Articles | Volume 20, issue 3
https://doi.org/10.5194/cp-20-495-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-20-495-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Mar 2024
Research article |
| 13 Mar 2024
| 13 Mar 2024
CO2-driven and orbitally driven oxygen isotope variability in the Early Eocene
Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI 48104, USA
Christopher J. Poulsen
Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI 48104, USA
Department of Earth Sciences, University of Oregon, Eugene, OR 97403, USA
Jiang Zhu
Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO 80301, USA
Jessica E. Tierney
Department of Geosciences, University of Arizona, Tucson, AZ 85721, USA
Jeremy Keeler
Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI 48104, USA
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EGUsphere, https://doi.org/10.5194/egusphere-2025-1616, https://doi.org/10.5194/egusphere-2025-1616, 2025
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This study uses state-of-the-art computer simulations to better understand how the Greenland ice sheet has changed over the past 24,000 years. By comparing model results with geological data, it reveals when and why the ice sheet grew and shrank, helping improve future predictions of sea level rise and climate change.
Magali Verkerk, Thomas J. Aubry, Christopher Smith, Peter O. Hopcroft, Michael Sigl, Jessica E. Tierney, Kevin Anchukaitis, Matthew Osman, Anja Schmidt, and Matthew Toohey
EGUsphere, https://doi.org/10.5194/egusphere-2024-3635, https://doi.org/10.5194/egusphere-2024-3635, 2024
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Large volcanic eruptions can trigger global cooling, affecting human societies. Using ice-core records and simple climate model to simulate volcanic effect over the last 8500 years, we show that volcanic eruptions cool climate by 0.12 °C on average. By comparing model results with temperature recorded by tree rings over the last 1000 years, we demonstrate that our models can predict the large-scale cooling caused by volcanic eruptions, and can be used in case of large eruption in the future.
Xiaodong Zhang, Brett J. Tipple, Jiang Zhu, William D. Rush, Christian A. Shields, Joseph B. Novak, and James C. Zachos
Clim. Past, 20, 1615–1626, https://doi.org/10.5194/cp-20-1615-2024, https://doi.org/10.5194/cp-20-1615-2024, 2024
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This study is motivated by the current anthropogenic-warming-forced transition in regional hydroclimate. We use observations and model simulations during the Paleocene–Eocene Thermal Maximum (PETM) to constrain the regional/local hydroclimate response. Our findings, based on multiple observational evidence within the context of model output, suggest a transition toward greater aridity and precipitation extremes in central California during the PETM.
Sarah L. Bradley, Raymond Sellevold, Michele Petrini, Miren Vizcaino, Sotiria Georgiou, Jiang Zhu, Bette L. Otto-Bliesner, and Marcus Lofverstrom
Clim. Past, 20, 211–235, https://doi.org/10.5194/cp-20-211-2024, https://doi.org/10.5194/cp-20-211-2024, 2024
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The Last Glacial Maximum (LGM) was the most recent period with large ice sheets in Europe and North America. We provide a detailed analysis of surface mass and energy components for two time periods that bracket the LGM: 26 and 21 ka BP. We use an earth system model which has been adopted for modern ice sheets. We find that all Northern Hemisphere ice sheets have a positive surface mass balance apart from the British and Irish ice sheets and the North American ice sheet complex.
Jonathan King, Jessica Tierney, Matthew Osman, Emily J. Judd, and Kevin J. Anchukaitis
Geosci. Model Dev., 16, 5653–5683, https://doi.org/10.5194/gmd-16-5653-2023, https://doi.org/10.5194/gmd-16-5653-2023, 2023
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Paleoclimate data assimilation is a useful method that allows researchers to combine climate models with natural archives of past climates. However, it can be difficult to implement in practice. To facilitate this method, we present DASH, a MATLAB toolbox. The toolbox provides routines that implement common steps of paleoclimate data assimilation, and it can be used to implement assimilations for a wide variety of time periods, spatial regions, data networks, and analytical algorithms.
Andrew Gettelman, Hugh Morrison, Trude Eidhammer, Katherine Thayer-Calder, Jian Sun, Richard Forbes, Zachary McGraw, Jiang Zhu, Trude Storelvmo, and John Dennis
Geosci. Model Dev., 16, 1735–1754, https://doi.org/10.5194/gmd-16-1735-2023, https://doi.org/10.5194/gmd-16-1735-2023, 2023
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Clouds are a critical part of weather and climate prediction. In this work, we document updates and corrections to the description of clouds used in several Earth system models. These updates include the ability to run the scheme on graphics processing units (GPUs), changes to the numerical description of precipitation, and a correction to the ice number. There are big improvements in the computational performance that can be achieved with GPU acceleration.
