Articles | Volume 32, issue 2
https://doi.org/10.5194/npg-32-201-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-32-201-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Jul 2025
Research article |
| 01 Jul 2025
| 01 Jul 2025
Explaining the high skill of reservoir computing methods in El Niño prediction
Francesco Guardamagna
CORRESPONDING AUTHOR
Institute for Marine and Atmospheric research Utrecht, Department of Physics, Utrecht University, Utrecht, the Netherlands
Center for Complex Systems Studies, Utrecht University, Utrecht, the Netherlands
Claudia Wieners
Institute for Marine and Atmospheric research Utrecht, Department of Physics, Utrecht University, Utrecht, the Netherlands
Center for Complex Systems Studies, Utrecht University, Utrecht, the Netherlands
Henk A. Dijkstra
Institute for Marine and Atmospheric research Utrecht, Department of Physics, Utrecht University, Utrecht, the Netherlands
Center for Complex Systems Studies, Utrecht University, Utrecht, the Netherlands
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Gideon Futerman, Mira Adhikari, Alistair Duffey, Yuanchao Fan, Jessica Gurevitch, Peter Irvine, and Claudia Wieners
Earth Syst. Dynam., 16, 939–978, https://doi.org/10.5194/esd-16-939-2025, https://doi.org/10.5194/esd-16-939-2025, 2025
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This review assesses the interaction of solar radiation modification (SRM), a technology to reduce the impacts of climate change by reflecting sunlight and earth system tipping elements. We find that SRM at least partially reduces the risk of hitting most (9 out of 15) of the tipping points we studied relative to the same emission pathway and did not overall worsen the risk for any. Uncertainties for all tipping elements studied were high, so we also lay out suggestions for future research.
Jasper de Jong, Daniel Pflüger, Simone Lingbeek, Claudia E. Wieners, Michiel L. J. Baatsen, and René R. Wijngaard
EGUsphere, https://doi.org/10.22541/essoar.174273333.31930996/v1, https://doi.org/10.22541/essoar.174273333.31930996/v1, 2025
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Injection of reflective sulphate aerosols high in the atmosphere is a proposed method to mitigate global warming. Climate simulations with injection are more expensive than standard future projections. We propose a method that dynamically scales the forcing fields based on pre-existing full-complexity data. This opens up possibilities for ensemble generation, new scenarios and higher resolution runs. We show that our method works for multiple model versions, injection scenarios and resolutions.
Swinda K. J. Falkena, Henk A. Dijkstra, and Anna S. von der Heydt
EGUsphere, https://doi.org/10.48550/arXiv.2408.16541, https://doi.org/10.48550/arXiv.2408.16541, 2025
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The subpolar gyre is a wind-driven circulation in the North Atlantic Ocean, which enables the mixing of water between the surface and deeper layers. We investigate the interactions between the strength of the gyre circulation, salinity, temperature and mixing in climate models. We find that most models capture an increase in salinity or a decrease in temperature leading to mixing. However, the feedback from the density in the gyre centre to the strength of its circulation is poorly represented.
Amber A. Boot and Henk A. Dijkstra
EGUsphere, https://doi.org/10.5194/egusphere-2025-758, https://doi.org/10.5194/egusphere-2025-758, 2025
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The Atlantic Meridional Overturning Circulation (AMOC) is a tipping element in the Earth System that affects the global climate. We often use models to understand how the AMOC tips. However, these models are flawed. Here we study the effect of these flaws on the AMOC multistable regime in a climate model. We artificially add additional flaws to the model. We find that AMOC stability can be affected by such flaws and a reductionof such flaws in climate models is therefore thought to be essential.
Woosok Moon, Seung Pyo Lee, Elian Vanderborght, Georgy Manucharyan, and Henk Dijkstra
EGUsphere, https://doi.org/10.5194/egusphere-2025-1004, https://doi.org/10.5194/egusphere-2025-1004, 2025
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As the climate warms, extreme weather is becoming more frequent in mid-latitudes. A key factor is the jet stream, shaped by atmospheric waves that influence wind and storm patterns. This study presents a simplified model showing how swirling air currents (eddies) maintain the jet stream and impact weather. As global warming alters these patterns, this research helps improve predictions of future weather changes.
Bouke Biemond, Wouter M. Kranenburg, Ymkje Huismans, Huib E. de Swart, and Henk A. Dijkstra
Ocean Sci., 21, 261–281, https://doi.org/10.5194/os-21-261-2025, https://doi.org/10.5194/os-21-261-2025, 2025
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We study salinity in estuaries consisting of a network of channels. To this end, we develop a model that computes the flow and salinity in such systems. We use the model to quantify the mechanisms by which salt is transported into estuarine networks, the response to changes in river discharge, and the impact of depth changes. Results show that when changing the depth of channels, the effects on salt intrusion into other channels in the network can be larger than the effect on the channel itself.
René M. van Westen, Elian Vanderborght, and Henk A. Dijkstra
EGUsphere, https://doi.org/10.5194/egusphere-2025-14, https://doi.org/10.5194/egusphere-2025-14, 2025
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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The Atlantic Meridional Overturning Circulation (AMOC) is a tipping element in the fully-coupled Community Earth System Model (CESM). Under varying freshwater flux forcing parameters or climate change, the AMOC may collapse from a relatively strong state to a substantially weaker state. It is important to understand the dynamics of the AMOC collapse in the CESM. We show that the stability of the AMOC in the CESM is controlled by only a few feedback processes.
Aurora Faure Ragani and Henk A. Dijkstra
EGUsphere, https://doi.org/10.5194/egusphere-2025-45, https://doi.org/10.5194/egusphere-2025-45, 2025
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The Atlantic Meridional Overturning Circulation (AMOC) is sensitive to changing surface forcing conditions. Under future greenhouse gas emission reductions, it was shown in a conceptual model that it may be possible to avoid a collapse of the AMOC. Using a detailed global ocean model, we clarify the physics of the collapse and recovery behaviour of the AMOC. The potential to avoid an AMOC collapse is tightly linked to a delicate balance of salt fluxes in the northern North Atlantic.
Amber A. Boot and Henk A. Dijkstra
Earth Syst. Dynam., 16, 115–150, https://doi.org/10.5194/esd-16-115-2025, https://doi.org/10.5194/esd-16-115-2025, 2025
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The ocean is forced at the surface by a heat flux and a freshwater flux. This noise can influence long-term ocean variability and large-scale circulation. Here we study noise characteristics in reanalysis data for these fluxes. We try to capture the noise characteristics by using several noise models and compare these to state-of-the-art climate models. A pointwise noise model performs better than the climate models and can be used as forcing in ocean-only models.
