Terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Mapping in-situ eddy covariance measurements of terrestrial carbon and water fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented up-scaling framework, FLUXCOM-X. The X-BASE products comprise of estimates of CO₂ net ecosystem exchange (NEE), gross primary productivity (GPP) as well as evapotranspiration (ET) and, for the first time, a novel fully data-driven global transpiration product (ET_T), at high spatial (0.05°) and temporal (hourly) resolution for the period 2001-2020.

One key improvement of the new products is the much more realistic estimates of global carbon uptake (NEE) at  -5.75 PgC yr^-1, which is a marked improvement compared to previous FLUXCOM versions as well as reconciles the bottom-up global eddy-covariance-based NEE and estimates from top-down atmospheric inversions. The improvement of global NEE was likely only possible thanks to the international effort to improve the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site-years resulting in a wider coverage of bio-climatic conditions. However, X-BASE global net ecosystem exchange shows a very low inter-annual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge.

With 125 PgC yr^-1, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas and shows a good agreement with TROPOMI based SIF. X-BASE evapotranspiration amounts to 74.7x10³ km³ yr^-1 globally, but exceeds precipitation in many dry areas likely indicating overestimation in these regions. On average 57% of evapotranspiration are estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models.

Despite considerable improvements to the previous up-scaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy-covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. Here we will outline how the new FLUXCOM-X framework provides the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.