Articles | Volume 12, issue 3
https://doi.org/10.5194/gmd-12-1139-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-1139-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
25 Mar 2019
Model experiment description paper |
| 25 Mar 2019
| 25 Mar 2019
The Polar Amplification Model Intercomparison Project (PAMIP) contribution to CMIP6: investigating the causes and consequences of polar amplification
Doug M. Smith
CORRESPONDING AUTHOR
Met Office Hadley Centre, Exeter, UK
James A. Screen
College of Engineering, Mathematics and Physical Sciences, University
of Exeter, Exeter, UK
Clara Deser
Climate and Global Dynamics, National Center for Atmospheric Research,
Boulder, CO, USA
Judah Cohen
Atmospheric and Environmental Research, Lexington, MA, USA
John C. Fyfe
Canadian Centre for Climate Modelling and Analysis, Environment and
Climate Change Canada, Victoria, British Columbia, Canada
Javier García-Serrano
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Group of Meteorology, Universitat de Barcelona, Barcelona, Spain
Thomas Jung
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Bremerhaven, Germany
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Vladimir Kattsov
Voeikov Main Geophysical Observatory, Roshydromet, St. Petersburg, Russia
Daniela Matei
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Rym Msadek
CERFACS/CNRS, UMR 5318, Toulouse, France
Yannick Peings
Department of Earth System Science, University of California Irvine,
Irvine, CA, USA
Michael Sigmond
Canadian Centre for Climate Modelling and Analysis, Environment and
Climate Change Canada, Victoria, British Columbia, Canada
Jinro Ukita
Institute of Science and Technology, Niigata University, Niigata,
Japan
Jin-Ho Yoon
Gwangju Institute of Science and Technology, School of Earth Sciences
and Environmental Engineering, Gwangju, South Korea
Xiangdong Zhang
International Arctic Research Center, University of Alaska Fairbanks,
Fairbanks, AK, USA
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Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
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A large ensemble of simulations with 100 members has been conducted with the state-of-the-art CESM2 Earth system model, using historical and SSP3-7.0 forcing. Our main finding is that there are significant changes in the variance of the Earth system in response to anthropogenic forcing, with these changes spanning a broad range of variables important to impacts for human populations and ecosystems.
Marilena Oltmanns, N. Penny Holliday, James Screen, D. Gwyn Evans, Simon A. Josey, Sheldon Bacon, and Ben I. Moat
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2021-79, https://doi.org/10.5194/wcd-2021-79, 2021
Revised manuscript not accepted
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The Arctic is currently warming twice as fast as the global average. This results in enhanced melting and thus freshwater releases into the North Atlantic. Using a combination of observations and models, we show that atmosphere-ocean feedbacks initiated by freshwater releases into the North Atlantic lead to warmer and drier weather over Europe in subsequent summers. The existence of this dynamical link suggests that European summer weather can potentially be predicted months to years in advance.
Amy Solomon, Céline Heuzé, Benjamin Rabe, Sheldon Bacon, Laurent Bertino, Patrick Heimbach, Jun Inoue, Doroteaciro Iovino, Ruth Mottram, Xiangdong Zhang, Yevgeny Aksenov, Ronan McAdam, An Nguyen, Roshin P. Raj, and Han Tang
Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, https://doi.org/10.5194/os-17-1081-2021, 2021
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Freshwater in the Arctic Ocean plays a critical role in the global climate system by impacting ocean circulations, stratification, mixing, and emergent regimes. In this review paper we assess how Arctic Ocean freshwater changed in the 2010s relative to the 2000s. Estimates from observations and reanalyses show a qualitative stabilization in the 2010s due to a compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the Amerasian and Eurasian basins.
Hyun Cheol Kim, Soontae Kim, Mark Cohen, Changhan Bae, Dasom Lee, Rick Saylor, Minah Bae, Eunhye Kim, Byeong-Uk Kim, Jin-Ho Yoon, and Ariel Stein
Atmos. Chem. Phys., 21, 10065–10080, https://doi.org/10.5194/acp-21-10065-2021, https://doi.org/10.5194/acp-21-10065-2021, 2021
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Global outbreaks of COVID-19 offer rare opportunities of natural experiments in emission control and corresponding responses of tropospheric chemistry. This study's novel approach investigates (1) isolating the pandemic's impact from natural and anthropogenic variations, (2) emission adjustment to reproduce real-time emissions, and (3) brute-force modeling to investigate Chinese economic activities. Results provide characteristics of the region's chemistry and emissions.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Renate Anna Irma Wilcke, Erik Kjellström, Changgui Lin, Daniela Matei, Anders Moberg, and Evangelos Tyrlis
Earth Syst. Dynam., 11, 1107–1121, https://doi.org/10.5194/esd-11-1107-2020, https://doi.org/10.5194/esd-11-1107-2020, 2020
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Two long-lasting high-pressure systems in summer 2018 led to heat waves over Scandinavia and an extended summer period with devastating impacts on both agriculture and human life. Using five climate model ensembles, the unique 263-year Stockholm temperature time series and a composite 150-year time series for the whole of Sweden, we found that anthropogenic climate change has strongly increased the probability of a warm summer, such as the one observed in 2018, occurring in Sweden.
Landon A. Rieger, Jason N. S. Cole, John C. Fyfe, Stephen Po-Chedley, Philip J. Cameron-Smith, Paul J. Durack, Nathan P. Gillett, and Qi Tang
Geosci. Model Dev., 13, 4831–4843, https://doi.org/10.5194/gmd-13-4831-2020, https://doi.org/10.5194/gmd-13-4831-2020, 2020
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Recently, the stratospheric aerosol forcing dataset used as an input to the Coupled Model Intercomparison Project phase 6 was updated. This work explores the impact of those changes on the modelled historical climates in the CanESM5 and EAMv1 models. Temperature differences in the stratosphere shortly after the Pinatubo eruption are found to be significant, but surface temperatures and precipitation do not show a significant change.
Rein Haarsma, Mario Acosta, Rena Bakhshi, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Susanna Corti, Paolo Davini, Eleftheria Exarchou, Federico Fabiano, Uwe Fladrich, Ramon Fuentes Franco, Javier García-Serrano, Jost von Hardenberg, Torben Koenigk, Xavier Levine, Virna Loana Meccia, Twan van Noije, Gijs van den Oord, Froila M. Palmeiro, Mario Rodrigo, Yohan Ruprich-Robert, Philippe Le Sager, Etienne Tourigny, Shiyu Wang, Michiel van Weele, and Klaus Wyser
Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, https://doi.org/10.5194/gmd-13-3507-2020, 2020
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HighResMIP is an international coordinated CMIP6 effort to investigate the improvement in climate modeling caused by an increase in horizontal resolution. This paper describes EC-Earth3P-(HR), which has been developed for HighResMIP. First analyses reveal that increasing resolution does improve certain aspects of the simulated climate but that many other biases still continue, possibly related to phenomena that are still not yet resolved and need to be parameterized.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Flavio Lehner, Clara Deser, Nicola Maher, Jochem Marotzke, Erich M. Fischer, Lukas Brunner, Reto Knutti, and Ed Hawkins
Earth Syst. Dynam., 11, 491–508, https://doi.org/10.5194/esd-11-491-2020, https://doi.org/10.5194/esd-11-491-2020, 2020
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Projections of climate change are uncertain because climate models are imperfect, future greenhouse gases emissions are unknown and climate is to some extent chaotic. To partition and understand these sources of uncertainty and make the best use of climate projections, large ensembles with multiple climate models are needed. Such ensembles now exist in a public data archive. We provide several novel applications focused on global and regional temperature and precipitation projections.
Koji Yamazaki, Tetsu Nakamura, Jinro Ukita, and Kazuhira Hoshi
Atmos. Chem. Phys., 20, 5111–5127, https://doi.org/10.5194/acp-20-5111-2020, https://doi.org/10.5194/acp-20-5111-2020, 2020
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It has been well known that the stratospheric quasi-biennial oscillation (QBO) affects the winter Arctic polar vortex. This relation has been explained through stratospheric processes. We show that a tropospheric process also plays a role, especially in early winter, based on data analysis and numerical simulations. The QBO modifies tropical convection, which affects planetary waves in the midlatitude troposphere, then modulating vertical propagation and the polar vortex.
