Articles | Volume 7, issue 5
https://doi.org/10.5194/gmd-7-2077-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-2077-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A suite of early Eocene (~ 55 Ma) climate model boundary conditions
N. Herold
Earth Systems Research Center, Institute for Earth, Ocean and Space Sciences, University of New Hampshire, Durham, NH, USA
Department of Earth, Atmosphere, Planetary and Space Sciences, Purdue University, West Lafayette, IN, USA
EarthByte Group, School of Geosciences, University of Sydney, Sydney NSW, Australia
A. Goldner
Department of Earth, Atmosphere, Planetary and Space Sciences, Purdue University, West Lafayette, IN, USA
J. A. M. Green
School of Ocean Sciences, Bangor University, Menai Bridge, UK
R. D. Müller
EarthByte Group, School of Geosciences, University of Sydney, Sydney NSW, Australia
P. Markwick
Getech, Leeds, LS8 2LJ, UK
Earth Systems Research Center, Institute for Earth, Ocean and Space Sciences, University of New Hampshire, Durham, NH, USA
Department of Earth Sciences, University of New Hampshire, Durham, NH, USA
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Dominique K. L. L. Jenny, Tammo Reichgelt, Charlotte L. O'Brien, Xiaoqing Liu, Peter K. Bijl, Matthew Huber, and Appy Sluijs
EGUsphere, https://doi.org/10.5194/egusphere-2023-2738, https://doi.org/10.5194/egusphere-2023-2738, 2023
This preprint is open for discussion and under review for Climate of the Past (CP).
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This study reviews the current state of knowledge regarding the Oligocene “icehouse” climate. We extend an existing marine climate proxy data compilation and present a new compilation and analysis of terrestrial plant assemblages to assess long-term climate trends and variability. Our data-climate model comparison reinforces the notion that models underestimate polar amplification of Oligocene climates and identify potential future research directions.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Preprint under review for BG
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For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Chris D. Fokkema, Tobias Agterhuis, Danielle Gerritsma, Myrthe de Goeij, Xiaoqing Liu, Pauline de Regt, Addison Rice, Laurens Vennema, Claudia Agnini, Peter K. Bijl, Joost Frieling, Matthew Huber, Francien Peterse, and Appy Sluijs
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-70, https://doi.org/10.5194/cp-2023-70, 2023
Preprint under review for CP
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Polar amplification (PA) is a key uncertainty in climate projections. The factors that dominantly control PA are difficult to separate. Here we provide an estimate for the non-ice-related PA by reconstructing tropical ocean temperature variability from the ice-free early Eocene, which we compare to deep-ocean-derived high latitude temperature variability across short-lived warming periods. We find a PA factor of 1.7–2.3 on 20-kyr timescales, which matches previous multi-million-year estimates.
Emmanuele Russo, Jonathan Buzan, Sebastian Lienert, Guillaume Jouvet, Patricio Velasquez Alvarez, Basil Davis, Patrick Ludwig, Fortunat Joos, and Christoph Raible
EGUsphere, https://doi.org/10.5194/egusphere-2023-1197, https://doi.org/10.5194/egusphere-2023-1197, 2023
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We present a series of experiments conducted for the Last Glacial Maximum (~21000 years ago) over Europe using the regional climate Weather Research and Forecasting model (WRF) at convection-permitting resolutions. The model, with new developments better suitable for paleo studies, agrees well with pollen-based climate reconstructions. This agreement is improved when considering different sources of uncertainty. The added value of convection-permitting resolutions is also demonstrated.
Jonathan Robert Buzan, Emmanuele Russo, Woon Mi Kim, and Christoph C. Raible
EGUsphere, https://doi.org/10.5194/egusphere-2023-324, https://doi.org/10.5194/egusphere-2023-324, 2023
Preprint archived
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Paleoclimate is used to test climate models to verify that simulations accurately project both future and past climate states. We present fully coupled climate sensitivity simulations of Preindustrial, Last Glacial Maximum, and the Quaternary climate periods. We show distinct climate states derived from non-linear responses to ice sheet heights and orbits. The implication is that as paleo proxy data become more reliable, they may constrain the specific climate states produced by climate models.
R. Dietmar Müller, Nicolas Flament, John Cannon, Michael G. Tetley, Simon E. Williams, Xianzhi Cao, Ömer F. Bodur, Sabin Zahirovic, and Andrew Merdith
Solid Earth, 13, 1127–1159, https://doi.org/10.5194/se-13-1127-2022, https://doi.org/10.5194/se-13-1127-2022, 2022
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We have built a community model for the evolution of the Earth's plate–mantle system. Created with open-source software and an open-access plate model, it covers the last billion years, including the formation, breakup, and dispersal of two supercontinents, as well as the creation and destruction of numerous ocean basins. The model allows us to
seeinto the Earth in 4D and helps us unravel the connections between surface tectonics and the
beating heartof the Earth, its convecting mantle.
Julia Rulent, Lucy M. Bricheno, J. A. Mattias Green, Ivan D. Haigh, and Huw Lewis
Nat. Hazards Earth Syst. Sci., 21, 3339–3351, https://doi.org/10.5194/nhess-21-3339-2021, https://doi.org/10.5194/nhess-21-3339-2021, 2021
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High coastal total water levels (TWLs) can lead to flooding and hazardous conditions for coastal communities and environment. In this research we are using numerical models to study the interactions between the three main components of the TWL (waves, tides, and surges) on UK and Irish coasts during winter 2013/14. The main finding of this research is that extreme waves and surges can indeed happen together, even at high tide, but they often occurred simultaneously 2–3 h before high tide.
Philip L. Woodworth, J. A. Mattias Green, Richard D. Ray, and John M. Huthnance
Ocean Sci., 17, 809–818, https://doi.org/10.5194/os-17-809-2021, https://doi.org/10.5194/os-17-809-2021, 2021
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This special issue marks the 100th anniversary of the founding of the Liverpool Tidal Institute (LTI). The preface gives a history of the LTI founding and of its first two directors. It also gives an overview of LTI research on tides. Summaries are given of the 26 papers in the special issue. Their topics could be thought of as providing a continuation of the research first undertaken at the LTI. They provide an interesting snapshot of work on tides now being made by groups around the world.
Eline Le Breton, Sascha Brune, Kamil Ustaszewski, Sabin Zahirovic, Maria Seton, and R. Dietmar Müller
Solid Earth, 12, 885–913, https://doi.org/10.5194/se-12-885-2021, https://doi.org/10.5194/se-12-885-2021, 2021
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The former Piemont–Liguria Ocean, which separated Europe from Africa–Adria in the Jurassic, opened as an arm of the central Atlantic. Using plate reconstructions and geodynamic modeling, we show that the ocean reached only 250 km width between Europe and Adria. Moreover, at least 65 % of the lithosphere subducted into the mantle and/or incorporated into the Alps during convergence in Cretaceous and Cenozoic times comprised highly thinned continental crust, while only 35 % was truly oceanic.
