Articles | Volume 17, issue 9
https://doi.org/10.5194/gmd-17-3949-2024
© 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/gmd-17-3949-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
15 May 2024
Development and technical paper |
| 15 May 2024
| 15 May 2024
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
Haoyue Zuo
Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
Institute of Carbon Neutrality, Peking University, Beijing, 100871, China
Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
Institute of Carbon Neutrality, Peking University, Beijing, 100871, China
Gaojun Li
Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing, China
Zhifang Xu
Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Liang Zhao
State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Zhengtang Guo
Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, China
Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
Institute of Carbon Neutrality, Peking University, Beijing, 100871, China
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Ziying Yang, Jiping Liu, Mirong Song, Yongyun Hu, Qinghua Yang, and Ke Fan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1001, https://doi.org/10.5194/egusphere-2024-1001, 2024
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Antarctic sea ice has changed rapidly in recent years. Here we developed a deep learning model trained by multiple climate variables for extended seasonal Antarctic sea ice prediction. Our model shows high predictive skills up to 6 months in advance, particularly in predicting extreme events. It also shows skillful predictions at the sea ice edge and year-to-year sea ice changes. Variable importance analyses suggest what variables are more important for prediction at different lead times.
Anni Zhao, Ran Feng, Chris M. Brierley, Jian Zhang, and Yongyun Hu
Clim. Past, 20, 1195–1211, https://doi.org/10.5194/cp-20-1195-2024, https://doi.org/10.5194/cp-20-1195-2024, 2024
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We analyse simulations with idealised aerosol scenarios to examine the importance of aerosol forcing on mPWP precipitation and how aerosol uncertainty could explain the data–model mismatch. We find further warming, a narrower and stronger ITCZ, and monsoon domain rainfall change after removal of industrial emissions. Aerosols have more impacts on tropical precipitation than the mPWP boundary conditions. This highlights the importance of prescribed aerosol scenarios in simulating mPWP climate.
Silvia Pondrelli, Simone Salimbeni, Judith M. Confal, Marco Malusà, Anne Paul, Stephane Guillot, Stefano Solarino, Elena Eva, Coralie Aubert, and Liang Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-468, https://doi.org/10.5194/egusphere-2024-468, 2024
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We analyse and interpret seismic anisotropy from CIFALPS2 data, that fills the gaps in Western Alps and support a new hypothesis. Instead of a continuous mantle flow parallel to the belt here we find: a NS mantle deformation pattern from beneath Europe that merges first with mantle deformed by slab retreat beneath Central Alps, then merges with an asthenospheric flow sourced beneath the Massif Central. This new sketch supports the extinction of slab retreat beneath Western Alps.
Zhongshi Zhang, Qing Yan, Ran Zhang, Florence Colleoni, Gilles Ramstein, Gaowen Dai, Martin Jakobsson, Matt O'Regan, Stefan Liess, Denis-Didier Rousseau, Naiqing Wu, Elizabeth J. Farmer, Camille Contoux, Chuncheng Guo, Ning Tan, and Zhengtang Guo
Clim. Past Discuss., https://doi.org/10.5194/cp-2020-38, https://doi.org/10.5194/cp-2020-38, 2020
Manuscript not accepted for further review
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Whether an ice sheet once grew over Northeast Siberia-Beringia has been debated for decades. By comparing climate modelling with paleoclimate and glacial records from around the North Pacific, this study shows that the Laurentide-Eurasia-only ice sheet configuration fails in explaining these records, while a scenario involving the ice sheet over Northeast Siberia-Beringia succeeds. It highlights the complexity in glacial climates and urges new investigations across Northeast Siberia-Beringia.
Yongyun Hu, Yan Xia, Zhengyu Liu, Yuchen Wang, Zhengyao Lu, and Tao Wang
Clim. Past, 16, 199–209, https://doi.org/10.5194/cp-16-199-2020, https://doi.org/10.5194/cp-16-199-2020, 2020
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The paper shows, using climate simulations, that the Pacific–North American (PNA) teleconnection was distorted or completely broken at the Last Glacial Maximum (LGM). The results suggest that ENSO would have little direct impact on North American climates at the LGM.
Ning Tan, Camille Contoux, Gilles Ramstein, Yong Sun, Christophe Dumas, Pierre Sepulchre, and Zhengtang Guo
Clim. Past, 16, 1–16, https://doi.org/10.5194/cp-16-1-2020, https://doi.org/10.5194/cp-16-1-2020, 2020
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To understand the warm climate during the late Pliocene (~3.205 Ma), modeling experiments with the new boundary conditions are launched and analyzed based on the Institut Pierre Simon Laplace (IPSL) atmosphere–ocean coupled general circulation model (AOGCM). Our results show that the warming in mid- to high latitudes enhanced due to the modifications of the land–sea mask and land–ice configuration. The pCO2 uncertainties within the records can produce asymmetrical warming patterns.
Yating Lin, Gilles Ramstein, Haibin Wu, Raj Rani, Pascale Braconnot, Masa Kageyama, Qin Li, Yunli Luo, Ran Zhang, and Zhengtang Guo
Clim. Past, 15, 1223–1249, https://doi.org/10.5194/cp-15-1223-2019, https://doi.org/10.5194/cp-15-1223-2019, 2019
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The mid-Holocene has been an excellent target for comparing models and data. This work shows that, over China, all the ocean–atmosphere general circulation models involved in PMIP3 show a very large discrepancy with pollen data reconstruction when comparing annual and seasonal temperature. It demonstrates that to reconcile models and data and to capture the signature of seasonal thermal response, it is necessary to integrate non-linear processes, particularly those related to vegetation changes.
Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Gaojun Li
Earth Surf. Dynam., 7, 191–197, https://doi.org/10.5194/esurf-7-191-2019, https://doi.org/10.5194/esurf-7-191-2019, 2019
Wenjing Liu, Zhifang Xu, Huiguo Sun, Tong Zhao, Chao Shi, and Taoze Liu
Biogeosciences, 15, 4955–4971, https://doi.org/10.5194/bg-15-4955-2018, https://doi.org/10.5194/bg-15-4955-2018, 2018
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The southeastern coastal region is the top acid-rain-impacted area in China. It is worth evaluating the acid deposition impacts on chemical weathering and CO2 consumption there. River water geochemistry evidenced an overestimation of CO2 sequestration if H2SO4/HNO3 involvement was ignored, which accounted for 33.6 % of the total flux by silicate weathering in this area. This study quantitatively highlights the anthropogenic acid effects on chemical weathering and associated CO2 consumption.
Chenxi Xu, Masaki Sano, Ashok Priyadarshan Dimri, Rengaswamy Ramesh, Takeshi Nakatsuka, Feng Shi, and Zhengtang Guo
Clim. Past, 14, 653–664, https://doi.org/10.5194/cp-14-653-2018, https://doi.org/10.5194/cp-14-653-2018, 2018
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We have constructed a regional tree ring cellulose oxygen isotope record using a total of five chronologies obtained from the Himalaya. Centennial changes in the regional tree ring record indicate a trend of weakened Indian summer monsoon (ISM) intensity since 1820. Decreasing ISM activity is also observed in various high-resolution ISM records from southwest China and Southeast Asia, and may be the result of reduced land–ocean thermal contrasts since 1820.
Feng Shi, Sen Zhao, Zhengtang Guo, Hugues Goosse, and Qiuzhen Yin
Clim. Past, 13, 1919–1938, https://doi.org/10.5194/cp-13-1919-2017, https://doi.org/10.5194/cp-13-1919-2017, 2017
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We reconstructed the multi-proxy precipitation field for China over the past 500 years, which includes three leading modes (a monopole, a dipole, and a triple) of precipitation variability. The dipole mode may be controlled by the El Niño–Southern Oscillation variability. Such reconstruction is an essential source of information to document the climate variability over decadal to centennial timescales and can be used to assess the ability of climate models to simulate past climate change.
Wenshou Tian, Yuanpu Li, Fei Xie, Jiankai Zhang, Martyn P. Chipperfield, Wuhu Feng, Yongyun Hu, Sen Zhao, Xin Zhou, Yun Yang, and Xuan Ma
Atmos. Chem. Phys., 17, 6705–6722, https://doi.org/10.5194/acp-17-6705-2017, https://doi.org/10.5194/acp-17-6705-2017, 2017
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Although the principal mechanisms responsible for the formation of the Antarctic ozone hole are well understood, the factors or processes that generate interannual variations in ozone levels in the southern high-latitude stratosphere remain under debate. This study finds that the SST variations across the East Asian marginal seas (5° S–35° N, 100–140° E) could modulate the southern high-latitude stratospheric ozone interannual changes.
Chao-Yuan Yang, Jiping Liu, Yongyun Hu, Radley M. Horton, Liqi Chen, and Xiao Cheng
The Cryosphere, 10, 2429–2452, https://doi.org/10.5194/tc-10-2429-2016, https://doi.org/10.5194/tc-10-2429-2016, 2016
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The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales.
Yan Xia, Yongyun Hu, and Yi Huang
Atmos. Chem. Phys., 16, 7559–7567, https://doi.org/10.5194/acp-16-7559-2016, https://doi.org/10.5194/acp-16-7559-2016, 2016
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In this work, we discover a strong cloud radiative adjustment that affects the sign of the global surface temperature change in response to stratospheric ozone forcing. We believe this discovery is both interesting, in that our GCM experiments show that a global cooling can result from a warming forcing, and new, in that a strong cloud adjustment to ozone forcing, to the best of our knowledge, has not being documented before.
P. X. Wang, B. Wang, H. Cheng, J. Fasullo, Z. T. Guo, T. Kiefer, and Z. Y. Liu
Clim. Past, 10, 2007–2052, https://doi.org/10.5194/cp-10-2007-2014, https://doi.org/10.5194/cp-10-2007-2014, 2014
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All regional monsoons belong to a cohesive global monsoon circulation system, albeit thateach regional subsystem has its own indigenous features. A comprehensive review of global monsoon variability reveals that regional monsoons can vary coherently across a range of timescales, from interannual up to orbital and tectonic. Study of monsoon variability from both global and regional perspectives is imperative and advantageous for integrated understanding of the modern and paleo-monsoon dynamics.
Q. Z. Yin, U. K. Singh, A. Berger, Z. T. Guo, and M. Crucifix
Clim. Past, 10, 1645–1657, https://doi.org/10.5194/cp-10-1645-2014, https://doi.org/10.5194/cp-10-1645-2014, 2014
H. Wu, C. Peng, T. R. Moore, D. Hua, C. Li, Q. Zhu, M. Peichl, M. A. Arain, and Z. Guo
Geosci. Model Dev., 7, 867–881, https://doi.org/10.5194/gmd-7-867-2014, https://doi.org/10.5194/gmd-7-867-2014, 2014
H. Wu, C. Peng, M. Lucotte, N. Soumis, Y. Gélinas, É. Duchemin, J.-B. Plouhinec, A. Ouellet, and Z. Guo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-3509-2013, https://doi.org/10.5194/gmdd-6-3509-2013, 2013
Revised manuscript not accepted
Y. Y. Yu, P. A. Finke, H. B. Wu, and Z. T. Guo
Geosci. Model Dev., 6, 29–44, https://doi.org/10.5194/gmd-6-29-2013, https://doi.org/10.5194/gmd-6-29-2013, 2013
J. Yang, Y. Hu, and W. R. Peltier
Clim. Past, 8, 2019–2029, https://doi.org/10.5194/cp-8-2019-2012, https://doi.org/10.5194/cp-8-2019-2012, 2012
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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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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.
