Articles | Volume 17, issue 4
https://doi.org/10.5194/gmd-17-1765-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-1765-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
Marlene Klockmann
CORRESPONDING AUTHOR
Institute for Coastal Systems – Analysis and Modelling, Helmholtz-Zentrum Hereon, Geesthacht, Germany
now at: Institute of Oceanography, Universität Hamburg, Hamburg, Germany
Udo von Toussaint
Max Planck Institute for Plasma Physics, Garching, Germany
Eduardo Zorita
Institute for Coastal Systems – Analysis and Modelling, Helmholtz-Zentrum Hereon, Geesthacht, Germany
Related authors
Zeguo Zhang, Sebastian Wagner, Marlene Klockmann, and Eduardo Zorita
Clim. Past, 18, 2643–2668, https://doi.org/10.5194/cp-18-2643-2022, https://doi.org/10.5194/cp-18-2643-2022, 2022
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A bidirectional long short-term memory (LSTM) neural network was employed for the first time for past temperature field reconstructions. The LSTM method tested in our experiments using a limited calibration and validation dataset shows worse reconstruction skills compared to traditional reconstruction methods. However, a certain degree of reconstruction performance achieved by the nonlinear LSTM method shows that skill can be achieved even when using small samples with limited datasets.
Florian Andreas Ziemen, Marie-Luise Kapsch, Marlene Klockmann, and Uwe Mikolajewicz
Clim. Past, 15, 153–168, https://doi.org/10.5194/cp-15-153-2019, https://doi.org/10.5194/cp-15-153-2019, 2019
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Heinrich events are among the dominant modes of glacial climate variability. They are caused by massive ice discharges from the Laurentide Ice Sheet into the North Atlantic. In previous studies, the climate changes were either seen as resulting from freshwater released from the melt of the discharged icebergs or by ice sheet elevation changes. With a coupled ice sheet–climate model, we show that both effects are relevant with the freshwater effects preceding the ice sheet elevation effects.
Marlene Klockmann, Uwe Mikolajewicz, and Jochem Marotzke
Clim. Past, 12, 1829–1846, https://doi.org/10.5194/cp-12-1829-2016, https://doi.org/10.5194/cp-12-1829-2016, 2016
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We study the response of the glacial AMOC to different forcings in a coupled AOGCM. The depth of the upper overturning cell remains almost unchanged in response to the full glacial forcing. This is the result of two opposing effects: a deepening due to the ice sheets and a shoaling due to the low GHG concentrations. Increased brine release in the Southern Ocean is key to the shoaling. With glacial ice sheets, a shallower cell can be simulated with GHG concentrations below the glacial level.
Nele Tim, Birgit Hünicke, and Eduardo Zorita
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-147, https://doi.org/10.5194/nhess-2023-147, 2023
Manuscript not accepted for further review
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Our study analyses extreme precipitation over southern Africa in regional high-resolution atmospheric simulations of the past and future. We investigated heavy precipitation over Southern Africa, coastal South Africa, Cape Town, and the KwaZulu-Natal province in eastern South Africa. Coastal precipitation extremes are projected to intensify, double in intensity in KwaZulu-Natal, and weaken in Cape Town. Extremes are not projected to occur more often in the 21st century than in the last decades.
Nele Tim, Eduardo Zorita, Birgit Hünicke, and Ioana Ivanciu
Weather Clim. Dynam., 4, 381–397, https://doi.org/10.5194/wcd-4-381-2023, https://doi.org/10.5194/wcd-4-381-2023, 2023
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As stated by the IPCC, southern Africa is one of the two land regions that are projected to suffer from the strongest precipitation reductions in the future. Simulated drying in this region is linked to the adjacent oceans, and prevailing winds as warm and moist air masses are transported towards the continent. Precipitation trends in past and future climate can be partly attributed to the strength of the Agulhas Current system, the current along the east and south coasts of southern Africa.
Kai Bellinghausen, Birgit Hünicke, and Eduardo Zorita
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-21, https://doi.org/10.5194/nhess-2023-21, 2023
Manuscript not accepted for further review
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The prediction of extreme coastal sea level, e.g. caused by a storm surge, is operationally carried out with dynamical computer models. These models are expensive to run and still display some limitations in predicting the height of extremes. We present a successful purely data-driven machine learning model to predict extreme sea levels along the Baltic Sea coast a few days in advance. The method is also able to identify the critical predictors for the different Baltic Sea regions.