Martin Renoult, Navjit Sagoo, Jiang Zhu, and Thorsten Mauritsen
Clim. Past, 19, 323–356, https://doi.org/10.5194/cp-19-323-2023, https://doi.org/10.5194/cp-19-323-2023, 2023
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The relationship between the Last Glacial Maximum and the sensitivity of climate models to a doubling of CO2 can be used to estimate the true sensitivity of the Earth. However, this relationship has varied in successive model generations. In this study, we assess multiple processes at the Last Glacial Maximum which weaken this relationship. For example, how models respond to the presence of ice sheets is a large contributor of uncertainty.
Ryan A. Green, Laurie Menviel, Katrin J. Meissner, Xavier Crosta, Deepak Chandan, Gerrit Lohmann, W. Richard Peltier, Xiaoxu Shi, and Jiang Zhu
Clim. Past, 18, 845–862, https://doi.org/10.5194/cp-18-845-2022, https://doi.org/10.5194/cp-18-845-2022, 2022
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Climate models are used to predict future climate changes and as such, it is important to assess their performance in simulating past climate changes. We analyze seasonal sea-ice cover over the Southern Ocean simulated from numerical PMIP3, PMIP4 and LOVECLIM simulations during the Last Glacial Maximum (LGM). Comparing these simulations to proxy data, we provide improved estimates of LGM seasonal sea-ice cover. Our estimate of summer sea-ice extent is 20 %–30 % larger than previous estimates.
Masa Kageyama, Sandy P. Harrison, Marie-L. Kapsch, Marcus Lofverstrom, Juan M. Lora, Uwe Mikolajewicz, Sam Sherriff-Tadano, Tristan Vadsaria, Ayako Abe-Ouchi, Nathaelle Bouttes, Deepak Chandan, Lauren J. Gregoire, Ruza F. Ivanovic, Kenji Izumi, Allegra N. LeGrande, Fanny Lhardy, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, André Paul, W. Richard Peltier, Christopher J. Poulsen, Aurélien Quiquet, Didier M. Roche, Xiaoxu Shi, Jessica E. Tierney, Paul J. Valdes, Evgeny Volodin, and Jiang Zhu
Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, https://doi.org/10.5194/cp-17-1065-2021, 2021
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The Last Glacial Maximum (LGM; ~21 000 years ago) is a major focus for evaluating how well climate models simulate climate changes as large as those expected in the future. Here, we compare the latest climate model (CMIP6-PMIP4) to the previous one (CMIP5-PMIP3) and to reconstructions. Large-scale climate features (e.g. land–sea contrast, polar amplification) are well captured by all models, while regional changes (e.g. winter extratropical cooling, precipitations) are still poorly represented.
Jiang Zhu and Christopher J. Poulsen
Clim. Past, 17, 253–267, https://doi.org/10.5194/cp-17-253-2021, https://doi.org/10.5194/cp-17-253-2021, 2021
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Climate sensitivity has been directly calculated from paleoclimate data. This approach relies on good understandings of climate forcings and interactions within the Earth system. We conduct Last Glacial Maximum simulations using a climate model to quantify the forcing and efficacy of ice sheets and greenhouse gases and to directly estimate climate sensitivity in the model. Results suggest that the direct calculation overestimates the truth by 25 % due to neglecting ocean dynamical feedback.
Daniel J. Lunt, Fran Bragg, Wing-Le Chan, David K. Hutchinson, Jean-Baptiste Ladant, Polina Morozova, Igor Niezgodzki, Sebastian Steinig, Zhongshi Zhang, Jiang Zhu, Ayako Abe-Ouchi, Eleni Anagnostou, Agatha M. de Boer, Helen K. Coxall, Yannick Donnadieu, Gavin Foster, Gordon N. Inglis, Gregor Knorr, Petra M. Langebroek, Caroline H. Lear, Gerrit Lohmann, Christopher J. Poulsen, Pierre Sepulchre, Jessica E. Tierney, Paul J. Valdes, Evgeny M. Volodin, Tom Dunkley Jones, Christopher J. Hollis, Matthew Huber, and Bette L. Otto-Bliesner
Clim. Past, 17, 203–227, https://doi.org/10.5194/cp-17-203-2021, https://doi.org/10.5194/cp-17-203-2021, 2021
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This paper presents the first modelling results from the Deep-Time Model Intercomparison Project (DeepMIP), in which we focus on the early Eocene climatic optimum (EECO, 50 million years ago). We show that, in contrast to previous work, at least three models (CESM, GFDL, and NorESM) produce climate states that are consistent with proxy indicators of global mean temperature and polar amplification, and they achieve this at a CO2 concentration that is consistent with the CO2 proxy record.
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Short summary
In this study, we use climate modeling to investigate the relative impact of CO2 and orbit on Early Eocene (~ 55 million years ago) climate and compare our modeled results to fossil records to determine the context for the Paleocene–Eocene Thermal Maximum, the most extreme hyperthermal in the Cenozoic. Our conclusions consider limitations and illustrate the importance of climate models when interpreting paleoclimate records in times of extreme warmth.
In this study, we use climate modeling to investigate the relative impact of CO2 and orbit on...
