Articles | Volume 14, issue 5
https://doi.org/10.5194/gmd-14-2843-2021
© Author(s) 2021. 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-14-2843-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
20 May 2021
Model description paper |
| 20 May 2021
| 20 May 2021
TransEBM v. 1.0: description, tuning, and validation of a transient model of the Earth's energy balance in two dimensions
Elisa Ziegler
CORRESPONDING AUTHOR
Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany
Kira Rehfeld
CORRESPONDING AUTHOR
Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany
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Elisa Ziegler, Nils Weitzel, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lauren Gregoire, Ruza Ivanovic, Paul J. Valdes, Christian Wirths, and Kira Rehfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-1396, https://doi.org/10.5194/egusphere-2024-1396, 2024
Short summary
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During the Last Deglaciation global surface temperature rose by about 4–7 degrees over several millennia. We show that changes of year-to-year up to century-to-century fluctuations of temperature and precipitation during the Deglaciation were mostly larger than during either the preceding or succeeding more stable periods in fifteen climate model simulations. The analysis demonstrates how ice sheets, meltwater and volcanism influence simulated variability to inform future simulation protocols.
Nils Weitzel, Heather Andres, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lukas Jonkers, Oliver Bothe, Elisa Ziegler, Thomas Kleinen, André Paul, and Kira Rehfeld
Clim. Past, 20, 865–890, https://doi.org/10.5194/cp-20-865-2024, https://doi.org/10.5194/cp-20-865-2024, 2024
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The ability of climate models to faithfully reproduce past warming episodes is a valuable test considering potentially large future warming. We develop a new method to compare simulations of the last deglaciation with temperature reconstructions. We find that reconstructions differ more between regions than simulations, potentially due to deficiencies in the simulation design, models, or reconstructions. Our work is a promising step towards benchmarking simulations of past climate transitions.
Christian Wirths, Elisa Ziegler, and Kira Rehfeld
EGUsphere, https://doi.org/10.5194/egusphere-2023-86, https://doi.org/10.5194/egusphere-2023-86, 2023
Preprint archived
Short summary
Short summary
We compare Holocene temperature trends from reconstructions and global climate models of different complexities. We find that models of all complexities disagree with mid-Holocene trends in reconstructions, and we show that this disagreement is largely independent of the type of reconstruction. From our results we conclude that a seasonal bias in the reconstructions is unlikely as a full explanation for the disagreement.
Mathurin A. Choblet, Janica C. Bühler, Valdir F. Novello, Nathan J. Steiger, and Kira Rehfeld
Clim. Past, 20, 2117–2141, https://doi.org/10.5194/cp-20-2117-2024, https://doi.org/10.5194/cp-20-2117-2024, 2024
Short summary
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Past climate reconstructions are essential for understanding climate mechanisms and drivers. Our focus is on the South American continent over the past 2000 years. We offer a new reconstruction that particularly utilizes data from speleothems, previously absent from continent-wide reconstructions. We use paleoclimate data assimilation, a reconstruction method that combines information from climate archives and climate simulations.
Jean-Philippe Baudouin, Nils Weitzel, Maximilian May, Lukas Jonkers, Andrew M. Dolman, and Kira Rehfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-1387, https://doi.org/10.5194/egusphere-2024-1387, 2024
Short summary
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We explore past global temperatures, critical for climate change comprehension. We devise a method to test temperature reconstruction using climate simulations. Uncertainties, mainly from past temperature measurement methods and age determination, impact reconstructions over time. While more data enhances accuracy for long-term trends, high quality data are more important for short-term precision. Our study lays the groundwork for better reconstructions and suggests avenues for improvement.
Elisa Ziegler, Nils Weitzel, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lauren Gregoire, Ruza Ivanovic, Paul J. Valdes, Christian Wirths, and Kira Rehfeld
EGUsphere, https://doi.org/10.5194/egusphere-2024-1396, https://doi.org/10.5194/egusphere-2024-1396, 2024
Short summary
Short summary
During the Last Deglaciation global surface temperature rose by about 4–7 degrees over several millennia. We show that changes of year-to-year up to century-to-century fluctuations of temperature and precipitation during the Deglaciation were mostly larger than during either the preceding or succeeding more stable periods in fifteen climate model simulations. The analysis demonstrates how ice sheets, meltwater and volcanism influence simulated variability to inform future simulation protocols.
