Equatorial Asia Global - Land High Latitudes South America - Amazon

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	23.0
bcc-csm1-1	[-]	20.8		-2.22	4.24	0.983		0.755	0.646	0.937	0.746
BCC-CSM2-MR	[-]	30.2		7.16	8.63	0.00		0.210	0.474	1.00	0.539
CanESM2	[-]	23.6		0.644	4.72	0.983		0.929	0.585	0.937	0.759
CanESM5	[-]	21.0		-2.05	3.83	0.983		0.774	0.726	0.937	0.791
CESM1-BGC	[-]	20.1		-2.89	3.88	0.983		0.680	0.787	0.937	0.798
CESM2	[-]	23.2		0.239	3.45	0.983		0.974	0.673	0.937	0.814
GFDL-ESM2G	[-]	23.6		0.617	3.22	2.00		0.932	0.691	0.756	0.767
GFDL-ESM4	[-]	27.1		4.12	7.17	0.983		0.545	0.439	0.937	0.590
IPSL-CM5A-LR	[-]	31.6		8.62	8.76	0.983		0.0485	0.639	0.937	0.566
IPSL-CM6A-LR	[-]	21.6		-1.42	3.36	0.983		0.843	0.696	0.937	0.793
MeanCMIP5	[-]	25.4		2.32	3.07	3.05		0.744	0.827	0.498	0.724
MeanCMIP6	[-]	25.9		2.87	4.20	0.983		0.684	0.719	0.937	0.764
MIROC-ESM	[-]	22.7		-0.322	6.53	2.00		0.964	0.382	0.756	0.621
MIROC-ESM2L	[-]	22.0		-0.985	5.17	0.983		0.891	0.501	0.937	0.708
MPI-ESM-LR	[-]	33.8		10.8	13.1	0.983		0.00	0.431	0.937	0.450
MPI-ESM1.2-HR	[-]	35.6		12.6	14.1	0.983		0.00	0.486	0.937	0.477
NorESM1-ME	[-]	20.3		-2.75	3.66	2.00		0.696	0.722	0.756	0.724
NorESM2-LM	[-]	22.9		-0.110	2.55	0.983		0.988	0.758	0.937	0.860
UK-HadGEM2-ES	[-]	27.5		4.40	4.89	3.05		0.515	0.807	0.498	0.656
UKESM1-0-LL	[-]	36.1		13.1	14.2	0.983		0.00	0.636	0.937	0.552

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	26.7
bcc-csm1-1	[-]	25.8		-3.54	14.0	1.49		0.336	0.342	0.798	0.454
BCC-CSM2-MR	[-]	26.6		-2.91	14.2	1.50		0.301	0.360	0.778	0.450
CanESM2	[-]	33.8		4.89	18.0	1.15		0.161	0.195	0.842	0.348
CanESM5	[-]	31.5		2.98	14.6	1.36		0.301	0.309	0.805	0.431
CESM1-BGC	[-]	26.4		-2.44	12.0	1.33		0.367	0.419	0.811	0.504
CESM2	[-]	27.9		-1.54	12.7	1.15		0.337	0.395	0.841	0.492
GFDL-ESM2G	[-]	32.6		4.45	16.9	1.36		0.210	0.232	0.811	0.371
GFDL-ESM4	[-]	33.6		4.57	16.5	1.11		0.215	0.280	0.856	0.408
IPSL-CM5A-LR	[-]	35.9		4.64	16.5	1.53		0.240	0.249	0.801	0.385
IPSL-CM6A-LR	[-]	26.3		-1.79	14.1	1.54		0.327	0.335	0.783	0.445
MeanCMIP5	[-]	30.0		0.686	13.2	1.51		0.288	0.391	0.778	0.462
MeanCMIP6	[-]	29.4		0.283	12.5	1.22		0.307	0.418	0.825	0.492
MIROC-ESM	[-]	29.9		3.26	19.1	1.36		0.196	0.206	0.795	0.351
MIROC-ESM2L	[-]	25.2		-3.67	13.7	1.44		0.355	0.376	0.792	0.475
MPI-ESM-LR	[-]	29.0		0.481	15.5	1.18		0.260	0.280	0.833	0.413
MPI-ESM1.2-HR	[-]	28.4		-2.90	14.3	1.25		0.278	0.356	0.837	0.457
NorESM1-ME	[-]	25.3		-3.03	13.1	1.19		0.382	0.404	0.830	0.505
NorESM2-LM	[-]	26.9		-2.19	13.6	1.21		0.355	0.355	0.826	0.473
UK-HadGEM2-ES	[-]	28.6		-0.912	15.0	1.42		0.229	0.318	0.796	0.415
UKESM1-0-LL	[-]	36.9		7.64	17.2	1.32		0.209	0.246	0.817	0.380

