Equatorial Africa 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	[-]	68.8
bcc-csm1-1	[-]	129.		25.8	30.9	4.08		0.00	0.518	0.244	0.320
BCC-CSM2-MR	[-]	121.		27.6	31.9	1.02		0.00	0.455	0.933	0.460
CanESM2	[-]	143.		43.4	51.3	3.07		0.00	0.107	0.494	0.177
CanESM5	[-]	138.		33.4	41.7	1.02		0.00	0.109	0.933	0.288
CESM1-BGC	[-]	119.		13.3	25.0	4.08		0.372	0.371	0.244	0.340
CESM2	[-]	117.		4.41	20.0	2.05		0.791	0.254	0.745	0.511
GFDL-ESM2G	[-]	128.		22.2	32.1	2.05		0.00	0.262	0.745	0.317
GFDL-ESM4	[-]	109.		12.0	17.4	2.05		0.433	0.467	0.745	0.528
IPSL-CM5A-LR	[-]	141.		1.57	11.5	1.02		0.926	0.549	0.933	0.739
IPSL-CM6A-LR	[-]	117.		26.2	33.9	1.02		0.00	0.473	0.933	0.470
MeanCMIP5	[-]	130.		20.3	29.8			0.0386	0.425
MeanCMIP6	[-]	121.		14.5	21.4	1.02		0.314	0.491	0.933	0.557
MIROC-ESM	[-]	147.		55.0	64.8	0.00		0.00	0.325	1.00	0.413
MIROC-ESM2L	[-]	141.		39.5	43.0	0.00		0.00	0.471	1.00	0.485
MPI-ESM-LR	[-]	137.		23.2	25.3	0.00		0.00	0.577	1.00	0.539
MPI-ESM1.2-HR	[-]	123.		10.3	20.6	1.02		0.512	0.502	0.933	0.612
NorESM1-ME	[-]	120.		15.4	22.3	2.05		0.269	0.471	0.745	0.489
NorESM2-LM	[-]	111.		-7.35	19.9	1.02		0.652	0.240	0.933	0.516
UK-HadGEM2-ES	[-]	123.		5.05	17.7			0.761	0.361
UKESM1-0-LL	[-]	113.		13.5	23.3	1.02		0.358	0.313	0.933	0.479

	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	[-]	147.
bcc-csm1-1	[-]	133.		-14.6	24.5	1.02		0.218	0.197	0.933	0.386
BCC-CSM2-MR	[-]	146.		-1.04	15.1	1.02		0.945	0.403	0.933	0.671
CanESM2	[-]	127.		-20.0	20.5	1.02		0.00	0.257	0.933	0.362
CanESM5	[-]	136.		-11.1	19.2	1.02		0.409	0.455	0.933	0.563
CESM1-BGC	[-]	125.		-22.7	27.7	1.02		0.00	0.471	0.933	0.468
CESM2	[-]	127.		-20.6	26.6	1.02		0.00	0.289	0.933	0.378
GFDL-ESM2G	[-]	132.		-15.2	23.7	0.00		0.186	0.286	1.00	0.439
GFDL-ESM4	[-]	126.		-20.8	29.4	1.02		0.00	0.209	0.933	0.338
IPSL-CM5A-LR	[-]	128.		-19.4	26.0	1.02		0.00	0.364	0.933	0.415
IPSL-CM6A-LR	[-]	126.		-21.2	28.2	1.02		0.00	0.203	0.933	0.335
MeanCMIP5	[-]	132.		-16.1	18.8	1.02		0.141	0.577	0.933	0.557
MeanCMIP6	[-]	138.		-9.24	15.2	1.02		0.507	0.508	0.933	0.614
MIROC-ESM	[-]	134.		-13.1	41.3	0.00		0.302	0.00	1.00	0.326
MIROC-ESM2L	[-]	146.		-0.787	18.8	1.02		0.958	0.246	0.933	0.596
MPI-ESM-LR	[-]	139.		-8.37	17.2	1.02		0.553	0.328	0.933	0.536
MPI-ESM1.2-HR	[-]	161.		14.0	24.7	1.02		0.253	0.182	0.933	0.388
NorESM1-ME	[-]	122.		-24.9	27.2	0.00		0.00	0.445	1.00	0.473
NorESM2-LM	[-]	140.		-6.90	19.6	0.00		0.631	0.284	1.00	0.550
UK-HadGEM2-ES	[-]	141.		-7.04	13.4	1.02		0.624	0.550	0.933	0.664
UKESM1-0-LL	[-]	127.		-20.7	24.6	1.02		0.00	0.336	0.933	0.401

