This paper examines the skill of a regional reanalysis COSMO-REA6 compared to BSRN observations. They found a systematic error in the reanalysis:
An underestimation of GHI in clear sky conditions – due to the aerosol climatology which causes too strong solar extinction.
An overestimation of GHI in cloudy sky conditions – due to the underestimation of optical depth of clouds.
Therefore, a post-processing method was developed to improve both regimes separately. A different scaling factor is developed for clear sky and cloudy sky situations. The situations were separated based on transmissivities.
For cloudy conditions twelve scaling factors were estimated, one for each month. While for clear sky conditions six scaling factors were estimated for different solar elevation regimes. There was a reduction in the systematic bias (Figure 1).
They also examined ramp events on scales of 3h, 1h and 30mins. The observed ramp rates are well represented on the longer time scales but on smaller time scales the performance decreases and ramp rates are underestimated.
Relevancy for our work:
Consider separating our post-processing methods depending on current weather situations.
Examine the solar energy ramp rates.
To remember when working with daily mean values, BSRN stations only take measurements when the solar angles are greater than 10°, whereas some reanalysis estimates include all values.
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.
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.
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.