Articles | Volume 22, issue 5
https://doi.org/10.5194/npg-22-545-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-22-545-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
23 Sep 2015
Review article |
| 23 Sep 2015
Review: visual analytics of climate networks
T. Nocke
CORRESPONDING AUTHOR
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
S. Buschmann
Hasso Plattner Institute, Prof.-Dr.-Helmert-Str. 2–3, 14482 Potsdam-Babelsberg, Germany
J. F. Donges
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
Stockholm Resilience Centre, Stockholm University, Kräftriket 2B, 114 19 Stockholm, Sweden
N. Marwan
Potsdam Institute for Climate Impact Research, Telegrafenberg A31, 14473 Potsdam, Germany
H.-J. Schulz
Fraunhofer Institute for Computer Graphics Research, Joachim-Jungius-Str. 11, 18059 Rostock, Germany
C. Tominski
Institute for Computer Science, University of Rostock, Albert-Einstein-Str. 22, 18059 Rostock, Germany
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Sonja Molnos, Tarek Mamdouh, Stefan Petri, Thomas Nocke, Tino Weinkauf, and Dim Coumou
Earth Syst. Dynam., 8, 75–89, https://doi.org/10.5194/esd-8-75-2017, https://doi.org/10.5194/esd-8-75-2017, 2017
Nico Wunderling, Anna S. von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Cristiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
Earth Syst. Dynam., 15, 41–74, https://doi.org/10.5194/esd-15-41-2024, https://doi.org/10.5194/esd-15-41-2024, 2024
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This paper maps out the state-of-the-art literature on interactions between tipping elements relevant for current global warming pathways. We find indications that many of the interactions between tipping elements are destabilizing. This means that tipping cascades cannot be ruled out on centennial to millennial timescales at global warming levels between 1.5 and 2.0 °C or on shorter timescales if global warming surpasses 2.0 °C.
This article is included in the Encyclopedia of Geosciences
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.
This article is included in the Encyclopedia of Geosciences
Jordan Paul Everall, Jonathan F. Donges, and Ilona M. Otto
EGUsphere, https://doi.org/10.5194/egusphere-2023-2241, https://doi.org/10.5194/egusphere-2023-2241, 2023
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A social tipping process is a rapid, large change in society, and can be started by few people. Does the 80/20 rule apply here? We see if this is the case for human social groups. We find that if so then it occurs when around 25 % of people engage. Tipping seems generally possible in the range of around 10 % to 40 % of the population, with most systems having tipped by the 40 % mark. When people don't change so easily, trusting groups of friends and housemates can help convince wayward friends.
This article is included in the Encyclopedia of Geosciences
Viktoria Spaiser, Sirkku Juhola, Sara M. Constantino, Weisi Guo, Tabitha Watson, Jana Sillmann, Alessandro Craparo, Ashleigh Basel, John T. Bruun, Krishna Krishnamurthy, Jürgen Scheffran, Patricia Pinho, Uche T. Okpara, Jonathan F. Donges, Avit Bhowmik, Taha Yasseri, Ricardo Safra de Campos, Graeme S. Cumming, Hugues Chenet, Florian Krampe, and Jesse F. Abrams
EGUsphere, https://doi.org/10.5194/egusphere-2023-1475, https://doi.org/10.5194/egusphere-2023-1475, 2023
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In this paper, we identify potential negative social tipping points linked to Earth system destabilisation and draw on related research to understand the drivers and likelihood of these negative social tipping dynamics, their potential effects on human societies and the Earth system, and the potential for cascading interactions and contribution to systemic risks.
This article is included in the Encyclopedia of Geosciences
E. Keith Smith, Marc Wiedermann, Jonathan F. Donges, Jobst Heitzig, and Ricarda Winkelmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-1622, https://doi.org/10.5194/egusphere-2023-1622, 2023
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Social tipping dynamics have received recent attention as a potential mechanism for effective climate actions – yet how such tipping dynamics could unfold remains largely unquantified. We explore how social tipping processes can developed via enabling necessary conditions (exemplified by climate change concern) and increased perceptions of localized impacts (sea-level rise). The likelihood for social tipping varies regionally, mostly along areas with highest exposure to persistent risks.
This article is included in the Encyclopedia of Geosciences
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023, https://doi.org/10.5194/hess-27-2645-2023, 2023
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Employing event synchronization and complex networks analysis, we reveal a cascade of heavy rainfall events, related to intense atmospheric rivers (ARs): heavy precipitation events (HPEs) in western North America (NA) that occur in the aftermath of land-falling ARs are synchronized with HPEs in central and eastern Canada with a delay of up to 12 d. Understanding the effects of ARs in the rainfall over NA will lead to better anticipating the evolution of the climate dynamics in the region.
This article is included in the Encyclopedia of Geosciences
Renee van Dongen, Dirk Scherler, Dadiyorto Wendi, Eric Deal, Luca Mao, Norbert Marwan, and Claudio I. Meier
EGUsphere, https://doi.org/10.5194/egusphere-2022-1234, https://doi.org/10.5194/egusphere-2022-1234, 2022
Preprint archived
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El Niño Southern Oscillation (ENSO) is a climatic phenomenon that causes abnormal climatic conditions in Chile. We investigated how ENSO affects catchment hydrology and found strong seasonal and spatial differences in the hydrological response to ENSO which was caused by different hydrological processes in catchments that are dominated by snowmelt-generated runoff or rainfall-generated runoff. These results are relevant for water resources management and ENSO mitigation in Chile.
This article is included in the Encyclopedia of Geosciences
Maria Zeitz, Jan M. Haacker, Jonathan F. Donges, Torsten Albrecht, and Ricarda Winkelmann
Earth Syst. Dynam., 13, 1077–1096, https://doi.org/10.5194/esd-13-1077-2022, https://doi.org/10.5194/esd-13-1077-2022, 2022
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The stability of the Greenland Ice Sheet under global warming is crucial. Here, using PISM, we study how the interplay of feedbacks between the ice sheet, the atmosphere and solid Earth affects the long-term response of the Greenland Ice Sheet under constant warming. Our findings suggest four distinct dynamic regimes of the Greenland Ice Sheet on the route to destabilization under global warming – from recovery via quasi-periodic oscillations in ice volume to ice sheet collapse.
This article is included in the Encyclopedia of Geosciences
Cinthya Esther Nava Fernandez, Tobias Braun, Bethany Fox, Adam Hartland, Ola Kwiecien, Chelsea Pederson, Sebastian Hoepker, Stefano Bernasconi, Madalina Jaggi, John Hellstrom, Fernando Gázquez, Amanda French, Norbert Marwan, Adrian Immenhauser, and Sebastian Franz Martin Breitenbach
Clim. Past Discuss., https://doi.org/10.5194/cp-2021-172, https://doi.org/10.5194/cp-2021-172, 2022
Manuscript not accepted for further review
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We provide a ca. 1000 year long (6.4–5.4 ka BP) stalagmite-based reconstruction of mid-Holocene rainfall variability in the tropical western Pacific. The annually laminated multi-proxy (δ13C, δ18O, X/Ca, gray values) record comes from Niue island and informs on El Nino-Southern Oscillation and South Pacific Convergence Zone dynamics. Our data suggest that ENSO was active and influenced rainfall seasonality over the covered time interval. Rainfall seasonality was subdued during active ENSO phases
This article is included in the Encyclopedia of Geosciences
Jonathan F. Donges, Wolfgang Lucht, Sarah E. Cornell, Jobst Heitzig, Wolfram Barfuss, Steven J. Lade, and Maja Schlüter
Earth Syst. Dynam., 12, 1115–1137, https://doi.org/10.5194/esd-12-1115-2021, https://doi.org/10.5194/esd-12-1115-2021, 2021
Nico Wunderling, Jonathan F. Donges, Jürgen Kurths, and Ricarda Winkelmann
Earth Syst. Dynam., 12, 601–619, https://doi.org/10.5194/esd-12-601-2021, https://doi.org/10.5194/esd-12-601-2021, 2021
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In the Earth system, climate tipping elements exist that can undergo qualitative changes in response to environmental perturbations. If triggered, this would result in severe consequences for the biosphere and human societies. We quantify the risk of tipping cascades using a conceptual but fully dynamic network approach. We uncover that the risk of tipping cascades under global warming scenarios is enormous and find that the continental ice sheets are most likely to initiate these failures.
This article is included in the Encyclopedia of Geosciences
Abhirup Banerjee, Bedartha Goswami, Yoshito Hirata, Deniz Eroglu, Bruno Merz, Jürgen Kurths, and Norbert Marwan
Nonlin. Processes Geophys., 28, 213–229, https://doi.org/10.5194/npg-28-213-2021, https://doi.org/10.5194/npg-28-213-2021, 2021
Sebastian H. R. Rosier, Ronja Reese, Jonathan F. Donges, Jan De Rydt, G. Hilmar Gudmundsson, and Ricarda Winkelmann
The Cryosphere, 15, 1501–1516, https://doi.org/10.5194/tc-15-1501-2021, https://doi.org/10.5194/tc-15-1501-2021, 2021
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Pine Island Glacier has contributed more to sea-level rise over the past decades than any other glacier in Antarctica. Ice-flow modelling studies have shown that it can undergo periods of rapid mass loss, but no study has shown that these future changes could cross a tipping point and therefore be effectively irreversible. Here, we assess the stability of Pine Island Glacier, quantifying the changes in ocean temperatures required to cross future tipping points using statistical methods.
This article is included in the Encyclopedia of Geosciences
Cinthya Nava-Fernandez, Adam Hartland, Fernando Gázquez, Ola Kwiecien, Norbert Marwan, Bethany Fox, John Hellstrom, Andrew Pearson, Brittany Ward, Amanda French, David A. Hodell, Adrian Immenhauser, and Sebastian F. M. Breitenbach
Hydrol. Earth Syst. Sci., 24, 3361–3380, https://doi.org/10.5194/hess-24-3361-2020, https://doi.org/10.5194/hess-24-3361-2020, 2020
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Speleothems are powerful archives of past climate for understanding modern local hydrology and its relation to regional circulation patterns. We use a 3-year monitoring dataset to test the sensitivity of Waipuna Cave to seasonal changes and El Niño–Southern Oscillation (ENSO) dynamics. Drip water data suggest a fast response to rainfall events; its elemental composition reflects a seasonal cycle and ENSO variability. Waipuna Cave speleothems have a high potential for past ENSO reconstructions.
