Skip to main content Accessibility help
Hostname: page-component-797576ffbb-xg4rj Total loading time: 0 Render date: 2023-12-10T05:18:33.339Z Has data issue: false Feature Flags: { "corePageComponentGetUserInfoFromSharedSession": true, "coreDisableEcommerce": false, "useRatesEcommerce": true } hasContentIssue false


Published online by Cambridge University Press:  15 February 2019

Henk A. Dijkstra
Universiteit Utrecht, The Netherlands
Emilio Hernández-García
Universitat de les Illes Balears, Spain
Cristina Masoller
Universitat Politècnica de Catalunya, Spain
Marcelo Barreiro
Universidad de la Republica, Montevideo, Uruguay
Get access
Networks in Climate , pp. 216 - 236
Publisher: Cambridge University Press
Print publication year: 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Achuthavarier, D., Krishnamurthy, V., Kirtman, B. P., and Huang, B. (2012). Role of the Indian Ocean in the ENSO–Indian summer monsoon teleconnection in the NCEP climate forecast system. Journal of Climate, 25(7), 24902508.CrossRefGoogle Scholar
Affenzeller, M., Wagner, S., Winkler, S., and Beham, A. (2018). Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications. Chapman and Hall/CRC.Google Scholar
Albert, R. and Barabási, A. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74, 4796.CrossRefGoogle Scholar
Alessandri, A., Borrelli, A., Cherchi, A., et al. (2014). Prediction of Indian summer monsoon onset using dynamical sub-seasonal forecasts: effects of realistic initialization of the atmosphere. Monthly Weather Review, 143, 778793.CrossRefGoogle Scholar
Alley, R. B., Marotzke, J., Nordhaus, W. D., et al. (2003). Abrupt climate change. Nature, 299, 20052010.Google ScholarPubMed
Almeida, R. A. F. de, Nobre, P., Haarsma, R. J., and Campos, E. J. D. (2007). Negative ocean-atmosphere feedback in the South Atlantic Convergence Zone. Geophysical Research Letters, 34(18), L18809.CrossRefGoogle Scholar
Altman, N. and Krzywinski, M. (2017). Interpreting P values. Nature Methods, 14, 213.CrossRefGoogle Scholar
Ananthakrishnan, R. and Soman, M. K. (1990). The onset of the southwest monsoon in 1990. Current Science, 61(7), 447453.Google Scholar
Andersen, T., Carstensen, J., Hernández-García, E., and Duarte, C. M. (2009). Ecological thresholds and regime shifts: approaches to identification. Trends in Ecology & Evolution, 24(1), 4957.CrossRefGoogle ScholarPubMed
Andronova, N. and Schlesinger, M. (2000). Causes of global temperature changes during the 19th and 20th centuries. Geophysical Research Letters, 27(14), 21372140.CrossRefGoogle Scholar
Arizmendi, F. and Barreiro, M. (2017). ENSO teleconnections in the southern hemisphere: a climate network view. Chaos, 27(9), 093109.CrossRefGoogle ScholarPubMed
Arizmendi, F., Marti, A., and Barreiro, M. (2014). Evolution of atmospheric connectivity in the 20th century. Nonlinear Processes in Geophysics, 21, 825839.CrossRefGoogle Scholar
Arizmendi, F., Barreiro, M. B., and Masoller, C. (2017). Identifying large-scale patterns of unpredictability and response to insolation in atmospheric data. Scientific Reports, 7, 45676.CrossRefGoogle ScholarPubMed
Ashkenazy, Y., Feliks, Y., Gildor, H., and Tziperman, E. (2008). Asymmetry of daily temperature records. Journal of the Atmospheric Sciences, 65(10), 33273336.CrossRefGoogle Scholar
AVISO (2013). SSALTO/DUACS User Handbook: (M)SLA and (M)ADT Near-Real Time and Delayed Time Products. Centre national d’études spatiales.Google Scholar
Baccala, L. A. and Sameshima, K. (2001). Partial directed coherence: a new concept in neural structure determination. Biological Cybernetics, 84, 463.CrossRefGoogle ScholarPubMed
Balasis, G., Donner, R. V., Potirakis, S. M., et al. (2013). Statistical mechanics and information-theoretic perspectives on complexity in the earth system. Entropy, 15(11), 48444888.CrossRefGoogle Scholar
Bandt, C. and Pompe, B. (2002). Permutation entropy: a natural complexity measure for time series. Physical Review Letters, 88(17), 174102.CrossRefGoogle ScholarPubMed
Banzhaf, W., Nordin, P., Keller, R. E., and Francone, F. D. (1998). Genetic Programming: An Introduction, volume 1. Morgan Kaufmann.CrossRefGoogle Scholar
Barabási, A.-L. (2009). Scale-free networks: a decade and beyond. Science, 325(5939), 412413.CrossRefGoogle ScholarPubMed
Barabási, A.-L. and Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509512.Google ScholarPubMed
Barnosky, A. D., Hadly, E. A., Bascompte, J., et al. (2012). Approaching a state shift in Earth’s biosphere. Nature, 486(7401), 5258.CrossRefGoogle ScholarPubMed
Barreiro, M., Chang, P., and Saravanan, R. (2002). Variability of the South Atlantic Convergence Zone as simulated by an atmospheric general circulation model. Journal of Climate, 15, 745.2.0.CO;2>CrossRefGoogle Scholar
Barreiro, M., Chang, P., and Saravanan, R. (2005). Simulated precipitation response to SST forcing and potential predictability in the region of the South Atlantic Convergence Zone. Climate Dynamics, 24, 105114.CrossRefGoogle Scholar
Barreiro, M., Marti, A. C., and Masoller, C. (2011). Inferring long memory processes in the climate network via ordinal pattern analysis. Chaos, 21(1), 013101.CrossRefGoogle ScholarPubMed
Barros, V., Doyle, M., González, M., et al. (2002). Climate variability over subtropical South America and the South American monsoon: a review. Meteorologica, 27(1–2), 3357.Google Scholar
Barsugli, J. J. and Battisti, D. S. (1998). The basic effects of atmosphere–ocean thermal coupling on midlatitude variability. Journal of the Atmospheric Sciences, 55, 477– 493.2.0.CO;2>CrossRefGoogle Scholar
Barthélemy, M. (2011). Spatial networks. Physics Reports, 499(1–3), 1101.CrossRefGoogle Scholar
Bathiany, S., Dijkstra, H., Crucifix, M., et al. (2016). Beyond bifurcation: using complex models to understand and predict abrupt climate change. Dynamics and Statistics of the Climate System, 1(1), dzw004.CrossRefGoogle Scholar
Bauer, P., Thorpe, A., and Brunet, G. (2015). The quiet revolution of numerical weather prediction. Nature, 525(7567), 4755.CrossRefGoogle ScholarPubMed
Benestad, R. E., Sutton, R. T., and Anderson, D. L. T. (2002). The effect of El Niño on intraseasonal Kelvin waves. Quarterly Journal of the Royal Meteorological Society, 128(582), 12771291.CrossRefGoogle Scholar
Berbery, E. H. and Vera, C. S. (1996). Characteristics of the Southern Hemisphere winter storm track with filtered and unfiltered data. Journal of the Atmospheric Sciences, 53(3), 468481.2.0.CO;2>CrossRefGoogle Scholar
Berezin, Y., Gozolchiani, A., Guez, O., and Havlin, S. (2012). Stability of climate networks with time. Scientific Reports, 2, 18.CrossRefGoogle ScholarPubMed
Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.Google Scholar
Black, E., Blackburn, M., Harrison, G., Hoskins, B., and Methven, J. (2004). Factors contributing to the summer 2003 European heatwave. Weather, 59, 217223.CrossRefGoogle Scholar
Blayo, É., Bocquet, M., Cosme, E., and Cugliandolo, L. F. (2014). Advanced Data Assimilation for Geosciences: Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012. Oxford University Press.CrossRefGoogle Scholar
Boers, N., Bookhagen, B., Barbosa, H. M. J., et al. (2014). Prediction of extreme floods in the eastern Central Andes based on a complex networks approach. Nature Communications, 5, 5199.CrossRefGoogle ScholarPubMed
Boffetta, G., Cencini, M., Falcioni, M., and Vulpiani, A. (2002). Predictability: a way to characterize complexity. Physics Reports, 356(6), 367474.CrossRefGoogle Scholar
Bombardi, R. J., Carvalho, L. M. V., Jones, C., and Reibota, M. S. (2013). Precipitation over eastern South America and the South Atlantic Sea surface temperature during neutral ENSO periods. Climate Dynamics, 42, 15531568.CrossRefGoogle Scholar
Boos, W. R. and Kuang, Z. (2010). Dominant control of the South Asian monsoon by orographic insulation versus plateau heating. Nature, 463(7278), 218222.CrossRefGoogle ScholarPubMed
Booth, B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., and Bellouin, N. (2012). Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability. Nature, 484(7393), 228232.CrossRefGoogle ScholarPubMed
Bracco, A., Kucharski, F., Kallummal, R., and Molteni, F. (2004). Internal variability, external forcing and climate trends in multi-decadal AGCM ensembles. Climate Dynamics, 23(6), 659678.CrossRefGoogle Scholar
Bradley, E. and Kantz, H. (2015). Nonlinear time-series analysis revisited. Chaos, 25, 097610.CrossRefGoogle ScholarPubMed
Bretherton, F. (1988). Earth System Science: A Closer View. NASA.Google Scholar
Broecker, W. S. (2006). Abrupt climate change revisited. Global and Planetary Change, 54(3), 211215.CrossRefGoogle Scholar