Amber A. Boot, Anna S. von der Heydt, and Henk A. Dijkstra
Earth Syst. Dynam., 15, 1567–1590, https://doi.org/10.5194/esd-15-1567-2024, https://doi.org/10.5194/esd-15-1567-2024, 2024
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We investigate the multiple equilibria window (MEW) of the Atlantic Meridional Overturning Circulation (AMOC) within a box model. We find that increasing the total carbon content of the system widens the MEW of the AMOC. The important mechanisms at play are the balance between the source and sink of carbon and the sensitivity of the AMOC to freshwater forcing over the Atlantic Ocean. Our results suggest that changes in the marine carbon cycle can influence AMOC stability in future climates.
Claudia Elisabeth Wieners and Guðmundur Hálfdanarson
Nat. Hazards Earth Syst. Sci., 24, 2971–2994, https://doi.org/10.5194/nhess-24-2971-2024, https://doi.org/10.5194/nhess-24-2971-2024, 2024
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After the 1783 Laki eruption, excess mortality in Iceland was one-sixth of the population, traditionally explained by famine due to livestock loss. Since 1970, it has been suggested that 1) fluorine poisoning may have contributed to mortality in Iceland and 2) air pollution might have caused excess deaths in both Iceland and Europe. Reviewing contemporary Icelandic demographic data, air pollution simulations, and medical records on fluorosis, we show that evidence for both hypotheses is weak.
Arthur Merlijn Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Frank M. Selten, and Henk A. Dijkstra
Earth Syst. Dynam., 15, 1037–1054, https://doi.org/10.5194/esd-15-1037-2024, https://doi.org/10.5194/esd-15-1037-2024, 2024
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We might be able to constrain uncertainty in future climate projections by investigating variations in the climate of the past. In this study, we investigate the interactions of climate variability between the tropical Pacific (El Niño) and the North Pacific in a warm past climate – the mid-Pliocene, a period roughly 3 million years ago. Using model simulations, we find that, although the variability in El Niño was reduced, the variability in the North Pacific atmosphere was not.
Sacha Sinet, Peter Ashwin, Anna S. von der Heydt, and Henk A. Dijkstra
Earth Syst. Dynam., 15, 859–873, https://doi.org/10.5194/esd-15-859-2024, https://doi.org/10.5194/esd-15-859-2024, 2024
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Some components of the Earth system may irreversibly collapse under global warming. Among them, the Atlantic Meridional Overturning Circulation (AMOC), the Greenland Ice Sheet, and West Antarctica Ice Sheet are of utmost importance for maintaining the present-day climate. In a simplified model, we show that both the rate of ice melting and the natural variability linked to freshwater fluxes over the Atlantic Ocean drastically affect how an ice sheet collapse impacts the AMOC stability.
Julia E. Weiffenbach, Henk A. Dijkstra, Anna S. von der Heydt, Ayako Abe-Ouchi, Wing-Le Chan, Deepak Chandan, Ran Feng, Alan M. Haywood, Stephen J. Hunter, Xiangyu Li, Bette L. Otto-Bliesner, W. Richard Peltier, Christian Stepanek, Ning Tan, Julia C. Tindall, and Zhongshi Zhang
Clim. Past, 20, 1067–1086, https://doi.org/10.5194/cp-20-1067-2024, https://doi.org/10.5194/cp-20-1067-2024, 2024
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Elevated atmospheric CO2 concentrations and a smaller Antarctic Ice Sheet during the mid-Pliocene (~ 3 million years ago) cause the Southern Ocean surface to become fresher and warmer, which affects the global ocean circulation. The CO2 concentration and the smaller Antarctic Ice Sheet both have a similar and approximately equal impact on the Southern Ocean. The conditions of the Southern Ocean in the mid-Pliocene could therefore be analogous to those in a future climate with smaller ice sheets.
René M. van Westen and Henk A. Dijkstra
Ocean Sci., 20, 549–567, https://doi.org/10.5194/os-20-549-2024, https://doi.org/10.5194/os-20-549-2024, 2024
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The Atlantic Meridional Overturning Circulation (AMOC) is an important component in the global climate system. Observations of the present-day AMOC indicate that it may weaken or collapse under global warming, with profound disruptive effects on future climate. However, AMOC weakening is not correctly represented because an important feedback is underestimated due to biases in the Atlantic's freshwater budget. Here we address these biases in several state-of-the-art climate model simulations.
Arthur Merlijn Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Aarnout J. van Delden, and Henk A. Dijkstra
Weather Clim. Dynam., 5, 395–417, https://doi.org/10.5194/wcd-5-395-2024, https://doi.org/10.5194/wcd-5-395-2024, 2024
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The mid-Pliocene, a geological period around 3 million years ago, is sometimes considered the best analogue for near-future climate. It saw similar CO2 concentrations to the present-day but also a slightly different geography. In this study, we use climate model simulations and find that the Northern Hemisphere winter responds very differently to increased CO2 or to the mid-Pliocene geography. Our results weaken the potential of the mid-Pliocene as a future climate analogue.
Michiel Baatsen, Peter Bijl, Anna von der Heydt, Appy Sluijs, and Henk Dijkstra
Clim. Past, 20, 77–90, https://doi.org/10.5194/cp-20-77-2024, https://doi.org/10.5194/cp-20-77-2024, 2024
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This work introduces the possibility and consequences of monsoons on Antarctica in the warm Eocene climate. We suggest that such a monsoonal climate can be important to understand conditions in Antarctica prior to large-scale glaciation. We can explain seemingly contradictory indications of ice and vegetation on the continent through regional variability. In addition, we provide a new mechanism through which most of Antarctica remained ice-free through a wide range of global climatic changes.
Sina Loriani, Yevgeny Aksenov, David Armstrong McKay, Govindasamy Bala, Andreas Born, Cristiano M. Chiessi, Henk Dijkstra, Jonathan F. Donges, Sybren Drijfhout, Matthew H. England, Alexey V. Fedorov, Laura Jackson, Kai Kornhuber, Gabriele Messori, Francesco Pausata, Stefanie Rynders, Jean-Baptiste Salée, Bablu Sinha, Steven Sherwood, Didier Swingedouw, and Thejna Tharammal
EGUsphere, https://doi.org/10.5194/egusphere-2023-2589, https://doi.org/10.5194/egusphere-2023-2589, 2023
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In this work, we draw on paleoreords, observations and modelling studies to review tipping points in the ocean overturning circulations, monsoon systems and global atmospheric circulations. We find indications for tipping in the ocean overturning circulations and the West African monsoon, with potentially severe impacts on the Earth system and humans. Tipping in the other considered systems is considered conceivable but currently not sufficiently supported by evidence.