Patrick Scholz, Dmitry Sidorenko, Ozgur Gurses, Sergey Danilov, Nikolay Koldunov, Qiang Wang, Dmitry Sein, Margarita Smolentseva, Natalja Rakowsky, and Thomas Jung
Geosci. Model Dev., 12, 4875–4899, https://doi.org/10.5194/gmd-12-4875-2019, https://doi.org/10.5194/gmd-12-4875-2019, 2019
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This paper is the first in a series documenting and assessing important key components of the Finite-volumE Sea ice-Ocean Model version 2.0 (FESOM2.0). We assess the hydrographic biases, large-scale circulation, numerical performance and scalability of FESOM2.0 compared with its predecessor, FESOM1.4. The main conclusion is that the results of FESOM2.0 compare well to FESOM1.4 in terms of model biases but with a remarkable performance speedup with a 3 times higher throughput.
Neil C. Swart, Jason N. S. Cole, Viatcheslav V. Kharin, Mike Lazare, John F. Scinocca, Nathan P. Gillett, James Anstey, Vivek Arora, James R. Christian, Sarah Hanna, Yanjun Jiao, Warren G. Lee, Fouad Majaess, Oleg A. Saenko, Christian Seiler, Clint Seinen, Andrew Shao, Michael Sigmond, Larry Solheim, Knut von Salzen, Duo Yang, and Barbara Winter
Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, https://doi.org/10.5194/gmd-12-4823-2019, 2019
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The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial-scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and quantifies the model performance. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science applications in Canada.
Nikolay V. Koldunov, Vadym Aizinger, Natalja Rakowsky, Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, and Thomas Jung
Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, https://doi.org/10.5194/gmd-12-3991-2019, 2019
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We measure how computational performance of the global FESOM2 ocean model (formulated on an unstructured mesh) changes with the increase in the number of computational cores. We find that for many components of the model the performance increases linearly but we also identify two bottlenecks: sea ice and ssh submodules. We show that FESOM2 is on par with the state-of-the-art ocean models in terms of throughput that reach 16 simulated years per day for eddy resolving configuration (1/10°).
Thomas Rackow, Dmitry V. Sein, Tido Semmler, Sergey Danilov, Nikolay V. Koldunov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, https://doi.org/10.5194/gmd-12-2635-2019, 2019
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Current climate models show errors in the deep ocean that are larger than the level of natural variability and the response to enhanced greenhouse gas concentrations. These errors are larger than the signals we aim to predict. With the AWI Climate Model, we show that increasing resolution to resolve eddies can lead to major reductions in deep ocean errors. AWI's next-generation (CMIP6) model configuration will thus use locally eddy-resolving computational grids for projecting climate change.
Ben Kravitz, Philip J. Rasch, Hailong Wang, Alan Robock, Corey Gabriel, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Duoying Ji, Andy Jones, Andrew Lenton, John C. Moore, Helene Muri, Ulrike Niemeier, Steven Phipps, Hauke Schmidt, Shingo Watanabe, Shuting Yang, and Jin-Ho Yoon
Atmos. Chem. Phys., 18, 13097–13113, https://doi.org/10.5194/acp-18-13097-2018, https://doi.org/10.5194/acp-18-13097-2018, 2018
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Marine cloud brightening has been proposed as a means of geoengineering/climate intervention, or deliberately altering the climate system to offset anthropogenic climate change. In idealized simulations that highlight contrasts between land and ocean, we find that the globe warms, including the ocean due to transport of heat from land. This study reinforces that no net energy input into the Earth system does not mean that temperature will necessarily remain unchanged.
Yuta Ando, Koji Yamazaki, Yoshihiro Tachibana, Masayo Ogi, and Jinro Ukita
Atmos. Chem. Phys., 18, 12639–12661, https://doi.org/10.5194/acp-18-12639-2018, https://doi.org/10.5194/acp-18-12639-2018, 2018
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We found the climatological strong stratospheric westerly circumpolar wind stops increasing temporarily during November, when the upward propagation of large-scale atmospheric waves from the troposphere increases. The propagation of atmospheric waves, which is strongest over Siberia, is related to strengthening of the low pressure. Longitudinally asymmetric forcing by land–sea heating contrasts caused by their different heat capacities might cause the strengthening of the low pressure.
Kai Zhang, Philip J. Rasch, Mark A. Taylor, Hui Wan, Ruby Leung, Po-Lun Ma, Jean-Christophe Golaz, Jon Wolfe, Wuyin Lin, Balwinder Singh, Susannah Burrows, Jin-Ho Yoon, Hailong Wang, Yun Qian, Qi Tang, Peter Caldwell, and Shaocheng Xie
Geosci. Model Dev., 11, 1971–1988, https://doi.org/10.5194/gmd-11-1971-2018, https://doi.org/10.5194/gmd-11-1971-2018, 2018
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The conservation of total water is an important numerical feature for global Earth system models. Even small conservation problems in the water budget can lead to systematic errors in century-long simulations for sea level rise projection. This study quantifies and reduces various sources of water conservation error in the atmosphere component of the Energy Exascale Earth System Model.
Paul J. Kushner, Lawrence R. Mudryk, William Merryfield, Jaison T. Ambadan, Aaron Berg, Adéline Bichet, Ross Brown, Chris Derksen, Stephen J. Déry, Arlan Dirkson, Greg Flato, Christopher G. Fletcher, John C. Fyfe, Nathan Gillett, Christian Haas, Stephen Howell, Frédéric Laliberté, Kelly McCusker, Michael Sigmond, Reinel Sospedra-Alfonso, Neil F. Tandon, Chad Thackeray, Bruno Tremblay, and Francis W. Zwiers
The Cryosphere, 12, 1137–1156, https://doi.org/10.5194/tc-12-1137-2018, https://doi.org/10.5194/tc-12-1137-2018, 2018
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Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Qiang Wang, Claudia Wekerle, Sergey Danilov, Xuezhu Wang, and Thomas Jung
Geosci. Model Dev., 11, 1229–1255, https://doi.org/10.5194/gmd-11-1229-2018, https://doi.org/10.5194/gmd-11-1229-2018, 2018
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For developing a system for Arctic research, we evaluate the Arctic Ocean simulated by FESOM. We use two global meshes differing in the horizontal resolution only in the Arctic Ocean (24 vs. 4.5 km). The high resolution significantly improves the model's representation of the Arctic Ocean. The most pronounced improvement is in the Arctic intermediate layer. The high resolution also improves the ocean surface circulation, mainly through a better representation of the Canadian Arctic Archipelago.
Chiyuki Narama, Mirlan Daiyrov, Murataly Duishonakunov, Takeo Tadono, Hayato Sato, Andreas Kääb, Jinro Ukita, and Kanatbek Abdrakhmatov
Nat. Hazards Earth Syst. Sci., 18, 983–995, https://doi.org/10.5194/nhess-18-983-2018, https://doi.org/10.5194/nhess-18-983-2018, 2018
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Four large drainages from glacial lakes occurred during 2006–2014 in the western Teskey Range, Kyrgyzstan. These floods caused extensive damage, killing people and livestock, as well as destroying property and crops. Due to their subsurface outlet, we refer to these short-lived glacial lakes as being of the
tunnel-type, a type that drastically grows and drains over a few months.
Neal Butchart, James A. Anstey, Kevin Hamilton, Scott Osprey, Charles McLandress, Andrew C. Bushell, Yoshio Kawatani, Young-Ha Kim, Francois Lott, John Scinocca, Timothy N. Stockdale, Martin Andrews, Omar Bellprat, Peter Braesicke, Chiara Cagnazzo, Chih-Chieh Chen, Hye-Yeong Chun, Mikhail Dobrynin, Rolando R. Garcia, Javier Garcia-Serrano, Lesley J. Gray, Laura Holt, Tobias Kerzenmacher, Hiroaki Naoe, Holger Pohlmann, Jadwiga H. Richter, Adam A. Scaife, Verena Schenzinger, Federico Serva, Stefan Versick, Shingo Watanabe, Kohei Yoshida, and Seiji Yukimoto
Geosci. Model Dev., 11, 1009–1032, https://doi.org/10.5194/gmd-11-1009-2018, https://doi.org/10.5194/gmd-11-1009-2018, 2018
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This paper documents the numerical experiments to be used in phase 1 of the Stratosphere–troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi), which was set up to improve the representation of the QBO and tropical stratospheric variability in global climate models.
