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.
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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Hu Yang, Xiaoxu Shi, Xulong Wang, Qingsong Liu, Yi Zhong, Xiaodong Liu, Youbin Sun, Yanjun Cai, Fei Liu, Gerrit Lohmann, Martin Werner, Zhimin Jian, Tainã M. L. Pinho, Hai Cheng, Lijuan Lu, Jiping Liu, Chao-Yuan Yang, Qinghua Yang, Yongyun Hu, Xing Cheng, Jingyu Zhang, and Dake Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2778, https://doi.org/10.5194/egusphere-2024-2778, 2024
This preprint is open for discussion and under review for Climate of the Past (CP).
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The precession driven low-latitude hydrological cycle is not paced by hemispheric summer insolation, but shifting perihelion.
Silvia Pondrelli, Simone Salimbeni, Judith M. Confal, Marco G. Malusà, Anne Paul, Stephane Guillot, Stefano Solarino, Elena Eva, Coralie Aubert, and Liang Zhao
Solid Earth, 15, 827–835, https://doi.org/10.5194/se-15-827-2024, https://doi.org/10.5194/se-15-827-2024, 2024
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We analyse and interpret seismic anisotropy from CIFALPS2 data that fill the gaps in the Western Alps and support a new hypothesis. Instead of a continuous mantle flow parallel to the belt, here we find a N–S mantle deformation pattern that merges first with a mantle deformed by slab steepening beneath the Central Alps and then merges with an asthenospheric flow sourced beneath the Massif Central. This new sketch supports the extinction of slab retreat beneath the Western Alps.
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.
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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CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0
ICON ComIn – The ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
A non-intrusive, multi-scale, and flexible coupling interface in WRF
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
TorchClim v1.0: a deep-learning plugin for climate model physics
The very-high resolution configuration of the EC-Earth global model for HighResMIP
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Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
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Hector V3.2.0: functionality and performance of a reduced-complexity climate model
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Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++ and Python) and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
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This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged between WRF and any other model (e.g. an ocean model) using the coupling library Ocean-Atmosphere-Sea-Ice-Soil – Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024, https://doi.org/10.5194/gmd-17-5573-2024, 2024
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We investigate the effects of reduced-precision arithmetic in a state-of-the-art regional climate model by studying the results of 10-year-long simulations. After this time, the results of the reduced precision and the standard implementation are hardly different. This should encourage the use of reduced precision in climate models to exploit the speedup and memory savings it brings. The methodology used in this work can help researchers verify reduced-precision implementations of their model.
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024, https://doi.org/10.5194/gmd-17-5459-2024, 2024
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Machine learning (ML) of unresolved processes offers many new possibilities for improving weather and climate models, but integrating ML into the models has been an engineering challenge, and there are performance issues. We present a new software plugin for this integration, TorchClim, that is scalable and flexible and thereby allows a new level of experimentation with the ML approach. We also provide guidance on ML training and demonstrate a skillful hybrid ML atmosphere model.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-119, https://doi.org/10.5194/gmd-2024-119, 2024
Revised manuscript accepted for GMD
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10-15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100-km and a 25-km grid. The three models are compared with observations to study the improvements thanks to the increased in the resolution.
Daniel Francis James Gunning, Kerim Hestnes Nisancioglu, Emilie Capron, and Roderik van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2024-1384, https://doi.org/10.5194/egusphere-2024-1384, 2024
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This work documents the first results from ZEMBA: an energy balance model of the climate system. The model is a computationally efficient tool designed to study the response of climate to changes in the Earth’s orbit. We demonstrate ZEMBA reproduces many features of the Earth’s climate for both the pre-industrial period and the Earth’s most recent cold extreme- the Last Glacial Maximum. We intend to develop ZEMBA further and investigate the glacial cycles of the last 2.5 million years.
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
K. Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
EGUsphere, https://doi.org/10.5194/egusphere-2024-1431, https://doi.org/10.5194/egusphere-2024-1431, 2024
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The study aimed to improve the representation of spring wheat and rice in the CLM5. The modified CLM5 model performed significantly better than the default model in simulating crop phenology, yield, carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific parameters for accurately simulating vegetation processes and land surface processes.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Cited articles
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...