David K. Hutchinson, Helen K. Coxall, Daniel J. Lunt, Margret Steinthorsdottir, Agatha M. de Boer, Michiel Baatsen, Anna von der Heydt, Matthew Huber, Alan T. Kennedy-Asser, Lutz Kunzmann, Jean-Baptiste Ladant, Caroline H. Lear, Karolin Moraweck, Paul N. Pearson, Emanuela Piga, Matthew J. Pound, Ulrich Salzmann, Howie D. Scher, Willem P. Sijp, Kasia K. Śliwińska, Paul A. Wilson, and Zhongshi Zhang
Clim. Past, 17, 269–315, https://doi.org/10.5194/cp-17-269-2021, https://doi.org/10.5194/cp-17-269-2021, 2021
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The Eocene–Oligocene transition was a major climate cooling event from a largely ice-free world to the first major glaciation of Antarctica, approximately 34 million years ago. This paper reviews observed changes in temperature, CO2 and ice sheets from marine and land-based records at this time. We present a new model–data comparison of this transition and find that CO2-forced cooling provides the best explanation of the observed global temperature changes.
Daniel J. Lunt, Fran Bragg, Wing-Le Chan, David K. Hutchinson, Jean-Baptiste Ladant, Polina Morozova, Igor Niezgodzki, Sebastian Steinig, Zhongshi Zhang, Jiang Zhu, Ayako Abe-Ouchi, Eleni Anagnostou, Agatha M. de Boer, Helen K. Coxall, Yannick Donnadieu, Gavin Foster, Gordon N. Inglis, Gregor Knorr, Petra M. Langebroek, Caroline H. Lear, Gerrit Lohmann, Christopher J. Poulsen, Pierre Sepulchre, Jessica E. Tierney, Paul J. Valdes, Evgeny M. Volodin, Tom Dunkley Jones, Christopher J. Hollis, Matthew Huber, and Bette L. Otto-Bliesner
Clim. Past, 17, 203–227, https://doi.org/10.5194/cp-17-203-2021, https://doi.org/10.5194/cp-17-203-2021, 2021
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This paper presents the first modelling results from the Deep-Time Model Intercomparison Project (DeepMIP), in which we focus on the early Eocene climatic optimum (EECO, 50 million years ago). We show that, in contrast to previous work, at least three models (CESM, GFDL, and NorESM) produce climate states that are consistent with proxy indicators of global mean temperature and polar amplification, and they achieve this at a CO2 concentration that is consistent with the CO2 proxy record.
Michiel Baatsen, Anna S. von der Heydt, Matthew Huber, Michael A. Kliphuis, Peter K. Bijl, Appy Sluijs, and Henk A. Dijkstra
Clim. Past, 16, 2573–2597, https://doi.org/10.5194/cp-16-2573-2020, https://doi.org/10.5194/cp-16-2573-2020, 2020
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Warm climates of the deep past have proven to be challenging to reconstruct with the same numerical models used for future predictions. We present results of CESM simulations for the middle to late Eocene (∼ 38 Ma), in which we managed to match the available indications of temperature well. With these results we can now look into regional features and the response to external changes to ultimately better understand the climate when it is in such a warm state.
J. A. Mattias Green and David T. Pugh
Ocean Sci., 16, 1337–1345, https://doi.org/10.5194/os-16-1337-2020, https://doi.org/10.5194/os-16-1337-2020, 2020
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Bardsey Island lies 3 km offshore the western end of the Llŷn Peninsula in northwestern Wales. However, the island is too small to show up in tidal databases based on satellite data, and thus they may not provide the correct local tides. Our new sea level data shows that the tidal currents in the satellite databases are one-third of the observed currents. Any investigation of other coastal activities, e.g. renewable energy installations, must use local observations to get the correct tides.
Gordon N. Inglis, Fran Bragg, Natalie J. Burls, Margot J. Cramwinckel, David Evans, Gavin L. Foster, Matthew Huber, Daniel J. Lunt, Nicholas Siler, Sebastian Steinig, Jessica E. Tierney, Richard Wilkinson, Eleni Anagnostou, Agatha M. de Boer, Tom Dunkley Jones, Kirsty M. Edgar, Christopher J. Hollis, David K. Hutchinson, and Richard D. Pancost
Clim. Past, 16, 1953–1968, https://doi.org/10.5194/cp-16-1953-2020, https://doi.org/10.5194/cp-16-1953-2020, 2020
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This paper presents estimates of global mean surface temperatures and climate sensitivity during the early Paleogene (∼57–48 Ma). We employ a multi-method experimental approach and show that i) global mean surface temperatures range between 27 and 32°C and that ii) estimates of
bulkequilibrium climate sensitivity (∼3 to 4.5°C) fall within the range predicted by the IPCC AR5 Report. This work improves our understanding of two key climate metrics during the early Paleogene.
Rohitash Chandra, Danial Azam, Arpit Kapoor, and R. Dietmar Müller
Geosci. Model Dev., 13, 2959–2979, https://doi.org/10.5194/gmd-13-2959-2020, https://doi.org/10.5194/gmd-13-2959-2020, 2020
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Forward landscape and sedimentary basin evolution models pose a major challenge in the development of efficient inference and optimization methods. Bayesian inference provides a methodology for estimation and uncertainty quantification of free model parameters. In this paper, we present an application of a surrogate-assisted Bayesian parallel tempering method where that surrogate mimics a landscape evolution model. We use the method for parameter estimation and uncertainty quantification.
Marie Laugié, Yannick Donnadieu, Jean-Baptiste Ladant, J. A. Mattias Green, Laurent Bopp, and François Raisson
Clim. Past, 16, 953–971, https://doi.org/10.5194/cp-16-953-2020, https://doi.org/10.5194/cp-16-953-2020, 2020
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To quantify the impact of major climate forcings on the Cretaceous climate, we use Earth system modelling to progressively reconstruct the Cretaceous state by changing boundary conditions one by one. Between the preindustrial and the Cretaceous simulations, the model simulates a global warming of more than 11°C. The study confirms the primary control exerted by atmospheric CO2 on atmospheric temperatures. Palaeogeographic changes represent the second major contributor to the warming.
Hannah S. Davies, J. A. Mattias Green, and Joao C. Duarte
Earth Syst. Dynam., 11, 291–299, https://doi.org/10.5194/esd-11-291-2020, https://doi.org/10.5194/esd-11-291-2020, 2020
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We have confirmed that there is a supertidal cycle associated with the supercontinent cycle. As continents drift due to plate tectonics, oceans also change size, controlling the strength of the tides and causing periods of supertides. In this work, we used a coupled tectonic–tidal model of Earth's future to test four different scenarios that undergo different styles of ocean closure and periods of supertides. This has implications for the Earth system and for other planets with liquid oceans.