This article is included in the Encyclopedia of Geosciences
Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Ugur Ozturk, Jürgen Kurths, and Bruno Merz
Hydrol. Earth Syst. Sci., 24, 2235–2251, https://doi.org/10.5194/hess-24-2235-2020, https://doi.org/10.5194/hess-24-2235-2020, 2020
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In the climate/hydrology network, each node represents a geographical location of climatological data, and links between nodes are set up based on their interaction or similar variability. Here, using network theory, we first generate a node-ranking measure and then prioritize the rain gauges to identify influential and expandable stations across Germany. To show the applicability of the proposed approach, we also compared the results with existing traditional and contemporary network measures.
This article is included in the Encyclopedia of Geosciences
Jonathan F. Donges, Jobst Heitzig, Wolfram Barfuss, Marc Wiedermann, Johannes A. Kassel, Tim Kittel, Jakob J. Kolb, Till Kolster, Finn Müller-Hansen, Ilona M. Otto, Kilian B. Zimmerer, and Wolfgang Lucht
Earth Syst. Dynam., 11, 395–413, https://doi.org/10.5194/esd-11-395-2020, https://doi.org/10.5194/esd-11-395-2020, 2020
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We present an open-source software framework for developing so-called
This article is included in the Encyclopedia of Geosciences
world–Earth modelsthat link physical, chemical and biological processes with social, economic and cultural processes to study the Earth system's future trajectories in the Anthropocene. Due to its modular structure, the software allows interdisciplinary studies of global change and sustainable development that combine stylized model components from Earth system science, climatology, economics, ecology and sociology.
Miguel D. Mahecha, Fabian Gans, Gunnar Brandt, Rune Christiansen, Sarah E. Cornell, Normann Fomferra, Guido Kraemer, Jonas Peters, Paul Bodesheim, Gustau Camps-Valls, Jonathan F. Donges, Wouter Dorigo, Lina M. Estupinan-Suarez, Victor H. Gutierrez-Velez, Martin Gutwin, Martin Jung, Maria C. Londoño, Diego G. Miralles, Phillip Papastefanou, and Markus Reichstein
Earth Syst. Dynam., 11, 201–234, https://doi.org/10.5194/esd-11-201-2020, https://doi.org/10.5194/esd-11-201-2020, 2020
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The ever-growing availability of data streams on different subsystems of the Earth brings unprecedented scientific opportunities. However, researching a data-rich world brings novel challenges. We present the concept of
This article is included in the Encyclopedia of Geosciences
Earth system data cubesto study the complex dynamics of multiple climate and ecosystem variables across space and time. Using a series of example studies, we highlight the potential of effectively considering the full multivariate nature of processes in the Earth system.
Jürgen Kurths, Ankit Agarwal, Roopam Shukla, Norbert Marwan, Maheswaran Rathinasamy, Levke Caesar, Raghavan Krishnan, and Bruno Merz
Nonlin. Processes Geophys., 26, 251–266, https://doi.org/10.5194/npg-26-251-2019, https://doi.org/10.5194/npg-26-251-2019, 2019
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We examined the spatial diversity of Indian rainfall teleconnection at different timescales, first by identifying homogeneous communities and later by computing non-linear linkages between the identified communities (spatial regions) and dominant climatic patterns, represented by climatic indices such as El Nino–Southern Oscillation, Indian Ocean Dipole, North Atlantic Oscillation, Pacific Decadal Oscillation and Atlantic Multi-Decadal Oscillation.
This article is included in the Encyclopedia of Geosciences
Steven J. Lade, Jonathan F. Donges, Ingo Fetzer, John M. Anderies, Christian Beer, Sarah E. Cornell, Thomas Gasser, Jon Norberg, Katherine Richardson, Johan Rockström, and Will Steffen
Earth Syst. Dynam., 9, 507–523, https://doi.org/10.5194/esd-9-507-2018, https://doi.org/10.5194/esd-9-507-2018, 2018
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Around half of the carbon that humans emit into the atmosphere each year is taken up on land (by trees) and in the ocean (by absorption). We construct a simple model of carbon uptake that, unlike the complex models that are usually used, can be analysed mathematically. Our results include that changes in atmospheric carbon may affect future carbon uptake more than changes in climate. Our simple model could also study mechanisms that are currently too uncertain for complex models.
This article is included in the Encyclopedia of Geosciences
Finn Müller-Hansen, Maja Schlüter, Michael Mäs, Jonathan F. Donges, Jakob J. Kolb, Kirsten Thonicke, and Jobst Heitzig
Earth Syst. Dynam., 8, 977–1007, https://doi.org/10.5194/esd-8-977-2017, https://doi.org/10.5194/esd-8-977-2017, 2017
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Today, human interactions with the Earth system lead to complex feedbacks between social and ecological dynamics. Modeling such feedbacks explicitly in Earth system models (ESMs) requires making assumptions about individual decision making and behavior, social interaction, and their aggregation. In this overview paper, we compare different modeling approaches and techniques and highlight important consequences of modeling assumptions. We illustrate them with examples from land-use modeling.
This article is included in the Encyclopedia of Geosciences
Ankit Agarwal, Norbert Marwan, Maheswaran Rathinasamy, Bruno Merz, and Jürgen Kurths
Nonlin. Processes Geophys., 24, 599–611, https://doi.org/10.5194/npg-24-599-2017, https://doi.org/10.5194/npg-24-599-2017, 2017
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Extreme events such as floods and droughts result from synchronization of different natural processes working at multiple timescales. Investigation on an observation timescale will not reveal the inherent underlying dynamics triggering these events. This paper develops a new method based on wavelets and event synchronization to unravel the hidden dynamics responsible for such sudden events. This method is tested with synthetic and real-world cases and the results are promising.
This article is included in the Encyclopedia of Geosciences
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
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We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
This article is included in the Encyclopedia of Geosciences
Wolfram Barfuss, Jonathan F. Donges, Marc Wiedermann, and Wolfgang Lucht
Earth Syst. Dynam., 8, 255–264, https://doi.org/10.5194/esd-8-255-2017, https://doi.org/10.5194/esd-8-255-2017, 2017
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Human societies depend on the resources ecosystems provide. We study this coevolutionary relationship by utilizing a stylized model of resource users on a social network. This model demonstrates that social–cultural processes can have a profound influence on the environmental state, such as determining whether the resources collapse from overuse or not. This suggests that social–cultural processes should receive more attention in the modeling of sustainability transitions and the Earth system.
This article is included in the Encyclopedia of Geosciences
Finn Müller-Hansen, Manoel F. Cardoso, Eloi L. Dalla-Nora, Jonathan F. Donges, Jobst Heitzig, Jürgen Kurths, and Kirsten Thonicke
Nonlin. Processes Geophys., 24, 113–123, https://doi.org/10.5194/npg-24-113-2017, https://doi.org/10.5194/npg-24-113-2017, 2017
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Deforestation and subsequent land uses in the Brazilian Amazon have huge impacts on greenhouse gas emissions, local climate and biodiversity. To better understand these land-cover changes, we apply complex systems methods uncovering spatial patterns in regional transition probabilities between land-cover types, which we estimate using maps derived from satellite imagery. The results show clusters of similar land-cover dynamics and thus complement studies at the local scale.
This article is included in the Encyclopedia of Geosciences
Sonja Molnos, Tarek Mamdouh, Stefan Petri, Thomas Nocke, Tino Weinkauf, and Dim Coumou
Earth Syst. Dynam., 8, 75–89, https://doi.org/10.5194/esd-8-75-2017, https://doi.org/10.5194/esd-8-75-2017, 2017
Vera Heck, Jonathan F. Donges, and Wolfgang Lucht
Earth Syst. Dynam., 7, 783–796, https://doi.org/10.5194/esd-7-783-2016, https://doi.org/10.5194/esd-7-783-2016, 2016
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We assess the co-evolutionary dynamics of the Earth's carbon cycle and societal interventions through terrestrial carbon dioxide removal (tCDR) with a conceptual model in a planetary boundary context. The focus on one planetary boundary alone may lead to navigating the Earth system out of the safe operating space due to transgression of other boundaries. The success of tCDR depends on the degree of anticipation of climate change, the potential tCDR rate and the underlying emission pathway.
This article is included in the Encyclopedia of Geosciences
Jonatan F. Siegmund, Marc Wiedermann, Jonathan F. Donges, and Reik V. Donner
Biogeosciences, 13, 5541–5555, https://doi.org/10.5194/bg-13-5541-2016, https://doi.org/10.5194/bg-13-5541-2016, 2016
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In this study we systematically quantify simultaneities between meteorological extremes and the timing of flowering of four shrub species across Germany by using event coincidence analysis. Our study confirms previous findings of experimental studies, highlighting the impact of early spring temperatures on the flowering of the investigated plants. Additionally, the analysis reveals statistically significant indications of an influence of temperature extremes in the fall preceding the flowering.
This article is included in the Encyclopedia of Geosciences
J. Heitzig, T. Kittel, J. F. Donges, and N. Molkenthin
Earth Syst. Dynam., 7, 21–50, https://doi.org/10.5194/esd-7-21-2016, https://doi.org/10.5194/esd-7-21-2016, 2016
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The debate about a safe and just operating space for humanity and the possible pathways towards and within it requires an analysis of the inherent dynamics of the Earth system and of the options for influencing its evolution. We present and illustrate with examples a conceptual framework for performing such an analysis not in a quantitative, optimizing mode, but in a qualitative way that emphasizes the main decision dilemmas that one may face in the sustainable management of the Earth system.
This article is included in the Encyclopedia of Geosciences
A. Y. Sun, J. Chen, and J. Donges
Nonlin. Processes Geophys., 22, 433–446, https://doi.org/10.5194/npg-22-433-2015, https://doi.org/10.5194/npg-22-433-2015, 2015
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Terrestrial water storage (TWS) plays a key role in global water and energy cycles. This work applies complex climate networks to analyzing spatial patterns in TWS. A comparative analysis is conducted using a remotely sensed (GRACE) and a model-generated TWS data set. Our results reveal hotspots of TWS anomalies around the global land surfaces. Prospects are offered on using network connectivity as constraints to further improve current global land surface models.
This article is included in the Encyclopedia of Geosciences
J. F. Donges, R. V. Donner, N. Marwan, S. F. M. Breitenbach, K. Rehfeld, and J. Kurths
Clim. Past, 11, 709–741, https://doi.org/10.5194/cp-11-709-2015, https://doi.org/10.5194/cp-11-709-2015, 2015
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Paleoclimate records from cave deposits allow the reconstruction of Holocene dynamics of the Asian monsoon system, an important tipping element in Earth's climate. Employing recently developed techniques of nonlinear time series analysis reveals several robust and continental-scale regime shifts in the complexity of monsoonal variability. These regime shifts might have played an important role as drivers of migration, cultural change, and societal collapse during the past 10,000 years.
