@article{BoersGoswamiGhil2017, author = {Boers, Niklas and Goswami, Bedartha and Ghil, Michael}, title = {A complete representation of uncertainties in layer-counted paleoclimatic archives}, series = {Climate of the past : an interactive open access journal of the European Geosciences Union}, volume = {13}, journal = {Climate of the past : an interactive open access journal of the European Geosciences Union}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1814-9324}, doi = {10.5194/cp-13-1169-2017}, pages = {12}, year = {2017}, abstract = {Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records - such as ice cores, sediments, corals, or tree rings - as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting-based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated. Our method is next applied to deriving the overall uncertainties of the Suigetsu radiocarbon comparison curve, which was recently obtained from varved sediment cores at Lake Suigetsu, Japan. This curve provides the only terrestrial radiocarbon comparison for the time interval 12.5-52.8 kyr BP. The uncertainties derived here can be readily employed to obtain complete error estimates for arbitrary radiometrically dated proxy records of this recent part of the last glacial interval.}, language = {en} } @misc{BoersGoswamiGhil2017, author = {Boers, Niklas and Goswami, Bedartha and Ghil, Michael}, title = {A complete representation of uncertainties in layer-counted paleoclimatic archives}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {641}, issn = {1866-8372}, doi = {10.25932/publishup-41803}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418030}, pages = {12}, year = {2017}, abstract = {Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records - such as ice cores, sediments, corals, or tree rings - as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting-based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated. Our method is next applied to deriving the overall uncertainties of the Suigetsu radiocarbon comparison curve, which was recently obtained from varved sediment cores at Lake Suigetsu, Japan. This curve provides the only terrestrial radiocarbon comparison for the time interval 12.5-52.8 kyr BP. The uncertainties derived here can be readily employed to obtain complete error estimates for arbitrary radiometrically dated proxy records of this recent part of the last glacial interval.}, language = {en} } @article{RheinwahltGoswamiBookhagen2019, author = {Rheinwahlt, Aljoscha and Goswami, Bedartha and Bookhagen, Bodo}, title = {A network-based flow accumulation algorithm for point clouds}, series = {Journal of geophysical research : Earth surface}, volume = {124}, journal = {Journal of geophysical research : Earth surface}, number = {7}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9003}, doi = {10.1029/2018JF004827}, pages = {2013 -- 2033}, year = {2019}, abstract = {Flow accumulation algorithms estimate the steady state of flow on real or modeled topographic surfaces and are crucial for hydrological and geomorphological assessments, including delineation of river networks, drainage basins, and sediment transport processes. Existing flow accumulation algorithms are typically designed to compute flows on regular grids and are not directly applicable to arbitrarily sampled topographic data such as lidar point clouds. In this study we present a random sampling scheme that generates homogeneous point densities, in combination with a novel flow path tracing approach-the Facet-Flow Network (FFN)-that estimates flow accumulation in terms of specific catchment area (SCA) on triangulated surfaces. The random sampling minimizes biases due to spatial sampling and the FFN allows for direct flow estimation from point clouds. We validate our approach on a Gaussian hill surface and study the convergence of its SCA compared to the analytical solution. Here, our algorithm outperforms the multiple flow direction algorithm, which is optimized for divergent surfaces. We also compute the SCA of a 6-km(2)-steep, vegetated catchment on Santa Cruz Island, California, based on airborne lidar point-cloud data. Point-cloud-based SCA values estimated by our method compare well with those estimated by the D-infinity or multiple flow direction algorithm on gridded data. The advantage of computing SCA from point clouds becomes relevant especially for divergent topography and for small drainage areas: These are depicted with much more detail due to the higher sampling density of point clouds.}, language = {en} } @article{GoswamiShekatkarRheinwaltetal.2015, author = {Goswami, Bedartha and Shekatkar, Snehal M. and Rheinwalt, Aljoscha and Ambika, G. and Kurths, J{\"u}rgen}, title = {A random interacting network model for complex networks}, series = {Scientific reports}, volume = {5}, journal = {Scientific reports}, publisher = {Nature Publ. Group}, address = {London}, issn = {2045-2322}, doi = {10.1038/srep18183}, pages = {10}, year = {2015}, abstract = {We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems.}, language = {en} } @misc{GoswamiBoersRheinwaltetal.2018, author = {Goswami, Bedartha and Boers, Niklas and Rheinwalt, Aljoscha and Marwan, Norbert and Heitzig, Jobst and Breitenbach, Sebastian Franz Martin and Kurths, J{\"u}rgen}, title = {Abrupt transitions in time series with uncertainties}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {576}, issn = {1866-8372}, doi = {10.25932/publishup-42311}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-423111}, pages = {10}, year = {2018}, abstract = {Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Nino-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.}, language = {en} } @article{GoswamiBoersRheinwaltetal.2018, author = {Goswami, Bedartha and Boers, Niklas and Rheinwalt, Aljoscha and Marwan, Norbert and Heitzig, Jobst and Breitenbach, Sebastian Franz Martin and Kurths, J{\"u}rgen}, title = {Abrupt transitions in time series with uncertainties}, series = {Nature Communications}, volume = {9}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/s41467-017-02456-6}, pages = {10}, year = {2018}, abstract = {Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Ni{\~n}o-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.}, language = {en} } @article{LechleitnerBreitenbachChengetal.2017, author = {Lechleitner, Franziska A. and Breitenbach, Sebastian Franz Martin and Cheng, Hai and Plessen, Birgit and Rehfeld, Kira and Goswami, Bedartha and Marwan, Norbert and Eroglu, Deniz and Adkins, Jess F. and Haug, Gerald}, title = {Climatic and in-cave influences on delta O-18 and delta C-13 in a stalagmite from northeastern India through the last deglaciation}, series = {Quaternary research : an interdisciplinary journal}, volume = {88}, journal = {Quaternary research : an interdisciplinary journal}, publisher = {Cambridge Univ. Press}, address = {New York}, issn = {0033-5894}, doi = {10.1017/qua.2017.72}, pages = {458 -- 471}, year = {2017}, abstract = {Northeastern (NE) India experiences extraordinarily pronounced seasonal climate, governed by the Indian summer monsoon (ISM). The vulnerability of this region to floods and droughts calls for detailed and highly resolved paleoclimate reconstructions to assess the recurrence rate and driving factors of ISM changes. We use stable oxygen and carbon isotope ratios (delta O-18 and delta C-13) from stalagmite MAW-6 from Mawmluh Cave to infer climate and environmental conditions in NE India over the last deglaciation (16-6ka). We interpret stalagmite delta O-18 as reflecting ISM strength, whereas delta C-13 appears to be driven by local hydroclimate conditions. Pronounced shifts in ISM strength over the deglaciation are apparent from the delta O-18 record, similarly to other records from monsoonal Asia. The ISM is weaker during the late glacial (LG) period and the Younger Dryas, and stronger during the BOlling-Allerod and Holocene. Local conditions inferred from the delta C-13 record appear to have changed less substantially over time, possibly related to the masking effect of changing precipitation seasonality. Time series analysis of the delta O-18 record reveals more chaotic conditions during the late glacial and higher predictability during the Holocene, likely related to the strengthening of the seasonal recurrence of the ISM with the onset of the Holocene.}, language = {en} } @article{BoersGoswamiRheinwaltetal.2019, author = {Boers, Niklas and Goswami, Bedartha and Rheinwalt, Aljoscha and Bookhagen, Bodo and Hoskins, Brian and Kurths, J{\"u}rgen}, title = {Complex networks reveal global pattern of extreme-rainfall teleconnections}, series = {Nature : the international weekly journal of science}, volume = {566}, journal = {Nature : the international weekly journal of science}, number = {7744}, publisher = {Nature Publ. Group}, address = {London}, issn = {0028-0836}, doi = {10.1038/s41586-018-0872-x}, pages = {373 -- 377}, year = {2019}, abstract = {Climatic observables are often correlated across long spatial distances, and extreme events, such as heatwaves or floods, are typically assumed to be related to such teleconnections(1,2). Revealing atmospheric teleconnection patterns and understanding their underlying mechanisms is of great importance for weather forecasting in general and extreme-event prediction in particular(3,4), especially considering that the characteristics of extreme events have been suggested to change under ongoing anthropogenic climate change(5-8). Here we reveal the global coupling pattern of extreme-rainfall events by applying complex-network methodology to high-resolution satellite data and introducing a technique that corrects for multiple-comparison bias in functional networks. We find that the distance distribution of significant connections (P < 0.005) around the globe decays according to a power law up to distances of about 2,500 kilometres. For longer distances, the probability of significant connections is much higher than expected from the scaling of the power law. We attribute the shorter, power-law-distributed connections to regional weather systems. The longer, super-power-law-distributed connections form a global