Articles | Volume 16, issue 19
https://doi.org/10.5194/gmd-16-5515-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5515-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
04 Oct 2023
Model description paper |
| 04 Oct 2023
| 04 Oct 2023
All aboard! Earth system investigations with the CH2O-CHOO TRAIN v1.0
Department of Geosciences, Colorado State University, Fort Collins, CO, USA
Daniel E. Ibarra
Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI, USA
Institute at Brown for Environment and Society, Brown University, Providence, RI, USA
Kimberly V. Lau
Department of Geosciences and Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, USA
Jeremy K. C. Rugenstein
CORRESPONDING AUTHOR
Department of Geosciences, Colorado State University, Fort Collins, CO, USA
Max Planck Institute for Meteorology, Hamburg, Germany
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Livia Manser, Tyler Kukla, and Jeremy K. C. Rugenstein
Clim. Past, 20, 1039–1065, https://doi.org/10.5194/cp-20-1039-2024, https://doi.org/10.5194/cp-20-1039-2024, 2024
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The Great Plains host the single most important climatic boundary in North America, separating the humid east from the semi-arid west. How this boundary will move as the world warms holds implications for the societies and ecosystems of the Plains. We study how this boundary changed in the past during a period of globally warmer temperatures. We find that this climatic boundary appears to be in the same location as today, suggesting that the Great Plains climate is resilient to global changes.
Daniel E. Ibarra, Carlos Primo C. David, and Pamela Louise M. Tolentino
Hydrol. Earth Syst. Sci., 25, 2805–2820, https://doi.org/10.5194/hess-25-2805-2021, https://doi.org/10.5194/hess-25-2805-2021, 2021
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We evaluate a recently published global product of monthly runoff using streamflow data from small tropical catchments in the Philippines. Using monthly runoff observations from catchments, we tested for correlation and prediction. We demonstrate the potential utility of this product in assessing trends in regional-scale runoff, as well as look at the correlation of phenomenon such as the El Niño–Southern Oscillation on streamflow in this wet but drought-prone archipelago.
Yuan Gao, Youfeng Gao, Daniel E. Ibarra, Xiaojing Du, Tian Dong, Zhifei Liu, and Chengshan Wang
Clim. Past Discuss., https://doi.org/10.5194/cp-2020-36, https://doi.org/10.5194/cp-2020-36, 2020
Revised manuscript not accepted
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We present a high-resolution clay mineralogical record in continental Songliao Basin of NE China from the latest Cretaceous through the earliest Paleogene. Three clay mineralogical proxies are used for paleoclimatic reconstructions and are correlated with marine records.
Fluctuations in terrestrial climate occurred during the latest Cretaceous and across the K-Pg boundary when warming (cooling) caused increasing (decreasing) precipitation and intensified (weakened) chemical weathering.
Louis Honegger, Thierry Adatte, Jorge E. Spangenberg, Jeremy K. Caves Rugenstein, Miquel Poyatos-Moré, Cai Puigdefàbregas, Emmanuelle Chanvry, Julian Clark, Andrea Fildani, Eric Verrechia, Kalin Kouzmanov, Matthieu Harlaux, and Sébastien Castelltort
Clim. Past, 16, 227–243, https://doi.org/10.5194/cp-16-227-2020, https://doi.org/10.5194/cp-16-227-2020, 2020
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A geochemical study of a continental section reveals a rapid global warming event (hyperthermal U), occurring ca. 50 Myr ago, only described until now in marine sediment cores. Documenting how the Earth system responded to rapid climatic shifts provides fundamental information to constrain climatic models. Our results suggest that continental deposits can be high-resolution recorders of these warmings. They also give an insight on the climatic conditions occurring during at the time.
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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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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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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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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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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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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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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.
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.