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A. Rammig, M. Wiedermann, J. F. Donges, F. Babst, W. von Bloh, D. Frank, K. Thonicke, and M. D. Mahecha
Biogeosciences, 12, 373–385, https://doi.org/10.5194/bg-12-373-2015, https://doi.org/10.5194/bg-12-373-2015, 2015
D. C. Zemp, C.-F. Schleussner, H. M. J. Barbosa, R. J. van der Ent, J. F. Donges, J. Heinke, G. Sampaio, and A. Rammig
Atmos. Chem. Phys., 14, 13337–13359, https://doi.org/10.5194/acp-14-13337-2014, https://doi.org/10.5194/acp-14-13337-2014, 2014
Y. Zou, R. V. Donner, N. Marwan, M. Small, and J. Kurths
Nonlin. Processes Geophys., 21, 1113–1126, https://doi.org/10.5194/npg-21-1113-2014, https://doi.org/10.5194/npg-21-1113-2014, 2014
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We use visibility graphs to characterize asymmetries in the dynamics of sunspot areas in both solar hemispheres. Our analysis provides deep insights into the potential and limitations of this method, revealing a complex interplay between effects due to statistical versus dynamical properties of the observed data. Temporal changes in the hemispheric predominance of the graph connectivity are found to lag those directly associated with the total hemispheric sunspot areas themselves.
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D. Eroglu, N. Marwan, S. Prasad, and J. Kurths
Nonlin. Processes Geophys., 21, 1085–1092, https://doi.org/10.5194/npg-21-1085-2014, https://doi.org/10.5194/npg-21-1085-2014, 2014
B. Goswami, J. Heitzig, K. Rehfeld, N. Marwan, A. Anoop, S. Prasad, and J. Kurths
Nonlin. Processes Geophys., 21, 1093–1111, https://doi.org/10.5194/npg-21-1093-2014, https://doi.org/10.5194/npg-21-1093-2014, 2014
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We present a new approach to estimating sedimentary proxy records along with the proxy uncertainty. We provide analytical expressions for the proxy record, while transparently propagating uncertainties from the ages to the proxy record. We represent proxies on an error-free, precise timescale. Our approach provides insight into the interrelations between proxy variability and the various uncertainties. We demonstrate our method with synthetic examples and proxy data from the Lonar lake in India.
This article is included in the Encyclopedia of Geosciences
V. Stolbova, P. Martin, B. Bookhagen, N. Marwan, and J. Kurths
Nonlin. Processes Geophys., 21, 901–917, https://doi.org/10.5194/npg-21-901-2014, https://doi.org/10.5194/npg-21-901-2014, 2014
L. Tupikina, K. Rehfeld, N. Molkenthin, V. Stolbova, N. Marwan, and J. Kurths
Nonlin. Processes Geophys., 21, 705–711, https://doi.org/10.5194/npg-21-705-2014, https://doi.org/10.5194/npg-21-705-2014, 2014
J. Hlinka, D. Hartman, N. Jajcay, M. Vejmelka, R. Donner, N. Marwan, J. Kurths, and M. Paluš
Nonlin. Processes Geophys., 21, 451–462, https://doi.org/10.5194/npg-21-451-2014, https://doi.org/10.5194/npg-21-451-2014, 2014
N. Itoh and N. Marwan
Nonlin. Processes Geophys., 20, 467–481, https://doi.org/10.5194/npg-20-467-2013, https://doi.org/10.5194/npg-20-467-2013, 2013
Related subject area
Subject: Time series, machine learning, networks, stochastic processes, extreme events | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere
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Using neural networks to improve simulations in the gray zone
Direct Bayesian model reduction of smaller scale convective activity conditioned on large-scale dynamics
A waveform skewness index for measuring time series nonlinearity and its applications to the ENSO–Indian monsoon relationship
The blessing of dimensionality for the analysis of climate data
Empirical evidence of a fluctuation theorem for the wind mechanical power input into the ocean
Producing realistic climate data with generative adversarial networks
Identification of droughts and heatwaves in Germany with regional climate networks
Recurrence analysis of extreme event-like data
Extracting statistically significant eddy signals from large Lagrangian datasets using wavelet ridge analysis, with application to the Gulf of Mexico
Improvements to the use of the Trajectory-Adaptive Multilevel Sampling algorithm for the study of rare events
Ensemble-based statistical interpolation with Gaussian anamorphosis for the spatial analysis of precipitation
Applications of matrix factorization methods to climate data
Beyond univariate calibration: verifying spatial structure in ensembles of forecast fields
Simulation-based comparison of multivariate ensemble post-processing methods
Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis
Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory
Remember the past: a comparison of time-adaptive training schemes for non-homogeneous regression
On fluctuating momentum exchange in idealised models of air–sea interaction
A prototype stochastic parameterization of regime behaviour in the stably stratified atmospheric boundary layer
Statistical post-processing of ensemble forecasts of the height of new snow
Unravelling the spatial diversity of Indian precipitation teleconnections via a non-linear multi-scale approach
Statistical hypothesis testing in wavelet analysis: theoretical developments and applications to Indian rainfall
Comparison of stochastic parameterizations in the framework of a coupled ocean–atmosphere model
Idealized models of the joint probability distribution of wind speeds
Nonlinear analysis of the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea
A general theory on frequency and time–frequency analysis of irregularly sampled time series based on projection methods – Part 1: Frequency analysis
A general theory on frequency and time–frequency analysis of irregularly sampled time series based on projection methods – Part 2: Extension to time–frequency analysis
Tipping point analysis of ocean acoustic noise
On the intrinsic timescales of temporal variability in measurements of the surface solar radiation
Optimal heavy tail estimation – Part 1: Order selection
Network-based study of Lagrangian transport and mixing
Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach
Fractional Brownian motion, the Matérn process, and stochastic modeling of turbulent dispersion
A matrix clustering method to explore patterns of land-cover transitions in satellite-derived maps of the Brazilian Amazon
Parameterization of stochastic multiscale triads
Compound extremes in a changing climate – a Markov chain approach
Wavelet analysis of the singular spectral reconstructed time series to study the imprints of solar–ENSO–geomagnetic activity on Indian climate
Bin Shi and Junjie Ma
Nonlin. Processes Geophys., 31, 165–174, https://doi.org/10.5194/npg-31-165-2024, https://doi.org/10.5194/npg-31-165-2024, 2024
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Different from traditional deterministic optimization algorithms, we implement the sampling method to compute the conditional nonlinear optimal perturbations (CNOPs) in the realistic and predictive coupled ocean–atmosphere model, which reduces the first-order information to the zeroth-order one, avoiding the high-cost computation of the gradient. The numerical performance highlights the importance of stochastic optimization algorithms to compute CNOPs and capture initial optimal precursors.
This article is included in the Encyclopedia of Geosciences
David Docquier, Giorgia Di Capua, Reik V. Donner, Carlos A. L. Pires, Amélie Simon, and Stéphane Vannitsem
Nonlin. Processes Geophys., 31, 115–136, https://doi.org/10.5194/npg-31-115-2024, https://doi.org/10.5194/npg-31-115-2024, 2024
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Identifying causes of specific processes is crucial in order to better understand our climate system. Traditionally, correlation analyses have been used to identify cause–effect relationships in climate studies. However, correlation does not imply causation, which justifies the need to use causal methods. We compare two independent causal methods and show that these are superior to classical correlation analyses. We also find some interesting differences between the two methods.
This article is included in the Encyclopedia of Geosciences
Louis Le Toumelin, Isabelle Gouttevin, Clovis Galiez, and Nora Helbig
Nonlin. Processes Geophys., 31, 75–97, https://doi.org/10.5194/npg-31-75-2024, https://doi.org/10.5194/npg-31-75-2024, 2024
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Forecasting wind fields over mountains is of high importance for several applications and particularly for understanding how wind erodes and disperses snow. Forecasters rely on operational wind forecasts over mountains, which are currently only available on kilometric scales. These forecasts can also be affected by errors of diverse origins. Here we introduce a new strategy based on artificial intelligence to correct large-scale wind forecasts in mountains and increase their spatial resolution.
This article is included in the Encyclopedia of Geosciences
Florian Dupuy, Pierre Durand, and Thierry Hedde
Nonlin. Processes Geophys., 30, 553–570, https://doi.org/10.5194/npg-30-553-2023, https://doi.org/10.5194/npg-30-553-2023, 2023
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Forecasting near-surface winds over complex terrain requires high-resolution numerical weather prediction models, which drastically increase the duration of simulations and hinder them in running on a routine basis. A faster alternative is statistical downscaling. We explore different ways of calculating near-surface wind speed and direction using artificial intelligence algorithms based on various convolutional neural networks in order to find the best approach for wind downscaling.
This article is included in the Encyclopedia of Geosciences
Sofia Flora, Laura Ursella, and Achim Wirth
Nonlin. Processes Geophys., 30, 515–525, https://doi.org/10.5194/npg-30-515-2023, https://doi.org/10.5194/npg-30-515-2023, 2023
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An increasing amount of data allows us to move from low-order moments of fluctuating observations to their PDFs. We found the analytical fat-tailed PDF form (a combination of Gaussian and two-exponential convolutions) for 2 years of sea surface current increments in the Gulf of Trieste, using superstatistics and the maximum-entropy principle twice: on short and longer timescales. The data from different wind regimes follow the same analytical PDF, pointing towards a universal behaviour.
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Yicun Zhen, Valentin Resseguier, and Bertrand Chapron
Nonlin. Processes Geophys., 30, 237–251, https://doi.org/10.5194/npg-30-237-2023, https://doi.org/10.5194/npg-30-237-2023, 2023
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This paper provides perspective that the displacement vector field of physical state fields should be determined by the tensor fields associated with the physical fields. The advantage of this perspective is that certain physical quantities can be conserved while applying a displacement vector field to transfer the original physical field. A direct application of this perspective is the physically constrained covariance inflation scheme proposed in this paper.
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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.
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Domenico Giaquinto, Warner Marzocchi, and Jürgen Kurths
Nonlin. Processes Geophys., 30, 167–181, https://doi.org/10.5194/npg-30-167-2023, https://doi.org/10.5194/npg-30-167-2023, 2023
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Despite being among the most severe climate extremes, it is still challenging to assess droughts’ features for specific regions. In this paper we study meteorological droughts in Europe using concepts derived from climate network theory. By exploring the synchronization in droughts occurrences across the continent we unveil regional clusters which are individually examined to identify droughts’ geographical propagation and source–sink systems, which could potentially support droughts’ forecast.
