Teleconnection in atmospheric science refers to climate anomalies being related to each other at large distances (typically thousands of kilometers).
Teleconnections are recurrent – as similar patterns tend to occur repeatedly.
An emblematic teleconnection is that linking sea-level pressure at Tahiti and Darwin, Australia, which defines the atmospheric component of El Niño.
New study extracts dominant influence routes from massive climate datasets. It shows causal pathways between teleconnections.
The computing framework avoids ML. Phases include:
• Gridded data is transformed and stored in relational and graph databases for fast geospatial retrieval.
• The pipeline attacks dimensionality through spatial clustering.
• Causal processing: one representative time series per cluster is computed by the SLARAC method.
• A Yen’s k-shortest path algorithm extracts the most relevant causal chains.
Cruz, J. E. C., da Rocha, V. R., de Andrade, F. M., & Quiles, M. G. (2026). "A multivariate causal chain detection methodology assessed on the ENSO modulation of the Northeastern Brazil precipitation" https://doi.org/10.1007/s41060-026-01322-3
#ENSO #ElNiño #causality #climate #weather #SLARAC #networks #dataEngineering #Brazil
