warming is causing accelerated Greenland ice sheet melt. Here, we use a computer model to understand how prolonged warming and ice melt could threaten ice sheet stability. We find a threshold beyond which Greenland will lose more than 80 % of its ice over several thousand years, due to the interaction of surface and solid-Earth processes. Nearly complete Greenland ice sheet melt occurs when the ice margin disconnects from a region of high elevation in western Greenland.
Heiko Goelzer, Petra M. Langebroek, Andreas Born, Stefan Hofer, Konstanze Haubner, Michele Petrini, Gunter Leguy, William H. Lipscomb, and Katherine Thayer-Calder
EGUsphere, https://doi.org/10.5194/egusphere-2024-3045, https://doi.org/10.5194/egusphere-2024-3045, 2025
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On the backdrop of observed accelerating ice sheet mass loss over the last few decades, there is growing interest in the role of ice sheet changes in global climate projections. In this regard, we have coupled an Earth system model with an ice sheet model and have produced an initial set of climate projections including an interactive coupling with a dynamic Greenland ice sheet.
Mira Berdahl, Gunter R. Leguy, William H. Lipscomb, Bette L. Otto-Bliesner, Esther C. Brady, Robert A. Tomas, Nathan M. Urban, Ian Miller, Harriet Morgan, and Eric J. Steig
Clim. Past, 20, 2349–2371, https://doi.org/10.5194/cp-20-2349-2024, https://doi.org/10.5194/cp-20-2349-2024, 2024
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Studying climate conditions near the Antarctic ice sheet (AIS) during Earth’s past warm periods informs us about how global warming may influence AIS ice loss. Using a global climate model, we investigate climate conditions near the AIS during the Last Interglacial (129 to 116 kyr ago), a period with warmer global temperatures and higher sea level than today. We identify the orbital and freshwater forcings that could cause ice loss and probe the mechanisms that lead to warmer climate conditions.
Annelise Waling, Adam Herrington, Katharine Duderstadt, Jack Dibb, and Elizabeth Burakowski
Weather Clim. Dynam., 5, 1117–1135, https://doi.org/10.5194/wcd-5-1117-2024, https://doi.org/10.5194/wcd-5-1117-2024, 2024
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Atmospheric rivers (ARs) are channel-shaped features within the atmosphere that carry moisture from the mid-latitudes to the poles, bringing warm temperatures and moisture that can cause melt in the Arctic. We used variable-resolution grids to model ARs around the Greenland ice sheet and compared this output to uniform-resolution grids and reanalysis products. We found that the variable-resolution grids produced ARs and precipitation that were more similar to observation-based products.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Xavier J. Levine, Ryan S. Williams, Gareth Marshall, Andrew Orr, Lise Seland Graff, Dörthe Handorf, Alexey Karpechko, Raphael Köhler, René R. Wijngaard, Nadine Johnston, Hanna Lee, Lars Nieradzik, and Priscilla A. Mooney
Earth Syst. Dynam., 15, 1161–1177, https://doi.org/10.5194/esd-15-1161-2024, https://doi.org/10.5194/esd-15-1161-2024, 2024
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While the most recent climate projections agree that the Arctic is warming, differences remain in how much and in other climate variables such as precipitation. This presents a challenge for stakeholders who need to develop mitigation and adaptation strategies. We tackle this problem by using the storyline approach to generate four plausible and actionable realisations of end-of-century climate change for the Arctic, spanning its most likely range of variability.
Tong Zhang, William Colgan, Agnes Wansing, Anja Løkkegaard, Gunter Leguy, William H. Lipscomb, and Cunde Xiao
The Cryosphere, 18, 387–402, https://doi.org/10.5194/tc-18-387-2024, https://doi.org/10.5194/tc-18-387-2024, 2024
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The geothermal heat flux determines how much heat enters from beneath the ice sheet, and thus impacts the temperature and the flow of the ice sheet. In this study we investigate how much geothermal heat flux impacts the initialization of the Greenland ice sheet. We use the Community Ice Sheet Model with two different initialization methods. We find a non-trivial influence of the choice of heat flow boundary conditions on the ice sheet initializations for further designs of ice sheet modeling.
Hélène Seroussi, Vincent Verjans, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Peter Van Katwyk, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 17, 5197–5217, https://doi.org/10.5194/tc-17-5197-2023, https://doi.org/10.5194/tc-17-5197-2023, 2023
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Mass loss from Antarctica is a key contributor to sea level rise over the 21st century, and the associated uncertainty dominates sea level projections. We highlight here the Antarctic glaciers showing the largest changes and quantify the main sources of uncertainty in their future evolution using an ensemble of ice flow models. We show that on top of Pine Island and Thwaites glaciers, Totten and Moscow University glaciers show rapid changes and a strong sensitivity to warmer ocean conditions.
Rajashree Tri Datta, Adam Herrington, Jan T. M. Lenaerts, David P. Schneider, Luke Trusel, Ziqi Yin, and Devon Dunmire
The Cryosphere, 17, 3847–3866, https://doi.org/10.5194/tc-17-3847-2023, https://doi.org/10.5194/tc-17-3847-2023, 2023
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Precipitation over Antarctica is one of the greatest sources of uncertainty in sea level rise estimates. Earth system models (ESMs) are a valuable tool for these estimates but typically run at coarse spatial resolutions. Here, we present an evaluation of the variable-resolution CESM2 (VR-CESM2) for the first time with a grid designed for enhanced spatial resolution over Antarctica to achieve the high resolution of regional climate models while preserving the two-way interactions of ESMs.
Constantijn J. Berends, Roderik S. W. van de Wal, Tim van den Akker, and William H. Lipscomb
The Cryosphere, 17, 1585–1600, https://doi.org/10.5194/tc-17-1585-2023, https://doi.org/10.5194/tc-17-1585-2023, 2023
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The rate at which the Antarctic ice sheet will melt because of anthropogenic climate change is uncertain. Part of this uncertainty stems from processes occurring beneath the ice, such as the way the ice slides over the underlying bedrock.
Inversion methodsattempt to use observations of the ice-sheet surface to calculate how these sliding processes work. We show that such methods cannot fully solve this problem, so a substantial uncertainty still remains in projections of sea-level rise.
