Data Information

Title:: FLUXCOM (RS+METEO) Global Land Energy Fluxes using GSWP3 climate data

Institutions:: Department Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Germany

Source:: Data generated by machine learning to merge energy flux measurements from FLUXNET eddy covariance towers with MODIS remote sensing and GSWP3v1 meteorological data (RS+METEO)

History:: 2019-05-07: downloaded source from doi:10.17871/FLUXCOM_EnergyFluxes_v1; 2019-06-28: converted to netCDF with https://github.com/mmu2019/Datasets/blob/master/read-sh-fluxcom.py

References:: Jung, M., S. Koirala, U. Weber, K. Ichii, F. Gans, G. Camps-Valls, D. Papale, C. Schwalm, G. Tramontana, M. Reichstein (2019), The FLUXCOM ensemble of global land-atmosphere energy fluxes, Scientific Data, submitted, 1-12, https://arxiv.org/abs/1812.04951; Tramontana, G., M. Jung, C.R. Schwalm, K. Ichii, G. Camps-Valls, B. Raduly, M. Reichstein, M.A. Arain, A. Cescatti, G. Kiely, L. Merbold, P. Serrano-Ortiz, S. Sickert, S. Wolf, and D. Papale (2016), Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms, Biogeosciences, 13, 4291-4313, doi:10.5194/bg-13-4291-2016

Comments:: time_period: 1980-01 through 2014-12; original_temporal_resolution: monthly; original_spatial_resolution: 0.5 degree; original_units: MJ/m2/day; final_temporal_resolution: monthly; final_spatial_resolution: 0.5 degree; final_units: watt/m2

Mean State