Sergey Danilov, Dmitry Sidorenko, Qiang Wang, and Thomas Jung
Geosci. Model Dev., 10, 765–789, https://doi.org/10.5194/gmd-10-765-2017, https://doi.org/10.5194/gmd-10-765-2017, 2017
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Numerical models of global ocean circulation are used to learn about future climate. The ocean circulation is characterized by processes on different spatial scales which are still beyond the reach of present computers. We describe a new model setup that allows one to vary a model's spatial resolution and hence focus the computational power on regional dynamics, reaching a better description of local processes in areas of interest.
George J. Boer, Douglas M. Smith, Christophe Cassou, Francisco Doblas-Reyes, Gokhan Danabasoglu, Ben Kirtman, Yochanan Kushnir, Masahide Kimoto, Gerald A. Meehl, Rym Msadek, Wolfgang A. Mueller, Karl E. Taylor, Francis Zwiers, Michel Rixen, Yohan Ruprich-Robert, and Rosie Eade
Geosci. Model Dev., 9, 3751–3777, https://doi.org/10.5194/gmd-9-3751-2016, https://doi.org/10.5194/gmd-9-3751-2016, 2016
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The Decadal Climate Prediction Project (DCPP) investigates our ability to skilfully predict climate variations from a year to a decade ahead by means of a series of retrospective forecasts. Quasi-real-time forecasts are also produced for potential users. In addition, the DCPP investigates how perturbations such as volcanoes affect forecasts and, more broadly, what new information can be learned about the mechanisms governing climate variations by means of case studies of past climate behaviour.
Jonathan J. Day, Steffen Tietsche, Mat Collins, Helge F. Goessling, Virginie Guemas, Anabelle Guillory, William J. Hurlin, Masayoshi Ishii, Sarah P. E. Keeley, Daniela Matei, Rym Msadek, Michael Sigmond, Hiroaki Tatebe, and Ed Hawkins
Geosci. Model Dev., 9, 2255–2270, https://doi.org/10.5194/gmd-9-2255-2016, https://doi.org/10.5194/gmd-9-2255-2016, 2016
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Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable.
Veronika Eyring, Mattia Righi, Axel Lauer, Martin Evaldsson, Sabrina Wenzel, Colin Jones, Alessandro Anav, Oliver Andrews, Irene Cionni, Edouard L. Davin, Clara Deser, Carsten Ehbrecht, Pierre Friedlingstein, Peter Gleckler, Klaus-Dirk Gottschaldt, Stefan Hagemann, Martin Juckes, Stephan Kindermann, John Krasting, Dominik Kunert, Richard Levine, Alexander Loew, Jarmo Mäkelä, Gill Martin, Erik Mason, Adam S. Phillips, Simon Read, Catherine Rio, Romain Roehrig, Daniel Senftleben, Andreas Sterl, Lambertus H. van Ulft, Jeremy Walton, Shiyu Wang, and Keith D. Williams
Geosci. Model Dev., 9, 1747–1802, https://doi.org/10.5194/gmd-9-1747-2016, https://doi.org/10.5194/gmd-9-1747-2016, 2016
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A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) in CMIP has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations.
Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, Lars Nerger, and Thomas Lavergne
The Cryosphere, 10, 761–774, https://doi.org/10.5194/tc-10-761-2016, https://doi.org/10.5194/tc-10-761-2016, 2016
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We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
K. Kreher, G. E. Bodeker, and M. Sigmond
Atmos. Chem. Phys., 15, 7653–7665, https://doi.org/10.5194/acp-15-7653-2015, https://doi.org/10.5194/acp-15-7653-2015, 2015
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This manuscript aims to answer the following question: which of the existing sites engaged in upper-air temperature measurements are best located to detect expected future trends within the shortest time possible? To do so, we explore one objective method for selecting the optimal locations for detecting projected 21st century trends and then demonstrate a similar technique for objectively selecting optimal locations for detecting expected future trends in total column ozone.
S. Danilov, Q. Wang, R. Timmermann, N. Iakovlev, D. Sidorenko, M. Kimmritz, T. Jung, and J. Schröter
Geosci. Model Dev., 8, 1747–1761, https://doi.org/10.5194/gmd-8-1747-2015, https://doi.org/10.5194/gmd-8-1747-2015, 2015
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Unstructured meshes allow multi-resolution modeling of ocean dynamics. Sea ice models formulated on unstructured meshes are a necessary component of ocean models intended for climate studies. This work presents a description of a finite-element sea ice model which is used as a component of a finite-element sea ice ocean circulation model. The principles underlying its design can be of interest to other groups pursuing ocean modelling on unstructured meshes.
K. Lohmann, J. Mignot, H. R. Langehaug, J. H. Jungclaus, D. Matei, O. H. Otterå, Y. Q. Gao, T. L. Mjell, U. S. Ninnemann, and H. F. Kleiven
Clim. Past, 11, 203–216, https://doi.org/10.5194/cp-11-203-2015, https://doi.org/10.5194/cp-11-203-2015, 2015
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We use model simulations to investigate mechanisms of similar Iceland--Scotland overflow (outflow from the Nordic seas) and North Atlantic sea surface temperature variability, suggested from palaeo-reconstructions (Mjell et al., 2015). Our results indicate the influence of Nordic Seas surface temperature on the pressure gradient across the Iceland--Scotland ridge, not a large-scale link through the meridional overturning circulation, is responsible for the (simulated) co-variability.
Q. Wang, S. Danilov, D. Sidorenko, R. Timmermann, C. Wekerle, X. Wang, T. Jung, and J. Schröter
Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, https://doi.org/10.5194/gmd-7-663-2014, 2014
K. Lohmann, J. H. Jungclaus, D. Matei, J. Mignot, M. Menary, H. R. Langehaug, J. Ba, Y. Gao, O. H. Otterå, W. Park, and S. Lorenz
Ocean Sci., 10, 227–241, https://doi.org/10.5194/os-10-227-2014, https://doi.org/10.5194/os-10-227-2014, 2014
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CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
A non-intrusive, multi-scale, and flexible coupling interface in WRF
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
The very-high resolution configuration of the EC-Earth global model for HighResMIP
ZEMBA v1.0: An energy and moisture balance climate model to investigate Quaternary climate
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++ and Python) and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
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.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
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This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged between WRF and any other model (e.g. an ocean model) using the coupling library Ocean-Atmosphere-Sea-Ice-Soil – Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-119, https://doi.org/10.5194/gmd-2024-119, 2024
Revised manuscript accepted for GMD
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10-15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100-km and a 25-km grid. The three models are compared with observations to study the improvements thanks to the increased in the resolution.
Daniel Francis James Gunning, Kerim Hestnes Nisancioglu, Emilie Capron, and Roderik van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2024-1384, https://doi.org/10.5194/egusphere-2024-1384, 2024
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth’s orbit. We demonstrate ZEMBA reproduces many features of the Earth’s climate for both the pre-industrial period and the Earth’s most recent cold extreme- the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
K. Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
EGUsphere, https://doi.org/10.5194/egusphere-2024-1431, https://doi.org/10.5194/egusphere-2024-1431, 2024
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The study aimed to improve the representation of spring wheat and rice in the CLM5. The modified CLM5 model performed significantly better than the default model in simulating crop phenology, yield, carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific parameters for accurately simulating vegetation processes and land surface processes.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Cited articles
Acosta Navarro, J. C., Varma, V., Riipinen, I., Seland, Ø., Kirkevåg,
A., Struthers, H., Iversen, T., Hansson H.-C., and Ekman, A. M. L.:
Amplification of Arctic warming by past air pollution reductions in Europe,
Nat. Geosci., 9, 277–281, https://doi.org/10.1038/ngeo2673, 2016.
Alexander, M. A., Bhatt, U. S., Walsh, J. E., Timlin, M. S., Miller, J. S.,
and Scott, J. D.: The atmospheric response to realistic Arctic sea ice
anomalies in an AGCM during winter, J. Clim., 17, 890–905, 2004.
