Articles | Volume 15, issue 3
https://doi.org/10.5194/gmd-15-1247-2022
© Author(s) 2022. 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-15-1247-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
10 Feb 2022
Model description paper |
| 10 Feb 2022
| 10 Feb 2022
ShellChron 0.4.0: a new tool for constructing chronologies in accretionary carbonate archives from stable oxygen isotope profiles
Department of Earth Sciences, Utrecht University, Utrecht, the
Netherlands
AMGC research group, Vrije Universiteit Brussel, Brussels, Belgium
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Rute Coimbra, Niels de Winter, Maria Ríos, Rui Bernardino, Darío Estraviz-López, Priscila Lohmann, Roberta Martino, Aurora Grandal-d'Anglade, Fernando Rocha, and Philippe Claeys
EGUsphere, https://doi.org/10.5194/egusphere-2025-1770, https://doi.org/10.5194/egusphere-2025-1770, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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To understand human impact on climate and biodiversity, we studied fossil teeth of Gomphotherium from Miocene Portugal. Chemical patterns, like those in modern elephants, show seasonal diet changes and geophagy during dry periods. This suggests dry seasons shaped animal behavior and ecosystems, offering insights into how land life responded to past warming—and how it might react to future climate change.
Niels J. de Winter, Najat al Fudhaili, Iris Arndt, Philippe Claeys, René Fraaije, Steven Goderis, John Jagt, Matthias López Correa, Axel Munnecke, Jarosław Stolarski, and Martin Ziegler
EGUsphere, https://doi.org/10.5194/egusphere-2025-2308, https://doi.org/10.5194/egusphere-2025-2308, 2025
This preprint is open for discussion and under review for Climate of the Past (CP).
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To test the tolerance of past shallow marine ecosystems to extreme climates, we collected and compiled stable and clumped isotope data from rudist bivalves that lived in tropical shallow marine waters in present-day Oman during the Campanian (75 million years ago). Our dataset shows that these animals were able to withstand exceptionally warm temperatures, exceeding 40 °C, during hot summers. Our finding highlights how seasonal climate extremes impact marine biodiversity.
Johan Vellekoop, Daan Vanhove, Inge Jelu, Philippe Claeys, Linda C. Ivany, Niels J. de Winter, Robert P. Speijer, and Etienne Steurbaut
EGUsphere, https://doi.org/10.5194/egusphere-2024-298, https://doi.org/10.5194/egusphere-2024-298, 2024
Preprint archived
Short summary
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Stable oxygen and carbon isotope analyses of fossil bivalves, gastropods and fish ear bones (otoliths) is frequently used for seasonality reconstructions of past climates. We measured stable isotope compositions in multiple specimens of two bivalve species, a gastropod species, and two species of otoliths, from two early Eocene (49.2 million year old) shell layers. Our study demonstrates considerable variability between different taxa, which has implications for seasonality reconstructions.
Niels J. de Winter, Daniel Killam, Lukas Fröhlich, Lennart de Nooijer, Wim Boer, Bernd R. Schöne, Julien Thébault, and Gert-Jan Reichart
Biogeosciences, 20, 3027–3052, https://doi.org/10.5194/bg-20-3027-2023, https://doi.org/10.5194/bg-20-3027-2023, 2023
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Mollusk shells are valuable recorders of climate and environmental changes of the past down to a daily resolution. To explore this potential, we measured changes in the composition of shells of two types of bivalves recorded at the hourly scale: the king scallop Pecten maximus and giant clams (Tridacna) that engaged in photosymbiosis. We find that photosymbiosis produces more day–night fluctuation in shell chemistry but that most of the variation is not periodic, perhaps recording weather.
Nina M. A. Wichern, Niels J. de Winter, Andrew L. A. Johnson, Stijn Goolaerts, Frank Wesselingh, Maartje F. Hamers, Pim Kaskes, Philippe Claeys, and Martin Ziegler
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Fossil bivalves are an excellent climate archive due to their rapidly forming growth increments and long lifespan. Here, we show that the extinct bivalve species Angulus benedeni benedeni can be used to reconstruct past temperatures using oxygen and clumped isotopes. This species has the potential to provide seasonally resolved temperature data for the Pliocene to Oligocene sediments of the North Sea basin. In turn, these past climates can improve our understanding of future climate change.