Zeguo Zhang, Sebastian Wagner, Marlene Klockmann, and Eduardo Zorita
Clim. Past, 18, 2643–2668, https://doi.org/10.5194/cp-18-2643-2022, https://doi.org/10.5194/cp-18-2643-2022, 2022
Short summary
Short summary
A bidirectional long short-term memory (LSTM) neural network was employed for the first time for past temperature field reconstructions. The LSTM method tested in our experiments using a limited calibration and validation dataset shows worse reconstruction skills compared to traditional reconstruction methods. However, a certain degree of reconstruction performance achieved by the nonlinear LSTM method shows that skill can be achieved even when using small samples with limited datasets.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
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Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Marcus Reckermann, Anders Omstedt, Tarmo Soomere, Juris Aigars, Naveed Akhtar, Magdalena Bełdowska, Jacek Bełdowski, Tom Cronin, Michał Czub, Margit Eero, Kari Petri Hyytiäinen, Jukka-Pekka Jalkanen, Anders Kiessling, Erik Kjellström, Karol Kuliński, Xiaoli Guo Larsén, Michelle McCrackin, H. E. Markus Meier, Sonja Oberbeckmann, Kevin Parnell, Cristian Pons-Seres de Brauwer, Anneli Poska, Jarkko Saarinen, Beata Szymczycha, Emma Undeman, Anders Wörman, and Eduardo Zorita
Earth Syst. Dynam., 13, 1–80, https://doi.org/10.5194/esd-13-1-2022, https://doi.org/10.5194/esd-13-1-2022, 2022
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As part of the Baltic Earth Assessment Reports (BEAR), we present an inventory and discussion of different human-induced factors and processes affecting the environment of the Baltic Sea region and their interrelations. Some are naturally occurring and modified by human activities, others are completely human-induced, and they are all interrelated to different degrees. The findings from this study can largely be transferred to other comparable marginal and coastal seas in the world.
Ralf Weisse, Inga Dailidienė, Birgit Hünicke, Kimmo Kahma, Kristine Madsen, Anders Omstedt, Kevin Parnell, Tilo Schöne, Tarmo Soomere, Wenyan Zhang, and Eduardo Zorita
Earth Syst. Dynam., 12, 871–898, https://doi.org/10.5194/esd-12-871-2021, https://doi.org/10.5194/esd-12-871-2021, 2021
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The study is part of the thematic Baltic Earth Assessment Reports – a series of review papers summarizing the knowledge around major Baltic Earth science topics. It concentrates on sea level dynamics and coastal erosion (its variability and change). Many of the driving processes are relevant in the Baltic Sea. Contributions vary over short distances and across timescales. Progress and research gaps are described in both understanding details in the region and in extending general concepts.
Oliver Bothe and Eduardo Zorita
Clim. Past, 17, 721–751, https://doi.org/10.5194/cp-17-721-2021, https://doi.org/10.5194/cp-17-721-2021, 2021
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The similarity between indirect observations of past climates and information from climate simulations can increase our understanding of past climates. The further we look back, the more uncertain our indirect observations become. Here, we discuss the technical background for such a similarity-based approach to reconstruct past climates for up to the last 15 000 years. We highlight the potential and the problems.
Oliver Bothe and Eduardo Zorita
Clim. Past, 16, 341–369, https://doi.org/10.5194/cp-16-341-2020, https://doi.org/10.5194/cp-16-341-2020, 2020
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One can use the similarity between sparse indirect observations of past climates and full fields of simulated climates to learn more about past climates. Here, we detail how one can compute uncertainty estimates for such reconstructions of past climates. This highlights the ambiguity of the reconstruction. We further show that such a reconstruction for European summer temperature agrees well with a more common approach.
Nele Tim, Eduardo Zorita, Kay-Christian Emeis, Franziska U. Schwarzkopf, Arne Biastoch, and Birgit Hünicke
Earth Syst. Dynam., 10, 847–858, https://doi.org/10.5194/esd-10-847-2019, https://doi.org/10.5194/esd-10-847-2019, 2019
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Our study reveals that the latitudinal position and intensity of Southern Hemisphere trades and westerlies are correlated. In the last decades the westerlies have shifted poleward and intensified. Furthermore, the latitudinal shifts and intensity of the trades and westerlies impact the sea surface temperatures around southern Africa and in the South Benguela upwelling region. The future development of wind stress depends on the strength of greenhouse gas forcing.
