Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-2975-2018
© Author(s) 2018. 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-11-2975-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Jul 2018
Model description paper |
| 25 Jul 2018
| 25 Jul 2018
The NUIST Earth System Model (NESM) version 3: description and preliminary evaluation
Jian Cao
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Bin Wang
CORRESPONDING AUTHOR
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Young-Min Yang
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Libin Ma
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Juan Li
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Bo Sun
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Yan Bao
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Jie He
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Xiao Zhou
China-US joint Atmosphere-Ocean Research Center and International Pacific Research Center, University of Hawaii, Honolulu, Hawaii 96822, USA
Liguang Wu
Earth System Modeling Center, the Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Revised manuscript not accepted
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Atmos. Chem. Phys., 16, 14925–14936, https://doi.org/10.5194/acp-16-14925-2016, https://doi.org/10.5194/acp-16-14925-2016, 2016
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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.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-162, https://doi.org/10.5194/gmd-2024-162, 2024
Revised manuscript accepted for GMD
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a sub-sea CO2 injection.
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.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-133, https://doi.org/10.5194/gmd-2024-133, 2024
Revised manuscript accepted for GMD
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
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CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used for climate impact assessments, adaptation and land-use planning.
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.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
EGUsphere, https://doi.org/10.5194/egusphere-2024-2072, https://doi.org/10.5194/egusphere-2024-2072, 2024
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We outline and validate developments to the pre-existing process-based model T&C to better represent cropland processes. Foreseen applications of T&C-CROP include hydrological and carbon storage implications of land-use transitions involving crop, forest, and pasture conversion, as well as studies on optimal irrigation and fertilization under a changing climate.
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.
Ulrich Georg Wortmann, Tina Tsan, Mahrukh Niazi, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
EGUsphere, https://doi.org/10.5194/egusphere-2024-1864, https://doi.org/10.5194/egusphere-2024-1864, 2024
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The Earth Science Box Modeling Toolkit (ESBMTK) is a Python library designed to separate model description from numerical implementation. This approach results in well-documented, easily readable, and maintainable model code, allowing students and researchers to concentrate on conceptual challenges rather than mathematical intricacies.
Malcolm John Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2582, https://doi.org/10.5194/egusphere-2024-2582, 2024
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HighResMIP2 is a model intercomparison project focussing on high resolution global climate models, that is those with grid spacings of 25 km or less in atmosphere and ocean, using simulations of decades to a century or so in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present day and future projections, and to build links with other communities to provide more robust climate information.
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.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O’Rourke, and Beth Dingley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2363, https://doi.org/10.5194/egusphere-2024-2363, 2024
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The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 132 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most heavily used variables from Earth System Models, based on an assessment of data publication and download records from the largest archive of global climate projects.
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-149, https://doi.org/10.5194/gmd-2024-149, 2024
Revised manuscript accepted for GMD
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis O'Brien
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-142, https://doi.org/10.5194/gmd-2024-142, 2024
Revised manuscript accepted for GMD
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1. A metrics package designed for easy analysis of AR characteristics and statistics is presented. 2. The tool is efficient for diagnosing systematic AR bias in climate models, and useful for evaluating new AR characteristics in model simulations. 3. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the north and south Atlantic (south Pacific and Indian Ocean).
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.
Cited articles
Adcroft, A., Hill, C., and Marshall, J.: Representation of topography by shaved
cells in a height coordinate ocean model, Mon. Weather Rev., 125, 2293–2315, 1997.
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P., Janowiak, J.,
Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A. Susskind, J.,
Arkin, P., and Nelkin, E.: The version 2 Global Precipitation Climatology
Project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol.,
4, 1147–1167, 2003.
Andrews, T., Gregory, J. M., Webb, M. J., and Taylor, K. E.: Forcing, feedbacks
and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models,
Geophys. Res. Lett., 39, L09712, https://doi.org/10.1029/2012GL051607, 2012.