Valérian Jacques-Dumas, René M. van Westen, Freddy Bouchet, and Henk A. Dijkstra
Nonlin. Processes Geophys., 30, 195–216, https://doi.org/10.5194/npg-30-195-2023, https://doi.org/10.5194/npg-30-195-2023, 2023
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Computing the probability of occurrence of rare events is relevant because of their high impact but also difficult due to the lack of data. Rare event algorithms are designed for that task, but their efficiency relies on a score function that is hard to compute. We compare four methods that compute this function from data and measure their performance to assess which one would be best suited to be applied to a climate model. We find neural networks to be most robust and flexible for this task.
Julia E. Weiffenbach, Michiel L. J. Baatsen, Henk A. Dijkstra, Anna S. von der Heydt, Ayako Abe-Ouchi, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Zixuan Han, Alan M. Haywood, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Julia C. Tindall, Charles J. R. Williams, Qiong Zhang, and Zhongshi Zhang
Clim. Past, 19, 61–85, https://doi.org/10.5194/cp-19-61-2023, https://doi.org/10.5194/cp-19-61-2023, 2023
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We study the behavior of the Atlantic Meridional Overturning Circulation (AMOC) in the mid-Pliocene. The mid-Pliocene was about 3 million years ago and had a similar CO2 concentration to today. We show that the stronger AMOC during this period relates to changes in geography and that this has a significant influence on ocean temperatures and heat transported northwards by the Atlantic Ocean. Understanding the behavior of the mid-Pliocene AMOC can help us to learn more about our future climate.
Amber Boot, Anna S. von der Heydt, and Henk A. Dijkstra
Earth Syst. Dynam., 13, 1041–1058, https://doi.org/10.5194/esd-13-1041-2022, https://doi.org/10.5194/esd-13-1041-2022, 2022
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Atmospheric pCO2 of the past shows large variability on different timescales. We focus on the effect of the strength of Atlantic Meridional Overturning Circulation (AMOC) on this variability and on the AMOC–pCO2 relationship. We find that climatic boundary conditions and the representation of biology in our model are most important for this relationship. Under certain conditions, we find internal oscillations, which can be relevant for atmospheric pCO2 variability during glacial cycles.
Mikael L. A. Kaandorp, Stefanie L. Ypma, Marijke Boonstra, Henk A. Dijkstra, and Erik van Sebille
Ocean Sci., 18, 269–293, https://doi.org/10.5194/os-18-269-2022, https://doi.org/10.5194/os-18-269-2022, 2022
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A large amount of marine litter, such as plastics, is located on or around beaches. Both the total amount of this litter and its transport are poorly understood. We investigate this by training a machine learning model with data of cleanup efforts on Dutch beaches between 2014 and 2019, obtained by about 14 000 volunteers. We find that Dutch beaches contain up to 30 000 kg of litter, largely depending on tides, oceanic transport, and how exposed the beaches are.
Peter D. Nooteboom, Peter K. Bijl, Christian Kehl, Erik van Sebille, Martin Ziegler, Anna S. von der Heydt, and Henk A. Dijkstra
Earth Syst. Dynam., 13, 357–371, https://doi.org/10.5194/esd-13-357-2022, https://doi.org/10.5194/esd-13-357-2022, 2022
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Having descended through the water column, microplankton in ocean sediments represents the ocean surface environment and is used as an archive of past and present surface oceanographic conditions. However, this microplankton is advected by turbulent ocean currents during its sinking journey. We use simulations of sinking particles to define ocean bottom provinces and detect these provinces in datasets of sedimentary microplankton, which has implications for palaeoclimate reconstructions.
Arthur M. Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Henk A. Dijkstra, Julia C. Tindall, Ayako Abe-Ouchi, Alice R. Booth, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Alan M. Haywood, Stephen J. Hunter, Youichi Kamae, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gabriel M. Pontes, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Qiong Zhang, Zhongshi Zhang, Ilana Wainer, and Charles J. R. Williams
Clim. Past, 17, 2427–2450, https://doi.org/10.5194/cp-17-2427-2021, https://doi.org/10.5194/cp-17-2427-2021, 2021
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In this work, we have studied the behaviour of El Niño events in the mid-Pliocene, a period of around 3 million years ago, using a collection of 17 climate models. It is an interesting period to study, as it saw similar atmospheric carbon dioxide levels to the present day. We find that the El Niño events were less strong in the mid-Pliocene simulations, when compared to pre-industrial climate. Our results could help to interpret El Niño behaviour in future climate projections.
André Jüling, Anna von der Heydt, and Henk A. Dijkstra
Ocean Sci., 17, 1251–1271, https://doi.org/10.5194/os-17-1251-2021, https://doi.org/10.5194/os-17-1251-2021, 2021
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On top of forced changes such as human-caused global warming, unforced climate variability exists. Most multidecadal variability (MV) involves the oceans, but current climate models use non-turbulent, coarse-resolution oceans. We investigate the effect of resolving important turbulent ocean features on MV. We find that ocean heat content, ocean–atmosphere heat flux, and global mean surface temperature MV is more pronounced in the higher-resolution model relative to higher-frequency variability.
Johannes Lohmann, Daniele Castellana, Peter D. Ditlevsen, and Henk A. Dijkstra
Earth Syst. Dynam., 12, 819–835, https://doi.org/10.5194/esd-12-819-2021, https://doi.org/10.5194/esd-12-819-2021, 2021
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Tipping of one climate subsystem could trigger a cascade of subsequent tipping points and even global-scale climate tipping. Sequential shifts of atmosphere, sea ice and ocean have been recorded in proxy archives of past climate change. Based on this we propose a conceptual model for abrupt climate changes of the last glacial. Here, rate-induced tipping enables tipping cascades in systems with relatively weak coupling. An early warning signal is proposed that may detect such a tipping.
André Jüling, Xun Zhang, Daniele Castellana, Anna S. von der Heydt, and Henk A. Dijkstra
Ocean Sci., 17, 729–754, https://doi.org/10.5194/os-17-729-2021, https://doi.org/10.5194/os-17-729-2021, 2021
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We investigate how the freshwater budget of the Atlantic changes under climate change, which has implications for the stability of the Atlantic Meridional Overturning Circulation. We compare the effect of ocean model resolution in a climate model and find many similarities between the simulations, enhancing trust in the current generation of climate models. However, ocean biases are reduced in the strongly eddying simulation, and significant local freshwater budget differences exist.