Nikita Kaushal, Franziska A. Lechleitner, Micah Wilhelm, Khalil Azennoud, Janica C. Bühler, Kerstin Braun, Yassine Ait Brahim, Andy Baker, Yuval Burstyn, Laia Comas-Bru, Jens Fohlmeister, Yonaton Goldsmith, Sandy P. Harrison, István G. Hatvani, Kira Rehfeld, Magdalena Ritzau, Vanessa Skiba, Heather M. Stoll, József G. Szűcs, Péter Tanos, Pauline C. Treble, Vitor Azevedo, Jonathan L. Baker, Andrea Borsato, Sakonvan Chawchai, Andrea Columbu, Laura Endres, Jun Hu, Zoltán Kern, Alena Kimbrough, Koray Koç, Monika Markowska, Belen Martrat, Syed Masood Ahmad, Carole Nehme, Valdir Felipe Novello, Carlos Pérez-Mejías, Jiaoyang Ruan, Natasha Sekhon, Nitesh Sinha, Carol V. Tadros, Benjamin H. Tiger, Sophie Warken, Annabel Wolf, Haiwei Zhang, and SISAL Working Group members
Earth Syst. Sci. Data, 16, 1933–1963, https://doi.org/10.5194/essd-16-1933-2024, https://doi.org/10.5194/essd-16-1933-2024, 2024
Short summary
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Speleothems are a popular, multi-proxy climate archive that provide regional to global insights into past hydroclimate trends with precise chronologies. We present an update to the SISAL (Speleothem Isotopes
Synthesis and AnaLysis) database, SISALv3, which, for the first time, contains speleothem trace element records, in addition to an update to the stable isotope records available in previous versions of the database, cumulatively providing data from 365 globally distributed sites.
Synthesis and AnaLysis) database, SISALv3, which, for the first time, contains speleothem trace element records, in addition to an update to the stable isotope records available in previous versions of the database, cumulatively providing data from 365 globally distributed sites.
Nils Weitzel, Heather Andres, Jean-Philippe Baudouin, Marie-Luise Kapsch, Uwe Mikolajewicz, Lukas Jonkers, Oliver Bothe, Elisa Ziegler, Thomas Kleinen, André Paul, and Kira Rehfeld
Clim. Past, 20, 865–890, https://doi.org/10.5194/cp-20-865-2024, https://doi.org/10.5194/cp-20-865-2024, 2024
Short summary
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The ability of climate models to faithfully reproduce past warming episodes is a valuable test considering potentially large future warming. We develop a new method to compare simulations of the last deglaciation with temperature reconstructions. We find that reconstructions differ more between regions than simulations, potentially due to deficiencies in the simulation design, models, or reconstructions. Our work is a promising step towards benchmarking simulations of past climate transitions.
Julie Christin Schindlbeck-Belo, Matthew Toohey, Marion Jegen, Steffen Kutterolf, and Kira Rehfeld
Earth Syst. Sci. Data, 16, 1063–1081, https://doi.org/10.5194/essd-16-1063-2024, https://doi.org/10.5194/essd-16-1063-2024, 2024
Short summary
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Volcanic forcing of climate resulting from major explosive eruptions is a dominant natural driver of past climate variability. To support model studies of the potential impacts of explosive volcanism on climate variability across timescales, we present an ensemble reconstruction of volcanic stratospheric sulfur injection over the last 140 000 years that is based primarily on tephra records.
Christian Wirths, Elisa Ziegler, and Kira Rehfeld
EGUsphere, https://doi.org/10.5194/egusphere-2023-86, https://doi.org/10.5194/egusphere-2023-86, 2023
Preprint archived
Short summary
Short summary
We compare Holocene temperature trends from reconstructions and global climate models of different complexities. We find that models of all complexities disagree with mid-Holocene trends in reconstructions, and we show that this disagreement is largely independent of the type of reconstruction. From our results we conclude that a seasonal bias in the reconstructions is unlikely as a full explanation for the disagreement.
Janica C. Bühler, Josefine Axelsson, Franziska A. Lechleitner, Jens Fohlmeister, Allegra N. LeGrande, Madhavan Midhun, Jesper Sjolte, Martin Werner, Kei Yoshimura, and Kira Rehfeld
Clim. Past, 18, 1625–1654, https://doi.org/10.5194/cp-18-1625-2022, https://doi.org/10.5194/cp-18-1625-2022, 2022
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We collected and standardized the output of five isotope-enabled simulations for the last millennium and assess differences and similarities to records from a global speleothem database. Modeled isotope variations mostly arise from temperature differences. While lower-resolution speleothems do not capture extreme changes to the extent of models, they show higher variability on multi-decadal timescales. As no model excels in all comparisons, we advise a multi-model approach where possible.
Raphaël Hébert, Kira Rehfeld, and Thomas Laepple
Nonlin. Processes Geophys., 28, 311–328, https://doi.org/10.5194/npg-28-311-2021, https://doi.org/10.5194/npg-28-311-2021, 2021
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Paleoclimate proxy data are essential for broadening our understanding of climate variability. There remain, however, challenges for traditional methods of variability analysis to be applied to such data, which are usually irregular. We perform a comparative analysis of different methods of scaling analysis, which provide variability estimates as a function of timescales, applied to irregular paleoclimate proxy data.
