Articles | Volume 14
https://doi.org/10.5194/asr-14-35-2017
https://doi.org/10.5194/asr-14-35-2017
21 Feb 2017
 | 21 Feb 2017

Do modelled or satellite-based estimates of surface solar irradiance accurately describe its temporal variability?

Marc Bengulescu, Philippe Blanc, Alexandre Boilley, and Lucien Wald

Abstract. This study investigates the characteristic time-scales of variability found in long-term time-series of daily means of estimates of surface solar irradiance (SSI). The study is performed at various levels to better understand the causes of variability in the SSI. First, the variability of the solar irradiance at the top of the atmosphere is scrutinized. Then, estimates of the SSI in cloud-free conditions as provided by the McClear model are dealt with, in order to reveal the influence of the clear atmosphere (aerosols, water vapour, etc.). Lastly, the role of clouds on variability is inferred by the analysis of in-situ measurements. A description of how the atmosphere affects SSI variability is thus obtained on a time-scale basis. The analysis is also performed with estimates of the SSI provided by the satellite-derived HelioClim-3 database and by two numerical weather re-analyses: ERA-Interim and MERRA2. It is found that HelioClim-3 estimates render an accurate picture of the variability found in ground measurements, not only globally, but also with respect to individual characteristic time-scales. On the contrary, the variability found in re-analyses correlates poorly with all scales of ground measurements variability.

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Short summary
This study investigates the characteristic time-scales of variability found in long-term time-series of daily means of surface solar irradiance (SSI). Estimates of SSI from satellite-derived HelioClim-3 and radiation products from ERA-Interim and MERRA-2 re-analyses are compared to WRDC measurements. It is found that HelioClim-3 renders a more accurate picture of the variability found in ground measurements, not only globally, but also with respect to individual characteristic time-scales.