	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	[-]	85.0
bcc-csm1-1	[-]	75.3		-15.1	24.4	0.624		0.251	0.176	0.950	0.388
BCC-CSM2-MR	[-]	78.8		-11.6	24.9	0.667		0.281	0.160	0.941	0.385
CanESM2	[-]	78.0		-11.3	24.9	0.565		0.326	0.201	0.944	0.418
CanESM5	[-]	79.5		-9.91	24.1	0.564		0.364	0.181	0.947	0.418
CESM1-BGC	[-]	83.1		-5.46	23.9	0.479		0.411	0.137	0.959	0.411
CESM2	[-]	79.7		-9.14	22.5	0.445		0.366	0.186	0.961	0.425
GFDL-ESM2G	[-]	75.6		-14.1	24.2	0.342		0.327	0.198	0.970	0.423
GFDL-ESM4	[-]	74.0		-15.0	23.7	0.436		0.276	0.215	0.967	0.418
IPSL-CM5A-LR	[-]	77.7		-11.3	27.6	0.709		0.328	0.122	0.947	0.380
IPSL-CM6A-LR	[-]	85.5		-3.62	24.5	0.633		0.392	0.167	0.947	0.418
MeanCMIP5	[-]	80.7		-9.87	21.1	0.551		0.353	0.241	0.952	0.447
MeanCMIP6	[-]	80.5		-8.90	20.9	0.453		0.380	0.262	0.965	0.467
MIROC-ESM	[-]	89.3		-1.15	28.7	0.547		0.347	0.0743	0.946	0.360
MIROC-ESM2L	[-]	85.7		-4.24	25.0	0.615		0.425	0.149	0.942	0.416
MPI-ESM-LR	[-]	79.0		-11.6	25.4	0.435		0.308	0.195	0.953	0.412
MPI-ESM1.2-HR	[-]	84.8		-4.06	23.0	0.531		0.380	0.207	0.941	0.434
NorESM1-ME	[-]	79.8		-9.42	22.9	0.496		0.368	0.178	0.960	0.421
NorESM2-LM	[-]	79.9		-9.63	23.6	0.487		0.349	0.164	0.963	0.410
UK-HadGEM2-ES	[-]	85.1		-4.06	24.0	0.611		0.415	0.147	0.948	0.414
UKESM1-0-LL	[-]	76.8		-12.3	22.9	0.538		0.305	0.240	0.951	0.434