Armour, K. C., Marshall, J., Scott, J., Donohoe A., and Newsom, E. R.:
Southern Ocean warming delayed by circumpolar upwelling and equatorward
transport, Nat. Geosci., 9, 549–554, https://doi.org/10.1038/ngeo2731, 2016.
Bader, J., Flügge, M., Kvamstø, N. G., Mesquita M. D. S., and Voigt,
A.: Atmospheric winter response to a projected future Antarctic sea-ice
reduction: a dynamical analysis, Clim. Dynam., 40, 2707–2718, 2013.
Balmaseda, M. A., Ferranti, L., Molteni F., and Palmer, T. N.: Impact of 2007
and 2008 Arctic ice anomalies on the atmospheric circulation: Implciations
for long-range predictions, Q. J. Roy. Meteor. Soc., 136, 1655–1664, 2010.
Barnes, E. A. and Screen, J. A.: The impact of Arctic warming on the
midlatitude jet-stream: Can it? Has it? Will it?, Clim. Change, 6, 277–286,
https://doi.org/10.1002/wcc.337, 2015.
Bindoff, N. L., Stott, P. A., Achuta Rao, K. M., Allen, M. R., Gillett, N.,
Gutzler, D., Hansingo, K., Hegerl, G., Hu, Y., Jain, S., Mokhov, I. I.,
Overland, J., Perlwitz, J., Sebbari R., and Zhang, X.: Detection and
Attribution of Climate Change: from Global to Regional, in: Climate Change
2013: The Physical Science Basis, Contribution of Working Group I to the
Fifth Assessment Report of the Intergovernmental Panel on Climate Change,
edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.
K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge
University Press, Cambridge, UK, New York, NY, USA, 2013.
Bintanja, R., van Oldenborgh, G. J., Drijfhout, S. S., Wouters, B., and
Katsman, C. A.: Important role for ocean warming and increased ice-shelf melt
in Antarctic sea-ice expansion, Nat. Geosci., 6, 376–379, 2013.
Blackport, R. and Kushner, P.: The transient and equilibrium climate response
to rapid summertime sea ice loss in CCSM4, J. Clim., 29, 401–417,
https://doi.org/10.1175/JCLI-D-15-0284.1, 2016.
Blackport, R. and P. J. Kushner: Isolating the atmospheric circulation
response to Arctic sea ice loss in the coupled climate system, J. Clim., 30,
2163–2185, https://doi.org/10.1175/JCLI-D-16-0257.1, 2017.
Boer, G. J., Smith, D. M., Cassou, C., Doblas-Reyes, F., Danabasoglu, G.,
Kirtman, B., Kushnir, Y., Kimoto, M., Meehl, G. A., Msadek, R., Mueller, W.
A., Taylor, K. E., Zwiers, F., Rixen, M., Ruprich-Robert, Y., and Eade, R.:
The Decadal Climate Prediction Project (DCPP) contribution to CMIP6, Geosci.
Model Dev., 9, 3751–3777, https://doi.org/10.5194/gmd-9-3751-2016, 2016.
Bracegirdle, T. J. and Stephenson, D. B.: On the robustness of emergent
constraints used in multimodel climate change projections of Arctic warming,
J. Clim. 26, 669–678, 2013.
Cassano, E. N., Cassano, J. J., Higgins, M. E., and Serreze, M. C.:
Atmospheric impacts of an Arctic sea ice minimum as seen in the Community
Atmosphere Model, Int. J. Climatol., 34, 766–779, https://doi.org/10.1002/joc.3723,
2014.
Chen, H. W., Zhang, F., and Alley, R. B.: The robustness of midlatitude
weather pattern changes due to Arctic sea ice loss, J. Climate, 29,
7831–7849, https://doi.org/10.1175/JCLI-D-16-0167.1, 2016.
Chiang, J. C. H. and Bitz, C. M.: Influence of high latitude ice on the
marine intertropical convergence zone, Clim. Dynam., 25, 477–496,
https://doi.org/10.1007/s00382-005-0040-5, 2005.
Chylek, P., Folland, C. K., Lesins, G., Dubey, M. K., and Wang, M.: Arctic
air temperature change amplification and the Atlantic Multidecadal
Oscillation, Geophys. Res. Lett., 36, L14801, https://doi.org/10.1029/2009GL038777, 2009.
Cohen, J. and Entekhabi, D.: Eurasian snow cover variability and Northern
Hemisphere climate predictability, Geophys. Res. Lett., 26, 345–348,
https://doi.org/10.1029/1998GL900321, 1999.
Cohen, J., Jones, J., Furtado, J. C., and Tziperman, E.: Warm Arctic, cold
continents: A common pattern related to Arctic sea ice melt, snow advance,
and extreme winter weather, Oceanography, 26, 150–160,
https://doi.org/10.5670/oceanog.2013.70, 2013.
Cohen, J., Screen, J. A., Furtado, J. C., Barlow, M., Whittleston, D.,
Coumou, D., Francis, J., Dethloff, K., Entekhabi, D., Overland, J., and
Jones, J.: Recent Arctic amplification and extreme mid-latitude weather, Nat.
Geosci., 7, 627–637, https://doi.org/10.1038/ngeo2234, 2014.
Collins, M., Chandler, R. E., Cox, P. M., Huthnance, J. M., Rougier, J., and
Stephenson, D. B.: Quantifying future climate change, Nat. Clim. Change, 2,
403–409, https://doi.org/10.1038/nclimate1414, 2012.
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T.,
Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G.,
Shongwe, M., Tebaldi, C., Weaver A. J., and Wehner, M.: Long-term Climate
Change: Projections, Commitments and Irreversibility, in: Climate Change
2013: The Physical Science Basis, Contribution of Working Group I to the
Fifth Assessment Report of the Intergovernmental Panel on Climate Change,
edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.
K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge
University Press, Cambridge, UK, New York, NY, USA, 2013.
Collins, W. J., Lamarque, J.-F., Schulz, M., Boucher, O., Eyring, V.,
Hegglin, M. I., Maycock, A., Myhre, G., Prather, M., Shindell, D., and Smith,
S. J.: AerChemMIP: quantifying the effects of chemistry and aerosols in
CMIP6, Geosci. Model Dev., 10, 585–607,
https://doi.org/10.5194/gmd-10-585-2017, 2017.
Cowtan, K. and Way, R. G.: Coverage bias in the HadCRUT4 temperature series
and its impact on recent temperature trends, Q. J. Roy. Meteor. Soc., 133,
459–477, 2013.
Cvijanovic, I., Santer, B. D., Bonfils, C., Lucas, D. D., Chiang, J. C. H.,
and Zimmerman, S.: Future loss of Arctic sea-ice cover could drive a
substantial decrease in California's rainfall, Nature Commun., 8, 1947,
https://doi.org/10.1038/s41467-017-01907-4, 2017.
Deser, C., Tomas, R., Alexander, M., and Lawrence, D.: The seasonal
atmospheric response to projected sea ice loss in the late twenty-first
century, J. Clim., 23, 333–351, 2010.
Deser, C., Tomas, R. A., and Sun, L.: The role of ocean-atmosphere coupling
in the zonal-mean atmospheric response to Arctic sea ice loss, J. Climate,
28, 2168–2186, https://doi.org/10.1175/JCLI-D-14-00325.1, 2015.
Deser, C., Sun, L., Tomas, R. A., and Screen, J.: Does ocean-coupling matter
for the northern extra-tropical response to projected Arctic sea ice loss?
Geophys. Res. Lett., 43, 2149–2157, https://doi.org/10.1002/2016GL067792, 2016.
Ding, Q., Wallace, J. M., Battisti, D. S., Steig, E. J., Galland, A. J. E.,
Kim, H.-J., and Geng, L.: Tropical forcing of the recent rapid Arctic warming
in northeastern Canada and Greenland, Nature, 509, 209–212,
https://doi.org/10.1038/nature13260, 2014.
Ding, Q., Schweiger, A., L'Heureux, M., Battisti, D. S., Po-Chedley, S.,
Johnson, N. C., Blanchard-Wrigglesworth, E., Harnos, K., Zhang, Q., Eastman,
R., and Steig, E. J.: Influence of high-latitude atmospheric circulation
changes on summertime Arctic sea ice, Nat. Clim. Change, 7, 289–295, 2017.
