An evaluation of semi-empirical models for partitioning photosynthetically active radiation into diffuse and direct beam components

Abstract

Photosynthesis is more efficient under diffuse than direct beam photosynthetically activeradiation (PAR) per unit PAR, but diffuse PAR is infrequently measured at research sites. We examine fourcommonly used semiempirical models (Erbs et al., 1982, https://doi.org/10.1016/0038-092X(82)90302-4; Guet al., 1999, https://doi.org/10.1029/1999JD901068; Roderick, 1999, https://doi.org/10.1016/S0168-1923(99)00028-3; Weiss & Norman, 1985, https://doi.org/10.1016/0168-1923(85)90020-6) that partition PARinto diffuse and direct beam components based on the negative relationship between atmospherictransparency and scattering of PAR. Radiation observations at 58 sites (140 site years) from the La ThuilleFLUXNET data set were used for model validation and coefficient testing. All four models did a reasonable jobof predicting the diffuse fraction of PAR (ϕ) at the 30 min timescale, with site median r2values rangingbetween 0.85 and 0.87, model efficiency coefficients (MECs) between 0.62 and 0.69, and regression slopeswithin 10% of unity. Model residuals were not strongly correlated with astronomical or standardmeteorological variables. We conclude that the Roderick (1999, https://doi.org/10.1016/S0168-1923(99)00028-3) and Gu et al. (1999, https://doi.org/10.1029/1999JD901068) models performed betteroverall than the two older models. Using the basic form of these models, the data set was used to find bothindividual site and universal model coefficients that optimized predictive accuracy. A new universal form ofthe model is presented in section 5 that increased site median MEC to 0.73. Site-specific modelcoefficients increased median MEC further to 0.78, indicating usefulness of local/regional training ofcoefficients to capture the local distributions of aerosols and cloud types.