Articles | Volume 31, issue 2
https://doi.org/10.5194/npg-31-185-2024
© 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/npg-31-185-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article: Interdisciplinary perspectives on climate sciences – highlighting past and current scientific achievements
Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
Tommaso Alberti
Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
Lesley De Cruz
Scientific Service Observations, Royal Meteorological Institute of Belgium, Brussels, Belgium
Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Brussels, Belgium
Christian L. E. Franzke
Center for Climate Physics, Institute for Basic Science, Busan, Republic of Korea
Pusan National University, Busan, Republic of Korea
Valerio Lembo
Institute of Atmospheric Sciences and Climate, National Research Council of Italy (CNR-ISAC), Bologna, Italy
Related authors
Valerio Lembo, Gabriele Messori, Davide Faranda, Vera Melinda Galfi, Rune Grand Graversen, and Flavio Emanuele Pons
EGUsphere, https://doi.org/10.5194/egusphere-2025-2189, https://doi.org/10.5194/egusphere-2025-2189, 2025
Short summary
Short summary
Hemispheric heatwaves have fundamental implications for ecosystems and societies. They are studied together with the large-scale atmospheric dynamics, through the lens of the poleward heat transports by planetary-scale waves. Extremely weak transports of heat towards the Poles are found to be associated with hemispheric heatwaves in the Northern Hemisphere mid-latitudes. Therefore, we conclude that heat transports are a clear indicator, and possibly a precursor of hemispehric heatwaves.
Valerio Lembo, Federico Fabiano, Vera Melinda Galfi, Rune Grand Graversen, Valerio Lucarini, and Gabriele Messori
Weather Clim. Dynam., 3, 1037–1062, https://doi.org/10.5194/wcd-3-1037-2022, https://doi.org/10.5194/wcd-3-1037-2022, 2022
Short summary
Short summary
Eddies in mid-latitudes characterize the exchange of heat between the tropics and the poles. This exchange is largely uneven, with a few extreme events bearing most of the heat transported across latitudes in a season. It is thus important to understand what the dynamical mechanisms are behind these events. Here, we identify recurrent weather regime patterns associated with extreme transports, and we identify scales of mid-latitudinal eddies that are mostly responsible for the transport.
Sun-Seon Lee, Sahil Sharma, Nan Rosenbloom, Keith B. Rodgers, Ji-Eun Kim, Eun Young Kwon, Christian L. E. Franzke, In-Won Kim, Mohanan Geethalekshmi Sreeush, and Karl Stein
Earth Syst. Dynam., 16, 1427–1451, https://doi.org/10.5194/esd-16-1427-2025, https://doi.org/10.5194/esd-16-1427-2025, 2025
Short summary
Short summary
A new 10-member ensemble simulation with the state-of-the-art Earth system model was employed to study the long-term climate response to sustained greenhouse warming through to the year 2500. The findings show that the projected changes in the forced mean state and internal variability during 2101–2500 differ substantially from the 21st-century projections, emphasizing the importance of multi-century perspectives for understanding future climate change and informing effective mitigation strategies.
Kerry Emanuel, Tommaso Alberti, Stella Bourdin, Suzana J. Camargo, Davide Faranda, Emmanouil Flaounas, Juan Jesus Gonzalez-Aleman, Chia-Ying Lee, Mario Marcello Miglietta, Claudia Pasquero, Alice Portal, Hamish Ramsay, Marco Reale, and Romualdo Romero
Weather Clim. Dynam., 6, 901–926, https://doi.org/10.5194/wcd-6-901-2025, https://doi.org/10.5194/wcd-6-901-2025, 2025
Short summary
Short summary
Storms strongly resembling hurricanes are sometimes observed to form well outside the tropics, even in polar latitudes. They behave capriciously, developing very rapidly and then dying just as quickly. We show that strong dynamical processes in the atmosphere can sometimes cause it to become much colder locally than the underlying ocean, creating the conditions for hurricanes to form but only over small areas and for short times. We call the resulting storms "CYCLOPs".
Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian L. E. Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Dae-Won Kim, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana N. Loza, Wonsun Park, Woncheol Roh, Dmitry V. Sein, Sahil Sharma, Dmitry Sidorenko, Jun-Hyeok Son, Malte F. Stuecker, Qiang Wang, Gyuseok Yi, Martina Zapponini, Thomas Jung, and Axel Timmermann
Earth Syst. Dynam., 16, 1103–1134, https://doi.org/10.5194/esd-16-1103-2025, https://doi.org/10.5194/esd-16-1103-2025, 2025
Short summary
Short summary
Based on a series of storm-resolving greenhouse warming simulations conducted with the AWI-CM3 model at 9 km global atmosphere and 4–25 km ocean resolution, we present new projections of regional climate change, modes of climate variability, and extreme events. The 10-year-long high-resolution simulations for the 2000s, 2030s, 2060s, and 2090s were initialized from a coarser-resolution transient run (31 km atmosphere) which follows the SSP5-8.5 greenhouse gas emission scenario from 1950–2100 CE.
Forrest M. Hoffman, Birgit Hassler, Ranjini Swaminathan, Jared Lewis, Bouwe Andela, Nathaniel Collier, Dóra Hegedűs, Jiwoo Lee, Charlotte Pascoe, Mika Pflüger, Martina Stockhause, Paul Ullrich, Min Xu, Lisa Bock, Felicity Chun, Bettina K. Gier, Douglas I. Kelley, Axel Lauer, Julien Lenhardt, Manuel Schlund, Mohanan G. Sreeush, Katja Weigel, Ed Blockley, Rebecca Beadling, Romain Beucher, Demiso D. Dugassa, Valerio Lembo, Jianhua Lu, Swen Brands, Jerry Tjiputra, Elizaveta Malinina, Brian Mederios, Enrico Scoccimarro, Jeremy Walton, Philip Kershaw, André L. Marquez, Malcolm J. Roberts, Eleanor O’Rourke, Elisabeth Dingley, Briony Turner, Helene Hewitt, and John P. Dunne
EGUsphere, https://doi.org/10.5194/egusphere-2025-2685, https://doi.org/10.5194/egusphere-2025-2685, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
As Earth system models become more complex, rapid and comprehensive evaluation through comparison with observational data is necessary. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require fast analysis. This paper describes a new Rapid Evaluation Framework (REF) that was developed for the Assessment Fast Track that will be run at the Earth System Grid Federation (ESGF) to inform the community about the performance of models.
Luc Hallali, Eirik Myrvoll-Nilsen, and Christian L. E. Franzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-2461, https://doi.org/10.5194/egusphere-2025-2461, 2025
Short summary
Short summary
We present an alternative statistical methodology to detect whether the Atlantic Ocean’s circulation system is approaching a tipping point. Our approach separates natural variability from real early warning signals of tipping, reducing false alarms. When applied to proxy of Atlantic Ocean’s circulation strength , we found significant signs that the system is ongoing destabilization . This suggests it may be approaching a tipping point, which could have major impacts on global climate patterns.
Valerio Lembo, Gabriele Messori, Davide Faranda, Vera Melinda Galfi, Rune Grand Graversen, and Flavio Emanuele Pons
EGUsphere, https://doi.org/10.5194/egusphere-2025-2189, https://doi.org/10.5194/egusphere-2025-2189, 2025
Short summary
Short summary
Hemispheric heatwaves have fundamental implications for ecosystems and societies. They are studied together with the large-scale atmospheric dynamics, through the lens of the poleward heat transports by planetary-scale waves. Extremely weak transports of heat towards the Poles are found to be associated with hemispheric heatwaves in the Northern Hemisphere mid-latitudes. Therefore, we conclude that heat transports are a clear indicator, and possibly a precursor of hemispehric heatwaves.