Mira Berdahl, Gunter Leguy, William H. Lipscomb, Nathan M. Urban, and Matthew J. Hoffman
The Cryosphere, 17, 1513–1543, https://doi.org/10.5194/tc-17-1513-2023, https://doi.org/10.5194/tc-17-1513-2023, 2023
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Contributions to future sea level from the Antarctic Ice Sheet remain poorly constrained. One reason is that ice sheet model initialization methods can have significant impacts on how the ice sheet responds to future forcings. We investigate the impacts of two key parameters used during model initialization. We find that these parameter choices alone can impact multi-century sea level rise by up to 2 m, emphasizing the need to carefully consider these choices for sea level rise predictions.
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
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We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, https://doi.org/10.5194/gmd-15-3721-2022, 2022
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We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
Seungmok Paik, Seung-Ki Min, Seok-Woo Son, Soon-Il An, Jong-Seong Kug, and Sang-Wook Yeh
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-187, https://doi.org/10.5194/acp-2022-187, 2022
Revised manuscript not accepted
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This paper investigates Earth’s surface climate response to volcanic eruptions at different latitudes. By analyzing last millennium ensemble simulations of a coupled climate model, we have identified physical processes associated with the diverse impacts of volcanic eruption latitudes, focusing on the tropical ocean surface warming and the stratospheric polar vortex intensification. Our results provide important global implications for atmospheric responses to future volcanic aerosols.
Alexander Robinson, Daniel Goldberg, and William H. Lipscomb
The Cryosphere, 16, 689–709, https://doi.org/10.5194/tc-16-689-2022, https://doi.org/10.5194/tc-16-689-2022, 2022
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Here we investigate the numerical stability of several commonly used methods in order to determine which of them are capable of resolving the complex physics of the ice flow and are also computationally efficient. We find that the so-called DIVA solver outperforms the others. Its representation of the physics is consistent with more complex methods, while it remains computationally efficient at high resolution.
Gunter R. Leguy, William H. Lipscomb, and Xylar S. Asay-Davis
The Cryosphere, 15, 3229–3253, https://doi.org/10.5194/tc-15-3229-2021, https://doi.org/10.5194/tc-15-3229-2021, 2021
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We present numerical features of the Community Ice Sheet Model in representing ocean termini glaciers. Using idealized test cases, we show that applying melt in a partly grounded cell is beneficial, in contrast to recent studies. We confirm that parameterizing partly grounded cells yields accurate ice sheet representation at a grid resolution of ~2 km (arguably 4 km), allowing ice sheet simulations at a continental scale. The choice of basal friction law also influences the ice flow.
Mira Berdahl, Gunter Leguy, William H. Lipscomb, and Nathan M. Urban
The Cryosphere, 15, 2683–2699, https://doi.org/10.5194/tc-15-2683-2021, https://doi.org/10.5194/tc-15-2683-2021, 2021
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Antarctic ice shelves are vulnerable to warming ocean temperatures and have already begun thinning in response to increased basal melt rates. Sea level is expected to rise due to Antarctic contributions, but uncertainties in rise amount and timing remain largely unquantified. To facilitate uncertainty quantification, we use a high-resolution ice sheet model to build, test, and validate an ice sheet emulator and generate probabilistic sea level rise estimates for 100 and 200 years in the future.
William H. Lipscomb, Gunter R. Leguy, Nicolas C. Jourdain, Xylar Asay-Davis, Hélène Seroussi, and Sophie Nowicki
The Cryosphere, 15, 633–661, https://doi.org/10.5194/tc-15-633-2021, https://doi.org/10.5194/tc-15-633-2021, 2021
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This paper describes Antarctic climate change experiments in which the Community Ice Sheet Model is forced with ocean warming predicted by global climate models. Generally, ice loss begins slowly, accelerates by 2100, and then continues unabated, with widespread retreat of the West Antarctic Ice Sheet. The mass loss by 2500 varies from about 150 to 1300 mm of equivalent sea level rise, based on the predicted ocean warming and assumptions about how this warming drives melting beneath ice shelves.
Josephine R. Brown, Chris M. Brierley, Soon-Il An, Maria-Vittoria Guarino, Samantha Stevenson, Charles J. R. Williams, Qiong Zhang, Anni Zhao, Ayako Abe-Ouchi, Pascale Braconnot, Esther C. Brady, Deepak Chandan, Roberta D'Agostino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, Ryouta O'ishi, Bette L. Otto-Bliesner, W. Richard Peltier, Xiaoxu Shi, Louise Sime, Evgeny M. Volodin, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, https://doi.org/10.5194/cp-16-1777-2020, 2020
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El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the current climate, but the response of ENSO to past or future changes in climate is uncertain. This study compares the strength and spatial pattern of ENSO in a set of climate model simulations in order to explore how ENSO changes in different climates, including past cold glacial climates and past climates with different seasonal cycles, as well as gradual and abrupt future warming cases.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
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In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Hélène Seroussi, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 14, 3033–3070, https://doi.org/10.5194/tc-14-3033-2020, https://doi.org/10.5194/tc-14-3033-2020, 2020
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The Antarctic ice sheet has been losing mass over at least the past 3 decades in response to changes in atmospheric and oceanic conditions. This study presents an ensemble of model simulations of the Antarctic evolution over the 2015–2100 period based on various ice sheet models, climate forcings and emission scenarios. Results suggest that the West Antarctic ice sheet will continue losing a large amount of ice, while the East Antarctic ice sheet could experience increased snow accumulation.
Cited articles
Bambach, N. E., Rhoades, A. M., Hatchett, B. J., Jones, A. D., Ullrich, P.
A., and Zarzycki, C. M.: Projecting climate change in South America using
variable-resolution Community Earth System Model: An application to Chile,
Int. J. Climatol., 42, 2514–2542,
https://doi.org/10.1002/joc.7379,
2021.
Beljaars, A. C. M., Brown, A. R., and Wood, N.: A new parametrization of
turbulent orographic form drag, Q. J. Roy.
Meteor. Soc., 130, 1327–1347, https://doi.org/10.1256/qj.03.73, 2004.