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.
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.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
EGUsphere, https://doi.org/10.5194/egusphere-2024-45, https://doi.org/10.5194/egusphere-2024-45, 2024
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This study focused 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 were applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method of Random Forest for increasing the accuracy of climate models, concerning the projection of the number of wet days.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
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The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Cited articles
Adams, B. A., Whipple, K. X., Forte, A. M., Heimsath, A. M., and Hodges, K. V.: Climate controls on erosion in tectonically active landscapes, Sci. Adv., 6, eaaz3166, https://doi.org/10.1126/sciadv.aaz3166, 2020.
Allen, J., Forrest, M., Hickler, T., Singarayer, J., Valdes, P., and Huntley, B.: Global vegetation patterns of the past 140,000 years, J. Biogeogr., 47, 2073–2090, https://doi.org/10.1111/jbi.13930, 2020.
Amiotte Suchet, P., Probst, J.-L., and Ludwig, W.: Worldwide distribution of continental rock lithology: Implications for the atmospheric/soil CO2 uptake by continental weathering and alkalinity river transport to the oceans, Global Biogeochem. Cy., 17, 1038, https://doi.org/10.1029/2002GB001891, 2003.
Andermann, T., Strömberg, C. A. E., Antonelli, A., and Silvestro, D.: The origin and evolution of open habitats in North America inferred by Bayesian deep learning models, Nat. Commun., 13, 4833, https://doi.org/10.1038/s41467-022-32300-5, 2022.
Anderson, R.: Modeling the tor-dotted crests, bedrock edges, and parabolic profiles of high alpine surfaces of the Wind River Range, Wyoming, Geomorphology, 46, 35–58, https://doi.org/10.1016/S0169-555X(02)00053-3, 2002.
Berner, E. K. and Berner, R. A.: Global Environment: Water, Air, and Geochemical Cycles – Second Edition, 2, Princeton University Press, https://doi.org/10.2307/j.ctv30pnvjd, 2012.
Berner, R.: The Phanerozoic Carbon Cycle: CO2 and O2, Oxford Academic, https://doi.org/10.1093/oso/9780195173338.001.0001, 2004.
Berner, R., Lasaga, A., and Garrells, R.: The carbonate-silicate geochemical cycle and its effect on atmospheric carbon dioxide over the past 100 million years, Am. J. Sci, 283, 641–683, https://doi.org/10.2475/ajs.283.7.641, 1983.
Berner, R. A.: A model for atmospheric CO2 over Phanerozoic time, Am. J. Sci., 291, 339, https://doi.org/10.2475/ajs.291.4.339, 1991.
Berner, R. A.: Weathering, plants, and the long-term carbon cycle, Geochim. Cosmochim. Ac., 56, 3225–3231, https://doi.org/10.1016/0016-7037(92)90300-8, 1992.
Berner, R. A. and Caldeira, K.: The need for mass balance and feedback in the geochemical carbon cycle, Geology, 25, 955–956, https://doi.org/10.1130/0091-7613(1997)025<0955:TNFMBA>2.3.CO;2, 1997.
Berner, R. A. and Kothavala, Z.: GEOCARB III: A revised model of atmospheric CO2 over phanerozoic time, Am. J. Sci., 301, 182–204, https://doi.org/10.2475/ajs.301.2.182, 2001.
Binney, H., Edwards, M., Macias-Fauria, M., Lozhkin, A., Anderson, P., Kaplan, J. O., Andreev, A., Bezrukova, E., Blyakharchuk, T., Jankovska, V., Khazina, I., Krivonogov, S., Kremenetski, K., Nield, J., Novenko, E., Ryabogina, N., Solovieva, N., Willis, K., and Zernitskaya, V.: Vegetation of Eurasia from the last glacial maximum to present: Key biogeographic patterns, Quaternary Sci. Rev., 157, 80–97, https://doi.org/10.1016/j.quascirev.2016.11.022, 2017.
Blanckenburg, F., Bouchez, J., and Wittmann, H.: Earth surface erosion and weathering from the 10Be (meteoric)/9Be ratio, Earth Planet. Sc. Lett., 351–352, 295–305, https://doi.org/10.1016/j.epsl.2012.07.022, 2012.
Bluth, G. and Kump, L.: Lithologic and climatologic controls of river chemistry, Geochim. Cosmochim. Ac., 58, 2341–2359, https://doi.org/10.1016/0016-7037(94)90015-9, 1994.
Brantley, S. L., Bandstra, J., Moore, J., and White, A. F.: Modelling chemical depletion profiles in regolith, Geoderma, 145, 494–504, https://doi.org/10.1016/j.geoderma.2008.02.010, 2008.
Burke, B., Heimsath, A., and White, A.: Coupling chemical weathering with soil production across soil-landscapes, Earth Surf. Proc. Land., 32, 853–873, https://doi.org/10.1002/esp.1443, 2007.
Calabrese, S., Wild, B., Bertagni, M. B., Bourg, I. C., White, C., Aburto, F., Cipolla, G., Noto, L. V., and Porporato, A.: Nano- to global-scale uncertainties in terrestrial enhanced weathering, Environ. Sci. Technol., 56, 15261–15272, https://doi.org/10.1021/acs.est.2c03163, 2022.
Canadell, J. G., Monteiro, P. M. S., Costa, M. H., Cotrim da Cunha, L., Cox, P. M., Eliseev, A. V., Henson, S., Ishii, M., Jaccard, S., Koven, C., Lohila, A., Patra, P. K., Piao, S., Rogelj, J., Syampungani, S., Zaehle, S., and Zickfeld, K.: Global Carbon and Other Biogeochemical Cycles and Feedbacks, in: Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Intergovernmental Panel on Climate, C., Cambridge University Press, Cambridge, 673–816, https://doi.org/10.1017/9781009157896.007, 2023.