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.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
EGUsphere, https://doi.org/10.5194/egusphere-2024-923, https://doi.org/10.5194/egusphere-2024-923, 2024
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The regional Earth system model GCOAST-AHOI version 2.0 including the regional climate model ICON-CLM coupled with 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 the ICON-CLM model makes it more flexible to couple with an external ocean model and an external hydrological discharge model.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-362, https://doi.org/10.5194/egusphere-2024-362, 2024
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In this study, we improve an existing climate model to account for human water usage across domestic, industrial, and agriculture purposes. With the new capabilities, the model is now better equipped for studying questions related to water scarcity in both present and future conditions under climate change. Despite the advancements, there remains important limitations in our modelling framework which requires further work.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-36, https://doi.org/10.5194/gmd-2024-36, 2024
Revised manuscript accepted for GMD
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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. Discuss., https://doi.org/10.5194/gmd-2024-49, https://doi.org/10.5194/gmd-2024-49, 2024
Revised manuscript accepted for GMD
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We study the parameters involved in the turbulent kinetic energy mixed layer penetration scheme of the NEMO model in Arctic sea ice-covered regions. This evaluation reveals the impact of these parameters on mixed layer depth, sea surface temperature and salinity, and ocean stratification. Our findings also demonstrate considerable impacts on sea ice thickness and sea ice concentration, emphasizing the importance of accurate ocean mixing representation in understanding Arctic climate dynamics.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-211, https://doi.org/10.5194/gmd-2023-211, 2024
Revised manuscript accepted for GMD
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Methane (CH4) cycling in the Baltic Sea is studied through model simulations, allowing 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 (87 % of the sinks) and outgassing to the atmosphere (13 % of the sinks). This study addresses CH4 emissions from coastal seas and is a first step towards understanding the relative importance of open water outgassing compared to local coastal hotspots.
Cited articles
Abbot, D. S., Cowan, N. B., and Ciesla, F. J.: Indication of Insensitivity of
Planetary Weathering Behavior and Habitable Zone to Surface Land Fraction,
Astrophys. J., 756, 178, https://doi.org/10.1088/0004-637X/756/2/178, 2012. a
Arndt, S., Regnier, P., Goddéris, Y., and Donnadieu, Y.: GEOCLIM reloaded (v 1.0): a new coupled earth system model for past climate change, Geosci. Model Dev., 4, 451–481, https://doi.org/10.5194/gmd-4-451-2011, 2011. a
Baum, M., Fu, M., and Bourguet, S.: Sensitive Dependence of Global
Climate to Continental Geometry, Geophys. Res. Lett., 49, e2022GL098843,
https://doi.org/10.1029/2022GL098843, 2022. a, b, c, d
Bergman, N. M.: COPSE: A New Model of Biogeochemical Cycling over
Phanerozoic Time, Am. J. Sci., 304, 397–437,
https://doi.org/10.2475/ajs.304.5.397, 2004. a, b, c, d
Berner, R. A.: A Model for Atmospheric CO2 over Phanerozoic Time,
Am. J. Sci., 291, 339–376, https://doi.org/10.2475/ajs.291.4.339,
1991. a, b, c
Berner, R. A.: GEOCARB II; a Revised Model of Atmospheric CO 2 over
