McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions

Abstract

A new fast clear-sky model called McClear was developed to estimate the downwelling shortwave direct and global irradiances received at ground level under clear skies. McClear implements a fully physical modelling replacing empirical relations or simpler models used before. It exploits the recent results on aerosol properties, and total column content in water vapor and ozone produced by the MACC project (Monitoring Atmosphere Composition and Climate). It accurately reproduces the irradiance computed by the libRadtran reference radiative transfer model with a computational speed approximately 10⁵ times greater by adopting the abaci, or look-up tables, approach combined with interpolation functions. It is therefore suited for geostationary satellite retrievals or numerical weather prediction schemes with many pixels or grid points, respectively. McClear irradiances were compared to 1 min measurements made in clear-sky conditions in several stations within the Baseline Surface Radiation Network in various climates. For global, respectively direct, irradiance, the correlation coefficient ranges between 0.95 and 0.99, resp. 0.86 and 0.99. The bias is comprised between −14 and 25 W m⁻², resp. −49 and +33 W m⁻². The RMSE ranges between 20 W m⁻² (3% of the mean observed irradiance) and 36 W m⁻² (5%), resp. 33 W m⁻² (5%) and 64 W m⁻² (10%). These results are much better than those from state-of-the-art models. This work demonstrates the quality of the McClear model combined with MACC products, and indirectly the quality of the aerosol properties modeled by the MACC reanalysis

Validation of the Surface Downwelling Solar Irradiance Estimates of the HelioClim-3 Database in Egypt

“…In HC3v5, the GHI is firstly computed as in HC3v4, then divided by the ESRA clear-sky GHI and eventually multiplied by the McClear clear-sky GHI using the method described in [37]. McClear is a clear-sky model [18] based on look-up-tables and interpolation functions established with the radiative transfer model libRadtran [38,39]. One main advantage of McClear is that it runs 10 5 times faster than libRadtran.…”

“…Therefore, a cloud-screening algorithm needs to be applied on the ground measurements to separate the cloud-contaminated hours from the cloud-free hours. The cloud-screening algorithm of Lefevre et al [18] was employed, but slightly modified to account for the difference in temporal steps since it was designed for measurements available at 1 min, while in this case the step is 1 h. The clearness index KT, corrected clearness index KTcor, direct normal clearness index KTB n and diffuse fraction KD are respectively defined as:…”

“…The validation is performed for all-sky conditions as well as in cloud-free conditions. In the latter case, another comparison is made with the estimates of the McClear database, based on the McClear model which predicts the SSI that should be observed if the sky were cloud-free [18]. Such a model predicting cloud-free SSI is called clear-sky model in the following.…”

Validation of models that estimate the clear sky global and beam solar irradiance

“…It is a fully physical model developed by Mines Paris Tech (Lefèvre 2013). The core of the model consists of look-up tables (LUT) calculated with the help of the LibRadTran radiative transfer model Killing 2005, Mayer et al 2010) in a 10-dimensions space including aerosol optical depths at two wavelengths, partial aerosol optical depths for the determination of the aerosol type, the water vapor column and the ozone amount.…”

Probabilistic Solar Forecasting Using Quantile Regression Models

“…The target variable for the forecasting model is then the stochastic component. Here, we used the clear sky data provided by the McClear model [14] publicly available on the Solar radiation Data (SoDa) website [15]. This model uses aerosol optical depth, water vapor and ozone data from the MACC (Monitoring Atmospheric Composition and Climate) project [16].…”