51162
2018
2018
eng
12
11
91
article
Springer
New York
1
--
2018-11-26
--
Wavelet-based multiscale similarity measure for complex networks
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.
The European physical journal : B, Condensed matter and complex systems
10.1140/epjb/e2018-90460-6
1434-6028
1434-6036
wos:2018
296
WOS:000451065900003
Agarwal, A (reprint author), Leibniz Assoc, Potsdam Inst Climate Impact Res PIK, Potsdam, Germany.; Agarwal, A (reprint author), Univ Potsdam, Inst Earth & Environm Sci, Potsdam, Germany.; Agarwal, A (reprint author), GFZ German Res Ctr Geosci, Sect Hydrol 5 4, Potsdam, Germany., agarwal@pik-potsdam.de
Deutsche Forschungsgemeinschaft (DFG)German Research Foundation (DFG) [GRK 2043/1]; Humboldt FoundationAlexander von Humboldt Foundation; Alexander Von Humboldt Fellowship award; DST, IndiaDepartment of Science & Technology (India)
2021-06-29T10:13:21+00:00
sword
importub
filename=package.tar
339a1f03d8e0164b21e1466c99e27fe8
Agarwal, Ankit
false
true
Ankit Agarwal
Rathinasamy Maheswaran
Norbert Marwan
Levke Caesar
Jürgen Kurths
eng
uncontrolled
Statistical and Nonlinear Physics
Physik
Institut für Physik und Astronomie
Referiert
Import
53918
2018
2018
eng
10
9
article
Nature Publ. Group
London
1
2018-12-03
2018-01-03
--
Abrupt transitions in time series with uncertainties
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 Niño-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.
Nature Communications
10.1038/s41467-017-02456-6
29298987
2041-1723
wos:2018
48
WOS:000419308000009
Goswami, B (reprint author), Potsdam Inst Climate Impact Res, Transdisciplinary Concepts & Methods, D-14412 Potsdam, Germany.; Goswami, B (reprint author), Univ Potsdam, Inst Earth & Environm Sci, Karl Liebknecht Str 24-25, D-14476 Potsdam, Germany., goswami@pik-potsdam.de
DFG/FAPESP [IRTG 1740/TRP 2011/50151-0]; DFG project IUCLiDGerman Research Foundation (DFG) [DFG MA4759/8]; Alexander von Humboldt FoundationAlexander von Humboldt Foundation; German Federal Ministry for Education and ResearchFederal Ministry of Education & Research (BMBF); DFGGerman Research Foundation (DFG); Government of the Russian Federation [14.Z50.31.0033]; European Unions Horizon Research and Innovation programme under the Marie Sklodowska-Curie grantEuropean Union (EU) [691037]; MWFK Brandenburg
2022-02-16T09:44:44+00:00
sword
importub
filename=package.tar
cf57aa54d58090130cbf9de67b825ae4
<a href="https://doi.org/10.25932/publishup-42311">Zweitveröffentlichung in der Schriftenreihe Postprints der Universität Potsdam : Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 576 </a>
Goswami, Bedartha
false
true
CC-BY - Namensnennung 4.0 International
Bedartha Goswami
Niklas Boers
Aljoscha Rheinwalt
Norbert Marwan
Jobst Heitzig
Sebastian Franz Martin Breitenbach
Jürgen Kurths
Geowissenschaften
Institut für Geowissenschaften
Referiert
Import
Gold Open-Access
DOAJ gelistet
50779
2018
2018
eng
103
119
17
1
152
article
Springer
Dordrecht
1
2018-11-01
2018-11-01
--
Climate change perception
Climate change and variability have created widespread risks for farmers’ food and livelihood security in the Himalayas. However, the extent of impacts experienced and perceived by farmers varies, as there is substantial diversity in the demographic, social, and economic conditions. Therefore, it is essential to understand how farmers with different resource-endowment and household characteristics perceive climatic risks. This study aims to analyze how farmer types perceive climate change processes and its impacts to gain insight into locally differentiated concerns by farming communities. The present study is based in the Uttarakhand state of Indian Western Himalayas. We examine farmer perceptions of climate change and how perceived impacts differ across farmer types. Primary household interviews with farming households (n = 241) were done in Chakrata and Bhikiyasian tehsil in Uttarakhand, India. In addition, annual and seasonal patterns of historical data of temperature (1951–2013) and precipitation (1901–2013) were analyzed to estimate trends and validate farmers’ perception. Using