Phanerozoic Time, Am. J. Sci., 294, 56–91,
https://doi.org/10.2475/ajs.294.1.56, 1994. a, b
Berner, R. A.: The Phanerozoic Carbon Cycle: CO2 and O2, Oxford
University Press, New York, https://doi.org/10.1093/oso/9780195173338.001.0001, 2004. a
Berner, R. A.: GEOCARBSULF: A Combined Model for Phanerozoic
Atmospheric O2 and CO2, Geochim. Cosmochim. Ac., 70,
5653–5664, https://doi.org/10.1016/j.gca.2005.11.032, 2006. a
Bluth, G. J. S. and Kump, L. R.: Lithologic and Climatologic Controls of River
Chemistry, Geochim. Cosmochim. Ac., 58, 2341–2359,
https://doi.org/10.1016/0016-7037(94)90015-9, 1994. a, b
Brady, P. V.: The Effect of Silicate Weathering on Global
Temperature and Atmospheric CO2, J. Geophys. Res., 96,
18101–18106,
https://doi.org/10.1029/91JB01898, 1991. a
Broecker, W.: Long-Term Water Prospects in the Western United States,
J. Climate, 23, 6669–6683, https://doi.org/10.1175/2010JCLI3780.1, 2010. a
Brook, G. A., Folkoff, M. E., and Box, E. O.: A World Model of Soil Carbon
Dioxide, Earth Surf. Proc. Land., 8, 79–88,
https://doi.org/10.1002/esp.3290080108, 1983. a, b
Budyko, M. I.: The Effect of Solar Radiation Variations on the Climate of the
Earth, Tellus, 21, 611–619, https://doi.org/10.1111/j.2153-3490.1969.tb00466.x,
1969. a
Caves, J. K., Jost, A. B., Lau, K. V., and Maher, K.: Cenozoic Carbon Cycle
Imbalances and a Variable Weathering Feedback,
Earth Planet. Sc. Lett., 450, 152–163, https://doi.org/10.1016/j.epsl.2016.06.035, 2016. a, b, c
Caves Rugenstein, J. K., Ibarra, D. E., and von Blanckenburg, F.: Neogene
Cooling Driven by Land Surface Reactivity Rather than Increased Weathering
Fluxes, Nature, 571, 99–102, https://doi.org/10.1038/s41586-019-1332-y, 2019. a, b
Charney, J. G.: Dynamics of Deserts and Drought in the Sahel,
Q. J. Roy. Meteor. Soc., 101, 193–202,
https://doi.org/10.1002/qj.49710142802, 1975. a, b
Claussen, M.: Modeling Bio-Geophysical Feedback in the African and
Indian Monsoon Region, Clim. Dynam., 13, 247–257,
https://doi.org/10.1007/s003820050164, 1997. a, b
Colbourn, G., Ridgwell, A., and Lenton, T. M.: The Rock Geochemical Model (RokGeM) v0.9, Geosci. Model Dev., 6, 1543–1573, https://doi.org/10.5194/gmd-6-1543-2013, 2013. a, b
Coogan, L. A. and Dosso, S. E.: Alteration of Ocean Crust Provides a Strong
Temperature Dependent Feedback on the Geological Carbon Cycle and Is a
Primary Driver of the Sr-isotopic Composition of Seawater, Earth Planet. Sc. Lett., 415, 38–46, https://doi.org/10.1016/j.epsl.2015.01.027,
2015. a
Coogan, L. A. and Gillis, K. M.: Evidence That Low-Temperature Oceanic
Hydrothermal Systems Play an Important Role in the Silicate-Carbonate
Weathering Cycle and Long-Term Climate Regulation,
Geochem. Geophy. Geosy., 14, 1771–1786, https://doi.org/10.1002/ggge.20113, 2013. a
Coogan, L. A. and Gillis, K. M.: Low-Temperature Alteration of the
Seafloor: Impacts on Ocean Chemistry,
Annu. Rev. Earth Planet. Sc., 46, 21–45, https://doi.org/10.1146/annurev-earth-082517-010027,
2018. a
Cotton, J. M. and Sheldon, N. D.: New Constraints on Using Paleosols to
Reconstruct Atmospheric pCO2, Geol. Soc. Am. Bull.,
124, 1411–1423, https://doi.org/10.1130/B30607.1, 2012. a
Cotton, J. M., Jeffery, M. L., and Sheldon, N. D.: Climate Controls on Soil
Respired CO2 in the United States: Implications for 21st Century
Chemical Weathering Rates in Temperate and Arid Ecosystems,
Chem. Geol.,
358, 37–45, https://doi.org/10.1016/j.chemgeo.2013.08.048, 2013. a
Cui, Y., Kump, L. R., Ridgwell, A. J., Charles, A. J., Junium, C. K.,
Diefendorf, A. F., Freeman, K. H., Urban, N. M., and Harding, I. C.: Slow
Release of Fossil Carbon during the Palaeocene-Eocene Thermal
