Abstract
Abstract The exponential growth in solar radiation measuring stations across the conterminous United States permits the generation of gridded solar irradiance data that capture the spatiotemporal variability of solar irradiance far more accurately than was previously possible from ground-based observations. Taking advantage of these observations, we generated a 30-yr climatology (1991–2020) of mean monthly global irradiance at a resolution of 30 arc s (∼800 m) on both a horizontal surface and a sloped ground surface. This paper describes the methods used to generate the gridded data, which include extensive quality control of station data, spatial interpolation of effective cloud transmittance using the “PRISM” method, and simulation of the effects of elevation, shading, and reflection from nearby terrain on solar irradiance. A comparison of the new dataset with several other solar radiation products reveals some spatial features in solar radiation that are either lacking or underresolved in some or all of the other datasets. Examples of these features include strong gradients near foggy coastlines and along mountain ranges where there is persistent orographically driven cloud formation. The workflow developed to create the long-term means will be used as a template for generating time series of monthly and daily solar radiation grids up to the present.
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