Janica C. Bühler, Carla Roesch, Moritz Kirschner, Louise Sime, Max D. Holloway, and Kira Rehfeld
Clim. Past, 17, 985–1004, https://doi.org/10.5194/cp-17-985-2021, https://doi.org/10.5194/cp-17-985-2021, 2021
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We present three new isotope-enabled simulations for the last millennium (850–1850 CE) and compare them to records from a global speleothem database. Offsets between the simulated and measured oxygen isotope ratios are fairly small. While modeled oxygen isotope ratios are more variable on decadal timescales, proxy records are more variable on (multi-)centennial timescales. This could be due to a lack of long-term variability in complex model simulations, but proxy biases cannot be excluded.
Laia Comas-Bru, Kira Rehfeld, Carla Roesch, Sahar Amirnezhad-Mozhdehi, Sandy P. Harrison, Kamolphat Atsawawaranunt, Syed Masood Ahmad, Yassine Ait Brahim, Andy Baker, Matthew Bosomworth, Sebastian F. M. Breitenbach, Yuval Burstyn, Andrea Columbu, Michael Deininger, Attila Demény, Bronwyn Dixon, Jens Fohlmeister, István Gábor Hatvani, Jun Hu, Nikita Kaushal, Zoltán Kern, Inga Labuhn, Franziska A. Lechleitner, Andrew Lorrey, Belen Martrat, Valdir Felipe Novello, Jessica Oster, Carlos Pérez-Mejías, Denis Scholz, Nick Scroxton, Nitesh Sinha, Brittany Marie Ward, Sophie Warken, Haiwei Zhang, and SISAL Working Group members
Earth Syst. Sci. Data, 12, 2579–2606, https://doi.org/10.5194/essd-12-2579-2020, https://doi.org/10.5194/essd-12-2579-2020, 2020
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This paper presents an updated version of the SISAL (Speleothem Isotope Synthesis and Analysis) database. This new version contains isotopic data from 691 speleothem records from 294 cave sites and new age–depth models, including their uncertainties, for 512 speleothems.
Kira Rehfeld, Raphaël Hébert, Juan M. Lora, Marcus Lofverstrom, and Chris M. Brierley
Earth Syst. Dynam., 11, 447–468, https://doi.org/10.5194/esd-11-447-2020, https://doi.org/10.5194/esd-11-447-2020, 2020
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Under continued anthropogenic greenhouse gas emissions, it is likely that global mean surface temperature will continue to increase. Little is known about changes in climate variability. We analyze surface climate variability and compare it to mean change in colder- and warmer-than-present climate model simulations. In most locations, but not on subtropical land, simulated temperature variability up to decadal timescales decreases with mean temperature, and precipitation variability increases.
Laia Comas-Bru, Sandy P. Harrison, Martin Werner, Kira Rehfeld, Nick Scroxton, Cristina Veiga-Pires, and SISAL working group members
Clim. Past, 15, 1557–1579, https://doi.org/10.5194/cp-15-1557-2019, https://doi.org/10.5194/cp-15-1557-2019, 2019
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We use an updated version of the Speleothem Isotopes Synthesis and Analysis (SISAL) database and palaeoclimate simulations generated using the ECHAM5-wiso isotope-enabled climate model to provide a protocol for using speleothem isotopic data for model evaluation, including screening the observations and the optimum period for the modern observational baseline. We also illustrate techniques through which the absolute isotopic values during any time period could be used for model evaluation.
Matthias M. May and Kira Rehfeld
Earth Syst. Dynam., 10, 1–7, https://doi.org/10.5194/esd-10-1-2019, https://doi.org/10.5194/esd-10-1-2019, 2019
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Current CO2 emission rates are incompatible with the 2 °C target for global warming. Negative emission technologies are therefore an important basis for climate policy scenarios. We show that photoelectrochemical CO2 reduction might be a viable, high-efficiency alternative to biomass-based approaches, which reduce competition for arable land. To develop them, chemical reactions have to be optimized for CO2 removal, which deviates from energetic efficiency optimization in solar fuel applications.
Kira Rehfeld, Mathias Trachsel, Richard J. Telford, and Thomas Laepple
Clim. Past, 12, 2255–2270, https://doi.org/10.5194/cp-12-2255-2016, https://doi.org/10.5194/cp-12-2255-2016, 2016
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Indirect evidence on past climate comes from the former composition of ecological communities such as plants, preserved as pollen grains in sediments of lakes. Transfer functions convert relative counts of species to a climatologically meaningful scale (e.g. annual mean temperature in degrees C). We show that the fundamental assumptions in the algorithms impact the reconstruction results in he idealized model world, in particular if the reconstructed variables were not ecologically relevant.