Maximum, Nat. Geosci., 4, 481–485, https://doi.org/10.1038/ngeo1179, 2011. a, b
Datseris, G. and Stevens, B.: Earth's Albedo and Its Symmetry,
AGU Advances, 2, e2021AV000440, https://doi.org/10.1029/2021AV000440, 2021. a
DeConto, R. M., Pollard, D., Wilson, P. A., Pälike, H., Lear, C. H., and
Pagani, M.: Thresholds for Cenozoic Bipolar Glaciation, Nature, 455,
652–656, https://doi.org/10.1038/nature07337, 2008. a
Donnadieu, Y., Goddéris, Y., Ramstein, G., Nédélec, A., and Meert,
J.: A `Snowball Earth' Climate Triggered by Continental Break-up through
Changes in Runoff, Nature, 428, 303–306, https://doi.org/10.1038/nature02408, 2004. a
Edwards, N. R. and Marsh, R.: Uncertainties Due to Transport-Parameter
Sensitivity in an Efficient 3-D Ocean-Climate Model, Clim. Dynam.,
24, 415–433, https://doi.org/10.1007/s00382-004-0508-8, 2005. a
Feldl, N. and Merlis, T. M.: Polar Amplification in Idealized Climates: The
Role of Ice, Moisture, and Seasons, Geophys. Res. Lett., 48, e2021GL094130,
https://doi.org/10.1029/2021GL094130, 2021. a
Flannery, B. P.: Energy Balance Models Incorporating Transport of
Thermal and Latent Energy, J. Atmos. Sci., 41,
414–421, https://doi.org/10.1175/1520-0469(1984)041<0414:EBMITO>2.0.CO;2, 1984. a, b, c
Francois, L. M. and Walker, J. C. G.: Modelling the Phanerozoic Carbon
Cycle and Climate; Constraints from the 87 Sr/ 86 Sr Isotopic Ratio
of Seawater, Am. J. Sci., 292, 81–135,
https://doi.org/10.2475/ajs.292.2.81, 1992. a, b, c
Frieling, J., Svensen, H. H., Planke, S., Cramwinckel, M. J., Selnes, H., and
Sluijs, A.: Thermogenic Methane Release as a Cause for the Long Duration of
the PETM, P. Natl. Acad. Sci. USA, 113,
201603348, https://doi.org/10.1073/PNAS.1603348113, 2016. a, b
Frierson, D. M. W., Held, I. M., and Zurita-Gotor, P.: A Gray-Radiation
Aquaplanet Moist GCM. Part II: Energy Transports in Altered
Climates, J. Atmos. Sci., 64, 1680–1693,
https://doi.org/10.1175/JAS3913.1, 2006. a, b, c
Gaillardet, J., Calmels, D., Romero-Mujalli, G., Zakharova, E., and Hartmann,
J.: Global Climate Control on Carbonate Weathering Intensity, Chem. Geol., 527, 118762, https://doi.org/10.1016/j.chemgeo.2018.05.009, 2019. a
Gibbs, M. T. and Kump, L. R.: Global Chemical Erosion during the Last Glacial
Maximum and the Present: Sensitivity to Changes in Lithology and
Hydrology, Paleoceanography, 9, 529–543, https://doi.org/10.1029/94PA01009, 1994. a, b
Goddéris, Y. and Joachimski, M. M.: Global Change in the Late Devonian:
Modelling the Frasnian-Famennian Short-Term Carbon Isotope
Excursions, Palaeogeogr. Palaeocl., 202, 309–329,
https://doi.org/10.1016/S0031-0182(03)00641-2, 2004. a, b
Graham, R. J. and Pierrehumbert, R.: Thermodynamic and Energetic Limits on
Continental Silicate Weathering Strongly Impact the Climate and
Habitability of Wet, Rocky Worlds, Astrophys. J.,
896, 115, https://doi.org/10.3847/1538-4357/ab9362, 2020. a, b
Greve, P., Gudmundsson, L., Orlowsky, B., and Seneviratne, S. I.: Introducing a
Probabilistic Budyko Framework, Geophys. Res. Lett., 42,
2261–2269, https://doi.org/10.1002/2015GL063449, 2015. a, b
Gutjahr, M., Ridgwell, A., Sexton, P. F., Anagnostou, E., Pearson, P. N.,
Pälike, H., Norris, R. D., Thomas, E., and Foster, G. L.: Very Large
Release of Mostly Volcanic Carbon during the
Palaeocene-Eocene Thermal Maximum, Nature, 548, 573–577,
https://doi.org/10.1038/nature23646, 2017. a, b
Hill, S. A., Burls, N. J., Fedorov, A., and Merlis, T. M.: Symmetric and
Antisymmetric Components of Polar-Amplified Warming, J. Climate, 35, number 20, 6757–6772,
1–49, https://doi.org/10.1175/JCLI-D-20-0972.1, 2022. a
Hilton, R. G. and West, A. J.: Mountains, Erosion and the Carbon Cycle, Nat.
