@article{AgarwalMaheswaranMarwanetal.2018, author = {Agarwal, Ankit and Maheswaran, Rathinasamy and Marwan, Norbert and Caesar, Levke and Kurths, J{\"u}rgen}, title = {Wavelet-based multiscale similarity measure for complex networks}, series = {The European physical journal : B, Condensed matter and complex systems}, volume = {91}, journal = {The European physical journal : B, Condensed matter and complex systems}, number = {11}, publisher = {Springer}, address = {New York}, issn = {1434-6028}, doi = {10.1140/epjb/e2018-90460-6}, pages = {12}, year = {2018}, abstract = {In recent years, complex network analysis facilitated the identification of universal and unexpected patterns in complex climate systems. However, the analysis and representation of a multiscale complex relationship that exists in the global climate system are limited. A logical first step in addressing this issue is to construct multiple networks over different timescales. Therefore, we propose to apply the wavelet multiscale correlation (WMC) similarity measure, which is a combination of two state-of-the-art methods, viz. wavelet and Pearson's correlation, for investigating multiscale processes through complex networks. Firstly we decompose the data over different timescales using the wavelet approach and subsequently construct a corresponding network by Pearson's correlation. The proposed approach is illustrated and tested on two synthetics and one real-world example. The first synthetic case study shows the efficacy of the proposed approach to unravel scale-specific connections, which are often undiscovered at a single scale. The second synthetic case study illustrates that by dividing and constructing a separate network for each time window we can detect significant changes in the signal structure. The real-world example investigates the behavior of the global sea surface temperature (SST) network at different timescales. Intriguingly, we notice that spatial dependent structure in SST evolves temporally. Overall, the proposed measure has an immense potential to provide essential insights on understanding and extending complex multivariate process studies at multiple scales.}, language = {en} } @article{TotzEliseevPetrietal.2018, author = {Totz, Sonja Juliana and Eliseev, Alexey V. and Petri, Stefan and Flechsig, Michael and Caesar, Levke and Petoukhov, Vladimir and Coumou, Dim}, title = {The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model}, series = {Geoscientific model development : an interactive open access journal of the European Geosciences Union}, volume = {11}, journal = {Geoscientific model development : an interactive open access journal of the European Geosciences Union}, number = {2}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1991-959X}, doi = {10.5194/gmd-11-665-2018}, pages = {665 -- 679}, year = {2018}, abstract = {Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0. The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower troposphere mass flux show good results in particular in the Northern Hemisphere. In the Southern Hemisphere, the model tends to produce too-weak zonal-mean zonal winds and a too-narrow Hadley circulation. We discuss possible reasons for these model biases as well as planned future model improvements and applications.}, language = {en} } @article{CaesarRahmstorfRobinsonetal.2018, author = {Caesar, Levke and Rahmstorf, Stefan and Robinson, Alexander and Feulner, Georg and Saba, V.}, title = {Observed fingerprint of a weakening Atlantic Ocean overturning circulation}, series = {Nature : the international weekly journal of science}, volume = {556}, journal = {Nature : the international weekly journal of science}, number = {7700}, publisher = {Nature Publ. Group}, address = {London}, issn = {0028-0836}, doi = {10.1038/s41586-018-0006-5}, pages = {191 -- 196}, year = {2018}, abstract = {The Atlantic meridional overturning circulation (AMOC)—a system of ocean currents in the North Atlantic—has a major impact on climate, yet its evolution during the industrial era is poorly known owing to a lack of direct current measurements. Here we provide evidence for a weakening of the AMOC by about 3 ± 1 sverdrups (around 15 per cent) since the mid-twentieth century. This weakening is revealed by a characteristic spatial and seasonal sea-surface temperature 'fingerprint'—consisting of a pattern of cooling in the subpolar Atlantic Ocean and warming in the Gulf Stream region—and is calibrated through an ensemble of model simulations from the CMIP5 project. We find this fingerprint both in a high-resolution climate model in response to increasing atmospheric carbon dioxide concentrations, and in the temperature trends observed since the late nineteenth century. The pattern can be explained by a slowdown in the AMOC and reduced northward heat transport, as well as an associated northward shift of the Gulf Stream. Comparisons with recent direct measurements from the RAPID project and several other studies provide a consistent depiction of record-low AMOC values in recent years.}, language = {en} }