Cross-calibrated AVHRR and MODIS long-term contiguous reflectance parameters (LCREF), 1982-2021

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, 1982-2021) and MODerate-resolution Imaging Spectroradiometer (MODIS, 2000-2021). Importantly, we fully 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 1982-2021 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 all vegetation types, ensuring a greater capacity of LCSIF for representing terrestrial photosynthesis. Globally, LCSIF shows an accelerating upward trend since 1982, with an average rate of 0.0025 mW m-2 nm-1 sr-1 decades-1 during 1982-2000 and 0.0048 mW m-2 nm-1 sr-1 decades-1 during 2001-2021. Previous greening hotspots of India and China since 2000 are also identified as hotspots for enhanced photosynthesis. Our LCSIF data provide opportunities to better understand the long-term dynamics of ecosystem photosynthesis and their underlying driving processes. This repository contains the calibrated reflectance parameters (red and near-infrared channels) used to generate the LCSIF dataset, available in netCDF format. The dataset is available at a bi-monthly resolution with a spatial resolution of 0.05 degrees. Due to the differences in spatial coverages between the MODIS and AVHRR products, we recommend the users apply a common spatial mask on the datasets to ensure consistent spatial coverage when doing a temporal analysis. Users are advised to refer to our paper (under review) to understand the features and limitations of our dataset before usage. Please reach out to jf3423@columbia.edu if you have questions about the dataset. The LCSIF dataset for the AVHRR period (1982-2000) is available at doi:10.5281/zenodo.7916851. The LCSIF dataset for the MODIS period (1982-2000) is available at doi:10.5281/zenodo.7916879. While we do not directly provide common red and near-infrared based vegetation indicies (e.g. NDVI, kNDVI, NIRv etc.), users can readily compute them from the reflectance parameters to suit their needs. This work was funded by the Land Ecosystem Models based On New Theory, obseRvations, and ExperimEnts (LEMONTREE) project (Grant No. UREAD 1005109-LEMONTREE), the European Research Council grant USMILE, and National Science Foundation Science and Technology Center LEAP, Learning the Earth with Artificial intelligence and Physics. The code used to generate and evaluate the LCSIF data is available at on GitHub