Carretier, S., Goddéris, Y., Delannoy, T., and Rouby, D.: Mean bedrock-to-saprolite conversion and erosion rates during mountain growth and decline, Geomorphology, 209, 39–52, https://doi.org/10.1016/j.geomorph.2013.11.025, 2014.
Carretier, S., Goddéris, Y., Martinez, J., Reich, M., and Martinod, P.: Colluvial deposits as a possible weathering reservoir in uplifting mountains, Earth Surf. Dynam., 6, 217–237, https://doi.org/10.5194/esurf-6-217-2018, 2018.
Caves Rugenstein, J., Ibarra, D., Zhang, S., Planavsky, N., and Blanckenburg, F.: Isotope mass-balance constraints preclude that mafic weathering drove Neogene cooling, P. Natl. Acad. Sci. USA, 118, e2026345118, https://doi.org/10.1073/pnas.2026345118, 2021.
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.
Danabasoglu, G.: NCAR CESM2 model output prepared for CMIP6 CMIP, WCRP [data set], https://doi.org/10.22033/ESGF/CMIP6.2185, 2019.
Dannhaus, N., Wittmann, H., Krám, P., Christl, M., and Blanckenburg, F.: Catchment-wide weathering and erosion rates of mafic, ultramafic, and granitic rock from cosmogenic meteoric 10 Be/ 9 Be ratios, Geochim. Cosmochim. Ac., 222, 618–641, https://doi.org/10.1016/j.gca.2017.11.005, 2017.
D'Antonio, M., Ibarra, D., and Boyce, C.: Land plant evolution decreased, rather than increased, weathering rates, Geology, 48, 29–33, https://doi.org/10.1130/G46776.1, 2019.
Davy, P. and Crave, A.: Upscaling local-scale transport processes in large-scale relief dynamics, Phys. Chem. Earth., 25, 533–541, https://doi.org/10.1016/S1464-1895(00)00082-X, 2000.
Dellinger, M., Gaillardet, J., Bouchez, J., Calmels, D., Louvat, P., Dosseto, A., Gorge, C., Alanoca, L., and Maurice, L.: Riverine Li isotope fractionation in the Amazon River basin controlled by the weathering regimes, Geochim. Cosmochim. Ac., 164, 71–93, https://doi.org/10.1016/j.gca.2015.04.042, 2015.
Dessert, C., Dupré, B., Gaillardet, J., François, L. M., and Allègre, C. J.: Basalt weathering laws and the impact of basalt weathering on the global carbon cycle, Chem. Geol., 202, 257–273, https://doi.org/10.1016/j.chemgeo.2002.10.001, 2003.
Dietrich, W., Reiss, R., Hsu, M.-L., and Montgomery, D.: A process-based model for colluvial soil depth and shallow landsliding using digital elevation data, Hydrol. Process., 9, 383–400, https://doi.org/10.1002/hyp.3360090311, 1995.
Dixon, J., Heimsath, A., and Amundson, R.: Critical role of climate and saprolite weathering in landscape evolution, Earth Surf. Proc. Land., 34, 1507–1521, https://doi.org/10.1002/esp.1836, 2009.
Edmond, J. M., Palmer, M. R., Measures, C. I., Grant, B., and Stallard, R. F.: The fluvial geochemistry and denudation rate of the Guayana Shield in Venezuela, Colombia, and Brazil, Geochim. Cosmochim. Ac., 59, 3301–3325, https://doi.org/10.1016/0016-7037(95)00128-M, 1995.
Emerson, S. and Hedges, J.: Chemical Oceanography and the Marine Carbon Cycle, Cambridge University Press, Cambridge, https://doi.org/10.1017/CBO9780511793202, 2008.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S., Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.: The shuttle radar topography mission, Rev. Geophys., 45, RG2004, https://doi.org/10.1029/2005RG000183, 2007.
Fekete, B., Vörösmarty, C. J., and Grabs, W.: Highresolution fields of global runoff combining river discharge and simulated water balances, Global Biogeochem. Cy., 16, 15-1–15-10, https://doi.org/10.1029/1999GB001254, 2002.
FAO/IIASA/ISRIC/ISSCAS/JRC: Harmonized World Soil Database (version 1.2), FAO, Rome, Italy and IIASA, Laxenburg, Austria [data set], https://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/ (last access: 1 December 2021), 2012.
France-Lanord, C. and Derry, L. A.: Organic carbon burial forcing of the carbon cycle from Himalayan erosion, Nature, 390, 65–67, https://doi.org/10.1038/36324, 1997.
Gabet, E. J. and Mudd, S. M.: A theoretical model coupling chemical weathering rates with denudation rates, Geology, 37, 151–154, https://doi.org/10.1130/G25270A.1, 2009.
Gaillardet, J., Dupré, B., Louvat, P., and Allègre, C. J.: Global silicate weathering and CO2 consumption rates deduced from the chemistry of large rivers, Chem. Geol., 159, 3–30, https://doi.org/10.1016/S0009-2541(99)00031-5, 1999.
Galy, A. and France-Lanord, C.: Weathering processes in the Ganges–Brahmaputra basin and the riverine alkalinity budget, Chem. Geol., 159, 31–60, https://doi.org/10.1016/S0009-2541(99)00033-9, 1999.
Gasparini, N., Whipple, K., and Bras, R.: Predictions of steady state and transient landscape morphology using sediment-flux-dependent river incision models, J. Geophys. Res., 112, F03S09, https://doi.org/10.1029/2006JF000567, 2007.
Gerlach, T.: Volcanic versus anthropogenic carbon dioxide, Eos Trans. Agu, 92, 201–202, https://doi.org/10.1029/2011EO240001, 2011.
