Machine learning and FLUXNET based Carbon and Water Fluxes (MF-CW) product
A 0.5-degree gross primary production (GPP), evapotranspiration (ET), and water use efficiency (WUE) product for the globe (1982-2016)
FLUXNET eddy covariance (EC) sites offer temporally continuous carbon and water flux data for a large number of sites encompassing a wide range of ecosystems and climate types across the globe. However, the EC measurements only represent the status of carbon and water fluxes around the tower footprint; they need to be upscaled to regional or global scales so that we can explore the dynamics of carbon and water fluxes over broad regions. The datasets of Machine learning and FLUXNET based Carbon and Water Fluxes (MF-CW), including monthly GPP and ET, and yearly WUEeco at 0.5-degree resolution over the global vegetated lands, were generated using 24 machine learning algorithms, FLUXNET in-situ observations of CO2 and water vapor fluxes, satellite-derived observations and climate reanalysis data. The methodology, validation, and spatial and temporal patterns of these datasets are detailed in the paper.
Li, F., Xiao, J., Chen, J., Ballantyne, A., Jin, K., Li, B., Abraha, M., John, R. (2023) Global water use efficiency saturation due to increased vapor pressure deficit. Science, 381, 672-677. DOI: 10.1126/science.adf5041. [PDF] (Highlighted by Science on the very top of its homepage)
Spatial resolution: 0.5 degree
Spatial extent: Globe
Temporal resolution: monthly and annual
Temporal extent: 1982 -2016
Fair Data Use Policy:
We make the datasets available to the research community as we believe that the dissemination of the datasets can be helpful to advancement in science. If you plan to use our datasets in a manuscript or project, we request that you inform us early in your work. If our datasets are essential to your results or findings, co-authorship will be appropriate.
Download MF-CW data:
Please read the fair data use policy above before you download the data. This data set is available at the Global Ecology Data Repository (Download MF-CW data).