Bogenschutz, P. A., Gettelman, A., Morrison, H., Larson, V. E., Craig, C.,
and Schanen, D. P.: Higher-order turbulence closure and its impact on
climate simulations in the community atmosphere model, J. Climate, 26, 9655–9676,
https://doi.org/10.1175/JCLI-D-13-00075.1, 2013.
Bonekamp, P. N. J., de Kok, R. J., Collier, E., and Immerzeel, W. W.:
Contrasting Meteorological Drivers of the Glacier Mass Balance Between the
Karakoram and Central Himalaya, Front. Earth Sci., 7, 107,
https://doi.org/10.3389/feart.2019.00107, 2019.
Brodzik, M. J. and Armstrong, R.: Northern Hemisphere EASE-Grid 2.0 Weekly
Snow Cover and Sea Ice Extent, Version 4, Boulder, Colorado USA, NASA DAAC
at the National Snow and Ice Data Center [data set],
https://doi.org/10.5067/P7O0HGJLYUQU, 2013.
Brun, F., Berthier, E., Wagnon, P., Kääb, A., and Treichler, D.: A
spatially resolved estimate of High Mountain Asia glacier mass balances from
2000 to 2016, Nat. Geosci., 10, 668–673, https://doi.org/10.1038/ngeo2999,
2017.
Cannon, F., Carvalho, L. M. V., Jones, C., and Bookhagen, B.: Multi-annual
variations in winter westerly disturbance activity affecting the Himalaya,
Clim. Dynam., 44, 441–455, https://doi.org/10.1007/s00382-014-2248-8, 2015.
Collier, E., Mölg, T., Maussion, F., Scherer, D., Mayer, C., and Bush, A. B. G.: High-resolution interactive modelling of the mountain glacier–atmosphere interface: an application over the Karakoram, The Cryosphere, 7, 779–795, https://doi.org/10.5194/tc-7-779-2013, 2013.
Computational and Information Systems Laboratory: Cheyenne supercomputer, https://doi.org/10.5065/D6RX99HX, 2019.
Danabasoglu, G., Lamarque, J. F., Bacmeister, J., Bailey, D. A., DuVivier,
A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A.,
Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M.,
Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R.,
Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S.,
van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C.,
Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J.,
Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E.,
Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System
Model Version 2 (CESM2), J. Adv. Model Earth. Sy., 12, e2019MS001916,
https://doi.org/10.1029/2019MS001916, 2020.
Danielson, J. J. and Gesch, D. B.: Global Multi-resolution Terrain Elevation
Data 2010 (GMTED2010), U.S. Geological Survey Open-File Report 2011-1073,
2011.
de Kok, R. J., Kraaijenbrink, P. D. A., Tuinenburg, O. A., Bonekamp, P. N. J., and Immerzeel, W. W.: Towards understanding the pattern of glacier mass balances in High Mountain Asia using regional climatic modelling, The Cryosphere, 14, 3215–3234, https://doi.org/10.5194/tc-14-3215-2020, 2020.
Dirmeyer, P. A., Gao, X., Zhao, M., Guo, Z., Oki, T., and Hanasaki, N.:
GSWP-2: Multimodel analysis and implications for our perception of the land
surface, B. Am. Meteorol. Soc., 87, 1381–1398, https://doi.org/10.1175/BAMS-87-10-1381,
2006.
Dudhia, J.: A nonhydrostatic version of the Penn State-NCAR mesoscale model:
validation tests and simulation of an Atlantic cyclone and cold front, Mon.
Weather Rev., 121, 1493–1513, https://doi.org/10.1175/1520-0493(1993)121<1493:ANVOTP>2.0.CO;2, 1993.
Dudhia, J.: A history of mesoscale model development, Asia Pac. J. Atmos. Sci.,
50, 121–131, https://doi.org/10.1007/s13143-014-0031-8, 2014.
Flanner, M. G. and Zender, C. S.: Snowpack radiative heating: Influence on
Tibetan Plateau climate, Geophys. Res. Lett., 32, L06501,
https://doi.org/10.1029/2004GL022076, 2005.
Flanner, M. G., Zender, C. S., Randerson, J. T., and Rasch, P. J.:
Present-day climate forcing and response from black carbon in snow, J.
Geophys. Res.-Atmos., 112, D11202,
https://doi.org/10.1029/2006JD008003, 2007.
Frey, H., Haeberli, W., Linsbauer, A., Huggel, C., and Paul, F.: A multi-level strategy for anticipating future glacier lake formation and associated hazard potentials, Nat. Hazards Earth Syst. Sci., 10, 339–352, https://doi.org/10.5194/nhess-10-339-2010, 2010.
Gates, W. L., Boyle, J. S., Covey, C., Dease, C. G., Doutriaux, C. M.,
Drach, R. S., Fiorino, M., Gleckler, P. J., Hnilo, J. J., Marlais, S. M.,
Phillips, T. J., Potter, G. L., Santer, B. D., Sperber, K. R., Taylor, K.
E., and Williams, D. N.: An Overview of the Results of the Atmospheric Model
Intercomparison Project (AMIP I), B. Am. Meteorol. Soc., 80, 29–55,
https://doi.org/10.1175/1520-0477(1999)080<0029:AOOTRO>2.0.CO;2, 1999.
Gettelman, A. and Morrison, H.: Advanced two-moment bulk microphysics for
global models. Part I: Off-line tests and comparison with other schemes, J.
Climate, 28, 1268–1287, https://doi.org/10.1175/JCLI-D-14-00102.1, 2015.
Gettelman, A., Callaghan, P., Larson, V. E., Zarzycki, C. M., Bacmeister, J.
T., Lauritzen, P. H., Bogenschutz, P. A., and Neale, R. B.: Regional Climate
Simulations With the Community Earth System Model, J. Adv. Model Earth Sy.,
46, 8329–8337, https://doi.org/10.1002/2017MS001227, 2018.
Gettelman, A., Hannay, C., Bacmeister, J. T., Neale, R. B., Pendergrass, A.
G., Danabasoglu, G., Lamarque, J. F., Fasullo, J. T., Bailey, D. A.,
Lawrence, D. M., and Mills, M. J.: High Climate Sensitivity in the Community
Earth System Model Version 2 (CESM2), Geophys. Res. Lett., 46,
https://doi.org/10.1029/2019GL083978, 2019a.
