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In a new weekly update for pv magazine , Solcast, a DNV company, reports that South America saw above-average widespread irradiance in January, despite weak La Niña conditions. However, storm systems fueled by Atlantic moisture suppressed solar generation in parts of Brazil and Bolivia. South America recorded above-average irradiance in January, despite weak La Niña conditions. However, storm systems fueled by Atlantic moisture suppressed solar generation in parts of Brazil and Bolivia. According to analysis using the Solcast API, irradiance ranged from 15% above average in most regions to 10% below average in areas affected by storms. January 2025 was favourable for PV production in much of South America, with irradiance 5-15% above average. This observation contrasts with typical weak La Niña conditions, which do not usually bring such widespread increases in irradiance. Although some modelling agencies have declared La Niña conditions for January, supported by Pacific sea surface temperatures meeting La Niña thresholds, historical data show that weak events rarely trigger such increases in irradiance. Compared to similar ENSO years, January 2025 recorded higher irradiance anomalies, particularly over western and southern parts of the continent. This is consistent with previous forecasts predicting a bright summer season in the region. Furthermore, record-high sea surface temperatures, a current indicator of climate change, may be influencing and altering typical La Niña effects. However, not all of South America benefited from these trends. In parts of Brazil and Bolivia, irradiation levels fell 5% to 10% below average due to storms and associated cloud cover. These conditions were driven by stronger-than-usual trade winds, which carried abundant moisture from the abnormally warm Atlantic Ocean into the region. The heavy rainfall caused widespread flooding and landslides, particularly in southeastern Brazil and Bolivia. These disruptive precipitations and associated irradiance impacts highlight the challenge of predicting solar conditions in a variable tropical summer climate. La Niña and climate change add complexity to the task. Solcast produces these figures by globally tracking clouds and aerosols at 1-2 km resolution, using satellite data and proprietary AI/ML algorithms . This data is used to drive irradiance models, allowing Solcast to calculate irradiance at high resolution, with a typical bias of less than 2%, and also cloud tracking forecasts. This data is used by over 300 companies managing over 150 GW of solar assets worldwide. |
