 |
| Titel |
"Time-dependent flow-networks" |
| VerfasserIn |
Liubov Tupikina, Nora Molkentin, Cristobal López, Emilio Hernández-García, Norbert Marwan, Jürgen Kurths |
| Konferenz |
EGU General Assembly 2015
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250105167
|
| Publikation (Nr.) |
 EGU/EGU2015-4620.pdf |
|
|
|
|
|
| Zusammenfassung |
| Complex networks have been successfully applied to various systems such as
society, technology, and recently climate. Links in a climate network are defined
between two geographical locations if the correlation between the time series of
some climate variable is higher than a threshold. Therefore, network links are
considered to imply information or heat exchange. However, the relationship
between the oceanic and atmospheric flows and the climate network's structure is
still unclear. Recently, a theoretical approach verifying the correlation between
ocean currents and surface air temperature networks has been introduced, where the
Pearson correlation networks were constructed from advection-diffusion dynamics on
an underlying flow. Since the continuous approach has its limitations, i.e. high
computational complexity and fixed variety of the flows in the underlying system,
we introduce a new, method of flow-networks for changing in time velocity fields
including external forcing in the system, noise and temperature-decay.
Method of the flow-network construction can be divided into several steps: first
we obtain the linear recursive equation for the temperature time-series. Then we
compute the correlation matrix for time-series averaging the tensor product over
all realizations of the noise, which we interpret as a weighted adjacency matrix
of the flow-network and analyze using network measures.
We apply the method to different types of moving flows with geographical relevance
such as meandering flow. Analyzing the flow-networks using network measures we
find that our approach can highlight zones of high velocity by degree and
transition zones by betweenness, while the combination of these network measures
can uncover how the flow propagates within time. Flow-networks can be powerful
tool to understand the connection between system's dynamics and network's topology
analyzed using network measures in order to shed light on different climatic
phenomena. |
|
|
|
|
|
|