Ghiggi, G., Humphrey, V., Seneviratne, S. I., and Gudmundsson, L.: GRUN: an observation-based global gridded runoff dataset from 1902 to 2014, Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019, 2019.
Gibbs, M., Bluth, G., Fawcett, P., and Kump, L.: Global chemical erosion over the last 250 MY: Variations due to changes in paleogeography, paleoclimate, and paleogeology, Am. J. Sci, 299, 611–651, https://doi.org/10.2475/ajs.299.7-9.611, 1999.
Godderis, Y., Donnadieu, Y., Tombozafy, M., and Dessert, C.: Shield effect on continental weathering: Implication for climatic evolution of the Earth at the geological timescale, Geoderma, 145, 439–448, https://doi.org/10.1016/j.geoderma.2008.01.020, 2008.
Goddéris, Y., Donnadieu, Y., Carretier, S., Aretz, M., Dera, G., Macouin, M., and Regard, V.: Onset and ending of the late Palaeozoic ice age triggered by tectonically paced rock weathering, Nat. Geosci., 10, 382–386, https://doi.org/10.1038/ngeo2931, 2017.
Goddéris, Y., Donnadieu, Y., and Mills, B. J. W.: What models tell us about the evolution of carbon sources and sinks over the Phanerozoic, Annu. Rev. Earth Pl. Sc., 51, 471–492, https://doi.org/10.1146/annurev-earth-032320-092701, 2023.
Gruber, C., Zhu, C., Georg, R. B., Zakon, Y., and Ganor, J.: Resolving the gap between laboratory and field rates of feldspar weathering, Geochim. Cosmochim. Ac., 147, 90–106, https://doi.org/10.1016/j.gca.2014.10.013, 2014.
Harel, M. A., Mudd, S. M., and Attal, M.: Global analysis of the stream power law parameters based on worldwide 10Be denudation rates, Geomorphology, 268, 184–196, https://doi.org/10.1016/j.geomorph.2016.05.035, 2016.
Harris, I., Jones, P., Osborn, T., and Lister, D.: Updated high-resolution grids of monthly climatic observations – The CRU TS3.10 Dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Hartmann, J. and Moosdorf, N.: The new global lithological map database GLiM: A representation of rock properties at the Earth surface, Geochem. Geophy. Geosy., 13, Q12004, https://doi.org/10.1029/2012gc004370, 2012.
Hartmann, J., Jansen, N., Dürr, H. H., Kempe, S., and Köhler, P.: Global CO2-consumption by chemical weathering: What is the contribution of highly active weathering regions?, Global Planet. Change, 69, 185–194, https://doi.org/10.1016/j.gloplacha.2009.07.007, 2009.
Hartmann, J., Moosdorf, N., Lauerwald, R., Hinderer, M., and West, A. J.: Global chemical weathering and associated P-release – The role of lithology, temperature and soil properties, Chem. Geol., 363, 145–163, https://doi.org/10.1016/j.chemgeo.2013.10.025, 2014.
Heimsath, A. and Korup, O.: Quantifying rates and processes of landscape evolution, Earth Surf. Proc. Land., 37, 249–251, https://doi.org/10.1002/esp.2251, 2012.
Heimsath, A., Dietrich, W., Nishiizumi, K., and Finkel, R.: Cosmogenic nuclides, topography, and the spatial variation of soil depth, Geomorphology, 27, 151–172, https://doi.org/10.1016/S0169-555X(98)00095-6, 1999.
Heimsath, A., Fink, D., and Hancock, G.: The “humped” soil production function: Eroding Arnhem Land, Australia, Earth Surf. Proc. Land., 34, 1674–1684, https://doi.org/10.1002/esp.1859, 2009.
Heimsath, A. M., Dietrich, W. E., Nishiizumi, K., and Finkel, R. C.: The soil production function and landscape equilibrium, Nature, 388, 358–361, https://doi.org/10.1038/41056, 1997.
Hewawasam, T., von Blanckenburg, F., Schaller, M., and Kubik, P.: Increase of human over natural erosion rates in tropical highlands constrained by cosmogenic nuclides, Geology, 31, 597–600, https://doi.org/10.1130/0091-7613(2003)031<0597:IOHONE>2.0.CO;2, 2003.
Hilton, R. G. and West, A. J.: Mountains, erosion and the carbon cycle, Nat. Rev. Earth Env., 1, 284–299, https://doi.org/10.1038/s43017-020-0058-6, 2020.
Howard, A.: A detachment-limited model of drainage-basin Evolution, Water Resour. Res., 30, 2261–2285, https://doi.org/10.1029/94WR00757, 1994.
Hu, Y., Teng, F.-Z., Plank, T., and Chauvel, C.: Potassium isotopic heterogeneity in subducting oceanic plates, Sci. Adv., 6, eabb2472, https://doi.org/10.1126/sciadv.abb2472, 2020.
Ibarra, D. E., Rugenstein, J. K. C., Bachan, A., Baresch, A., Lau, K. V., Thomas, D. L., Lee, J.-E., Boyce, C. K., and Chamberlain, C. P.: Modeling the consequences of land plant evolution on silicate weathering, Am. J. Sci, 319, 1–43, https://doi.org/10.2475/01.2019.01, 2019.
Kalderon-Asael, B., Katchinoff, J., Planavsky, N., Hood, A., Dellinger, M., Bellefroid, E., Jones, D., Hofmann, A., Ossa, F., Macdonald, F., Wang, C., Isson, T., Murphy, J., Higgins, J., West, A. J., Wallace, M., Asael, D., and Pogge von Strandmann, P.: A lithium-isotope perspective on the evolution of carbon and silicon cycles, Nature, 595, 394–398, https://doi.org/10.1038/s41586-021-03612-1, 2021.