Dunstone, N. J., Smith, D. M., Scaife, A. A., Hermanson, L., Eade, R.,
Robinson, N., Andrews, M., and Knight, J.: Skilful predictions of the winter
North Atlantic Oscillation one year ahead, Nat. Geosci., 9, 809–814,
https://doi.org/10.1038/NGEO2824, 2016.
Eade, R., Smith, D. M., Scaife, A. A., Wallace, E., Dunstone, N., Hermanson,
L., and Robinson, N.: Do seasonal to decadal climate predictions
underestimate the predictability of the real world?, Geophys. Res. Lett., 41,
5620–5628, https://doi.org/10.1002/2014GL061146, 2014.
England, M., Polvani, L., and Sun, L.: Contrasting the Antarctic and Arctic
atmospheric responses to projected sea ice loss in the late 21st Century
Contrasting the Antarctic and Arctic atmospheric responses to projected sea
ice loss in the late 21st Century, J. Climate, 31, 6353–6370,
https://doi.org/10.1175/JCLI-D-17-0666.1, 2018
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R.
J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project
Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9,
1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Feldstein, S. and Lee, S.: Intraseasonal and interdecadal jet shifts in the
Northern Hemisphere: The role of warm pool tropical convection and sea ice,
J. Climate, 27, 6497–6518, https://doi.org/10.1175/JCLI-D-14-00057.1, 2014.
Francis, J. A. and Vavrus, S. J.: Evidence linking Arctic amplification to
extreme weather in mid-latitudes, Geophys. Res. Lett., 39, L06801,
https://doi.org/10.1029/2012GL051000, 2012.
Furtado, J. C., Cohen, J. L., Butler, A. H., Riddle, E. E., and Kumar, A.:
Eurasian snow cover variability and links to winter climate in the CMIP5
models, Clim. Dynam., 45, 2591–2605, 2015.
Fyfe, J. C., von Salzen, K., Gillett, N. P., Arora, V. K., Flato, G. M., and
McConnell, J. R.: One hundred years of Arctic surface temperature variation
due to anthropogenic influence, Sci. Rep., 3, 2645, https://doi.org/10.1038/srep02645,
2013.
Gagné, M.-È., Fyfe, J. C., Gillett, N. P., Polyakov, I. V., and
Flato, G. M.: Aerosol-driven increase in Arctic sea ice over the middle of
the twentieth century, Geophys. Res. Lett., 44, 7338–7346,
https://doi.org/10.1002/2016GL071941, 2017.
García-Serrano, J., Frankignoul, C., Gastineau, G., and de la
Cámara, A.: On the predictability of the winter Euro-Atlantic climate:
lagged influence of autumn Arctic sea ice, J. Clim., 28, 5195–5216, 2015.
García-Serrano, J., Frankignoul, C., King, M. P., Arribas, A., Gao, Y.,
Guemas, V., Matei, D., Msadek, R., Park, W., and Sanchez-Gomez, E.:
Multi-model assessment of linkages between eastern Arctic sea-ice variability
and the Euro-Atlantic atmospheric circulation in current climate, Clim.
Dynam., 49, 2407, https://doi.org/10.1007/s00382-016-3454-3, 2017
Gastineau, G., García-Serrano, J., and Frankignoul, C.: The influence of
autumnal Eurasian snow cover on climate and its link with Arctic sea ice
cover, J. Clim., 19, 7599–7619, 2017.
Gerber, E. P. and Manzini, E.: The Dynamics and Variability Model
Intercomparison Project (DynVarMIP) for CMIP6: assessing the
stratosphere–troposphere system, Geosci. Model Dev., 9, 3413–3425,
https://doi.org/10.5194/gmd-9-3413-2016, 2016.
Graversen, R. G. and Wang, M.: Polar amplification in a coupled climate model
with locked albedo, Clim. Dynam., 33, 629–643, 2009.
Graversen, R., Mauritsen, T., Tjernström, M., Källén, E., and
Svensson, G.: Vertical structure of recent Arctic warming, Nature, 451,
53–56, 2008.
Gillett, N. P., Shiogama, H., Funke, B., Hegerl, G., Knutti, R., Matthes, K.,
Santer, B. D., Stone, D., and Tebaldi, C.: The Detection and Attribution
Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6, Geosci.
Model Dev., 9, 3685–3697, https://doi.org/10.5194/gmd-9-3685-2016, 2016.
Hall, A.: The role of surface albedo feedback in climate, J. Clim., 17,
1550–1568, 2004.
Hall, A. and Qu, X.: Using the current seasonal cycle to constrain the snow
albedo feedback in future climate change, Geophys. Res. Lett., 33, L03502,
https://doi.org/10.1029/2005GL025127, 2006.
Hansen, J., Ruedy, R., Sato, M., and Lo, K.: Global surface temperature
change, Rev. Geophys., 48, RG4004, https://doi.org/10.1029/2010RG000345, 2010.
Haustein, K., Allen, M. R., Forster, P. M., Otto, F. E. L., Mitchell, D. M.,
Matthews, H. D., and Frame, D. J.: A real-time Global Warming Index, Sci.
Rep., 7, 15417, https://doi.org/10.1038/s41598-017-14828-5, 2017.
Hind, A., Zhang, Q., and Brattström, G.: Problems encountered when
defining Arctic amplification as a ratio, Sci. Rep., 6, 30469,
https://doi.org/10.1038/srep30469, 2016.
Holland, M. and Bitz, C.: Polar amplification of climate change in coupled
models, Clim. Dynam., 21, 221–232, 2003.
Honda, M., Yamazaki, K., Tachibana, Y., and Takeuchi, K.: Influence of
Okhotsk sea-ice extent on atmospheric circulation, Geophys. Res. Lett., 23,
3595–3598, https://doi.org/10.1029/96GL03474, 1996.
Honda, M., Inoue, J., and Yamane, S.: Influence of low Arctic sea ice minima
on anomalously cold Eurasian winters. Geophys. Res. Lett., 36, L08707,
https://doi.org/10.1029/2008GL037079, 2009.
Huang, Y., Xia, Y., and Tan, X.: On the pattern of CO2 radiative
forcing and poleward energy transport, J. Geophys. Res.-Atmos., 122,
10578–10593, https://doi.org/10.1002/2017JD027221, 2017
Jaiser, R., Dethloff, K., and Handorf, D.: Stratospheric response to Arctic
sea ice retreat and associated planetary wave propagation changes, Tellus A,
65, 19375, https://doi.org/10.3402/tellusa.v65i0.19375, 2013.
Jones, C. D., Arora, V., Friedlingstein, P., Bopp, L., Brovkin, V., Dunne,
J., Graven, H., Hoffman, F., Ilyina, T., John, J. G., Jung, M., Kawamiya, M.,
Koven, C., Pongratz, J., Raddatz, T., Randerson, J. T., and Zaehle, S.: C4MIP
– The Coupled Climate–Carbon Cycle Model Intercomparison Project:
experimental protocol for CMIP6, Geosci. Model Dev., 9, 2853–2880,
https://doi.org/10.5194/gmd-9-2853-2016, 2016a.
Jones, J. M., Gille, S. T., Goosse, H., Abram, N. J., Canziani, P. O.,
Charman, D. J., Clem, K. R., Crosta, X., de Lavergne, C., Eisenman, I.,
England, M. H., Fogt, R. L., Frankcombe, L. M., Marshall, G. J.,
Masson-Delmotte, V., Morrison, A. K., Orsi, A. J., Raphael, M. N., Renwick,
J. A., Schneider, D. P., Simpkins, G. R., Steig, E. J., Stenni, B.,
Swingedouw, D., and Vance, T. R.: Assessing recent trends in high-latitude
Southern Hemisphere surface climate, Nat. Clim. Change, 6, 917–926,
https://doi.org/10.1038/nclimate3103, 2016b.
Kageyama, M., Braconnot, P., Harrison, S. P., Haywood, A. M., Jungclaus, J.
H., Otto-Bliesner, B. L., Peterschmitt, J.-Y., Abe-Ouchi, A., Albani, S.,
Bartlein, P. J., Brierley, C., Crucifix, M., Dolan, A., Fernandez-Donado, L.,
Fischer, H., Hopcroft, P. O., Ivanovic, R. F., Lambert, F., Lunt, D. J.,
Mahowald, N. M., Peltier, W. R., Phipps, S. J., Roche, D. M., Schmidt, G. A.,
Tarasov, L., Valdes, P. J., Zhang, Q., and Zhou, T.: The PMIP4 contribution
to CMIP6 – Part 1: Overview and over-arching analysis plan, Geosci. Model
Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, 2018.
