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Climate network stability measures of El Niño variability
Qing Yi Feng1, Henk A Dijkstra1
1Department of Physics and Astronomy, Institute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht University, Utrecht, The Netherlands.
Chaos (Woodbury, N.Y.)
|April 3, 2017
Summary
New network-based measures improve El Niño predictions by assessing Pacific climate state stability. These methods use only sea surface temperature data to indicate feedback amplification potential.
Area of Science:
- Climate Science
- Oceanography
- Atmospheric Science
Background:
- El Niño prediction success is limited by understanding the Pacific climate state's stability.
- This stability dictates whether sea surface temperature anomalies are amplified by ocean-atmosphere feedbacks.
- Existing methods like the Bjerknes stability index are hindered by data limitations.
Purpose of the Study:
- To introduce novel network-based measures for assessing Pacific climate state stability.
- To provide a data-efficient alternative for evaluating climate feedback mechanisms.
Main Methods:
- Development of new network-based stability measures.
- Evaluation using solely sea surface temperature (SST) data.
Main Results:
- The proposed network-based measures effectively indicate the potential for positive feedback amplification.
- These measures overcome the data constraints of traditional indices.
Conclusions:
- Network-based approaches offer a viable and data-efficient method for assessing climate stability.
- Improved stability assessment can enhance the accuracy of El Niño predictions.