K. Rehfeld, N. Molkenthin, and J. Kurths
Nonlin. Processes Geophys., 21, 691–703, https://doi.org/10.5194/npg-21-691-2014, https://doi.org/10.5194/npg-21-691-2014, 2014
L. Tupikina, K. Rehfeld, N. Molkenthin, V. Stolbova, N. Marwan, and J. Kurths
Nonlin. Processes Geophys., 21, 705–711, https://doi.org/10.5194/npg-21-705-2014, https://doi.org/10.5194/npg-21-705-2014, 2014
N. Molkenthin, K. Rehfeld, V. Stolbova, L. Tupikina, and J. Kurths
Nonlin. Processes Geophys., 21, 651–657, https://doi.org/10.5194/npg-21-651-2014, https://doi.org/10.5194/npg-21-651-2014, 2014
K. Rehfeld and J. Kurths
Clim. Past, 10, 107–122, https://doi.org/10.5194/cp-10-107-2014, https://doi.org/10.5194/cp-10-107-2014, 2014
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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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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.
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.
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.
Deifilia Aurora To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
EGUsphere, https://doi.org/10.5194/egusphere-2024-1714, https://doi.org/10.5194/egusphere-2024-1714, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers three-dimensional 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 accessibility of training and working with the model.
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.
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. Discuss., https://doi.org/10.5194/gmd-2024-98, https://doi.org/10.5194/gmd-2024-98, 2024
Revised manuscript accepted for GMD
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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 range of data is likely encountered outside the calibration period. The end result is highly dependent on the method used, and we show that one needs to exclude data in the calibration range to activate the extrapolation functionality also in that time period, else there will be discontinuities in the timeseries.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-1456, https://doi.org/10.5194/egusphere-2024-1456, 2024
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We evaluate downscaled products by examining locally relevant covariances during convective and frontal precipitation events. Common statistical downscaling techniques preserve expected covariances during convective precipitation. However, they dampen future intensification of frontal precipitation captured in global climate models and dynamical downscaling. This suggests statistical downscaling may not fully resolve non-stationary hydrologic processes as compared to dynamical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-97, https://doi.org/10.5194/gmd-2024-97, 2024
Revised manuscript accepted for GMD
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Research software is crucial for scientific progress but is often developed by scientists with limited training, time, and funding, leading to software that is hard to understand, (re)use, modify, and maintain. Our study across 10 research sectors highlights strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. Recommendations include workshops, code quality metrics, funding, and adherence to FAIR standards.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-70, https://doi.org/10.5194/gmd-2024-70, 2024
Revised manuscript accepted for GMD
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Hurricanes may worsen the water quality in the lower Mississippi River Basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate-nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in LMRB during Hurricane Ida in 2021, but less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni G. Seijo-Ellis, Donata Giglio, Gustavo M. Marques, and Frank O. Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1378, https://doi.org/10.5194/egusphere-2024-1378, 2024
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A CESM/MOM6 regional configuration of the Caribbean Sea was developed as a response to the rising need of high-resolution models for climate impact studies. The configuration is validated for the period of 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 across the multiple passages in the Caribbean Sea agree with observations.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
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. Discuss., https://doi.org/10.5194/gmd-2024-85, https://doi.org/10.5194/gmd-2024-85, 2024
Revised manuscript accepted for GMD