Pascal Wang, Daniele Castellana, and Henk A. Dijkstra
Nonlin. Processes Geophys., 28, 135–151, https://doi.org/10.5194/npg-28-135-2021, https://doi.org/10.5194/npg-28-135-2021, 2021
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This paper proposes two improvements to the use of Trajectory-Adaptive Multilevel Sampling, a rare-event algorithm which computes noise-induced transition probabilities. The first improvement uses locally linearised dynamics in order to reduce the arbitrariness associated with defining what constitutes a transition. The second improvement uses empirical transition paths accumulated at high noise in order to formulate the score function which determines the performance of the algorithm.
Amber Boot, René M. van Westen, and Henk A. Dijkstra
Ocean Sci., 17, 335–350, https://doi.org/10.5194/os-17-335-2021, https://doi.org/10.5194/os-17-335-2021, 2021
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The Maud Rise polynya is a hole in the sea ice surrounding Antarctica that occurs during winter. It appeared in 2016 and 2017. Our study concludes that heat and salt accumulation around 1000 m depth are likely to be important for polynya formation. The heat is mixed upward to the surface where it is able to melt the sea ice and, thus, create a polynya. How often the polynya forms depends largely on the variation in the time of the heat and salt accumulation.
David Wichmann, Christian Kehl, Henk A. Dijkstra, and Erik van Sebille
Nonlin. Processes Geophys., 28, 43–59, https://doi.org/10.5194/npg-28-43-2021, https://doi.org/10.5194/npg-28-43-2021, 2021
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Fluid parcels transported in complicated flows often contain subsets of particles that stay close over finite time intervals. We propose a new method for detecting finite-time coherent sets based on the density-based clustering technique of ordering points to identify the clustering structure (OPTICS). Unlike previous methods, our method has an intrinsic notion of coherent sets at different spatial scales. OPTICS is readily implemented in the SciPy sklearn package, making it easy to use.
Carine G. van der Boog, J. Otto Koetsier, Henk A. Dijkstra, Julie D. Pietrzak, and Caroline A. Katsman
Earth Syst. Sci. Data, 13, 43–61, https://doi.org/10.5194/essd-13-43-2021, https://doi.org/10.5194/essd-13-43-2021, 2021
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Thermohaline staircases are stepped structures in the ocean that contain enhanced diapycnal salt and heat transport. In this study, we present a global dataset of thermohaline staircases derived from 487 493 observations of Argo profiling floats and Ice-Tethered Profilers using a novel detection algorithm.
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.
René M. van Westen and Henk A. Dijkstra
Ocean Sci., 16, 1443–1457, https://doi.org/10.5194/os-16-1443-2020, https://doi.org/10.5194/os-16-1443-2020, 2020
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During the mid-1970s and quite recently in 2017, a large open-water area appeared in the Antarctic sea-ice pack, the so-called Maud Rise polynya. From several model studies, the reoccurrence time of this polynya seems arbitrary. In this study, we address the reoccurrence time of the polynya using a high-resolution climate model. We find a preferred multidecadal return time in polynya formation. The return time of the polynya is associated with a large-scale ocean mode in the Southern Ocean.
David Wichmann, Christian Kehl, Henk A. Dijkstra, and Erik van Sebille
Nonlin. Processes Geophys., 27, 501–518, https://doi.org/10.5194/npg-27-501-2020, https://doi.org/10.5194/npg-27-501-2020, 2020
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The surface transport of heat, nutrients and plastic in the North Atlantic Ocean is organized into large-scale flow structures. We propose a new and simple method to detect such features in ocean drifter data sets by identifying groups of trajectories with similar dynamical behaviour using network theory. We successfully detect well-known regions such as the Subpolar and Subtropical gyres, the Western Boundary Current region and the Caribbean Sea.
René M. van Westen and Henk A. Dijkstra
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-33, https://doi.org/10.5194/os-2020-33, 2020
Revised manuscript not accepted
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In 2016 and 2017, an open-water area emerged within the Antarctic sea-ice pack, the so-called Maud Rise polynya. The opening of the sea ice has been linked to intense winter storms. In this study, we investigate another important contributor to polynya formation by analysing subsurface static instabilities. These static instabilities initiate subsurface convection near Maud Rise. We conclude that apart from winter storms, subsurface convection plays an important role in polynya formation.
Ann Kristin Klose, René M. van Westen, and Henk A. Dijkstra
Ocean Sci., 16, 435–449, https://doi.org/10.5194/os-16-435-2020, https://doi.org/10.5194/os-16-435-2020, 2020
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We give an explanation of the decadal timescale path variations in the Kuroshio Current in the North Pacific based on highly detailed climate
model simulations.
Carine G. van der Boog, Julie D. Pietrzak, Henk A. Dijkstra, Nils Brüggemann, René M. van Westen, Rebecca K. James, Tjeerd J. Bouma, Riccardo E. M. Riva, D. Cornelis Slobbe, Roland Klees, Marcel Zijlema, and Caroline A. Katsman
Ocean Sci., 15, 1419–1437, https://doi.org/10.5194/os-15-1419-2019, https://doi.org/10.5194/os-15-1419-2019, 2019
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We use a model of the Caribbean Sea to study how coastal upwelling along Venezuela impacts the evolution of energetic anticyclonic eddies. We show that the anticyclones grow by the advection of the cold upwelling filaments. These filaments increase the density gradient and vertical shear of the anticyclones. Furthermore, we show that stronger upwelling results in stronger eddies, while model simulations with weaker upwelling contain weaker eddies.
Henk A. Dijkstra
Nonlin. Processes Geophys., 26, 359–369, https://doi.org/10.5194/npg-26-359-2019, https://doi.org/10.5194/npg-26-359-2019, 2019
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I provide a personal view on the role of bifurcation analysis of climate models in the development of a theory of variability in the climate system. By outlining the state of the art of the methodology and by discussing what has been done and what has been learned from a hierarchy of models, I will argue that there are low-order phenomena of climate variability, such as El Niño and the Atlantic Multidecadal Oscillation.
Juan-Manuel Sayol, Henk Dijkstra, and Caroline Katsman
Ocean Sci., 15, 1033–1053, https://doi.org/10.5194/os-15-1033-2019, https://doi.org/10.5194/os-15-1033-2019, 2019
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This work uses high-resolution ocean model data to quantify the sinking of waters in the subpolar North Atlantic. The largest amount of sinking is found at the depth of maximum AMOC at 45° N below the mixed layer depth, and 90 % of the sinking occurs near the boundaries in the first 250 km off the shelf. The characteristics of the sinking (total amount, seasonal variability, and vertical structure) vary largely according to the region considered, revealing a complex picture for the sinking.