Maria Pyrina, Eduardo Moreno-Chamarro, Sebastian Wagner, and Eduardo Zorita
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2019-50, https://doi.org/10.5194/esd-2019-50, 2019
Revised manuscript not accepted
Oliver Bothe, Sebastian Wagner, and Eduardo Zorita
Earth Syst. Sci. Data, 11, 1129–1152, https://doi.org/10.5194/essd-11-1129-2019, https://doi.org/10.5194/essd-11-1129-2019, 2019
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Reconstructions try to extract a climate signal from paleo-observations. It is essential to understand their uncertainties. Similarly, comparing climate simulations and paleo-observations requires approaches to address their uncertainties. We describe a simple but flexible noise model for climate proxies for temperature on millennial timescales, which can assist these goals.
Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, Eduardo Zorita, and Fernando Jaume-Santero
Clim. Past, 15, 1099–1111, https://doi.org/10.5194/cp-15-1099-2019, https://doi.org/10.5194/cp-15-1099-2019, 2019
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A database of North American long-term ground surface temperatures, from approximately 1300 CE to 1700 CE, was assembled from geothermal data. These temperatures are useful for studying the future stability of permafrost, as well as for evaluating simulations of preindustrial climate that may help to improve estimates of climate models’ equilibrium climate sensitivity. The database will be made available to the climate science community.
Oliver Bothe, Sebastian Wagner, and Eduardo Zorita
Clim. Past, 15, 307–334, https://doi.org/10.5194/cp-15-307-2019, https://doi.org/10.5194/cp-15-307-2019, 2019
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Our understanding of future climate changes increases if different sources of information agree on past climate variations. Changing climates particularly impact local scales for which future changes in precipitation are highly uncertain. Here, we use information from observations, model simulations, and climate reconstructions for regional precipitation over the British Isles. We find these do not agree well on precipitation variations over the past few centuries.
Florian Andreas Ziemen, Marie-Luise Kapsch, Marlene Klockmann, and Uwe Mikolajewicz
Clim. Past, 15, 153–168, https://doi.org/10.5194/cp-15-153-2019, https://doi.org/10.5194/cp-15-153-2019, 2019
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Heinrich events are among the dominant modes of glacial climate variability. They are caused by massive ice discharges from the Laurentide Ice Sheet into the North Atlantic. In previous studies, the climate changes were either seen as resulting from freshwater released from the melt of the discharged icebergs or by ice sheet elevation changes. With a coupled ice sheet–climate model, we show that both effects are relevant with the freshwater effects preceding the ice sheet elevation effects.
Xing Yi, Birgit Hünicke, and Eduardo Zorita
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-63, https://doi.org/10.5194/cp-2018-63, 2018
Revised manuscript not accepted
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In this study, we analyse the outputs of Earth System Models to investigate the Arabian Sea upwelling for the last 1000 years and in the 21st century. Due to the orbital forcing of the models, the upwelling in the past is found to reveal a negative long-term trend, which matches the observed sediment records. In the future under the RCP8.5 scenario, the warming of the sea water tends to stabilize the surface layer and thus interrupts the upwelling.
Sitar Karabil, Eduardo Zorita, and Birgit Hünicke
Earth Syst. Dynam., 9, 69–90, https://doi.org/10.5194/esd-9-69-2018, https://doi.org/10.5194/esd-9-69-2018, 2018
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We analysed the contribution of atmospheric factors to interannual off-shore sea-level variability in the Baltic Sea region. We identified a different atmospheric circulation pattern that is more closely linked to sea-level variability than the NAO. The inverse barometer effect contributes to that link in the winter and summer seasons. Freshwater flux is connected to the link in summer and net heat flux in winter.The new atmospheric-pattern-related wind forcing plays an important role in summer.
Sitar Karabil, Eduardo Zorita, and Birgit Hünicke
Earth Syst. Dynam., 8, 1031–1046, https://doi.org/10.5194/esd-8-1031-2017, https://doi.org/10.5194/esd-8-1031-2017, 2017
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We statistically analysed the mechanisms of the variability in decadal sea-level trends for the whole Baltic Sea basin over the last century. We used two different sea-level data sets and several climatic data sets. The results of this study showed that precipitation has a lagged effect on decadal sea-level trend variations from which the signature of atmospheric effect is removed. This detected underlying factor is not connected to oceanic forcing driven from the North Atlantic region.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
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Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Maria Pyrina, Sebastian Wagner, and Eduardo Zorita
Clim. Past, 13, 1339–1354, https://doi.org/10.5194/cp-13-1339-2017, https://doi.org/10.5194/cp-13-1339-2017, 2017
Svenja E. Bierstedt, Birgit Hünicke, Eduardo Zorita, and Juliane Ludwig
Earth Syst. Dynam., 8, 639–652, https://doi.org/10.5194/esd-8-639-2017, https://doi.org/10.5194/esd-8-639-2017, 2017
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We statistically analyse the relationship between the structure of migrating dunes in the southern Baltic and the driving wind conditions over the past 26 years, with the long-term aim of using migrating dunes as a proxy for past wind conditions at an interannual resolution.