Bacmeister, J. T., Suarez, M. J., and Robertson, F. R.: Rain reevaporation,
boundary layer–convection interactions, and Pacific rainfall patterns in an
AGCM, J. Atmos. Sci., 63, 3383–3403, 2006.
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Treguier, A.-M., Sommer,
J. L., Beckmann, A., Biastoch, A., Boning, C., Dengg, J., Derval, C., Durand,
E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud, M., McClean, J.,
and Cuevas, B. D.: Impact of partial steps and momentum advection schemes in a
global ocean circulation model at eddy-permitting resolution, Ocean Dynam.,
56, 543–567, 2006.
Beckmann, A. and Doscher, R.: A method for improved representation of dense
water spreading over topography in geopotential-coordinate models, J. Phys.
Oceanogr., 27, 581–591, 1997.
Brinkop, S. and Roeckner, E.: Sensitivity of a general circulation model to
parameterizations of cloud-turbulence interactions in the atmospheric boundary
layer, Tellus A, 47, 197–220, 1995.
Brovkin, V., Boysen, L., Raddatz, T., Gayler, V., Loew, A., and Claussen, M.:
Evaluation of vegetation cover and landsurface albedo in MPI-ESM CMIP5
simulations, J. Adv. Model. Earth Syst., 5, 48–57, https://doi.org/10.1029/2012MS000169, 2013.
Cao, J. and Wu, L.: Asymmetric impact of last glacial maximum ice sheets on
global monsoon activity, J. Meteorol. Sci., 36, 425–435, 2016.
Cao, J., Wang, B., Xiang, B., Li, J., Wu, T., Fu, X., Wu, L., and Min, J.: Major
modes of short-term climate variability in the newly developed NUIST Earth
System Model (NESM), Adv. Atmos. Sci., 32, 585–600, https://doi.org/10.1007/s00376-014-4200-6, 2015.
Cunningham, S. A., Kanzow, T., Rayner, D., Baringer, M. O., Johns, W. E.,
Marotzke, J., Longworth, H. R., Grant, E. M., Hirschi, J. J.-M., Beal, L. M.,
Meinen, C. S., and Bryden, H. L.: Temporal variability of the Atlantic Meridional
Overturning Circulation at 26∘ N, Science, 317, 935–938, 2007.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars,
A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R.,
Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm,
E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally,
A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay,
P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis:
configuration and performance of the data assimilation system, Q. J. Roy.
Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J.,
and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project
Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9,
1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins, W.,
Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P., Guilyardi,
E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.: Evaluation of
Climate Models, in: Climate Change 2013: The Physical Science Basis, Contribution
of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor,
M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M.,
Cambridge University Press, Cambridge, UK and New York, NY, USA, 2013.
Fu, X. and Wang, B.: Critical roles of the stratiform rainfall in sustaining
the Madden-Julian Oscillation: GCM Experiments, J. Climate, 22, 3939–3959, 2009.
Gent, P. R. and McWilliams, J. C.: Isopycnal mixing in ocean circulation models,
J. Phys. Oceanogr., 20, 150–155, 1990.
Giorgetta, M. A., Roeckner, E., Mauritsen, T., Bader, J., Crueger, T., Esch, M.,
Rast, S., Kornblueh, L., Schmidt, H., Kinne, S., Hohenegger, C., Möbis, B.,
Krismer, T., Wieners, K.-H., and Stevens, B.: The Atmospheric General Circulation
Model ECHAM6: Model Description, Tech. rep., Max Planck Institute for Meteorology,
Hamburg, Germany, 2013.
Gregory, J. M. and Webb, M. J.: Tropospheric adjustment induces a cloud component
in CO2 forcing, J. Climate, 21, 58–71, https://doi.org/10.1175/2007JCLI1834.1, 2008.
Gregory, J. M., Ingram, W. J., Palmer, M. A., Jones, G. S., Stott, P. A., Thorpe,
R. B., Lowe, J. A., Johns, T. C., and Williams, K. D.: A new method for
diagnosing radiative forcing and climate sensitivity, Geophys. Res. Lett., 31,
L03205, https://doi.org/10.1029/2003GL018747, 2004.