Rev. Earth Environ., 1, 284–299, https://doi.org/10.1038/s43017-020-0058-6,
2020. a
Holden, P. B., Edwards, N. R., Fraedrich, K., Kirk, E., Lunkeit, F., and Zhu, X.: PLASIM–GENIE v1.0: a new intermediate complexity AOGCM, Geosci. Model Dev., 9, 3347–3361, https://doi.org/10.5194/gmd-9-3347-2016, 2016. a, b, c
Hülse, D., Arndt, S., Daines, S., Regnier, P., and Ridgwell, A.: OMEN-SED 1.0: a novel, numerically efficient organic matter sediment diagenesis module for coupling to Earth system models, Geosci. Model Dev., 11, 2649–2689, https://doi.org/10.5194/gmd-11-2649-2018, 2018. a
Hwang, Y. T. and Frierson, D. M.: Increasing Atmospheric Poleward Energy
Transport with Global Warming, Geophys. Res. Lett., 37, 1–5,
https://doi.org/10.1029/2010GL045440, 2010. a, b, c
Ibarra, D. E., Caves, J. K., Moon, S., Thomas, D. L., Hartmann, J.,
Chamberlain, C. P., and Maher, K.: Differential Weathering of Basaltic and
Granitic Catchments from Concentration-Discharge Relationships, Geochim.
Cosmochim. Ac., 190, 265–293, https://doi.org/10.1016/j.gca.2016.07.006, 2016. a
Ibarra, D. E., Moon, S., Caves, J. K., Chamberlain, C. P., and Maher, K.:
Concentration-Discharge Patterns of Weathering Products from
Global Rivers, Acta Geochimica, 36, 405–409,
https://doi.org/10.1007/s11631-017-0177-z, 2017. a
Jellinek, A. M., Lenardic, A., and Pierrehumbert, R. T.: Ice, Fire, or
Fizzle: The Climate Footprint of Earth's Supercontinental
Cycles, Geochem. Geophy. Geosy., 21, e2019GC008464,
https://doi.org/10.1029/2019GC008464, 2020. a, b, c
Key, R. M., Kozyr, A., Sabine, C. L., Lee, K., Wanninkhof, R., Bullister,
J. L., Feely, R. A., Millero, F. J., Mordy, C., and Peng, T.-H.: A Global
Ocean Carbon Climatology: Results from Global Data Analysis Project
(GLODAP): GLOBAL OCEAN CARBON CLIMATOLOGY, Global Biogeochem.
Cy., 18, 4, https://doi.org/10.1029/2004GB002247, 2004. a
Koll, D. D. B. and Cronin, T. W.: Earth's Outgoing Longwave Radiation Linear
Due to H2 O Greenhouse Effect, P.