Brovkin, V. and Claussen, M. (1998). On the stability of the atmosphere–vegetation system in the Sahara/Sahel region. Journal of Climate, 103(D24), 3161332624.Google Scholar
Bryan, F. O. (1986). High-latitude salinity effects and interhemispheric thermohaline circulations. Nature, 323, 301304.CrossRefGoogle Scholar
Budyko, M. I. (1969). The effect of solar radiations on the climate on the Earth. Tellus, 21, 611619.CrossRefGoogle Scholar
Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G., and Saba, V. (2018). Observed fingerprint of a weakening Atlantic Ocean overturning circulation. Nature, 556, 191– 196.CrossRefGoogle ScholarPubMed
Cai, W. and Cowan, T. (2009). La Niña Modoki impacts Australia autumn rainfall variability. Geophysical Research Letters, 36(12), L12805.CrossRefGoogle Scholar
Caldarelli, G. (2007). Scale-Free Networks: Complex Webs in Nature and Technology. Oxford University Press.CrossRefGoogle Scholar
Carvalho, L. M. V., Jones, C., and Liebmann, B. (2002). Extreme precipitation events in southeastern South America and large-scale convective patterns in the South Atlantic convergence zone. Journal of Climate, 15, 23772394.2.0.CO;2>CrossRefGoogle Scholar
Carvalho, L. M. V., Jones, C., and Liebmann, B. (2004). The South Atlantic Convergence Zone: intensity, form, persistence, and relationships with intraseasonal to interannual activity and extreme rainfall. Journal of Climate, 17, 88107.2.0.CO;2>CrossRefGoogle Scholar
Castiglione, P., Falcioni, M., Lesne, A., and Vulpiani, A. (2010). Chaos and Coarse Graining in Statistical Mechanics. Cambridge University Press.Google Scholar
Cellucci, C. J., Albano, A. M., and Rapp, P. E. (2005). Statistical validation of mutual information calculations: comparison of alternative numerical algorithms. Physical Review E, 71, 066208.CrossRefGoogle ScholarPubMed
Cencini, M., Cecconi, F., and Vulpiani, A. (2010). Chaos: From Simple Models to Complex Systems. World Scientific.Google Scholar
Chaikin, P. and Lubensly, T. (1995). Principles of Condensed Matter Physics. Cambridge University Press.CrossRefGoogle Scholar
Chan, A., Dehne, F., and Taylor, R. (2005). CGMgraph/CGMlib: implementing and testing CGM graph algorithms on PC clusters and shared memory machines. International Journal of High Performance Computing Applications, 19, 8197.CrossRefGoogle Scholar
Chang, E. (1993). Downstream development of baroclinic waves as inferred from regression analysis. Journal of the Atmospheric Sciences, 50, 20382053.2.0.CO;2>CrossRefGoogle Scholar
Chang, E. K. M. (1999). Characteristics of wave packets in the upper troposphere. Part II: seasonal and hemispheric variations. Journal of the Atmospheric Sciences, 56(11), 17291747.2.0.CO;2>CrossRefGoogle Scholar
Chang, E. K. M. and Yu, D. B. (1999). Characteristics of wave packets in the upper troposphere. Part I: Northern Hemisphere winter. Journal of the Atmospheric Sciences, 56(11), 17081728.2.0.CO;2>CrossRefGoogle Scholar
Chaves, R. R. and Nobre, P. (2004). Interactions between sea surface temperature over the South Atlantic Ocean and the South Atlantic Convergence Zone. Geophysical Research Letters, 31, L03204–1.CrossRefGoogle Scholar
Chelton, D. B. and Schlax, M. (1996). Global observations of oceanic Rossby waves. Science, 272, 234238.CrossRefGoogle Scholar
Chelton, D. B., Schlax, M., Lyman, J., and Johnson, G. (2003). Equatorially trapped Rossby waves in the presence of meridionally sheared baroclinic flow in the Pacific Ocean. Progress in Oceanography, 56, 323380.CrossRefGoogle Scholar
Chen, D., Cane, M. A., Kaplan, A., Zebiak, S. E., and Huang, D. (2004). Predictability of El Niño over the past 148 years. Nature, 428(6984), 733736.CrossRefGoogle ScholarPubMed
Choudhury, A. D. and Krishnan, R. (2011). Dynamical response of the South Asian monsoon trough to latent heating from stratiform and convective precipitation. Journal of the Atmospheric Sciences, 68(6), 13471363.CrossRefGoogle Scholar
Cimponeriu, L., Rosenblum, M., and Pikovsky, A. (2004). Estimation of delay in coupling from time series. Physical Review E, 70, 046213.CrossRefGoogle ScholarPubMed
Clarke, A. J. (2008). An Introduction to the Dynamics of El Niño the Southern Oscillation. Elsevier.Google Scholar
Claussen, M., Mysak, L., Weaver, A., et al. (2002). Earth system models of intermediate complexity: closing the gap in the spectrum of climate system models. Climate Dynamics, 18, 579586.Google Scholar
Clement, A. C. and Peterson, L. C. (2008). Mechanisms of abrupt climate change of the last glacial period. Reviews of Geophysics, 46, RG4002.CrossRefGoogle Scholar
Collins, M., Knutti, R., Arblaster, J., et al. (2013). Long-term climate change: projections, commitments and irreversibility. In Stocker, T., Qin, D., Plattner, G.-K., editors, Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, pages 10291136. University of Cambridge Press.Google Scholar
Cover, T. M. and Thomas, J. A. (2006). Elements of Information Theory, 2nd ed. Wiley.Google Scholar
Csardi, G. and Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, 1695.Google Scholar
Cunningham, S. A., Kanzow, T., Rayner, D., et al. (2007). Temporal variability of the Atlantic Meridional Overturning Circulation at 26.5 N. Science, 317(5840), 935938.CrossRefGoogle ScholarPubMed
Da Costa, E. D. and Colin de Verdiere, A. C. (2004). The 7.7 year North Atlantic oscillation. Quarterly Journal of the Royal Meteorological Society, 128, 797817.CrossRefGoogle Scholar
Dakos, V., Scheffer, M., van Nes, E. H., et al. (2008). Slowing down as an early warning signal for abrupt climate change. PNAS, 105(38), 1430814312.CrossRefGoogle ScholarPubMed
Dakos, V., van Nes, E. H., Donangelo, R., Fort, H., and Scheffer, M. (2010). Spatial correlation as leading indicator of catastrophic shifts. Theoretical Ecology, 3(3), 163– 174.CrossRefGoogle Scholar
Dakos, V., Kéfi, S., Rietkerk, M., van Nes, E. H., and Scheffer, M. (2011). Slowing down in spatially patterned ecosystems at the brink of collapse. The American Naturalist, 177(6), 154166.CrossRefGoogle Scholar
Dakos, V., Carpenter, S. R., van Nes, E. H., and Scheffer, M. (2015). Resilience indicators: prospects and limitations for early warnings of regime shifts. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 370(1659), 20130263.CrossRefGoogle Scholar
Dansgaard, W. (1993). Evidence for general instability of past climate from a 250-kyr ice-core record. Nature, 364, 218220.CrossRefGoogle Scholar
Das, S., Mitra, A. K., Iyengar, G. R., and Singh, J. (2002). Skill of medium-range forecasts over the Indian Monsoon region using different parameterizations of deep convection. Weather and Forecasting, 17(1992), 11941210.2.0.CO;2>CrossRefGoogle Scholar
Daubechies, I. (1992). Ten Lectures on Wavelets. SIAM.CrossRefGoogle Scholar
De Niet, A., Wubs, F., van Scheltinga, A. T., and Dijkstra, H. A. (2007). A tailored solver for bifurcation analysis of ocean–climate models. Journal of Computational Physics, 227(1), 654679.CrossRefGoogle Scholar
DeAngelis, D. L., Post, W. M., and Travis, C. C. (1986). Positive Feedback in Natural Systems. Springer-Verlag.CrossRefGoogle Scholar
Dee, D., Uppala, S., Simmons, , et al. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553597.CrossRefGoogle Scholar
Delcroix, T., Boulanger, J.-P., Masia, F., and Menkes, C. (1994). Geosat-derived sea level and surface current anomalies in the equatorial Pacific during the 1986-1989 El Niño and La Niña. Journal of Geophysical Research, 99, 2509325107.CrossRefGoogle Scholar
Dellnitz, M., Hessel-von Molo, M., Metzner, P., Preis, R., and Schütte, C. (2006). Graph algorithms for dynamical systems. In Mielke, A., editor, Analysis, Modeling and Simulation of Multiscale Problems, pages 619645. Springer Verlag.CrossRefGoogle Scholar
Dellnitz, M., Froyland, G., Horenkamp, C., Padberg-Gehle, K., and Sen Gupta, A. (2009). Seasonal variability of the subpolar gyres in the Southern Ocean: a numerical investigation based on transfer operators. Nonlinear Processes in Geophysics, 16(6), 655663.CrossRefGoogle Scholar
Dellnitz, M., Froyland, G., Horenkamp, C., Padberg-Gehle, K., and Sen Gupta, A. (2009b). Seasonal variability of the subpolar gyres in the southern ocean: a numerical investigation based on transfer operators. Nonlinear Processes in Geophysics, 16(6), 655663.CrossRefGoogle Scholar
Delworth, T. L. and Mann, M. E. (2000). Observed and simulated multidecadal variability in the Northern Hemisphere. Climate Dynamics, 16, 661676.CrossRefGoogle Scholar
Den Toom, M., Dijkstra, H. A., and Wubs, F. W. (2011). Spurious multiple equilibria introduced by convective adjustment. Ocean Modelling, 38(1–2), 126137.CrossRefGoogle Scholar
Deser, C. and Blackmon, M. L. (1993). Surface climate variations over the North Atlantic Ocean during winter: 1900–1989. Journal of Climate, 6, 17431753.2.0.CO;2>CrossRefGoogle Scholar
