A climate network-based index to discriminate different types of El Niño and La Niña
| dc.contributor.author | Wiedermann, Marc | |
| dc.contributor.author | Radebach, Alexander | |
| dc.contributor.author | Donges, Jonathan F. | |
| dc.contributor.author | Kurths, Jürgen | |
| dc.contributor.author | Donner, Reik V. | |
| dc.contributor.institution | University of Aberdeen.Physics | en |
| dc.contributor.institution | University of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB) | en |
| dc.date.accessioned | 2017-08-11T09:00:12Z | |
| dc.date.available | 2017-08-11T09:00:12Z | |
| dc.date.embargoedUntil | 2017-01-14 | |
| dc.date.issued | 2016-07-16 | |
| dc.description | Funded by German Federal Ministry for Education and Research via the BMBF Young Investigators Group CoSy-CC2. Grant Number: 01LN1306A Planetary Boundary Research Network (PB.net) Earth League's EarthDoc DFG FAPESP Acknowledgments M.W. and R.V.D. have been supported by the German Federal Ministry for Education and Research via the BMBF Young Investigators Group CoSy-CC2 (grant 01LN1306A). J.F.D. thanks the Stordalen Foundation via the Planetary Boundary Research Network (PB.net) and the Earth League's EarthDoc program for financial support. J.K. acknowledges the IRTG 1740 funded by DFG and FAPESP. NCEP Reanalysis data are provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website http://www.esrl.noaa.gov/psd/. Parts of the analysis have been performed using the Python package pyunicorn [Donges et al., 2015b] available at https://github.com/pik-copan/pyunicorn. | en |
| dc.description.status | Peer reviewed | en |
| dc.format.extent | 10 | |
| dc.format.extent | 2951537 | |
| dc.identifier | 66130532 | |
| dc.identifier | d2ee3e72-95ad-423d-ba05-3b2a2709b21a | |
| dc.identifier | 84978484156 | |
| dc.identifier.citation | Wiedermann, M, Radebach, A, Donges, J F, Kurths, J & Donner, R V 2016, 'A climate network-based index to discriminate different types of El Niño and La Niña', Geophysical Research Letters, vol. 43, no. 13, pp. 7176-7185. https://doi.org/10.1002/2016GL069119 | en |
| dc.identifier.doi | 10.1002/2016GL069119 | |
| dc.identifier.iss | 13 | en |
| dc.identifier.issn | 0094-8276 | |
| dc.identifier.other | ArXiv: http://arxiv.org/abs/1604.04432v1 | |
| dc.identifier.uri | http://hdl.handle.net/2164/9128 | |
| dc.identifier.vol | 43 | en |
| dc.language.iso | eng | |
| dc.relation.ispartof | Geophysical Research Letters | en |
| dc.subject | physics.data-an | en |
| dc.subject | physics.ao-ph | en |
| dc.subject | QC Physics | en |
| dc.subject.lcc | QC | en |
| dc.title | A climate network-based index to discriminate different types of El Niño and La Niña | en |
| dc.type | Journal article | en |