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	21.7
bcc-csm1-1	[-]	20.7		-3.61	13.6	1.21		0.364	0.442	0.869	0.529
BCC-CSM2-MR	[-]	24.8		-0.407	13.7	0.904		0.330	0.393	0.889	0.501
CanESM2	[-]	30.9		7.70	18.2	0.904		0.174	0.190	0.878	0.358
CanESM5	[-]	27.9		2.82	12.4	1.17		0.376	0.342	0.842	0.476
CESM1-BGC	[-]	24.9		0.236	10.3	1.05		0.455	0.519	0.841	0.583
CESM2	[-]	22.6		-2.50	11.6	0.904		0.405	0.477	0.871	0.558
GFDL-ESM2G	[-]	29.8		4.51	16.7	1.02		0.229	0.266	0.859	0.405
GFDL-ESM4	[-]	26.3		3.93	16.5	1.09		0.197	0.323	0.857	0.425
IPSL-CM5A-LR	[-]	29.1		5.39	17.1	1.43		0.257	0.211	0.825	0.376
IPSL-CM6A-LR	[-]	22.7		-1.84	13.2	1.36		0.388	0.385	0.828	0.496
MeanCMIP5	[-]	26.7		2.85	12.3	1.02		0.289	0.461	0.866	0.519
MeanCMIP6	[-]	24.7		0.594	11.9	0.942		0.331	0.458	0.864	0.528
MIROC-ESM	[-]	26.3		7.26	22.7	1.17		0.143	0.161	0.829	0.324
MIROC-ESM2L	[-]	21.4		-1.52	13.1	0.980		0.382	0.395	0.875	0.512
MPI-ESM-LR	[-]	26.1		2.58	14.7	0.942		0.278	0.318	0.860	0.443
MPI-ESM1.2-HR	[-]	22.7		-3.14	12.7	0.980		0.371	0.429	0.875	0.526
NorESM1-ME	[-]	24.0		-0.248	11.5	0.942		0.459	0.477	0.860	0.568
NorESM2-LM	[-]	21.1		-2.92	11.8	0.942		0.401	0.437	0.867	0.535
UK-HadGEM2-ES	[-]	25.3		2.83	14.7	0.978		0.284	0.310	0.862	0.442
UKESM1-0-LL	[-]	30.6		8.11	15.7	0.980		0.192	0.223	0.868	0.377

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	22.6
bcc-csm1-1	[-]	32.5		9.90	11.2	0.508		0.0498	0.608	0.966	0.558
BCC-CSM2-MR	[-]	28.9		6.30	8.50	1.02		0.350	0.652	0.933	0.647
CanESM2	[-]	32.2		9.61	10.8	1.02		0.0778	0.520	0.933	0.513
CanESM5	[-]	30.6		7.99	9.94	0.508		0.152	0.612	0.966	0.586
CESM1-BGC	[-]	20.4		-2.18	6.24	0.508		0.591	0.566	0.966	0.672
CESM2	[-]	23.8		1.22	5.83	0.00		0.531	0.663	1.00	0.714
GFDL-ESM2G	[-]	36.4		13.8	15.4	1.02		0.0372	0.529	0.933	0.507
GFDL-ESM4	[-]	36.0		13.4	16.8	0.508		0.00	0.324	0.966	0.403
IPSL-CM5A-LR	[-]	31.7		9.09	10.8	1.02		0.323	0.672	0.933	0.650
IPSL-CM6A-LR	[-]	26.3		3.64	6.11	1.02		0.590	0.669	0.933	0.715
MeanCMIP5	[-]	29.8		7.13	8.31	0.508		0.254	0.700	0.966	0.655
MeanCMIP6	[-]	27.9		5.29	7.27	0.508		0.416	0.692	0.966	0.692
MIROC-ESM	[-]	26.7		4.08	6.21	1.53		0.550	0.527	0.839	0.611
MIROC-ESM2L	[-]	19.7		-2.96	4.12	0.508		0.674	0.704	0.966	0.762
MPI-ESM-LR	[-]	40.1		17.5	19.3	0.508		0.00	0.440	0.966	0.462
MPI-ESM1.2-HR	[-]	21.4		-1.22	9.22	1.02		0.130	0.663	0.933	0.597
NorESM1-ME	[-]	19.8		-2.76	4.69	1.52		0.695	0.630	0.841	0.699
NorESM2-LM	[-]	25.8		3.24	5.30	0.00		0.643	0.680	1.00	0.751
UK-HadGEM2-ES	[-]	26.8		4.12	8.15	0.00		0.330	0.664	1.00	0.664
UKESM1-0-LL	[-]	36.0		13.4	15.0	1.02		0.200	0.583	0.933	0.575

Equatorial Africa Equatorial Asia Global - Land High Latitudes South America - Amazon 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

  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: SW_OUT