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This study provides the first comprehensive assessment of historical fire simulations from 19 CMIP6 ESMs. Most models reproduce global total, spatial pattern, seasonality, and regional historical changes well, but fail to simulate the recent decline in global burned area and underestimate the fire sensitivity to wet-dry conditions. They addressed three critical issues in CMIP5. We present targeted guidance for fire scheme development and methodologies to generate reliable fire projections.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Giovanni Di Virgilio, Jason Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew Riley, and Jyothi Lingala
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-87, https://doi.org/10.5194/gmd-2024-87, 2024
Revised manuscript accepted for GMD
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models, and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleußner
EGUsphere, https://doi.org/10.5194/egusphere-2024-278, https://doi.org/10.5194/egusphere-2024-278, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Their joint distribution largely determines the division into climate regimes. Yet, projecting 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 to generate monthly means of local precipitation and temperature at low computational costs.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
Short summary
Short summary
In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Cited articles
Abe-Ouchi, A., Saito, F., Kawamura, K., Raymo, M. E., Okuno, J., Takahashi, K.,
and Blatter, H.: Insolation-driven 100,000-year glacial cycles and
hysteresis of ice-sheet volume, Nature, 500, 190–193,
https://doi.org/10.1038/nature12374, 2013. a
Andres, H. J. and Tarasov, L.: Towards understanding potential atmospheric contributions to abrupt climate changes: characterizing changes to the North Atlantic eddy-driven jet over the last deglaciation, Clim. Past, 15, 1621–1646, https://doi.org/10.5194/cp-15-1621-2019, 2019. a
Bathiany, S., Dijkstra, H., Crucifix, M., Dakos, V., Brovkin, V., Williamson,
M. S., Lenton, T. M., and Scheffer, M.: Beyond bifurcation: using complex
models to understand and predict abrupt climate change, Dynamics and
Statistics of the Climate System, https://doi.org/10.1093/climsys/dzw004, 2016. a, b
Berger, A. L.: Long-Term Variations of Daily Insolation and Quaternary
Climatic Changes, J. Atmos. Sci., 35, 2362–2367,
https://doi.org/10.1175/1520-0469(1978)035<2362:LTVODI>2.0.CO;2, 1978. a, b, c, d
Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte,
V., Abe-Ouchi, A., Otto-Bliesner, B., and Zhao, Y.: Evaluation of climate
models using palaeoclimatic data, Nat. Clim. Change, 2, 417–424,
https://doi.org/10.1038/nclimate1456, 2012. a
Briggs, W. L., Hensen, V. E., and McCormick, S. F.: A Multigrid Tutorial,
Society for Industrial and Applied Mathematics, 2nd Edn.,
https://doi.org/10.1137/1.9780898719505, 2000. a
Budyko, M. I.: The effect of solar radiation variations on the climate of the
Earth, Tellus, 21, 611–619, https://doi.org/10.3402/tellusa.v21i5.10109, 1968. a, b, c, d
Bühler, J. C., Roesch, C., Kirschner, M., Sime, L., Holloway, M. D., and Rehfeld, K.: Comparison of the oxygen isotope signatures in speleothem records and iHadCM3 model simulations for the last millennium, Clim. Past Discuss. [preprint], https://doi.org/10.5194/cp-2020-121, in review, 2020. a, b, c
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T.,
Friedlingstein, P., Gao, X., Gutowski, W., Johns, T., Krinner, G., Shongwe,
M., Tebaldi, C., Weaver, A., and Wehner, M.: Long-term Climate Change:
Projections, Commitments and Irreversibility, book section 12,
Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, 1029–1136, https://doi.org/10.1017/CBO9781107415324.024, 2013. a
Crowley, T. J. and Hyde, W. T.: Transient nature of late Pleistocene climate
variability, Nature, 456, 226–230, https://doi.org/10.1038/nature07365, 2008. a
Crowley, T. J. and North, G. R.: Abrupt climate change and Extinction Events
in Earth History, Science, 240, 996–1002, 1988. a
Crowley, T. J. and North, G. R.: Modeling onset of glaciation, Ann.
Glaciol., 14, 39–42, https://doi.org/10.3189/S0260305500008223, 1990. a, b, c
Crowley, T. J., Short, D. A., Mengel, J. G., and North, G. R.: Role of
seasonality in the evolution of climate during the last 100 million years,
Science, 231, 579–584, https://doi.org/10.1126/science.231.4738.579, 1986. a, b, c
Crowley, T. J., Mengel, J. G., and Short, D. A.: Gondwanaland's seasonal
cycle, Nature, 329, 803–807, https://doi.org/10.1038/329803a0, 1987. a
Crowley, T. J., Hyde, W. T., and Short, D. A.: Seasonal cycle variations on