Juan José Gómez-Navarro, Eduardo Zorita, Christoph C. Raible, and Raphael Neukom
Clim. Past, 13, 629–648, https://doi.org/10.5194/cp-13-629-2017, https://doi.org/10.5194/cp-13-629-2017, 2017
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This contribution aims at assessing to what extent the analogue method, a classic technique used in other branches of meteorology and climatology, can be used to perform gridded reconstructions of annual temperature based on the limited information from available but un-calibrated proxies spread across different locations of the world. We conclude that it is indeed possible, albeit with certain limitations that render the method comparable to more classic techniques.
Xing Yi and Eduardo Zorita
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-124, https://doi.org/10.5194/cp-2016-124, 2016
Revised manuscript not accepted
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In this paper we study the upwelling in the Arabian Sea simulated in two Earth System Models for the last millennium and for the 21st century. Revealing a negative long-term trend due to the model orbital forcing, the upwelling over the last millennium is strongly correlated with the SST, the Indian summer Monsoon and the G.bulloides abundance observed in the sediment records. In the future scenarios the warming of the sea water tends to stabilize the surface layer and hinder the upwelling.
Marlene Klockmann, Uwe Mikolajewicz, and Jochem Marotzke
Clim. Past, 12, 1829–1846, https://doi.org/10.5194/cp-12-1829-2016, https://doi.org/10.5194/cp-12-1829-2016, 2016
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We study the response of the glacial AMOC to different forcings in a coupled AOGCM. The depth of the upper overturning cell remains almost unchanged in response to the full glacial forcing. This is the result of two opposing effects: a deepening due to the ice sheets and a shoaling due to the low GHG concentrations. Increased brine release in the Southern Ocean is key to the shoaling. With glacial ice sheets, a shallower cell can be simulated with GHG concentrations below the glacial level.
Nele Tim, Eduardo Zorita, Birgit Hünicke, Xing Yi, and Kay-Christian Emeis
Ocean Sci., 12, 807–823, https://doi.org/10.5194/os-12-807-2016, https://doi.org/10.5194/os-12-807-2016, 2016
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The impact of external climate forcing on the four eastern boundary upwelling systems is investigated for the recent past and future. Under increased radiative forcing, upwelling-favourable winds should strengthen due to unequal heating of land and oceans. However, coastal upwelling simulated in ensembles of climate simulations do not show any imprint of external forcing neither for the past millennium nor for the future, with the exception of the strongest future scenario.
Svenja E. Bierstedt, Birgit Hünicke, Eduardo Zorita, Sebastian Wagner, and Juan José Gómez-Navarro
Clim. Past, 12, 317–338, https://doi.org/10.5194/cp-12-317-2016, https://doi.org/10.5194/cp-12-317-2016, 2016
X. Yi, B. Hünicke, N. Tim, and E. Zorita
Ocean Sci. Discuss., https://doi.org/10.5194/osd-12-2683-2015, https://doi.org/10.5194/osd-12-2683-2015, 2015
Revised manuscript not accepted
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In this paper, we use the vertical water mass transport data provided by a high-resolution global ocean simulation to study the western Arabian Sea coastal upwelling system. Our results show that: 1). no significant long-term trend is detected in the upwelling time series. 2). the impact of Indian summer monsoon on the simulated upwelling is weak. 3). the upwelling is strongly affected by the sea level pressure gradient and the air temperature gradient.
J. J. Gómez-Navarro, O. Bothe, S. Wagner, E. Zorita, J. P. Werner, J. Luterbacher, C. C. Raible, and J. P Montávez
Clim. Past, 11, 1077–1095, https://doi.org/10.5194/cp-11-1077-2015, https://doi.org/10.5194/cp-11-1077-2015, 2015
N. Tim, E. Zorita, and B. Hünicke
Ocean Sci., 11, 483–502, https://doi.org/10.5194/os-11-483-2015, https://doi.org/10.5194/os-11-483-2015, 2015
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The atmospheric drivers of the Benguela upwelling systems and its variability are statistically analysed with an ocean-only simulation over the last decades. Atmospheric upwelling-favourable conditions are southerly wind/wind stress, a strong subtropical anticyclone, and an ocean-land sea level pressure gradient as well as a negative ENSO and a positive AAO phase. No long-term trends of upwelling and of ocean-minus-land air pressure gradients, as supposed by Bakun, can be seen in our analysis.