Natl. Acad. Sci. USA, 115, 10293–10298,
https://doi.org/10.1073/pnas.1809868115, 2018. a
Kölling, M., Bouimetarhan, I., Bowles, M. W., Felis, T., Goldhammer, T.,
Hinrichs, K.-U., Schulz, M., and Zabel, M.: Consistent CO2 Release by
Pyrite Oxidation on Continental Shelves Prior to Glacial Terminations, Nat. Geosci., 12, 929–934, https://doi.org/10.1038/s41561-019-0465-9, 2019. a
Koster, R. D., Fekete, B. M., Huffman, G. J., and Stackhouse, P. W.: Revisiting
a Hydrological Analysis Framework with International Satellite Land Surface
Climatology Project Initiative 2 Rainfall, Net Radiation, and Runoff
Fields, J. Geophys. Res., 111, D22S05,
https://doi.org/10.1029/2006JD007182, 2006. a
Kukla, T., Ibarra, D., Lau, K., and Rugenstein, J. K. C.: Project Files, Data,
and Code, Zenodo [code], https://doi.org/10.5281/zenodo.8045412, 2023. a, b
Kump, L. R. and Alley, R. B.: Global Chemical Weathering on Glacial Time
Scales, in: Material Fluxes on the Surface of the Earth, Board on
Earth Sciences and Resources, National Research Council,
Washington, D.C., 44–60, 1994. a
Kump, L. R. and Arthur, M. A.: Global Chemical Erosion during the
Cenozoic: Weatherability Balances the Budgets, in: Tectonic
Uplift and Climate Change, Springer, US,
Boston, MA 399–426, https://doi.org/10.1007/978-1-4615-5935-1,
1997. a
Kump, L. R. and Arthur, M. A.: Interpreting Carbon-Isotope Excursions:
Carbonates and Organic Matter, Chem. Geol., 161, 181–198,
https://doi.org/10.1016/S0009-2541(99)00086-8, 1999. a, b
Kump, L. R., Brantley, S. L., and a. Arthur, M.: Chemical Weathering,
Atmospheric CO2, and Climate, Annu. Rev. Earth Planet. Sci.
28,
611–667, 2000. a
Lasaga, A. C.: Chemical Kinetics of Water-Rock Interactions, J. Geophys. Res.-Sol. Ea., 89, 4009–4025,
https://doi.org/10.1029/JB089iB06p04009, 1984. a
Lenton, T. M., Daines, S. J., and Mills, B. J.: COPSE Reloaded: An
Improved Model of Biogeochemical Cycling over Phanerozoic Time,
Earth-Sci. Rev., 178, 1–28, https://doi.org/10.1016/j.earscirev.2017.12.004,
2018. a, b, c
Maher, K.: The Dependence of Chemical Weathering Rates on Fluid Residence Time,
Earth Planet. Sc. Lett., 294, 101–110,
https://doi.org/10.1016/j.epsl.2010.03.010, 2010. a
Maher, K.: The Role of Fluid Residence Time and Topographic Scales in
Determining Chemical Fluxes from Landscapes, Earth Planet. Sc. Lett., 312, 48–58, https://doi.org/10.1016/j.epsl.2011.09.040, 2011. a, b
Marsh, R., Müller, S. A., Yool, A., and Edwards, N. R.: Incorporation of the C-GOLDSTEIN efficient climate model into the GENIE framework: ”eb_go_gs” configurations of GENIE, Geosci. Model Dev., 4, 957–992, https://doi.org/10.5194/gmd-4-957-2011, 2011. a
Mazzia, F., Cash, J. R., and Soetaert, K.: Solving Boundary Value Problems in
the Open Source Software R: Package bvpSolve, Opuscula mathematica,
34, 387–403, 2014. a
Mills, J. V., Gomes, M. L., Kristall, B., Sageman, B. B., Jacobson, A. D., and
Hurtgen, M. T.: Massive Volcanism, Evaporite Deposition, and the Chemical
Evolution of the Early Cretaceous Ocean, Geology, 45, G38667.1,
https://doi.org/10.1130/G38667.1, 2017. a
Moon, S., Chamberlain, C., and Hilley, G.: New Estimates of Silicate Weathering
Rates and Their Uncertainties in Global Rivers, Geochim. Cosmochim. Ac., 134, 257–274, https://doi.org/10.1016/j.gca.2014.02.033, 2014. a
Morse, J. W. and Arvidson, R. S.: The Dissolution Kinetics of Major Sedimentary
Carbonate Minerals, Earth-Sci. Rev., 58, 51–84,
https://doi.org/10.1016/S0012-8252(01)00083-6, 2002. a
Murphy, B., Farley, K., and Zachos, J.: An Extraterrestrial 3He-based
Timescale for the Paleocene-Eocene Thermal Maximum
(PETM) from Walvis Ridge, IODP Site 1266, Geochim. Cosmochim. Ac., 74, 5098–5108, https://doi.org/10.1016/j.gca.2010.03.039, 2010. a
North, G. R., Cahalan, R. F., and Coakley, J. A.: Energy Balance Climate
Models, Rev. Geophys. Space Phys., 19, 91–121,
https://doi.org/10.1029/RG019i001p00091, 1981. a
Otto-Bliesner, B. L.: Continental Drift, Runoff, and Weathering Feedbacks:
Implications from Climate Model Experiments, J. Geophys. Res., 100, 11537, https://doi.org/10.1029/95JD00591, 1995. a
Ozaki, K. and Tajika, E.: Biogeochemical Effects of Atmospheric Oxygen
Concentration, Phosphorus Weathering, and Sea-Level Stand on Oceanic Redox
Chemistry: Implications for Greenhouse Climates, Earth Planet. Sc. Lett., 373, 129–139, https://doi.org/10.1016/j.epsl.2013.04.029, 2013. a, b
Park, Y., Maffre, P., Goddéris, Y., Macdonald, F. A., Anttila, E. S. C.,
and Swanson-Hysell, N. L.: Emergence of the Southeast Asian Islands as
a Driver for Neogene Cooling, P. Natl. Acad.