Lia Rapella, Tommaso Alberti, Davide Faranda, and Philippe Drobinski
EGUsphere, https://doi.org/10.5194/egusphere-2025-1219, https://doi.org/10.5194/egusphere-2025-1219, 2025
Short summary
Short summary
Extreme weather events pose increasing challenges for aviation, including flight disruptions and infrastructure damage. This study examines the influence of anthropogenic climate change on four recent major storms across Europe, the USA, and East Asia. Our research underscores the growing intensity of extreme storms, driven by human-induced climate change, underscoring the need to adapt aviation strategies to an increasingly hazardous environment.
Anouk Dierickx, Wout Dewettinck, Bert Van Schaeybroeck, Lesley De Cruz, Steven Caluwaerts, Piet Termonia, and Hans Van de Vyver
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-30, https://doi.org/10.5194/essd-2025-30, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
This study introduces the EURO-SUPREME dataset consisting of extreme precipitation events selected from a large ensemble of climate models over Europe. The dataset contains information on extreme precipitation events with a precipitation duration of 1 hour to 72 hours that can lead to flooding, high mortality rates and infrastructure damage. We highlight the usefulness of the dataset as a benchmark for improving high-resolution climate models for risk assessment of future extreme floods.
Davide Faranda, Gabriele Messori, Erika Coppola, Tommaso Alberti, Mathieu Vrac, Flavio Pons, Pascal Yiou, Marion Saint Lu, Andreia N. S. Hisi, Patrick Brockmann, Stavros Dafis, Gianmarco Mengaldo, and Robert Vautard
Weather Clim. Dynam., 5, 959–983, https://doi.org/10.5194/wcd-5-959-2024, https://doi.org/10.5194/wcd-5-959-2024, 2024
Short summary
Short summary
We introduce ClimaMeter, a tool offering real-time insights into extreme-weather events. Our tool unveils how climate change and natural variability affect these events, affecting communities worldwide. Our research equips policymakers and the public with essential knowledge, fostering informed decisions and enhancing climate resilience. We analysed two distinct events, showcasing ClimaMeter's global relevance.
Federico Fabiano, Paolo Davini, Virna L. Meccia, Giuseppe Zappa, Alessio Bellucci, Valerio Lembo, Katinka Bellomo, and Susanna Corti
Earth Syst. Dynam., 15, 527–546, https://doi.org/10.5194/esd-15-527-2024, https://doi.org/10.5194/esd-15-527-2024, 2024
Short summary
Short summary
Even after the concentration of greenhouse gases is stabilized, the climate will continue to adapt, seeking a new equilibrium. We study this long-term stabilization through a set of 1000-year simulations, obtained by suddenly "freezing" the atmospheric composition at different levels. If frozen at the current state, global warming surpasses 3° in the long term with our model. We then study how climate impacts will change after various centuries and how the deep ocean will warm.
Daniel Gliksman, Paul Averbeck, Nico Becker, Barry Gardiner, Valeri Goldberg, Jens Grieger, Dörthe Handorf, Karsten Haustein, Alexia Karwat, Florian Knutzen, Hilke S. Lentink, Rike Lorenz, Deborah Niermann, Joaquim G. Pinto, Ronald Queck, Astrid Ziemann, and Christian L. E. Franzke
Nat. Hazards Earth Syst. Sci., 23, 2171–2201, https://doi.org/10.5194/nhess-23-2171-2023, https://doi.org/10.5194/nhess-23-2171-2023, 2023
Short summary
Short summary
Wind and storms are a major natural hazard and can cause severe economic damage and cost human lives. Hence, it is important to gauge the potential impact of using indices, which potentially enable us to estimate likely impacts of storms or other wind events. Here, we review basic aspects of wind and storm generation and provide an extensive overview of wind impacts and available indices. This is also important to better prepare for future climate change and corresponding changes to winds.
Valerio Lembo, Federico Fabiano, Vera Melinda Galfi, Rune Grand Graversen, Valerio Lucarini, and Gabriele Messori
Weather Clim. Dynam., 3, 1037–1062, https://doi.org/10.5194/wcd-3-1037-2022, https://doi.org/10.5194/wcd-3-1037-2022, 2022
Short summary
Short summary
Eddies in mid-latitudes characterize the exchange of heat between the tropics and the poles. This exchange is largely uneven, with a few extreme events bearing most of the heat transported across latitudes in a season. It is thus important to understand what the dynamical mechanisms are behind these events. Here, we identify recurrent weather regime patterns associated with extreme transports, and we identify scales of mid-latitudinal eddies that are mostly responsible for the transport.