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Scott Hottovy and Samuel N. Stechmann
Nonlin. Processes Geophys., 30, 85–100, https://doi.org/10.5194/npg-30-85-2023, https://doi.org/10.5194/npg-30-85-2023, 2023
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Rainfall is erratic and difficult to predict. Thus, random models are often used to describe rainfall events. Since many of these random models are based more on statistics than physical laws, it is desirable to develop connections between the random statistical models and the underlying physics of rain. Here, a physics-based model is shown to converge to a statistics-based model, which helps to provide a physical basis for the statistics-based model.
This article is included in the Encyclopedia of Geosciences
Joko Sampurno, Valentin Vallaeys, Randy Ardianto, and Emmanuel Hanert
Nonlin. Processes Geophys., 29, 301–315, https://doi.org/10.5194/npg-29-301-2022, https://doi.org/10.5194/npg-29-301-2022, 2022
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In this study, we successfully built and evaluated machine learning models for predicting water level dynamics as a proxy for compound flooding hazards in a data-scarce delta. The issues that we tackled here are data scarcity and low computational resources for building flood forecasting models. The proposed approach is suitable for use by local water management agencies in developing countries that encounter these issues.
This article is included in the Encyclopedia of Geosciences
Olivier Delage, Thierry Portafaix, Hassan Bencherif, Alain Bourdier, and Emma Lagracie
Nonlin. Processes Geophys., 29, 265–277, https://doi.org/10.5194/npg-29-265-2022, https://doi.org/10.5194/npg-29-265-2022, 2022
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The complexity of geophysics systems results in time series with fluctuations at all timescales. The analysis of their variability then consists in decomposing them into a set of basis signals. We developed here a new adaptive filtering method called empirical adaptive wavelet decomposition that optimizes the empirical-mode decomposition existing technique, overcoming its drawbacks using the rigour of wavelets as defined in the recently published empirical wavelet transform method.
This article is included in the Encyclopedia of Geosciences
Benjamin Walleshauser and Erik Bollt
Nonlin. Processes Geophys., 29, 255–264, https://doi.org/10.5194/npg-29-255-2022, https://doi.org/10.5194/npg-29-255-2022, 2022
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As sea surface temperature (SST) is vital for understanding the greater climate of the Earth and is also an important variable in weather prediction, we propose a model that effectively capitalizes on the reduced complexity of machine learning models while still being able to efficiently predict over a large spatial domain. We find that it is proficient at predicting the SST at specific locations as well as over the greater domain of the Earth’s oceans.
This article is included in the Encyclopedia of Geosciences
Valerio Lucarini, Larissa Serdukova, and Georgios Margazoglou
Nonlin. Processes Geophys., 29, 183–205, https://doi.org/10.5194/npg-29-183-2022, https://doi.org/10.5194/npg-29-183-2022, 2022
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In most of the investigations on metastable systems, the stochastic forcing is modulated by Gaussian noise. Lévy noise laws, which describe jump processes, have recently received a lot of attention, but much less is known. We study stochastic versions of the Ghil–Sellers energy balance model, and we highlight the fundamental difference between how transitions are performed between the competing warm and snowball states, depending on whether Gaussian or Lévy noise acts as forcing.
This article is included in the Encyclopedia of Geosciences
Raphael Kriegmair, Yvonne Ruckstuhl, Stephan Rasp, and George Craig
Nonlin. Processes Geophys., 29, 171–181, https://doi.org/10.5194/npg-29-171-2022, https://doi.org/10.5194/npg-29-171-2022, 2022
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Our regional numerical weather prediction models run at kilometer-scale resolutions. Processes that occur at smaller scales not yet resolved contribute significantly to the atmospheric flow. We use a neural network (NN) to represent the unresolved part of physical process such as cumulus clouds. We test this approach on a simplified, yet representative, 1D model and find that the NN corrections vastly improve the model forecast up to a couple of days.
This article is included in the Encyclopedia of Geosciences
Robert Polzin, Annette Müller, Henning Rust, Peter Névir, and Péter Koltai
Nonlin. Processes Geophys., 29, 37–52, https://doi.org/10.5194/npg-29-37-2022, https://doi.org/10.5194/npg-29-37-2022, 2022
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In this study, a recent algorithmic framework called Direct Bayesian Model Reduction (DBMR) is applied which provides a scalable probability-preserving identification of reduced models directly from data. The stochastic method is tested in a meteorological application towards a model reduction to latent states of smaller scale convective activity conditioned on large-scale atmospheric flow.
This article is included in the Encyclopedia of Geosciences
Justin Schulte, Frederick Policelli, and Benjamin Zaitchik
Nonlin. Processes Geophys., 29, 1–15, https://doi.org/10.5194/npg-29-1-2022, https://doi.org/10.5194/npg-29-1-2022, 2022
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The skewness of a time series is commonly used to quantify the extent to which positive (negative) deviations from the mean are larger than negative (positive) ones. However, in some cases, traditional skewness may not provide reliable information about time series skewness, motivating the development of a waveform skewness index in this paper. The waveform skewness index is used to show that changes in the relationship strength between climate time series could arise from changes in skewness.
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Bo Christiansen
Nonlin. Processes Geophys., 28, 409–422, https://doi.org/10.5194/npg-28-409-2021, https://doi.org/10.5194/npg-28-409-2021, 2021
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In geophysics we often need to analyse large samples of high-dimensional fields. Fortunately but counterintuitively, such high dimensionality can be a blessing, and we demonstrate how this allows simple analytical results to be derived. These results include estimates of correlations between sample members and how the sample mean depends on the sample size. We show that the properties of high dimensionality with success can be applied to climate fields, such as those from ensemble modelling.
This article is included in the Encyclopedia of Geosciences
Achim Wirth and Bertrand Chapron
Nonlin. Processes Geophys., 28, 371–378, https://doi.org/10.5194/npg-28-371-2021, https://doi.org/10.5194/npg-28-371-2021, 2021
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In non-equilibrium statistical mechanics, which describes forced-dissipative systems such as air–sea interaction, there is no universal probability density function (pdf). Some such systems have recently been demonstrated to exhibit a symmetry called a fluctuation theorem (FT), which strongly constrains the shape of the pdf. Using satellite data, the mechanical power input to the ocean by air–sea interaction following or not a FT is questioned. A FT is found to apply over specific ocean regions.
This article is included in the Encyclopedia of Geosciences
Camille Besombes, Olivier Pannekoucke, Corentin Lapeyre, Benjamin Sanderson, and Olivier Thual
Nonlin. Processes Geophys., 28, 347–370, https://doi.org/10.5194/npg-28-347-2021, https://doi.org/10.5194/npg-28-347-2021, 2021
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This paper investigates the potential of a type of deep generative neural network to produce realistic weather situations when trained from the climate of a general circulation model. The generator represents the climate in a compact latent space. It is able to reproduce many aspects of the targeted multivariate distribution. Some properties of our method open new perspectives such as the exploration of the extremes close to a given state or how to connect two realistic weather states.
This article is included in the Encyclopedia of Geosciences
Gerd Schädler and Marcus Breil
Nonlin. Processes Geophys., 28, 231–245, https://doi.org/10.5194/npg-28-231-2021, https://doi.org/10.5194/npg-28-231-2021, 2021
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We used regional climate networks (RCNs) to identify past heatwaves and droughts in Germany. RCNs provide information for whole areas and can provide many details of extreme events. The RCNs were constructed on the grid of the E-OBS data set. Time series correlation was used to construct the networks. Network metrics were compared to standard extreme indices and differed considerably between normal and extreme years. The results show that RCNs can identify severe and moderate extremes.
This article is included in the Encyclopedia of Geosciences
Abhirup Banerjee, Bedartha Goswami, Yoshito Hirata, Deniz Eroglu, Bruno Merz, Jürgen Kurths, and Norbert Marwan
Nonlin. Processes Geophys., 28, 213–229, https://doi.org/10.5194/npg-28-213-2021, https://doi.org/10.5194/npg-28-213-2021, 2021
Jonathan M. Lilly and Paula Pérez-Brunius
Nonlin. Processes Geophys., 28, 181–212, https://doi.org/10.5194/npg-28-181-2021, https://doi.org/10.5194/npg-28-181-2021, 2021
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Long-lived eddies are an important part of the ocean circulation. Here a dataset for studying eddies in the Gulf of Mexico is created through the analysis of trajectories of drifting instruments. The method involves the identification of quasi-periodic signals, characteristic of particles trapped in eddies, from the displacement records, followed by the creation of a measure of statistical significance. It is expected that this dataset will be of use to other authors studying this region.
This article is included in the Encyclopedia of Geosciences
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.
This article is included in the Encyclopedia of Geosciences
Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, and Christoffer A. Elo
Nonlin. Processes Geophys., 28, 61–91, https://doi.org/10.5194/npg-28-61-2021, https://doi.org/10.5194/npg-28-61-2021, 2021
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An unprecedented amount of rainfall data is available nowadays, such as ensemble model output, weather radar estimates, and in situ observations from networks of both traditional and opportunistic sensors. Nevertheless, the exact amount of precipitation, to some extent, eludes our knowledge. The objective of our study is precipitation reconstruction through the combination of numerical model outputs with observations from multiple data sources.
This article is included in the Encyclopedia of Geosciences
Dylan Harries and Terence J. O'Kane
Nonlin. Processes Geophys., 27, 453–471, https://doi.org/10.5194/npg-27-453-2020, https://doi.org/10.5194/npg-27-453-2020, 2020
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Different dimension reduction methods may produce profoundly different low-dimensional representations of multiscale systems. We perform a set of case studies to investigate these differences. When a clear scale separation is present, similar bases are obtained using all methods, but when this is not the case some methods may produce representations that are poorly suited for describing features of interest, highlighting the importance of a careful choice of method when designing analyses.
This article is included in the Encyclopedia of Geosciences
Josh Jacobson, William Kleiber, Michael Scheuerer, and Joseph Bellier
Nonlin. Processes Geophys., 27, 411–427, https://doi.org/10.5194/npg-27-411-2020, https://doi.org/10.5194/npg-27-411-2020, 2020
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Most verification metrics for ensemble forecasts assess the representation of uncertainty at a particular location and time. We study a new diagnostic tool based on fractions of threshold exceedance (FTE) which evaluates an additional important attribute: the ability of ensemble forecast fields to reproduce the spatial structure of observed fields. The utility of this diagnostic tool is demonstrated through simulations and an application to ensemble precipitation forecasts.