rainfall teleconnection pattern that is probably controlled by upper-level Rossby waves. We show that extreme-rainfall events in the monsoon systems of south-central Asia, east Asia and Africa are significantly synchronized. Moreover, we uncover concise links between south-central Asia and the European and North American extratropics, as well as the Southern Hemisphere extratropics. Analysis of the atmospheric conditions that lead to these teleconnections confirms Rossby waves as the physical mechanism underlying these global teleconnection patterns and emphasizes their crucial role in dynamical tropical-extratropical couplings. Our results provide insights into the function of Rossby waves in creating stable, global-scale dependencies of extreme-rainfall events, and into the potential predictability of associated natural hazards.}, language = {en} } @article{BreitenbachRehfeldGoswamietal.2012, author = {Breitenbach, Sebastian Franz Martin and Rehfeld, Kira and Goswami, Bedartha and Baldini, James U. L. and Ridley, H. E. and Kennett, D. J. and Prufer, K. M. and Aquino, Valorie V. and Asmerom, Yemane and Polyak, V. J. and Cheng, Hai and Kurths, J{\"u}rgen and Marwan, Norbert}, title = {Constructing Proxy Records from Age models (COPRA)}, series = {Climate of the past : an interactive open access journal of the European Geosciences Union}, volume = {8}, journal = {Climate of the past : an interactive open access journal of the European Geosciences Union}, number = {5}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1814-9324}, doi = {10.5194/cp-8-1765-2012}, pages = {1765 -- 1779}, year = {2012}, abstract = {Reliable age models are fundamental for any palaeoclimate reconstruction. Available interpolation procedures between age control points are often inadequately reported, and very few translate age uncertainties to proxy uncertainties. Most available modeling algorithms do not allow incorporation of layer counted intervals to improve the confidence limits of the age model in question. We present a framework that allows detection and interactive handling of age reversals and hiatuses, depth-age modeling, and proxy-record reconstruction. Monte Carlo simulation and a translation procedure are used to assign a precise time scale to climate proxies and to translate dating uncertainties to uncertainties in the proxy values. The presented framework allows integration of incremental relative dating information to improve the final age model. The free software package COPRA1.0 facilitates easy interactive usage.}, language = {en} } @article{GoswamiHeitzigRehfeldetal.2014, author = {Goswami, Bedartha and Heitzig, Jobst and Rehfeld, Kira and Marwan, Norbert and Anoop, Ambili and Prasad, Sushma and Kurths, J{\"u}rgen}, title = {Estimation of sedimentary proxy records together with associated uncertainty}, series = {Nonlinear processes in geophysics}, volume = {21}, journal = {Nonlinear processes in geophysics}, number = {6}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1023-5809}, doi = {10.5194/npg-21-1093-2014}, pages = {1093 -- 1111}, year = {2014}, abstract = {Sedimentary proxy records constitute a significant portion of the recorded evidence that allows us to investigate paleoclimatic conditions and variability. However, uncertainties in the dating of proxy archives limit our ability to fix the timing of past events and interpret proxy record intercomparisons. While there are various age-modeling approaches to improve the estimation of the age-depth relations of archives, relatively little focus has been placed on the propagation of the age (and radiocarbon calibration) uncertainties into the final proxy record. We present a generic Bayesian framework to estimate proxy records along with their associated uncertainty, starting with the radiometric age-depth and proxy-depth measurements, and a radiometric calibration curve if required. We provide analytical expressions for the posterior proxy probability distributions at any given calendar age, from which the expected proxy values and their uncertainty can be estimated. We illustrate our method using two synthetic data sets and then use it to construct the proxy records for groundwater inflow and surface erosion from Lonar lake in central India. Our analysis reveals interrelations between the uncertainty of the proxy record over time and the variance of proxies along the depth of the archive. For the Lonar lake proxies, we show that, rather than the age uncertainties, it is the proxy variance combined with calibration uncertainty that accounts for most of the final uncertainty. We represent the proxy records as probability distributions on a precise, error-free timescale that makes further time series analyses and intercomparisons of proxies relatively simple and clear. Our approach provides a coherent understanding of age uncertainties within sedimentary proxy records that involve radiometric dating. It can be potentially used within existing age modeling structures to bring forth a reliable and consistent framework for proxy record estimation.}, language = {en} }