Koen G. Helwegen, Claudia E. Wieners, Jason E. Frank, and Henk A. Dijkstra
Earth Syst. Dynam., 10, 453–472, https://doi.org/10.5194/esd-10-453-2019, https://doi.org/10.5194/esd-10-453-2019, 2019
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We use the climate-economy model DICE to perform a cost–benefit analysis of sulfate geoengineering, i.e. producing a thin artificial sulfate haze in the higher atmosphere to reflect some sunlight and cool the Earth.
We find that geoengineering can increase future welfare by reducing global warming, and should be taken seriously as a policy option, but it can only complement, not replace, carbon emission reduction. The best policy is to combine CO2 emission reduction with modest geoengineering.
Martijn Westhoff, Axel Kleidon, Stan Schymanski, Benjamin Dewals, Femke Nijsse, Maik Renner, Henk Dijkstra, Hisashi Ozawa, Hubert Savenije, Han Dolman, Antoon Meesters, and Erwin Zehe
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2019-6, https://doi.org/10.5194/esd-2019-6, 2019
Publication in ESD not foreseen
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Even models relying on physical laws have parameters that need to be measured or estimated. Thermodynamic optimality principles potentially offer a way to reduce the number of estimated parameters by stating that a system evolves to an optimum state. These principles have been applied successfully within the Earth system, but it is often unclear what to optimize and how. In this review paper we identify commonalities between different successful applications as well as some doubtful applications.
Mark M. Dekker, Anna S. von der Heydt, and Henk A. Dijkstra
Earth Syst. Dynam., 9, 1243–1260, https://doi.org/10.5194/esd-9-1243-2018, https://doi.org/10.5194/esd-9-1243-2018, 2018
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We introduce a framework of cascading tipping, i.e. a sequence of abrupt transitions occurring because a transition in one system affects the background conditions of another system. Using bifurcation theory, various types of these events are considered and early warning indicators are suggested. An illustration of such an event is found in a conceptual model, coupling the North Atlantic Ocean with the equatorial Pacific. This demonstrates the possibility of events such as this in nature.
Matthias Aengenheyster, Qing Yi Feng, Frederick van der Ploeg, and Henk A. Dijkstra
Earth Syst. Dynam., 9, 1085–1095, https://doi.org/10.5194/esd-9-1085-2018, https://doi.org/10.5194/esd-9-1085-2018, 2018
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We determine the point of no return (PNR) for climate change, which is the latest year to take action to reduce greenhouse gases to stay, with a certain probability, within thresholds set by the Paris Agreement. For a 67 % probability and a 2 K threshold, the PNR is the year 2035 when the share of renewable energy rises by 2 % per year. We show the impact on the PNR of the speed by which emissions are cut, the risk tolerance, climate uncertainties and the potential for negative emissions.
Femke J. M. M. Nijsse and Henk A. Dijkstra
Earth Syst. Dynam., 9, 999–1012, https://doi.org/10.5194/esd-9-999-2018, https://doi.org/10.5194/esd-9-999-2018, 2018
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State-of-the-art climate models sometimes differ in their prediction of key aspects of climate change. The technique of
emergent constraintsuses observations of current climate to improve those predictions, using relationships between different climate models. Our paper first classifies the different uses of the technique, and continues with proposing a mathematical justification for their use. We also highlight when the application of emergent constraints might give biased predictions.
Peter D. Nooteboom, Qing Yi Feng, Cristóbal López, Emilio Hernández-García, and Henk A. Dijkstra
Earth Syst. Dynam., 9, 969–983, https://doi.org/10.5194/esd-9-969-2018, https://doi.org/10.5194/esd-9-969-2018, 2018
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The prediction of the El Niño phenomenon, an increased sea surface temperature in the eastern Pacific, fascinates people for a long time. El Niño is associated with natural disasters, such as droughts and floods. Current methods can make a reliable prediction of this phenomenon up to 6 months ahead. However, this article presents a method which combines network theory and machine learning which predicts El Niño up to 1 year ahead.
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.
Inti Pelupessy, Ben van Werkhoven, Arjen van Elteren, Jan Viebahn, Adam Candy, Simon Portegies Zwart, and Henk Dijkstra
Geosci. Model Dev., 10, 3167–3187, https://doi.org/10.5194/gmd-10-3167-2017, https://doi.org/10.5194/gmd-10-3167-2017, 2017
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Researchers from the Netherlands present OMUSE, a software package
developed from core technology originating in the astrophysical
community. Using OMUSE, oceanographic and climate researchers can
develop numerical models of the ocean and the interactions between
different parts of the ocean and the atmosphere. This provides a novel
way to investigate, for example, the local effects of climate change on
the ocean. OMUSE is freely available as open-source software.
Brenda C. van Zalinge, Qing Yi Feng, Matthias Aengenheyster, and Henk A. Dijkstra
Earth Syst. Dynam., 8, 707–717, https://doi.org/10.5194/esd-8-707-2017, https://doi.org/10.5194/esd-8-707-2017, 2017
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The increase in atmospheric greenhouse gases (GHGs) is one of the main causes for the increase in global mean surface temperature. There is no good quantitative measure to determine when it is
too lateto start reducing GHGs in order to avoid dangerous anthropogenic interference. We develop a method for determining a so-called point of no return (PNR) for several GHG emission scenarios. The innovative element in this approach is the applicability to high-dimensional climate models.
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.
S.-E. Brunnabend, H. A. Dijkstra, M. A. Kliphuis, H. E. Bal, F. Seinstra, B. van Werkhoven, J. Maassen, and M. van Meersbergen
Ocean Sci., 13, 47–60, https://doi.org/10.5194/os-13-47-2017, https://doi.org/10.5194/os-13-47-2017, 2017
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An important contribution to future changes in regional sea level extremes is due to the changes in intrinsic ocean variability, in particular ocean eddies. Here, we study a scenario of future dynamic sea level (DSL) extremes using a strongly eddying version of the Parallel Ocean Program. Changes in 10-year return time DSL extremes are very inhomogeneous over the globe and are related to changes in ocean currents and corresponding regional shifts in ocean eddy pathways.
Michiel Baatsen, Douwe J. J. van Hinsbergen, Anna S. von der Heydt, Henk A. Dijkstra, Appy Sluijs, Hemmo A. Abels, and Peter K. Bijl
Clim. Past, 12, 1635–1644, https://doi.org/10.5194/cp-12-1635-2016, https://doi.org/10.5194/cp-12-1635-2016, 2016
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One of the major difficulties in modelling palaeoclimate is constricting the boundary conditions, causing significant discrepancies between different studies. Here, a new method is presented to automate much of the process of generating the necessary geographical reconstructions. The latter can be made using various rotational frameworks and topography/bathymetry input, allowing for easy inter-comparisons and the incorporation of the latest insights from geoscientific research.
