ABoVE domain Globe

	Download Data	Period Mean (original grids) [g m-2 d-1]		Bias [g m-2 d-1]	RMSE [g m-2 d-1]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	1.98
ACCESS-ESM1-5	[-]	1.71		-0.270	1.50	0.0646		0.722	0.562	0.999	0.711
BCC-CSM2-MR	[-]	1.79		-0.188	1.51	0.254		0.721	0.547	0.975	0.697
CanESM2	[-]	1.09		-0.943	1.94	0.409		0.578	0.491	0.970
CanESM5	[-]	1.81		-0.172	1.49	0.517		0.730	0.544	0.969
CESM2	[-]	2.27		0.292	1.91	0.381		0.713	0.506	0.967	0.673
CNRM-ESM2-1	[-]	1.56		-0.421	1.54	0.0635		0.692	0.561	0.993
EnsembleCMIP5	[-]	2.03		0.0510	1.50	0.00		0.751	0.568	1.00
EnsembleCMIP6	[-]	1.92		-0.0533	1.34	0.00		0.748	0.590	1.00
GFDL-ESM2M	[-]	2.04		-0.0173	3.05	0.203		0.655	0.307	0.994	0.566
GFDL_ESM4	[-]	1.88		-0.0932	1.75	0.127		0.687	0.511	0.997
GISS-E2-1-G	[-]	1.01		-0.970	1.80	0.0646		0.609	0.503	0.999	0.653
IPSL-CM5A-LR	[-]	3.19		1.22	2.73	0.339		0.665	0.377	0.968
IPSL-CM6A-LR	[-]	1.37		-0.612	1.83	0.00		0.637	0.513	1.00
MIROC-ES2L	[-]	3.34		1.36	2.90	1.20		0.575	0.347	0.918	0.547
MPI-ESM-LR	[-]	2.69		0.788	2.11	0.00		0.661	0.468	1.00	0.649
MPI-ESM1-2-LR	[-]	2.95		0.968	2.25	0.00		0.693	0.415	1.00	0.631
NorESM1-M	[-]	1.17		-0.762	1.88	1.02		0.644	0.483	0.921	0.633
NorESM2-LM	[-]	2.16		0.187	1.88	0.758		0.705	0.504	0.946	0.665
UKESM1-0-LL	[-]	1.94		-0.0347	1.64	0.00		0.717	0.532	1.00

	Download Data	Period Mean (original grids) [g m-2 d-1]		Bias [g m-2 d-1]	RMSE [g m-2 d-1]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	3.34
ACCESS-ESM1-5	[-]	2.56		-0.790	2.62	1.11		0.574	0.459	0.867	0.590
BCC-CSM2-MR	[-]	2.61		-0.716	2.64	1.19		0.587	0.430	0.880	0.582
CanESM2	[-]	2.26		-1.37	2.92	1.56		0.547	0.442	0.749
CanESM5	[-]	3.31		-0.0209	2.73	1.24		0.624	0.434	0.850
CESM2	[-]	2.49		-0.834	2.82	1.09		0.537	0.448	0.880	0.578
CNRM-ESM2-1	[-]	2.59		-0.750	2.55	1.16		0.589	0.441	0.849
EnsembleCMIP5	[-]	2.94		-0.590	2.43	0.905		0.606	0.483	0.842
EnsembleCMIP6	[-]	2.73		-0.607	2.23	0.882		0.622	0.507	0.895
GFDL-ESM2M	[-]	2.72		-0.993	3.50	0.962		0.543	0.346	0.849	0.521
GFDL_ESM4	[-]	2.02		-1.32	2.83	1.27		0.506	0.431	0.814
GISS-E2-1-G	[-]	3.04		-0.300	2.46	0.889		0.633	0.470	0.873	0.611
IPSL-CM5A-LR	[-]	3.85		0.535	3.32	1.04		0.599	0.380	0.832
IPSL-CM6A-LR	[-]	2.41		-0.955	2.80	1.13		0.542	0.445	0.867
MIROC-ES2L	[-]	2.91		-0.421	2.88	1.64		0.559	0.440	0.807	0.561
MPI-ESM-LR	[-]	3.96		0.292	3.00	0.690		0.617	0.430	0.903	0.595
MPI-ESM1-2-LR	[-]	3.27		-0.0434	3.01	0.942		0.602	0.408	0.889	0.576
NorESM1-M	[-]	2.68		-0.811	2.70	0.984		0.588	0.452	0.849	0.585
NorESM2-LM	[-]	2.50		-0.837	2.75	1.19		0.540	0.456	0.867	0.580
UKESM1-0-LL	[-]	2.57		-0.757	2.77	1.15		0.554	0.429	0.878

