Article Title: Tropical Forcing of the Summer East Atlantic Pattern
Published in Geophysical Research Letters journal in October 2017.
The paper has focused on the second mode of atmospheric summer variability in the Euro-Atlantic sector – the summer East Atlantic pattern (SEA). Recurring to reanalysis data, the authors defined the SEA and showed that (1) the SEA has influence on cloudiness, temperature and precipitation over Europe and (2) that to some extent, the interannual variability of the SEA is forced by diabatic heating anomalies in the tropical Pacific and Caribbean.
These diabatic heating anomalies come from a precipitation dipole defined as the “Pacific-Caribbean Dipole” – captured as the PCD index – which is related to SST anomalies arising from the ENSO phases. These anomalies therefore influence the PCD index, which by changing the amount of local radiative heating, can induce a Rossby wave train which influences the SEA. As the SEA was further related to cloud cover in some parts of Europe, SEA variability influences temperature and precipitation.
This paper therefore hints at the fact that some temperature extremes in Europe had some tropical forcing. In addition to that, given that some lag-lead correlations were demonstrated between ENSO and both the PCD index and the SEA, there is some potential for prediction of boreal summer variability.
The second mode of boreal summer variability is influenced by anomalies occurring in the tropics, with some lag-lead relationships offering potential for predictability of cloudiness, temperature and precipitation in Europe in the summer, through the forecasting of the SEA phase.
Relevancy for our research:
Better understanding atmospheric variability in the European summer increases the understanding of renewable power sources variability, as their operation is connected to various meteorological variables impacted by the EA pattern, such as temperature and cloudiness. Additionally, these variables influence electricity demand. Although the North Atlantic Oscillation is fairly more studied in the topic of predictability and seasonal forecasting, furthering potential predictability to the secondary mode of variability will add further opportunities of renewable energy forecasting.