Niels J. de Winter, Tobias Agterhuis, and Martin Ziegler
Clim. Past, 17, 1315–1340, https://doi.org/10.5194/cp-17-1315-2021, https://doi.org/10.5194/cp-17-1315-2021, 2021
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Climate researchers often need to compromise in their sampling between increasing the number of measurements to obtain higher time resolution and combining measurements to improve the reliability of climate reconstructions. In this study, we test several methods for achieving the optimal balance between these competing interests by simulating seasonality reconstructions using stable and clumped isotopes. Our results inform sampling strategies for climate reconstructions in general.
Niels J. de Winter, Clemens V. Ullmann, Anne M. Sørensen, Nicolas Thibault, Steven Goderis, Stijn J. M. Van Malderen, Christophe Snoeck, Stijn Goolaerts, Frank Vanhaecke, and Philippe Claeys
Biogeosciences, 17, 2897–2922, https://doi.org/10.5194/bg-17-2897-2020, https://doi.org/10.5194/bg-17-2897-2020, 2020
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In this study, we present a detailed investigation of the chemical composition of 12 specimens of very well preserved, 78-million-year-old oyster shells from southern Sweden. The chemical data show how the oysters grew, the environment in which they lived and how old they became and also provide valuable information about which chemical measurements we can use to learn more about ancient climate and environment from such shells. In turn, this can help improve climate reconstructions and models.
Stef Vansteenberge, Niels J. de Winter, Matthias Sinnesael, Sophie Verheyden, Steven Goderis, Stijn J. M. Van Malderen, Frank Vanhaecke, and Philippe Claeys
Clim. Past, 16, 141–160, https://doi.org/10.5194/cp-16-141-2020, https://doi.org/10.5194/cp-16-141-2020, 2020
Short summary
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We measured the chemical composition (trace-element concentrations and stable-isotope ratios) of a Belgian speleothem that deposited annual layers. Our sub-annual resolution dataset allows us to investigate how the chemistry of this speleothem recorded changes in the environment and climate in northwestern Europe. We then use this information to reconstruct climate change during the 16th and 17th century on the seasonal scale and demonstrate that environmental change drives speleothem chemistry.
Niels J. de Winter, Johan Vellekoop, Robin Vorsselmans, Asefeh Golreihan, Jeroen Soete, Sierra V. Petersen, Kyle W. Meyer, Silvio Casadio, Robert P. Speijer, and Philippe Claeys
Clim. Past, 14, 725–749, https://doi.org/10.5194/cp-14-725-2018, https://doi.org/10.5194/cp-14-725-2018, 2018
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In this work, we apply a range of methods to measure the geochemical composition of the calcite from fossil shells of Pycnodonte vesicularis (so-called honeycomb oysters). The goal is to investigate how the composition of these shells reflect the environment in which the animals grew. Ultimately, we propose a methodology to check whether the shells of pycnodonte oysters are well-preserved and to reconstruct meaningful information about the seasonal changes in the past climate and environment.
Niels J. de Winter
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-137, https://doi.org/10.5194/gmd-2017-137, 2017
Revised manuscript not accepted
Short summary
Short summary
Bivalves grow by expanding their shells incrementally and record environmental conditions in the chemistry of their carbonate. To reconstruct these conditions, it is important to constrain the growth and trace element uptake rates in these bivalve shells. The present study models the development and chemical composition of the shells of bivalves based on XRF mapping of shell cross sections and allows changes in trace element uptake rates to be interpreted to reconstruct palaeoenvironment.
N. J. de Winter, C. Zeeden, and F. J. Hilgen
Clim. Past, 10, 1001–1015, https://doi.org/10.5194/cp-10-1001-2014, https://doi.org/10.5194/cp-10-1001-2014, 2014
Rute Coimbra, Niels de Winter, Maria Ríos, Rui Bernardino, Darío Estraviz-López, Priscila Lohmann, Roberta Martino, Aurora Grandal-d'Anglade, Fernando Rocha, and Philippe Claeys
EGUsphere, https://doi.org/10.5194/egusphere-2025-1770, https://doi.org/10.5194/egusphere-2025-1770, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
To understand human impact on climate and biodiversity, we studied fossil teeth of Gomphotherium from Miocene Portugal. Chemical patterns, like those in modern elephants, show seasonal diet changes and geophagy during dry periods. This suggests dry seasons shaped animal behavior and ecosystems, offering insights into how land life responded to past warming—and how it might react to future climate change.