Ham, Y.-G. and Kug, J.-S.: ENSO phase-locking to the boreal winter in CMIP3 and
CMIP5 models, Clim. Dynam., 43, 305–318, https://doi.org/10.1007/s00382-014-2064-1, 2014.
Hansen, J., Sato, M., Ruedy, R., Nazarenko, L., Lacis, A., Schmidt, G. A.,
Russell, G., Aleinov, I., Bauer, M., Bauer, S., Bell, N., Cairns, B., Canuto,
V., Chandler, M., Cheng, Y., Del Genio, A., Faluvegi, G., Fleming, E., Friend,
A., Hall, T., Jackman, C., Kelley, M., Kiang, N., Koch, D., Lean, J., Lerner,
J., Lo, K., Menon, S., Miller, R., Minnis, P., Novakov, T., Oinas, V., Perlwitz,
Ja., Perlwitz, Ju., Rind, D., Romanou, A., Shindell, D., Stone, P., Sun, S.,
Tausnev, N., Thresher, D., Wielicki, B., Wong, T., Yao, M., and Zhang, S.:
Efficacy of climate forcings, J. Geophys. Res., 110, D18104, https://doi.org/10.1029/2005JD005776, 2005a.
Hansen, J., Nazarenko, L., Ruedy, R., Sato, M., Willis, J., DelGenio, A., Koch,
D., Lacis, A., Lo, K., Menon, S., Novakov, T., Perlwitz, J., Russell, G., Schmidt,
G. A., and Tausnev, N.: Earth's energy imbalance: Confirmation and implications,
Science, 308, 1431–1435, https://doi.org/10.1126/science.1110252, 2005b.
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, 2014.
Held, I. M. and Soden, B. J.: Robust response of the hydrological cycle to
global warming, J. Climate, 19, 5686–5699, 2006.
Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J.-C., Balaji, V., Duan, Q.,
Folini, D., Ji, D., Klocke, D., Qian, Y., Rauser, F., Rio, C., Tomassini, L.,
Watanabe, M., and Williamson, D.: The art and science of climate model tuning,
B. Am. Meteorol. Soc., 98, 589–602, https://doi.org/10.1175/bams-d-15-00135.1, 2017.
Hunke, E. C.: Thickness sensitivities in the CICE sea ice model, Ocean Model.,
34, 137–149, https://doi.org/10.1016/j.ocemod.2010.05.004, 2010.
Hunke, E. C. and Dukowicz, J. K.: The elastic–viscous–plastic sea ice dynamics
model in general orthogonal curvilinear coordinates on a sphere – Incorporation
of metric terms, Mon. Weather Rev., 130, 1848–1865, 2002.
Hunke, E. C. and Lipscomb, W. H.: CICE: The Los Alamos Sea Ice Model Documentation
and Software User's Manual Version 4.1, LA-CC-06-012, T-3 Fluid Dynamics Group,
Los Alamos National Laboratory, Los Alamos, NM, 2010.
Iacono, M., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and
Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations
with the AER radiative transfer models, J. Geophys. Res., 113, D13103,
https://doi.org/10.1029/2008JD009944, 2008.
Lee, J. Y. and Wang, B.: Future change of global monsoon in the CMIP5, Clim.
Dynam., 42, 101–119, 2014.
Lengaigne, M., Madec, G. Bopp, L. Menkes, C. Aumont, O., and Cadule, P.:
Bio-physical feedbacks in the Arctic Ocean using an Earth system model, Geophys.
Res. Lett., 36, L21602, https://doi.org/10.1029/2009GL040145, 2009.
Li, J., Wang, B., and Yang, Y. M.: Retrospective seasonal prediction of summer
monsoon rainfall over West Central and Peninsular India in the past 142 years,
Clim. Dynam., 48, 2581–2596, 2017.