Nicolas Ghilain, Stéphane Vannitsem, Quentin Dalaiden, Hugues Goosse, Lesley De Cruz, and Wenguang Wei
Earth Syst. Sci. Data, 14, 1901–1916, https://doi.org/10.5194/essd-14-1901-2022, https://doi.org/10.5194/essd-14-1901-2022, 2022
Short summary
Short summary
Modeling the climate at high resolution is crucial to represent the snowfall accumulation over the complex orography of the Antarctic coast. While ice cores provide a view constrained spatially but over centuries, climate models can give insight into its spatial distribution, either at high resolution over a short period or vice versa. We downscaled snowfall accumulation from climate model historical simulations (1850–present day) over Dronning Maud Land at 5.5 km using a statistical method.
Herminia Torelló-Sentelles and Christian L. E. Franzke
Hydrol. Earth Syst. Sci., 26, 1821–1844, https://doi.org/10.5194/hess-26-1821-2022, https://doi.org/10.5194/hess-26-1821-2022, 2022
Short summary
Short summary
Drought affects many regions worldwide, and future climate projections imply that drought severity and frequency will increase. Hence, the impacts of drought on the environment and society will also increase considerably. Monitoring and early warning systems for drought rely on several indicators; however, assessments on how these indicators are linked to impacts are still lacking. Our results show that meteorological indices are best linked to impact occurrences.
Tommaso Alberti, Reik V. Donner, and Stéphane Vannitsem
Earth Syst. Dynam., 12, 837–855, https://doi.org/10.5194/esd-12-837-2021, https://doi.org/10.5194/esd-12-837-2021, 2021
Short summary
Short summary
We provide a novel approach to diagnose the strength of the ocean–atmosphere coupling by using both a reduced order model and reanalysis data. Our findings suggest the ocean–atmosphere dynamics presents a rich variety of features, moving from a chaotic to a coherent coupled dynamics, mainly attributed to the atmosphere and only marginally to the ocean. Our observations suggest further investigations in characterizing the occurrence and spatial dependency of the ocean–atmosphere coupling.
Sara Top, Lola Kotova, Lesley De Cruz, Svetlana Aniskevich, Leonid Bobylev, Rozemien De Troch, Natalia Gnatiuk, Anne Gobin, Rafiq Hamdi, Arne Kriegsmann, Armelle Reca Remedio, Abdulla Sakalli, Hans Van De Vyver, Bert Van Schaeybroeck, Viesturs Zandersons, Philippe De Maeyer, Piet Termonia, and Steven Caluwaerts
Geosci. Model Dev., 14, 1267–1293, https://doi.org/10.5194/gmd-14-1267-2021, https://doi.org/10.5194/gmd-14-1267-2021, 2021
Short summary
Short summary
Detailed climate data are needed to assess the impact of climate change on human and natural systems. The performance of two high-resolution regional climate models, ALARO-0 and REMO2015, was investigated over central Asia, a vulnerable region where detailed climate information is scarce. In certain subregions the produced climate data are suitable for impact studies, but bias adjustment is required for subregions where significant biases have been identified.
Thomas Önskog, Christian L. E. Franzke, and Abdel Hannachi
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 141–157, https://doi.org/10.5194/ascmo-6-141-2020, https://doi.org/10.5194/ascmo-6-141-2020, 2020
Short summary
Short summary
The North Atlantic Oscillation (NAO) has a significant impact on seasonal climate and surface weather conditions throughout Europe, North America and the North Atlantic. In this paper, we study a number of linear and nonlinear models for a station-based time series of the daily winter NAO. We find that a class of nonlinear models, including both short and long lags, excellently reproduce the characteristic statistical properties of the NAO. These models can hence be used to simulate the NAO.