J. A. Santos, M. F. Carneiro, A. Correia, M. J. Alcoforado, E. Zorita, and J. J. Gómez-Navarro
Clim. Past, 11, 825–834, https://doi.org/10.5194/cp-11-825-2015, https://doi.org/10.5194/cp-11-825-2015, 2015
J. J. Gómez-Navarro, J. P. Montávez, S. Wagner, and E. Zorita
Clim. Past, 9, 1667–1682, https://doi.org/10.5194/cp-9-1667-2013, https://doi.org/10.5194/cp-9-1667-2013, 2013
G. Esnaola, J. Sáenz, E. Zorita, A. Fontán, V. Valencia, and P. Lazure
Ocean Sci., 9, 655–679, https://doi.org/10.5194/os-9-655-2013, https://doi.org/10.5194/os-9-655-2013, 2013
O. Bothe, J. H. Jungclaus, D. Zanchettin, and E. Zorita
Clim. Past, 9, 1089–1110, https://doi.org/10.5194/cp-9-1089-2013, https://doi.org/10.5194/cp-9-1089-2013, 2013
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Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
EGUsphere, https://doi.org/10.5194/egusphere-2024-45, https://doi.org/10.5194/egusphere-2024-45, 2024
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This study focused on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies were applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method of Random Forest for increasing the accuracy of climate models, concerning the projection of the number of wet days.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
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The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
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The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Carl Svenhag, Moa Kristina Sporre, Tinja Olenius, Daniel Yazgi, Sara Marie Blichner, Lars Peter Nieradzik, and Pontus Roldin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2665, https://doi.org/10.5194/egusphere-2023-2665, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we showed that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacted the number of particles in the air and clouds. It also changed the radiation balance in the same magnitude as man-made greenhouse emissions.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
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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 some 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.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
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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.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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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 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
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The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
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
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused 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 retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused 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 retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Cited articles
Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., and Zheng, X.: TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems, https://www.tensorflow.org/ (last access 22 February 2024), 2015. a
Barboza, L., Li, B., Tingley, M. P., and Viens, F. G.: Reconstructing past temperatures from natural proxies and estimated climate forcings using short- and long-memory models, Ann. Appl. Stat., 8, 1966–2001, 2014. a
Büntgen, U., Allen, K., Anchukaitis, K. J., Arseneault, D., Boucher, É., Bräuning, A., Chatterjee, S., Cherubini, P., Churakova, O. V., Corona, C., Gennaretti, F., Grießinger, J., Guillet, S., Guiot, J., Gunnarson, B., Helama, S., Hochreuther, P., Hughes, M. K., Huybers, P., Kirdyanov, A. V., Krusic, P. J., Ludescher, J., Meier, W. J.-H., Myglan, V. S., Nicolussi, K., Oppenheimer, C., Reinig, F., Salzer, M. W., Seftigen, K., Stine, A. R., Stoffel, M., St. George, S., Tejedor, E., Trevino, A., Trouet, V., Wang, J., Wilson, R., Yang, B., Xu, G., and Esper, J.: The influence of decision-making in tree ring-based climate reconstructions, Nat. Commun., 12, 1–10, 2021. a