Locarnini, R. A., Mishonov, A. V., Antonov, J. I., Boyer, T. P., Garcia, H. E.,
Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World Ocean Atlas 2009, in:
Volume 1: Temperature, NOAA Atlas NESDIS 68, edited by: Levitus, S.,
US Government Printing Office, Washington, D.C., 184 pp., 2010.
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F., Kato,
S., Manalo-Smith, N., and Wong, T.: Toward Optimal Closure of the Earth's
Top-of-Atmosphere Radiation Budget, J. Climate, 22, 748–766, https://doi.org/10.1175/2008JCLI2637.1, 2009.
Lott, F.: Alleviation of Stationary Biases in a GCM through a Mountain Drag
Parameterization Scheme and a Simple Representation of Mountain Lift Forces,
Mon. Weather Rev., 127, 788–801, 1999.
Lott, F. and Miller, M. J.: A new-subgrid-scale orographic drag parameterization:
Its formulation and testing, Q. J. Roy. Meteorol. Soc., 123, 101–127, 1997.
Luo, X. and Wang, B.: Predictability and prediction of the total number of
winter extremely cold days over China, Clim. Dynam., 50, 1769–1784, 2018.
Madec, G. and Imbard, M.: A global ocean mesh to overcome the North Pole
singularity, Clim. Dynam., 12, 381–388, 1996.
Mahajan., S., Zhang, R., and Delworth, T. L.: Impact of the Atlantic Meridional
Overturning circulation (AMOC) on Arctic surface air temperature and sea ice
variability, J. Climate, 24, 6573–6581, 2011.
Mauritsen, T., Stevens, B., Roeckner, E., Crueger, T., Esch, M., Giorgetta, M.,
Haak, H., Jungclaus, J., Klocke, D., Matei, D., Mikolajewicz, U., Notz, D.,
Pincus, R., Schmidt, H., and Tomassini, L.: Tuning the climate of a global model,
J. Adv. Model. Earth Syst., 4, M00A01, https://doi.org/10.1029/2012MS000154, 2012.
Meehl, G. A., Boer, G. J., Covey, C., Latif, M., and Stouffer, R. J.: The
Coupled Model Intercomparison Project (CMIP), B. Am. Meterool. Soc., 81, 313–318, 2000.
Nordeng, T. E.: Extended versions of the convective parameterization scheme at
ECMWF and their impact on the mean and transient activity of the model in the
tropics, Tech. Rep. 206, ECMWF, Reading, 1994.
Raddatz, T. J., Reick, C. H., Knorr, W., Kattge, J., Roeckner, E., Schnur, R.,
Schnitzler, K.-G., Wetzel, P., and Jungclaus, J.: Will the tropical land
biosphere dominate the climate-carbon cycle feedback during the twenty-first
century?, Clim. Dynam., 29, 565–574, 2007.
Rahmstorf, S.: Bifurcations of the Atlantic thermohaline circulation in response
to changes in the hydrological cycle, Nature, 378, 145–149, 1995.
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V.,
Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface
temperature, sea ice, and nightmarine air temperature since the late nineteenth
century, J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003.
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J. Phys. Oceanogr.,
12, 1154–1158, 1982.
Rothrock, D. A.: The energetics of the plastic deformation of pack ice by
ridging, J. Geophys. Res., 80, 4514–4519, 1975.
Roullet, G. and Madec, G.: Salt conservation, free surface and varying volume:
A new formulation for ocean GCMs, J. Geophys. Res., 105, 23927–23942, 2000.
Screen, J. A. and Simmonds, I.: The central role of diminishing sea ice in
recent Arctic temperature amplification, Nature, 464, 1334–1337, https://doi.org/10.1038/nature09051, 2010.
Simmons, A. J. and Burridge, D. M.: An energy and angular-momentum conserving
vertical finite difference scheme and hybrid vertical coordinates, Mon. Weather
Rev., 109, 758–766, 1981.
