How good are existing, gridded solar irradiance datasets? If no good datasets exist, should we create one?!
To be specific: I need solar irradiance at the Earth’s surface, at high temporal and spatial resolution (15 minutely data @ 1km grid spacing would be great!), and at regular grid spacings, for several years. Ideally with uncertainty estimates.
Ground-based measurements of irradiance provide excellent accuracy; but very poor spatial coverage.
Satellite estimates of irradiance provide great spatial coverage but I’ve heard researchers say that satellite estimates provide poor accuracy, especially in developing countries. (These estimates basically look at satellite images of the Earth’s surface, and infer surface irradiance from the brightness of each pixel. But, of course, the brightness of each pixel is affected by albedo & angle of the surface, and the atmosphere between the Earth’s surface and the satellite).
Re-analyses like ERA5 are great for many meteorological parameters; but I’ve heard that they’re not great for irradiance.
If no good estimates of irradiance exist, should we look into developing an open dataset of irradiance, at high temporal and spatial resolution?! The basic idea might be to learn to infer irradiance from satellite imagery of clouds & water vapour, pollution data, and reanalyses. Use as much ground-based data as possible to train & calibrate the model (e.g. PV power output data). Maybe start in the UK. Does this sound like a good idea?!?