the supercontinent of Pangaea, Geology, 17, 457–460,
https://doi.org/10.1130/0091-7613(1989)017<0457:SCVOTS>2.3.CO;2, 1989. a, b, c, d
Dommenget, D., Nice, K., Bayr, T., Kasang, D., Stassen, C., and Rezny, M.: The Monash Simple Climate Model experiments (MSCM-DB v1.0): an interactive database of mean climate, climate change, and scenario simulations, Geosci. Model Dev., 12, 2155–2179, https://doi.org/10.5194/gmd-12-2155-2019, 2019. a
Dortmans, B., Langford, W. F., and Willms, A. R.: An energy balance model for paleoclimate transitions, Clim. Past, 15, 493–520, https://doi.org/10.5194/cp-15-493-2019, 2019. a
Fraedrich, K., Bordi, I., and Zhu, X.: Climate dynamics on global scale:
resilience, hysteresis and attribution of change, CISM International Centre
for Mechanical Sciences, Courses and Lectures, 564, 143–159,
https://doi.org/10.1007/978-3-7091-1893-1_6, 2016. a, b
Ghil, M.: A Mathematical Theory of Climate Sensitivity or, How to Deal With
Both Anthropogenic Forcing and Natural Variability?, in: Climate Change:
Multidecadal and Beyond, edited by: Chang, C.-P., Ghil, M., Latif, M., and
Wallace, J. M., chap. 2, World Scientific, 31–51,
https://doi.org/10.1142/9789814579933_0002, 2015. a, b
Goosse, H., Brovkin, V., Fichefet, T., Haarsma, R., Huybrechts, P., Jongma, J., Mouchet, A., Selten, F., Barriat, P.-Y., Campin, J.-M., Deleersnijder, E., Driesschaert, E., Goelzer, H., Janssens, I., Loutre, M.-F., Morales Maqueda, M. A., Opsteegh, T., Mathieu, P.-P., Munhoven, G., Pettersson, E. J., Renssen, H., Roche, D. M., Schaeffer, M., Tartinville, B., Timmermann, A., and Weber, S. L.: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603–633, https://doi.org/10.5194/gmd-3-603-2010, 2010. a
Gordon, C., Cooper, C., Senior, C. A., Banks, H., Gregory, J. M., Johns, T. C.,
Mitchell, J. F. B., and Wood, R. A.: The simulation of SST, sea ice extents
and ocean heat transports in a version of the Hadley Centre coupled model
without flux adjustments, Clim. Dynam., 16, 147–168,
https://doi.org/10.1007/s003820050010, 2000. a, b, c
Grant, K. M., Rohling, E. J., Bar-Matthews, M., Ayalon, A., Medina-Elizalde,
M., Ramsey, C. B., Satow, C., and Roberts, A. P.: Rapid coupling between ice
volume and polar temperature over the past 150,000 years, Nature, 491,
744–747, https://doi.org/10.1038/nature11593, 2012. a, b, c, d
Harvey, L. D. and Schneider, S. H.: Transient climate response to external
forcing on 100-104 year time scales, 2. Sensitivity experiments with a
seasonal, hemispherically averaged, coupled atmosphere, land, and ocean
energy balance model, J. Geophys. Res., 90, 2207–2222,
https://doi.org/10.1029/JD090iD01p02207, 1985. a
Hébert, R., Lovejoy, S., and Tremblay, B.: An observation-based scaling
model for climate sensitivity estimates and global projections to 2100,
Clim. Dynam., 56, 1105–1129, https://doi.org/10.1007/s00382-020-05521-x, 2020. a
Huang, J. and Bowman, K. P.: The small ice cap instability in seasonal energy
balance models, Clim. Dynam., 7, 205–215, https://doi.org/10.1007/BF00206862,
1992. a, b
Huybers, P. and Curry, W.: Links between annual, Milankovitch and continuum
temperature variability, Nature, 441, 329–332, https://doi.org/10.1038/nature04745,
2006. a
Kim, K.-Y. and North, G. R.: Surface temperature fluctuations in a stochastic
climate model, J. Geophys. Res., 96, 18573,
https://doi.org/10.1029/91JD01959, 1991. a
Kyle, H. L., Weiss, M., and Ardanuy, P.: Cloud, Surface Temperature, and
Outgoing Longwave Radiation for the Period from 1979 to 1990, J.
Climate, 8, 2644–2658,
https://doi.org/10.1175/1520-0442(1995)008<2644:CSTAOL>2.0.CO;2, 1995. a, b
Laepple, T. and Huybers, P.: Ocean surface temperature variability: Large
model–data differences at decadal and longer periods, P.
Natl. Acad. Sci. USA, 111, 16682–16687,
https://doi.org/10.1073/pnas.1412077111, 2014. a
Laskar, J., Robutel, P., Joutel, F., Gastineau, M., Correia, A. C. M., and
Levrard, B.: A long-term numerical solution for the insolation quantities
of the Earth, Astron. Astrophys., 428, 261–285,
https://doi.org/10.1051/0004-6361:20041335, 2004. a, b, c
Liu, Z., Otto-Bliesner, B. L., He, F., Brady, E. C., Tomas, R., Clark, P. U.,
Carlson, A. E., Lynch-Stieglitz, J., Curry, W., Brook, E., Erickson, D.,
Jacob, R., Kutzbach, J., and Cheng, J.: Transient simulation of last
deglaciation with a new mechanism for bolling-allerød warming, Science,
325, 310–314, https://doi.org/10.1126/science.1171041, 2009. a
Liu, Z., Zhu, J., Rosenthal, Y., Zhang, X., Otto-Bliesner, B. L., Timmermann,
A., Smith, R. S., Lohmann, G., Zheng, W., and Elison Timm, O.: The
Holocene temperature conundrum, P. Natl. Acad.