Christiansen, B., Schmith, T., and Thejll, P.: A surrogate ensemble study of climate reconstruction methods: Stochasticity and robustness, J. Climate, 22, 951–976, https://doi.org/10.1175/2008JCLI2301.1, 2009. a
Clement, A., Bellomo, K., Murphy, L. N., Cane, M. A., Mauritsen, T., Rädel, G., and Stevens, B.: The Atlantic Multidecadal Oscillation without a role for ocean circulation, Science, 350, 320–324, https://doi.org/10.1126/science.aab3980, 2015. a
Duvenaud, D., Lloyd, J., Grosse, R., Tenenbaum, J., and Zoubin, G.: Structure discovery in nonparametric regression through compositional kernel search, in: International Conference on Machine Learning, edited by: Dasgupta, S. and McAllester, D., vol. 28, Proceedings of Machine Learning Research, PMLR, Atlanta, Georgia, USA, 1166–1174, https://proceedings.mlr.press/v28/duvenaud13.html (last access: 22 February 2024), 2013. a
Esper, J., Frank, D. C., Wilson, R. J., and Briffa, K. R.: Effect of scaling and regression on reconstructed temperature amplitude for the past millennium, Geophys. Res. Lett., 32, L07711, https://doi.org/10.1029/2004GL021236, 2005. a
Garuba, O. A., Lu, J., Singh, H. A., Liu, F., and Rasch, P.: On the relative roles of the atmosphere and ocean in the Atlantic multidecadal variability, Geophys. Res. Lett., 45, 9186–9196, https://doi.org/10.1029/2018GL078882, 2018. a
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P. H., Yang, Z.-L., and Zhang, M.: The community climate system model version 4, J. Climate, 24, 4973–4991, https://doi.org/10.1175/2011JCLI4083.1, 2011. a, b
Giorgetta, M. A., Jungclaus, J., Reick, C., Legutke, S., Bader, J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K., Claussen, M., Marotzke, J., and Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Sy., 5, 572–597, https://doi.org/10.1002/jame.20038, 2013. a
Gray, S. T., Graumlich, L. J., Betancourt, J. L., and Pederson, G. T.: A tree-ring based reconstruction of the Atlantic Multidecadal Oscillation since 1567 AD, Geophys. Res. Lett., 31, L12205, https://doi.org/10.1029/2004GL019932, 2004. a, b, c
Hanhijärvi, S., Tingley, M. P., and Korhola, A.: Pairwise comparisons to reconstruct mean temperature in the Arctic Atlantic Region over the last 2,000 years, Clim. Dynam., 41, 2039–2060, https://doi.org/10.1007/s00382-013-1701-4, 2013. a
Haustein, K., Otto, F. E., Venema, V., Jacobs, P., Cowtan, K., Hausfather, Z., Way, R. G., White, B., Subramanian, A., and Schurer, A. P.: A limited role for unforced internal variability in twentieth-century warming, J. Climate, 32, 4893–4917, https://doi.org/10.1175/JCLI-D-18-0555.1, 2019. a
Hensman, J., Fusi, N., and Lawrence, N. D.: Gaussian processes for Big data, in: Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, ArXiv [preprint], https://doi.org/10.48550/arXiv.1309.6835, 2013. a, b, c, d
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Jones, P. D. and Mann, M. E.: Climate over past millennia, Rev. Geophys., 42, RG2002, https://doi.org/10.1029/2003RG000143, 2004. a
Kilbourne, H., Yu, Z., Neukom, R., Nash, D., Gergis, J., Steig, E. J., Ge, Q., McKay, N. P., Kaufman, D. S., Curran, M. A. J., Thomas, E. R., Sigl, M., Thirumalai, K., Emile-Geay, J., Chen, M.-T., Seidenkrantz, M.-S., Turney, C., Jacques, J. S., Linderholm, H. W., Horiuchi, K., Björklund, J., Severi, M., Cook, E., Bertler, N., Isaksson, E., wahl, eugene, Leduc, G., Martrat, B., E Tierney, J., Goosse, H., Thamban, M., DeLong, K., Anchukaitis, K., Zinke, J., Uemura, R., Abram, N. J., Shao, X., Dixon, D., von Gunten, L., Wang, J., Addison, J., Evans, M. N., Henley, B., Zhixin, H., McGregor, H. V., Pederson, G. T., Stenni, B., Werner, J., Xu, C., Divine, D., Dixon, B. C., Mundo, I. A., Nakatsuka, T., Phipps, S. J., Routson, C., Tyler, J. J., Allen, K. J., Chase, B., de Jong, R., Ekaykin, A. A., Ersek, V., Filipsson, H. L., Francus, P., Freund, M., Frezzotti, M., Gaire, N., Gajewski, K., Gornostaeva, A., Grosjean, M., Hormes, A., Husum, K., Selvaraj, K., Kawamura, K., Nalan, K., Lorrey, A., Mikhalenko, V., Mortyn, G. P., Motoyama, H., Moy, A., Mulvaney, R., Munz, P., Oerter, H., Opel, T., Orsi, A., Ovchinnikov, D., Porter, T., Roop, H., Saenger, C., Sano, M., Sauchyn, D., Saunders, K., Sicre, M.-A., Sinclair, K., St George, S., Thapa, U., Viau, A., Vladimirova, D., and White, J.: A global multiproxy database for temperature reconstructions of the Common Era, figshare [data set], https://doi.org/10.6084/m9.figshare.c.3285353.v2, 2017. a
