Impact of the Euro Atlantic Teleconnection on Solar Power Generation in Reanalysis and Seasonal Forecast Systems.
Abstract
Accurate and reliable information from climate predictions at seasonal time-scales can have an essential role to anticipate climate variability affecting supply of solar energy and to stabilize and secure the energy network as a whole. A number of recognized modes of variability -often called teleconnections- explain a large part of Earth's climate variations and represent an important source of climate predictability. The leading atmospheric variability modes in the Euro-Atlantic sector (EATC) affect surface solar radiation downward (and temperature) anomalies in Europe and, therefore, the solar power generation.
Characterizing EATC in observations and assessing their simulation and prediction and their impact on the solar energy sector can help 1) to better understand patterns of seasonal-scale inter annual variability in solar resources and to consider to what extent this variability might be predictable up to several months in advance, 2) to formulate empirical prediction of local climate variability (relevant for the solar energy sector) based on the large scale atmospheric variability modes predicted by the forecast systems. To achieve this goal we analyze reanalysis dataset ERA5 and the multi-system seasonal forecast service provided by the Climate Data Store. Geopotential height anomalies at 500 hPa from the ERA5 have been employed to compute the four Euro-Atlantic teleconnections North Atlantic Oscillation, East Atlantic, Scandinavian and East Atlantic-West Russian The computation is based on the calculation of the first four EOF. Geopotential height anomalies at 500 hPa from the the multi-system seasonal forecast have been employed to calculate the time series of the indices associated with the observed EATC patterns, derived from projecting the re-forecast onto the four ERA5 EOF. Indices distribution has been compared to the reanalysis at different lead time and season. The impacts of those four variability modes have been assessed through correlation analysis of the teleconnection indices with surface solar radiation downward and with the photovoltaic capacity factor in both observed and predicted system. The analysis suggest the possibility to extract consistent informations on solar power generation from teleconnection patterns across reanalysis and seasonal prediction systems.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFMGC53I1203C
- Keywords:
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- 0360 Radiation: transmission and scattering;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 1610 Atmosphere;
- GLOBAL CHANGE