Abstract
AbstractEstimates of radiative fluxes under cloud‐free conditions (“clear‐sky”) are required in many fields, from climatic analyses of solar transmission to estimates of solar energy potential for electricity generation. Ideally, these fluxes can be obtained directly from measurements of solar fluxes at the surface. However, common standard methods to identify clear‐sky conditions require observations of both the total and the diffuse radiative fluxes at very high temporal resolution of minutes, which restricts these methods to a few, well‐equipped sites. Here we propose a simple method to estimate clear‐sky fluxes only from typically available global radiation measurements (Rsd) at (half‐)hourly resolution. Plotting a monthly sample of observed Rsd against the corresponding incoming solar radiation at the top of atmosphere (potential solar radiation) reveals a typical triangle shape with clear‐sky conditions forming a distinct, linear slope in the upper range of observations. This upper slope can be understood as the fractional transmission of solar radiation representative for cloud‐free conditions of the sample period. We estimate this upper slope through quantile regression. We employ data of 42 stations of the worldwide Baseline Surface Radiation Network to compare our monthly estimates with the standard clear‐sky identification method developed by Long and Ackerman (2000, https://doi.org/10.1029/2000JD900077). We find very good agreement of the derived fractional solar transmission (R2 = 0.73) across sites. These results thus provide confidence in applying the proposed method to the larger set of global radiation measurements to obtain further observational constraints on clear‐sky fluxes and cloud radiative effects.
Highlights
Solar radiation provides the main energy input to the Earth system and is of great importance for the local climate and human activities such as agriculture and solar energy generation
The proposed method relies on quantile regression which requires to choose a quantile ω to estimate the fractional clear‐sky shortwave transmission for a given sample
The explained variance of the monthly fractional solar transmission estimates is R2 = 0.79 at ω = 85% which is within a flat peak of the maximum correlation
Summary
Solar radiation provides the main energy input to the Earth system and is of great importance for the local climate and human activities such as agriculture and solar energy generation. Diurnal and seasonal variations in surface solar radiation are mainly determined by astronomical settings which determine the incoming solar radiation at the top of atmosphere (in the following referred to as potential solar radiation). Further variation is caused by the atmospheric conditions with clouds being the most dominant source of variation. The radiative properties of clouds contribute to most of the uncertainty in our ability to model and predict current and future climate (Bony et al, 2015). Apart from clouds, the solar beam is attenuated by the presence and concentration of gases and aerosols, which cause variations of Rsd in space and time (Iqbal, 1983)
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