Deza, J. I. (2015). Climate networks constructed by using information-theoretic measures and ordinal time-series analysis. PhD thesis, Universitat Politècnica de Catalunya.Google Scholar
Deza, J. I., Barreiro, M., and Masoller, C. (2013). Inferring interdependencies in climate networks constructed at inter-annual, intra-season and longer time scales. The European Physical Journal Special Topics, 222(2), 511523.CrossRefGoogle Scholar
Deza, J., Masoller, C., and Barreiro, M. (2014). Distinguishing the effects of internal and forced atmospheric variability in climate networks. Nonlinear Processes in Geophysics, 21, 617631.CrossRefGoogle Scholar
Deza, J., Barreiro, M., and Masoller, C. (2015). Assessing the direction of climate interactions by means of complex networks and information theoretic tools. Chaos, 25, 033105.CrossRefGoogle ScholarPubMed
Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269271.CrossRefGoogle Scholar
Dijkstra, H. A. (2006). Interaction of SST modes in the North Atlantic Ocean. Journal of Physical Oceanography, 36, 286299.CrossRefGoogle Scholar
Dijkstra, H. A. (2013). Nonlinear Climate Dynamics. Cambridge University Press.CrossRefGoogle Scholar
Dijkstra, H. A. and Ghil, M. (2005). Low-frequency variability of the large-scale ocean circulation: a dynamical systems approach. Reviews of Geophysics, 43(3), RG3002.CrossRefGoogle Scholar
Dijkstra, H. A., Frankcombe, L. M., and Von der Heydt, A. S. (2008). A stochastic dynamical systems view of the Atlantic Multidecadal Oscillation. Philosophical Transactions of the Royal Society A, 366(1875), 25432558.CrossRefGoogle ScholarPubMed
Dobson, I., Carreras, B. A., Lynch, V. E., and Newman, D. E. (2007). Complex systems analysis of series of blackouts: cascading failure, critical points, and self-organization. Chaos, 17(2), 026103.CrossRefGoogle ScholarPubMed
Donangelo, R., Fort, H., Dakos, V., Scheffer, M., and van Nes, E. H. (2010). Early warnings for catastrophic shifts in ecosystems: comparison between spatial and temporal indicators. International Journal of Bifurcation and Chaos, 20, 315321.CrossRefGoogle Scholar
Donges, J. F., Zou, Y., Marwan, N., and Kurths, J. (2009a). Complex networks in climate dynamics. The European Physical Journal Special Topics, 174(1), 157179.CrossRefGoogle Scholar
Donges, J. F., Zou, Y., and Marwan, N. (2009b). The backbone of the climate network. EPL, 87, 48007.CrossRefGoogle Scholar
Donges, J. F., Heitzig, J., Beronov, B., et al. (2015). Unified functional network and nonlinear time series analysis for complex systems science: the pyunicorn package. Chaos, 25, 126.CrossRefGoogle ScholarPubMed
Donner, R. V., Zou, Y., Donges, J. F., et al. (2010). Recurrence networks: a novel paradigm for nonlinear time series analysis. New Journal of Physics, 12(3), 033025.CrossRefGoogle Scholar
Donner, R. V., Small, M., Donges, J. F., et al. (2011). Recurrence-based time series analysis by means of complex network methods. International Journal of Bifurcation and Chaos, 21(4), 10191046.CrossRefGoogle Scholar
d’Ovidio, F., Fernandez, V., Hernandez-García, E., and Lopez, C. (2004). Mixing structures in the Mediterranean Sea from finite-size Lyapunov exponents. Geophysics Research Letters, 31, L17203.Google Scholar
Drumond, A., Nieto, R., Gimeno, L., and Ambrizzi, T. (2008). A Lagrangian identification of major sources of moisture over Central Brazil and La Plata basin. Journal of Geophysical Research, 113, D14128.CrossRefGoogle Scholar
Duan, W. and Wei, C. (2013). The “spring predictability barrier” for ENSO predictions and its possible mechanism: results from a fully coupled model. International Journal of Climatology, 33(5), 12801292.CrossRefGoogle Scholar
Dubois, M., Rossi, V., Ser-Giacomi, E., et al. (2016). Linking basin-scale connectivity, oceanography and population dynamics for the conservation and management of marine ecosystems. Global Ecology and Biogeography, 25(5), 503515.CrossRefGoogle Scholar
Dukowicz, J. K. and Smith, R. D. (1994). Implicit free-surface method for the Bryan–Cox– Semtner ocean model. Journal of Geophysical Research, 99(C4), 79918014.CrossRefGoogle Scholar
Durai, V. R. and Roy Bhowmik, S. K. (2014). Prediction of Indian summer monsoon in short to medium range time scale with high resolution global forecast system (GFS) T574 and T382. Climate Dynamics, 42, 15271551.CrossRefGoogle Scholar
ECMWF (2009). European Centre for Medium-Range Weather Forecasts, 2009: ERA-Interim Project. Research data archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, CO. Available at Scholar
Eichler, M., Dahlhaus, R., and Sandkuhler, J. (2003). Partial directed coherence: a new concept in neural structure determination. Biological Cybernetics, 89, 289.CrossRefGoogle Scholar
Eisenman, I., Yu, L., and Tziperman, E. (2005). Westerly wind bursts: ENSO’s tail rather than the dog? Journal of Climate, 18, 52243238.CrossRefGoogle Scholar
Enfield, D. B., Mestas-Nunes, A. M., and Trimble, P. (2001). The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental US. Geophysics Research Letters, 28, 20772080.CrossRefGoogle Scholar
Fasullo, J. and Webster, P. J. (2003). A hydrological definition of Indian Monsoon onset and withdrawal. Journal of Climate, 16, 32003211.2.0.CO;2>CrossRefGoogle Scholar
Fedorov, A., Harper, S., Philander, S., Winter, B., and Wittenberg, A. (2003). How predictable is El Niño? Bulletin of the American Meteorological Society, 84(7), 911– 919.CrossRefGoogle Scholar
Feldhoff, J. H., Donner, R. V., Donges, J. F., Marwan, N., and Kurths, J. (2012). Geometric detection of coupling directions by means of inter-system recurrence networks. Physics Letters A, 376(46), 35043513.CrossRefGoogle Scholar
Feng, Q. and Dijkstra, H. (2014). Are North Atlantic multidecadal SST anomalies westward propagating? Geophysical Research Letters, 41, 541546.CrossRefGoogle Scholar
Feng, Q. and Dijkstra, H. A. (2017). Climate network stability measures of El Niño variability. Chaos, 27(3), 035801-15.CrossRefGoogle ScholarPubMed
Feng, Q. Y., Viebahn, J. P., and Dijkstra, H. A. (2014). Deep ocean early warning signals of an Atlantic MOC collapse. Geophysical Research Letters, 41, 60086014.CrossRefGoogle Scholar
Feng, Q., Vasile, R., Segond, M., et al. (2016). Climatelearn: a machine-learning approach for climate prediction using network measures. Geoscientific Model Development Discussion. DOI: 10.5194/gmd-2015-273CrossRefGoogle Scholar
Feng, S. and Hu, Q. (2008). How the North Atlantic Multidecadal Oscillation may have influenced the Indian summer monsoon during the past two millennia. Geophysical Research Letters, 35, L01707.CrossRefGoogle Scholar
Flatau, M. K., Flatau, P. J., and Rudnick, D. (2001). The dynamics of double monsoon onsets. Journal of Climate, 14, 41304146.2.0.CO;2>CrossRefGoogle Scholar
Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486, 75174.CrossRefGoogle Scholar
Fortunato, S. and Barthélemy, M. (2007). Resolution limit in community detection. PNAS, 104(1), 3641.CrossRefGoogle ScholarPubMed
Fortunato, S. and Hric, D. (2016). Community detection in networks: a user guide. Physics Reports, 659, 144.CrossRefGoogle Scholar
Frankcombe, L., Dijkstra, H., and von der Heydt, A. (2008). Sub-surface signatures of the Atlantic Multidecadal Oscillation. Geophysical Research Letters, 35, L19602.CrossRefGoogle Scholar
Frankcombe, L. M. and Dijkstra, H. A. (2009). Coherent multidecadal variability in North Atlantic sea level. Geophysical Research Letters, 36, L15604.CrossRefGoogle Scholar
Frankcombe, L. M., von der Heydt, A. S., and Dijkstra, H. A. (2010). North Atlantic multidecadal climate variability: an investigation of dominant time scales and processes. Journal of Climate, 23(13), 36263638.CrossRefGoogle Scholar
Frankignoul, C. and Hasselmann, K. (1977). Stochastic climate models. II: application to sea-surface temperature anomalies and thermocline variability. Tellus, 29, 289305.CrossRefGoogle Scholar
Froyland, G. (2005). Statistically optimal almost-invariant sets. Physica D: Nonlinear Phenomena, 200(3–4), 205219.CrossRefGoogle Scholar
Froyland, G. and Dellnitz, M. (2003). Detecting and locating near-optimal almost-invariant sets and cycles. SIAM Journal on Scientific Computing, 24(6), 18391863.CrossRefGoogle Scholar
Froyland, G. and Padberg-Gehle, K. (2012). Finite-time entropy: a probabilistic approach for measuring nonlinear stretching. Physica D: Nonlinear Phenomena, 241(19), 1612– 1628.CrossRefGoogle Scholar
Froyland, G., Padberg, K., England, M. H., and Treguier, A. M. (2007). Detection of coherent oceanic structures via transfer operators. Physical Review Letters, 98(22), 224503.CrossRefGoogle ScholarPubMed