Gettelman, A., Morrison, H., Thayer-Calder, K., and Zarzycki, C. M.: The
Impact of Rimed Ice Hydrometeors on Global and Regional Climate, J. Adv. Model
Earth Sy., 11, 1543–1562, https://doi.org/10.1029/2018MS001488, 2019b.
Gu, H., Wang, G., Yu, Z., and Mei, R.: Assessing future climate changes and
extreme indicators in east and south Asia using the RegCM4 regional climate
model, Climatic Change, 114, 301–317, https://doi.org/10.1007/s10584-012-0411-y, 2012.
Guba, O., Taylor, M. A., Ullrich, P. A., Overfelt, J. R., and Levy, M. N.: The spectral element method (SEM) on variable-resolution grids: evaluating grid sensitivity and resolution-aware numerical viscosity, Geosci. Model Dev., 7, 2803–2816, https://doi.org/10.5194/gmd-7-2803-2014, 2014.
Herreid, S. and Pellicciotti, F.: The state of rock debris covering Earth's
glaciers, Nat. Geosci., 13, 621–627, https://doi.org/10.1038/s41561-020-0615-0, 2020.
Herrington, A. R. and Reed, K. A.: On resolution sensitivity in the
Community Atmosphere Model, Q. J. Roy. Meteor.
Soc., 146, 3789–3807, https://doi.org/10.1002/qj.3873, 2020.
Herrington, A. R., Lauritzen, P. H., Lofverstrom, M., Lipscomb, W. H.,
Gettelman, A., and Taylor, M. A.: Impact of grids and dynamical cores in
CESM2.2 on the surface mass balance of the Greenland Ice Sheet, J. Adv. Model
Earth Sy., 14, e2022MS003192, https://doi.org/10.1029/2022MS003192, 2022.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5
global reanalysis, Q. J. Roy. Meteor. Soc.,
146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hock, R., Rasul, G., Adler, C., Cáceres, B., Gruber, S., Hirabayashi,
Y., Jackson, M., Kääb, A., Kang, S., Kutuzov, S., Milner, A., Molau,
U., Morin, S., Orlove, B., and Steltzer, H. I.: High Mountain Areas, in:
IPCC Special Report on the Ocean and Cryosphere in a Changing Climate,
edited by: Pörtner, H.-O., Roberts, D. C.,
Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K.,
Alegriìa, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N.
M., IPCC Intergovernmental Panel on Climate Change, Geneva, Switzerland, Cambridge University Press, Cambridge, UK and New York, NY, USA, 131–202, https://doi.org/10.1017/9781009157964.004,
2019.
Huang, X., Rhoades, A. M., Ullrich, P. A., and Zarzycki, C. M.: An
evaluation of the variable-resolution CESM for modeling California's
climate, J. Adv. Model Earth Sy., 8, 345–369,
https://doi.org/10.1002/2015MS000559, 2016.
Huang, X., Gettelman, A., Skamarock, W. C., Lauritzen, P. H., Curry, M., Herrington, A., Truesdale, J. T., and Duda, M.: Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States, Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, 2022.
Hurrell, J. W., Hack, J. J., Shea, D., Caron, J. M., and Rosinski, J.: A new
sea surface temperature and sea ice boundary dataset for the community
atmosphere model, J. Climate, 21, 5145–5153, https://doi.org/10.1175/2008JCLI2292.1, 2008.
Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Klein Goldewijk, K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenöder, F., Jungclaus, J., Kaplan, J. O., Kennedy, J., Krisztin, T., Lawrence, D., Lawrence, P., Ma, L., Mertz, O., Pongratz, J., Popp, A., Poulter, B., Riahi, K., Shevliakova, E., Stehfest, E., Thornton, P., Tubiello, F. N., van Vuuren, D. P., and Zhang, X.: Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6, Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, 2020.
Immerzeel, W. W., Wanders, N., Lutz, A. F., Shea, J. M., and Bierkens, M. F. P.: Reconciling high-altitude precipitation in the upper Indus basin with glacier mass balances and runoff, Hydrol. Earth Syst. Sci., 19, 4673–4687, https://doi.org/10.5194/hess-19-4673-2015, 2015.
Immerzeel, W. W., Lutz, A. F., Andrade, M., Bahl, A., Biemans, H., Bolch,
T., Hyde, S., Brumby, S., Davies, B. J., Elmore, A. C., Emmer, A., Feng, M.,
Fernández, A., Haritashya, U., Kargel, J. S., Koppes, M., Kraaijenbrink,
P. D. A., Kulkarni, A. v., Mayewski, P. A., Nepal, S., Pacheco, P., Painter,
T. H., Pellicciotti, F., Rajaram, H., Rupper, S., Sinisalo, A., Shrestha, A.
B., Viviroli, D., Wada, Y., Xiao, C., Yao, T., and Baillie, J. E. M.:
Importance and vulnerability of the world's water towers, Nature, 577, 364–369,
https://doi.org/10.1038/s41586-019-1822-y, 2020.
Jang, J. and Hong, S. Y.: Comparison of simulated precipitation over East
Asia in two regional models with hydrostatic and nonhydrostatic dynamical
cores, Mon. Weather Rev., 144, 3579–3590, https://doi.org/10.1175/MWR-D-15-0428.1, 2016.
Janjic, Z. I., Gerrity, J., and Nickovic, S.: An alternative approach to
nonhydrostatic modeling, Mon. Weather Rev., 129, 1164–1178,
https://doi.org/10.1175/1520-0493(2001)129<1164:AAATNM>2.0.CO;2, 2001.
Jeevanjee, N.: Vertical Velocity in the Gray Zone, J. Adv. Model Earth Sy.,
9, 2304–2316, https://doi.org/10.1002/2017MS001059, 2017.
Jennings, K. S., Winchell, T. S., Livneh, B., and Molotch, N. P.: Spatial
variation of the rain-snow temperature threshold across the Northern
Hemisphere, Nat. Commun., 9, 1148, https://doi.org/10.1038/s41467-018-03629-7, 2018.
Jiang, X., Wu, C., Chen, B., Wang, W., Liu, X., Lin, Z., and Han, Z.:
Exploring a variable-resolution approach for simulating the regional climate
in Southwest China using VR-CESM, Atmos. Res., 292, 106851,
https://doi.org/10.1016/j.atmosres.2023.106851, 2023.
