Visual Analysis of Spatio-Temporal Trends in Time-Dependent Ensemble Data Sets on the Example of the North Atlantic Oscillation

Dominik Vietinghoff, Christian Heine, Michael Bottinger, Nicola Maher, Johann Jungclaus, Gerik Scheuermann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

A driving factor of the winter weather in Western Europe is the North Atlantic Oscillation (NAO), manifested by fluctuations in the difference of sea level pressure between the Icelandic Low and the Azores High. Different methods have been developed that describe the strength of this oscillation, but they rely on certain assumptions, e.g., fixed positions of these two pressure systems. It is possible that climate change affects the mean location of both the Low and the High and thus the validity of these descriptive methods. This study is the first to visually analyze large ensemble climate change simulations (the MPI Grand Ensemble) to robustly assess shifts of the drivers of the NAO phenomenon using the uncertain northern hemispheric surface pressure fields. For this, we use a sliding window approach and compute empirical orthogonal functions (EOFs) for each window and ensemble member, then compare the uncertainty of local extrema in the results as well as their temporal evolution across different CO2 scenarios. We find systematic northeastward shifts in the location of the pressure systems that correlate with the simulated warming. Applying visualization techniques for this analysis was not straightforward; we reflect and give some lessons learned for the field of visualization.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 14th Pacific Visualization Symposium, PacificVis 2021
PublisherIEEE Computer Society
Pages71-80
Number of pages10
ISBN (Electronic)9781665439312
DOIs
Publication statusPublished - Apr 2021
Externally publishedYes
Event14th IEEE Pacific Visualization Symposium, PacificVis 2021 - Virtual, Tianjin, China
Duration: 19 Apr 202122 Apr 2021

Publication series

NameIEEE Pacific Visualization Symposium
Volume2021-April
ISSN (Print)2165-8765
ISSN (Electronic)2165-8773

Conference

Conference14th IEEE Pacific Visualization Symposium, PacificVis 2021
Country/TerritoryChina
CityVirtual, Tianjin
Period19/04/2122/04/21

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