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Satellite-derived solar radiation for intra-hour and intra-day applications: biases and uncertainties by season and altitude
Accurate estimates of the surface solar radiation (SSR) are a prerequisite for intra-day forecasts of solar resources and photovoltaic power generation. Intra-day SSR forecasts are of interest to power traders and to operators of solar plants and power grids who seek to optimize their revenues and maintain the grid stability by matching power supply and demand. Our study analyzes systematic biases and the uncertainty of SSR estimates derived from Meteosat with the SARAH-2 and HelioMont algorithms at intra-hour and intra-day time scales. The satellite SSR estimates are analyzed based on 136 ground stations across altitudes from 200 m to 3570 m Switzerland in 2018. We find major biases and uncertainties in the instantaneous, hourly and daily-mean SSR. In peak daytime periods, the instantaneous satellite SSR deviates from the ground-measured SSR by a mean absolute deviation (MAD) of 110.4 and 99.6 W/m2 for SARAH-2 and HelioMont, respectively. For the daytime SSR, the instantaneous, hourly and daily-mean MADs amount to 91.7, 81.1, 50.8 and 82.5, 66.7, 42.9 W/m2 for SARAH-2 and HelioMont, respectively. Further, the SARAH-2 instantaneous SSR drastically underestimates the solar resources at altitudes above 1000 m in the winter half year. A possible explanation in line with the seasonality of the bias is that snow cover may be misinterpreted as clouds at higher altitudes.
- Federal Office of Meteorology and Climatology Switzerland
- Institute for Atmospheric and Climate Science Switzerland
- University of Zurich Switzerland
- ETH Zurich Switzerland
- Bern University of Applied Sciences Switzerland
FOS: Computer and information sciences, Computer Science - Machine Learning, FOS: Physical sciences, Bias and uncertainties assessment of global horizontal irradiance, Machine Learning (cs.LG), Surface solar radiation, Physics - Atmospheric and Oceanic Physics, Meteosat satellite and SwissMetNet pyranometers, Surface solar radiation; Meteosat satellite and SwissMetNet pyranometers; Bias and uncertainties assessment of global horizontal irradiance; Heliosat SARAH and HelioMont retrievals; Season and altitude dependence; Intra-hour and intra-day forecasting, Heliosat SARAH and HelioMont retrievals, Atmospheric and Oceanic Physics (physics.ao-ph), Season and altitude dependence, Intra-hour and intra-day forecasting
FOS: Computer and information sciences, Computer Science - Machine Learning, FOS: Physical sciences, Bias and uncertainties assessment of global horizontal irradiance, Machine Learning (cs.LG), Surface solar radiation, Physics - Atmospheric and Oceanic Physics, Meteosat satellite and SwissMetNet pyranometers, Surface solar radiation; Meteosat satellite and SwissMetNet pyranometers; Bias and uncertainties assessment of global horizontal irradiance; Heliosat SARAH and HelioMont retrievals; Season and altitude dependence; Intra-hour and intra-day forecasting, Heliosat SARAH and HelioMont retrievals, Atmospheric and Oceanic Physics (physics.ao-ph), Season and altitude dependence, Intra-hour and intra-day forecasting
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