Cloud-driven patterns of surface solar irradiance as seen by a spatial network of radiometers
- Wageningen University, Meteorology & Air Quality, Wageningen, Netherlands (wbmol@wur.nl)
Surface solar irradiance varies on scales down to seconds or meters due to clouds. This highly variable nature of irradiance is not resolved by atmospheric models, yet heterogeneity in surface irradiance impacts the overlying cloud field. The inability to resolve irradiance variability, aside from insufficient model resolution, is explained by our limited understanding of cloud-driven solar irradiance variability at short spatiotemporal scales and the lack of high resolution spatial observational data. Cloud resolving models utilizing ray tracing techniques are a useful research tool, but ultimately require validation against observations.
In 2021, we gathered new observational data with a network of radiometers, specifically designed to gather data on cloud-driven surface patterns of irradiance. I will present results on various kinds of surface patterns in relation to cloud type and atmospheric conditions, based on these observations. Our radiometers sample surface solar irradiance at 10 Hz for 18 wavelengths, which we deployed in different setups in the FESSTVaL (Germany) and LIAISE (Spain) field campaigns. Our results highlight the complexity and wide range of regimes in spatiotemporal irradiance variability, but also provide insights into its driving mechanisms. These insights help guide the development of improved radiative transfer calculations, in order to move towards models that can accurately resolve irradiance variability in an operational setting.
How to cite: Mol, W., Heusinkveld, B., Hartogensis, O., and van Heerwaarden, C.: Cloud-driven patterns of surface solar irradiance as seen by a spatial network of radiometers, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5762, https://doi.org/10.5194/egusphere-egu23-5762, 2023.