Christopher J. Hollis, Tom Dunkley Jones, Eleni Anagnostou, Peter K. Bijl, Margot J. Cramwinckel, Ying Cui, Gerald R. Dickens, Kirsty M. Edgar, Yvette Eley, David Evans, Gavin L. Foster, Joost Frieling, Gordon N. Inglis, Elizabeth M. Kennedy, Reinhard Kozdon, Vittoria Lauretano, Caroline H. Lear, Kate Littler, Lucas Lourens, A. Nele Meckler, B. David A. Naafs, Heiko Pälike, Richard D. Pancost, Paul N. Pearson, Ursula Röhl, Dana L. Royer, Ulrich Salzmann, Brian A. Schubert, Hannu Seebeck, Appy Sluijs, Robert P. Speijer, Peter Stassen, Jessica Tierney, Aradhna Tripati, Bridget Wade, Thomas Westerhold, Caitlyn Witkowski, James C. Zachos, Yi Ge Zhang, Matthew Huber, and Daniel J. Lunt
Geosci. Model Dev., 12, 3149–3206, https://doi.org/10.5194/gmd-12-3149-2019, https://doi.org/10.5194/gmd-12-3149-2019, 2019
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The Deep-Time Model Intercomparison Project (DeepMIP) is a model–data intercomparison of the early Eocene (around 55 million years ago), the last time that Earth's atmospheric CO2 concentrations exceeded 1000 ppm. Previously, we outlined the experimental design for climate model simulations. Here, we outline the methods used for compilation and analysis of climate proxy data. The resulting climate
atlaswill provide insights into the mechanisms that control past warm climate states.
Alexander Harker, J. A. Mattias Green, Michael Schindelegger, and Sophie-Berenice Wilmes
Ocean Sci., 15, 147–159, https://doi.org/10.5194/os-15-147-2019, https://doi.org/10.5194/os-15-147-2019, 2019
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We used a computer model to help predict how changing sea levels around Australia will affect the ebb and flow of the tide. We found that sea-level rise and coastal flooding affect where energy from the tide is dissipated and how the tide flows around the coastline. We found that we must consider how sea-level rise will affect tides across the rest of the world, as that will have an impact on Australia too. This sort of investigation can help direct coastal management and protection efforts.
Hugo K. H. Olierook, Richard Scalzo, David Kohn, Rohitash Chandra, Ehsan Farahbakhsh, Gregory Houseman, Chris Clark, Steven M. Reddy, and R. Dietmar Müller
Solid Earth Discuss., https://doi.org/10.5194/se-2019-4, https://doi.org/10.5194/se-2019-4, 2019
Revised manuscript not accepted
Sascha Brune, Simon E. Williams, and R. Dietmar Müller
Solid Earth, 9, 1187–1206, https://doi.org/10.5194/se-9-1187-2018, https://doi.org/10.5194/se-9-1187-2018, 2018
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Fragmentation of continents often involves obliquely rifting segments that feature a complex three-dimensional structural evolution. Here we show that more than ~ 70 % of Earth’s rifted margins exceeded an obliquity of 20° demonstrating that oblique rifting should be considered the rule, not the exception. This highlights the importance of three-dimensional approaches in modelling, surveying, and interpretation of those rift segments where oblique rifting is the dominant mode of deformation.
Robert McKay, Neville Exon, Dietmar Müller, Karsten Gohl, Michael Gurnis, Amelia Shevenell, Stuart Henrys, Fumio Inagaki, Dhananjai Pandey, Jessica Whiteside, Tina van de Flierdt, Tim Naish, Verena Heuer, Yuki Morono, Millard Coffin, Marguerite Godard, Laura Wallace, Shuichi Kodaira, Peter Bijl, Julien Collot, Gerald Dickens, Brandon Dugan, Ann G. Dunlea, Ron Hackney, Minoru Ikehara, Martin Jutzeler, Lisa McNeill, Sushant Naik, Taryn Noble, Bradley Opdyke, Ingo Pecher, Lowell Stott, Gabriele Uenzelmann-Neben, Yatheesh Vadakkeykath, and Ulrich G. Wortmann
Sci. Dril., 24, 61–70, https://doi.org/10.5194/sd-24-61-2018, https://doi.org/10.5194/sd-24-61-2018, 2018
J. A. Mattias Green, David G. Bowers, and Hannah A. M. Byrne
Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-72, https://doi.org/10.5194/os-2018-72, 2018
Preprint withdrawn
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In a double tide the ocean reaches high or low tide, starts to fall or rise, only to go back to a new high or low. Here, we describe three ways this can happen by dividing locations with observed double tides into three classes. This showed that double tides are more common than we thought, and more complicated than most textbooks claim because they only describe one class of double tides. This matters to shipping, coastal flood management, and other disciplines interested in sea-level change.
Jodie Pall, Sabin Zahirovic, Sebastiano Doss, Rakib Hassan, Kara J. Matthews, John Cannon, Michael Gurnis, Louis Moresi, Adrian Lenardic, and R. Dietmar Müller
Clim. Past, 14, 857–870, https://doi.org/10.5194/cp-14-857-2018, https://doi.org/10.5194/cp-14-857-2018, 2018
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Subduction zones intersecting buried carbonate platforms liberate significant atmospheric CO2 and have the potential to influence global climate. We model the spatio-temporal distribution of carbonate platform accumulation within a plate tectonic framework and use wavelet analysis to analyse linked behaviour between atmospheric CO2 and carbonate-intersecting subduction zone (CISZ) lengths since the Devonian. We find that increasing CISZ lengths likely contributed to a warmer Palaeogene climate.
Michiel Baatsen, Anna S. von der Heydt, Matthew Huber, Michael A. Kliphuis, Peter K. Bijl, Appy Sluijs, and Henk A. Dijkstra
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-43, https://doi.org/10.5194/cp-2018-43, 2018
Revised manuscript not accepted
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The Eocene marks a period where the climate was in a hothouse state, without any continental-scale ice sheets. Such climates have proven difficult to reproduce in models, especially their low temperature difference between equator and poles. Here, we present high resolution CESM simulations using a new geographic reconstruction of the middle-to-late Eocene. The results provide new insights into a period for which knowledge is limited, leading up to a transition into the present icehouse state.
Wenchao Cao, Sabin Zahirovic, Nicolas Flament, Simon Williams, Jan Golonka, and R. Dietmar Müller
Biogeosciences, 14, 5425–5439, https://doi.org/10.5194/bg-14-5425-2017, https://doi.org/10.5194/bg-14-5425-2017, 2017
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We present a workflow to link paleogeographic maps to alternative plate tectonic models, alleviating the problem that published global paleogeographic maps are generally presented as static maps and tied to a particular plate model. We further develop an approach to improve paleogeography using paleobiology. The resulting paleogeographies are consistent with proxies of eustatic sea level change since ~400 Myr ago. We make the digital global paleogeographic maps available as an open resource.