Niels J. de Winter, Najat al Fudhaili, Iris Arndt, Philippe Claeys, René Fraaije, Steven Goderis, John Jagt, Matthias López Correa, Axel Munnecke, Jarosław Stolarski, and Martin Ziegler
EGUsphere, https://doi.org/10.5194/egusphere-2025-2308, https://doi.org/10.5194/egusphere-2025-2308, 2025
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
Short summary
To test the tolerance of past shallow marine ecosystems to extreme climates, we collected and compiled stable and clumped isotope data from rudist bivalves that lived in tropical shallow marine waters in present-day Oman during the Campanian (75 million years ago). Our dataset shows that these animals were able to withstand exceptionally warm temperatures, exceeding 40 °C, during hot summers. Our finding highlights how seasonal climate extremes impact marine biodiversity.
Johan Vellekoop, Daan Vanhove, Inge Jelu, Philippe Claeys, Linda C. Ivany, Niels J. de Winter, Robert P. Speijer, and Etienne Steurbaut
EGUsphere, https://doi.org/10.5194/egusphere-2024-298, https://doi.org/10.5194/egusphere-2024-298, 2024
Preprint archived
Short summary
Short summary
Stable oxygen and carbon isotope analyses of fossil bivalves, gastropods and fish ear bones (otoliths) is frequently used for seasonality reconstructions of past climates. We measured stable isotope compositions in multiple specimens of two bivalve species, a gastropod species, and two species of otoliths, from two early Eocene (49.2 million year old) shell layers. Our study demonstrates considerable variability between different taxa, which has implications for seasonality reconstructions.
Niels J. de Winter, Daniel Killam, Lukas Fröhlich, Lennart de Nooijer, Wim Boer, Bernd R. Schöne, Julien Thébault, and Gert-Jan Reichart
Biogeosciences, 20, 3027–3052, https://doi.org/10.5194/bg-20-3027-2023, https://doi.org/10.5194/bg-20-3027-2023, 2023
Short summary
Short summary
Mollusk shells are valuable recorders of climate and environmental changes of the past down to a daily resolution. To explore this potential, we measured changes in the composition of shells of two types of bivalves recorded at the hourly scale: the king scallop Pecten maximus and giant clams (Tridacna) that engaged in photosymbiosis. We find that photosymbiosis produces more day–night fluctuation in shell chemistry but that most of the variation is not periodic, perhaps recording weather.
Nina M. A. Wichern, Niels J. de Winter, Andrew L. A. Johnson, Stijn Goolaerts, Frank Wesselingh, Maartje F. Hamers, Pim Kaskes, Philippe Claeys, and Martin Ziegler
Biogeosciences, 20, 2317–2345, https://doi.org/10.5194/bg-20-2317-2023, https://doi.org/10.5194/bg-20-2317-2023, 2023
Short summary
Short summary
Fossil bivalves are an excellent climate archive due to their rapidly forming growth increments and long lifespan. Here, we show that the extinct bivalve species Angulus benedeni benedeni can be used to reconstruct past temperatures using oxygen and clumped isotopes. This species has the potential to provide seasonally resolved temperature data for the Pliocene to Oligocene sediments of the North Sea basin. In turn, these past climates can improve our understanding of future climate change.
Niels J. de Winter, Tobias Agterhuis, and Martin Ziegler
Clim. Past, 17, 1315–1340, https://doi.org/10.5194/cp-17-1315-2021, https://doi.org/10.5194/cp-17-1315-2021, 2021
Short summary
Short summary
Climate researchers often need to compromise in their sampling between increasing the number of measurements to obtain higher time resolution and combining measurements to improve the reliability of climate reconstructions. In this study, we test several methods for achieving the optimal balance between these competing interests by simulating seasonality reconstructions using stable and clumped isotopes. Our results inform sampling strategies for climate reconstructions in general.
Niels J. de Winter, Clemens V. Ullmann, Anne M. Sørensen, Nicolas Thibault, Steven Goderis, Stijn J. M. Van Malderen, Christophe Snoeck, Stijn Goolaerts, Frank Vanhaecke, and Philippe Claeys
Biogeosciences, 17, 2897–2922, https://doi.org/10.5194/bg-17-2897-2020, https://doi.org/10.5194/bg-17-2897-2020, 2020
Short summary
Short summary
In this study, we present a detailed investigation of the chemical composition of 12 specimens of very well preserved, 78-million-year-old oyster shells from southern Sweden. The chemical data show how the oysters grew, the environment in which they lived and how old they became and also provide valuable information about which chemical measurements we can use to learn more about ancient climate and environment from such shells. In turn, this can help improve climate reconstructions and models.