statistical methods farmer typology was constructed, and five unique farmer types are identified. Majority of respondents across all farmer types noticed a decrease in summer and winter precipitation and an increase in summer temperature. Whereas the perceptions of impacts of climate change diverged across farmer types, as specific farmer types exclusively experienced few impacts. Impact of climatic risks on household food security and income was significantly perceived stronger by low-resource-endowed subsistence farmers, whereas the landless farmer type exclusively felt impacts on the communities social bond. This deeper understanding of the differentiated perception of impacts has strong implications for agricultural and development policymaking, highlighting the need for providing flexible adaptation options rather than specific solutions to avoid inequalities in fulfilling the needs of the heterogeneous farming communities.
Climatic change : an interdisciplinary, intern. journal devoted to the description, causes and implications of climatic change
an analysis of climate change and risk perceptions among farmer types of Indian Western Himalayas
10.1007/s10584-018-2314-z
0165-0009
1573-1480
wos:2019
WOS:000457271900007
Joshi, PK (reprint author), Jawaharlal Nehru Univ, Sch Environm Sci, New Delhi 110067, India.; Joshi, PK (reprint author), Jawaharlal Nehru Univ, Special Ctr Disaster Res, New Delhi 110067, India., pkjoshi27@hotmail.com
MoEFCC, GoI [R&D/NNRMS/2/2013-14]; Deutsche Forschungsgemeinschaft (DFG) within the "NatRiskChange" graduate research training group at the University of Potsdam [GRK 2043/1]; Erasmus+ funding
2021-05-21T08:40:59+00:00
sword
importub
filename=package.tar
e37272903331f3cca99437828a5fad2e
Joshi, P.K.
false
true
Roopam Shukla
Ankit Agarwal
Kamna Sachdeva
Jürgen Kurths
P. K. Joshi
Geowissenschaften
Referiert
Institut für Umweltwissenschaften und Geographie
Import
Green Open-Access
42311
2018
2019
eng
10
576
postprint
1
2019-02-05
2019-02-05
--
Abrupt transitions in time series with uncertainties
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.
Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
10.25932/publishup-42311
urn:nbn:de:kobv:517-opus4-423111
1866-8372
online registration
Nature Communications 9 (2018) 48 DOI: 10.1038/s41467-017-02456-6
<a href="http://publishup.uni-potsdam.de/53918">Bibliographieeintrag der Originalveröffentlichung/Quelle</a>
CC-BY - Namensnennung 4.0 International
Bedartha Goswami
Niklas Boers
Aljoscha Rheinwalt
Norbert Marwan
Jobst Heitzig
Sebastian Franz Martin Breitenbach
Jürgen Kurths
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
576
eng
uncontrolled
North-Atlantic climate
eng
uncontrolled
Indian monsoon
eng
uncontrolled
Holocene
eng
uncontrolled
teleconnections
eng
uncontrolled
variability
eng
uncontrolled
periods
eng
uncontrolled
records
Naturwissenschaften und Mathematik
open_access
Mathematisch-Naturwissenschaftliche Fakultät
Referiert
Open Access
Universität Potsdam
https://publishup.uni-potsdam.de/files/42311/pmnr576.pdf
52534
2018
2018
eng
8
7
28
article
American Institute of Physics
Melville
1
2018-07-06
--
--
Complex networks for tracking extreme rainfall during typhoons
Reconciling the paths of extreme rainfall with those of typhoons remains difficult despite advanced forecasting techniques. We use complex networks defined by a nonlinear synchronization measure termed event synchronization to track extreme rainfall over the Japanese islands. Directed networks objectively record patterns of heavy rain brought by frontal storms and typhoons but mask out contributions of local convective storms. We propose a radial rank method to show that paths of extreme rainfall in the typhoon season (August-November, ASON) follow the overall southwest-northeast motion of typhoons and mean rainfall gradient of Japan. The associated eye-of-the-typhoon tracks deviate notably and may thus distort estimates of heavy typhoon rainfall. We mainly found that the lower spread of rainfall tracks in ASON may enable better hindcasting than for westerly-fed frontal storms in June and July.