Kato, S., Rose, F. G., Rutan, D. A., Thorsen, T. J., Loeb, N. G., Doelling,
D. R., Huang, X., Smith, W. L., Su, W., and Ham, S. H.: Surface irradiances
of edition 4.0 Clouds and the Earth's Radiant Energy System (CERES) Energy
Balanced and Filled (EBAF) data product, J. Climate, 31, 4501–4527,
https://doi.org/10.1175/JCLI-D-17-0523.1, 2018.
Kato, T.: Hydrostatic and non-hydrostatic simulations of the 6 August 1993
Kagoshima torrential rain, J. Meteorol. Soc. Jpn.,
74, 355–363, https://doi.org/10.2151/jmsj1965.74.3_355, 1996.
Klein Goldewijk, K., Beusen, A., Doelman, J., and Stehfest, E.: Anthropogenic land use estimates for the Holocene – HYDE 3.2, Earth Syst. Sci. Data, 9, 927–953, https://doi.org/10.5194/essd-9-927-2017, 2017.
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Kiyotoshi, T.:
The JRA-55 reanalysis: General specifications and basic characteristics,
J. Meteorol. Soc. Jpn., 93, 5–48,
https://doi.org/10.2151/jmsj.2015-001, 2015.
Körner, C., Jetz, W., Paulsen, J., Payne, D., Rudmann-Maurer, K., and M.
Spehn, E.: A global inventory of mountains for bio-geographical
applications, Alp. Bot., 127, 1–15, https://doi.org/10.1007/s00035-016-0182-6, 2017.
Kraaijenbrink, P. D. A., Bierkens, M. F. P., Lutz, A. F., and Immerzeel, W.
W.: Impact of a global temperature rise of 1.5 degrees Celsius on Asia's
glaciers, Nature, 549, 257–260, https://doi.org/10.1038/nature23878, 2017.
Kruse, C. G., Bacmeister, J. T., Zarzycki, C. M., Larson, V. E., and
Thayer-Calder, K.: Do Nudging Tendencies Depend on the Nudging Timescale
Chosen in Atmospheric Models?, J. Adv. Model Earth Sy., 14, e2022MS003024,
https://doi.org/10.1029/2022MS003024, 2022.
Lalande, M., Ménégoz, M., Krinner, G., Naegeli, K., and Wunderle, S.: Climate change in the High Mountain Asia in CMIP6, Earth Syst. Dynam., 12, 1061–1098, https://doi.org/10.5194/esd-12-1061-2021, 2021.
Lauritzen, P. H., Bacmeister, J. T., Callaghan, P. F., and Taylor, M. A.: NCAR_Topo (v1.0): NCAR global model topography generation software for unstructured grids, Geosci. Model Dev., 8, 3975–3986, https://doi.org/10.5194/gmd-8-3975-2015, 2015.
Lauritzen, P. H., Nair, R. D., Herrington, A. R., Callaghan, P., Goldhaber,
S., Dennis, J. M., Bacmeister, J. T., Eaton, B. E., Zarzycki, C. M., Taylor,
M. A., Ullrich, P. A., Dubos, T., Gettelman, A., Neale, R. B., Dobbins, B.,
Reed, K. A., Hannay, C., Medeiros, B., Benedict, J. J., and Tribbia, J. J.:
NCAR Release of CAM-SE in CESM2.0: A Reformulation of the Spectral Element
Dynamical Core in Dry-Mass Vertical Coordinates With Comprehensive Treatment
of Condensates and Energy, J. Adv. Model Earth Sy., 10, 1537–1570,
https://doi.org/10.1029/2017MS001257, 2018.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C.,
Bonan, G., Collier, N., Ghimire, B., Kampenhout, L., Kennedy, D., Kluzek,
E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J., Sacks,
W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A., Badger,
A. M., Bisht, G., Broeke, M., Brunke, M. A., Burns, S. P., Buzan, J., Clark,
M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B., Flanner, M., Fox, A.
M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox, R., Kumar, S.,
Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey, A., Pelletier,
J. D., Perket, J., Randerson, J. T., Ricciuto, D. M., Sanderson, B. M.,
Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val Martin, M., and Zeng,
X.: The Community Land Model Version 5: Description of New Features,
Benchmarking, and Impact of Forcing Uncertainty, J. Adv. Model Earth Sy., 11,
4245–4287, https://doi.org/10.1029/2018MS001583, 2019.
Lenaerts, J. T. M., Vizcaino, M., Fyke, J., van Kampenhout, L., and van den
Broeke, M. R.: Present-day and future Antarctic ice sheet climate and
surface mass balance in the Community Earth System Model, Clim. Dynam., 47,
1367–1381, https://doi.org/10.1007/s00382-015-2907-4, 2016.
Lenaerts, J. T. M., Medley, B., van den Broeke, M. R., and Wouters, B.:
Observing and Modeling Ice Sheet Surface Mass Balance, Rev.
Geophys., 57, 376–420, https://doi.org/10.1029/2018RG000622, 2019.
Li, D., Lu, X., Walling, D. E., Zhang, T., Steiner, J. F., Wasson, R. J.,
Harrison, S., Nepal, S., Nie, Y., Immerzeel, W. W., Shugar, D. H., Koppes,
M., Lane, S., Zeng, Z., Sun, X., Yegorov, A., and Bolch, T.: High Mountain
Asia hydropower systems threatened by climate-driven landscape instability,
Nat. Geosci., 15, 520–530, https://doi.org/10.1038/s41561-022-00953-y, 2022.
Lindzen, R. S. and Fox-Rabinovitz, M.: Consistent vertical and horizontal
resolution, Mon. Weather Rev., 117, 2575–2583,
https://doi.org/10.1175/1520-0493(1989)117<2575:CVAHR>2.0.CO;2, 1989.
Lipscomb, W. H., Fyke, J. G., Vizcaíno, M., Sacks, W. J., Wolfe, J.,
Vertenstein, M., Craig, A., Kluzek, E., and Lawrence, D. M.: Implementation
and Initial Evaluation of the Glimmer Community Ice Sheet Model in the
Community Earth System Model, J. Climate, 26, 7352–7371,
https://doi.org/10.1175/JCLI-D-12-00557.1, 2013.