Karl, T. R., Arguez, A., Huang, B., Lawrimore, J. H., McMahon, J. R., Menne,
M. J., Peterson, T. C., Vose, R. S., and Zhang, H.-M.: Possible artifacts of
data biases in the recent global surface warming hiatus, Science, 348,
1469–1472, 2015.
Khodri, M., Leclainche, Y., Ramstein, G., Braconnot, P., Marti, O., and
Cortijo, E.: Simulating the amplification of orbital forcing by ocean
feedbacks in the last glaciations, Nature, 410, 570–574, 2001.
Kidston, J., Taschetto, A. S., Thompson, D. W. J., and England, M. H.: The
influence of Southern Hemisphere sea-ice extent on the latitude of the
mid-latitude jet stream, Geophys. Res. Lett., 38, L15804,
https://doi.org/10.1029/2011GL048056, 2011.
Kim, B. M., Son, S. W., Min, S. K., Jeong, J. H., Kim, S. J., Zhang, X.,
Shim, T., and Yoon, J. H.: Weakening of the stratospheric polar vortex by
Arctic sea-ice loss, Nat. Commun., 5, 4646, https://doi.org/10.1038/ncomms5646, 2014.
Kravitz, B., Robock, A., Tilmes, S., Boucher, O., English, J. M., Irvine, P.
J., Jones, A., Lawrence, M. G., MacCracken, M., Muri, H., Moore, J. C.,
Niemeier, U., Phipps, S. J., Sillmann, J., Storelvmo, T., Wang, H., and
Watanabe, S.: The Geoengineering Model Intercomparison Project Phase 6
(GeoMIP6): simulation design and preliminary results, Geosci. Model Dev., 8,
3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, 2015.
Kretschmer, M., Coumou, D., Angel, L., Barlow, M., Tziperman, E., and Cohen,
J.: More frequent weak stratospheric polar vortex states linked to
mid-latitude cold extremes, B. Am. Meteorol. Soc., 99, 49–60,
https://doi.org/10.1175/BAMS-D-16-0259.1, 2018.
Kug, J.-S., Jeong, J.-H., Jang, Y.-S., Kim, B.-M., Folland, C. K., Min,
S.-K., and Son, S.-W.: Two distinct influences of Arctic warming on cold
winters over North America and East Asia, Nat. Geosci., 8, 759–762,
https://doi.org/10.1038/ngeo2517, 2015.
Kumar, A., Perlwitz, J., Eischeid, J., Quan, X., Xu, T., Zhang, T., Hoerling,
M., Jha, B., and Wang, W.: Contribution of sea ice loss to Arctic
amplification, Geophys. Res. Lett., 37, L21701, https://doi.org/10.1029/2010GL045022,
2010.
Li, X., Holland, D. M., Gerber, E. P., and Yoo, C.: Impacts of the north and
tropical Atlantic Ocean on the Antarctic Peninsula and sea ice, Nature, 505,
538–542, https://doi.org/10.1038/nature12945, 2014.
Liu, J. P., Curry, J. A., Wang, H., Song, M., and Horton, R. M.: Impact of
declining Arctic sea ice on winter snowfall, P. Natl. Acad. Sci. USA, 109,
4074–4079, https://doi.org/10.1073/pnas.1114910109, 2012.
Manabe, S. and Stouffer, R.: Multiple-century response of a coupled
ocean-atmosphere model to an increase of atmospheric carbon-dioxide, J.
Clim., 7, 5–23, 1994.
Manabe, S. and Wetherald, R. T.: On the distribution of climate change
resulting from an increase in CO2 content of the atmosphere, J.
Atmos. Sci., 37, 99–118, 1980.
Masson-Delmotte, V., Schulz, M., Abe-Ouchi, A., Beer, J., Ganopolski, A.,
González Rouco, J. F., Jansen, E., Lambeck, K., Luterbacher, J., Naish,
T., Osborn, T., Otto-Bliesner, B., Quinn, T., Ramesh, R., Rojas, M., Shao,
X., and Timmermann, A.: Information from Paleoclimate Archives, in: Climate
Change 2013: The Physical Science Basis, Contribution of Working Group I to
the Fifth Assessment Report of the Intergovernmental Panel on Climate Change,
edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.
K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge
University Press, Cambridge, UK, New York, NY, USA, 2013.
McCusker, K. E., Fyfe, J. C., and Sigmond, M.: Twenty-five winters of
unexpected Eurasian cooling unlikely due to Arctic sea ice loss, Nat.
Geosci., 9, 838–842, https://doi.org/10.1038/ngeo2820, 2016.
McCusker, K. E., Kushner, P., Fyfe, J. C., Sigmond, M., Kharin, V. V., and
Bitz, C. M.: Remarkable separability of circulation response to Arctic sea
ice loss and greenhouse gas forcing, Geophys. Res. Lett., 44, 7955–7964,
https://doi.org/10.1002/2017gl074327, 2017.
Menéndez, C., Serafini, V., and Le Treut, H.: The effect of sea-ice on
the transient atmospheric eddies of the Southern Hemisphere, Clim. Dynam.,
15, 659–671, https://doi.org/10.1007/s003820050308, 1999.
Mori, M., Watanabe, M., Shiogama, H., Inoue, J., and Kimoto, M.: Robust
arctic sea ice influence on the frequent Eurasian cold winters in past
decades, Nat. Geosci., 7, 869–873, 2014.
Morice, C. P., Kennedy, J. J., Rayner, N. A., and Jones, P. D.: Quantifying
uncertainties in global and regional temperature change using an ensemble of
observational estimates: the HadCRUT4 data set, J. Geophys. Res., 117,
D08101, https://doi.org/10.1029/2011JD017187, 2012.
Nakamura, T., Yamazaki, K., Iwamoto, K., Honda, M., Miyoshi, Y., Ogawa, Y.,
and Ukita, J.: A negative phase shift of the winter AO/NAO due to the recent
Arctic sea-ice reduction in late autumn, J. Geophys. Res.-Atmos., 120,
3209–3227, https://doi.org/10.1002/2014JD022848, 2015.
Nowicki, S. M. J., Payne, A., Larour, E., Seroussi, H., Goelzer, H.,
Lipscomb, W., Gregory, J., Abe-Ouchi, A., and Shepherd, A.: Ice Sheet Model
Intercomparison Project (ISMIP6) contribution to CMIP6, Geosci. Model Dev.,
9, 4521–4545, https://doi.org/10.5194/gmd-9-4521-2016, 2016.
Ogawa, F., Keenlyside, N., Gao, Y., Koenigk, T., Yang, S., Suo, L., Wang, T.,
Gastineau, G., Nakamura, T., Cheung, H. N., Omrani, N.-E., Ukita, J., and
Semenov, V.: Evaluating impacts of recent Arctic sea ice loss on the northern
hemisphere winter climate change, Geophys. Res. Lett., 45, 3255–3263,
https://doi.org/10.1002/2017GL076502, 2018.
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein,
P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G.
A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model
Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9,
3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016.
Orsolini, Y. J., Senan, R., Benestad, R. E., and Melsom, A.: Autumn
atmospheric response to the 2007 low Arctic sea ice extent in coupled
ocean–atmosphere hindcasts, Clim. Dynam., 38, 2437–2448,
https://doi.org/10.1007/s00382-011-1169-z, 2012.
Oudar, T., Sanchez-Gomez, E., Chauvin, F., Cattiaux, J., Terray, L., and
Cassou, C.: Respective roles of direct GHG radiative forcing and induced
Arctic sea ice loss on the Northern Hemisphere atmospheric circulation, Clim.
Dynam., 49, 3693–3713, https://doi.org/10.1007/s00382-017-3541-0, 2017.
Overland, J. E., Wood, K. R., and Wang, M.: Warm Arctic-cold continents:
Climate impacts of the newly open Arctic Sea, Polar Res., 30, 15787,
https://doi.org/10.3402/polar.v30i0.15787, 2011.
