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Correction to: Scientific Data https://doi.org/10.1038/s41597-020-0534-3, published online 09 July 2020

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such asmore » gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.« less

Aerodynamic canopy height (h_a) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate h_a from data are limited. This synthesis evaluates the applicability and robustness of the calculation of h_a from eddy covariance momentum-flux data. At 69 forest sites, annual h_a robustly predicted site-to-site and year-to-year differences in canopy heights (R² = 0.88, 111 site-years). At 23 cropland/grassland sites, weekly h_a successfully captured the dynamics of vegetation canopies over growing seasons (R² > 0.70 in 74 site-years). Our results demonstrate the potential of flux-derived h_a determination for tracking the seasonal,more » interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying h_a derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure.« less