Sci. USA, 111, E3501–E3505, https://doi.org/10.1073/pnas.1407229111, 2014. a
Max Planck Institute für Meteorologie: Climate Data Operators,
available at: https://code.mpimet.mpg.de/projects/cdo, last access: 30 April 2021. a
Meyer, P., Hoell, M., and Kantz, H.: Reproducing Long-Range Correlations in
Global Mean Temperatures in Simple Energy Balance Models, J.
Geophys. Res.-Atmos., 123, 4413–4422,
https://doi.org/10.1002/2017JD028078, 2018. a
Myhre, G., Highwood, E. J., Shine, K. P., and Stordal, F.: New estimates of
radiative forcing due to well mixed greenhouse gases, Geophys. Res.
Lett., 25, 2715–2718, https://doi.org/10.1029/98GL01908, 1998. a
National Geophysical Data Center: 5-minute Gridded Global Relief Data
(ETOPO5), National Geophysical Data Center, NOAA, https://doi.org/10.7289/V5D798BF, 1993. a, b, c
Neukom, R., Barboza, L. A., Erb, M. P., Shi, F., Emile-Geay, J., Evans, M. N.,
Franke, J., Kaufman, D. S., Lücke, L., Rehfeld, K., Schurer, A., Zhu,
F., Brönnimann, S., Hakim, G. J., Henley, B. J., Ljungqvist, F. C.,
McKay, N., Valler, V., and von Gunten, L.: Consistent multidecadal
variability in global temperature reconstructions and simulations over the
Common Era, Nat. Geosci., 12, 643–649,
https://doi.org/10.1038/s41561-019-0400-0, 2019. a, b, c, d
North, G. R.: The small ice cap instability in diffusive climate models,
J. Atmos. Sci., 41, 3390–3395,
https://doi.org/10.1175/1520-0469(1984)041<3390:TSICII>2.0.CO;2, 1984. a, b
North, G. R. and Coakley, J. A.: Differences between seasonal and mean annual
energy balance model calculations of climate and climate sensitivity,
J. Atmos. Sci., 36, 1189–1204,
https://doi.org/10.1175/1520-0469(1979)036<1189:DBSAMA>2.0.CO;2, 1979. a
North, G. R., Cahalan, R. F., and Coakley, J. A.: Energy-Balance Climate
Models, Rev. Geophys. Space Phys., 16, 2000–2001, 1980. a
Otto-Bliesner, B. L., Brady, E. C., Fasullo, J., Jahn, A., Landrum, L.,
Stevenson, S., Rosenbloom, N., Mai, A., and Strand, G.: Climate variability
and change since 850 CE. An ensemble approach with the community earth system
model, B. Am. Meteorol. Soc., 97, 787–801,
https://doi.org/10.1175/BAMS-D-14-00233.1, 2016. a, b
Otto-Bliesner, B. L., Braconnot, P., Harrison, S. P., Lunt, D. J., Abe-Ouchi, A., Albani, S., Bartlein, P. J., Capron, E., Carlson, A. E., Dutton, A., Fischer, H., Goelzer, H., Govin, A., Haywood, A., Joos, F., LeGrande, A. N., Lipscomb, W. H., Lohmann, G., Mahowald, N., Nehrbass-Ahles, C., Pausata, F. S. R., Peterschmitt, J.-Y., Phipps, S. J., Renssen, H., and Zhang, Q.: The PMIP4 contribution to CMIP6 – Part 2: Two interglacials, scientific objective and experimental design for Holocene and Last Interglacial simulations, Geosci. Model Dev., 10, 3979–4003, https://doi.org/10.5194/gmd-10-3979-2017, 2017. a
Pope, V. D., Gallani, M. L., Rowntree, P. R., and Stratton, R. A.: The impact
of new physical parametrizations in the Hadley Centre climate model: HadAM3,
Clim. Dynam., 16, 123–146, https://doi.org/10.1007/s003820050009, 2000. a, b, c
Rahmstorf, S., Crucifix, M., Ganopolski, A., Goosse, H., Kamenkovich, I.,
Knutti, R., Lohmann, G., Marsh, R., Mysak, L. a., Wang, Z., and Weaver,
A. J.: Thermohaline circulation hysteresis: A model intercomparison,
Geophys. Res. Lett., 32, 1–5, https://doi.org/10.1029/2005GL023655, 2005. a
Rehfeld, K., Hébert, R., Lora, J. M., Lofverstrom, M., and Brierley, C. M.: Variability of surface climate in simulations of past and future, Earth Syst. Dynam., 11, 447–468, https://doi.org/10.5194/esd-11-447-2020, 2020. a
Rohling, E. J., Sluijs, A., Dijkstra, H. A., Köhler, P., Van De Wal,
R. S., Von Der Heydt, A. S., Beerling, D. J., Berger, A., Bijl, P. K.,
Crucifix, M., Deconto, R., Drijfhout, S. S., Fedorov, A., Foster, G. L.,
Ganopolski, A., Hansen, J., Hönisch, B., Hooghiemstra, H., Huber, M.,