Krapp, M., Beyer, R. M., Edmundson, S. L., Valdes, P. J., and Manica, A.: A statistics-based reconstruction of high-resolution global terrestrial climate for the last 800,000 years, Sci. Data, 8, 228, https://doi.org/10.1038/s41597-021-01009-3, 2021.
Lague, D.: The stream power river incision model: evidence, theory and beyond, Earth Surf. Proc. Land., 39, 38–61, https://doi.org/10.1002/esp.3462, 2014.
Larsen, I. J., Almond, P. C., Eger, A., Stone, J. O., Montgomery, D. R., and Malcolm, B.: Rapid soil production and weathering in the Southern Alps, New Zealand, Science, 343, 637–640, https://doi.org/10.1126/science.1244908, 2014.
Lawrence, P. and Chase, T.: Representing a new MODIS consistent land surface in the Community Land Model (CLM 3.0), J. Geophys. Res., 112, G01023, https://doi.org/10.1029/2006JG000168, 2007.
Lécuyer, C.: Seawater residence times of some elements of geochemical interest and the salinity of the oceans, Bulletin de la Société Géologique de France, 187, 245–260, https://doi.org/10.2113/gssgfbull.187.6.245, 2016.
Lee, C.-T. A., Jiang, H., Dasgupta, R., and Torres, M.: A framework for understanding whole-Earth carbon cycling, in: Deep Carbon, 313–357, https://doi.org/10.1017/9781108677950.011, 2019.
Lenton, T. M., Crouch, M., Johnson, M., Pires, N., and Dolan, L.: First plants cooled the Ordovician, Nat. Geosci., 5, 86–89, https://doi.org/10.1038/ngeo1390, 2012.
Li, S., Li, W., Beard, B. L., Raymo, M. E., Wang, X., Chen, Y., and Chen, J.: K isotopes as a tracer for continental weathering and geological K cycling, P. Natl. Acad. Sci. USA, 116, 8740–8745, https://doi.org/10.1073/pnas.1811282116, 2019.
Li, X., Hu, Y., Yang, J., Wei, M., Guo, J., Lan, J., Lin, Q., Yuan, S., Zhang, J., Wei, Q., Liu, Y., Nie, J., Xia, Y., and Hu, S.: Climate variations in the past 250 million years and contributing factors, Paleoceanogr. Paleoclimatol., 38, e2022PA004503, https://doi.org/10.1029/2022pa004503, 2023.
Liu, Y., Yang, J., Bao, H., Shen, B., and Hu, Y.: Large equatorial seasonal cycle during Marinoan snowball Earth, Sci. Adv., 6, eaay2471, https://doi.org/10.1126/sciadv.aay2471, 2020.
Lyla, T., Steve, B., Jonathan, L., and David, J. B.: Modeling the evolutionary rise of ectomycorrhiza on sub-surface weathering environments and the geochemical carbon cycle, Am. J. Sci., 311, 369, https://doi.org/10.2475/05.2011.01, 2011.
Maffre, P., Ladant, J.-B., Moquet, J.-S., Carretier, S., Labat, D., and Goddéris, Y.: Mountain ranges, climate and weathering. Do orogens strengthen or weaken the silicate weathering carbon sink?, Earth Planet. Sc. Lett., 493, 174–185, https://doi.org/10.1016/j.epsl.2018.04.034, 2018.
Maffre, P., Godderis, Y., Pohl, A., Donnadieu, Y., Carretier, S., and Hir, G.: The complex response of continental silicate rock weathering to the colonization of the continents by vascular plants in the Devonian, Am. J. Sci, 322, 461–492, https://doi.org/10.2475/03.2022.02, 2022.
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.
Maher, K. and Chamberlain, C. P.: Hydrologic regulation of chemical weathering and the geologic, Science, 343, 1502–1504, https://doi.org/10.1126/science.1250770, 2014.
McMahon, W. J. and Davies, N. S.: Evolution of alluvial mudrock forced by early land plants, Science, 359, 1022–1024, https://doi.org/10.1126/science.aan4660, 2018.
Meybeck, M.: Global chemical weathering of surficial rocks estimated from river dissolved loads, Am. J. Sci., 287, 401–428, https://doi.org/10.2475/ajs.287.5.401, 1987.
Milliman, J. and Farnsworth, K.: River Discharge to the Coastal Ocean – A Global Synthesis, Cambridge University Press, https://doi.org/10.1017/CBO9780511781247, 2011.
Milliman, J. and Syvitski, J.: Geomorphic tectonic control of sediment discharge to ocean – The importance of small mountainous rivers, J. Geol., 100, 525–544, https://doi.org/10.1086/629606, 1991.
Milliman, J. D., Rutkowski, C., and Meybeck, M.: River discharge to the sea; a global river index (GLORI), loicz reports & studies, no. 2, https://www.futureearthcoasts.org/report-and-study-series/ (last access: 15 June 2022), 1995.
Mills, B. J. W., Donnadieu, Y., and Goddéris, Y.: Spatial continuous integration of Phanerozoic global biogeochemistry and climate, Gondwana Res., 100, 73–86, https://doi.org/10.1016/j.gr.2021.02.011, 2021.
Mishra, A., Placzek, C., and Jones, R.: Coupled influence of precipitation and vegetation on millennial-scale erosion rates derived from 10Be, PLOS ONE, 14, e0211325, https://doi.org/10.1371/journal.pone.0211325, 2019.
Moon, S., Chamberlain, C. P., and Hilley, G. E.: 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.
Moquet, J.-S., Crave, A., Viers, J., Seyler, P., Armijos, E., Bourrel, L., Chavarri, E., Lagane, C., Laraque, A., Lavado, W., Pombosa, R., Noriega, L., Vera, A., and Guyot, J.-L.: Chemical weathering and atmospheric/soil CO2 uptake in the Andean and Foreland Amazon basins, Chem. Geol., 287, 1–26, https://doi.org/10.1016/j.chemgeo.2011.01.005, 2011.
