## 1 Introduction
However, with increasing attention in the literature, nonlinear relationships between SIF and GPP have been revealed [30; 31; 32; 33], which have provided evidence for fluorescence and photosynthesis divergence at smaller spatiotemporal scales [34]. ChlF contains lots of information related to photosynthesis regarding the light utility efficiency and is closely related to plant vitality and biological yield. This means it is directly related to photosynthesis on the physiological level. SIF and GPP compete for absorbed light photons and an increase in the photosynthetic rate will reduce the ChlF. However, fluorescence is not only a \"photon competitor\"; when the incident light is too high, fluorescence acts as a \"protector\" that can emit excess light photons to protect the photosynthesis system from damage. The sensitivity of the relationship may change during the day and season with changes in light conditions, as well as varying by species. Despite there being empirical evidence that SIF has novel information about photosynthesis dynamics compared with previous remote sensing data [11; 23; 35], the mechanism link between SIF and GPP is still unclear. The coupling mechanism process of SIF and GPP on a seasonal scale also needs further study since the accuracy of GPP estimates by SIF is influenced by the multiple meteorological factors [36]. Airborne platforms and satellite remote sensing obtain instantaneous data of SIF on discrete days [34; 37]. SIF and GPP show daily variations with changes in incident radiation and the temporal and spatial distribution of SIF is more indicative than its absolute value [38] for estimating GPP. The connection between SIF and GPP is very complex and is difficult to explain by only analyzing satellite instantaneous fluorescence and daily average GPP [39]. Therefore, automatic and continuous ground observation data is necessary for exploring the dynamic changes between SIF and GPP [8; 25; 40]. However, most current research focus on croplands [17; 23] or grasslands [41], and there is a lack of research on forest ecosystems with more complex canopy structures and longer growth cycles [8]. Therefore, the feasibility of the linear relationship and its applicability to different time scales and plant functions needs to be verified and more research on forest ecosystems is needed to confirm the use of continuous ground-based SIF observations combined with tower-based GPP data to explore the links between SIF and GPP. We combine tower-based carbon flux and continuous ground far-red SIF data with meteorological data taken at a cork oak plantation at the Xiaolangdi station in Henan province, China, between June and November 2019, to explore the temporal change characteristics of SIF and its relationship with GPP under different weather conditions. The aim is to reveal the effects of changes in meteorological factors, such as radiation, on SIF and GPP and provide a theoretical basis to support the use of SIF to estimate ecosystem productivity. The major objectives of this study are as follows: (1) to explore the temporal distribution characteristics of SIF in the canopy of cork oak plantation, (2) to determine the relationship between canopy SIF and GPP on different time scales, and (3) to understand the impact of meteorological factors on the relationship between canopy SIF and GPP.