Huybers, P., Knutti, R., Lea, D. W., Lourens, L. J., Lunt, D.,
Masson-Demotte, V., Medina-Elizalde, M., Otto-Bliesner, B., Pagani, M.,
Pälike, H., Renssen, H., Royer, D. L., Siddall, M., Valdes, P., Zachos,
J. C., and Zeebe, R. E.: Making sense of palaeoclimate sensitivity, Nature,
491, 683–691, https://doi.org/10.1038/nature11574, 2012. a
Ruddiman, W. F.: Earth's Climate. Past and Future, W. H. Freeman and Company,
3rd Edn., 2014. a
Rypdal, K., Rypdal, M., and Fredriksen, H. B.: Spatiotemporal long-range
persistence in earth's temperature field: Analysis of stochastic-diffusive
energy balance models, J. Climate, 28, 8379–8395,
https://doi.org/10.1175/JCLI-D-15-0183.1, 2015. a, b
Schmidt, G. A., Annan, J. D., Bartlein, P. J., Cook, B. I., Guilyardi, E., Hargreaves, J. C., Harrison, S. P., Kageyama, M., LeGrande, A. N., Konecky, B., Lovejoy, S., Mann, M. E., Masson-Delmotte, V., Risi, C., Thompson, D., Timmermann, A., Tremblay, L.-B., and Yiou, P.: Using palaeo-climate comparisons to constrain future projections in CMIP5, Clim. Past, 10, 221–250, https://doi.org/10.5194/cp-10-221-2014, 2014. a, b, c
Sellers, W. D.: A Global Climatic Model Based on the Energy Balance of the
Earth-Atmosphere System, J. Appl. Meteorol., 8, 392–400,
https://doi.org/10.1175/1520-0450(1969)008<0392:AGCMBO>2.0.CO;2, 1969. a, b, c, d
Short, D. A., Mengel, J. G., Crowley, T. J., Hyde, W. T., and North, G. R.:
Filtering of milankovitch cycles by earth's geography, Quaternary Res.,
35, 157–173, https://doi.org/10.1016/0033-5894(91)90064-C, 1991. a, b, c
Singarayer, J. S. and Valdes, P. J.: High-latitude climate sensitivity to
ice-sheet forcing over the last 120 kyr, Quaternary Sci. Rev., 29,
43–55, https://doi.org/10.1016/j.quascirev.2009.10.011, 2010. a
Smith, R. S. and Gregory, J.: The last glacial cycle: Transient simulations
with an AOGCM, Clim. Dynam., 38, 1545–1559,
https://doi.org/10.1007/s00382-011-1283-y, 2012. a, b
Stap, L. B., van de Wal, R. S. W., de Boer, B., Bintanja, R., and Lourens, L. J.: The influence of ice sheets on temperature during the past 38 million years inferred from a one-dimensional ice sheet–climate model, Clim. Past, 13, 1243–1257, https://doi.org/10.5194/cp-13-1243-2017, 2017. a, b, c
Stap, L. B., van de Wal, R. S., de Boer, B., Köhler, P., Hoencamp, J. H.,
Lohmann, G., Tuenter, E., and Lourens, L. J.: Modeled Influence of Land Ice
and CO2 on Polar Amplification and Paleoclimate Sensitivity During the
Past 5 Million Years, Paleoceanogr. Paleoclim., 33, 381–394,
https://doi.org/10.1002/2017PA003313, 2018. a
Wagner, T. J. W. and Eisenman, I.: How Climate Model Complexity Influences Sea
Ice Stability, J.Climate, 28, 3998–4014,
https://doi.org/10.1175/jcli-d-14-00654.1, 2015. a
Zhuang, K., North, G. R., and Giardino, J. R.: Hysteresis of glaciations in
the Permo-Carboniferous, J. Geophys. Res.-(Atmo., 119,
6196–6206, https://doi.org/10.1002/2013JD020524, 2014. a
Ziegler, E. and Rehfeld, K.: Data and model from TransEBM v. 1.0: Description,
tuning, and validation of a transient model of the Earth's energy balance in
two dimensions, Zenodo, https://doi.org/10.5281/zenodo.3941311, 2020. a
Short summary
Past climate changes are the only record of how the climate responds to changes in conditions on Earth, but simulations with complex climate models are challenging. We extended a simple climate model such that it simulates the development of temperatures over time. In the model, changes in carbon dioxide and ice distribution affect the simulated temperatures the most. The model is very efficient and can therefore be used to examine past climate changes happening over long periods of time.
Past climate changes are the only record of how the climate responds to changes in conditions on...
