Ratio of photosynthetically active radiation to global solar radiation above forest canopy in complex terrain: measurements and analyses based on Qingyuan Ker Towers

Understanding of the ratio of photosynthetic photon flux density (Qp) to global solar radiation (Rs) (Qp/Rs) is crucial for applying Rs to ecology-related studies. Previous studies reported Qp/Rs and its variations based on measurements from a single observatory tower, instead of multi-site-based measurements over complex terrains. This may neglect spatial heterogeneity in the terrain, creating a gap in an understanding of how terrain affects Qp/Rs and how this effect interacts with meteorological factors. Here the Qingyuan Ker Towers (three towers in a valley with different terrains: T1, T2, and T3) were utilized to measure Qp and Rs over mountainous forests of Northeast China. An airborne LiDAR system was used to generate a digital elevation model, and sky view factor of sectors (SVFs) divided from the field of view of tower’s pyranometer was calculated as a topographic factor to explain the variations of Qp/Rs. The results identified significant differences in Qp/Rs of the three towers at both daily and half-hour scales, with larger differences on clear days than on overcast days. Qp/Rs was positively correlated with SVFs of T1 and T3, while this correlation was negative with that of T2. The effect of SVFs on Qp/Rs interacted with clearness index, water vapor pressure and solar zenith angle. Random forest-based importance assessment demonstrated that explanation (R2) on Qp/Rs was improved when SVFs was included in the predictor variable set, indicating that incorporating terrain effects enhances the prediction accuracy of Qp/Rs. The improvement in the R2 values was more pronounced on clear days than on overcast days, suggesting that the effect of terrain on Qp/Rs depended on sky conditions. All findings suggested that Qp/Rs is affected by terrain, and integrating terrain information into existing Qp/Rs models is a feasible solution to improve Qp/Rs estimates in mountainous areas.