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\begin{document}

\title{Solar-induced fluorescence products show variable skill in constraining
global patterns in biospheric CO2 fluxes}



\author[1]{Mingyang Zhang}%
\author[2]{Joe Berry}%
\author[3]{Yoichi Paolo Shiga}%
\author[4]{Russell Doughty}%
\author[5]{Nima Madani}%
\author[6]{Xing Li}%
\author[7]{Jingfeng Xiao}%
\author[8]{Jiaming Wen}%
\author[8]{Ying Sun}%
\author[1]{Ruixue Lei}%
\author[1]{Scot Miller}%
\affil[1]{Johns Hopkins University}%
\affil[2]{Carnegie Institution for Science}%
\affil[3]{Independent Researcher}%
\affil[4]{California Institute of Technology}%
\affil[5]{Jet Propulsion Laboratory}%
\affil[6]{Seoul National University}%
\affil[7]{University of New Hampshire}%
\affil[8]{Cornell University}%


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  \date{June 11, 2024}


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\begin{abstract}
Solar-induced fluorescence (SIF) shows enormous promise as a proxy for
photosynthesis and as a tool for modeling variability in gross primary
productivity (GPP) and net biosphere exchange (NBE). In this study, we
explore the skill of SIF and other vegetation indicators in predicting
variability in global atmospheric CO2 observations, and thus global
variability in NBE. We do so using a four-year record of global CO2
observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite
and using a geostatistical inverse model. We find that existing SIF
products closely correlate with space-time variability in atmospheric
CO2 observations in the extra-tropics but show weaker explanatory power
across the tropics. In the extra-tropics, all SIF products exhibit
greater skill in explaining variability in atmospheric CO2 observations
compared to an ensemble of process-based CO2 flux models and other
vegetation indicators. Furthermore, we find that using SIF as a
predictor variable in the geosatistical inverse model shifts the
seasonal cycle of estimated NBE and yields an earlier end to the growing
season relative to other vegetation indicators. In tropical biomes, by
contrast, the seasonal cycles of SIF products and estimated NBE are out
of phase, and existing respiration and biomass burning estimates do not
reconcile this discrepancy. Overall, our results highlight several
advantages and challenges of using SIF products to help predict global
variability in GPP and NBE.%
\end{abstract}%



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