Froyland, G., Santitissadeekorn, N., and Monahan, A. (2010). Transport in time-dependent dynamical systems: finite-time coherent sets. Chaos, 20(4), 043116.CrossRefGoogle ScholarPubMed
Froyland, G., Horenkamp, C., Rossi, V., Santitissadeekorn, N., and Gupta, A. S. (2012). Three-dimensional characterization and tracking of an Agulhas ring. Ocean Modelling, 52, 6975.CrossRefGoogle Scholar
Froyland, G., Stuart, R. M., and van Sebille, E. (2014). How well-connected is the surface of the global ocean? Chaos, 24(3), 033126.CrossRefGoogle ScholarPubMed
Gadgil, S. (2003). The Indian monsoon and its variability. Annual Review of Earth and Planetary Sciences, 31, 429467.CrossRefGoogle Scholar
Gadgil, S. (2004). Extremes of the Indian summer monsoon rainfall, ENSO and equatorial Indian Ocean oscillation. Geophysical Research Letters, 31(12), L12213.CrossRefGoogle Scholar
Ganachaud, A. and Wunsch, C. (2000). Improved estimates of global ocean circulation, heat transport and mixing from hydrographic data. Nature, 408, 453457.CrossRefGoogle ScholarPubMed
Gautier, N., Aider, J., Duriez, T., et al. (2015). Closed-loop separation control using machine learning. Journal of Fluid Mechanics, 770, 442457.CrossRefGoogle Scholar
Gill, A. E. (1982). Atmosphere–Ocean Dynamics. Academic Press.Google Scholar
Gladwell, M. (2000). The Tipping Point. Little Brown.Google Scholar
Glantz, M. H., Katz, R. W., and Nicholls, N. (1991). Teleconnections Linking Worldwide Climate Anomalies. Information Systems Division, National Agricultural Library.Google Scholar
Goddard, L., Mason, S. J., Zebiak, S. E., et al. (2001). Current approaches to seasonal to interannual climate predictions. International Journal of Climatology, 21(9), 1111– 1152.CrossRefGoogle Scholar
Goswami, B. N., Kulkarni, J. R., Mujumdar, V. R., and Chattopadhyay, R. (2010). On factors responsible for recent secular trend in the onset phase of monsoon intraseasonal oscillations. International Journal of Climatology, 30(14), 22402246.CrossRefGoogle Scholar
Goswami, P. and Gouda, K. C. (2010). Evaluation of a dynamical basis for advance forecasting of the date of onset of monsoon rainfall over India. Monthly Weather Review, 138.CrossRefGoogle Scholar
Gozolchiani, A., Havlin, S., and Yamasaki, K. (2011). Emergence of El Niño as an autonomous component in the climate network. Physical Review Letters, 107(14), 148501.CrossRefGoogle ScholarPubMed
Granger, C. W. J. (1969). Investigating causal relations by econometric and cross-spectral methods. Econometrica, 37, 424438.CrossRefGoogle Scholar
Gray, W. M., Sheaffer, J. D., and Landsea, C. W. (1997). Variability of Atlantic hurricane activity. In Diaz, H. and Pulwarthy, D., editors, Hurricanes, pages 1553. Springer.CrossRefGoogle Scholar
Gregor, D. and Lumsdaine, A. (2005). The parallel bgl: a generic library for distributed graph computations. In Publications, O. I. U., editor, In Parallel Object-Oriented Scientific Computing (POOSC). OSL Indiana University Publications.Google Scholar
Guckenheimer, J. and Holmes, P. (1990). Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields, 2nd edition. Springer-Verlag.Google Scholar
Guez, O. C., Gozolchiani, A., and Havlin, S. (2014). Influence of autocorrelation on the topology of the climate network. Physical Review E, 90(6), 062814.CrossRefGoogle ScholarPubMed
Guttal, V. and Jayaprakash, C. (2007). Impact of noise in bistable ecological systems. Ecological Modelling, 201, 420428.CrossRefGoogle Scholar
Guttal, V. and Jayaprakash, C. (2009). Spatial variance and spatial skewness: leading indicators of regime shifts in spatial ecological systems. Theoretical Ecology, 2(1), 312.CrossRefGoogle Scholar
Hagberg, A. A., Schult, D. A., and Swart, P. J. (2008). Exploring network structure, dynamics, and function using NetworkX. In G. Varoquaux, T. Vaught, and J. Millman, editors, SciPy 2008: Proceedings of the 7th Python in Science Conference, pages 11– 15.Google Scholar
Haken, H. (1977). Synergetics: An Introduction. Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry and Biology. Springer-Verlag.Google Scholar
Haller, G. (2015). Lagrangian coherent structures. Annual Review of Fluid Mechanics, 47(1), 137162.CrossRefGoogle Scholar
Halpin-Healy, T. and Zhang, Y.-C. (1995). Kinetic roughening phenomena, stochastic growth, directed polymers and all that: aspects of multidisciplinary statistical mechanics. Physics Reports, 254(4–6), 215414.CrossRefGoogle Scholar
Hamed, K. H. and Rao, A. R. (1998). A modified Mann–Kendall trend test for autocorre-lated data. Journal of Hydrology, 204(1), 182196.CrossRefGoogle Scholar
Hamming, R. W. (1950). Error detecting and error correcting codes. Bell System Technical Journal, 26, 147157.CrossRefGoogle Scholar
Hartmann, D. L. (1994). Global Physical Climatology. Academic Press.Google Scholar
Hasselmann, K. (1976). Stochastic climate models. I: theory. Tellus, 28, 473485.CrossRefGoogle Scholar
Hawkins, E., Smith, R. S., Allison, L. C., et al. (2011). Bistability of the Atlantic overturning circulation in a global climate model and links to ocean freshwater transport. Geophysical Research Letters, 38(10), L10605.Google Scholar
Hegger, R., Kantz, H., and Schreiber, T. (1999). Practical implementation of nonlinear time series methods: the TISEAN package. Chaos, 9(2), 413435.CrossRefGoogle ScholarPubMed
Held, H. and Kleinen, T. (2004). Detection of climate system bifurcations by degenerate fingerprinting. Geophysical Research Letters, 31, L23207.CrossRefGoogle Scholar
Held, I. M., Ting, M., and Wang, H. (2002). Northern winter stationary waves: theory and modeling. Journal of Climate, 15, 21252144.2.0.CO;2>CrossRefGoogle Scholar
Hernández-Carrasco, I., López, C., Hernández-García, E., and Turiel, A. (2012). Seasonal and regional characterization of horizontal stirring in the global ocean. Journal of Geophysical Research, 117, C10007.CrossRefGoogle Scholar
Hlavackovaschindler, K., Paluš, M., Vejmelka, M., and Bhattacharya, J. (2007). Causality detection based on information-theoretic approaches in time series analysis. Physics Reports, 441(1), 146.CrossRefGoogle Scholar
Hlinka, J., Hartman, D., Vejmelka, M., et al. (2013). Reliability of inference of directed climate networks using conditional mutual information. Entropy, 15, 20232045.CrossRefGoogle Scholar
Holme, P. and Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97125.CrossRefGoogle Scholar
Huisman, S. E., den Toom, M., Dijkstra, H. A., and Drijfhout, S. (2010). An indicator of the multiple equilibria regime of the Atlantic Meridional Overturning Circulation. Journal of Physical Oceanography, 40(3), 551567.CrossRefGoogle Scholar
Ihshaish, H., Tantet, A., Dijkzeul, J. C. M., and Dijkstra, H. A. (2015). ParaGraph: a parallel toolbox for the construction and analysis of large complex climate networks. Geoscientific Model Development, 8(10), 33213331.CrossRefGoogle Scholar
Imkeller, P. and Von Storch, J.-S. (2001). Stochastic Climate Models, volume 49. Springer Science & Business Media.CrossRefGoogle Scholar
James, I. (1994). Introduction to Circulating Atmospheres. Cambridge University Press.CrossRefGoogle Scholar
Johns, W., Baringer, M., and Beal, L. (2011). Continuous, array-based estimates of Atlantic Ocean heat transport at 26.5 N. Journal of Climate, 24, 24292449.CrossRefGoogle Scholar
Johnsen, S. J., Clausen, H. B., Dansgaard, W., et al. (1992). Irregular glacial interstadials recorded in a new Greenland ice core. Nature, 359, 311313.CrossRefGoogle Scholar
Joseph, P. V., Eischeid, J. K., and Pyle, R. J. (1994). Interannual variability of the onset of the Indian Summer Monsoon and its association with atmospheric features, El Niño, and sea surface temperature anomalies. Journal of Climate, 7, 81105.2.0.CO;2>CrossRefGoogle Scholar
Junquas, C., Vera, C., Li, L., and Treut, H. L. (2012). Summer precipitation variability over Southeastern South America in a global warming scenario. Climate Dynamics, 38, 18671883.CrossRefGoogle Scholar
Kalnay, E., Kanamitsu, M., Kistler, R., et al. (1996). The NCEP/NCAR reanalysis 40-year project. Bulletin of the American Meteorological Society, 77(3), 437471.2.0.CO;2>CrossRefGoogle Scholar
Kantz, H. and Schreiber, T. (2003). Nonlinear Time Series Analysis, volume 7. Cambridge University Press.CrossRefGoogle Scholar
Kao, H.-Y. and Yu, J.-Y. (2009). Contrasting Eastern-Pacific and Central-Pacific types of ENSO. Journal of Climate, 22(3), 615632.CrossRefGoogle Scholar
Karimi, A. and Paul, M. R. (2010). Extensive chaos in the Lorenz-96 model. Chaos, 20(4), 043105.CrossRefGoogle ScholarPubMed
Keller, H. B. (1977). Numerical solution of bifurcation and nonlinear eigenvalue problems. In Rabinowitz, P. H., editor, Applications of Bifurcation Theory. Academic Press.Google Scholar