Kingma, D. P. and Ba, J.: Adam: A method for stochastic optimization, arXiv [preprint], https://doi.org/10.48550/arXiv.1412.6980, 2014. a
Knudsen, M. F., Jacobsen, B. H., Seidenkrantz, M.-S., and Olsen, J.: Evidence for external forcing of the Atlantic Multidecadal Oscillation since termination of the Little Ice Age, Nat. Commun., 5, 1–8, https://doi.org/10.1038/ncomms4323, 2014. a
Kopp, R. E., Kemp, A. C., Bittermann, K., Horton, B. P., Donnelly, J. P., Gehrels, W. R., Hay, C. C., Mitrovica, J. X., Morrow, E. D., and Rahmstorf, S.: Temperature-driven global sea-level variability in the Common Era, P. Natl. Acad. Sci. USA, 113, E1434–E1441, https://doi.org/10.1073/pnas.1517056113, 2016. a
Landrum, L., Otto-Bliesner, B. L., Wahl, E. R., Conley, A., Lawrence, P. J., Rosenbloom, N., and Teng, H.: Last millennium climate and its variability in CCSM4, J. Climate, 26, 1085–1111, https://doi.org/10.1175/JCLI-D-11-00326.1, 2013. a
Mann, M. E., Zhang, Z., Hughes, M. K., Bradley, R. S., Miller, S. K., Rutherford, S., and Ni, F.: Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia, P. Natl. Acad. Sci. USA, 105, 13252–13257, https://doi.org/10.1073/pnas.0805721105, 2008. a
Mann, M. E., Steinman, B. A., Brouillette, D. J., and Miller, S. K.: Multidecadal climate oscillations during the past millennium driven by volcanic forcing, Science, 371, 1014–1019, https://doi.org/10.1126/science.abc5810, 2021. a
Mann, M. E., Steinman, B. A., Brouillette, D. J., Fernandez, A., and Miller, S. K.: On The Estimation of Internal Climate Variability During the Preindustrial Past Millennium, Geophys. Res. Lett., 49, e2021GL096596, https://doi.org/10.1029/2021GL096596, 2022. a
Mansfield, L. A., Nowack, P. J., Kasoar, M., Everitt, R. G., Collins, W. J., and Voulgarakis, A.: Predicting global patterns of long-term climate change from short-term simulations using machine learning, npj Clim. Atmos. Sci., 3, 1–9, https://doi.org/10.1038/s41612-020-00148-5, 2020. a
Matthews, A. G. d. G., Van Der Wilk, M., Nickson, T., Fujii, K., Boukouvalas, A., León-Villagrá, P., Ghahramani, Z., and Hensman, J.: GPflow: A Gaussian Process Library using TensorFlow, J. Mach. Learn. Res., 18, 1–6, 2017. a
Mead, A.: Review of the Development of Multidimensional Scaling Methods, J. Roy. Stat. Soc. Ser. D, 41, 27–39, https://doi.org/10.2307/2348634, 1992. a, b
Meehl, J.: CCSM4 coupled run for CMIP5 historical (1850–2005), World Data Center for Climate (WDCC) at DKRZ [data set], https://doi.org/10.1594/WDCC/CMIP5.NRS4hi, 2014. a, b
Mette, M. J., Wanamaker Jr, A. D., Retelle, M. J., Carroll, M. L., Andersson, C., and Ambrose Jr., W. G.: Persistent multidecadal variability since the 15th century in the southern Barents Sea derived from annually resolved shell-based records, J. Geophys. Res.-Oceans, 126, e2020JC017074, https://doi.org/10.1029/2020JC017074, 2021. a
Michel, S., Swingedouw, D., Chavent, M., Ortega, P., Mignot, J., and Khodri, M.: Reconstructing climatic modes of variability from proxy records using ClimIndRec version 1.0, Geosci. Model Dev., 13, 841–858, https://doi.org/10.5194/gmd-13-841-2020, 2020. a, b
Miles, M. W., Divine, D. V., Furevik, T., Jansen, E., Moros, M., and Ogilvie, A. E.: A signal of persistent Atlantic multidecadal variability in Arctic sea ice, Geophys. Res. Lett., 41, 463–469, https://doi.org/10.1002/2013GL058084, 2014. a
Otto-Bliesner, B.: CCSM4 coupled simulation for CMIP5 past 1000 years (850–1850) with natural forcings, World Data Center for Climate (WDCC) at DKRZ [data set], https://doi.org/10.1594/WDCC/CMIP5.NRS4pk, 2014. a, b
PAGES2k: A global multiproxy database for temperature reconstructions of the Common Era, Sci. Data, 4, 170088, https://doi.org/10.1038/sdata.2017.88, 2017. a, b