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Sebastian Lerch, Sándor Baran, Annette Möller, Jürgen Groß, Roman Schefzik, Stephan Hemri, and Maximiliane Graeter
Nonlin. Processes Geophys., 27, 349–371, https://doi.org/10.5194/npg-27-349-2020, https://doi.org/10.5194/npg-27-349-2020, 2020
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Accurate models of spatial, temporal, and inter-variable dependencies are of crucial importance for many practical applications. We review and compare several methods for multivariate ensemble post-processing, where such dependencies are imposed via copula functions. Our investigations utilize simulation studies that mimic challenges occurring in practical applications and allow ready interpretation of the effects of different misspecifications of the numerical weather prediction ensemble.
This article is included in the Encyclopedia of Geosciences
Jaqueline Lekscha and Reik V. Donner
Nonlin. Processes Geophys., 27, 261–275, https://doi.org/10.5194/npg-27-261-2020, https://doi.org/10.5194/npg-27-261-2020, 2020
Julian Steinheuer and Petra Friederichs
Nonlin. Processes Geophys., 27, 239–252, https://doi.org/10.5194/npg-27-239-2020, https://doi.org/10.5194/npg-27-239-2020, 2020
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Many applications require wind gust estimates at very different atmospheric altitudes, such as in the wind energy sector. However, numerical weather prediction models usually only derive estimates for gusts at 10 m above the land surface. We present a statistical model that gives the hourly peak wind speed. The model is trained based on a weather reanalysis and observations from the Hamburg Weather Mast. Reliable predictions are derived at up to 250 m, even at unobserved intermediate levels.
This article is included in the Encyclopedia of Geosciences
Moritz N. Lang, Sebastian Lerch, Georg J. Mayr, Thorsten Simon, Reto Stauffer, and Achim Zeileis
Nonlin. Processes Geophys., 27, 23–34, https://doi.org/10.5194/npg-27-23-2020, https://doi.org/10.5194/npg-27-23-2020, 2020
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Statistical post-processing aims to increase the predictive skill of probabilistic ensemble weather forecasts by learning the statistical relation between historical pairs of observations and ensemble forecasts within a given training data set. This study compares four different training schemes and shows that including multiple years of data in the training set typically yields a more stable post-processing while it loses the ability to quickly adjust to temporal changes in the underlying data.
This article is included in the Encyclopedia of Geosciences
Achim Wirth
Nonlin. Processes Geophys., 26, 457–477, https://doi.org/10.5194/npg-26-457-2019, https://doi.org/10.5194/npg-26-457-2019, 2019
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The conspicuous feature of the atmosphere–ocean system is the large difference in the masses of the two media. In this respect there is a strong analogy to Brownian motion, with light and fast molecules colliding with heavy and slow Brownian particles. I apply the tools of non-equilibrium statistical mechanics for studying Brownian motion to air–sea interaction.
This article is included in the Encyclopedia of Geosciences
Carsten Abraham, Amber M. Holdsworth, and Adam H. Monahan
Nonlin. Processes Geophys., 26, 401–427, https://doi.org/10.5194/npg-26-401-2019, https://doi.org/10.5194/npg-26-401-2019, 2019
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Atmospheric stably stratified boundary layers display transitions between regimes of sustained and intermittent turbulence. These transitions are not well represented in numerical weather prediction and climate models. A prototype explicitly stochastic turbulence parameterization simulating regime dynamics is presented and tested in an idealized model. Results demonstrate that the approach can improve the regime representation in models.
This article is included in the Encyclopedia of Geosciences
Jari-Pekka Nousu, Matthieu Lafaysse, Matthieu Vernay, Joseph Bellier, Guillaume Evin, and Bruno Joly
Nonlin. Processes Geophys., 26, 339–357, https://doi.org/10.5194/npg-26-339-2019, https://doi.org/10.5194/npg-26-339-2019, 2019
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Forecasting the height of new snow is crucial for avalanche hazard, road viability, ski resorts and tourism. The numerical models suffer from systematic and significant errors which are misleading for the final users. Here, we applied for the first time a state-of-the-art statistical method to correct ensemble numerical forecasts of the height of new snow from their statistical link with measurements in French Alps and Pyrenees. Thus the realism of automatic forecasts can be quickly improved.
This article is included in the Encyclopedia of Geosciences
Jürgen Kurths, Ankit Agarwal, Roopam Shukla, Norbert Marwan, Maheswaran Rathinasamy, Levke Caesar, Raghavan Krishnan, and Bruno Merz
Nonlin. Processes Geophys., 26, 251–266, https://doi.org/10.5194/npg-26-251-2019, https://doi.org/10.5194/npg-26-251-2019, 2019
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We examined the spatial diversity of Indian rainfall teleconnection at different timescales, first by identifying homogeneous communities and later by computing non-linear linkages between the identified communities (spatial regions) and dominant climatic patterns, represented by climatic indices such as El Nino–Southern Oscillation, Indian Ocean Dipole, North Atlantic Oscillation, Pacific Decadal Oscillation and Atlantic Multi-Decadal Oscillation.
This article is included in the Encyclopedia of Geosciences
Justin A. Schulte
Nonlin. Processes Geophys., 26, 91–108, https://doi.org/10.5194/npg-26-91-2019, https://doi.org/10.5194/npg-26-91-2019, 2019
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Statistical hypothesis tests in wavelet analysis are used to asses the likelihood that time series features are noise. The choice of test will determine which features emerge as a signal. Tests based on area do poorly at distinguishing abrupt fluctuations from periodic behavior, unlike tests based on arclength that do better. The application of the tests suggests that there are features in Indian rainfall time series that emerge from background noise.
This article is included in the Encyclopedia of Geosciences
Jonathan Demaeyer and Stéphane Vannitsem
Nonlin. Processes Geophys., 25, 605–631, https://doi.org/10.5194/npg-25-605-2018, https://doi.org/10.5194/npg-25-605-2018, 2018
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We investigate the modeling of the effects of the unresolved scales on the large scales of the coupled ocean–atmosphere model MAOOAM. Two different physically based stochastic methods are considered and compared, in various configurations of the model. Both methods show remarkable performances and are able to model fundamental changes in the model dynamics. Ways to improve the parameterizations' implementation are also proposed.
This article is included in the Encyclopedia of Geosciences
Adam H. Monahan
Nonlin. Processes Geophys., 25, 335–353, https://doi.org/10.5194/npg-25-335-2018, https://doi.org/10.5194/npg-25-335-2018, 2018
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Bivariate probability density functions (pdfs) of wind speed characterize the relationship between speeds at two different locations or times. This study develops such pdfs of wind speed from distributions of the components, following a well-established approach for univariate distributions. The ability of these models to characterize example observed datasets is assessed. The mathematical complexity of these models suggests further extensions of this line of reasoning may not be practical.
This article is included in the Encyclopedia of Geosciences
Berenice Rojo-Garibaldi, David Alberto Salas-de-León, María Adela Monreal-Gómez, Norma Leticia Sánchez-Santillán, and David Salas-Monreal
Nonlin. Processes Geophys., 25, 291–300, https://doi.org/10.5194/npg-25-291-2018, https://doi.org/10.5194/npg-25-291-2018, 2018
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Hurricanes are complex systems that carry large amounts of energy. Its impact produces, most of the time, natural disasters involving the loss of human lives and of materials and infrastructure that is accounted for in billions of US dollars. Not everything is negative as hurricanes are the main source of rainwater for the regions where they develop. In this study we make a nonlinear analysis of the time series obtained from 1749 to 2012 of the hurricane occurrence in the Gulf of Mexico.
This article is included in the Encyclopedia of Geosciences
Guillaume Lenoir and Michel Crucifix
Nonlin. Processes Geophys., 25, 145–173, https://doi.org/10.5194/npg-25-145-2018, https://doi.org/10.5194/npg-25-145-2018, 2018
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We develop a general framework for the frequency analysis of irregularly sampled time series. We also design a test of significance against a general background noise which encompasses the Gaussian white or red noise. Our results generalize and unify methods developed in the fields of geosciences, engineering, astronomy and astrophysics. All the analysis tools presented in this paper are available to the reader in the Python package WAVEPAL.
This article is included in the Encyclopedia of Geosciences
Guillaume Lenoir and Michel Crucifix
Nonlin. Processes Geophys., 25, 175–200, https://doi.org/10.5194/npg-25-175-2018, https://doi.org/10.5194/npg-25-175-2018, 2018
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There is so far no general framework for handling the continuous wavelet transform when the time sampling is irregular. Here we provide such a framework with the Morlet wavelet, based on the results of part I of this study. We also design a test of significance against a general background noise which encompasses the Gaussian white or red noise. All the analysis tools presented in this article are available to the reader in the Python package WAVEPAL.
This article is included in the Encyclopedia of Geosciences
Valerie N. Livina, Albert Brouwer, Peter Harris, Lian Wang, Kostas Sotirakopoulos, and Stephen Robinson
Nonlin. Processes Geophys., 25, 89–97, https://doi.org/10.5194/npg-25-89-2018, https://doi.org/10.5194/npg-25-89-2018, 2018
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We have applied tipping point analysis to a large record of ocean acoustic data to identify the main components of the acoustic dynamical system: long-term and seasonal trends, system states and fluctuations. We reconstructed a one-dimensional stochastic model equation to approximate the acoustic dynamical system. We have found a signature of El Niño events in the deep ocean acoustic data near the southwest Australian coast, which proves the investigative power of the tipping point methodology.
This article is included in the Encyclopedia of Geosciences
Marc Bengulescu, Philippe Blanc, and Lucien Wald
Nonlin. Processes Geophys., 25, 19–37, https://doi.org/10.5194/npg-25-19-2018, https://doi.org/10.5194/npg-25-19-2018, 2018
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We employ the Hilbert–Huang transform to study the temporal variability in time series of daily means of the surface solar irradiance (SSI) at different locations around the world. The data have a significant spectral peak corresponding to the yearly variability cycle and feature quasi-stochastic high-frequency "weather noise", irrespective of the geographical location or of the local climate. Our findings can improve models for estimating SSI from satellite images or forecasts of the SSI.
This article is included in the Encyclopedia of Geosciences
Manfred Mudelsee and Miguel A. Bermejo
Nonlin. Processes Geophys., 24, 737–744, https://doi.org/10.5194/npg-24-737-2017, https://doi.org/10.5194/npg-24-737-2017, 2017
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Risk analysis of extremes has high socioeconomic relevance. Of crucial interest is the tail probability, P, of the distribution of a variable, which is the chance of observing a value equal to or greater than a certain threshold value, x. Many variables in geophysical systems (e.g. climate) show heavy tail behaviour, where P may be rather large. In particular, P decreases with x as a power law that is described by a parameter, α. We present an improved method to estimate α on data.
