@inproceedings{BarryBoettcherGrabensteinetal.2021,
  author    = {James Barry and Dirk B{\"o}ttcher and Johannes Grabenstein and Klaus Pfeilsticker and Anna Herman-Czezuch and Nicola Kimiaie and Stefanie Meilinger and Christopher Schirrmeister and Felix G{\"o}dde and Bernhard Mayer and Hartwig Deneke and Jonas Witthuhn and Philipp Hofbauer and Matthias Struck},
  title     = {Irradiance and atmospheric optical properties from photovoltaic power data: model improvements and first results},
  series = {EGU General Assembly 2021, Gather Online, 19-30 April 2021},
  publisher = {Copernicus GmbH},
  doi       = {10.5194/egusphere-egu21-7581},
  url       = {https://nbn-resolving.org/urn:nbn:de:hbz:1044-opus-54013},
  year      = {2021},
  abstract  = {Photovoltaic (PV) power data are a valuable but as yet under-utilised resource that could be used to characterise global irradiance with unprecedented spatio-temporal resolution. The resulting knowledge of atmospheric conditions can then be fed back into weather models and will ultimately serve to improve forecasts of PV power itself. This provides a data-driven alternative to statistical methods that use post-processing to overcome inconsistencies between ground-based irradiance measurements and the corresponding predictions of regional weather models (see for instance Frank et al., 2018). This work reports first results from an algorithm developed to infer global horizontal irradiance as well as atmospheric optical properties such as aerosol or cloud optical depth from PV power measurements.},
  language  = {en}
}