Moquet, J.-S., Guyot, J.-L., Crave, A., Viers, J., Filizola Jr, N., Martinez, J., Oliveira, T., Hidalgo Sánchez, L., Lagane, C., Lavado, W., Noriega, L., and Pombosa, R.: Amazon River dissolved load: temporal dynamics and annual budget from the Andes to the ocean, Environ. Sci. Pollut. R., 23, 11405–11429, https://doi.org/10.1007/s11356-015-5503-6, 2016.
Moquet, J.-S., Guyot, J.-L., Morera, S., Crave, A., Rau, P., Vauchel, P., Lagane, C., Sondag, F., Lavado, W., Pombosa, R., and Martinez, J.: Temporal variability and annual budget of inorganic dissolved matter in Andean Pacific Rivers located along a climate gradient from northern Ecuador to southern Peru, Cr. Geosci., 350, 76–87, https://doi.org/10.1016/j.crte.2017.11.002, 2018.
Müller, R. D., Mather, B., Dutkiewicz, A., Keller, T., Merdith, A., Gonzalez, C. M., Gorczyk, W., and Zahirovic, S.: Evolution of Earth's tectonic carbon conveyor belt, Nature, 605, 629–639, https://doi.org/10.1038/s41586-022-04420-x, 2022.
Muñoz Sabater, J.: ERA5-Land monthly averaged data from 1950 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.68d2bb30, 2019.
Olson, S., Jansen, M. F., Abbot, D. S., Halevy, I., and Goldblatt, C.: The effect of ocean salinity on climate and its implications for Earth's habitability, Geophys. Res. Lett., 49, e2021GL095748, https://doi.org/10.1029/2021GL095748, 2022.
Park, Y., Maffre, P., Godderis, Y., Macdonald, F., Anttila, E., and Swanson-Hysell, N.: 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.
Phillips, J.: The convenient fiction of steady-state soil thickness, Geoderma, 156, 389–398, https://doi.org/10.1016/j.geoderma.2010.03.008, 2010.
Prentice, I. C. and Webb III, T.: BIOME 6000: reconstructing global mid-Holocene vegetation patterns from palaeoecological records, J. Biogeogr., 25, 997–1005, https://doi.org/10.1046/j.1365-2699.1998.00235.x, 1998.
Prentice, I. C., Jolly, D., and BIOME 6000 participants: Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa, J. Biogeogr., 27, 507–519, https://doi.org/10.1046/j.1365-2699.2000.00425.x, 2000.
Quye-Sawyer, J., Whittaker, A. C., and Roberts, G. G.: Calibrating fluvial erosion laws and quantifying river response to faulting in Sardinia, Italy, Geomorphology, 370, 107388, https://doi.org/10.1016/j.geomorph.2020.107388, 2020.
Raymo, M. E. and Ruddiman, W. F.: Tectonic forcing of late Cenozoic climate, Nature, 359, 117–122, 1992.
Riebe, C. S., Kirchner, J. W., and Finkel, R. C.: Erosional and climatic effects on long-term chemical weathering rates in granitic landscapes spanning diverse climate regimes, Earth Planet. Sc. Lett., 224, 547–562, https://doi.org/10.1016/j.epsl.2004.05.019, 2004.
Royden, L. and Taylor Perron, J.: Solutions of the stream power equation and application to the evolution of river longitudinal profiles, J. Geophys. Res-Earth., 118, 497–518, https://doi.org/10.1002/jgrf.20031, 2013.
Rudnick, R. and Gao, S.: Composition of the Continental Crust, Treatise on Geochemistry, 1–64 pp., https://doi.org/10.1016/B0-08-043751-6/03016-4, 2003.
Scotese, C. R. and Wright, N.: PALEOMAP Paleodigital Elevation Models (PaleoDEMS) for the Phanerozoic, PALEOMAP Project [data set], https://www.earthbyte.org/paleodem-resource-scotese-and-wright-2018/ (last access: 20 April 2019), 2018.
Shao, Y., Anhäuser, A., Ludwig, P., Schlüter, P., and Williams, E.: Statistical reconstruction of global vegetation for the last glacial maximum, Global Planet. Change, 168, 67–77, https://doi.org/10.1016/j.gloplacha.2018.06.002, 2018.
Small, E., Anderson, R., and Hancock, G.: Estimates of the rate of regolith production using 10Be and 26Al from an alpine hillslope, Geomorphology, 27, 131–150, https://doi.org/10.1016/S0169-555X(98)00094-4, 1999.
Stallard, R. F.: River Chemistry, Geology, Geomorphology, and Soils in the Amazon and Orinoco Basins, in: The Chemistry of Weathering, edited by: Drever, J. I., Springer Netherlands, Dordrecht, 293–316, https://doi.org/10.1007/978-94-009-5333-8_17, 1985.
Stallard, R. F. and Edmond, J. M.: Geochemistry of the Amazon: 1. Precipitation chemistry and the marine contribution to the dissolved load at the time of peak discharge, J. Geophys. Res-Oceans., 86, 9844–9858, https://doi.org/10.1029/JC086iC10p09844, 1981.
Stallard, R. F. and Edmond, J. M.: Geochemistry of the Amazon: 2. The influence of geology and weathering environment on the dissolved load, J. Geophys. Res-Oceans., 88, 9671–9688, https://doi.org/10.1029/JC088iC14p09671, 1983.
Strudley, M., Murray, A. B., and Haff, P.: Emergence of pediments, tors, and piedmont junctions from a bedrock weathering-regolith thickness feedback, Geology, 34, 805–808, https://doi.org/10.1130/G22482.1, 2006.
