  Satellite-observed solar-induced chlorophyll fluorescence (SIF) is a powerful
proxy for diagnosing the photosynthetic characteristics of terrestrial
ecosystems. Despite the increasing spatial and temporal resolutions of these
satellite retrievals, records of SIF are primarily limited to the recent
decade, impeding their application in detecting long-term dynamics of ecosystem
function and structure. In this study, we leverage the two surface reflectance
bands (red and near-infrared) available both from Advanced Very High-Resolution
Radiometer (AVHRR, 1982-2022) and MODerate-resolution Imaging Spectroradiometer
(MODIS, 2001-2022). Importantly, we calibrate and orbit-correct the AVHRR bands
against their MODIS counterparts during their overlapping period. Using the
long-term bias-corrected reflectance data, a neural network is then built to
reproduce the Orbiting Carbon Observatory-2 SIF using AVHRR and MODIS, and used
to map SIF globally over the entire 1982-2022 period. Compared with the
previous MODIS-based CSIF product relying on four reflectance bands, our
two-band-based product has similar skill but can be advantageously extended to
the bias-corrected AVHRR period. Further comparison with three widely used
vegetation indices (NDVI, kNDVI, NIRv; all based empirically on red and
near-infrared bands) shows a higher or comparable correlation of LCSIF with
satellite SIF and site-level GPP estimates across vegetation types, ensuring a
greater capacity of LCSIF for representing terrestrial photosynthesis.
Globally, LCSIF-AVHRR shows an accelerating upward trend since 1982, with an
average rate of 0.0025 mW m-2 nm-1 sr-1 per decade during 1982-2000 and 0.0038
mW m-2 nm-1 sr-1 per decade during 2001-2022. Our LCSIF data provide
opportunities to better understand the long-term dynamics of ecosystem
photosynthesis and their underlying driving processes.
