@article{TrauthMarwan2022,
  author    = {Trauth, Martin H. and Marwan, Norbert},
  title     = {Introduction-time series analysis for Earth, climate and life interactions},
  series = {Quaternary science reviews : the international multidisciplinary research and review journal},
  volume    = {284},
  journal   = {Quaternary science reviews : the international multidisciplinary research and review journal},
  publisher = {Elsevier},
  address   = {Amsterdam [u.a.]},
  issn      = {0277-3791},
  doi       = {10.1016/j.quascirev.2022.107475},
  pages     = {3},
  year      = {2022},
  language  = {en}
}
@article{AgarwalGuntuBanerjeeetal.2022,
  author    = {Agarwal, Ankit and Guntu, Ravikumar and Banerjee, Abhirup and Gadhawe, Mayuri Ashokrao and Marwan, Norbert},
  title     = {A complex network approach to study the extreme precipitation patterns in a river basin},
  series = {Chaos : an interdisciplinary journal of nonlinear science},
  volume    = {32},
  journal   = {Chaos : an interdisciplinary journal of nonlinear science},
  number    = {1},
  publisher = {American Institute of Physics},
  address   = {Woodbury, NY},
  issn      = {1054-1500},
  doi       = {10.1063/5.0072520},
  pages     = {12},
  year      = {2022},
  abstract  = {The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.},
  language  = {en}
}
@article{KraemerGelbrechtPavithranetal.2022,
  author    = {Kr{\"a}mer, Hauke Kai and Gelbrecht, Maximilian and Pavithran, Induja and Sujith, Ravindran and Marwan, Norbert},
  title     = {Optimal state space reconstruction via Monte Carlo decision tree search},
  series = {Nonlinear Dynamics},
  volume    = {108},
  journal   = {Nonlinear Dynamics},
  number    = {2},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {0924-090X},
  doi       = {10.1007/s11071-022-07280-2},
  pages     = {1525 -- 1545},
  year      = {2022},
  abstract  = {A novel idea for an optimal time delay state space reconstruction from uni- and multivariate time series is presented. The entire embedding process is considered as a game, in which each move corresponds to an embedding cycle and is subject to an evaluation through an objective function. This way the embedding procedure can be modeled as a tree, in which each leaf holds a specific value of the objective function. By using a Monte Carlo ansatz, the proposed algorithm populates the tree with many leafs by computing different possible embedding paths and the final embedding is chosen as that particular path, which ends at the leaf with the lowest achieved value of the objective function. The method aims to prevent getting stuck in a local minimum of the objective function and can be used in a modular way, enabling practitioners to choose a statistic for possible delays in each embedding cycle as well as a suitable objective function themselves. The proposed method guarantees the optimization of the chosen objective function over the parameter space of the delay embedding as long as the tree is sampled sufficiently. As a proof of concept, we demonstrate the superiority of the proposed method over the classical time delay embedding methods using a variety of application examples. We compare recurrence plot-based statistics inferred from reconstructions of a Lorenz-96 system and highlight an improved forecast accuracy for map-like model data as well as for palaeoclimate isotope time series. Finally, we utilize state space reconstruction for the detection of causality and its strength between observables of a gas turbine type thermoacoustic combustor.},
  language  = {en}
}
@article{McCoolCoddingVernonetal.2022,
  author    = {McCool, Weston C. and Codding, Brian F. and Vernon, Kenneth B. and Wilson, Kurt M. and Yaworsky, Peter M. and Marwan, Norbert and Kennett, Douglas J.},
  title     = {Climate change-induced population pressure drives high rates of lethal violence in the Prehispanic central Andes},
  series = {Proceedings of the National Academy of Sciences of the United States of America : PNAS},
  volume    = {119},
  journal   = {Proceedings of the National Academy of Sciences of the United States of America : PNAS},
  number    = {17},
  publisher = {National Acad. of Sciences},
  address   = {Washington},
  issn      = {0027-8424},
  doi       = {10.1073/pnas.2117556119},
  pages     = {8},
  year      = {2022},
  abstract  = {Understanding the influence of climate change and population pressure on human conflict remains a critically important topic in the social sciences. Long-term records that evaluate these dynamics across multiple centuries and outside the range of modern climatic variation are especially capable of elucidating the relative effect of-and the interaction between-climate and demography. This is crucial given that climate change may structure population growth and carrying capacity, while both climate and population influence per capita resource availability. This study couples paleoclimatic and demographic data with osteological evaluations of lethal trauma from 149 directly accelerator mass spectrometry C-14-dated individuals from the Nasca highland region of Peru. Multiple local and supraregional precipitation proxies are combined with a summed probability distribution of 149 C-14 dates to estimate population dynamics during a 700-y study window. Counter to previous findings, our analysis reveals a precipitous increase in violent deaths associated with a period of productive and stable climate, but volatile population dynamics. We conclude that favorable local climate conditions fostered population growth that put pressure on the marginal and highly circumscribed resource base, resulting in violent resource competition that manifested in over 450 y of internecine warfare. These findings help support a general theory of intergroup violence, indicating that relative resource scarcity-whether driven by reduced resource abundance or increased competition-can lead to violence in subsistence societies when the outcome is lower per capita resource availability.},
  language  = {en}
}