Gary Shaffer, Esteban Fernández Villanueva, Roberto Rondanelli, Jens Olaf Pepke Pedersen, Steffen Malskær Olsen, and Matthew Huber
Geosci. Model Dev., 10, 4081–4103, https://doi.org/10.5194/gmd-10-4081-2017, https://doi.org/10.5194/gmd-10-4081-2017, 2017
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We include methane cycling in the simplified but well-tested Danish Center for Earth System Science model. We now can deal with very large methane inputs to the Earth system that can lead to more methane in the atmosphere, extreme warming and ocean dead zones. We can now study ancient global warming events, probably forced by methane inputs. Some such events were accompanied by mass extinctions. We wish to understand such events, both for learning about the past and for looking into the future.
Michael Rubey, Sascha Brune, Christian Heine, D. Rhodri Davies, Simon E. Williams, and R. Dietmar Müller
Solid Earth, 8, 899–919, https://doi.org/10.5194/se-8-899-2017, https://doi.org/10.5194/se-8-899-2017, 2017
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Earth's surface is constantly warped up and down by the convecting mantle. Here we derive geodynamic rules for this so-called
dynamic topographyby employing high-resolution numerical models of global mantle convection. We define four types of dynamic topography history that are primarily controlled by the ever-changing pattern of Earth's subduction zones. Our models provide a predictive quantitative framework linking mantle convection with plate tectonics and sedimentary basin evolution.
Hannah A. M. Byrne, J. A. Mattias Green, and David G. Bowers
Ocean Sci., 13, 599–607, https://doi.org/10.5194/os-13-599-2017, https://doi.org/10.5194/os-13-599-2017, 2017
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Some places experience double high tides, where the tide starts to ebb for a short while, only to briefly flood again before finally receding. The result is a very long high tide with weak currents, and is important for navigational purposes. The existing theory for when and where double high tides occur does not always capture them, and it can only be applied to double highs occurring on a twice-daily tide. Here, the criterion has been generalized to capture all double high or low tides.
Daniel J. Lunt, Matthew Huber, Eleni Anagnostou, Michiel L. J. Baatsen, Rodrigo Caballero, Rob DeConto, Henk A. Dijkstra, Yannick Donnadieu, David Evans, Ran Feng, Gavin L. Foster, Ed Gasson, Anna S. von der Heydt, Chris J. Hollis, Gordon N. Inglis, Stephen M. Jones, Jeff Kiehl, Sandy Kirtland Turner, Robert L. Korty, Reinhardt Kozdon, Srinath Krishnan, Jean-Baptiste Ladant, Petra Langebroek, Caroline H. Lear, Allegra N. LeGrande, Kate Littler, Paul Markwick, Bette Otto-Bliesner, Paul Pearson, Christopher J. Poulsen, Ulrich Salzmann, Christine Shields, Kathryn Snell, Michael Stärz, James Super, Clay Tabor, Jessica E. Tierney, Gregory J. L. Tourte, Aradhna Tripati, Garland R. Upchurch, Bridget S. Wade, Scott L. Wing, Arne M. E. Winguth, Nicky M. Wright, James C. Zachos, and Richard E. Zeebe
Geosci. Model Dev., 10, 889–901, https://doi.org/10.5194/gmd-10-889-2017, https://doi.org/10.5194/gmd-10-889-2017, 2017
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In this paper we describe the experimental design for a set of simulations which will be carried out by a range of climate models, all investigating the climate of the Eocene, about 50 million years ago. The intercomparison of model results is called 'DeepMIP', and we anticipate that we will contribute to the next IPCC report through an analysis of these simulations and the geological data to which we will compare them.
Nicholas Barnett-Moore, Rakib Hassan, Nicolas Flament, and Dietmar Müller
Solid Earth, 8, 235–254, https://doi.org/10.5194/se-8-235-2017, https://doi.org/10.5194/se-8-235-2017, 2017
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We use 3D mantle flow models to investigate the evolution of the Iceland plume in the North Atlantic. Results show that over the last ~ 100 Myr a remarkably stable pattern of flow in the lowermost mantle beneath the region resulted in the formation of a plume nucleation site. At the surface, a model plume compared to published observables indicates that its large plume head, ~ 2500 km in diameter, arriving beneath eastern Greenland in the Palaeocene, can account for the volcanic record and uplift.
Daniel J. Lunt, Alex Farnsworth, Claire Loptson, Gavin L. Foster, Paul Markwick, Charlotte L. O'Brien, Richard D. Pancost, Stuart A. Robinson, and Neil Wrobel
Clim. Past, 12, 1181–1198, https://doi.org/10.5194/cp-12-1181-2016, https://doi.org/10.5194/cp-12-1181-2016, 2016
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We explore the influence of changing geography from the period ~ 150 million years ago to ~ 35 million years ago, using a set of 19 climate model simulations. We find that without any CO2 change, the global mean temperature is remarkably constant, but that regionally there are significant changes in temperature which we link back to changes in ocean circulation. Finally, we explore the implications of our findings for the interpretation of geological indicators of past temperatures.
Matthew J. Carmichael, Daniel J. Lunt, Matthew Huber, Malte Heinemann, Jeffrey Kiehl, Allegra LeGrande, Claire A. Loptson, Chris D. Roberts, Navjit Sagoo, Christine Shields, Paul J. Valdes, Arne Winguth, Cornelia Winguth, and Richard D. Pancost
Clim. Past, 12, 455–481, https://doi.org/10.5194/cp-12-455-2016, https://doi.org/10.5194/cp-12-455-2016, 2016
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In this paper, we assess how well model-simulated precipitation rates compare to those indicated by geological data for the early Eocene, a warm interval 56–49 million years ago. Our results show that a number of models struggle to produce sufficient precipitation at high latitudes, which likely relates to cool simulated temperatures in these regions. However, calculating precipitation rates from plant fossils is highly uncertain, and further data are now required.
S. H. R. Rosier, G. H. Gudmundsson, and J. A. M. Green
The Cryosphere, 9, 1649–1661, https://doi.org/10.5194/tc-9-1649-2015, https://doi.org/10.5194/tc-9-1649-2015, 2015
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We use a full-Stokes model to investigate the long period modulation of Rutford Ice Stream flow by the ocean tide. We find that using a nonlinear sliding law cannot fully explain the measurements and an additional mechanism, whereby tidally induced subglacial pressure variations are transmitted upstream from the grounding line, is also required to match the large amplitude and decay length scale of the observations.