ABoVE domain Globe

	Download Data	Precipitation|GPCPv2.3 Hellinger Distance [1]	SurfaceDownwardSWRadiation|CERESed4.1 Hellinger Distance [1]	SurfaceAirTemperature|CRU4.02 Hellinger Distance [1]		Precipitation|GPCPv2.3 Score [1]	SurfaceDownwardSWRadiation|CERESed4.1 Score [1]	SurfaceAirTemperature|CRU4.02 Score [1]	Overall Score [1]
ACCESS-ESM1-5	[-]	1.00	0.896	0.744		0.433	0.841	0.642	0.639
BCC-CSM2-MR	[-]	0.763	1.00			0.730	0.965		0.847
CanESM2	[-]	0.739	1.00			0.663	0.607
CanESM5	[-]	1.00				0.450
CESM2	[-]		0.823	0.927			0.454	0.573	0.514
CNRM-ESM2-1	[-]
EnsembleCMIP5	[-]	0.706				0.956
EnsembleCMIP6	[-]	0.705	0.652			0.817	0.769
GFDL-ESM2M	[-]								0.00
GFDL_ESM4	[-]	1.00				0.662
GISS-E2-1-G	[-]								0.00
IPSL-CM5A-LR	[-]	1.00	1.00			0.582	0.238
IPSL-CM6A-LR	[-]	1.00				0.843
MIROC-ES2L	[-]	0.927	1.00	1.00		0.604	0.566	0.659	0.610
MPI-ESM-LR	[-]								0.00
MPI-ESM1-2-LR	[-]	0.896	0.781	0.781		0.568	0.695	0.841	0.702
NorESM1-M	[-]	0.781	0.781	0.781		0.548	0.662	0.689	0.633
NorESM2-LM	[-]	0.669	0.855	0.803		0.707	0.977	0.694	0.793
UKESM1-0-LL	[-]

	Download Data	Precipitation|GPCPv2.3 Hellinger Distance [1]	SurfaceDownwardSWRadiation|CERESed4.1 Hellinger Distance [1]	SurfaceAirTemperature|CRU4.02 Hellinger Distance [1]		Precipitation|GPCPv2.3 Score [1]	SurfaceDownwardSWRadiation|CERESed4.1 Score [1]	SurfaceAirTemperature|CRU4.02 Score [1]	Overall Score [1]
ACCESS-ESM1-5	[-]	0.764	0.785	0.792		0.707	0.655	0.597	0.653
BCC-CSM2-MR	[-]	0.761	0.780			0.733	0.626		0.680
CanESM2	[-]	0.734	0.772	0.762		0.692	0.578	0.646
CanESM5	[-]	0.713	0.766			0.681	0.576
CESM2	[-]		0.800	0.756			0.615	0.592	0.604
CNRM-ESM2-1	[-]	0.762				0.634
EnsembleCMIP5	[-]	0.696	0.772			0.811	0.732
EnsembleCMIP6	[-]	0.746	0.734	0.731		0.788	0.603	0.773
GFDL-ESM2M	[-]								0.00
GFDL_ESM4	[-]	0.721	0.806			0.636	0.636
GISS-E2-1-G	[-]								0.00
IPSL-CM5A-LR	[-]	0.701	0.761	0.732		0.614	0.600	0.638
IPSL-CM6A-LR	[-]	0.741	0.784			0.623	0.598
MIROC-ES2L	[-]	0.750	0.846	0.728		0.677	0.581	0.737	0.665
MPI-ESM-LR	[-]								0.00
MPI-ESM1-2-LR	[-]	0.767	0.741	0.722		0.749	0.711	0.635	0.698
NorESM1-M	[-]	0.729	0.784	0.735		0.629	0.630	0.566	0.608
NorESM2-LM	[-]	0.710	0.760	0.782		0.718	0.640	0.663	0.674
UKESM1-0-LL	[-]	0.729				0.746

ABoVE domain Globe Temporally integrated period mean Temporally integrated period mean bias Temporally integrated period mean bias score Temporally integrated period mean max month Temporally integrated mean phase shift Temporally integrated mean phase shift score Temporally integrated period mean rmse Temporally integrated period mean rmse score Spatially integrated regional mean cycle Spatially integrated regional mean detrended cycle Spatially integrated regional mean Relationship with Precipitation Relationship with func_Precipitation Relationship with SurfaceDownwardSWRadiation Relationship with func_SurfaceDownwardSWRadiation Relationship with SurfaceAirTemperature Relationship with func_SurfaceAirTemperature

  Title:

FluxNet Tower eddy covariance measurements (Tier 1)

  Version:

2015

  Institutions:

FluxNet, AmeriFlux, AfriFlux, AsiaFlux, ChinaFlux, Fluxnet-Canada, KoFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, GreenGrass, OzFlux-TERN, LBA, NECC, ICOS, TCOS-Siberia, and USCCC

  References:

Reichstein, M., D. Papale, R. Valentini, M. Aubinet, C. Bernhofer, A. Knohl, T. Laurila, A. Lindroth, E. Moors, K. Pilegaard, and G. Seufert (2007), Determinants of terrestrialecosystem carbon balance inferred from European eddy covarianceflux sites, Geophys. Res. Lett., 34, L01402, doi:10.1029/2006GL027880

Lasslop, G., M. Reichstein, D. Papale, A.D. Richardson, A. Arneth, A. Barr, P. Stoy, and G. Wohlfahrt (2010), Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation, Global Change Biology, 16, 187-208, doi:10.1111/j.1365-2486.2009.02041.x

Knauer, J., S. Zaehle, B.E. Medlyn, M. Reichstein, C.A. Williams, M. Migliavacca, M.G. De Kauwe, C. Werner, C. Keitel, P. Kolari, J.-M. Limousin, and M.-L. Linderson (2018), Towards physiologically meaningful water use efficiency estimates from eddy covariance data, Global Change Biology, 24(2), 694-710, doi:10.1111/gcb.13893

  Comment:

Fluxnet variable(s) used: GPP_DT_VUT_REF