Kempe, D., Kleinberg, J., and Kumar, A. (2000). Connectivity and inference problems for temporal networks. In Proceedings of the Thirty-Second Annual ACM Symposium on Theory of Computing, pages 504513. ACM.Google Scholar
Kerr, R. A. (2000). A North Atlantic climate pacemaker for the centuries. Science, 288, 19841986.CrossRefGoogle ScholarPubMed
Kessler, W. S. (1990). Observations of long Rossby waves in the northern tropical Pacific. Journal of Geophysical Research, 95, 51835217.CrossRefGoogle Scholar
Kim, H. and Anderson, R. (2012). Temporal node centrality in complex networks. Physical Review E, 85(2), 026107.CrossRefGoogle ScholarPubMed
Kim, H.-M., Webster, P. J., and Curry, J. A. (2009). Impact of shifting patterns of Pacific Ocean warming on North Atlantic tropical cyclones. Science, 325(5936), 7780.CrossRefGoogle ScholarPubMed
Kistler, R., Collins, W., Saha, S., et al. (2001). The NCEP-NCAR 50-year reanalysis: monthly means CD-ROM and documentation. Bulletin of the American Meteorological Society, 82(2), 247267.2.3.CO;2>CrossRefGoogle Scholar
Kleeman, R. (2002). Measuring dynamical prediction utility using relative entropy. Journal of the Atmospheric Sciences, 59, 20572072.2.0.CO;2>CrossRefGoogle Scholar
Knight, J. R., Allan, R. J., Folland, C. K., Vellinga, M., and Mann, M. E. (2005). A signature of persistent natural thermohaline circulation cycles in observed climate. Geophysical Research Letters, 32, L20708.CrossRefGoogle Scholar
Knight, J. R., Folland, C. K., and Scaife, A. A. (2006). Climate impacts of the Atlantic Multidecadal Oscillation. Geophysical Research Letters, 33, L17706.CrossRefGoogle Scholar
Kochen, M. (1989). The Small World. Ablex.Google Scholar
Kodama, Y. M. (1992). Large-scale common features of subtropical precipitation zones (the Baiu frontal zone, the SPCZ, and the SACZ) Part I: characteristics of subtropical frontal zones. Journal of the Meteorological Society of Japan, 70, 813836.CrossRefGoogle Scholar
Kostakos, V. (2009). Temporal graphs. Physica A, 388(6), 10071023.CrossRefGoogle Scholar
Krishnamurti, T. N. and Ramanathan, Y. (1982). Sensitivity of the Monsoon onset to differential heating. Journal of the Atmospheric Sciences, 39, 12901306.2.0.CO;2>CrossRefGoogle Scholar
Kuehn, C. (2011). A mathematical framework for critical transitions: bifurcations, fast– slow systems and stochastic dynamics. Physica D, 240(12), 10201035.CrossRefGoogle Scholar
Kuehn, C. (2013). A mathematical framework for critical transitions: normal forms, variance and applications. Journal of Nonlinear Science, 23(23), 457510.CrossRefGoogle Scholar
Kuhlbrodt, T., Griesel, A., Montoya, M., Levermann, A., Hofmann, M., and Rahmstorf, S. (2007). On the driving processes of the atlantic meridional overturning circulation, Rev. Geophysics, 45, 132.Google Scholar
Kushnir, Y. (1994). Interdecadal variations in North Atlantic sea surface temperature and associated atmospheric conditions. Journal of Physical Oceanography, 7, 141157.Google Scholar
Lancaster, G. et al. (2018). Surrogate data for hypothesis testing of physical systems. Physics Reports, 748, 160CrossRefGoogle Scholar
Large, W. G. and Yeager, S. (2004). Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies. Technical report, National Center for Atmospheric Research.Google Scholar
Larkin, N. K. and Harrison, D. (2005). On the definition of El Niño and associated seasonal average U.S. weather anomalies. Geophysical Research Letters, 32(13), L13705.CrossRefGoogle Scholar
Latif, M. (1998). Dynamics of interdecadal variability in coupled ocean–atmosphere models. Journal of Climate, 11, 602624.2.0.CO;2>CrossRefGoogle Scholar
Latif, M. and Barnett, T. P. (1994). Causes of decadal climate variability over the North Pacific and North America. Science, 266, 634637.CrossRefGoogle ScholarPubMed
Legler, D. and O’Brien, J. (1988). Tropical Pacific wind stress analysis for TOGA. Intergovernmental Oceanographic Commission.Google Scholar
Lenton, T. M. (2011). Early warning of climate tipping points. Nature Climate Change, 1(4), 201209.CrossRefGoogle Scholar
Lenton, T. M., Held, H., Kriegler, E., et al. (2008). Tipping elements in the Earth’s climate system. PNAS, 105(6), 17861793.CrossRefGoogle ScholarPubMed
Lenton, T. M., Livina, V. N., Dakos, V., van Nes, E. H., and Scheffer, M. (2012). Early warning of climate tipping points from critical slowing down: comparing methods to improve robustness. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 370(1962), 11851204.CrossRefGoogle ScholarPubMed
Lentz, H. H., Selhorst, T., and Sokolov, I. M. (2013). Unfolding accessibility provides a macroscopic approach to temporal networks. Physical Review Letters, 110(11), 118701.CrossRefGoogle ScholarPubMed
Levermann, A. (2011). When glacial giants roll over. Nature, 472, 4344.CrossRefGoogle ScholarPubMed
Levermann, A., Schewe, J., Petoukhov, V., and Held, H. (2009). Basic mechanism for abrupt monsoon transitions. PNAS, 106(49), 2057220577.CrossRefGoogle ScholarPubMed
Levnajić, Z. and Mezić, I. (2010). Ergodic theory and visualization: I. Mesochronic plots for visualization of ergodic partition and invariant sets. Chaos, 20(3), 033114.CrossRefGoogle ScholarPubMed
Lian, T., Chen, D., Tang, Y., and Wu, Q. (2014). Effects of westerly wind bursts on El Niño: a new perspective. Geophysical Research Letters, 41(10), 35223527.CrossRefGoogle Scholar
Lifland, J. (2003). The North Atlantic Oscillation: climatic significance and environmental impact. Eos, Transactions of the American Geophysical Union, 84(8), 7373.CrossRefGoogle Scholar
Livina, V. N. and Lenton, T. M. (2007). A modified method for detecting incipient bifurcations in a dynamical system. Geophysical Research Letters, 34(3). DOI: 10.1029/2006GL028672CrossRefGoogle Scholar
Livina, V. N., Kwasniok, F., and Lenton, T. M. (2010). Potential analysis reveals changing number of climate states during the last 60 kyr. Climate of the Past, 6(1), 7782.CrossRefGoogle Scholar
Livina, V. N., Kwasniok, F., Lohmann, G., Kantelhardt, J. W., and Lenton, T. M. (2011). Changing climate states and stability: from Pliocene to present. Climate Dynamics, 37(11–12), 24372453.CrossRefGoogle Scholar
Lorenz, E. N. (1969). The predictability of a flow which possesses many scales of motion. Tellus, 21(3), 289307.CrossRefGoogle Scholar
Lorenz, E. N. (1996). Predictability: a problem partly solved. In Palmer, T. and Hagedorn, R., editors, Proceedings of the Seminar on Predictability, Vol. I, ECMWF Seminar, pages 4058. ECMWF.Google Scholar
Lovejoy, S. (2014). Scaling fluctuation analysis and statistical hypothesis testing of anthropogenic warming. Climate Dynamics, 42(9–10), 23392351.CrossRefGoogle Scholar
Ludescher, J., Gozolchiani, A., Bogachev, M. I., Bunde, A., Havlin, S., and Schellnhuber, H. J. (2013). Improved El Niño forecasting by cooperativity detection. PNAS, 110(29), 1174211745.CrossRefGoogle ScholarPubMed
Ludescher, J., Gozolchiani, A., Bogachev, M. I., et al. (2014). Very early warning of next El Niño. PNAS, 111(6), 20642066.Google ScholarPubMed
Lukoševičius, M. and Jaeger, H. (2009). Reservoir computing approaches to recurrent neural network training. Computer Science Review, 3(3), 127149.CrossRefGoogle Scholar
Lumsdaine, A., Gregor, D., Hendrickson, B., and Berry, J. W. (2007). Challenges in parallel graph processing. Parallel Processing Letters, 17(1), 520.CrossRefGoogle Scholar
Lyman, J. M., Chelton, D. B., Deszoeke, R. A., and Samelson, R. M. (2005). Tropical instability waves as a resonance between equatorial Rossby waves. Journal of Physical Oceanography, 35, 232254.CrossRefGoogle Scholar
Malik, N., Marwan, N., and Kurths, J. (2010). Spatial structures and directionalities in Monsoonal precipitation over South Asia. Nonlinear Processes in Geophysics, 17(5), 371381.CrossRefGoogle Scholar
Malik, N., Bookhagen, B., Marwan, N., and Kurths, J. (2012). Analysis of spatial and temporal extreme monsoonal rainfall over South Asia using complex networks. Climate Dynamics, 39(3–4), 971987.CrossRefGoogle Scholar
Mancho, A. M., Small, D., and Wiggins, S. (2006). A tutorial on dynamical systems concepts applied to Lagrangian transport in oceanic flows defined as finite time data sets: theoretical and computational issues. Physics Reports, 437(3–4), 55124.CrossRefGoogle Scholar
Mancho, A. M., Wiggins, S., Curbelo, J., and Mendoza, C. (2013). Lagrangian descriptors: a method for revealing phase space structures of general time dependent dynamical systems. Communications in Nonlinear Science and Numerical Simulation, 18, 3530– 3557.CrossRefGoogle Scholar
Mantua, N. J. and Hare, S. R. (2002). The Pacific decadal oscillation. Journal of Oceanography, 58(1), 3544.CrossRefGoogle Scholar