Cited articles
Alberti, T., Daviaud, F., Donner, R. V., Dubrulle, B., Faranda, D., and Lucarini, V.: Chameleon attractors in turbulent flows, Chaos, Solitons & Fractals, 168, 113195, https://doi.org/10.1016/j.chaos.2023.113195, 2023. a
Benzi, R., Parisi, G., Sutera, A., and Vulpiani, A.: Stochastic resonance in climatic change, Tellus, 34, 10–16, 1982. a
Bohémier, K. A.: Analysis for Science Librarians of the 2021 Nobel Prize in Physics: Climate, Spin Glass, and Complex Systems, Sci. Tech. Libr., 41, 1–23, 2022. a
Charó, G. D., Chekroun, M. D., Sciamarella, D., and Ghil, M.: Noise-driven topological changes in chaotic dynamics, Chaos, 31 10, 103115, https://doi.org/10.1063/5.0059461, 2021. a
Chekroun, M. D., Simonnet, E., and Ghil, M.: Stochastic climate dynamics: Random attractors and time-dependent invariant measures, Physica D, 240, 1685–1700, 2011. a
Crauel, H. and Flandoli, F.: Attractors for random dynamical systems, Probab. Theory Rel., 100, 365–393, 1994. a
De Cruz, L., Demaeyer, J., and Vannitsem, S.: The Modular Arbitrary-Order Ocean-Atmosphere Model: MAOOAM v1.0, Geosci. Model Dev., 9, 2793–2808, https://doi.org/10.5194/gmd-9-2793-2016, 2016. a
Deser, C. and Phillips, A. S.: A range of outcomes: the combined effects of internal variability and anthropogenic forcing on regional climate trends over Europe, Nonlin. Processes Geophys., 30, 63–84, https://doi.org/10.5194/npg-30-63-2023, 2023. a
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate change projections: the role of internal variability, Clim. Dynam., 38, 527–546, 2012. a
Deser, C., Lehner, F., Rodgers, K. B., Ault, T., Delworth, T. L., DiNezio, P. N., Fiore, A., Frankignoul, C., Fyfe, J. C., Horton, D. E., Kay, J. E., Knutti, R., Lovenduski, N. S., Marotzke, J., McKinnon, K. A., Minobe, S., Randerson, J., Screen, J. A., Simpson, I. R., and Ting, M.: Insights from Earth system model initial-condition large ensembles and future prospects, Nat. Clim. Change, 10, 277–286, 2020. a
Dijkstra, H. A.: Nonlinear climate dynamics, Cambridge University Press, https://doi.org/10.1017/CBO9781139034135, 2013. a
Dorrington, J. and Palmer, T.: On the interaction of stochastic forcing and regime dynamics, Nonlin. Processes Geophys., 30, 49–62, https://doi.org/10.5194/npg-30-49-2023, 2023. a
Drótos, G., Bódai, T., and Tél, T.: Probabilistic Concepts in a Changing Climate: A Snapshot Attractor Picture, J. Climate, 28, 3275–3288, 2015. a
Dubrulle, B.: Multi-Fractality, Universality and Singularity in Turbulence, Fractal and Fractional, 6, 613, https://doi.org/10.3390/fractalfract6100613, 2022. a
Dubrulle, B. and Gibbon, J. D.: A correspondence between the multifractal model of turbulence and the Navier-Stokes equations, Philos.T. R. Soc.Lond., 380, 20210092, https://doi.org/10.1098/rsta.2021.0092, 2022. a
Dubrulle, B., Daviaud, F., Faranda, D., Marié, L., and Saint-Michel, B.: How many modes are needed to predict climate bifurcations? Lessons from an experiment, Nonlin. Processes Geophys., 29, 17–35, https://doi.org/10.5194/npg-29-17-2022, 2022. a
Franzke, C. L. and O'Kane, T. J.: Nonlinear and stochastic climate dynamics, Cambridge University Press, https://doi.org/10.1017/9781316339251, 2017. a
Franzke, C. L., Blender, R., O'Kane, T. J., and Lembo, V.: Stochastic Methods and Complexity Science in Climate Research and Modeling, Front. Phys., 521, 931596, https://doi.org/10.3389/fphy.2022.931596, 2022. a, b, c