Overland, J., Francis, J., Hall, R., Hanna, E., Kim, S., and Vihma, T.: The
melting arctic and Mid-latitude weather patterns: Are they connected?, J.
Clim., 28, 7917–7932, https://doi.org/10.1175/JCLI-D-14-00822.1, 2015.
Overland, J. E., Dethloff, K., Francis, J. A., Hall, R. J., Hanna, E., Kim,
S.-J., Screen, J. A., Shepherd, T. G., and Vihma, T.: Nonlinear response of
midlatitude weather to the changing Arctic, Nat. Clim. Change, 6, 992–999,
2016.
Overpeck, J., Hughen, K., Hardy, D., Bradley, R., Case, R., Douglas, M.,
Finney, B., Gajewski, K., Jacoby, G., Jennings, A., Lamoureux, S., Lasca, A.,
MacDonald, G., Moore, J., Retelle, M., Smith, S., Wolfe, A., and Zielinski,
G.: Arctic environmental change of the last four centuries, Science, 278,
1251–1256, 1997.
Pedersen, R., Cvijanovic, I., Langen, P., and Vinther, B.: The impact of
regional Arctic sea ice loss on atmospheric circulation and the NAO, J.
Climate, 29, 889–902, https://doi.org/10.1175/JCLI-D-15-0315.1, 2016.
Peings, Y. and Magnusdottir, G.: Response of the wintertime Northern
Hemispheric atmospheric circulation to current and projected Arctic sea ice
decline: a numerical study with CAM5, J. Climate, 27, 244–264, 2014.
Perlwitz, J., Hoerling, M., and Dole, R.: Arctic Tropospheric Warming: Causes
and Linkages to Lower Latitudes, J. Climate, 28, 2154–2167,
https://doi.org/10.1175/JCLI-D-14-00095.1, 2015.
Petoukhov, V. and Semenov, V. A.: A link between reduced Barents-Kara sea ice
and cold winter extremes over northern continents, J. Geophys. Res., 115,
D21111, https://doi.org/10.1029/2009JD013568, 2010.
Petrie, R. E., Shaffrey, L. C., and Sutton, R. T.: Atmospheric Impact of
Arctic Sea Ice Loss in a Coupled Ocean–Atmosphere Simulation, J. Climate,
28, 9606–9622, https://doi.org/10.1175/JCLI-D-15-0316.1, 2015.
Pithan, F. and Mauritsen, T.: Arctic amplification dominated by temperature
feedbacks in contemporary climate models, Nat. Geosci., 7, 181–184,
https://doi.org/10.1038/ngeo2071, 2014.
Purich, A., England, M. H., Cai, W., Chikamoto, Y., Timmermann, A., Fyfe, J.
C., Frankcombe, L., Meehl, G. A., and Arblaster, J. M.: Tropical Pacific SST
drivers of recent Antarctic Sea ice trends, J. Clim., 29, 8931–8948,
https://doi.org/10.1175/JCLI-D-16-0440.1, 2016.
Raphael, M. N., Hobbs, W., and Wainer, I.: The effect of Antarctic sea ice on
the Southern Hemisphere atmosphere during the southern summer, Clim. Dynam.,
36, 1403–1417, https://doi.org/10.1007/s00382-010-0892-1, 2011.
Raphael, M. N., Marshall, G. J., Turner, J., Fogt, R., Schneider, D. P.,
Dixon, D. A., Hosking, J. S., Jones, J., and Hobbs, W.: The Amundsen Sea Low:
Variability, change and impact on Antarctic climate, B. Am. Meteorol. Soc.,
97, 111–121, 2015.
Rinke, A., Dethloff, K., Dorn, W., Handorf, D., and Moore, J. C.: Simulated
Arctic atmospheric feedbacks associated with late summer sea ice anomalies,
J. Geophys. Res.-Atmos., 118, 7698–7714, https://doi.org/10.1002/jgrd.50584, 2013.
Ruane, A. C., Teichmann, C., Arnell, N. W., Carter, T. R., Ebi, K. L.,
Frieler, K., Goodess, C. M., Hewitson, B., Horton, R., Kovats, R. S., Lotze,
H. K., Mearns, L. O., Navarra, A., Ojima, D. S., Riahi, K., Rosenzweig, C.,
Themessl, M., and Vincent, K.: The Vulnerability, Impacts, Adaptation and
Climate Services Advisory Board (VIACS AB v1.0) contribution to CMIP6,
Geosci. Model Dev., 9, 3493–3515, https://doi.org/10.5194/gmd-9-3493-2016,
2016.
Screen, J. A. and Simmonds, I.: The central role of diminishing sea ice in
recent Arctic temperature amplification, Nature, 464, 1334–1337, 2010.
Screen, J. A., Deser, C., and Simmonds, I.: Local and remote controls on
observed Arctic warming, Geophys. Res. Lett., 39, L10709,
https://doi.org/10.1029/2012GL051598, 2012.
Screen, J. A.: Influence of Arctic sea ice on European summer precipitation,
Environ. Res. Lett., 8, 044015, https://doi.org/10.1088/1748-9326/8/4/044015, 2013.
Screen, J. A., Simmonds, I., Deser, C., and Tomas, R.: The atmospheric
response to three decades of observed Arctic sea ice loss, J. Climate, 26,
1230–1248, https://doi.org/10.1175/JCLI-D-12-00063.1, 2013.
Screen, J. A., Deser, C., Simmonds, I., and Tomas, R.: Atmospheric impacts of
Arctic sea ice loss, 1979–2009: Separating forced change from atmospheric
internal variability, Clim. Dynam., 43, 333–344, 2014.
Screen, J. A., Deser, C., and Sun, L.: Reduced risk of North American cold
extremes due to continued Arctic sea ice loss, B. Am. Meteorol. Soc., 96,
1489–1503, https://doi.org/10.1175/BAMS-D-14-00185.1, 2015.
Screen, J. A.: Simulated atmospheric response to regional and pan-Arctic sea
ice loss, J. Clim., 30, 3945–3962, 2017.
Screen, J. A., Deser, C., Smith, D. M., Zhang, X., Blackport, R., Kushner, P.
J., Oudar, T., McCusker, K. E., and Sun, L.: Consistency and discrepancy in
the atmospheric response to Arctic sea-ice loss across climate models, Nat.
Geosci., 11, 155–163, https://doi.org/10.1038/s41561-018-0059-y, 2018.
Scaife, A. A., Arribas, A., Blockley, E., Brookshaw, A., Clark, R. T.,
Dunstone, N., Eade, R., Fereday, D., Folland, C. K., Gordon, M., Hermanson,
L., Knight, J. R., Lea, D. J., MacLachlan, C., Maidens, A., Martin, M.,
Peterson, A. K., Smith, D., Vellinga, M., Wallace, E., Water, J., and
Williams, A.: Skilful long range prediction of European and North American
winters, Geophys. Res. Lett., 41, 2514–2519, https://doi.org/10.1002/2014GL059637, 2014.
Schneider, D. P., Deser, C., and Fan, T.: Comparing the impacts of tropical
SST variability and polar stratospheric ozone loss on the Southern Ocean
westerly winds, J. Climate, 28, 9350–9372, 2015.
Schneider, D. P. and Deser, C.: Tropically driven and externally forced
patterns of Antarctic sea ice change: Reconcilling observed and modeled
trends, Clim. Dynam., 50, 4599–4618, https://doi.org/10.1007/s00382-017-3893-5, 2017.
Semenov, V. A. and Latif, M.: Nonlinear winter atmospheric circulation
response to Arctic sea ice concentration anomalies for different periods
during 1966–2012, Environ. Res. Lett., 10, 054020,
https://doi.org/10.1088/1748-9326/10/5/054020, 2015.
Seierstad, I. and Bader, J.: Impact of a projected future Arctic sea ice
reduction on extratropical storminess and the NAO, Clim. Dynam., 33,
937–943, https://doi.org/10.1007/s00382-008-0463-x, 2009.
Serreze, M. C., Barrett, A. P., Stroeve, J. C., Kindig, D. N., and Holland,
M. M.: The emergence of surface-based Arctic amplification, The Cryosphere,
3, 11–19, https://doi.org/10.5194/tc-3-11-2009, 2009.
Sévellec, F., Fedorov, A. V., and Liu, W.: Arctic sea-ice decline weakens
the Atlantic meridional overturning circulation, Nat. Clim. Change, 7,
604–610, 2017.