This article is included in the Encyclopedia of Geosciences
Kathrin Padberg-Gehle and Christiane Schneide
Nonlin. Processes Geophys., 24, 661–671, https://doi.org/10.5194/npg-24-661-2017, https://doi.org/10.5194/npg-24-661-2017, 2017
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Transport and mixing processes in fluid flows are crucially influenced by coherent structures, such as eddies, gyres, or jets in geophysical flows. We propose a very simple and computationally efficient approach for analyzing coherent behavior in fluid flows. The central object is a flow network constructed directly from particle trajectories. The network's local and spectral properties are shown to give a very good indication of coherent as well as mixing regions in the underlying flow.
This article is included in the Encyclopedia of Geosciences
Ankit Agarwal, Norbert Marwan, Maheswaran Rathinasamy, Bruno Merz, and Jürgen Kurths
Nonlin. Processes Geophys., 24, 599–611, https://doi.org/10.5194/npg-24-599-2017, https://doi.org/10.5194/npg-24-599-2017, 2017
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Extreme events such as floods and droughts result from synchronization of different natural processes working at multiple timescales. Investigation on an observation timescale will not reveal the inherent underlying dynamics triggering these events. This paper develops a new method based on wavelets and event synchronization to unravel the hidden dynamics responsible for such sudden events. This method is tested with synthetic and real-world cases and the results are promising.
This article is included in the Encyclopedia of Geosciences
Jonathan M. Lilly, Adam M. Sykulski, Jeffrey J. Early, and Sofia C. Olhede
Nonlin. Processes Geophys., 24, 481–514, https://doi.org/10.5194/npg-24-481-2017, https://doi.org/10.5194/npg-24-481-2017, 2017
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This work arose from a desire to understand the nature of particle motions in turbulence. We sought a simple conceptual model that could describe such motions, then realized that this model could be applicable to an array of other problems. The basic idea is to create a string of random numbers, called a stochastic process, that mimics the properties of particle trajectories. This model could be useful in making best use of data from freely drifting instruments tracking the ocean currents.
This article is included in the Encyclopedia of Geosciences
Finn Müller-Hansen, Manoel F. Cardoso, Eloi L. Dalla-Nora, Jonathan F. Donges, Jobst Heitzig, Jürgen Kurths, and Kirsten Thonicke
Nonlin. Processes Geophys., 24, 113–123, https://doi.org/10.5194/npg-24-113-2017, https://doi.org/10.5194/npg-24-113-2017, 2017
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Deforestation and subsequent land uses in the Brazilian Amazon have huge impacts on greenhouse gas emissions, local climate and biodiversity. To better understand these land-cover changes, we apply complex systems methods uncovering spatial patterns in regional transition probabilities between land-cover types, which we estimate using maps derived from satellite imagery. The results show clusters of similar land-cover dynamics and thus complement studies at the local scale.
This article is included in the Encyclopedia of Geosciences
Jeroen Wouters, Stamen Iankov Dolaptchiev, Valerio Lucarini, and Ulrich Achatz
Nonlin. Processes Geophys., 23, 435–445, https://doi.org/10.5194/npg-23-435-2016, https://doi.org/10.5194/npg-23-435-2016, 2016
Katrin Sedlmeier, Sebastian Mieruch, Gerd Schädler, and Christoph Kottmeier
Nonlin. Processes Geophys., 23, 375–390, https://doi.org/10.5194/npg-23-375-2016, https://doi.org/10.5194/npg-23-375-2016, 2016
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Compound extreme events (e.g., simultaneous occurrence of hot and dry days) are likely to have a big impact on society. In our paper, we propose a new method to analyze the temporal succession of compound extreme events, an aspect that has been largely neglected so far. We analyze past and future changes and identify regions within Europe, which are probably susceptible to a future change in the succession of heavy precipitation and cold days in winter and hot and dry days in summer.
This article is included in the Encyclopedia of Geosciences
Sri Lakshmi Sunkara and Rama Krishna Tiwari
Nonlin. Processes Geophys., 23, 361–374, https://doi.org/10.5194/npg-23-361-2016, https://doi.org/10.5194/npg-23-361-2016, 2016
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This paper presents a new spectral approach to identifying the periodic patterns from the published Indian temperature variability records. The wavelet analysis of the SSA reconstructed time series highlights the removal of noise in the data and identifies the existence of a high-amplitude, recurrent, multidecadal scale patterns in the Indian continent, confirming the possible influences of sunspot-geomagnetic activity-ENSO through teleconnection.
This article is included in the Encyclopedia of Geosciences
Cited articles
Abello, J. and Pogel, A.: Graph Partitions and Concept Lattices, Discrete Methods in Epidemiology, AMS-DIMACS Series, 70, 115–138, 2006.
Abello, J., Hadlak, S., Schumann, H., and Schulz, H.-J.: A Modular Degree-of-Interest Specification for the Visual Analysis of Large Dynamic Networks, IEEE T. Visual. Comput. Graph., 20, 337–350, 2014.
Adar, E.: GUESS: A Language and Interface for Graph Exploration, in: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI), ACM, New York, NY, USA, 2006.
Aigner, W., Miksch, S., Schumann, H., and Tominski, C.: Visualization of Time-Oriented Data, Springer, London, UK, 2011.
Albert, R. and Barabasi, A. L.: Statistical Mechanics of Complex Networks, Rev. Modern Phys., 74, 47–97, 2002.
Alper, B., Sümengen, S., and Balcisoy, S.: Dynamic visualization of geographic networks using surface deformations with constraints, in: Proc. of the Computer Graphics International Conference (CGI), Computer Graphics Society, Petrópolis, Brazil, 2007.
Andrienko, G., Andrienko, N., Bak, P., Keim, D., and Wrobel, S.: Visual Analytics of Movement, Springer, Berlin, Heidelberg, 2013.
Bach, B., Pietriga, E., and Fekete, J.-D.: GraphDiaries: Animated Transitions and Temporal Navigation for Dynamic Networks, T. Visual. Comput. Graph., 20, 740–754, 2013.
Bastian, M., Heymann, S., and Jacomy, M.: Gephi: An Open Source Software for Exploring and Manipulating Networks, in: International AAAI Conference on Weblogs and Social Media, San Jose, California, USA, 2009.
Berezin, Y., Gozolchiani, A., Guez, O., and Havlin, S.: Stability of climate networks with time, Scient. Rep., 2, 666, 2012.
Bierkandt, R., Wenz, L., Willner, S. N., and Levermann, A.: Acclimate – a model for economic damage propagation, Part 1: basic formulation of damage transfer within a global supply network and damage conserving dynamics, Environ. Syst. Decis., 34, 507–524, 2014.
Blaas, J., Botha, C., Peters, B., Vos, F., and Post, F.: Fast and reproducible fiber bundle selection in DTI visualization, in: IEEE Visualization'05, IEEE Computer Society, Minneapolis, MN, USA, 59–64, 2005.
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., and Hwang, D. U.: Complex Networks: Structure and Dynamics, Phys. Rep., 424, 175–308, 2006.
Boers, N., Bookhagen, B., Marwan, N., Kurths, J., and Marengo, J.: Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System, Geophys. Res. Lett., 40, 4386–4392, 2013.
Boers, N., Bookhagen, B., Barbosa, H. M. J., Marwan, N., Kurths, J., and Marengo, J. A.: Prediction of extreme floods in the eastern Central Andes based on a complex networks approach, Nat. Commun., 5, 5199, 2014.
Böttger, J., Schafer, A., Lohmann, G., Villringer, A., and Margulies, D. S.: Three-Dimensional Mean-Shift Edge Bundling for the Visualization of Functional Connectivity in the Brain, IEEE T. Visual. Comput. Graph., 20, 471–480, 2014.
Brambilla, A., Carnecky, R., Peikert, R., Viola, I., and Hauser, H.: Illustrative Flow Visualization: State of the Art, Trends and Challenges, in: EuroGraphics 2012 State of the Art Reports (STARs), 75–94, https://doi.org/10.2312/conf/EG2012/stars/075-094, 2012.
Brodkorb, F., Kuijper, A., Andrienko, G., Andrienko, N., and von Landesberger, T.: Overview with Details for Exploring Geo-located Graphs on Maps, Information Visualization, IEEE Computer Society, Chicago, IL, USA, https://doi.org/10.1177/1473871615597077, 2015.
Buschmann, S., Trapp, M., and Döllner, J.: Real-Time Animated Visualization of Massive Air-Traffic Trajectories, in: Proceedings of CyberWorlds 2014, IEEE Computer Society, Santander, Spain, 172–181, 2014a.
Buschmann, S., Trapp, M., Lühne, P., and Döllner, J.: Hardware-accelerated attribute mapping for interactive visualization of complex 3D trajectories, in: Proc. of International Conference on Information Visualization Theory and Applications, Lisbon, Portugal, 355–363, 2014b.
Cui, W., Zhou, H., Qu, H., Wong, P. C., and Li, X.: Geometry-based edge clustering for graph visualization, IEEE T. Visual. Comput. Graph., 14, 1277–1284, 2008.
Davidsen, J., Grassberger, P., and Paczuski, M.: Networks of recurrent events, a theory of records, and an application to finding causal signatures in seismicity, Phys. Rev. E, 77, 066104, https://doi.org/10.1103/PhysRevE.77.066104, 2008.
de Nooy, W., Mrvar, A., and Batagelj, V.: Exploratory Social Network Analysis with Pajek, Cambridge University Press, 2005.
Díaz, J., Petit, J., and Serna, M.: A Survey of Graph Layout Problems, ACM Comput. Surv., 34, 313–356, 2002.
Donges, J. F., Zou, Y., Marwan, N., and Kurths, J.: The Backbone of the Climate Network, Europhys. Lett., 87, 48007, 2009a.
Donges, J. F., Zou, Y., Marwan, N., and Kurths, J.: Complex Networks in Climate Dynamics, Eur. Phys. J., 174, 157–179, 2009b.
Donges, J. F., Schultz, H. C. H., Marwan, N., Zou, Y., and Kurths, J.: Investigating the topology of interacting networks: theory and application to coupled climate subnetworks, Eur. Phys. J. B, 84, 635–651, 2011.
Donges, J. F., Heitzig, J., Beronov, B., Wiedermann, M., Runge, J., Feng, Q.-Y., Tupikina, L., Stolbova, V., Donner, R. V., Marwan, N., Dijkstra, H. A., and Kurths, J.: Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Preprint: arxiv.org:1507.01571 [physics.data-an], 2015a.
Donges, J. F., Petrova, I., Loew, A., Marwan, N., and Kurths, J.: How complex climate networks complement eigen techniques for the statistical analysis of climatological data, Clim. Dynam., https://doi.org/10.1007/s00382-015-2479-3, in press, 2015b.
