Reconciling Observations of Solar Irradiance Variability With Cloud Size Distributions

Author:

Mol Wouter B.1ORCID,van Stratum Bart J. H.1ORCID,Knap Wouter H.2,van Heerwaarden Chiel C.1ORCID

Affiliation:

1. Meteorology and Air Quality Group Wageningen University Wageningen The Netherlands

2. Royal Netherlands Meteorological Institute De Bilt The Netherlands

Abstract

AbstractClouds cast shadows on the surface and locally enhance solar irradiance by absorbing and scattering sunlight, resulting in fast and large solar irradiance fluctuations on the surface. Typical spatiotemporal scales and driving mechanisms of this intra‐day irradiance variability are not well known, hence even 1 day ahead forecasts of variability are inaccurate. Here, we use long‐term, high‐frequency solar irradiance observations combined with satellite imagery, numerical simulations, and conceptual modeling to show how irradiance variability is linked to the cloud size distribution. Cloud shadow sizes are distributed according to a power law over multiple orders of magnitude, deviating only from the cloud size distribution due to cloud edge transparency at scales below ≈750 m. Locally cloud‐enhanced irradiance occurs as frequently as shadows, and is similarly driven mostly by boundary layer clouds, but distributed over a smaller range of scales. We reconcile studies of solar irradiance variability with those on clouds, which brings fundamental understanding to what drives irradiance variability. Our findings have implications not only for weather and climate modeling, but also for solar energy and photosynthesis by vegetation, where detailed knowledge of surface solar irradiance is essential.

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Koninklijk Nederlands Meteorologisch Instituut

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geophysics

Reference57 articles.

1. powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions

2. A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System

3. The MSG-SEVIRI-based cloud property data record CLAAS-2

4. Temporal Variability of Fair-Weather Cumulus Statistics at the ACRF SGP Site

5. Bosveld F.(2020).Meteo profiles ‐ validated tower profiles of wind dew point temperature and visibility at 10 min interval at Cabauw[Dataset]. Retrieved fromhttps://dataplatform.knmi.nl/dataset/cesar-tower-meteo-lb1-t10-v1-2

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