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

Inflection point optimization graph
Authors: 
Oliphant AJ, Stoy PC
Department Author(s): 
Published: 
2018
Journal Title or Book Publisher: 
Journal of Geophysical Research: Biogeosciences
Publication type: 

Citation

Oliphant, A.J. and Stoy, P.C. 2018. An evaluation of semi-empirical models for partitioning photosynthetically active radiation into diffuse and direct beam components. Journal of Geophysical Research: Biogeosciences, 123, 889-901.

Abstract: 
Photosynthesis is more efficient under diffuse than direct beam photosynthetically active radiation (PAR) per unit PAR, but diffuse PAR is infrequently measured at research sites. We examine four commonly used semiempirical models (Erbs et al., 1982, https://doi.org/10.1016/0038-092X(82)90302-4; Gu et al., 1999, https://doi.org/10.1029/1999JD901068; Roderick, 1999,  ttps://doi.org/10.1016/S0168-1923(99)00028-3; Weiss & Norman, 1985, https://doi.org/10.1016/0168-1923(85)90020-6) that partition PAR into diffuse and direct beam components based on the negative relationship between atmospheric transparency and scattering of PAR. Radiation observations at 58 sites (140 site years) from the La Thuille FLUXNET data set were used for model validation and coefficient testing. All four models did a reasonable job of predicting the diffuse fraction of PAR (ϕ) at the 30 min timescale, with site median r2 values ranging between 0.85 and 0.87, model efficiency coefficients (MECs) between 0.62 and 0.69, and regression slopes within 10% of unity. Model residuals were not strongly correlated with astronomical or standard meteorological 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 better overall than the two older models. Using the basic form of these models, the data set was used to find both individual site and universal model coefficients that optimized predictive accuracy. A new universal form of the model is presented in section 5 that increased site median MEC to 0.73. Site-specific model coefficients increased median MEC further to 0.78, indicating usefulness of local/regional training of coefficients to capture the local distributions of aerosols and cloud types.