Africa - Central Africa - South Asia - East Siberia Asia - Indonesia Asia - North Central Asia - South Central Asia and China Australia Europe Global - Land North America - Alaska and Northern Canada North America - Eastern United States North America - Southern Canada North America - Western United States 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	[-]	436.
CESM3_092H	[-]	468.		32.5	33.9	1.02		0.00	0.609	0.933	0.538
CESM3_098bH	[-]	466.		33.6	38.5	1.02		0.00	0.528	0.933	0.497
CMIP6_001	[-]	468.		32.1	36.2	1.02		0.00	0.467	0.933	0.467
LE2_001	[-]	468.		32.3	37.4	1.02		0.00	0.527	0.933	0.497

	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	[-]	429.
CESM3_092H	[-]	461.		32.0	35.7	0.00		0.00	0.268	1.00	0.384
CESM3_098bH	[-]	461.		31.8	39.3	0.00		0.00	0.182	1.00	0.341
CMIP6_001	[-]	460.		30.4	36.6	1.02		0.00	0.0210	0.933	0.244
LE2_001	[-]	460.		30.7	36.8	1.02		0.00	0.0850	0.933	0.276

	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	[-]	295.
CESM3_092H	[-]	274.		-21.2	18.0	0.00		0.123	0.00	1.00	0.281
CESM3_098bH	[-]	277.		-19.8	17.6	0.00		0.252	0.00	1.00	0.313
CMIP6_001	[-]	282.		-12.8	22.8	0.508		0.482	0.00	0.966	0.362
LE2_001	[-]	282.		-12.3	24.4	0.508		0.482	0.00	0.966	0.362

	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	[-]	452.
CESM3_092H	[-]	471.		19.4	21.4	2.03		0.00	0.656	0.749	0.515
CESM3_098bH	[-]	470.		18.3	19.9	1.02		0.00	0.638	0.933	0.552
CMIP6_001	[-]	465.		12.9	14.6	0.00		0.0480	0.679	1.00	0.602
LE2_001	[-]	465.		12.9	14.1	1.02		0.0474	0.714	0.933	0.602

	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	[-]	339.
CESM3_092H	[-]	361.		21.5	28.7	0.00		0.00	0.0372	1.00	0.269
CESM3_098bH	[-]	366.		25.9	31.4	1.03		0.00	0.0427	0.930	0.254
CMIP6_001	[-]	350.		10.1	20.0	0.00		0.193	0.0861	1.00	0.341
LE2_001	[-]	352.		12.2	22.0	0.00		0.0266	0.0456	1.00	0.279

	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	[-]	356.
CESM3_092H	[-]	380.		23.7	30.8	0.00		0.00	0.218	1.00	0.359
CESM3_098bH	[-]	381.		24.9	31.7	0.00		0.00	0.229	1.00	0.364
CMIP6_001	[-]	365.		8.95	17.0	0.344		0.511	0.366	0.977	0.555
LE2_001	[-]	367.		10.3	18.8	0.344		0.431	0.297	0.977	0.500

	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	[-]	428.
CESM3_092H	[-]	443.		15.7	26.4	0.730		0.246	0.270	0.947	0.433
CESM3_098bH	[-]	442.		12.2	25.2	0.683		0.330	0.278	0.950	0.459
CMIP6_001	[-]	440.		11.3	23.5	0.589		0.353	0.304	0.956	0.479
LE2_001	[-]	440.		11.6	24.0	0.546		0.343	0.296	0.959	0.473

	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	[-]	361.
CESM3_092H	[-]	384.		22.2	33.2	0.759		0.0857	0.0854	0.947	0.301
CESM3_098bH	[-]	386.		24.4	34.8	0.653		0.0722	0.0897	0.954	0.301
CMIP6_001	[-]	374.		12.7	24.6	0.885		0.204	0.189	0.938	0.380
LE2_001	[-]	376.		14.2	25.0	0.611		0.177	0.188	0.956	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	[-]	376.
CESM3_092H	[-]	396.		19.3	31.6	0.778		0.128	0.119	0.939	0.326
CESM3_098bH	[-]	397.		20.6	32.3	0.703		0.135	0.115	0.945	0.328
CMIP6_001	[-]	390.		13.9	26.2	0.755		0.226	0.173	0.945	0.379
LE2_001	[-]	391.		14.6	26.5	0.632		0.212	0.165	0.954	0.374

	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	[-]	285.
CESM3_092H	[-]	294.		8.43	20.5	0.00		0.454	0.00	1.00	0.363
CESM3_098bH	[-]	295.		12.1	22.3	0.00		0.227	0.0230	1.00	0.318
CMIP6_001	[-]	299.		13.9	25.8	0.00		0.275	0.00	1.00	0.319
LE2_001	[-]	302.		17.5	27.8	0.508		0.127	0.00	0.966	0.273

	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	[-]	364.
CESM3_092H	[-]	388.		24.2	37.6	0.964		0.0272	0.00	0.935	0.241
CESM3_098bH	[-]	390.		25.2	37.4	0.964		0.0216	0.00	0.935	0.239
CMIP6_001	[-]	381.		17.6	31.6	1.03		0.163	0.00729	0.923	0.275
LE2_001	[-]	381.		17.2	32.3	0.774		0.178	0.00	0.948	0.281

	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	[-]	325.
CESM3_092H	[-]	341.		16.6	31.5	0.738		0.0219	0.00	0.950	0.243
CESM3_098bH	[-]	345.		19.7	34.1	0.295		0.00	0.00	0.980	0.245
CMIP6_001	[-]	336.		11.3	22.1	0.295		0.147	0.0875	0.980	0.326
LE2_001	[-]	336.		11.2	21.5	0.148		0.155	0.0799	0.990	0.326

	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	[-]	388.
CESM3_092H	[-]	404.		15.7	32.6	1.14		0.253	0.0819	0.884	0.325
CESM3_098bH	[-]	404.		19.9	32.5	1.14		0.258	0.0518	0.884	0.311
CMIP6_001	[-]	408.		20.0	32.9	0.855		0.190	0.0692	0.930	0.315
LE2_001	[-]	408.		19.8	32.2	0.969		0.203	0.0528	0.922	0.308

	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	[-]	450.
CESM3_092H	[-]	470.		19.8	22.8	0.00		0.00	0.445	1.00	0.473
CESM3_098bH	[-]	471.		20.7	27.6	0.00		0.00	0.357	1.00	0.429
CMIP6_001	[-]	466.		15.6	18.9	0.00		0.0774	0.651	1.00	0.595
LE2_001	[-]	466.		15.7	20.3	0.00		0.0698	0.582	1.00	0.559

Africa - Central Africa - Sahel Africa - South Asia - East Siberia Asia - Indonesia Asia - North Central Asia - South Central Asia and China Asia - Southeast Asia and India Asia - West Siberia Australia Europe Global - Land Middle East and Sahara North America - Alaska and Northern Canada North America - Central America North America - Eastern United States North America - Southern Canada North America - Western United States South America - Amazon South America - Southeast South America - Southwest 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: LW_OUT