Frisch, U.: Turbulence: the legacy of AN Kolmogorov, Cambridge university press, https://doi.org/10.1017/CBO9781139170666, 1995. a
Gálfi, V. M., Lucarini, V., Ragone, F., and Wouters, J.: Applications of large deviation theory in geophysical fluid dynamics and climate science, La Rivista del Nuovo Cimento, 44, 291–363, https://doi.org/10.1007/s40766-021-00020-z, 2021. a
Ghil, M. and Lucarini, V.: The physics of climate variability and climate change, Rev. Mod. Phys., 92, 035002, https://doi.org/10.1103/RevModPhys.92.035002, 2020. a
Ghil, M. and Sciamarella, D.: Review article: Dynamical systems, algebraic topology and the climate sciences, Nonlin. Processes Geophys., 30, 399–434, https://doi.org/10.5194/npg-30-399-2023, 2023. a
Ghil, M., Chekroun, M. D., and Simonnet, E.: Climate dynamics and fluid mechanics: Natural variability and related uncertainties, Phys. D, 237, 2111–2126, 2008. a
Golden, K. M., Bennetts, L. G., Cherkaev, E., Eisenman, I., Feltham, D., Horvat, C., Hunke, E., Jones, C., Perovich, D. K., Ponte-Castañeda, P., Strong, C., Sulsky, D., and Wells, A. J.: Modeling sea ice, Not. Am. Math. Soc., 67, 1535–1555, https://doi.org/10.1090/noti2171, 2020a. a
Golden, K. M., Ma, Y., Strong, C., and Sudakov, I.: From Magnets to Melt Ponds, SIAM News, 53, 5–7, 2020b. a
Golden, K. M., Murphy, N. B., Hallman, D., and Cherkaev, E.: Stieltjes functions and spectral analysis in the physics of sea ice, Nonlin. Processes Geophys., 30, 527–552, https://doi.org/10.5194/npg-30-527-2023, 2023. a
Hasselmann, K.: Stochastic climate models part I. Theory, Tellus, 28, 473–485, 1976. a
Hasselmann, K.: PIPs and POPs: The reduction of complex dynamical systems using principal interaction and oscillation patterns, J. Geophys. Res.-Atmos., 93, 11015–11021, 1988. a
Hasselmann, K.: Optimal fingerprints for the detection of time-dependent climate change, J. Climate, 6, 1957–1971, 1993. a
Hoskins, B. J., McIntyre, M. E., and Robertson, A. W.: On the use and significance of isentropic potential vorticity maps, Q. J. Roy. Meteor. Soc., 111, 877–946, 1985. a
Jona-Lasinio, G.: Review article: Large fluctuations in non-equilibrium physics, Nonlin. Processes Geophys., 30, 253–262, https://doi.org/10.5194/npg-30-253-2023, 2023. a
Kalnay, E., Sluka, T., Yoshida, T., Da, C., and Mote, S.: Review article: Towards strongly coupled ensemble data assimilation with additional improvements from machine learning, Nonlin. Processes Geophys., 30, 217–236, https://doi.org/10.5194/npg-30-217-2023, 2023. a
Kleinschmidt, E.: Grundlagen einer Theorie der tropischen Zyklonen, Archiv für Meteorologie, Geophysik und Bioklimatologie, Serie A, 4, 53–72, 1951. a
Kolmogorov, A. N.: The local structure of turbulence in incompressible viscous fluid for very large Reynolds numbers, Cr Acad. Sci. URSS, 30, 301–305, 1941. a
Kuzzay, D., Saw, E.-W., Martins, F. J., Faranda, D., Foucaut, J.-M., Daviaud, F., and Dubrulle, B.: New method for detecting singularities in experimental incompressible flows, Nonlinearity, 30, 2381, https://doi.org/10.1088/1361-6544/aa6aaf, 2017. a
Laskar, J.: A numerical experiment on the chaotic behaviour of the Solar System, Nature, 338, 237–238, https://doi.org/10.1038/338237a0, 1989. a
Lembo, V., Alberti, T., De Cruz, L., Franzke, C., and Galfi, V. M.: Perspectives on Climate Sciences, https://sites.google.com/view/perspectivesonclimate/materials (last access: 28 March 2024), 2024. a