PAGES2k: Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era, Nat. Geosci., 12, 643, https://doi.org/10.1038/s41561-019-0400-0, 2019. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-learn: Machine learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011. a
Saenger, C., Cohen, A. L., Oppo, D. W., Halley, R. B., and Carilli, J. E.: Surface-temperature trends and variability in the low-latitude North Atlantic since 1552, Nat. Geosci., 2, 492–495, https://doi.org/10.1038/ngeo552, 2009. a
Särkkä, S.: Bayesian filtering and smoothing, 3, Cambridge University Press, https://doi.org/10.1017/CBO9781139344203, 2013. a
Singh, H. K. A., Hakim, G. J., Tardif, R., Emile-Geay, J., and Noone, D. C.: Insights into Atlantic multidecadal variability using the Last Millennium Reanalysis framework, Clim. Past, 14, 157–174, https://doi.org/10.5194/cp-14-157-2018, 2018. a, b
Smerdon, J. E.: Climate models as a test bed for climate reconstruction methods: pseudoproxy experiments, Wires Clim. Change, 3, 63–77, https://doi.org/10.1002/wcc.149, 2012. a, b
Smerdon, J. E., Kaplan, A., Zorita, E., González-Rouco, J. F., and Evans, M.: Spatial performance of four climate field reconstruction methods targeting the Common Era, Geophys. Res. Lett., 38, L11705, https://doi.org/10.1029/2011GL047372, 2011. a
Svendsen, L., Hetzinger, S., Keenlyside, N., and Gao, Y.: Marine-based multiproxy reconstruction of Atlantic multidecadal variability, Geophys. Res. Lett., 41, 1295–1300, https://doi.org/10.1002/2013GL059076, 2014. a
Von Storch, H., Zorita, E., Jones, J. M., Dimitriev, Y., González-Rouco, F., and Tett, S. F.: Reconstructing past climate from noisy data, Science, 306, 679–682, https://doi.org/10.1126/science.1096109, 2004. a
von Storch, H., Zorita, E., and González-Rouco, F.: Assessment of three temperature reconstruction methods in the virtual reality of a climate simulation, Int. J. Earth Sci., 98, 67–82, https://doi.org/10.1007/s00531-008-0349-5, 2009. a
Wang, J., Yang, B., Ljungqvist, F. C., Luterbacher, J., Osborn, T. J., Briffa, K. R., and Zorita, E.: Internal and external forcing of multidecadal Atlantic climate variability over the past 1,200 years, Nat. Geosci., 10, 512–517, https://doi.org/10.1038/ngeo2962, 2017. a, b, c, d
Wegmann, M. and Jaume-Santero, F.: Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data, Commun. Earth Environ., 4, 217, https://doi.org/10.1038/s43247-023-00872-9, 2023. a
Yan, X., Zhang, R., and Knutson, T. R.: A multivariate AMV index and associated discrepancies between observed and CMIP5 externally forced AMV, Geophys. Res. Lett., 46, 4421–4431, https://doi.org/10.1029/2019GL082787, 2019. a
Zhang, R. and Delworth, T. L.: Impact of Atlantic multidecadal oscillations on India/Sahel rainfall and Atlantic hurricanes, Geophys. Res. Lett., 33, L17712, https://doi.org/10.1029/2006GL026267, 2006. a
Zhang, R., Delworth, T. L., and Held, I. M.: Can the Atlantic Ocean drive the observed multidecadal variability in Northern Hemisphere mean temperature?, Geophys. Res. Lett., 34, L02709, https://doi.org/10.1029/2006GL028683, 2007. a
Zhang, R., Sutton, R., Danabasoglu, G., Kwon, Y.-O., Marsh, R., Yeager, S. G., Amrhein, D. E., and Little, C. M.: A review of the role of the Atlantic meridional overturning circulation in Atlantic multidecadal variability and associated climate impacts, Rev. Geophys., 57, 316–375, https://doi.org/10.1029/2019RG000644, 2019. a, b
Zhang, Z., Wagner, S., Klockmann, M., and Zorita, E.: Evaluation of statistical climate reconstruction methods based on pseudoproxy experiments using linear and machine-learning methods, Clim. Past, 18, 2643–2668, https://doi.org/10.5194/cp-18-2643-2022, 2022. a, b
Zorita, E., González-Rouco, F., and Legutke, S.: Testing the approach to paleoclimate reconstructions in the context of a 1000-yr control simulation with the ECHO-G coupled climate model, J. Climate, 16, 1378–1390, https://doi.org/10.1175/1520-0442(2003)16<1378:TTMEAA>2.0.CO;2, 2003. a
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Reconstructions of climate variability before the observational period rely on climate proxies...