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)
History:
2020-08-25: downloaded source from ftp://ftp.bgc-jena.mpg.de/pub/outgoing/FluxCom/CarbonFluxes_v1_2017/RS+METEO/CRUNCEPv6/raw/monthly/
2020-08-25: converted to netCDF, additionally we apply a mask where |var|<1e-15 for all time.
References:
Jung, M., M. Reichstein, C.R. Schwalm, C. Huntingford, S. Sitch, A. Ahlstrom, A. Arneth, G. Camps-Valls, P. Ciais, P. Friedlingstein, F. Gans, K. Ichii, A.K. Jain, E. Kato, D. Papale, B. Poulter, B. Raduly, C. Rodenbeck, G. Tramontana, N. Viovy, Y.P. Wang, U. Weber, S. Zaehle and N. Zeng (2017), Compensatory water effects link yearly global land CO2 sink changes to temperature, Nature, 541, 516-520, doi:10.1038/nature20780
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