Li, T.-Y. and Yorke, J. A.: Period Three Implies Chaos, Am. Math. Mon., 82, 985–992, https://doi.org/10.2307/2318254, 1975. a
Lorenz, E. N.: Deterministic Nonperiodic Flow, J. Atmos. Sci., 20, 130–141, https://doi.org/10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2, 1963. a
Lovejoy, S.: Weather, Macroweather, and the Climate: Our Random Yet Predictable Atmosphere, Oxford University Press, https://doi.org/10.1093/oso/9780190864217.001.0001, 2019. a
Lovejoy, S.: Review article: Scaling, dynamical regimes, and stratification. How long does weather last? How big is a cloud?, Nonlin. Processes Geophys., 30, 311–374, https://doi.org/10.5194/npg-30-311-2023, 2023. a
Mandelbrot, B.: Fractals, Freeman San Francisco, ISBN-13 978-0716704737, 1977. 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, 2021. a
Penland, C.: Random forcing and forecasting using principal oscillation pattern analysis, Mon. Weather Rev., 117, 2165–2185, 1989. a
Pierrehumbert, R. T.: Thermostats, radiator fins, and the local runaway greenhouse, J. Atmos. Sci., 52, 1784–1806, 1995. a
Pierrehumbert, R. T.: Science Fiction Atmospheres, B. Am. Meteor. Soc., 86, 696–699, 2005. a
POCS: Perspectives on Climate Sciences home page, https://sites.google.com/view/perspectivesonclimate/home-page (last access: 19 September 2023), 2021. a
Poincaré, H.: Science et méthode, E. Flammarion, 1908. a
Richardson, L. F.: Weather prediction by numerical process, 2nd Edition, University Press, https://doi.org/10.1017/CBO9780511618291, 2007. a
Riehl, H.: A model of hurricane formation, J. Appl. Phys., 21, 917–925, 1950. a
Rossby, C.-G.: On the mutual adjustment of pressure and velocity distributions in certain simple current systems, II, J. Mar. Res., 1, 239–263, 1938. a
Rossby, C.-G.: Planetary flow pattern in the atmosphere, Q. J. Roy. Meteor. Soc., 66, 68–87, 1940. a
Ruelle, D. and Takens, F.: On the nature of trubulence, Commun. Math. Phys., 20, 167–192, https://doi.org/10.1007/BF01646553, 1971. a
Saiki, Y., Sanjuán, M. A. F., and Yorke, J. A.: Low-dimensional paradigms for high-dimensional hetero-chaos, Chaos, 28, 103110, https://doi.org/10.1063/1.5045693, 2018. a
Saiki, Y., Takahasi, H., and Yorke, J. A.: Piecewise linear maps with heterogeneous chaos, Nonlinearity, 34, 5744, https://doi.org/10.1088/1361-6544/ac0d45, 2021. a
Sciamarella, D. and Mindlin, G. B.: Unveiling the topological structure of chaotic flows from data, Phys. Rev. E, 643, 036209, https://doi.org/10.1103/PhysRevE.64.036209, 2001. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the Experiment Design, B. Am. Meteor. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a
von Storch, H.: Brief communication: Climate science as a social process – history, climatic determinism, Mertonian norms and post-normality, Nonlin. Processes Geophys., 30, 31–36, https://doi.org/10.5194/npg-30-31-2023, 2023. a
Short summary
In the online seminar series "Perspectives on climate sciences: from historical developments to future frontiers" (2020–2021), well-known and established scientists from several fields – including mathematics, physics, climate science and ecology – presented their perspectives on the evolution of climate science and on relevant scientific concepts. In this paper, we first give an overview of the content of the seminar series, and then we introduce the written contributions to this special issue.
In the online seminar series "Perspectives on climate sciences: from historical developments to...