Chaos : an interdisciplinary journal of nonlinear science
10.1063/1.5004480
30070498
1054-1500
1089-7682
wos:2018
075301
WOS:000440606100018
Ozturk, U (reprint author), Potsdam Inst Climate Impact Res PIK, D-14476 Potsdam, Germany.; Ozturk, U (reprint author), Univ Potsdam, Inst Earth & Environm Sci, D-14473 Potsdam, Germany., ugur.oeztuerk@uni-postdam.de
Deutsche Forschungsgemeinschaft (DFG) within the Research Training Group at the University of Potsdam [DFG GRK 2043/1]
2021-11-08T12:08:20+00:00
sword
importub
filename=package.tar
4d06bdc2a5529c1ab0f5918fc3cd227c
Ozturk, Ugur
false
true
Ugur Ozturk
Norbert Marwan
Oliver Korup
H. Saito
Ankit Agarwa
M. J. Grossman
M. Zaiki
Jürgen Kurths
Physik
Institut für Physik und Astronomie
Referiert
Import
Green Open-Access
52318
2018
2018
eng
802
810
9
563
article
Elsevier
Amsterdam
1
2018-06-23
--
--
Quantifying the roles of single stations within homogeneous regions using complex network analysis
Regionalization and pooling stations to form homogeneous regions or communities are essential for reliable parameter transfer, prediction in ungauged basins, and estimation of missing information. Over the years, several clustering methods have been proposed for regional analysis. Most of these methods are able to quantify the study region in terms of homogeneity but fail to provide microscopic information about the interaction between communities, as well as about each station within the communities. We propose a complex network-based approach to extract this valuable information and demonstrate the potential of our approach using a rainfall network constructed from the Indian gridded daily precipitation data. The communities were identified using the network-theoretical community detection algorithm for maximizing the modularity. Further, the grid points (nodes) were classified into universal roles according to their pattern of within- and between-community connections. The method thus yields zoomed-in details of individual rainfall grids within each community.
Journal of hydrology
10.1016/j.jhydrol.2018.06.050
0022-1694
1879-2707
wos:2018
WOS:000441492700064
Agarwal, A (reprint author), Univ Potsdam, Inst Earth & Environm Sci, Potsdam, Germany., aagarwal@uni-potsdam.de
Deutsche Forschungsgemeinschaft (DFG) within the graduate research training group "Natural risk in a changing world (NatRiskChange)" at the University of PotsdamGerman Research Foundation (DFG) [GRK 2043/1]; Humboldt FoundationAlexander von Humboldt Foundation
2021-10-20T09:05:02+00:00
sword
importub
filename=package.tar
c023fcc4e0597c334a559d37a9682f9e
Agarwal, Ankit
false
true
Ankit Agarwal
Norbert Marwan
Rathinasamy Maheswaran
Bruno Merz
Jürgen Kurths
eng
uncontrolled
Complex network
eng
uncontrolled
Event synchronization
eng
uncontrolled
Rainfall network
eng
uncontrolled
Z-P approach
Geowissenschaften
Institut für Geowissenschaften
Referiert
Import
Green Open-Access