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

Background Understanding of the ratio of photosynthetic photon flux density ( Q p ) to global solar radiation ( R s ) ( Q p / R s ) is crucial for applying R s to ecology-related studies. Previous studies reported Q p / R s 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 Q p / R s and how this effect interacts with meteorological factors. Methods Here the Qingyuan Ker Towers (three towers in a valley with different terrains: T1, T2, and T3) were utilized to measure Q p and R s over mountainous forests of Northeast China. An airborne LiDAR system was used to generate a digital elevation model, and sky view factor of sectors (SVF s ) divided from the field of view of tower’s pyranometer was calculated as a topographic factor to explain the variations of Q p / R s . Results The results identified significant differences in Q p / R s of the three towers at both daily and half-hour scales, with larger differences on clear days than on overcast days. Q p / R s was positively correlated with SVF s of T1 and T3, while this correlation was negative with that of T2. The effect of SVF s on Q p / R s interacted with clearness index, water vapor pressure and solar zenith angle. Random forest-based importance assessment demonstrated that explanation ( R 2 ) on Q p / R s was improved when SVF s was included in the predictor variable set, indicating that incorporating terrain effects enhances the prediction accuracy of Q p / R s . The improvement in the R 2 values was more pronounced on clear days than on overcast days, suggesting that the effect of terrain on Q p / R s depended on sky conditions. Conclusions All findings suggested that Q p / R s is affected by terrain, and integrating terrain information into existing Q p / R s models is a feasible solution to improve Q p / R s estimates in mountainous areas.