Impact of Euro-Atlantic teleconnection phases on satellite-based solar irradiance forecasting errors

Satellite-based solar irradiance forecasting plays a key role in the short-term management of photovoltaic (PV) power generation. It provides intraday Global Horizontal Irradiance (GHI) forecasts more accurate than NWP models, but their performance remains highly sensitive to cloud cover dynamics and synoptic weather situations.

Large-scale circulation over the Euro-Atlantic area can be commonly described by four leading teleconnection patterns: the North Atlantic Oscillation (NAO), East Atlantic (EA), East Atlantic–Western Russia (EAWR), and Scandinavian (SCA) patterns, each characterized by positive and negative phases. While their influence on climate variability and seasonal renewable energy production has been widely studied, their impact on satellite-based solar irradiance forecasting errors has never been quantified. Previous analyses have shown that individual NAO circulation indices can modulate solar irradiance forecast errors, motivating a comprehensive daily assessment of Euro-Atlantic teleconnection phases.

Here, we analyze eight years (2016-2023) of satellite-derived GHI forecasts at the SIRTA observatory near Paris (France). Four-hour-ahead forecasts with a 15-minute temporal resolution are generated using CMV-based extrapolation of geostationary satellite cloud fields and evaluated against pyranometer observations. Daily Euro-Atlantic teleconnection indices (NAO, EA, EAWR, SCA) are computed from ERA5 500 hPa geopotential height anomalies using an EOF-based methodology. Each day is classified according to the dominant teleconnection pattern and its positive or negative phase.

Forecast errors are quantified using the relative root mean square error (RRMSE) up to a lead time of 4 hours, with a particular focus on the 2-hour forecast horizon as a representative forecast skill assessment. The RRMSE across the full period is 30.8%. Distinct error regimes emerge across the eight teleconnection states (NAO±, EA±, EAWR±, SCA±), with generally lower forecast errors during NAO+, EA+, and SCA phases, and higher errors during NAO-, EA-, and EAWR phases.

Pronounced seasonal contrasts are observed, with the highest (37.4%) and lowest (27.9%) RRMSE values occurring in winter and summer, respectively. Variations in forecast errors across teleconnection phases reflect both circulation dominance and phase frequency. For example, EAWR- exhibits elevated errors in winter (+18.5% relative to the seasonal mean), which progressively decrease from spring to autumn, while NAO- shows reduced errors in winter (-12.8%) but increased errors during spring, summer, and autumn. RRMSE were elevated in winter and spring (20.5% and 7.7%) and reduced in summer and autumn (-15.8%, -6.3%) during EA+. Similar but opposite error patterns were observed during EA- phases across consecutive seasons.

These results highlight the importance of considering the full Euro-Atlantic teleconnection framework when interpreting satellite-based solar irradiance forecast performance. By extending teleconnection analysis to intraday forecast errors, this study demonstrates that large-scale circulation phases provide valuable information for understanding and anticipating variability in solar forecasting skill, with direct implications for PV forecasting and energy system management.