Marotzke, J. (2000). Abrupt climate change and thermohaline circulation: mechanisms and predictability. PNAS, 97, 13471350.CrossRefGoogle ScholarPubMed
Marshall, J. and Plumb, R. A. (2008). Atmosphere, Ocean and Climate Dynamics: An Introductory Text. Academic Press.Google Scholar
Martin, E., Paczuski, M., and Davidsen, J. (2013). Interpretation of link fluctuations in climate networks during El Niño periods. EPL, 102(4), 48003.CrossRefGoogle Scholar
Martin-Gomez, V. and Barreiro, M. (2016). Complex network analysis of ocean’s influence on spring time rainfall variability over southeastern South America during the 20th century. International Journal of Climatology, 36, 13441358.CrossRefGoogle Scholar
Martin-Gomez, V. and Barreiro, M. (2017). Effect of future climate change on the coupling between the tropical oceans and precipitation over southeastern South America. Climatic Change, 141, 315329.CrossRefGoogle Scholar
Martin-Gomez, V., Hernandez-Garcia, E., Barreiro, M., and Lopez, C. (2016). Interdecadal variability of southeastern South America rainfall and moisture sources during the austral summertime. Journal of Climate, 29, 67516763.CrossRefGoogle Scholar
Marwan, N., Donges, J. F., Zou, Y., Donner, R. V., and Kurths, J. (2009). Complex network approach for recurrence analysis of time series. Physics Letters A, 373(46), 4246– 4254.CrossRefGoogle Scholar
Masuda, N., Klemm, K., and Eguíluz, V. M. (2013). Temporal networks: slowing down diffusion by long lasting interactions. Physical Review Letters, 111, 188701.CrossRefGoogle ScholarPubMed
Matsueda, M. (2011). Predictability of Euro-Russian blocking in summer 2010. Geophysical Research Letters, 38, L06801.Google Scholar
McNeall, D., Halloran, P. R., Good, P., and Betts, R. A. (2011). Analyzing abrupt and nonlinear climate changes and their impacts. Wiley Interdisciplinary Reviews: Climate Change, 2(5), 663686.Google Scholar
McPhaden, M. J. (1999). Genesis and evolution of the 1997–98 El Niño. Science, 283, 950954.CrossRefGoogle ScholarPubMed
Mehlhorn, K. and Näher, S. (1995). Leda: a platform for combinatorial and geometric computing. Communications of the ACM, 38(1), 96102.CrossRefGoogle Scholar
Meng, J., Fan, J., Ashkenazy, Y., and Havlin, S. (2017). Percolation framework to describe El Niño conditions. Chaos, 27(3), 035807.CrossRefGoogle ScholarPubMed
Menkes, C. E., Lengaigne, M., Vialard, J., et al. (2014). About the role of Westerly wind events in the possible development of an El Niño in 2014. Geophysical Research Letters, 41(18), 64766483.CrossRefGoogle Scholar
Milgram, S. (1967). The small world problem. Psychology Today, 1(1), 6167.Google Scholar
Millot, C. and Taupier-Letage, I. (2005). Circulation in the Mediterranean sea. In Goffredo, S. and Dubinsky, Z., editors, The Mediterranean Sea, pages 2966. Springer.CrossRefGoogle Scholar
Mitchell, J.M. (1976). An overview of climate variability and its causal mechanisms, Quaternary Research, 6, 481493.CrossRefGoogle Scholar
Mitchell, T. (1997). Machine Learning. McGraw-Hill.Google Scholar
Mokhov, I., Smirnov, D., Nakonechny, P., et al. (2011). Alternating mutual influence of El-Niño/Southern Oscillation and Indian monsoon. Geophysical Research Letters, 38(8).CrossRefGoogle Scholar
Molkenthin, N., Rehfeld, K., Marwan, N., and Kurths, J. (2014). Networks from flows: from dynamics to topology. Scientific Reports, 4. DOI: 10.1038/srep04119Google ScholarPubMed
Molteni, F. (2003). Atmospheric simulations using a GCM with simplified physical parameterizations: I. Model climatology and variability in multi-decadal experiments. Climate Dynamics, 20, 175191.CrossRefGoogle Scholar
Moron, V., Vautard, R., and Ghil, M. (1998). Trends, interdecadal and interannual oscillations in global sea-surface temperature. Climate Dynamics, 14, 545569.CrossRefGoogle Scholar
Mosquera-Vásquez, K., Dewitte, B., and Illig, S. (2014). The Central Pacific El Niño intraseasonal Kelvin wave. Journal of Geophysical Research: Oceans, 119(10), 6605– 6621.Google Scholar
Mudelsee, M. (2014). Climate Time Series Analysis Springer.Google Scholar
Mudelsee, M. and Bermejo, M. A. (2017). Optimal heavy tail estimation: part 1. Order selection. Nonlinear Processes in Geophysics, 24(4), 737744.CrossRefGoogle Scholar
Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., and Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510.CrossRefGoogle ScholarPubMed
Muller, R. A., Curry, J., Groom, D., et al. (2013). Decadal variations in the global atmospheric land temperatures. Journal of Geophysical Research: Atmospheres, 118(11), 52805286.Google Scholar
Navarra, A. and Simoncini, V. A. (2010). Guide to Empirical Orthogonal Functions for Climate Data Analysis. Springer-Verlag.CrossRefGoogle Scholar
Newman, M. (2010). Networks: An introduction. Oxford University Press.CrossRefGoogle Scholar
Newman, M. (2004). Analysis of weighted networks. Physical Review E, 70(5), 056131.CrossRefGoogle ScholarPubMed
Newman, M. and Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113.CrossRefGoogle ScholarPubMed
Newman, M., Barabási, A.-L., and Watts, D. J. (2006). The Structure and Dynamics of Networks. Princeton University Press.Google Scholar
Nilsson-Jacobi, M., André, C., Doos, K., and Jonsson, P. R. (2012). Identification of subpopulations from connectivity matrices. Ecography, 35, 10041016.CrossRefGoogle Scholar
Nogués-Paegle, J. and Mo, K. C. (1997). Alternating wet and dry conditions over South America during summer. Monthly Weather Review, 125, 279291.2.0.CO;2>CrossRefGoogle Scholar
Oddo, P., Adani, M., Pinardi, N., et al. (2009). A nested Atlantic–Mediterranean sea general circulation model for operational forecasting. Ocean Science, 5(4), 461.CrossRefGoogle Scholar
Overpeck, J. T. and Cole, J. E. (2006). Abrupt change in Earth’s climate system. Annual Review of Environment and Resources, 31(1), 131.CrossRefGoogle Scholar
Paladin, G. and Vulpiani, A. (1987). Anomalous scaling laws in multifractal objects. Physics Reports, 156(4), 147225.CrossRefGoogle Scholar
Palus, M. (2007). From nonlinearity to causality: statistical testing and inference of physical mechanisms underlying complex dynamics. Contemporary Physics, 48, 307.CrossRefGoogle Scholar
Palus, M. and Stefanovska, A. (2003). Direction of coupling from phases of interacting oscillators: an information-theoretic approach. Physical Review E, 67, 055201.CrossRefGoogle Scholar
Pathak, J., Lu, Z., Hunt, B., Girvan, M., and Ott, E. (2017). Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data. Chaos, 27, 121102.CrossRefGoogle ScholarPubMed
Pathak, J., Hunt, B., Girvan, M., Lu, Z., and Ott, E. (2018). Model-free prediction of large spatiotemporally chaotic systems from data: a reservoir computing approach. Physical Review Letters, 120, 024102.CrossRefGoogle ScholarPubMed
Peacock, T. and Dabiri, J. (2010). Introduction to focus issue: Lagrangian coherent structures. Chaos, 20(1), 017501.CrossRefGoogle ScholarPubMed
Philander, S. G. H. (1990). El Niño and the Southern Oscillation. Academic Press.Google Scholar
Prasad, V. S. (2005). Onset and withdrawal of Indian summer monsoon. Geophysical Research Letters, 32(20), L20715.CrossRefGoogle Scholar
Preis, R., Dellnitz, M., Hessel, M., Schütte, C., and Meerbach, E. (2004). Dominant paths between almost invariant sets of dynamical systems. Preprint 154 of the DFG Schwer-punktprogramm 1095, available from Scholar
Puranik, S. S., Ray, K. C. S., Sen, P. N., and Kumar, P. P. (2013). An index for predicting the onset of monsoon over Kerala. Current Science, 105(7).Google Scholar
Quail, T., Shrier, A., and Glass, L. (2015). Predicting the onset of period-doubling bifurcations in noisy cardiac systems. PNAS, 112(30), 93589363.CrossRefGoogle ScholarPubMed
Quian Quiroga, R., Kreuz, T., and Grassberger, P. (2002). Event synchronization: a simple and fast method to measure synchronicity and time delay patterns. Physical Review E, 66(4), 041904.CrossRefGoogle ScholarPubMed
Rahmstorf, S. (2000). The thermohaline circulation: a system with dangerous thresholds? Climatic Change, 46, 247256.CrossRefGoogle Scholar
Rahmstorf, S., Crucifix, M., Ganopolski, A., et al. (2005). Thermohaline circulation hysteresis: a model intercomparison. Geophysical Research Letters, L23605, 15.CrossRefGoogle Scholar
Rajagopalan, B. and Molnar, P. (2014). Combining regional moist static energy and ENSO for forecasting of early and late season Indian monsoon rainfall and its extremes. Geophysical Research Letters, 41, 43234331.CrossRefGoogle Scholar
Rao, P. L. S., Mohanty, U. C., and Ramesh, K. J. (2005). The evolution and retreat features of the summer monsoon over India. Meteorological Applications, 12, 241.CrossRefGoogle Scholar
Rayner, N., Parker, D., Horton, E., et al. (2003). Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research, 108(D14), 4407.CrossRefGoogle Scholar