Lipscomb, W. H., Price, S. F., Hoffman, M. J., Leguy, G. R., Bennett, A. R., Bradley, S. L., Evans, K. J., Fyke, J. G., Kennedy, J. H., Perego, M., Ranken, D. M., Sacks, W. J., Salinger, A. G., Vargo, L. J., and Worley, P. H.: Description and evaluation of the Community Ice Sheet Model (CISM) v2.1, Geosci. Model Dev., 12, 387–424, https://doi.org/10.5194/gmd-12-387-2019, 2019.
Liu, W., Ullrich, P. A., Guba, O., Caldwell, P. M., and Keen, N. D.: An
Assessment of Nonhydrostatic and Hydrostatic Dynamical Cores at Seasonal
Time Scales in the Energy Exascale Earth System Model (E3SM), J. Adv. Model
Earth. Sy., 14, e2021MS002805, https://doi.org/10.1029/2021MS002805, 2022.
Liu, X., Ma, P.-L., Wang, H., Tilmes, S., Singh, B., Easter, R. C., Ghan, S. J., and Rasch, P. J.: Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model, Geosci. Model Dev., 9, 505–522, https://doi.org/10.5194/gmd-9-505-2016, 2016.
Loeb, N. G., Doelling, D. R., Wang, H., Su, W., Nguyen, C., Corbett, J. G.,
Liang, L., Mitrescu, C., Rose, F. G., and Kato, S.: Clouds and the Earth'S
Radiant Energy System (CERES) Energy Balanced and Filled (EBAF)
top-of-atmosphere (TOA) edition-4.0 data product, J. Climate, 31, 895–918,
https://doi.org/10.1175/JCLI-D-17-0208.1, 2018.
Lutz, A. F., ter Maat, H. W., Wijngaard, R. R., Biemans, H., Syed, A.,
Shrestha, A. B., Wester, P., and Immerzeel, W. W.: South Asian river basins
in a 1.5 ∘C warmer world, Reg. Environ. Change, 19, 833–847,
https://doi.org/10.1007/s10113-018-1433-4, 2019.
Lutz, A. F., Immerzeel, W. W., Siderius, C., Wijngaard, R. R., Nepal, S.,
Shrestha, A. B., Wester, P., and Biemans, H.: South Asian agriculture
increasingly dependent on meltwater and groundwater, Nat. Clim. Change, 12,
566–573, https://doi.org/10.1038/s41558-022-01355-z, 2022.
Marzeion, B., Hock, R., Anderson, B., Bliss, A., Champollion, N., Fujita,
K., Huss, M., Immerzeel, W. W., Kraaijenbrink, P., Malles, J., Maussion, F.,
Radić, V., Rounce, D. R., Sakai, A., Shannon, S., Wal, R., and
Zekollari, H.: Partitioning the Uncertainty of Ensemble Projections of
Global Glacier Mass Change, Earths Future, 8, e2019EF001470,
https://doi.org/10.1029/2019EF001470, 2020.
Mölg, T. and Kaser, G.: A new approach to resolving climate-cryosphere
relations: Downscaling climate dynamics to glacier-scale mass and energy
balance without statistical scale linking, J. Geophys. Res., 116, D16101,
https://doi.org/10.1029/2011JD015669, 2011.
Muntjewerf, L., Sacks, W. J., Lofverstrom, M., Fyke, J., Lipscomb, W. H.,
Ernani da Silva, C., Vizcaino, M., Thayer-Calder, K., Lenaerts, J. T. M.,
and Sellevold, R.: Description and Demonstration of the Coupled Community
Earth System Model v2 – Community Ice Sheet Model v2 (CESM2-CISM2), J. Adv.
Model Earth Sy., 13, e2020MS002356, https://doi.org/10.1029/2020MS002356, 2021.
Nie, Y., Pritchard, H. D., Liu, Q., Hennig, T., Wang, W., Wang, X., Liu, S.,
Nepal, S., Samyn, D., Hewitt, K., and Chen, X.: Glacial change and
hydrological implications in the Himalaya and Karakoram, Nat. Rev. Earth
Environ., 2, 91–106, https://doi.org/10.1038/s43017-020-00124-w, 2021.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M., Koven, C. D. , Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S., Thornton, P. E. , Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E., Lamarque, J.-F., Ruby Leung, L., Lipscomb, W., Muszala, S. P., Ricciuto, D. M., Sacks, W. J., Tang, J., and Yang, Z.-L.: Technical description of version 4.5 of the Community Land Model (CLM), Ncar Tech. Note NCAR/TN-503+STR. National Center for Atmospheric Research, Boulder, 1–434, https://doi.org/10.5065/D6RR1W7M, 2013.
Orsolini, Y., Wegmann, M., Dutra, E., Liu, B., Balsamo, G., Yang, K., de Rosnay, P., Zhu, C., Wang, W., Senan, R., and Arduini, G.: Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations, The Cryosphere, 13, 2221–2239, https://doi.org/10.5194/tc-13-2221-2019, 2019.
Palazzi, E., Von Hardenberg, J., Terzago, S., and Provenzale, A.:
Precipitation in the Karakoram-Himalaya: a CMIP5 view, Clim. Dynam., 45, 21–45,
https://doi.org/10.1007/s00382-014-2341-z, 2015.
Rahimi, S. R., Wu, C., Liu, X., and Brown, H.: Exploring a
Variable-Resolution Approach for Simulating Regional Climate Over the
Tibetan Plateau Using VR-CESM, J. Geophys. Res.-Atmos.,
124, 4490–4513, https://doi.org/10.1029/2018JD028925, 2019.
Rauscher, S. A., Ringler, T. D., Skamarock, W. C., and Mirin, A. A.:
Exploring a global multiresolution modeling approach using aquaplanet
simulations, J. Climate, 26, 2432–2452, https://doi.org/10.1175/JCLI-D-12-00154.1, 2013.
RGI-Consortium: Randolph Glacier Inventory – A Dataset of Global Glacier Outlines: Version 6.0, Technical Report, Global Land Ice Measurements from Space, Colorado, USA, Boulder, Colorado, USA, https://doi.org/10.7265/4m1f-gd79, 2017.