J. R. Buzan, K. Oleson, and M. Huber
Geosci. Model Dev., 8, 151–170, https://doi.org/10.5194/gmd-8-151-2015, https://doi.org/10.5194/gmd-8-151-2015, 2015
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We implemented the HumanIndexMod, which calculates 13 diagnostic heat stress metrics, into the Community Land Model (CLM4.5). The goal of this module is to have a common predictive framework for measuring heat stress globally. These metrics are in operational use by weather forecasters, industry, and agriculture. We show metric-dependent results of regional partitioning of extreme moisture and temperature levels in a 1901-2010 simulation.
S. H. R. Rosier, G. H. Gudmundsson, and J. A. M. Green
The Cryosphere, 8, 1763–1775, https://doi.org/10.5194/tc-8-1763-2014, https://doi.org/10.5194/tc-8-1763-2014, 2014
J. Cannon, E. Lau, and R. D. Müller
Solid Earth, 5, 741–755, https://doi.org/10.5194/se-5-741-2014, https://doi.org/10.5194/se-5-741-2014, 2014
S. J. Gallagher, N. Exon, M. Seton, M. Ikehara, C. J. Hollis, R. Arculus, S. D'Hondt, C. Foster, M. Gurnis, J. P. Kennett, R. McKay, A. Malakoff, J. Mori, K. Takai, and L. Wallace
Sci. Dril., 17, 45–50, https://doi.org/10.5194/sd-17-45-2014, https://doi.org/10.5194/sd-17-45-2014, 2014
S. Zahirovic, M. Seton, and R. D. Müller
Solid Earth, 5, 227–273, https://doi.org/10.5194/se-5-227-2014, https://doi.org/10.5194/se-5-227-2014, 2014
A. Goldner, N. Herold, and M. Huber
Clim. Past, 10, 523–536, https://doi.org/10.5194/cp-10-523-2014, https://doi.org/10.5194/cp-10-523-2014, 2014
E. Gasson, D. J. Lunt, R. DeConto, A. Goldner, M. Heinemann, M. Huber, A. N. LeGrande, D. Pollard, N. Sagoo, M. Siddall, A. Winguth, and P. J. Valdes
Clim. Past, 10, 451–466, https://doi.org/10.5194/cp-10-451-2014, https://doi.org/10.5194/cp-10-451-2014, 2014
M. Hosseinpour, R. D. Müller, S. E. Williams, and J. M. Whittaker
Solid Earth, 4, 461–479, https://doi.org/10.5194/se-4-461-2013, https://doi.org/10.5194/se-4-461-2013, 2013
C. Heine, J. Zoethout, and R. D. Müller
Solid Earth, 4, 215–253, https://doi.org/10.5194/se-4-215-2013, https://doi.org/10.5194/se-4-215-2013, 2013
N. Wright, S. Zahirovic, R. D. Müller, and M. Seton
Biogeosciences, 10, 1529–1541, https://doi.org/10.5194/bg-10-1529-2013, https://doi.org/10.5194/bg-10-1529-2013, 2013
A. Goldner, M. Huber, and R. Caballero
Clim. Past, 9, 173–189, https://doi.org/10.5194/cp-9-173-2013, https://doi.org/10.5194/cp-9-173-2013, 2013
R. L. Sriver, M. Huber, and L. Chafik
Earth Syst. Dynam., 4, 1–10, https://doi.org/10.5194/esd-4-1-2013, https://doi.org/10.5194/esd-4-1-2013, 2013
R. D. Müller and T. C. W. Landgrebe
Solid Earth, 3, 447–465, https://doi.org/10.5194/se-3-447-2012, https://doi.org/10.5194/se-3-447-2012, 2012
Related subject area
Climate and Earth system modeling
An emulation-based approach for interrogating reactive transport models
A sub-grid parameterization scheme for topographic vertical motion in CAM5-SE
Technology to aid the analysis of large-volume multi-institute climate model output at a central analysis facility (PRIMAVERA Data Management Tool V2.10)
A diffusion-based kernel density estimator (diffKDE, version 1) with optimal bandwidth approximation for the analysis of data in geoscience and ecological research
Monte Carlo drift correction – quantifying the drift uncertainty of global climate models
Improvements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1
Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations
CIOFC1.0: a common parallel input/output framework based on C-Coupler2.0
Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method
Introducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlands
URock 2023a: an open-source GIS-based wind model for complex urban settings
DASH: a MATLAB toolbox for paleoclimate data assimilation
Comparing the Performance of Julia on CPUs versus GPUs and Julia-MPI versus Fortran-MPI: a case study with MPAS-Ocean (Version 7.1)
All aboard! Earth system investigations with the CH2O-CHOO TRAIN v1.0
The Canadian Atmospheric Model version 5 (CanAM5.0.3)
The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis
Assimilation of the AMSU-A radiances using the CESM (v2.1.0) and the DART (v9.11.13)–RTTOV (v12.3)
Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicability
Simulated stable water isotopes during the mid-Holocene and pre-industrial periods using AWI-ESM-2.1-wiso
Truly Conserving with Conservative Remapping Methods
Rainbows and climate change: a tutorial on climate model diagnostics and parameterization
ModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009)
MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean region
Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications
IceTFT v1.0.0: interpretable long-term prediction of Arctic sea ice extent with deep learning
Earth system modeling on Modular Supercomputing Architectures: coupled atmosphere-ocean simulations with ICON 2.6.6-rc
The KNMI Large Ensemble Time Slice (KNMI–LENTIS)
ENSO statistics, teleconnections, and atmosphere–ocean coupling in the Taiwan Earth System Model version 1
Using probabilistic machine learning to better model temporal patterns in parameterizations: a case study with the Lorenz 96 model
The Regional Aerosol Model Intercomparison Project (RAMIP)
DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise
TIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover change
Recalibration of a three-dimensional water quality model with a newly developed autocalibration toolkit (EFDC-ACT v1.0.0): how much improvement will be achieved with a wider hydrological variability?
Description and evaluation of the JULES-ES set-up for ISIMIP2b
Simplified Kalman smoother and ensemble Kalman smoother for improving reanalyses
Understanding Changes in Cloud Simulations from E3SM Version 1 to Version 2
Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM
Modeling river water temperature with limiting forcing data: Air2stream v1.0.0, machine learning and multiple regression
WRF (v4.0)-SUEWS (v2018c) Coupled System: Development, Evaluation and Application
A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)
Resolving the mesoscale at reduced computational cost with FESOM 2.5: efficient modeling approaches applied to the Southern Ocean
Modeling and evaluating the effects of irrigation on land-atmosphere interaction in South-West Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization
The fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river results
The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies
A new simplified parameterization of secondary organic aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)
Deep learning for stochastic precipitation generation – deep SPG v1.0
Developing spring wheat in the Noah-MP land surface model (v4.4) for growing season dynamics and responses to temperature stress
Deep Learning Model based on Multi-scale Feature Fusion for Precipitation Nowcasting
Robust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0
High resolution downscaling of CMIP6 Earth System and Global Climate Models using deep learning for Iberia
Angus Fotherby, Harold J. Bradbury, Jennifer L. Druhan, and Alexandra V. Turchyn
Geosci. Model Dev., 16, 7059–7074, https://doi.org/10.5194/gmd-16-7059-2023, https://doi.org/10.5194/gmd-16-7059-2023, 2023
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We demonstrate how, given a simulation of fluid and rock interacting, we can emulate the system using machine learning. This means that, for a given initial condition, we can predict the final state, avoiding the simulation step once the model has been trained. We present a workflow for applying this approach to any fluid–rock simulation and showcase two applications to different fluid–rock simulations. This approach has applications for improving model development and sensitivity analyses.
