Journal Club: 01-11-2018

Article title: Does the lower stratosphere provide predictability for month-ahead wind electricity generation in Europe?

Published in the Quarterly Journal of the Royal Meteorological Society in 2017.

This paper’s work aims at assessing a potential relationship between the lower stratosphere and month-ahead wind electricity generation in Europe which could be used to improve wind electricity generation forecasts.

Geopotential height anomalies at 150 hPa (indicator of the state of the lower stratospheric circulation) were used, averaged over the domain of 60 N to the North Pole. These anomalies are grouped into percentile bins, which indicate different intensities of the polar-vortex. For wind energy generation, daily capacity factor (CF) anomalies are computed from a 31 day running mean. Geopotential height and wind speeds anomalies composites are analyzed to check on the relationship between different vortex events (strong and weak) over the stratosphere, and wind speed anomalies in the troposphere, as well the temporal evolution of both anomalies before and after the events. This enables the observation of the coupling of the flow in “high” and “low” altitudes.

Figure: Composite mean of geopotential height anomalies averaged over the polar cap north of 60N in units of standard deviations (with respect to the variability of from 60 days before until 60 days after strong vortex events in different bins (rows). Right column refers to weak polar events. The bold black line indicates the 150 hPa level. The numbers in brackets in the panel titles indicate the number of events that are included in the respective bins.

Although the strong polar vortex events can be start showing up to 40 days before the event (a), it is in the weak polar vortex events (e) that a clear downward propagation of the geopotencial height anomalies can be seen. These relationships are a results of persistent long-lived periods with NAO+ or NAO- conditions, and they offer potential for some wind generation predictability but, as shown in the work, this predictability varies greatly amongst different regions of Europe, with countries in northern Europe (Sweden, Denmark) achieving higher scores in the wind electricity generation forecasts, when comparing with countries in southern Europe (Italy, Spain). Moderate predictability is found for countries like Germany, UK and Poland. This is due to the geographical location of the mentioned countries in relation to the location of the strongest geopotential anomalies – highest predictability is found for locations consistently under the spatial range of those anomalies for the various bins.


This work suggests that anomalous flow conditions in the lower stratosphere offer month-ahead predictability of wind electricity generation in Europe, specially for Northern Europe.


Journal Club: 08-05-2018

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.

Regressions of the ERA-interim derived SEA index onto surface temperature (left plot) and total precipitation (right plot). Hatched areas represent areas where the assessed relationships are statistically significant. Note the black boxes on the plot in the right, outlining the areas from where the PCD index was defined.

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.


EGU2018: Regional wind-solar complementarity and atmospheric pressure patterns – a case study for Ireland & the UK

Last month I attended EGU2018 in Vienna, where I presented a poster titled “Regional wind-solar complementarity and atmospheric pressure patterns – a case study for Ireland & the UK” . This poster was part of the “Energy meteorology and spatial modelling of renewable energies” session (ERE3.1), which was a subset of the “Non-carbon based energy” session, part of the Energy, Resources and the Environment programme group (ERE).

Expanding on previously assessed relationships between both solar and wind resources and large scale atmospheric pressure patterns (NAO, EA pattern; SCAND pattern), this work investigated how both energetic resources respond to those patterns’ interannual variability. This was performed aiming at the assessment of potential winter season spatial complementarity between wind and solar resources in the Ireland and UK region. Further exploration of these results will shed more light on energy resources variability and potentially strengthen future renewable energy mixes’ resilience to interannual scale natural variability of atmospheric conditions.

I also saw several interesting talks from the following sessions: Climate variability of the Atlantic and Europe; Energy meteorology and spatial modelling of renewable energies. In addition, I saw some interesting posters from various sessions.


EMS2017: Large scale atmospheric circulation patterns and solar energy resources in the UK and Ireland

I attended the EMS2017 in DCU, Dublin in September 2017, where I presented a poster titled “Large scale atmospheric circulation patterns and solar energy resources in the UK and Ireland”. This work was part of the Energy Meteorology session (OSA2.6).

In this work I focused on the links between some large scale atmospheric circulation patterns (North Atlantic Oscillation; East Atlantic pattern and the Scandinavian pattern) and solar energy resources in Ireland and the UK. This was investigated using a reanalysis product (MERRA-2) and additionally observations for the island of Ireland. The relationship between the winter short-wave solar radiation and some of those patterns is characterized by east-west gradients in the correlation signal. This was shown with MERRA-2 for Ireland and the UK mainland; and with pyranometer observations for the island of Ireland. This information can be potentially used in solar energy resource assessments which aim at power facility location selection for energy balancing purposes.

In addition, I saw several interesting talks from the following sessions: Energy Meteorology; Mid-latitude atmospheric teleconnections; Climate monitoring: data rescue, management, quality and homogenization; Climate change detection, assessment of trends, variability and extremes.