Satellite-derived solar radiation for intra-hour and intra-day applications: Biases and uncertainties by season and altitude

TL;DR

This study evaluates biases and uncertainties in satellite-derived surface solar radiation estimates at intra-hour and intra-day scales, revealing significant deviations from ground measurements influenced by altitude and season, especially in winter.

Contribution

It provides a detailed analysis of biases in satellite SSR estimates using Meteosat data, highlighting altitude and seasonal effects, which improves understanding of satellite-based solar resource assessments.

Findings

Major biases in instantaneous SSR estimates from satellites.

Underestimation of solar resources at high altitudes in winter.

Seasonal bias linked to snow cover misinterpretation.

Abstract

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.