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
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In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Jon Seddon, Ag Stephens, Matthew S. Mizielinski, Pier Luigi Vidale, and Malcolm J. Roberts
Geosci. Model Dev., 16, 6689–6700, https://doi.org/10.5194/gmd-16-6689-2023, https://doi.org/10.5194/gmd-16-6689-2023, 2023
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The PRIMAVERA project aimed to develop a new generation of advanced global climate models. The large volume of data generated was uploaded to a central analysis facility (CAF) and was analysed by 100 PRIMAVERA scientists there. We describe how the PRIMAVERA project used the CAF's facilities to enable users to analyse this large dataset. We believe that similar, multi-institute, big-data projects could also use a CAF to efficiently share, organise and analyse large volumes of data.
Maria-Theresia Pelz, Markus Schartau, Christopher J. Somes, Vanessa Lampe, and Thomas Slawig
Geosci. Model Dev., 16, 6609–6634, https://doi.org/10.5194/gmd-16-6609-2023, https://doi.org/10.5194/gmd-16-6609-2023, 2023
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Kernel density estimators (KDE) approximate the probability density of a data set without the assumption of an underlying distribution. We used the solution of the diffusion equation, and a new approximation of the optimal smoothing parameter build on two pilot estimation steps, to construct such a KDE best suited for typical characteristics of geoscientific data. The resulting KDE is insensitive to noise and well resolves multimodal data structures as well as boundary-close data.
Benjamin S. Grandey, Zhi Yang Koh, Dhrubajyoti Samanta, Benjamin P. Horton, Justin Dauwels, and Lock Yue Chew
Geosci. Model Dev., 16, 6593–6608, https://doi.org/10.5194/gmd-16-6593-2023, https://doi.org/10.5194/gmd-16-6593-2023, 2023
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Global climate models are susceptible to spurious trends known as drift. Fortunately, drift can be corrected when analysing data produced by models. To explore the uncertainty associated with drift correction, we develop a new method: Monte Carlo drift correction. For historical simulations of thermosteric sea level rise, drift uncertainty is relatively large. When analysing data susceptible to drift, researchers should consider drift uncertainty.
Michael Sigmond, James Anstey, Vivek Arora, Ruth Digby, Nathan Gillett, Viatcheslav Kharin, William Merryfield, Catherine Reader, John Scinocca, Neil Swart, John Virgin, Carsten Abraham, Jason Cole, Nicolas Lambert, Woo-Sung Lee, Yongxiao Liang, Elizaveta Malinina, Landon Rieger, Knut von Salzen, Christian Seiler, Clint Seinen, Andrew Shao, Reinel Sospedra-Alfonso, Libo Wang, and Duo Yang
Geosci. Model Dev., 16, 6553–6591, https://doi.org/10.5194/gmd-16-6553-2023, https://doi.org/10.5194/gmd-16-6553-2023, 2023
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We present a new activity which aims to organize the analysis of biases in the Canadian Earth System model (CanESM) in a systematic manner. Results of this “Analysis for Development” (A4D) activity includes a new CanESM version, CanESM5.1, which features substantial improvements regarding the simulation of dust and stratospheric temperatures, a second CanESM5.1 variant with reduced climate sensitivity, and insights into potential avenues to reduce various other model biases.
Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, and Po-Lun Ma
Geosci. Model Dev., 16, 6355–6376, https://doi.org/10.5194/gmd-16-6355-2023, https://doi.org/10.5194/gmd-16-6355-2023, 2023
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To assess the ability of Earth system model (ESM) predictions, we developed a tool called ESMAC Diags to understand how aerosols, clouds, and aerosol–cloud interactions are represented in ESMs. This paper describes its version 2 functionality. We compared the model predictions with measurements taken by planes, ships, satellites, and ground instruments over four regions across the world. Results show that this new tool can help identify model problems and guide future development of ESMs.
Xinzhu Yu, Li Liu, Chao Sun, Qingu Jiang, Biao Zhao, Zhiyuan Zhang, Hao Yu, and Bin Wang
Geosci. Model Dev., 16, 6285–6308, https://doi.org/10.5194/gmd-16-6285-2023, https://doi.org/10.5194/gmd-16-6285-2023, 2023
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In this paper we propose a new common, flexible, and efficient parallel I/O framework for earth system modeling based on C-Coupler2.0. CIOFC1.0 can handle data I/O in parallel and provides a configuration file format that enables users to conveniently change the I/O configurations. It can automatically make grid and time interpolation, output data with an aperiodic time series, and accelerate data I/O when the field size is large.
Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima
Geosci. Model Dev., 16, 6211–6245, https://doi.org/10.5194/gmd-16-6211-2023, https://doi.org/10.5194/gmd-16-6211-2023, 2023
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A particle-based cloud model was developed for meter- to submeter-scale resolution in cloud simulations. Our new cloud model's computational performance is superior to a bin method and comparable to a two-moment bulk method. A highlight of this study is the 2 m resolution shallow cloud simulations over an area covering ∼10 km2. This model allows for studying turbulence and cloud physics at spatial scales that overlap with those covered by direct numerical simulations and field studies.
Anthony Schrapffer, Jan Polcher, Anna Sörensson, and Lluís Fita
Geosci. Model Dev., 16, 5755–5782, https://doi.org/10.5194/gmd-16-5755-2023, https://doi.org/10.5194/gmd-16-5755-2023, 2023
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The present paper introduces a floodplain scheme for a high-resolution land surface model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land–atmosphere fluxes and highlights the potential impact of floodplains on land–atmosphere interactions and the importance of integrating this module in coupled simulations.
Jérémy Bernard, Fredrik Lindberg, and Sandro Oswald
Geosci. Model Dev., 16, 5703–5727, https://doi.org/10.5194/gmd-16-5703-2023, https://doi.org/10.5194/gmd-16-5703-2023, 2023
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The UMEP plug-in integrated in the free QGIS software can now calculate the spatial variation of the wind speed within urban settings. This paper shows that the new wind model, URock, generally fits observations well and highlights the main needed improvements. According to this work, pedestrian wind fields and outdoor thermal comfort can now simply be estimated by any QGIS user (researchers, students, and practitioners).