Suchet, P. and Probst, J.-L.: A global model for present-day atmospheric/soil CO2 consumption by chemical erosion of continental rocks (GEM-CO2), Tellus B., 47, 273–280, https://doi.org/10.1034/j.1600-0889.47.issue1.23.x, 2002.
Syvitski, J. and Milliman, J.: Geology, geography, and humans battle for dominance over the delivery of fluvial sediment to the coastal ocean, J. Geol., 115, 1–19, https://doi.org/10.1086/509246, 2007.
Walker, J. C. G., Hays, P. B., and Kasting, J. F.: A negative feedback mechanism for the long-term stabilization of Earth's surface temperature, J. Geophys. Res.-Oceans, 86, 9776–9782, https://doi.org/10.1029/JC086iC10p09776, 1981.
Wang, G., Feng, X., Han, J., Zhou, L., Tan, W., and Su, F.: Paleovegetation reconstruction using δ13C of Soil Organic Matter, Biogeosciences, 5, 1325–1337, https://doi.org/10.5194/bg-5-1325-2008, 2008.
West, A. J.: Thickness of the chemical weathering zone and implications for erosional and climatic drivers of weathering and for carbon-cycle feedbacks, Geology, 40, 811–814, https://doi.org/10.1130/g33041.1, 2012.
West, A. J., Galy, A., and Bickle, M.: Tectonic and climatic controls on silicate weathering, Earth Planet. Sc. Lett., 235, 211–228, https://doi.org/10.1016/j.epsl.2005.03.020, 2005.
Whipple, K., Heimsath, A., and DiBiase, R.: Soil production limits and the transition to bedrock-dominated landscapes, Nat. Geosci., 5, 210–214, https://doi.org/10.1038/ngeo1380, 2012.
White, A. F. and Blum, A. E.: Effects of climate on chemical weathering in watersheds, Geochim. Cosmochim. Ac., 59, 1729–1747, https://doi.org/10.1016/0016-7037(95)00078-E, 1995.
White, A. F. and Brantley, S. L.: The effect of time on the weathering of silicate minerals: Why do weathering rates differ in the laboratory and field?, Chem. Geol., 202, 479–506, https://doi.org/10.1016/j.chemgeo.2003.03.001, 2003.
Wittmann, H., Oelze, M., Gaillardet, J., Garzanti, E., and Blanckenburg, F.: A global rate of denudation from cosmogenic nuclides in the Earth's largest rivers, Earth-Sci. Rev., 204, 103147, https://doi.org/10.1016/j.earscirev.2020.103147, 2020.
Wittmann, H., Blanckenburg, F., Bourgoin, L., Guyot, J.-L., Filizola Jr., N., and Kubick, P. W.: Sediment production and delivery in the Amazon River basin quantified by in situ produced cosmogenic nuclides and recent river loads, Geol. Soc. Am. Bull., 123, 934–950, https://doi.org/10.1130/B30317.1, 2011.
Wittmann, H., Blanckenburg, F., Dannhaus, N., Bouchez, J., Gaillardet, J., Guyot, J.-L., Bourgoin, L., Roig, H., Filizola Jr, N., and Christl, M.: A test of the cosmogenic 10 Be(meteoric)/9 Be proxy for simultaneously determining basin-wide erosion rates, denudation rates, and the degree of weathering in the Amazon basin, J. Geophys. Res-Earth., 120, 2498–2528, https://doi.org/10.1002/2015JF003581, 2015.
Woillez, M.-N., Kageyama, M., Krinner, G., de Noblet-Ducoudré, N., Viovy, N., and Mancip, M.: Impact of CO2 and climate on the Last Glacial Maximum vegetation: results from the ORCHIDEE/IPSL models, Clim. Past, 7, 557–577, https://doi.org/10.5194/cp-7-557-2011, 2011.
Yao, Y.-F., Bera, S., Ferguson, D. K., Mosbrugger, V., Paudayal, K. N., Jin, J.-H., and Li, C.-S.: Reconstruction of paleovegetation and paleoclimate in the Early and Middle Eocene, Hainan Island, China, Clim. Change, 92, 169–189, https://doi.org/10.1007/s10584-008-9457-2, 2009.
Zeichner, S. S., Nghiem, J., Lamb, M. P., Takashima, N., de Leeuw, J., Ganti, V., and Fischer, W. W.: Early plant organics increased global terrestrial mud deposition through enhanced flocculation, Science, 371, 526–529, https://doi.org/10.1126/science.abd0379, 2021.
Zhang, M., Liu, Y., Zhu, J., Wang, Z., and Liu, Z.: Impact of dust on climate and AMOC during the Last Glacial Maximum simulated by CESM1.2, Geophys. Res. Lett., 49, e2021GL096672, https://doi.org/10.1029/2021GL096672, 2022.
Zhang, S., Bai, X., Zhao, C., Tan, Q., Yun, L., Wang, J., Li, L., Wu, L., Chen, F., Li, C., Deng, Y., Yang, Y., and Xi, H.: Global CO2 consumption by silicate rock chemical weathering: Its past and future, Earths Future, 9, e2020EF001938, https://doi.org/10.1029/2020EF001938, 2021.
Zhang, Y., Mills, B., Yang, T., He, T., and Zhu, M.: Simulating the long-term carbon cycle in the Phanerozoic: current status and future developments, Chinese Journal, 68, 1580–1592, https://doi.org/10.1360/TB-2022-0813, 2022.
Zuo, H.: zuohaoyue1/Silicate-weathering-model: Silicate weathering model through fitting parameters (Version v1), Zenodo [code], https://doi.org/10.5281/zenodo.8423769, 2023.
Short summary
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.
Compared to the silicate weathering fluxes measured at large river basins, the current models...