Zun Yin, Stefan C. Dekker, Bart J. J. M. van den Hurk, and Henk A. Dijkstra
Biogeosciences, 13, 3343–3357, https://doi.org/10.5194/bg-13-3343-2016, https://doi.org/10.5194/bg-13-3343-2016, 2016
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Bimodality is found in aboveground biomass and mean annual shortwave radiation in West Africa, which is a strong evidence of alternative stable states. The condition with low biomass and low radiation is demonstrated under which ecosystem state can shift between savanna and forest states. Moreover, climatic indicators have different prediction confidences to different land cover types. A new method is proposed to predict potential land cover change with a combination of climatic indicators.
Qing Yi Feng, Ruggero Vasile, Marc Segond, Avi Gozolchiani, Yang Wang, Markus Abel, Shilomo Havlin, Armin Bunde, and Henk A. Dijkstra
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2015-273, https://doi.org/10.5194/gmd-2015-273, 2016
Revised manuscript not accepted
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We present the toolbox ClimateLearn to tackle problems in climate prediction using machine learning techniques and climate network analysis. Because spatial temporal information on climate variability can be efficiently represented by complex network measures, such data are considered here as input to the machine-learning algorithms. As an example, the toolbox is applied to the prediction of the occurrence and the development of El Niño in the equatorial Pacific.
H. Ihshaish, A. Tantet, J. C. M. Dijkzeul, and H. A. Dijkstra
Geosci. Model Dev., 8, 3321–3331, https://doi.org/10.5194/gmd-8-3321-2015, https://doi.org/10.5194/gmd-8-3321-2015, 2015
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Par@Graph, a software toolbox to reconstruct and analyze large-scale complex climate networks. It exposes parallelism on distributed-memory computing platforms to enable the construction of massive networks from large number of time series based on the calculation of common statistical similarity measures between them. Providing additionally parallel graph algorithms to enable fast calculation of important and common properties of the generated networks on SMP machines.
L. Hahn-Woernle, H. A. Dijkstra, and H. J. Van der Woerd
Ocean Sci., 10, 993–1011, https://doi.org/10.5194/os-10-993-2014, https://doi.org/10.5194/os-10-993-2014, 2014
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Measured vertical mixing profiles are applied to a 1-D phytoplankton model. Results show that shifts in vertical mixing are able to induce a transition from an upper chlorophyll maximum to a deep one and vice versa. Furthermore, a clear correlation between the surface phytoplankton concentration and mixing-induced nutrient flux is found for nutrient-limited cases. This result suggests that characteristics of the vertical mixing could be determined from the surface phytoplankton concentration.
S.-E. Brunnabend, H. A. Dijkstra, M. A. Kliphuis, B. van Werkhoven, H. E. Bal, F. Seinstra, J. Maassen, and M. van Meersbergen
Ocean Sci., 10, 881–891, https://doi.org/10.5194/os-10-881-2014, https://doi.org/10.5194/os-10-881-2014, 2014
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Regional sea surface height (SSH) changes due to an abrupt weakening of the Atlantic meridional overturning circulation (AMOC) are simulated with a high- and low-resolution model. A rapid decrease of the AMOC in the high-resolution version induces shorter return times of several specific regional and coastal extremes in North Atlantic SSH than in the low-resolution version. This effect is caused by a change in main eddy pathways associated with a change in separation latitude of the Gulf Stream.
Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra
Earth Syst. Dynam., 5, 257–270, https://doi.org/10.5194/esd-5-257-2014, https://doi.org/10.5194/esd-5-257-2014, 2014
D. Le Bars, J. V. Durgadoo, H. A. Dijkstra, A. Biastoch, and W. P. M. De Ruijter
Ocean Sci., 10, 601–609, https://doi.org/10.5194/os-10-601-2014, https://doi.org/10.5194/os-10-601-2014, 2014
Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra
Geosci. Model Dev., 7, 821–845, https://doi.org/10.5194/gmd-7-821-2014, https://doi.org/10.5194/gmd-7-821-2014, 2014
G. Sgubin, S. Pierini, and H. A. Dijkstra
Ocean Sci., 10, 201–213, https://doi.org/10.5194/os-10-201-2014, https://doi.org/10.5194/os-10-201-2014, 2014
A. Tantet and H. A. Dijkstra
Earth Syst. Dynam., 5, 1–14, https://doi.org/10.5194/esd-5-1-2014, https://doi.org/10.5194/esd-5-1-2014, 2014
A. A. Cimatoribus, S. Drijfhout, and H. A. Dijkstra
Ocean Sci. Discuss., https://doi.org/10.5194/osd-10-2461-2013, https://doi.org/10.5194/osd-10-2461-2013, 2013
Preprint withdrawn
A. S. von der Heydt, A. Nnafie, and H. A. Dijkstra
Clim. Past, 7, 903–915, https://doi.org/10.5194/cp-7-903-2011, https://doi.org/10.5194/cp-7-903-2011, 2011
M. Tigchelaar, A. S. von der Heydt, and H. A. Dijkstra
Clim. Past, 7, 235–247, https://doi.org/10.5194/cp-7-235-2011, https://doi.org/10.5194/cp-7-235-2011, 2011
J. O. Sewall, R. S. W. van de Wal, K. van der Zwan, C. van Oosterhout, H. A. Dijkstra, and C. R. Scotese
Clim. Past, 3, 647–657, https://doi.org/10.5194/cp-3-647-2007, https://doi.org/10.5194/cp-3-647-2007, 2007
Related subject area
Subject: Predictability, probabilistic forecasts, data assimilation, inverse problems | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere | Techniques: Simulation
Bridging Data Assimilation and Control: Ensemble Model Predictive Control for High-Dimensional Nonlinear Systems
Evaluation of Effectiveness of Intervention Strategy in Control Simulation Experiment through Comparison with Model Predictive Control
Simulation and Data Assimilation in an Idealized Coupled Atmosphere-Ocean-Sea Ice Floe Model with Cloud Effects
A comparison of two nonlinear data assimilation methods
On Process-Oriented Conditional Targeted Covariance Inflation (TCI) for 3D-Volume Radar Data Assimilation
Leading the Lorenz 63 system toward the prescribed regime by model predictive control coupled with data assimilation
Quantum data assimilation: a new approach to solving data assimilation on quantum annealers
Computation of covariant lyapunov vectors using data assimilation
Comparative study of strongly and weakly coupled data assimilation with a global land–atmosphere coupled model
Reducing manipulations in a control simulation experiment based on instability vectors with the Lorenz-63 model
Control simulation experiments of extreme events with the Lorenz-96 model
A range of outcomes: the combined effects of internal variability and anthropogenic forcing on regional climate trends over Europe
Using a hybrid optimal interpolation–ensemble Kalman filter for the Canadian Precipitation Analysis
Control simulation experiment with Lorenz's butterfly attractor
Reduced non-Gaussianity by 30 s rapid update in convective-scale numerical weather prediction
A study of capturing Atlantic meridional overturning circulation (AMOC) regime transition through observation-constrained model parameters
Fast hybrid tempered ensemble transform filter formulation for Bayesian elliptical problems via Sinkhorn approximation
Simulating model uncertainty of subgrid-scale processes by sampling model errors at convective scales
Data-driven versus self-similar parameterizations for stochastic advection by Lie transport and location uncertainty
Generalization properties of feed-forward neural networks trained on Lorenz systems
Kenta Kurosawa, Atsushi Okazaki, Fumitoshi Kawasaki, and Shunji Kotsuki
EGUsphere, https://doi.org/10.5194/egusphere-2025-595, https://doi.org/10.5194/egusphere-2025-595, 2025
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We propose Ensemble Model Predictive Control (EnMPC), a novel method that improves control of complex systems like weather by integrating control theory with data assimilation. Unlike traditional methods, which are computationally expensive, EnMPC uses ensemble simulations to efficiently handle uncertainties and optimize solutions. This approach reduces computational cost while maintaining accuracy, making it a promising step toward real-world applications in dynamic system control.
