Observed and modelled GPP at 61 eddy covariance sites (2007-2018)

In the frame of the ECOPROPHET project, data was collected from in situ observations, remote-sensing sources and models for 61 sites. The objective of this project was to improve our understanding of ecosystem productivity and the role of vegetation phenology as a key determinant of ecosystem carbon, water and energy balances. More info and publications can be found at http://ecoprophet.meteo.be<br> This dataset contains timeseries of observed GPP, modelled GPP (using 15 models), along with key hydrometeorological variables (shortwave radiation, air temperature, vapor pressure deficit and soil moisture).<br> The timeseries are at daily resolution, covering the period 2007-2018 (depending on the data availability per site).<br> The dataset is partly extracted from: FLUXNET2015 dataset (Pastorello et al., 2020) and the ICOS ’2018 drought initiative’ dataset (Drought 2018 Team<br> and ICOS Ecosystem Thematic Centre, 2019). Original dataset available at https://fluxnet.org/ and https://www.icos-cp.eu/data-products/ YVR0-4898 ERA5 product (Hersbach et al., 2020); Original dataset available at https://cds.climate.copernicus.eu/ MODIS: Original dataset available at https://modis.gsfc.nasa.gov/data/ SPOT Vegetation/PROBA V: Original dataset available at https://land.copernicus.eu/global/ Downscaled GOME2 SIF product by Duveiller et al. (2020). Original dataset available at https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1 FluxCom product ensemble (Jung et al., 2020). Original dataset available at http://fluxcom.org/ <strong>File descriptions</strong>:<br> README.pdf : description<br> EcopropheciesMeta.txt : metadata<br> EcopropheciesDataset.txt : data More details and analysis of the data can be found in:<br> De Pue, J., Wieneke, Bastos, A., S., Barrios, J.M., Liu, L., Ciais, P., Arboleda, A., Hamdi, R., Maleki, M., Maignan, F., Gellens-Meulenberghs, F., Janssens, I., and Balzarolo, M., Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers 2023, Agricultural and Forest Meteorology (submitted)