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	[-]	178.
bcc-csm1-1	[-]	181.		2.74	30.0	0.983		0.870	0.00	0.937	0.452
BCC-CSM2-MR	[-]	192.		14.1	21.0	0.983		0.329	0.376	0.937	0.504
CanESM2	[-]	151.		-26.5	25.7	0.983		0.00	0.116	0.937	0.292
CanESM5	[-]	174.		-4.01	18.0	0.983		0.809	0.427	0.937	0.650
CESM1-BGC	[-]	157.		-20.7	27.7	0.983		0.0159	0.480	0.937	0.478
CESM2	[-]	167.		-10.7	25.4	0.983		0.494	0.184	0.937	0.450
GFDL-ESM2G	[-]	179.		1.28	22.4	2.00		0.939	0.221	0.756	0.534
GFDL-ESM4	[-]	175.		-2.97	23.7	0.983		0.859	0.193	0.937	0.545
IPSL-CM5A-LR	[-]	174.		-3.88	19.8	0.983		0.816	0.347	0.937	0.612
IPSL-CM6A-LR	[-]	167.		-10.5	25.0	0.983		0.499	0.186	0.937	0.452
MeanCMIP5	[-]	170.		-8.63	14.2	1.02		0.590	0.587	0.933	0.674
MeanCMIP6	[-]	180.		1.92	15.3	0.983		0.909	0.476	0.937	0.700
MIROC-ESM	[-]	167.		-10.9	50.3	2.00		0.484	0.00	0.756	0.310
MIROC-ESM2L	[-]	180.		2.16	36.3	0.983		0.898	0.00	0.937	0.459
MPI-ESM-LR	[-]	182.		4.32	25.8	0.983		0.795	0.139	0.937	0.502
MPI-ESM1.2-HR	[-]	202.		24.0	37.3	0.983		0.00	0.0296	0.937	0.249
NorESM1-ME	[-]	154.		-24.2	28.1	2.00		0.00	0.380	0.756	0.379
NorESM2-LM	[-]	186.		7.91	22.7	0.983		0.624	0.235	0.937	0.508
UK-HadGEM2-ES	[-]	190.		11.1	16.9	1.02		0.472	0.545	0.933	0.624
UKESM1-0-LL	[-]	169.		-8.98	21.1	0.983		0.574	0.302	0.937	0.529

	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	[-]	131.
bcc-csm1-1	[-]	132.		-10.2	30.8	0.794		0.258	0.0359	0.928	0.314
BCC-CSM2-MR	[-]	138.		-4.02	31.2	0.766		0.375	0.0452	0.928	0.348
CanESM2	[-]	147.		7.54	34.7	0.626		0.327	0.0316	0.939	0.332
CanESM5	[-]	145.		4.16	29.2	0.571		0.400	0.0726	0.952	0.374
CESM1-BGC	[-]	150.		12.9	34.7	0.487		0.170	0.0459	0.953	0.304
CESM2	[-]	145.		4.27	28.7	0.530		0.354	0.0840	0.944	0.366
GFDL-ESM2G	[-]	135.		-6.95	27.3	0.460		0.390	0.0955	0.953	0.384
GFDL-ESM4	[-]	131.		-11.6	28.2	0.571		0.290	0.0825	0.949	0.351
IPSL-CM5A-LR	[-]	146.		4.81	37.5	0.836		0.201	0.0352	0.932	0.301
IPSL-CM6A-LR	[-]	143.		3.87	34.5	0.669		0.342	0.0268	0.945	0.335
MeanCMIP5	[-]	143.		0.873	25.6	0.648		0.394	0.145	0.943	0.407
MeanCMIP6	[-]	141.		0.476	23.4	0.543		0.470	0.173	0.953	0.442
MIROC-ESM	[-]	147.		6.97	36.6	0.543		0.330	0.0285	0.943	0.333
MIROC-ESM2L	[-]	144.		3.05	27.8	0.543		0.392	0.0935	0.953	0.383
MPI-ESM-LR	[-]	136.		-5.98	28.3	0.571		0.308	0.0557	0.943	0.340
MPI-ESM1.2-HR	[-]	143.		2.67	27.3	0.641		0.378	0.0853	0.931	0.370
NorESM1-ME	[-]	141.		1.74	29.0	0.627		0.294	0.0622	0.947	0.341
NorESM2-LM	[-]	144.		3.37	29.3	0.683		0.348	0.0705	0.937	0.356
UK-HadGEM2-ES	[-]	154.		11.6	35.5	0.684		0.236	0.0350	0.938	0.311
UKESM1-0-LL	[-]	140.		-1.61	27.0	0.613		0.441	0.0802	0.946	0.387