Rikuto Nagai, Yang Bai, Masaki Ogura, Shunji Kotsuki, and Naoki Wakamiya
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npg-2024-26, https://doi.org/10.5194/npg-2024-26, 2024
Revised manuscript accepted for NPG
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Controlling chaotic systems is a key step toward weather control. The Control Simulation Experiment (CSE) modifies weather systems using small perturbations, as shown in studies with the Lorenz-63 model. However, the effectiveness of CSE compared to other methods is unclear. This study evaluates CSE against Model Predictive Control (MPC). Simulations reveal that MPC achieves higher success rates with less effort under certain conditions, linking control theory and atmospheric science.
Changhong Mou, Samuel N. Stechmann, and Nan Chen
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npg-2024-21, https://doi.org/10.5194/npg-2024-21, 2024
Revised manuscript accepted for NPG
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Sea ice is crucial in the climate system, especially in the Marginal Ice Zone (MIZ). As the MIZ expands, understanding its dynamics is essential for predicting climate impacts. This paper addresses the largely overlooked role of clouds, developing an idealized atmosphere-ocean-ice model with cloud effects, tackling both simulation and data assimilation. The results imply the potential of integrating idealized models with data assimilation for understanding of Arctic dynamics and predictions.
Vivian A. Montiforte, Hans E. Ngodock, and Innocent Souopgui
Nonlin. Processes Geophys., 31, 463–476, https://doi.org/10.5194/npg-31-463-2024, https://doi.org/10.5194/npg-31-463-2024, 2024
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Advanced data assimilation methods are complex and computationally expensive. We compare two simpler methods, diffusive back-and-forth nudging and concave–convex nonlinearity, which account for change over time with the potential of providing accurate results with a reduced computational cost. We evaluate the accuracy of the two methods by implementing them within simple chaotic models. We conclude that the length and frequency of observations impact which method is better suited for a problem.
Klaus Vobig, Roland Potthast, and Klaus Stephan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2876, https://doi.org/10.5194/egusphere-2024-2876, 2024
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We present a novel approach to targeted covariance inflation (TCI) which aims to improve the assimilation of 3D radar reflectivity and, eventually, the short-term forecast of reflectivity and precipitation.
Using an operational numerical weather prediction framework, our numerical results show that TCI makes the system accurately generate new reflectivity cells and significantly improves the fractional skill score of forecasts over lead times of up to six hours by up to 10 %.
Fumitoshi Kawasaki and Shunji Kotsuki
Nonlin. Processes Geophys., 31, 319–333, https://doi.org/10.5194/npg-31-319-2024, https://doi.org/10.5194/npg-31-319-2024, 2024
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Recently, scientists have been looking into ways to control the weather to lead to a desirable direction for mitigating weather-induced disasters caused by torrential rainfall and typhoons. This study proposes using the model predictive control (MPC), an advanced control method, to control a chaotic system. Through numerical experiments using a low-dimensional chaotic system, we demonstrate that the system can be successfully controlled with shorter forecasts compared to previous studies.
Shunji Kotsuki, Fumitoshi Kawasaki, and Masanao Ohashi
Nonlin. Processes Geophys., 31, 237–245, https://doi.org/10.5194/npg-31-237-2024, https://doi.org/10.5194/npg-31-237-2024, 2024
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In Earth science, data assimilation plays an important role in integrating real-world observations with numerical simulations for improving subsequent predictions. To overcome the time-consuming computations of conventional data assimilation methods, this paper proposes using quantum annealing machines. Using the D-Wave quantum annealer, the proposed method found solutions with comparable accuracy to conventional approaches and significantly reduced computational time.
Shashank Kumar Roy and Amit Apte
EGUsphere, https://doi.org/10.5194/egusphere-2023-2168, https://doi.org/10.5194/egusphere-2023-2168, 2023
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We focus on the computation of Lyapunov vectors for dynamical systems using partial and noisy observations using data assimilation. We study how the errors in the approximated LVs are implicitly affected by the errors in the estimated trajectory. Our results reveal the difference in sensitivity of the individual vectors in low and high dimensions. Additionally, we find that the subspaces defined by the LVs computed from the approximate trajectory are less sensitive than the individual vectors.
Kenta Kurosawa, Shunji Kotsuki, and Takemasa Miyoshi
Nonlin. Processes Geophys., 30, 457–479, https://doi.org/10.5194/npg-30-457-2023, https://doi.org/10.5194/npg-30-457-2023, 2023
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This study aimed to enhance weather and hydrological forecasts by integrating soil moisture data into a global weather model. By assimilating atmospheric observations and soil moisture data, the accuracy of forecasts was improved, and certain biases were reduced. The method was found to be particularly beneficial in areas like the Sahel and equatorial Africa, where precipitation patterns vary seasonally. This new approach has the potential to improve the precision of weather predictions.
Mao Ouyang, Keita Tokuda, and Shunji Kotsuki
Nonlin. Processes Geophys., 30, 183–193, https://doi.org/10.5194/npg-30-183-2023, https://doi.org/10.5194/npg-30-183-2023, 2023
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This research found that weather control would change the chaotic behavior of an atmospheric model. We proposed to introduce chaos theory in the weather control. Experimental results demonstrated that the proposed approach reduced the manipulations, including the control times and magnitudes, which throw light on the weather control in a real atmospheric model.