Rehfeld, K., Marwan, N., Heitzig, J., and Kurths, J. (2011). Comparison of correlation analysis techniques for irregularly sampled time series. Nonlinear Processes in Geophysics, 18(3), 389404.CrossRefGoogle Scholar
Rehfeld, K., Marwan, N., Breitenbach, S. F. M., and Kurths, J. (2012). Late Holocene Asian Summer Monsoon dynamics from small but complex networks of palaeoclimate data. Climate Dynamics, 41, 319.CrossRefGoogle Scholar
Reilly, B. (2009). Disaster and Human History: Case Studies in Nature, Society and Catastrophe. McFarland.Google Scholar
Rényi, A. (1970). Probability Theory. North-Holland.Google Scholar
Ribeiro, B., Perra, N., and Baronchelli, A. (2013). Quantifying the effect of temporal resolution on time-varying networks. Scientific Reports, 3, 3006.CrossRefGoogle ScholarPubMed
Robertson, A. W. and Mechoso, C. R. (2000). Interannual and interdecadal variability of the South Atlantic Convergence Zone. Monthly Weather Review, 128(8), 29472957.2.0.CO;2>CrossRefGoogle Scholar
Rodríguez-Méndez, V., Eguíluz, V. M., Hernández-García, E., and Ramasco, J. J. (2016). Percolation-based precursors of transitions in extended systems. Scientific Reports, 6, 295525.Google ScholarPubMed
Rosenblum, M. and Pikovsky, A. (2001). Detecting direction of coupling in interacting oscillators. Physical Review E, 64, 045202.CrossRefGoogle ScholarPubMed
Rossi, V., López, C., Hernández-García, E., et al. (2009). Surface mixing and biological activity in the four Eastern Boundary upwelling systems. Nonlinear Processes in Geophysics, 16, 557568.CrossRefGoogle Scholar
Rossi, V., Ser-Giacomi, E., López, C., and Hernández-García, E. (2014). Hydrodynamic provinces and oceanic connectivity from a transport network help designing marine reserves. Geophysical Research Letters, 41(8), 28832891.CrossRefGoogle Scholar
Rosvall, M. and Bergstrom, C. T. (2008). Maps of random walks on complex networks reveal community structure. PNAS, 105(4), 11181123.CrossRefGoogle ScholarPubMed
Roulston, M. and Neelin, J. (2000). The response of an ENSO model to climate noise, weather noise and intraseasonal forcing. Geophysical Research Letters, 27, 3723– 3726.CrossRefGoogle Scholar
Roundy, P. E. and Kiladis, G. N. (2006). Observed relationships between oceanic kelvin waves and atmospheric forcing. Journal of Climate, 19(20), 52535272.CrossRefGoogle Scholar
Rummelhart, D. (1986). Learning representations by back-propagation errors. Nature, 323, 533536.CrossRefGoogle Scholar
Runge, J., Petoukhov, V., Donges, J. F., et al. (2015). Identifying causal gateways and mediators in complex spatio-temporal systems. Nature Communications, 6, 8502.CrossRefGoogle ScholarPubMed
Russell, S. J. and Norvig, P. (2003). Artificial Intelligence: A Modern Approach, 2nd edition. Pearson Education.Google Scholar
Sabeerali, C. T., Rao, S. A., Ajayamohan, R. S., and Murtugudde, R. (2011). On the relationship between Indian summer monsoon withdrawal and Indo-Pacific SST anomalies before and after 1976/1977 climate shift. Climate Dynamics, 39(3–4), 841– 859.Google Scholar
Saha, S. and Saha, K. (1980). A hypothesis on onset, advance and withdrawal of the Indian summer monsoon. Pure and Applied Geophysics, 118(2), 10661075.CrossRefGoogle Scholar
Saha, S., Moorthi, S., and Pan, H.-L., et al. (2010). The NCEP climate forecast system reanalysis. Bulletin of the American Meteorological Society, 91, 10151057.CrossRefGoogle Scholar
Saltzmann, B. (2001). Dynamical Paleoclimatology. Academic Press.Google Scholar
Samelson, R. and Wiggins, S. (2006). Lagrangian Transport in Geophysical Jets and Waves. Springer.Google Scholar
Sameshima, K. and Baccala, L. A. (1999). Using partial directed coherence to describe neuronal ensemble interactions. Journal of Neuroscience Methods, 94, 93.CrossRefGoogle ScholarPubMed
Sankar, S., Kumar, M. R. R., Reason, C., and Paula, D. (2011). On the relative roles of El Niño and Indian Ocean dipole events on the Monsoon onset over Kerala. Theoretical and Applied Climatology, 103, 359374.CrossRefGoogle Scholar
Santitissadeekorn, N. and Bollt, E. (2007). Identifying stochastic basin hopping by partitioning with graph modularity. Physica D: Nonlinear Phenomena, 231(2), 95– 107.CrossRefGoogle Scholar
Santitissadeekorn, N., Froyland, G., and Monahan, A. (2010). Optimally coherent sets in geophysical flows: a transfer-operator approach to delimiting the stratospheric polar vortex. Physical Review E, 82(5), 056311.CrossRefGoogle ScholarPubMed
Sarachik, E. S. and Cane, M. A. (2010). The El Niño-Southern Oscillation Phenomenon. Cambridge University Press.CrossRefGoogle Scholar
Schaub, M., Lambiotte, R., and Barahona, M. (2012). Encoding dynamics for multiscale community detection: Markov time sweeping for the map equation. Physical Review E, 86, 026112.CrossRefGoogle ScholarPubMed
Scheffer, M., Carpenter, S., Foley, J. A., Folke, C., and Walker, B. (2001). Catastrophic shifts in ecosystems. Nature, 413(6856), 591596.CrossRefGoogle ScholarPubMed
Scheffer, M., Bascompte, J., Brock, W. A., and Brovkin, V. (2009). Early-warning signals for critical transitions. Nature, 461(7260), 5359.CrossRefGoogle ScholarPubMed
Scheffer, M., Carpenter, S. R., Lenton, T. M., et al. (2012). Anticipating critical transitions. Science, 338(6105), 344348.CrossRefGoogle ScholarPubMed
Schlesinger, M. E. and Ramankutty, N. (1994). An oscillation in the global climate system of period 65–70 years. Nature, 367, 723726.CrossRefGoogle Scholar
Schneider, T. and Griffies, S. (1999). A conceptual framework for predictability studies. Journal of Climate, 12(10), 31333155.2.0.CO;2>CrossRefGoogle Scholar
Schneider, U., Becker, A., Finger, P., et al. (2011). GPCC full data reanalysis version 6.0 at 1.0: monthly land-surface precipitation from rain-gauges built on GTS-based and historic data. Data set.Google Scholar
Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6(2), 461– 464.CrossRefGoogle Scholar
Seber, G. A. and Lee, A. J. (2012). Linear Regression Analysis Wiley.Google Scholar
Sellers, W. D. (1969). A global climate model based on the energy balance of the earth– atmosphere system. Journal of Applied Meteorology, 8, 392400.2.0.CO;2>CrossRefGoogle Scholar
Ser-Giacomi, E., Vasile, R., Recuerda, I., Hernández-García, E., and López, C. (2015a). Dominant transport pathways in an atmospheric blocking event. Chaos, 25, 087413.CrossRefGoogle Scholar
Ser-Giacomi, E., Rossi, V., López, C., and Hernández-García, E. (2015b). Flow networks: a characterization of geophysical fluid transport. Chaos, 25(3), 036404.CrossRefGoogle ScholarPubMed
Ser-Giacomi, E., Vasile, R., Hernández-García, E., and López, C. (2015c). Most probable paths in temporal weighted networks: an application to ocean transport. Physical review E, 92, 036404.CrossRefGoogle ScholarPubMed
Shadden, S. C., Lekien, F., and Marsden, J. E. (2005). Definition and properties of Lagrangian coherent structures from finite-time Lyapunov exponents in two-dimensional aperiodic flows. Physica D, 212(3–4), 271304.CrossRefGoogle Scholar
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 623656.CrossRefGoogle Scholar
Sharma, N., Sharma, P., Irwin, D., and Shenoy, P. (2011). Predicting solar generation from weather forecasts using machine learning. In 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm), pages 528533. IEEE.CrossRefGoogle Scholar
Shnerb, N. M., Sarah, P., Lavee, H., and Solomon, S. (2003). Reactive grass and vegetation patterns. Physical Review Letters, 90.CrossRefGoogle Scholar
Shukla, J. (1998). Predictability in the midst of chaos: a scientific basis for climate forecasting. Science, 282, 728731.CrossRefGoogle ScholarPubMed
Siek, J., Lee, L.-Q., and Lumsdaine, A. (2002). The Boost Graph Library: User Guide and Reference Manual. Addison-Wesley Longman Publishing Co.Google Scholar
Simmons, A., Jones, P., Bechtold, V., et al. (2005). Comparison of trends and low-frequency variability in CRU, ERA-40, and NCEP/NCAR analyses of surface air temperature. Journal of Geophysical Research-Atmospheres, 109, D24115.CrossRefGoogle Scholar
Simmons, A. J., Willett, K. M., Jones, P. D., Thorne, P. W., and Dee, D. P. (2010). Comparison of trends and low-frequency variability in CRU, ERA-40, and NCEP/NCAR analyses of surface air temperature. Journal of Geophysical Research, 115, D01110.Google Scholar
Singh, N. and Ranade, A. A. (2010). Determination of Onset and Withdrawal Dates of Summer Monsoon across India using NCEP/NCAR Re-analysis Data Set. Indian Institute of Tropical Meteorology.Google Scholar
Smeed, D. A., McCarthy, G., Cunningham, S. A., et al. (2013). Observed decline of the Atlantic meridional overturning circulation 2004 to 2012. Ocean Science Discussions, 10(5), 16191645.CrossRefGoogle Scholar
