Recent advances in satellite observations of solar‐induced chlorophyll fluorescence (SIF) provide a new opportunity to constrain the simulation of terrestrial gross primary productivity (GPP). Accurate representation of the processes driving SIF emission and its radiative transfer to remote sensing sensors is an essential prerequisite for data assimilation. Recently, SIF simulations have been incorporated into several land surface models, but the scaling of SIF from leaf‐level to canopy‐level is usually not well‐represented. Here, we incorporate the simulation of far‐red SIF observed at nadir into the Community Land Model version 5 (CLM5). Leaf‐level fluorescence yield was simulated by a parametric simplification of the Soil Canopy‐Observation of Photosynthesis and Energy fluxes model (SCOPE). And an efficient and accurate method based on escape probability is developed to scale SIF from leaf‐level to top‐of‐canopy while taking clumping and the radiative transfer processes into account. SIF simulated by CLM5 and SCOPE agreed well at sites except one in needleleaf forest (R² > 0.91, root‐mean‐square error 0.68). At the global scale, simulated SIF generally captured the spatial and seasonal patterns of satellite‐observed SIF. Factors including the fluorescence emission model, clumping, bidirectional effect, and leaf optical properties had considerable impacts on SIF simulation, and the discrepancies between simulate d and observed SIF varied with plant functional type. By improving the representation of radiative transfer for SIF simulation, our model allows better comparisons between simulated and observed SIF toward constraining GPP simulations.

The magnitude of the terrestrial carbon sink remains a key uncertainty in future climate projections, in part due to poorly understood links between carbon uptake and its allocation to woody biomass in vegetation. Here, in this study, we show that photosynthesis and aboveground growth occur asynchronously across diel to seasonal scales in eight North American oak species. Across 137 tree ring sites, current-year annual growth was insensitive to climate variability after midsummer despite 26 to 36% of annual gross primary productivity (GPP) occurring during this period. Hourly GPP flux and growth measurements at four sites spanning seven site years further demonstrate that wood formation ceases earlier than photosynthesis and is restricted to periods of low atmospheric aridity and temperature. This photosynthesis-growth decoupling intensifies with interannual variability in vapor pressure deficit ( r = 0.86, P < 0.05), suggesting that by assuming tight coupling between photosynthesis and woody biomass, current earth system models may overestimate long-term carbon sequestration in forests.

Solar-induced chlorophyll fluorescence is closely related to photosynthesis and can serve as an indicator of plant status. Several methods have been proposed to retrieve fluorescence signal (Fs) either at specific spectral bands or within the whole fluorescence emission region. In this study, we investigated the precision of the fluorescence signal obtained through these methods under various sensor spectral characteristics. Simulated datasets generated by the SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) model with known ‘true’ Fs as well as an experimental dataset are exploited to investigate four commonly used Fs retrieval methods, namely the original Fraunhofer Line Discriminator method (FLD), the 3 bands FLD (3FLD), the improved FLD (iFLD), and the Spectral Fitting Methods (SFMs). Fluorescence Spectrum Reconstruction (FSR) method is also investigated using simulated datasets. The sensor characteristics of spectral resolution (SR) and signal-to-noise ratio (SNR) are taken into account. According to the results, finer SR and SNR both lead to better accuracy. Lowest precision is obtained for the FLD method with strong overestimation. Some improvements are made by the 3FLD method, but it still tends to overestimate. Generally, the iFLD method and the SFMs provide better accuracy. As to FSR, the shape and magnitude of reconstructed Fs are generally consistent with the ‘true’ Fs distributions when fine SR is exploited. With coarser SR, however, though R² of the retrieved Fs may be high, large bias is likely to be obtained as well.

Solar-Induced chlorophyll Fluorescence (SIF) measured by a remote sensor offers a nondestructive method for evaluation of plant physiological conditions. Models that are capable of accurately simulating radiative transfer (RT) of SIF in three-dimensional (3-D) canopy are needed to understand the mechanism of the RT of SIF flux within the vegetation canopy and better interpret the measured SIF signal. A model based on the radiosity method to simulate the RT of SIF in 3-D canopy, FluorRGM (Fluorescence model with Radiosity-Graphics combined Method), was proposed and evaluated. The radiosity method is a mathematical concept adopted in computer graphics applications to describe the scattering of light between Lambertian surfaces. It has the advantage of high efficiency by applying the mature techniques in computer graphics. The adaption of the radiosity method to simulate RT of SIF is implemented in a physically-based and rigorous way. Comparisons of simulated SIF with a validated Monte Carlo ray-tracing model (FluorWPS) show that FluorRGM can accurately simulate the RT of SIF for 3-D canopies.

Since solar-induced chlorophyll fluorescence (SIF) of vegetation is closely linked to photosynthetic efficiency, it shows great potential that SIF can be exploited to monitor plant status. Since the spectrum of SIF can be used to obtain useful information like peak-ratio and spectral positions of the left and right peaks, it is valuable to retrieve the whole SIF spectrum accurately. In this study, the accuracies of three SIF spectrum reconstruction algorithms, i.e. the Full-spectrum Spectral Fitting Method (F-SFM), the Fluorescence Spectrum Reconstruction (FSR) method, and the SpecFit method, were investigated using simulated datasets. Results show that under most circumstances, the methods of F-SFM and FSR can provide more accurate reconstructed spectra than the SpecFit method.