Qiwen Sun, Takemasa Miyoshi, and Serge Richard
Nonlin. Processes Geophys., 30, 117–128, https://doi.org/10.5194/npg-30-117-2023, https://doi.org/10.5194/npg-30-117-2023, 2023
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This paper is a follow-up of a work by Miyoshi and Sun which was published in NPG Letters in 2022. The control simulation experiment is applied to the Lorenz-96 model for avoiding extreme events. The results show that extreme events of this partially and imperfectly observed chaotic system can be avoided by applying pre-designed small perturbations. These investigations may be extended to more realistic numerical weather prediction models.
Clara Deser and Adam S. Phillips
Nonlin. Processes Geophys., 30, 63–84, https://doi.org/10.5194/npg-30-63-2023, https://doi.org/10.5194/npg-30-63-2023, 2023
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Past and future climate change at regional scales is a result of both human influences and natural (internal) variability. Here, we provide an overview of recent advances in climate modeling and physical understanding that has led to new insights into their respective roles, illustrated with original results for the European climate. Our findings highlight the confounding role of internal variability in attribution, climate model evaluation, and accuracy of future projections.
Dikraa Khedhaouiria, Stéphane Bélair, Vincent Fortin, Guy Roy, and Franck Lespinas
Nonlin. Processes Geophys., 29, 329–344, https://doi.org/10.5194/npg-29-329-2022, https://doi.org/10.5194/npg-29-329-2022, 2022
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This study introduces a well-known use of hybrid methods in data assimilation (DA) algorithms that has not yet been explored for precipitation analyses. Our approach combined an ensemble-based DA approach with an existing deterministically based DA. Both DA scheme families have desirable aspects that can be leveraged if combined. The DA hybrid method showed better precipitation analyses in regions with a low rate of assimilated surface observations, which is typically the case in winter.
Takemasa Miyoshi and Qiwen Sun
Nonlin. Processes Geophys., 29, 133–139, https://doi.org/10.5194/npg-29-133-2022, https://doi.org/10.5194/npg-29-133-2022, 2022
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The weather is chaotic and hard to predict, but the chaos implies an effective control where a small control signal grows rapidly to make a big difference. This study proposes a control simulation experiment where we apply a small signal to control
naturein a computational simulation. Idealized experiments with a low-order chaotic system show successful results by small control signals of only 3 % of the observation error. This is the first step toward realistic weather simulations.
Juan Ruiz, Guo-Yuan Lien, Keiichi Kondo, Shigenori Otsuka, and Takemasa Miyoshi
Nonlin. Processes Geophys., 28, 615–626, https://doi.org/10.5194/npg-28-615-2021, https://doi.org/10.5194/npg-28-615-2021, 2021
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Effective use of observations with numerical weather prediction models, also known as data assimilation, is a key part of weather forecasting systems. For precise prediction at the scales of thunderstorms, fast nonlinear processes pose a grand challenge because most data assimilation systems are based on linear processes and normal distribution errors. We investigate how, every 30 s, weather radar observations can help reduce the effect of nonlinear processes and nonnormal distributions.
Zhao Liu, Shaoqing Zhang, Yang Shen, Yuping Guan, and Xiong Deng
Nonlin. Processes Geophys., 28, 481–500, https://doi.org/10.5194/npg-28-481-2021, https://doi.org/10.5194/npg-28-481-2021, 2021
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A general methodology is introduced to capture regime transitions of the Atlantic meridional overturning circulation (AMOC). The assimilation models with different parameters simulate different paths for the AMOC to switch between equilibrium states. Constraining model parameters with observations can significantly mitigate the model deviations, thus capturing AMOC regime transitions. This simple model study serves as a guideline for improving coupled general circulation models.
Sangeetika Ruchi, Svetlana Dubinkina, and Jana de Wiljes
Nonlin. Processes Geophys., 28, 23–41, https://doi.org/10.5194/npg-28-23-2021, https://doi.org/10.5194/npg-28-23-2021, 2021
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To infer information of an unknown quantity that helps to understand an associated system better and to predict future outcomes, observations and a physical model that connects the data points to the unknown parameter are typically used as information sources. Yet this problem is often very challenging due to the fact that the unknown is generally high dimensional, the data are sparse and the model can be non-linear. We propose a novel approach to address these challenges.
Michiel Van Ginderachter, Daan Degrauwe, Stéphane Vannitsem, and Piet Termonia
Nonlin. Processes Geophys., 27, 187–207, https://doi.org/10.5194/npg-27-187-2020, https://doi.org/10.5194/npg-27-187-2020, 2020
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A generic methodology is developed to estimate the model error and simulate the model uncertainty related to a specific physical process. The method estimates the model error by comparing two different representations of the physical process in otherwise identical models. The found model error can then be used to perturb the model and simulate the model uncertainty. When applying this methodology to deep convection an improvement in the probabilistic skill of the ensemble forecast is found.
Valentin Resseguier, Wei Pan, and Baylor Fox-Kemper
Nonlin. Processes Geophys., 27, 209–234, https://doi.org/10.5194/npg-27-209-2020, https://doi.org/10.5194/npg-27-209-2020, 2020
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Geophysical flows span a broader range of temporal and spatial scales than can be resolved numerically. One way to alleviate the ensuing numerical errors is to combine simulations with measurements, taking account of the accuracies of these two sources of information. Here we quantify the distribution of numerical simulation errors without relying on high-resolution numerical simulations. Specifically, small-scale random vortices are added to simulations while conserving energy or circulation.
Sebastian Scher and Gabriele Messori
Nonlin. Processes Geophys., 26, 381–399, https://doi.org/10.5194/npg-26-381-2019, https://doi.org/10.5194/npg-26-381-2019, 2019
Short summary
Short summary
Neural networks are a technique that is widely used to predict the time evolution of physical systems. For this the past evolution of the system is shown to the neural network – it is
trained– and then can be used to predict the evolution in the future. We show some limitations in this approach for certain systems that are important to consider when using neural networks for climate- and weather-related applications.
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Short summary
Artificial intelligence (AI) has recently shown promising results in ENSO (El Niño–Southern Oscillation) forecasting, outperforming traditional models. Yet AI models deliver accurate predictions without showing the underlying mechanisms. Our study examines a specific AI model, the reservoir computer (RC). Our results show that the RC is less sensitive to initial perturbations than the traditional Zebiak–Cane (ZC) model. This reduced sensitivity can explain the RC's superior skills.
Artificial intelligence (AI) has recently shown promising results in ENSO (El Niño–Southern...
