FLUXCOM (RS+METEO) Global Land Carbon Fluxes using CRUNCEP climate data
Version:
1
Institutions:
Department Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Germany
Source:
Data generated by Artificial Neural Networks and forced with CRUNCEPv6 meteorological data and MODIS (RS+METEO)
ftp://ftp.bgc-jena.mpg.de/pub/outgoing/FluxCom/CarbonFluxes_v1_2017/RS+METEO/CRUNCEPv6/raw/monthly/
ftp://ftp.bgc-jena.mpg.de/pub/outgoing/FluxCom/EnergyFluxes/RS_METEO/member/CRUNCEP_v8/monthly/
2024-01-19: converted to netCDF, additionally we apply a mask where |var|<1e-15 for all time.
References:
Jung, M., S. Koirala, U. Weber, K. Ichii, F. Gans, Gustau-Camps-Valls, D. Papale, C. Schwalm, G. Tramontana, and M. Reichstein (2019), The FLUXCOM ensemble of global land-atmosphere energy fluxes, Scientific Data, 74, doi:10.1038/s41597-019-0076-8
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