Donner, R. V., Zou, Y., Donges, J. F., Marwan, N., and Kurths, J.: Recurrence networks – A novel paradigm for nonlinear time series analysis, New J. Phys., 12, 033205, https://doi.org/10.1088/1367-2630/12/3/033025, 2010.
Ebert-Uphoff, I. and Deng, Y.: Causal Discovery Methods for Climate Networks, Tech. Rep. GT-ME-2010-001, Georgia Institute of Technology, Atlanta, Georgia, USA, 2010.
Ellis, G. and Dix, A.: A Taxonomy of Clutter Reduction for Information Visualisation, IEEE T. Visual. Comput. Graph., 13, 1216–1223, 2007.
Elmqvist, N. and Tsigas, P.: A Taxonomy of 3D Occlusion Management for Visualization, IEEE T. Visual. Comput. Graph., 14, 1095–1109, 2008.
Ersoy, O., Hurter, C., Paulovich, F. V., Cantareiro, G., and Telea, A.: Skeleton-based edge bundling for graph visualization, IEEE T. Visual. Comput. Graph., 17, 2364–2373, 2011.
Feldhoff, J. H., Lange, S., Volkholz, J., Donges, J. F., Kurths, J., and Gerstengarbe, F.-W.: Complex networks for climate model evaluation with application to statistical versus dynamical modeling of South American climate, Clim. Dynam., 44, 1567–1581, https://doi.org/10.1007/s00382-014-2182-9, 2015.
Feng, A., Gong, Z., Wang, Q., and Feng, G.: Three-dimensional air–sea interactions investigated with bilayer networks, Theor. Appl. Climatol., 109, 635–643, 2012.
Feng, Q. Y. and Dijkstra, H.: Are North Atlantic multidecadal SST anomalies westward propagating?, Geophys. Res. Lett., 41, 541–546, 2014.
Fruchterman, T. M. J. and Reingold, E. M.: Graph drawing by force-directed placement, Softw. Pract. Exp., 21, 1129–1164, 1991.
Fuchs, R. and Hauser, H.: Visualization of Multi-variate Scientific Data, The Eurographics Association and Blackwell Publishing Ltd, Comput. Graph. Forum, 28, 1670–1690, https://doi.org/10.1111/j.1467-8659.2009.01429.x, 2009.
Furnas, G. W.: Generalized Fisheye Views, SIGCHI Bull., 17, 16–23, 1986.
Ganguly, A. R., Kodra, E. A., Agrawal, A., Banerjee, A., Boriah, S., Chatterjee, Sn., Chatterjee, So., Choudhary, A., Das, D., Faghmous, J., Ganguli, P., Ghosh, S., Hayhoe, K., Hays, C., Hendrix, W., Fu, Q., Kawale, J., Kumar, D., Kumar, V., Liao, W., Liess, S., Mawalagedara, R., Mithal, V., Oglesby, R., Salvi, K., Snyder, P. K., Steinhaeuser, K., Wang, D., and Wuebbles, D.: Toward enhanced understanding and projections of climate extremes using physics-guided data mining techniques, Nonlin. Processes Geophys., 21, 777–795, https://doi.org/10.5194/npg-21-777-2014, 2014.
Gansner, E. R., Koren, Y., and North, S.: Topological fisheye views for visualizing large graphs, IEEE T. Visual. Comput. Graph., 11, 457–468, 2005.
Gansner, E. R., Hu, Y., North, S., and Scheidegger, C.: Multilevel agglomerative edge bundling for visualizing large graphs, in: IEEE 2011 Pacific Visualization Symposium (PacificVis), Hong Kong, 187–194, 2011.
Gladisch, S., Schumann, H., and Tominski, C.: Navigation Recommendations for Exploring Hierarchical Graphs, in: Advances in Visual Computing, vol. 8034 of Lecture Notes in Computer Science, edited by: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Li, B., Porikli, F., Zordan, V., Klosowski, J., Coquillart, S., Luo, X., Chen, M., and Gotz, D., Springer, Berlin, Heidelberg, 36–47, 2013.
Guez, O., Gozolchiani, A., Berezin, Y., Brenner, S., and Havlin, S.: Climate network structure evolves with North Atlantic Oscillation phases, Europhys. Lett., 98, 38006, 2012.
Guez, O., Gozolchiani, A., Berezin, Y., Wang, Y., and Havlin, S.: Global climate network evolves with North Atlantic Oscillation phases: Coupling to Southern Pacific Ocean, Europhys. Lett., 103, 68006, 2013.
Hadlak, S., Schulz, H.-J., and Schumann, H.: In Situ Exploration of Large Dynamic Networks, IEEE T. Visual. Comput. Graph., 17, 2334–2343, 2011.
Hadlak, S., Schumann, H., and Schulz, H.-J.: A Survey of Multi-faceted Graph Visualization, State-of-the-Art Report at EuroVis'15, Cagliari, Sardinia, Italy, 1–20, 2015.
Heitzig, J., Donges, J. F., Zou, Y., Marwan, N., and Kurths, J.: Node-weighted measures for complex networks with spatially embedded, sampled, or differently sized nodes, Eur. Phys. J. B, 85, 38, 2012.
Hlinka, J., Hartman, D., Jajcay, N., Vejmelka, M., Donner, R., Marwan, N., Kurths, J., and Paluš, M.: Regional and inter-regional effects in evolving climate networks, Nonlin. Processes Geophys., 21, 451–462, https://doi.org/10.5194/npg-21-451-2014, 2014.
Holme, P. and Saramäki, J.: Temporal networks, Phys. Rep., 519, 97–125, 2012.
Holten, D.: Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data, IEEE T. Visual. Comput. Graph., 12, 741–748, 2006.
Holten, D. and van Wijk, J. J.: Force-Directed Edge Bundling for Graph Visualization, Comput. Graph. Forum, 28, 983–990, 2009.
Hu, P. and Lau, W. C.: A Survey and Taxonomy of Graph Sampling, CoRR, abs/1308.5865, arXiv:1308.5865 [cs.SI], 2013.
Hu, Y. and Shi, L.: Visualizing large graphs, Wiley Interdis. Rev.: Comput. Stat., 7, 115–136, 2015.
Hurter, C., Telea, A., and Ersoy, O.: Moleview: An attribute and structure-based semantic lens for large element-based plots, IEEE. T. Visual. Comput. Graph., 17, 2600–2609, 2011.
Hurter, C., Ersoy, O., and Telea, A.: Graph bundling by kernel density estimation, Comput. Graph. Forum, 31, 865–874, 2012.
Hurter, C., Ersoy, O., Fabrikant, S., Klein, T., and Telea, A.: Bundled Visualization of DynamicGraph and Trail Data, IEEE. T. Visual. Comput. Graph., 20, 1141–1157, 2014.
Iwayama, K., Hirata, Y., Takahashi, K., Watanabe, K., Aihara, K., and Suzuki, H.: Characterizing global evolutions of complex systems via intermediate network representations, Scient. Rep., https://doi.org/10.1038/srep00423, in press, 2012.
Jacomy, M., Venturini, T., Heymann, S., and Bastian, M.: ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software, PLoS ONE, 9, e98679, https://doi.org/10.1371/journal.pone.0098679, 2014.
Keim, D., Andrienko, G., Fekete, J.-D., Görg, C., Kohlhammer, J., and Melancon, G.: Visual Analytics: Definition, Process, and Challenges, in: Information Visualization, vol. 4950 of Lecture Notes in Computer Science, edited by: Kerren, A., Stasko, J., Fekete, J.-D., and North, C., Springer, Berlin, Heidelberg, 154–175, 2008.
Keim, D. A., Kohlhammer, J., Ellis, G., and Mansmann, F. (Eds.): Mastering the Information Age – Solving Problems with Visual Analytics, Eurographics, Eurographics Association, Goslar, Germany, 2010.
Kistler, R., Kalnay, E., Collins, W., Saha, S., White, G., Woollen, J., Chelliah, M., Ebisuzaki, W., Kanamitsu, M., Kousky, V., Dool, H. V. D., Jenne, R., and Fiorino, M.: The NCEP–NCAR 50-Year Reanalysis: Monthly Means CD–ROM and Documentation, B. Am. Meteorol. Soc., 82, 247–268, 2001.
Krüger, R., Thom, D., Wörner, M., Bosch, H., and Ertl, T.: TrajectoryLenses – A Set-based Filtering and Exploration Technique for Long-term Trajectory Data, Comput. Graph. Forum, 32, 451–460, 2013.
Lambert, A., Bourqui, R., and Auber, D.: Winding roads: Routing edges into bundles, Comput. Graph. Forum, 29, 853–862, 2010.
Lange, S., Donges, J. F., Volkholz, J., and Kurths, J.: Local difference measures between complex networks for dynamical system model evaluation, PLoS ONE, 10, e0118088, https://doi.org/10.1371/journal.pone.0118088, 2015.
Lehnertz, K., Ansmann, G., Bialonski, S., Dickten, H., Geier, C., and Porz, S.: Evolving networks in the human epileptic brain, Physica D, 267, 7–15, 2014.
Ludescher, J., Gozolchiani, A., Bogachev, M. I., Bunde, A., Havlin, S., and Schellnhuber, H. J.: Improved El Niño forecasting by cooperativity detection, P. Natl. Acad. Sci. USA, 110, 11742–11745, 2013.
Ludescher, J., Gozolchiani, A., Bogachev, M. I., Bunde, A., Havlin, S., and Schellnhuber, H. J.: Very early warning of next El Niño, P. Natl. Acad. Sci. USA, 111, 2064–2066, 2014.
Malik, N., Marwan, N., and Kurths, J.: Spatial structures and directionalities in Monsoonal precipitation over South Asia, Nonlin. Processes Geophys., 17, 371–381, https://doi.org/10.5194/npg-17-371-2010, 2010.
Malik, N., Bookhagen, B., Marwan, N., and Kurths, J.: Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks, Clim. Dynam., 39, 971–987, 2012.
Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J. F. B., Stouffer, R. J., and Taylor, K. E.: The WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research, B. Am. Meteorol. Soc., 88, 1383, https://doi.org/10.1175/BAMS-88-9-1383, 2007.
Menck, P. J., Heitzig, J., Kurths, J., and Schellnhuber, H. J.: How dead ends undermine power grid stability, Nat. Commun., 5, 3969, https://doi.org/10.1038/ncomms4969, 2014.