Sci. USA, 117, 25319–25326, https://doi.org/10.1073/pnas.2011033117, 2020. a
Peterson, H. G. and Boos, W. R.: Feedbacks and Eddy Diffusivity in an Energy
Balance Model of Tropical Rainfall Shifts, npj Climate and Atmospheric
Science, 3, https://doi.org/10.1038/s41612-020-0114-4, https://doi.org/10.1038/s41612-020-0114-4, 2020. a, b, c, d
Pierrehumbert, R. T.: Principles of Planetary Climate, Cambridge
University Press, 2010. a
Pollard, D. and DeConto, R. M.: Hysteresis in Cenozoic Antarctic Ice-Sheet
Variations, Global Planet. Change, 45, 9–21,
https://doi.org/10.1016/j.gloplacha.2004.09.011, 2005. a
Pollard, D., Kump, L., and Zachos, J.: Interactions between Carbon Dioxide,
Climate, Weathering, and the Antarctic Ice Sheet in the Earliest
Oligocene, Global Planet. Change, 111, 258–267,
https://doi.org/10.1016/j.gloplacha.2013.09.012, 2013. a, b, c, d
Prentice, I. C. and Harrison, S. P.: Ecosystem effects of CO2 concentration: evidence from past climates, Clim. Past, 5, 297–307, https://doi.org/10.5194/cp-5-297-2009, 2009. a
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M., Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling, Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007. a, b, c, d
Ridgwell, A. J.: An End to the “Rain Ratio” Reign?, Geochem. Geophy.
Geosy., 4, 6, https://doi.org/10.1029/2003GC000512, 2003. a
Roderick, M. L., Sun, F., Lim, W. H., and Farquhar, G. D.: A general framework for understanding the response of the water cycle to global warming over land and ocean, Hydrol. Earth Syst. Sci., 18, 1575–1589, https://doi.org/10.5194/hess-18-1575-2014, 2014. a
Roe, G. H., Feldl, N., Armour, K. C., Hwang, Y.-T., and Frierson, D. M. W.: The
Remote Impacts of Climate Feedbacks on Regional Climate Predictability,
Nat. Geosci., 8, 35–139, https://doi.org/10.1038/NGEO2346, 2015. a, b, c, d
Scheff, J., Seager, R., Liu, H., and Coats, S.: Are Glacials Dry?
