@article {24437,
	title = {Testing reanalysis data sets in Antarctica: Trends, persistence properties, and trend significance},
	journal = {Journal of Geophysical Research - Atmospheres},
	volume = {121},
	year = {2016},
	month = {11/2016},
	pages = {12,839-12,855},
	publisher = {American Geophysical Union (United States)},
	abstract = {The reanalysis datasets provide very important sources for investigating the climate dynamics and climate changes in Antarctica. In this paper, five major reanalysis data are compared with observational Antarctic stations data over the last 36 years: the National Centers for Environmental Prediction and the National Center for Atmospheric Research Reanalysis (NCEP1), NCEP-DOE Reanalysis 2 (NCEP2), the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), the Japanese 55-year Reanalysis (JRA-55), and the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective-analysis for Research and Applications (MERRA). In our assessment, we compare the linear trends, the fluctuations around the trends, the persistence properties and the significance level of warming trends in the reanalysis data with the observational ones. We find that NCEP1 and NCEP2 show spurious warming trends in all parts of Antarctica except the Peninsula and JRA-55 exhibits spurious warming trends at several East Antarctic stations. On the other hand, ERA-Interim and MERRA are quite reliable, with only few exceptions. To investigate the persistence of the datasets, we consider the lag-1 autocorrelation C(1) and the Hurst exponent α. While C(1) varies quite erratically in different stations, the Hurst exponent shows similar patterns between observational and reanalysis data all over Antarctica. Regarding the significance of the trends, NCEP1 and NCEP2 differ considerably from observational datasets by strongly exaggerating the warming trends. Moreover, JRA-55 provides significant warming trends at Casey and Amundsen-Scott. In contrast, ERA-Interim and MERRA give reliable results at most stations except at Amundsen-Scott where ERA-Interim shows a significant cooling trend.},
	author = {Wang, Yang and Zhou, Dong and Bunde, Armin and Havlin, Shlomo}
}
@article {23835,
	title = {Long-Range Correlations and Memory in the Dynamics of Internet Interdomain Routing},
	journal = {PLoS ONE},
	year = {2015},
	publisher = {Public Library of Science},
	abstract = {Data transfer is one of the main functions of the Internet. The Internet consists of a large number of interconnected subnetworks or domains, known as Autonomous Systems (ASes). Due to privacy and other reasons the information about what route to use to reach devices within other ASes is not readily available to any given AS. The Border Gateway Protocol (BGP) is responsible for discovering and distributing this reachability information to all ASes. Since the topology of the Internet is highly dynamic, all ASes constantly exchange and update this reachability information in small chunks, known as routing control packets or BGP updates. In the view of the quick growth of the Internet there are significant concerns with the scalability of the BGP updates and the efficiency of the BGP routing in general. Motivated by these issues we conduct a systematic time series analysis of BGP update rates. We find that BGP update time series are extremely volatile, exhibit long-term correlations and memory effects, similar to seismic time series, or temperature and stock market price fluctuations. The presented statistical characterization of BGP update dynamics could serve as a basis for validation of existing and developing better models of Internet interdomain routing.},
	doi = {10.1371/journal.pone.0141481},
	url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0141481},
	author = {Kitsak, Maksim and Elmokashfi, Ahmed and Havlin, Shlomo and Krioukov, Dmitri}
}
@article {23836,
	title = {Long-Range Correlations and Memory in the Dynamics of Internet Interdomain Routing},
	journal = {PLoS ONE},
	year = {2015},
	publisher = {Public Library of Science},
	abstract = {Data transfer is one of the main functions of the Internet. The Internet consists of a large number of interconnected subnetworks or domains, known as Autonomous Systems (ASes). Due to privacy and other reasons the information about what route to use to reach devices within other ASes is not readily available to any given AS. The Border Gateway Protocol (BGP) is responsible for discovering and distributing this reachability information to all ASes. Since the topology of the Internet is highly dynamic, all ASes constantly exchange and update this reachability information in small chunks, known as routing control packets or BGP updates. In the view of the quick growth of the Internet there are significant concerns with the scalability of the BGP updates and the efficiency of the BGP routing in general. Motivated by these issues we conduct a systematic time series analysis of BGP update rates. We find that BGP update time series are extremely volatile, exhibit long-term correlations and memory effects, similar to seismic time series, or temperature and stock market price fluctuations. The presented statistical characterization of BGP update dynamics could serve as a basis for validation of existing and developing better models of Internet interdomain routing.},
	doi = {10.1371/journal.pone.0141481},
	url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0141481},
	author = {Kitsak, Maksim and Elmokashfi, Ahmed and Havlin, Shlomo}
}
@article {PhysRevLett.115.268501,
	title = {Teleconnection Paths via Climate Network Direct Link Detection},
	journal = {Phys. Rev. Lett.},
	volume = {115},
	year = {2015},
	month = {12/2015},
	pages = {268501},
	publisher = {American Physical Society},
	doi = {10.1103/PhysRevLett.115.268501},
	url = {http://link.aps.org/doi/10.1103/PhysRevLett.115.268501},
	author = {Zhou, Dong and Gozolchiani, Avi and Ashkenazy, Yosef and Havlin, Shlomo}
}
@article {PhysRevE.90.012803,
	title = {Simultaneous first- and second-order percolation transitions in interdependent networks},
	journal = {Phys. Rev. E},
	volume = {90},
	year = {2014},
	month = {07/2014},
	pages = {012803},
	publisher = {American Physical Society},
	doi = {10.1103/PhysRevE.90.012803},
	url = {http://link.aps.org/doi/10.1103/PhysRevE.90.012803},
	author = {Zhou, Dong and Bashan, Amir and Cohen, Reuven and Berezin, Yehiel and Shnerb, Nadav and Havlin, Shlomo}
}
@article {PhysRevE.88.052805,
	title = {Percolation of interdependent networks with intersimilarity},
	journal = {Phys. Rev. E},
	volume = {88},
	year = {2013},
	month = {11/2013},
	pages = {052805},
	publisher = {American Physical Society},
	doi = {10.1103/PhysRevE.88.052805},
	url = {http://link.aps.org/doi/10.1103/PhysRevE.88.052805},
	author = {Hu, Yanqing and Zhou, Dong and Zhang, Rui and Han, Zhangang and Rozenblat, C{\'e}line and Havlin, Shlomo}
}