Smith, T. M. and Reynolds, R. W. (2003). Extended reconstruction of global sea surface temperatures based on COADS data (1854–1997). Journal of Climate, 16(10), 1495– 1510.CrossRefGoogle Scholar
Smith, T. M. and Reynolds, R. W. (2004). Improved extended reconstruction of SST (1854– 1997). Journal of Climate, 17, 24662477.2.0.CO;2>CrossRefGoogle Scholar
Smith, T. M., Reynolds, R., Peterson, T., and Lawrimore, J. (2008). Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). Journal of Climate, 21, 22832296.CrossRefGoogle Scholar
Soman, M. K. and Krishna Kumar, K. (1993). Space–time evolution of the meteorological features associated with the onset of the Indian summer monsoon. Monthly Weather Review, 121, 11771194.2.0.CO;2>CrossRefGoogle Scholar
Speetjens, M., Lauret, M., Nijmeijer, H., and Anderson, P. (2013). Footprints of Lagrangian flow structures in Eulerian concentration distributions in periodic mixing flows. Physica D: Nonlinear Phenomena, 250, 2033.CrossRefGoogle Scholar
Stainforth, D. A., Aina, T., Christensen, C., and Collins, M. (2005). Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature, 433(7024), 403406.CrossRefGoogle ScholarPubMed
Starnini, M., Baronchelli, A., Barrat, A., and Pastor-Satorras, R. (2012). Random walks on temporal networks. Physical Review E, 85(5), 056115.CrossRefGoogle ScholarPubMed
Stauffer, D. and Aharony, A. (1994). Introduction to Percolation Theory, 2nd edition. Taylor & Francis.Google Scholar
Steuer, R., Kurths, J., Daub, C. O., Weise, J., and Selbig, J. (2002). The mutual information: detecting and evaluating dependencies between variables. Bioinformatics, 18(2), S231S240.CrossRefGoogle ScholarPubMed
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G. (2005). Technical note: the Lagrangian particle dispersion model FLEXPART version 6.2. Atmospheric Chemistry and Physics, 5, 24612474.CrossRefGoogle Scholar
Stohl, A., Sodemann, H., Eckhardt, S., et al. (2011). The Lagrangian particle dispersion model FLEXPART version 8.2. FLEXPART User Guide.Google Scholar
Stolbova, V., Martin, P., Bookhagen, B., Marwan, N., and Kurths, J. (2014). Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka. Nonlinear Processes in Geophysics, 21, 901917.CrossRefGoogle Scholar
Stolbova, V., Surovyatkina, E., Bookhagen, B., and Kurths, J. (2016). Tipping elements of the Indian monsoon: prediction of onset and withdrawal. Geophysical Research Letters, 43, 39823990.CrossRefGoogle Scholar
Stommel, H. (1961). Thermohaline convection with two stable regimes of flow. Tellus, 13, 244230.CrossRefGoogle Scholar
Straus, D. M. and Shukla, J. (2010). Distinguishing between the SST-forced variability and internal variability in mid latitudes: analysis of observations and GCM simulations. Quarterly Journal of the Royal Meteorological Society, 126(567), 23232350.CrossRefGoogle Scholar
Strogatz, S. H. (2001). Exploring complex networks. Nature, 410(6825), 268276.CrossRefGoogle ScholarPubMed
Subash, N. and Gangwar, B. (2014). Statistical analysis of Indian rainfall and rice productivity anomalies over the last decades. International Journal of Climatology, 34(7), 23782392.CrossRefGoogle Scholar
Sugihara, G., May, R., Ye, H., et al. (2012). Detecting causality in complex ecosystems. Science, 338, 496500.CrossRefGoogle ScholarPubMed
Sutton, R. T. and Hodson, D. L. (2005). Atlantic Ocean forcing of North American and European summer climate. Science, 309, 115118.CrossRefGoogle ScholarPubMed
Tallapragada, P. and Ross, S. D. (2013). A set oriented definition of finite-time Lyapunov exponents and coherent sets. Communications in Nonlinear Science and Numerical Simulation, 18(5), 11061126.CrossRefGoogle Scholar
Tang, J., Musolesi, M., Mascolo, C., Latora, V., and Nicosia, V. (2010a). Analysing information flows and key mediators through temporal centrality metrics. In Proceedings of the 3rd Workshop on Social Network Systems, page 3. ACM.Google Scholar
Tang, J., Scellato, S., Musolesi, M., Mascolo, C., and Latora, V. (2010b). Small-world behavior in time-varying graphs. Physical Review E, 81(5), 055101.CrossRefGoogle ScholarPubMed
Taniguchi, K. and Koike, T. (2006). Comparison of definitions of Indian summer monsoon onset: better representation of rapid transitions of atmospheric conditions. Geophysical Research Letters, 33(2), L02709.CrossRefGoogle Scholar
Tantet, A. and Dijkstra, H. A. (2014). An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature. Earth System Dynamics, 5(1), 114.CrossRefGoogle Scholar
Te Raa, L. A. and Dijkstra, H. A. (2002). Instability of the thermohaline ocean circulation on interdecadal timescales. Journal of Physical Oceanography, 32(1), 138160.2.0.CO;2>CrossRefGoogle Scholar
Tél, T. and Gruiz, M. (2006). Chaotic Dynamics: An Introduction Based on Classical Mechanics. Cambridge University Press.CrossRefGoogle Scholar
Thomas, C. J., Lambrechts, J., Wolanski, E., et al. (2014). Numerical modelling and graph theory tools to study ecological connectivity in the Great Barrier Reef. Ecological Modelling, 272, 160174.CrossRefGoogle Scholar
Thompson, J. M. T. and Sieber, J. (2011). Predicting climate tipping as a noisy bifurcation: a review. International Journal of Bifurcation and Chaos, 21(2), 399423.CrossRefGoogle Scholar
Thornalley, D. J. R., Oppo, D. W., Ortega, P., et al. (2018). Anomalously weak Labrador Sea convection and Atlantic overturning during the past 150 years. Nature, 556, 227230.CrossRefGoogle ScholarPubMed
Tietsche, S., Notz, D., Jungclaus, J., and Marotzke, J. (2011). Recovery mechanisms of Arctic summer sea ice. Geophysical Research Letters, 38(2). DOI: 10.1029/2010GL045698CrossRefGoogle Scholar
Ting, M., Kushnir, Y., Seager, R., and Li, C. (2009). Forced and internal twentieth-century SST trends in the North Atlantic. Journal of Climate, 22(6), 14691481.CrossRefGoogle Scholar
Tirabassi, G. (2015). Disentangling Climatic Interactions and Detecting Tipping Points by Means of Complex Networks. Universitat Politecnica de Catalunya.Google Scholar
Tirabassi, G. and Masoller, C. (2013). On the effects of lag-times in networks constructed from similarities of monthly fluctuations of climate fields. EPL, 102, 59003.CrossRefGoogle Scholar
Tirabassi, G. and Masoller, C. (2016). Unravelling the community structure of the climate system by using lags and symbolic time-series analysis. Scientific Reports, 6, 29804.CrossRefGoogle ScholarPubMed
Tirabassi, G., Viebahn, J., Dakos, V., et al. (2014). Interaction network based early-warning indicators of vegetation transitions. Ecological Complex., 19, 148157.CrossRefGoogle Scholar
Tirabassi, G., Masoller, C., and Barreiro, M. (2015a). A study of the air–sea interaction in the South Atlantic Convergence Zone through Granger causality. International Journal of Climatology, 35, 34403453.CrossRefGoogle Scholar
Tirabassi, G., Sevilla-Escoboza, R., Buldu, J. M., and Masoller, C. (2015b). Inferring the connectivity of coupled oscillators from time-series statistical similarity analysis. Scientific Reports, 5, 10829.CrossRefGoogle ScholarPubMed
Tirabassi, G., Sommerlade, L., and Masoller, C. (2017). Inferring directed climatic interactions with renormalized partial directed coherence and directed partial correlation. Chaos, 27, 035815.CrossRefGoogle ScholarPubMed
Toshiaki, S., Roundy, P., and Kiladis, G. (2008). Variability of intraseasonal Kelvin waves in the equatorial Pacific Ocean. Journal of Physical Oceanography, 38, 921944.Google Scholar
Tourre, Y. M., Rajagopalan, B., and Kushnir, Y. (1999). Dominant patterns of climate variability in the Atlantic Ocean during the last 136 Years. Journal of Climate, 12, 22852299.2.0.CO;2>CrossRefGoogle Scholar
Trenberth, K. E., Branstator, G. W., Karoly, D., et al. (1998). Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. Journal of Geophysical Research, 103(C7), 14291.CrossRefGoogle Scholar
Trenberth, K. E., Fasullo, J., and Smith, L. (2005). Trends and variability in column-integrated atmospheric water vapor. Climate Dynamics, 24, 741758.CrossRefGoogle Scholar
Tsonis, A. A. and Roebber, P. J. (2004). The architecture of the climate network. Physica A: Statistical Mechanics and its Applications, 333, 497504.CrossRefGoogle Scholar
Tsonis, A. A. and Swanson, K. L. (2006). What do networks have to do with climate? Bulletin of the American Meteorological Society, 87(5), 585595.CrossRefGoogle Scholar
Tsonis, A. A. and Swanson, K. L. (2008). Topology and predictability of El Niño and La Niña networks. Physical Review Letters, 100(22), 228502.CrossRefGoogle ScholarPubMed
Tupikina, L., Molkenthin, N., Lopez, C., et al. (2016). Correlation networks from flows: the case of forced and time-dependent advection-diffusion dynamics.