Stef Vansteenberge, Niels J. de Winter, Matthias Sinnesael, Sophie Verheyden, Steven Goderis, Stijn J. M. Van Malderen, Frank Vanhaecke, and Philippe Claeys
Clim. Past, 16, 141–160, https://doi.org/10.5194/cp-16-141-2020, https://doi.org/10.5194/cp-16-141-2020, 2020
Short summary
Short summary
We measured the chemical composition (trace-element concentrations and stable-isotope ratios) of a Belgian speleothem that deposited annual layers. Our sub-annual resolution dataset allows us to investigate how the chemistry of this speleothem recorded changes in the environment and climate in northwestern Europe. We then use this information to reconstruct climate change during the 16th and 17th century on the seasonal scale and demonstrate that environmental change drives speleothem chemistry.
Niels J. de Winter, Johan Vellekoop, Robin Vorsselmans, Asefeh Golreihan, Jeroen Soete, Sierra V. Petersen, Kyle W. Meyer, Silvio Casadio, Robert P. Speijer, and Philippe Claeys
Clim. Past, 14, 725–749, https://doi.org/10.5194/cp-14-725-2018, https://doi.org/10.5194/cp-14-725-2018, 2018
Short summary
Short summary
In this work, we apply a range of methods to measure the geochemical composition of the calcite from fossil shells of Pycnodonte vesicularis (so-called honeycomb oysters). The goal is to investigate how the composition of these shells reflect the environment in which the animals grew. Ultimately, we propose a methodology to check whether the shells of pycnodonte oysters are well-preserved and to reconstruct meaningful information about the seasonal changes in the past climate and environment.
Niels J. de Winter
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-137, https://doi.org/10.5194/gmd-2017-137, 2017
Revised manuscript not accepted
Short summary
Short summary
Bivalves grow by expanding their shells incrementally and record environmental conditions in the chemistry of their carbonate. To reconstruct these conditions, it is important to constrain the growth and trace element uptake rates in these bivalve shells. The present study models the development and chemical composition of the shells of bivalves based on XRF mapping of shell cross sections and allows changes in trace element uptake rates to be interpreted to reconstruct palaeoenvironment.
N. J. de Winter, C. Zeeden, and F. J. Hilgen
Clim. Past, 10, 1001–1015, https://doi.org/10.5194/cp-10-1001-2014, https://doi.org/10.5194/cp-10-1001-2014, 2014
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025, https://doi.org/10.5194/gmd-18-2193-2025, 2025
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam 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. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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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 bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe 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 subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. 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
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century 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.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange 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.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information 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., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system 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.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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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.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. 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).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2025-169, https://doi.org/10.5194/egusphere-2025-169, 2025
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Satellites have observed earth's emission of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about the earth and atmosphere. We present a tool that runs alongside global climate models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. 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 L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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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.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen 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 the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Sian Megan Chilcott and Malte Meinshausen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-203, https://doi.org/10.5194/gmd-2024-203, 2025
Revised manuscript accepted for GMD
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Climate models are expensive to run and often underestimate how sensitive Arctic sea ice is to climate change. To address this, we developed a simple model that emulates the response of sea ice to global warming. We find the remaining carbon dioxide (CO2) emissions that will avoid a seasonally ice-free Arctic Ocean is lower than previous estimates of 821 Gigatonnes of CO2. Our model also provides insights into the future of winter sea ice, examining a larger ensemble than previously possible.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Elizabeth J. Drenkard, Charles A. Stock, Andrew C. Ross, Yi-Cheng Teng, Theresa Morrison, Wei Cheng, Alistair Adcroft, Enrique Curchitser, Raphael Dussin, Robert Hallberg, Claudine Hauri, Katherine Hedstrom, Albert Hermann, Michael G. Jacox, Kelly A. Kearney, Remi Pages, Darren J. Pilcher, Mercedes Pozo Buil, Vivek Seelanki, and Niki Zadeh
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-195, https://doi.org/10.5194/gmd-2024-195, 2024
Revised manuscript accepted for GMD
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We made a new regional ocean model to assist fisheries and ecosystem managers make decisions in the Northeast Pacific Ocean (NEP). We found that the model did well simulating past ocean conditions like temperature, and nutrient and oxygen levels, and can even reproduce metrics used by and important to ecosystem managers.
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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.
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Short summary
ShellChron is a tool for determining the relative age of samples in carbonate (climate) archives based on the seasonal variability in temperature and salinity or precipitation recorded in stable oxygen isotope measurements. The model allows dating of fossil archives within a year, which is important for climate reconstructions on the sub-seasonal to decadal scale. In this paper, I introduce ShellChron and test it on a range of real and virtual datasets to demonstrate its use.
ShellChron is a tool for determining the relative age of samples in carbonate (climate) archives...