	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	[-]	100.
bcc-csm1-1	[-]	81.4		-13.4	29.0	0.980		0.246	0.0173	0.902	0.296
BCC-CSM2-MR	[-]	87.1		-5.56	27.9	0.904		0.493	0.0195	0.907	0.360
CanESM2	[-]	98.0		5.76	30.7	0.791		0.437	0.0128	0.908	0.343
CanESM5	[-]	95.2		2.41	25.0	0.528		0.519	0.0671	0.947	0.400
CESM1-BGC	[-]	108.		17.4	35.4	0.490		0.0736	0.0230	0.937	0.264
CESM2	[-]	95.2		2.08	25.3	0.377		0.493	0.0792	0.953	0.401
GFDL-ESM2G	[-]	91.4		-1.61	22.3	0.528		0.605	0.115	0.934	0.442
GFDL-ESM4	[-]	87.7		-7.86	25.9	0.490		0.346	0.0597	0.950	0.354
IPSL-CM5A-LR	[-]	103.		11.1	34.4	0.754		0.267	0.00779	0.939	0.305
IPSL-CM6A-LR	[-]	100.		7.66	32.6	0.716		0.433	0.00851	0.941	0.348
MeanCMIP5	[-]	98.1		4.67	22.6	0.352		0.508	0.113	0.977	0.428
MeanCMIP6	[-]	94.1		0.763	20.0	0.490		0.583	0.172	0.950	0.469
MIROC-ESM	[-]	98.7		4.78	34.4	0.490		0.450	0.00439	0.950	0.352
MIROC-ESM2L	[-]	97.9		2.66	21.4	0.490		0.537	0.147	0.950	0.445
MPI-ESM-LR	[-]	86.2		-8.96	25.2	0.603		0.379	0.0535	0.929	0.354
MPI-ESM1.2-HR	[-]	92.8		0.943	23.5	0.490		0.512	0.0581	0.950	0.394
NorESM1-ME	[-]	96.8		6.18	26.2	0.528		0.312	0.0616	0.947	0.346
NorESM2-LM	[-]	91.6		-1.90	25.8	0.641		0.460	0.0557	0.927	0.375
UK-HadGEM2-ES	[-]	109.		14.2	33.7	0.430		0.191	0.0166	0.972	0.299
UKESM1-0-LL	[-]	94.1		-0.836	22.5	0.415		0.568	0.0854	0.955	0.423

	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	[-]	178.
bcc-csm1-1	[-]	199.		21.6	35.5	0.00		0.0828	0.130	1.00	0.336
BCC-CSM2-MR	[-]	222.		44.2	57.5	0.508		0.00	0.147	0.966	0.315
CanESM2	[-]	222.		43.8	59.4	0.508		0.0812	0.00	0.966	0.262
CanESM5	[-]	218.		40.5	55.5	1.02		0.00	0.0911	0.933	0.279
CESM1-BGC	[-]	196.		18.3	37.7	0.00		0.316	0.0175	1.00	0.338
CESM2	[-]	212.		33.9	44.9	0.00		0.00	0.108	1.00	0.304
GFDL-ESM2G	[-]	209.		31.1	43.1	0.508		0.00	0.147	0.966	0.315
GFDL-ESM4	[-]	207.		29.2	39.1	0.00		0.0856	0.229	1.00	0.386
IPSL-CM5A-LR	[-]	249.		71.3	78.3	0.508		0.00	0.145	0.966	0.314
IPSL-CM6A-LR	[-]	213.		35.4	45.9	0.508		0.00	0.122	0.966	0.303
MeanCMIP5	[-]	207.		28.6	38.3	0.00		0.00	0.282	1.00	0.391
MeanCMIP6	[-]	208.		30.2	39.9	0.00		0.00	0.304	1.00	0.402
MIROC-ESM	[-]	194.		16.0	36.0	0.00		0.300	0.125	1.00	0.388
MIROC-ESM2L	[-]	180.		2.21	25.6	1.02		0.451	0.243	0.933	0.468
MPI-ESM-LR	[-]	208.		30.5	44.2	0.00		0.0265	0.117	1.00	0.315
MPI-ESM1.2-HR	[-]	217.		38.8	52.9	3.06		0.00	0.0483	0.498	0.149
NorESM1-ME	[-]	169.		-9.09	29.3	1.02		0.568	0.0224	0.933	0.386
NorESM2-LM	[-]	200.		22.5	38.2	0.00		0.0793	0.128	1.00	0.334
UK-HadGEM2-ES	[-]	208.		29.5	39.3	0.00		0.00	0.194	1.00	0.347
UKESM1-0-LL	[-]	208.		29.8	42.2	0.508		0.00	0.145	0.966	0.314

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_IN_F-SW_OUT