Jonathan King, Jessica Tierney, Matthew Osman, Emily J. Judd, and Kevin J. Anchukaitis
Geosci. Model Dev., 16, 5653–5683, https://doi.org/10.5194/gmd-16-5653-2023, https://doi.org/10.5194/gmd-16-5653-2023, 2023
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Paleoclimate data assimilation is a useful method that allows researchers to combine climate models with natural archives of past climates. However, it can be difficult to implement in practice. To facilitate this method, we present DASH, a MATLAB toolbox. The toolbox provides routines that implement common steps of paleoclimate data assimilation, and it can be used to implement assimilations for a wide variety of time periods, spatial regions, data networks, and analytical algorithms.
Siddhartha Bishnu, Robert R. Strauss, and Mark R. Petersen
Geosci. Model Dev., 16, 5539–5559, https://doi.org/10.5194/gmd-16-5539-2023, https://doi.org/10.5194/gmd-16-5539-2023, 2023
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Here we test Julia, a relatively new programming language, which is designed to be simple to write, but also fast on advanced computer architectures. We found that Julia is both convenient and fast, but there is no free lunch. Our first attempt to develop an ocean model in Julia was relatively easy, but the code was slow. After several months of further development, we created a Julia code that is as fast on supercomputers as a Fortran ocean model.
Tyler Kukla, Daniel E. Ibarra, Kimberly V. Lau, and Jeremy K. C. Rugenstein
Geosci. Model Dev., 16, 5515–5538, https://doi.org/10.5194/gmd-16-5515-2023, https://doi.org/10.5194/gmd-16-5515-2023, 2023
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The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact across millions of years on a standard PC. While efficient, the model accounts for many factors including the location of land masses, the spatial pattern of the water cycle, and fundamental climate feedbacks. The model is a powerful tool for investigating how short-term climate processes can affect long-term changes in the Earth system.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
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The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Florian Zabel and Benjamin Poschlod
Geosci. Model Dev., 16, 5383–5399, https://doi.org/10.5194/gmd-16-5383-2023, https://doi.org/10.5194/gmd-16-5383-2023, 2023
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Today, most climate model data are provided at daily time steps. However, more and more models from different sectors, such as energy, water, agriculture, and health, require climate information at a sub-daily temporal resolution for a more robust and reliable climate impact assessment. Here we describe and validate the Teddy tool, a new model for the temporal disaggregation of daily climate model data for climate impact analysis.
Young-Chan Noh, Yonghan Choi, Hyo-Jong Song, Kevin Raeder, Joo-Hong Kim, and Youngchae Kwon
Geosci. Model Dev., 16, 5365–5382, https://doi.org/10.5194/gmd-16-5365-2023, https://doi.org/10.5194/gmd-16-5365-2023, 2023
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This is the first attempt to assimilate the observations of microwave temperature sounders into the global climate forecast model in which the satellite observations have not been assimilated in the past. To do this, preprocessing schemes are developed to make the satellite observations suitable to be assimilated. In the assimilation experiments, the model analysis is significantly improved by assimilating the observations of microwave temperature sounders.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151, https://doi.org/10.5194/gmd-16-5131-2023, https://doi.org/10.5194/gmd-16-5131-2023, 2023
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Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
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We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Karl E. Taylor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-177, https://doi.org/10.5194/gmd-2023-177, 2023
Revised manuscript accepted for GMD
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Andrew Gettelman
Geosci. Model Dev., 16, 4937–4956, https://doi.org/10.5194/gmd-16-4937-2023, https://doi.org/10.5194/gmd-16-4937-2023, 2023
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A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
Geosci. Model Dev., 16, 4853–4866, https://doi.org/10.5194/gmd-16-4853-2023, https://doi.org/10.5194/gmd-16-4853-2023, 2023
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ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
Geosci. Model Dev., 16, 4811–4833, https://doi.org/10.5194/gmd-16-4811-2023, https://doi.org/10.5194/gmd-16-4811-2023, 2023
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Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Anna L. Merrifield, Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti
Geosci. Model Dev., 16, 4715–4747, https://doi.org/10.5194/gmd-16-4715-2023, https://doi.org/10.5194/gmd-16-4715-2023, 2023
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Using all Coupled Model Intercomparison Project (CMIP) models is unfeasible for many applications. We provide a subselection protocol that balances user needs for model independence, performance, and spread capturing CMIP’s projection uncertainty simultaneously. We show how sets of three to five models selected for European applications map to user priorities. An audit of model independence and its influence on equilibrium climate sensitivity uncertainty in CMIP is also presented.
Bin Mu, Xiaodan Luo, Shijin Yuan, and Xi Liang
Geosci. Model Dev., 16, 4677–4697, https://doi.org/10.5194/gmd-16-4677-2023, https://doi.org/10.5194/gmd-16-4677-2023, 2023
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To improve the long-term forecast skill for sea ice extent (SIE), we introduce IceTFT, which directly predicts 12 months of averaged Arctic SIE. The results show that IceTFT has higher forecasting skill. We conducted a sensitivity analysis of the variables in the IceTFT model. These sensitivities can help researchers study the mechanisms of sea ice development, and they also provide useful references for the selection of variables in data assimilation or the input of deep learning models.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
EGUsphere, https://doi.org/10.5194/egusphere-2023-1476, https://doi.org/10.5194/egusphere-2023-1476, 2023
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere-ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 59 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597, https://doi.org/10.5194/gmd-16-4581-2023, https://doi.org/10.5194/gmd-16-4581-2023, 2023
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The KNMI Large Ensemble Time Slice (KNMI–LENTIS) is a large ensemble of global climate model simulations with EC-Earth3. It covers two climate scenarios by focusing on two time slices: the present day (2000–2009) and a future +2 K climate (2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub-)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.
Yi-Chi Wang, Wan-Ling Tseng, Yu-Luen Chen, Shih-Yu Lee, Huang-Hsiung Hsu, and Hsin-Chien Liang
Geosci. Model Dev., 16, 4599–4616, https://doi.org/10.5194/gmd-16-4599-2023, https://doi.org/10.5194/gmd-16-4599-2023, 2023
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This study focuses on evaluating the performance of the Taiwan Earth System Model version 1 (TaiESM1) in simulating the El Niño–Southern Oscillation (ENSO), a significant tropical climate pattern with global impacts. Our findings reveal that TaiESM1 effectively captures several characteristics of ENSO, such as its seasonal variation and remote teleconnections. Its pronounced ENSO strength bias is also thoroughly investigated, aiming to gain insights to improve climate model performance.
Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, and Damon J. Wischik
Geosci. Model Dev., 16, 4501–4519, https://doi.org/10.5194/gmd-16-4501-2023, https://doi.org/10.5194/gmd-16-4501-2023, 2023
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How can we create better climate models? We tackle this by proposing a data-driven successor to the existing approach for capturing key temporal trends in climate models. We combine probability, allowing us to represent uncertainty, with machine learning, a technique to learn relationships from data which are undiscoverable to humans. Our model is often superior to existing baselines when tested in a simple atmospheric simulation.
Laura J. Wilcox, Robert J. Allen, Bjørn H. Samset, Massimo A. Bollasina, Paul T. Griffiths, James Keeble, Marianne T. Lund, Risto Makkonen, Joonas Merikanto, Declan O'Donnell, David J. Paynter, Geeta G. Persad, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Sabine Undorf, and Daniel M. Westervelt
Geosci. Model Dev., 16, 4451–4479, https://doi.org/10.5194/gmd-16-4451-2023, https://doi.org/10.5194/gmd-16-4451-2023, 2023
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Changes in anthropogenic aerosol emissions have strongly contributed to global and regional climate change. However, the size of these regional impacts and the way they arise are still uncertain. With large changes in aerosol emissions a possibility over the next few decades, it is important to better quantify the potential role of aerosol in future regional climate change. The Regional Aerosol Model Intercomparison Project will deliver experiments designed to facilitate this.
Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang
Geosci. Model Dev., 16, 4331–4366, https://doi.org/10.5194/gmd-16-4331-2023, https://doi.org/10.5194/gmd-16-4331-2023, 2023
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This work presents a novel open-source modeling platform for evaluating future sea level rise (SLR) impacts. Using nearly 10 000 discrete coastline segments around the world, we estimate 21st-century costs for 230 SLR and socioeconomic scenarios. We find that annual end-of-century costs range from USD 100 billion under a 2 °C warming scenario with proactive adaptation to 7 trillion under a 4 °C warming scenario with minimal adaptation, illustrating the cost-effectiveness of coastal adaptation.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
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Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Chen Zhang and Tianyu Fu
Geosci. Model Dev., 16, 4315–4329, https://doi.org/10.5194/gmd-16-4315-2023, https://doi.org/10.5194/gmd-16-4315-2023, 2023
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A new automatic calibration toolkit was developed and implemented into the recalibration of a 3-D water quality model, with observations in a wider range of hydrological variability. Compared to the model calibrated with the original strategy, the recalibrated model performed significantly better in modeled total phosphorus, chlorophyll a, and dissolved oxygen. Our work indicates that hydrological variability in the calibration periods has a non-negligible impact on the water quality models.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264, https://doi.org/10.5194/gmd-16-4249-2023, https://doi.org/10.5194/gmd-16-4249-2023, 2023
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This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines
Geosci. Model Dev., 16, 4233–4247, https://doi.org/10.5194/gmd-16-4233-2023, https://doi.org/10.5194/gmd-16-4233-2023, 2023
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Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2023-1263, https://doi.org/10.5194/egusphere-2023-1263, 2023
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We performed systematic evaluation of clouds simulated in the E3SMv2 to document model performance on clouds and understand what updates in E3SMv2 have caused the changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved primarily due to the re-tuning of cloud macrophysics parameters. This study offers additional insights about clouds simulated in E3SMv2 and will benefit the future E3SM developments.
Makcim L. De Sisto, Andrew H. MacDougall, Nadine Mengis, and Sophia Antoniello
Geosci. Model Dev., 16, 4113–4136, https://doi.org/10.5194/gmd-16-4113-2023, https://doi.org/10.5194/gmd-16-4113-2023, 2023
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In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
Manuel C. Almeida and Pedro S. Coelho
Geosci. Model Dev., 16, 4083–4112, https://doi.org/10.5194/gmd-16-4083-2023, https://doi.org/10.5194/gmd-16-4083-2023, 2023
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Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different models are used to predict the WT of 83 rivers. Generally, the results show that the models' hyperparameter optimization is essential and that to minimize the prediction error it is relevant to apply all the models considered in this study. Results also show that there is a logarithmic correlation among the error of the predicted river WT and the watershed time of concentration.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-117, https://doi.org/10.5194/gmd-2023-117, 2023
Revised manuscript accepted for GMD
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040, https://doi.org/10.5194/gmd-16-4017-2023, https://doi.org/10.5194/gmd-16-4017-2023, 2023
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Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
EGUsphere, https://doi.org/10.5194/egusphere-2023-1496, https://doi.org/10.5194/egusphere-2023-1496, 2023
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Ocean models struggle to simulate small-scale ocean flows due to the computational cost of high-resolution simulations. Several cost-reducing strategies are applied to simulations of the Southern Ocean and evaluated with respect to observations and traditional, lower-resolution modelling methods. The high-resolution simulations effectively reproduce small-scale flows seen in satellite data and are largely consistent with traditional model simulations regarding their response to climate change.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
EGUsphere, https://doi.org/10.5194/egusphere-2023-890, https://doi.org/10.5194/egusphere-2023-890, 2023
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Irrigation modifies the land surface and soil conditions. The caused effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which is simulating the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
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The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev., 16, 3893–3906, https://doi.org/10.5194/gmd-16-3893-2023, https://doi.org/10.5194/gmd-16-3893-2023, 2023
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A new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM) based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Leroy J. Bird, Matthew G. W. Walker, Greg E. Bodeker, Isaac H. Campbell, Guangzhong Liu, Swapna Josmi Sam, Jared Lewis, and Suzanne M. Rosier
Geosci. Model Dev., 16, 3785–3808, https://doi.org/10.5194/gmd-16-3785-2023, https://doi.org/10.5194/gmd-16-3785-2023, 2023
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Deriving the statistics of expected future changes in extreme precipitation is challenging due to these events being rare. Regional climate models (RCMs) are computationally prohibitive for generating ensembles capable of capturing large numbers of extreme precipitation events with statistical robustness. Stochastic precipitation generators (SPGs) provide an alternative to RCMs. We describe a novel single-site SPG that learns the statistics of precipitation using a machine-learning approach.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825, https://doi.org/10.5194/gmd-16-3809-2023, https://doi.org/10.5194/gmd-16-3809-2023, 2023
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Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-109, https://doi.org/10.5194/gmd-2023-109, 2023
Revised manuscript accepted for GMD
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1. This study present a deep learning architecture MFF to improve the forecast skills of precipitations especially for heavy precipitations. 2. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. 3. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors, so that heavy precipitations are produced.
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Feijia Yin, Federica Castino, Volker Grewe, and Sabine Baumann
Geosci. Model Dev., 16, 3723–3748, https://doi.org/10.5194/gmd-16-3723-2023, https://doi.org/10.5194/gmd-16-3723-2023, 2023
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This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio Bento, and Angelina Bushenkova
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-136, https://doi.org/10.5194/gmd-2023-136, 2023
Revised manuscript accepted for GMD
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data, and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
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