Introducing AustroSIF: A compilation of combined passive and active fluorescence data at flux tower sites across Europe; dataset overview and potential applications

Remote sensing of sun-induced fluorescence (SIF) provides a valuable tool to assess vegetation state and productivity at large spatial scales and in an unintrusive way. SIF is the absorbed light re-emitted by chlorophyll pigments in the red to infrared range (650-850 nm). It represents one of the three main mechanisms that plants use to dissipate the absorbed light energy, the other two being photochemistry and thermal dissipation (non-photochemical quenching, NPQ). Because both photosynthesis and SIF emission occur at the chloroplast level and share the same excitation energy, SIF can be related to photosynthesis. SIF has been successfully used to predict GPP and the absorbed photosynthetic active radiation (APAR), and in recent years, it has been implemented in state-of-the-art radiative transfer models and several TBMs. Still, the development of SIF-based methods for the prediction of GPP is hindered by the lack of data, especially in regard to coupled GPP-SIF-NPQ estimates. The NPQ mechanism has proven to be the dominant energy dissipation pathway, especially during extreme heat events, and it is the key missing element to correctly relate SIF to GPP. However, so far, SIF has mostly been linked to GPP in a simplistic way, without properly considering the effect of NPQ and with no explicit calculation of the allocation of excitation energy. The present work aims at presenting a novel dataset from the AustroSIF project. In this project, we collected time series of ground-based active and passive chlorophyll fluorescence and hyperspectral reflectance from 7 eddy-covariance flux tower sites in Europe. The dataset includes sites from Austria, Italy, Poland, Germany and Spain. Key variables present in the dataset include GPP from eddy-covariance, SIF and reflectance-based indices from tower-mounted hyperspectral spectrometers, as well as NPQ, photochemical quenching (PQ), and electron transport rate (ETR) from a continuous pulse amplitude modulation (PAM) instrument. These data have been obtained for periods varying from 3 to 9 months per site between 2018-2022. In this contribution, we will present the dataset and highlight potential applications for model development and improved mechanistic understanding of the SIF-GPP-NPQ interplay. Prospective applications include improved NPQ characterizations in models such as SCOPE (a radiative transfer and energy balance model) and ORCHIDEE (a terrestrial biosphere model capable of ingesting SIF).