Rhoades, A. M., Huang, X., Ullrich, P. A., and Zarzycki, C. M.:
Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM, J. Appl.
Meteorol. Clim., 55, 173–196, https://doi.org/10.1175/JAMC-D-15-0156.1,
2016.
Rhoades, A. M., Ullrich, P. A., Zarzycki, C. M., Johansen, H., Margulis, S.
A., Morrison, H., Xu, Z., and Collins, W. D.: Sensitivity of Mountain
Hydroclimate Simulations in Variable-Resolution CESM to Microphysics and
Horizontal Resolution, J. Adv. Model Earth Sy., 10, 1357–1380,
https://doi.org/10.1029/2018MS001326, 2018.
Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M. A., Hagemann, S.,
Kornblueh, L., Manzini, E., Schlese, U., and Schulzweida, U.: Sensitivity of
simulated climate to horizontal and vertical resolution in the ECHAM5
atmosphere model, J. Climate, 19, 3771–3791, https://doi.org/10.1175/JCLI3824.1, 2006.
Sellevold, R., van Kampenhout, L., Lenaerts, J. T. M., Noël, B., Lipscomb, W. H., and Vizcaino, M.: Surface mass balance downscaling through elevation classes in an Earth system model: application to the Greenland ice sheet, The Cryosphere, 13, 3193–3208, https://doi.org/10.5194/tc-13-3193-2019, 2019.
Shannon, S., Smith, R., Wiltshire, A., Payne, T., Huss, M., Betts, R., Caesar, J., Koutroulis, A., Jones, D., and Harrison, S.: Global glacier volume projections under high-end climate change scenarios, The Cryosphere, 13, 325–350, https://doi.org/10.5194/tc-13-325-2019, 2019.
Shean, D. E., Bhushan, S., Montesano, P., Rounce, D. R., Arendt, A., and
Osmanoglu, B.: A Systematic, Regional Assessment of High Mountain Asia
Glacier Mass Balance, Front. Earth Sci., 7, 363,
https://doi.org/10.3389/feart.2019.00363, 2020.
Skamarock, W. C., Snyder, C., Klemp, J. B., and Park, S. H.: Vertical
resolution requirements in atmospheric simulation, Mon. Weather Rev., 147, 2641–2656,
https://doi.org/10.1175/MWR-D-19-0043.1, 2019.
Slater, A. G., Schlosser, C. A., Desborough, C. E., Pitman, A. J.,
Henderson-Sellers, A., Robock, A., Vinnikov, K. Y., Mitchell, K., Boone, A.,
Braden, H., Chen, F., Cox, P. M., De Rosnay, P., Dickinson, R. E., Dai, Y.
J., Duan, Q., Entin, J., Etchevers, P., Gedney, N., Gusev, Y. M., Habets,
F., Kim, J., Koren, V., Kowalczyk, E. A., Nasonova, O. N., Noilhan, J.,
Schaake, S., Shmakin, A. B., Smirnova, T. G., Verseghy, D., Wetzel, P., Xue,
Y., Yang, Z. L., and Zeng, Q.: The representation of snow in land surface
schemes: Results from PILPS 2(d), J. Hydrometeorol., 2, 7–25,
https://doi.org/10.1175/1525-7541(2001)002<0007:TROSIL>2.0.CO;2, 2001.
Smith, T. and Bookhagen, B.: Changes in seasonal snow water equivalent
distribution in High Mountain Asia (1987 to 2009), Sci. Adv., 4, e1701550,
https://doi.org/10.1126/sciadv.1701550, 2018.
Swenson, S. C., Clark, M., Fan, Y., Lawrence, D. M., and Perket, J.:
Representing Intrahillslope Lateral Subsurface Flow in the Community Land
Model, J. Adv. Model Earth Sy., 11, 4044–4065, https://doi.org/10.1029/2019MS001833,
2019.
Tesfa, T. K., Leung, L. R., and Ghan, S. J.: Exploring Topography-Based
Methods for Downscaling Subgrid Precipitation for Use in Earth System
Models, J. Geophys. Res.-Atmos., 125, e2019JD031456,
https://doi.org/10.1029/2019JD031456, 2020.
Ullrich, P. A.: SQuadGen: spherical quadrilateral grid generator, https://climate.ucdavis.edu/squadgen.php (last access: 29 August 2023), 2014.
van Kampenhout, L., Lenaerts, J. T. M., Lipscomb, W. H., Sacks, W. J.,
Lawrence, D. M., Slater, A. G., and van den Broeke, M. R.: Improving the
Representation of Polar Snow and Firn in the Community Earth System Model, J.
Adv. Model Earth Sy., 9, 2583–2600, https://doi.org/10.1002/2017MS000988,
2017.
van Kampenhout, L., Rhoades, A. M., Herrington, A. R., Zarzycki, C. M., Lenaerts, J. T. M., Sacks, W. J., and van den Broeke, M. R.: Regional grid refinement in an Earth system model: impacts on the simulated Greenland surface mass balance, The Cryosphere, 13, 1547–1564, https://doi.org/10.5194/tc-13-1547-2019, 2019.
van Kampenhout, L., Lenaerts, J. T. M., Lipscomb, W. H., Lhermitte, S.,
Noël, B., Vizcaíno, M., Sacks, W. J., and van den Broeke, M. R.:
Present-Day Greenland Ice Sheet Climate and Surface Mass Balance in CESM2, J
Geophys. Res.-Earth, 125, e2019JF005318,
https://doi.org/10.1029/2019JF005318, 2020.
Van Tricht, K., Lhermitte, S., Gorodetskaya, I. V., and van Lipzig, N. P. M.: Improving satellite-retrieved surface radiative fluxes in polar regions using a smart sampling approach, The Cryosphere, 10, 2379–2397, https://doi.org/10.5194/tc-10-2379-2016, 2016.
Viste, E. and Sorteberg, A.: Snowfall in the Himalayas: an uncertain future from a little-known past, The Cryosphere, 9, 1147–1167, https://doi.org/10.5194/tc-9-1147-2015, 2015.
Vizcaino, M.: Ice sheets as interactive components of Earth System Models:
progress and challenges, Wires Clim. Change, 5, 557–568,
https://doi.org/10.1002/wcc.285, 2014.