Consequences for Paleoclimatology and for Greenhouse Warming,
J. Climate, 30, 6593–6609, https://doi.org/10.1175/JCLI-D-16-0854.1, 2017. a
Shields, G. A. and Mills, B. J. W.: Tectonic Controls on the Long-Term Carbon
Isotope Mass Balance, P. Natl. Acad. Sci. USA, 114, 4318–4323, https://doi.org/10.1073/pnas.1614506114, 2017. a
Siler, N., Roe, G. H., Armour, K. C., and Feldl, N.: Revisiting the
Surface-Energy-Flux Perspective on the Sensitivity of Global Precipitation to
Climate Change, Clim. Dynam., 52, 3983–3995,
https://doi.org/10.1007/s00382-018-4359-0, 2019. a, b, c, d
Terrer, C., Phillips, R. P., Hungate, B. A., Rosende, J., Pett-Ridge, J.,
Craig, M. E., van Groenigen, K. J., Keenan, T. F., Sulman, B. N., Stocker,
B. D., Reich, P. B., Pellegrini, A. F. A., Pendall, E., Zhang, H., Evans,
R. D., Carrillo, Y., Fisher, J. B., Van Sundert, K., Vicca, S., and Jackson,
R. B.: A Trade-off between Plant and Soil Carbon Storage under Elevated
CO2, Nature, 591, 599–603, https://doi.org/10.1038/s41586-021-03306-8, 2021. a
Torres, M. A., Moosdorf, N., Hartmann, J., Adkins, J. F., and West, A. J.:
Glacial Weathering, Sulfide Oxidation, and Global Carbon Cycle Feedbacks,
P. Natl. Acad. Sci. USA, 114, 8716–8721,
https://doi.org/10.1073/pnas.1702953114, 2017. a, b
Veizer, J., Godderis, Y., and François, L. M.: Evidence for Decoupling of
Atmospheric CO2 and Global Climate during the Phanerozoic Eon,
Nature, 408, 698–701, https://doi.org/10.1038/35047044, 2000. a
Volk, T.: Rise of Angiosperms as a Factor in Long-Term Climatic Cooling,
Geology, 17, 107–110, https://doi.org/10.1130/0091-7613(1989)017<0107:ROAAAF>2.3.CO;2,
1989. a
von Blanckenburg, F., Bouchez, J., Ibarra, D. E., and Maher, K.: Stable
Runoff and Weathering Fluxes into the Oceans over Quaternary Climate
Cycles, Nat. Geosci., 8, 538–542, https://doi.org/10.1038/ngeo2452, 2015. a
Waldbauer, J. R. and Chamberlain, C. P.: Influence of Uplift,
Weathering, and Base Cation Supply on Past and Future CO2
Levels, in: A History of Atmospheric CO2 and Its Effects on
Plants, Animals, and Ecosystems, edited by: Ehleringer, J. R., Cerling, T. E.,
and Dearing, M. D., Ecological Studies, Springer, New York, NY, USA, https://doi.org/10.1007/0-387-27048-5_8,
2005. a
Wallmann, K.: Controls on the Cretaceous and Cenozoic Evolution of Seawater
Composition, Atmospheric CO 2 and Climate, Geochim. Cosmochim. Ac., 65, 3005–3025, https://doi.org/10.1016/S0016-7037(01)00638-X, 2001. a
Zachos, J. and Kump, L.: Carbon Cycle Feedbacks and the Initiation of
Antarctic Glaciation in the Earliest Oligocene, Global Planet.
Change, 47, 51–66, https://doi.org/10.1016/j.gloplacha.2005.01.001, 2005. a, b
Zeebe, R. E.: LOSCAR: Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir Model v2.0.4, Geosci. Model Dev., 5, 149–166, https://doi.org/10.5194/gmd-5-149-2012, 2012. a, b, c, d
Zeebe, R. E. and Tyrrell, T.: History of Carbonate Ion Concentration over the
Last 100 Million Years II: Revised Calculations and New Data,
Geochim. Cosmochim. Ac., 257, 373–392,
https://doi.org/10.1016/j.gca.2019.02.041, 2019.
a, b
Zhang, L., Hickel, K., and Dawes, W. R.: A Rational Function Approach for
Estimating Mean Annual Evapotranspiration, Water Resour. Res., 40,
1–14, https://doi.org/10.1029/2003WR002710, 2004. a, b, c
Short summary
The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact across millions of years on a standard PC. While efficient, the model accounts for many factors including the location of land masses, the spatial pattern of the water cycle, and fundamental climate feedbacks. The model is a powerful tool for investigating how short-term climate processes can affect long-term changes in the Earth system.
The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact...