Song, X. and Zhang, G.: Convection parameterization, tropical Pacific double
ITCZ, and upper-ocean biases in the NCAR CCSM3. Part I: Climatology and
atmospheric feedback, J. Climate, 22, 4299–4315, 2009.
Sterl., A., Bintanja, R., Brodean, L., Gleeson, E., Koenigk, T., Schmith, T.,
Semmler, T., Severijns, C., Wyser, K., and Yang, S.: A look at the ocean in the
EC-Earth climate model, Clim. Dynam., 29, 2631–2657, 2012.
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S.,
Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne,
S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: The
atmospheric component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model.
Earth Syst., 5, 46–172, https://doi.org/10.1002/jame.20015, 2012.
Sundqvist, H., Berge, E., and Kristjansson, J.: Condensation and cloud
parameterization studies with a mesoscale numerical weather prediction model,
Mon. Weather Rev., 117, 1641–1657, 1989.
Tiedtke, M.: A Comprehensive Mass Flux Scheme for Cumulus Parameterization in
Large-Scale Models, Mon. Weather Rev., 117, 1779–1800, 1989.
Urrego-Blanco, J. R., Urban, N. M., Hunke, E. C., Turner, A. K., and Jeffery,
N.: Uncertainty quantification and global sensitivity analysis of the Los Alamos
sea ice model, J. Geophys. Res.-Oceans, 121, 2709–2732, https://doi.org/10.1002/2015JC011558, 2016.
Valcke, S. and Coquart, L.: OASIS3-MCT User Guide, OASIS3-MCT 3.0. CERFACS
Technical Report, CERFACS TR/CMGC/15/38, Toulouse, France, available at:
http://www.cerfacs.fr/oa4web/oasis3-mct_3.0/oasis3mct_UserGuide.pdf
(last access: July 2018), 2015.
Webb, M. J., Senior, C. A., Sexton, D. M. H., Ingram, W. J., Williams, K. D.,
Ringer, M. A., McAvaney, B. J., Colman, R., Soden, B. J., Gudgel, R., Knutson,
T., Emori, S., Ogura, T., Tsushima, Y., Andronova, N., Li, B., Musat, I., Bony,
S., and Taylor, K. E.: On the contribution of local feedback mechanisms to the
range of climate sensitivity in two GCM ensembles, Clim. Dynam., 27, 17–38, 2006.
Wengel, C., Latif, M., Park, W., Harlaß, J., and Bayr, T.: Seasonal ENSO
phase locking in the Kiel Climate Model: The importance of the equatorial cold
sea surface temperature bias, Clim. Dynam., 50, 901–919, https://doi.org/10.1007/s00382-017-3648-3, 2018.
Xiang, B., Zhao, M., Held, I. M., and Golaz, J.-C.: Predicting the severity of
spurious `double ITCZ' problem in CMIP5 coupled models from AMIP simulations,
Geophys. Res. Lett., 44, 1520–1527, 2017.
Xie, P. and Arkin, P. A.: Global precipitation: A 17-year monthly analysis
based on gauge observations, satellite estimates, and numerical model outputs,
B. Am. Meteorol. Soc., 78, 2539–2558, 1997.
Zalesak, S. T.: Fully multidimensional flux corrected transport algorithms for
fluids, J. Comput. Phys., 31, 335–362, 1979.
Zdunkowski, W. G., Welch, R. M., and Korb, G. J.: An investigation of the
structure of typical two-stream methods for the calculation of solar fluxes and
heating rates in clouds, Beitr. Phys. Atmos., 53, 147–166, 1980.
Short summary
The development of version 3 of the Nanjing University of Information Science and Technology (NUIST) Earth System Model (NESM v3) aims at building up a comprehensive numerical modeling laboratory for multidisciplinary studies of the climate system and Earth system. The model evaluation shows the model obtained stable long-term integrations and reasonable global mean states under preindustrial (PI) forcing and simulated reasonable climate responses to transient and abrupt CO2 forcing.
The development of version 3 of the Nanjing University of Information Science and Technology...