Vizcaíno, M., Lipscomb, W. H., Sacks, W. J., van Angelen, J. H.,
Wouters, B., and van den Broeke, M. R.: Greenland Surface Mass Balance as
Simulated by the Community Earth System Model. Part I: Model Evaluation and
1850–2005 Results, J. Climate, 26, 7793–7812,
https://doi.org/10.1175/JCLI-D-12-00615.1, 2013.
Wang, R., Ding, Y., Shangguan, D., Guo, W., Zhao, Q., Li, Y., and Song, M.:
Influence of Topographic Shading on the Mass Balance of the High Mountain
Asia Glaciers, Remote Sens.-Basel, 14, 1576, https://doi.org/10.3390/rs14071576,
2022.
Wang, X., Tolksdorf, V., Otto, M., and Scherer, D.: WRF-based dynamical
downscaling of ERA5 reanalysis data for High Mountain Asia: Towards a new
version of the High Asia Refined analysis, Int. J.
Climatol., 41, 743–762, https://doi.org/10.1002/joc.6686, 2021.
Waterman, T., Bragg, A., Simon, J., and Chaney, N.: Capturing the Effects of Surface Heterogeneity Induced Secondary Circulations on the Lower Sub-grid Atmosphere in Earth System Models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10646, https://doi.org/10.5194/egusphere-egu22-10646, 2022.
Wedi, N., Benard, P., Yessad, K., Untch, A., Malardel, S., Hamrud, M.,
Mozdzynski, G., Fisher, M., and Smolarkiewicz, P.: Non-hydrostatic modeling
with IFS: current status,
https://www.ecmwf.int/en/elibrary/78642-non-hydrostatic-modeling-ifs-current-status (last access: 30 August 2023),
November 2010.
Wedi, N. P. and Smolarkiewicz, P. K.: A framework for testing global
non-hydrostatic models, Q. J. Roy. Meteor.
Soc., 135, 469–484, https://doi.org/10.1002/qj.377, 2009.
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and
Viterbo, P.: The WFDEI meteorological forcing data set: WATCH Forcing data
methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50,
7505–7514, https://doi.org/10.1002/2014WR015638, 2014.
Wijngaard, R. R., Lutz, A. F., Nepal, S., Khanal, S., Pradhananga, S.,
Shrestha, A. B., and Immerzeel, W. W.: Future changes in hydro-climatic
extremes in the Upper Indus, Ganges, and Brahmaputra River basins, PLoS One,
12, e0190224, https://doi.org/10.1371/journal.pone.0190224, 2017.
Wijngaard, R. R., Herrington, A. R., Lipscomb, W. H., Leguy, G. R., and An,
S.-I.: CLM/CTSM glacier input datasets used for study on evaluation
variable-resolution CESM2 in High-Mountain Asia, Zenodo [data set],
https://doi.org/10.5281/ZENODO.7864689, 2023a.
Wijngaard, R. R., Herrington, A. R., Lipscomb, W. H., Leguy, G. R., and An,
S.-I.: Dataset used for “Exploring the ability of the variable-resolution CESM to simulate cryospheric-hydrological variables in High Mountain Asia”, Zenodo [data set], https://doi.org/10.5281/zenodo.7864633, 2023b.
Wu, X., Reed, K. A., Callaghan, P., and Bacmeister, J. T.: Exploring Western
North Pacific Tropical Cyclone Activity in the High-Resolution Community
Atmosphere Model, Earth Space Sci., 9, e2021EA001862,
https://doi.org/10.1029/2021EA001862, 2022.
Xu, Z., di Vittorio, A., Zhang, J., Rhoades, A., Xin, X., Xu, H., and Xiao,
C.: Evaluating Variable-Resolution CESM Over China and Western United States
for Use in Water-Energy Nexus and Impacts Modeling, J. Geophys.
Res.-Atmos., 126, e2020JD034361,
https://doi.org/10.1029/2020JD034361, 2021.
Yang, Q., Leung, L. R., Lu, J., Lin, Y. L., Hagos, S., Sakaguchi, K., and
Gao, Y.: Exploring the effects of a nonhydrostatic dynamical core in
high-resolution aquaplanet simulations, J. Geophys. Res., 122, 3245–3265,
https://doi.org/10.1002/2016JD025287, 2017.
Yao, T., Thompson, L., Yang, W., Yu, W., Gao, Y., Guo, X., Yang, X., Duan,
K., Zhao, H., Xu, B., Pu, J., Lu, A., Xiang, Y., Kattel, D. B., and Joswiak,
D.: Different glacier status with atmospheric circulations in Tibetan
Plateau and surroundings, Nat. Clim. Change, 2, 663–667,
https://doi.org/10.1038/nclimate1580, 2012.
Zarzycki, C. M., Levy, M. N., Jablonowski, C., Overfelt, J. R., Taylor, M.
A., and Ullrich, P. A.: Aquaplanet Experiments Using CAM's
Variable-Resolution Dynamical Core, J. Climate, 27, 5481–5503,
https://doi.org/10.1175/JCLI-D-14-00004.1, 2014.
Zemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J.,
Barandun, M., Machguth, H., Nussbaumer, S. U., Gärtner-Roer, I.,
Thomson, L., Paul, F., Maussion, F., Kutuzov, S., and Cogley, J. G.: Global
glacier mass changes and their contributions to sea-level rise from 1961 to
2016, Nature, 568, 382–386, https://doi.org/10.1038/s41586-019-1071-0,
2019.
Zhang, G. J. and McFarlane, N. A.: Sensitivity of climate simulations to the
parameterization of cumulus convection in the canadian climate centre
general circulation model, Atmos. Ocean, 33, 407–446,
https://doi.org/10.1080/07055900.1995.9649539, 1995.
Short summary
We evaluate the ability of the Community Earth System Model (CESM2) to simulate cryospheric–hydrological variables, such as glacier surface mass balance (SMB), over High Mountain Asia (HMA) by using a global grid (~111 km) with regional refinement (~7 km) over HMA. Evaluations of two different simulations show that climatological biases are reduced, and glacier SMB is improved (but still too negative) by modifying the snow and glacier model and using an updated glacier cover dataset.
We evaluate the ability of the Community Earth System Model (CESM2) to simulate...