Shepherd, T. G.: Effects of a warming Arctic, Science, 353, 989–990, 2016.
Singarayer, J. S., Bamber, J. L., and Valdes, P. J.: Twenty-first-century
climate impacts from a declining Arctic sea ice cover, J. Climate, 19,
1109–1125, https://doi.org/10.1175/JCLI3649.1, 2006.
Smith, K. L. and Polvani, L. M.: Spatial patterns of recent Antarctic surface
temperature trends and the importance of natural variability: lessons from
multiple reconstructions and the CMIP5 models, Clim. Dynam., 48, 2653–2670,
https://doi.org/10.1007/s00382-016-3230-4, 2017.
Smith, D. M., Dunstone, N. J., Scaife, A. A., Fiedler, E. K., Copsey, D., and
Hardiman, S. C.: Atmospheric response to Arctic and Antarctic sea ice: the
importance of ocean-atmosphere coupling and the background state, J. Climate,
30, 4547–4565, https://doi.org/10.1175/JCLI-D-16-0564.1, 2017.
Spielhagen, R. F., Werner, K., Sørensen, S. A., Zamelczyk, K., Kandiano,
E., Budeus, G., Husum, K., Marchitto, T. M., and Hald, M.: Enhanced modern
heat transfer to the arctic by warm Atlantic water, Science, 331, 450–453,
2011.
Strey, S. T., Chapman, W. L., and Walsh, J. E.: The 2007 sea ice minimum:
impacts on the Northern Hemisphere atmosphere in late autumn and early
winter, J. Geophys. Res., 115, D23103, https://doi.org/10.1029/2009JD013294, 2010.
Stroeve, J. C., Kattsov, V., Barrett, A., Serreze, M., Pavlova, T., Holland,
M., and Meier, W. N.: Trends in Arctic sea ice extent from CMIP5, CMIP3 and
observations, Geophys. Res. Lett., 39, L16502, https://doi.org/10.1029/2012GL052676,
2012.
Sun, L., Deser, C., and Tomas, R. A.: Mechanisms of stratospheric and
tropospheric circulation response to projected Arctic sea ice loss, J. Clim.,
28, 7824–7845, https://doi.org/10.1175/JCLI-D-15-0169.1, 2015.
Sun, L., Perlwitz, J. and Hoerling, M.: What caused the recent “Warm Arctic,
Cold Continents” trend pattern in winter temperatures?, Geophys. Res. Lett.,
43, 5345–5352, https://doi.org/10.1002/2016GL069024, 2016.
Suo, L., Gao, Y., Guo, D., and Bethke, I.: Sea-ice free Arctic contributes to
the projected warming minimum in the North Atlantic, Environ. Res. Lett., 12,
074004, https://doi.org/10.1088/1748-9326/aa6a5e, 2017.
Swart, N. C. and Fyfe, J. C.: The influence of recent Antarctic ice sheet
retreat on simulated sea ice area trends, Geophys. Res. Lett., 40,
4328–4332, 2013.
Taylor, K. E., Williamson, D., and Zwiers, F.: The sea surface temperature
and sea-ice concentration boundary conditions for AMIP II simulations, PCMDI
Report No. 60, Program for Climate Model Diagnosis and Intercomparison,
Lawrence Livermore National Laboratory, Livermore, California, 25 pp., 2000.
Taylor P. C., Cai, M., Hu, A., Meehl, J., Washington, W., and Zhang, G. J.: A
decomposition of feedback contributions to polar warming amplification, J.
Clim., 26, 7023–7043, 2013.
Thompson, D. W. J. and Solomon, S.: Interpretation of recent Southern
Hemisphere climate change, Science, 296, 895–899, 2002.
Tokinaga, H., Xie, S.-P., and Mukougawa, H.: Early 20th-century Arctic
warming intensified by Pacific and Atlantic multidecadal variability, P.
Natl. Acad. Sci. USA, 114, 6227–6232, 2017.
Tomas, R. A., Deser, C., and Sun, L.: The role of ocean heat transport in the
global climate response to projected Arctic sea ice loss, J. Clim., 29,
6841–6859, 2016.
Turner, J., Hosking, J. S., Bracegirdle, T. J., Marshall, G. J., and
Phillips, T.: Recent changes in Antarctic Sea Ice, Phil. Trans. R. Soc. A,
373, 20140163, https://doi.org/10.1098/rsta.2014.0163, 2015.
Turner, J. and Comiso, J.: Solve Antarctica's sea-ice puzzle, Nature, 547,
275–277, https://doi.org/10.1038/547275a, 2017.
Vaughan, D. G., Comiso, J. C., Allison, I., Carrasco, J., Kaser, G., Kwok,
R., Mote, P., Murray, T., Paul, F., Ren, J., Rignot, E., Solomina, O.,
Steffen, K., and Zhang, T.: Observations: Cryosphere, in: Climate Change
2013: The Physical Science Basis, Contribution of Working Group I to the
Fifth Assessment Report of the Intergovernmental Panel on Climate Change,
edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.
K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge
University Press, Cambridge, UK, New York, NY, USA, 2013.
Vavrus, S.: The impact of cloud feedbacks on Arctic climate under greenhouse
forcing, J. Clim., 17, 603–615, 2004.
Vihma, T.: Effects of Arctic sea ice decline on weather and climate: A
review, Surv. Geophys., 35, 1175–1214, https://doi.org/10.1007/s10712-014-9284-0, 2014.
Walsh, J. E.: Intensified warming of the Arctic: Causes and impacts on middle
latitudes, Global Planet. Change, 117, 52–63, 2014.
Webb, M. J., Andrews, T., Bodas-Salcedo, A., Bony, S., Bretherton, C. S.,
Chadwick, R., Chepfer, H., Douville, H., Good, P., Kay, J. E., Klein, S. A.,
Marchand, R., Medeiros, B., Siebesma, A. P., Skinner, C. B., Stevens, B.,
Tselioudis, G., Tsushima, Y., and Watanabe, M.: The Cloud Feedback Model
Intercomparison Project (CFMIP) contribution to CMIP6, Geosci. Model Dev.,
10, 359–384, https://doi.org/10.5194/gmd-10-359-2017, 2017.
Wu, Y. and Smith, K. L.: Response of the Northern Hemisphere midlatitude
circulation to Arctic amplification in a simple atmospheric general
circulation model, J. Climate, https://doi.org/10.1175/JCLI-D-15-0602.1, 2016.
Zanchettin, D., Khodri, M., Timmreck, C., Toohey, M., Schmidt, A., Gerber, E.
P., Hegerl, G., Robock, A., Pausata, F. S. R., Ball, W. T., Bauer, S. E.,
Bekki, S., Dhomse, S. S., LeGrande, A. N., Mann, G. W., Marshall, L., Mills,
M., Marchand, M., Niemeier, U., Poulain, V., Rozanov, E., Rubino, A., Stenke,
A., Tsigaridis, K., and Tummon, F.: The Model Intercomparison Project on the
climatic response to Volcanic forcing (VolMIP): experimental design and
forcing input data for CMIP6, Geosci. Model Dev., 9, 2701–2719,
https://doi.org/10.5194/gmd-9-2701-2016, 2016.
Zhang, J. L. and Rothrock, D. A.: Modeling global sea ice with a thickness
and enthalpy distribution model in generalized curvilinear coordinates, Mon.
Weather Rev., 131, 845–861, 2003.
Zhou, T., Turner, A. G., Kinter, J. L., Wang, B., Qian, Y., Chen, X., Wu, B.,
Wang, B., Liu, B., Zou, L., and He, B.: GMMIP (v1.0) contribution to CMIP6:
Global Monsoons Model Inter-comparison Project, Geosci. Model Dev., 9,
3589–3604, https://doi.org/10.5194/gmd-9-3589-2016, 2016.
Short summary
The Polar Amplification Model Intercomparison Project (PAMIP) is an endorsed contribution to the sixth Coupled Model Intercomparison Project (CMIP6). It will investigate the causes and global consequences of polar amplification through coordinated multi-model numerical experiments. This paper documents the experimental protocol.
The Polar Amplification Model Intercomparison Project (PAMIP) is an endorsed contribution to the...