Molkenthin, N., Rehfeld, K., Marwan, N., and Kurths, J.: Networks from flows – from dynamics to topology, Scient. Rep., 4, 4119, https://doi.org/10.1038/srep04119, 2014.
New, M., Lister, D., Hulme, M., and Makin, I.: A high-resolution data set of surface climate over global land areas, Clim. Res., 21, 1–25, 2002.
Newman, M. E. J.: The Structure and Function of Complex Networks, SIAM Rev., 45, 167–256, 2003.
Nicholson, S.: The nature of rainfall variability over Africa on time scales of decades to millenia, Global Planet. Change, 26, 137–158, 2000.
Nocaj, A., Ortmann, M., and Brandes, U.: Untangling Hairballs, in: Graph Drawing, vol. 8871 of Lecture Notes in Computer Science, edited by: Duncan, C. and Symvonis, A., Springer, Berlin, Heidelberg, 101–112, 2014.
Petrova, I.: Structural interrelationships between evaporation and precipitation: Application of complex networks to satellite based fields, Master's thesis, University of Hamburg, 2012.
Phan, D., Xiao, L., Yeh, R., Hanrahan, P., and Winograd, T.: Flow Map Layout, in: Proc. of IEEE Symposium on Information Visualization, edited by: Stasko, J. and Ward, M. O., IEEE Computer Society, Minneapolis, Minnesota, USA, 219–224, 2005.
Phillips, J. D., Schwanghart, W., and Heckmann, T.: Graph theory in the geosciences, Earth-Sci. Rev., 143, 147–160, 2015.
Radebach, A., Donner, R. V., Runge, J., Donges, J. F., and Kurths, J.: Disentangling different types of El Niño episodes by evolving climate network analysis, Phys. Rev. E, 88, 052807, https://doi.org/10.1103/PhysRevE.88.052807, 2013.
Rehfeld, K., Marwan, N., Breitenbach, S. F. M., and Kurths, J.: Late Holocene Asian summer monsoon dynamics from small but complex networks of paleoclimate data, Clim. Dynam., 41, 3–19, 2012.
Rheinwalt, A., Marwan, N., Kurths, J., Werner, P., and Gerstengarbe, F.-W.: Boundary effects in network measures of spatially embedded networks, Europhys. Lett., 100, 28002, https://doi.org/10.1209/0295-5075/100/28002, 2012.
Rodgers, P.: Graph Drawing Techniques for Geographic Visualization, in: Exploring Geovisualization, edited by: Dykes, J., MacEachren, A. M., and Kraak, M.-J., Elsevier, Amsterdam, 143–158,2005.
Rozenblat, C. and Melançon, G. (Eds.): Methods for Multilevel Analysis and Visualisation of Geographical Networks, in: vol. 11 of Methodos Series, Springer, Dordrecht, 2013.
Runge, J., Heitzig, J., Petoukhov, V., and Kurths, J.: Escaping the Curse of Dimensionality in Estimating Multivariate Transfer Entropy, Phys. Rev., Lett., 108, 258701, https://doi.org/10.1103/PhysRevLett.108.258701, 2012.
Schulz, H.-J., Hadlak, S., and Schumann, H.: Point-Based Visualization for Large Hierarchies, IEEE T. Visual. Comput. Graph., 17, 598–611, 2011.
Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., Tignor, M., and Miller, H. (Eds.): IPCC, 2007: Climate Change 2007: The Physical Science Basis, in: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New York, NY, USA, 2007.
Steinhaeuser, K. and Tsonis, A. A.: A climate model intercomparison at the dynamics level, Clim. Dynam., 42, 1665–1670, 2013.
Steinhaeuser, K., Chawla, N. V., and Ganguly, A. R.: Complex networks as a unified framework for descriptive analysis and predictive modeling in climate science, Statistical Analysis and Data Mining, ASA Data Sci. J., 4, 497–511, 2011.
Stolbova, V., Martin, P., Bookhagen, B., Marwan, N., and Kurths, J.: Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka, Nonlin. Processes Geophys., 21, 901–917, https://doi.org/10.5194/npg-21-901-2014, 2014.
Tantet, A. and Dijkstra, H. A.: An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature, Earth Syst. Dynam., 5, 1–14, https://doi.org/10.5194/esd-5-1-2014, 2014.
Telea, A. and Ersoy, O.: Image-Based Edge Bundles: Simplified Visualization of Large Graphs, Comput. Graph. Forum, 29, 843–852, 2010.
Thomas, J. J. and Cook, K. A.: Illuminating the path: The research and development agenda for visual analytics, IEEE Computer Society Press, National Visualization and Analytics Center, 2005.
Tominski, C., Abello, J., and Schumann, H.: CGV – An Interactive Graph Visualization System, Comput. Graph., 33, 660–678, 2009.
Tominski, C., Donges, J. F., and Nocke, T.: Information Visualization in Climate Research, in: Proceedings of the International Conference Information Visualisation (IV), IEEE Computer Society, London, 298–305, 2011.
Tominski, C., Gladisch, S., Kister, U., Dachselt, R., and Schumann, H.: A Survey on Interactive Lenses in Visualization, in: EuroVis State-of-the-Art Reports, Eurographics Association, Swansea, UK, 43–62, 2014.
Tsonis, A. and Swanson, K.: Topology and Predictability of El Niño and La Niña Networks, Phys. Rev. Lett., 100, 228502, https://doi.org/10.1103/PhysRevLett.100.228502, 2008.
Tsonis, A. A. and Roebber, P. J.: The Architecture of the Climate Network, Physica A, 333, 497–504, 2004.
Tsonis, A. A., Swanson, K., and Kravtsov, S.: A new dynamical mechanism for major climate shifts, Geophys. Res. Lett., 34, l13705, https://doi.org/10.1029/2007GL030288, 2007.
Tsonis, A. A., Swanson, K. L., and Wang, G.: On the Role of Atmospheric Teleconnections in Climate, J. Climate, 21, 2990–3001, 2008.
Tupikina, L., Rehfeld, K., Molkenthin, N., Stolbova, V., Marwan, N., and Kurths, J.: Characterizing the evolution of climate networks, Nonlin. Processes Geophys., 21, 705–711, https://doi.org/10.5194/npg-21-705-2014, 2014.
van der Mheen, M., Dijkstra, H. A., Gozolchiani, A., den Toom, M., Feng, Q., Kurths, J., and Hernandez-Garcia, E.: Interaction network based early warning indicators for the Atlantic MOC collapse, Geophys. Res. Lett., 40, 2714–2719, 2013.
van Ham, F. and Perer, A.: "Search, Show Context, Expand on Demand": Supporting Large Graph Exploration with Degree-of-Interest, IEEE T. Visual. Comput. Graph., 15, 953–960, 2009.
van Ham, F. and Wattenberg, M.: Centrality Based Visualization of Small World Graphs, Comput. Graph. Forum, 27, 975–982, 2008.
von Landesberger, T., Kuijper, A., Schreck, T., Kohlhammer, J., van Wijk, J., Fekete, J.-D., and Fellner, D.: Visual Analysis of Large Graphs: State-of-the-Art and Future Research Challenges, Comput. Graph. Forum, 30, 1719–1749, 2011.
von Storch, H. and Zwiers, F. W.: Statistical Analysis in Climate Research, Cambridge University Press, 1999.
Wallace, J. and Gutzler, D.: Teleconnections in the Geopotential Height Field During the Northern Hemisphere Winter, Mon. Weather Rev., 109, 784–812, 1981.
Wang, Y., Gozolchiani, A., Ashkenazy, Y., Berezin, Y., Guez, O., and Havlin, S.: Dominant Imprint of Rossby Waves in the Climate Network, Phys. Rev. Lett., 111, 138501, https://doi.org/10.1103/PhysRevLett.111.138501, 2013.
Wiedermann, M., Donges, J. F., Heitzig, J., and Kurths, J.: Node-weighted interacting network measures improve the representation of real-world complex systems, Europhys. Lett., 102, 28007, https://doi.org/10.1209/0295-5075/102/28007, 2013.
Wiedermann, M., Donges, J. F., Handorf, D., Kurths, J., and Donner, R. V.: Hierarchical structures in Northern Hemispheric extratropical winter ocean–atmosphere interactions, arXiv preprint arXiv:1506.06634, 2015.
Withall, M., Phillips, I., and Parish, D.: Network visualisation: a review, IET Commun., 1, 365–372, 2007.
Wolff, A.: Graph Drawing and Cartography, in: Handbook of Graph Drawing and Visualization, edited by: Tamassia, R., CRC Press, Boca Raton, FL, USA, 697–736, 2013.
Wong, P. C., Shen, H.-W., Leung, R., Hagos, S., Lee, T.-Y., Tong, X., and Lu, K.: Visual analytics of large-scale climate model data, in: IEEE 4th Symposium on Large Data Analysis and Visualization (LDAV) 2014, Paris, France, 85–92, 2014.
Yamasaki, K., Gozolchiani, A., and Havlin, S.: Climate Networks Around the Globe are Significantly Affected by El Niño, Phys. Rev. Lett., 100, 228501, https://doi.org/10.1103/PhysRevLett.100.228501, 2008.
Zemp, D. C., Schleussner, C.-F., Barbosa, H. M. J., van der Ent, R. J., Donges, J. F., Heinke, J., Sampaio, G., and Rammig, A.: On the importance of cascading moisture recycling in South America, Atmos. Chem. Phys., 14, 13337–13359, https://doi.org/10.5194/acp-14-13337-2014, 2014a.
Zemp, D., Wiedermann, M., Kurths, J., Rammig, A., and Donges, J. F.: Node-weighted measures for complex networks with directed and weighted edges for studying continental moisture recycling, Europhys. Lett., 107, 58005, https://doi.org/10.1209/0295-5075/107/58005, 2014b.
Zhang, Q., Eagleson, R., and Peters, T. M.: Volume Visualization: A Technical Overview with a Focus on Medical Applications, J. Digit. Imag., 24, 640–664, 2011.
Zhu, X. and Guo, D.: Mapping Large Spatial Flow Data with Hierarchical Clustering, Trans. GIS, 18, 421–435, 2014.
Zou, Y., Donges, J. F., and Kurths, J.: Recent Advances in Complex Climate Network Analysis, Complex Syst. Complex. Sci., 8, 27–38, 2011.
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The paper reviews the available visualisation techniques and tools for the visual analysis of geo-physical climate networks. The results from a questionnaire with experts from non-linear physics are presented, and the paper surveys recent developments from information visualisation and cartography with respect to their applicability for visual climate network analytics. Several case studies based on own solutions illustrate the potentials of state-of-the-art network visualisation technology.
The paper reviews the available visualisation techniques and tools for the visual analysis of...