	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	[-]	60.6
bcc-csm1-1	[-]	40.4		-16.9	23.6	0.537		0.247	0.187	0.961	0.396
BCC-CSM2-MR	[-]	42.6		-13.7	23.3	0.508		0.318	0.161	0.963	0.401
CanESM2	[-]	46.5		-10.9	20.7	0.198		0.423	0.260	0.987	0.483
CanESM5	[-]	47.9		-9.05	22.3	0.226		0.440	0.199	0.985	0.456
CESM1-BGC	[-]	49.2		-6.66	23.0	0.169		0.484	0.109	0.989	0.423
CESM2	[-]	48.8		-8.09	20.5	0.198		0.455	0.211	0.987	0.466
GFDL-ESM2G	[-]	45.2		-11.3	20.0	0.0847		0.389	0.266	0.994	0.479
GFDL-ESM4	[-]	45.3		-12.1	21.2	0.169		0.353	0.245	0.989	0.458
IPSL-CM5A-LR	[-]	48.8		-7.46	25.0	0.762		0.482	0.113	0.946	0.413
IPSL-CM6A-LR	[-]	54.7		-1.91	22.0	0.424		0.550	0.172	0.972	0.466
MeanCMIP5	[-]	48.4		-9.16	18.5	0.209		0.456	0.280	0.986	0.501
MeanCMIP6	[-]	48.7		-8.04	18.6	0.198		0.495	0.288	0.987	0.514
MIROC-ESM	[-]	52.5		-4.71	28.5	0.254		0.381	0.0473	0.983	0.365
MIROC-ESM2L	[-]	51.7		-5.50	23.7	0.169		0.450	0.165	0.989	0.442
MPI-ESM-LR	[-]	44.3		-13.1	21.4	0.0847		0.323	0.270	0.994	0.464
MPI-ESM1.2-HR	[-]	51.1		-5.26	19.2	0.198		0.503	0.244	0.987	0.494
NorESM1-ME	[-]	44.0		-11.7	20.7	0.282		0.398	0.205	0.981	0.447
NorESM2-LM	[-]	46.4		-10.2	21.5	0.282		0.452	0.174	0.981	0.445
UK-HadGEM2-ES	[-]	56.5		-1.65	23.0	0.209		0.541	0.150	0.986	0.457
UKESM1-0-LL	[-]	48.5		-9.61	18.9	0.198		0.428	0.285	0.987	0.496

	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	[-]	137.
bcc-csm1-1	[-]	142.		4.76	19.4	0.339		0.570	0.294	0.978	0.534
BCC-CSM2-MR	[-]	169.		31.4	39.3	3.72		0.126	0.231	0.354	0.236
CanESM2	[-]	140.		2.60	28.2	3.06		0.700	0.0691	0.436	0.319
CanESM5	[-]	137.		-0.331	24.8	3.40		0.779	0.116	0.413	0.356
CESM1-BGC	[-]	148.		10.5	24.6	0.339		0.438	0.180	0.978	0.444
CESM2	[-]	159.		22.3	29.9	0.339		0.00965	0.305	0.978	0.400
GFDL-ESM2G	[-]	145.		7.86	20.8	1.02		0.580	0.271	0.894	0.504
GFDL-ESM4	[-]	144.		7.25	20.4	0.339		0.613	0.264	0.978	0.530
IPSL-CM5A-LR	[-]	176.		39.3	43.8	0.339		0.00	0.234	0.978	0.361
IPSL-CM6A-LR	[-]	156.		18.8	27.2	0.339		0.0473	0.274	0.978	0.393
MeanCMIP5	[-]	148.		10.2	19.0	1.36		0.455	0.405	0.871	0.534
MeanCMIP6	[-]	155.		17.5	24.3	0.339		0.0685	0.393	0.978	0.458
MIROC-ESM	[-]	146.		8.34	27.3	3.72		0.428	0.0349	0.354	0.213
MIROC-ESM2L	[-]	150.		13.3	23.1	4.06		0.331	0.288	0.333	0.310
MPI-ESM-LR	[-]	137.		0.116	22.9	5.73		0.694	0.139	0.0225	0.249
MPI-ESM1.2-HR	[-]	164.		27.1	39.4	4.76		0.0110	0.0374	0.123	0.0523
NorESM1-ME	[-]	131.		-5.84	20.6	1.36		0.630	0.250	0.871	0.500
NorESM2-LM	[-]	153.		16.3	24.5	0.339		0.179	0.317	0.978	0.448
UK-HadGEM2-ES	[-]	153.		14.8	25.1	0.678		0.224	0.233	0.955	0.411
UKESM1-0-LL	[-]	149.		12.2	24.4	3.72		0.347	0.210	0.354	0.281

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: NETRAD