Boreal forest Global - Land Subtropical desert Temperate grassland/desert Temperate seasonal forest Tropical rain forest Tropical seasonal forest/savanna Tundra Woodland/shrubland

	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	[-]	264.
ACCESS-ESM1-5	[-]	276.		12.2	24.7	0.128		0.775	0.675	0.986	0.778
BCC-CSM2-MR	[-]	265.		0.789	21.6	0.172		0.868	0.664	0.988	0.796
CanESM5	[-]	263.		-0.958	21.8	0.0431		0.884	0.656	0.997	0.798
CESM2	[-]	274.		10.2	22.6	0.128		0.797	0.684	0.986	0.788
GFDL-ESM4	[-]	271.		7.31	22.6	0.172		0.811	0.683	0.988	0.791
IPSL-CM6A-LR	[-]	266.		2.36	22.3	0.0861		0.859	0.656	0.994	0.791
MeanCMIP6	[-]	271.		7.02	17.7	0.0861		0.837	0.743	0.994	0.829
MIROC-ESM2L	[-]	279.		14.8	27.5	0.129		0.711	0.667	0.991	0.759
MPI-ESM1.2-HR	[-]	272.		8.02	20.9	0.129		0.816	0.695	0.991	0.799
NorESM2-LM	[-]	275.		10.9	23.3	0.0861		0.782	0.684	0.994	0.786
UKESM1-0-LL	[-]	263.		-1.09	22.8	0.0861		0.877	0.641	0.994	0.789

	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	[-]	312.
ACCESS-ESM1-5	[-]	320.		7.91	23.2	0.531		0.690	0.593	0.949	0.707
BCC-CSM2-MR	[-]	310.		-2.09	21.5	0.416		0.738	0.584	0.957	0.716
CanESM5	[-]	310.		-2.75	21.6	0.492		0.720	0.579	0.959	0.709
CESM2	[-]	318.		5.91	21.5	0.527		0.715	0.597	0.949	0.714
GFDL-ESM4	[-]	313.		0.764	20.7	0.546		0.741	0.596	0.943	0.719
IPSL-CM6A-LR	[-]	314.		2.05	21.5	0.670		0.724	0.593	0.949	0.715
MeanCMIP6	[-]	314.		1.36	17.0	0.467		0.743	0.683	0.956	0.766
MIROC-ESM2L	[-]	318.		5.59	23.3	0.416		0.694	0.588	0.962	0.708
MPI-ESM1.2-HR	[-]	313.		0.930	20.2	0.521		0.739	0.604	0.944	0.723
NorESM2-LM	[-]	319.		6.62	21.9	0.508		0.700	0.594	0.955	0.711
UKESM1-0-LL	[-]	309.		-3.65	21.6	0.536		0.726	0.593	0.946	0.714

	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	[-]	348.
ACCESS-ESM1-5	[-]	345.		-3.59	20.4	0.894		0.715	0.556	0.929	0.689
BCC-CSM2-MR	[-]	343.		-5.34	20.5	0.567		0.722	0.567	0.949	0.701
CanESM5	[-]	339.		-9.90	22.4	0.563		0.663	0.529	0.963	0.671
CESM2	[-]	350.		1.72	20.3	0.676		0.744	0.559	0.955	0.704
GFDL-ESM4	[-]	346.		-2.02	19.4	0.448		0.759	0.557	0.971	0.711
IPSL-CM6A-LR	[-]	344.		-4.34	19.7	0.787		0.797	0.536	0.948	0.704
MeanCMIP6	[-]	344.		-4.72	14.7	0.678		0.787	0.660	0.955	0.766
MIROC-ESM2L	[-]	352.		3.71	20.5	0.339		0.753	0.552	0.978	0.709
MPI-ESM1.2-HR	[-]	345.		-3.11	20.3	0.569		0.717	0.559	0.962	0.699
NorESM2-LM	[-]	352.		3.47	20.8	0.678		0.806	0.527	0.955	0.704
UKESM1-0-LL	[-]	338.		-9.98	20.7	0.667		0.667	0.570	0.944	0.688

	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	[-]	319.
ACCESS-ESM1-5	[-]	314.		-5.18	18.4	0.886		0.785	0.658	0.940	0.760
BCC-CSM2-MR	[-]	314.		-5.60	17.6	0.738		0.774	0.656	0.950	0.759
CanESM5	[-]	305.		-14.0	20.9	0.886		0.668	0.614	0.940	0.709
CESM2	[-]	323.		3.50	18.3	1.03		0.882	0.645	0.931	0.776
GFDL-ESM4	[-]	310.		-9.30	18.2	0.886		0.771	0.664	0.940	0.760
IPSL-CM6A-LR	[-]	310.		-8.92	21.0	0.886		0.792	0.613	0.940	0.739
MeanCMIP6	[-]	312.		-6.81	14.5	0.886		0.759	0.734	0.940	0.792
MIROC-ESM2L	[-]	315.		-4.10	17.1	0.738		0.800	0.659	0.950	0.767
MPI-ESM1.2-HR	[-]	318.		-1.50	16.5	0.886		0.824	0.656	0.940	0.769
NorESM2-LM	[-]	329.		10.2	24.9	0.886		0.763	0.606	0.940	0.729
UKESM1-0-LL	[-]	310.		-8.98	18.4	0.886		0.722	0.657	0.940	0.744

	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	[-]	305.
ACCESS-ESM1-5	[-]	315.		9.76	24.9	0.448		0.660	0.607	0.965	0.710
BCC-CSM2-MR	[-]	303.		-2.77	23.1	0.189		0.765	0.576	0.987	0.726
CanESM5	[-]	306.		0.718	21.9	0.320		0.756	0.602	0.978	0.734
CESM2	[-]	310.		4.53	22.0	0.420		0.724	0.607	0.967	0.726
GFDL-ESM4	[-]	307.		1.71	22.0	0.247		0.743	0.605	0.983	0.734
IPSL-CM6A-LR	[-]	310.		4.15	22.5	0.757		0.708	0.608	0.949	0.718
MeanCMIP6	[-]	307.		2.03	17.7	0.218		0.747	0.696	0.985	0.781
MIROC-ESM2L	[-]	312.		6.63	24.5	0.247		0.708	0.594	0.983	0.720
MPI-ESM1.2-HR	[-]	306.		0.624	20.9	0.160		0.755	0.616	0.989	0.744
NorESM2-LM	[-]	311.		5.68	21.5	0.335		0.710	0.616	0.977	0.730
UKESM1-0-LL	[-]	302.		-3.54	22.7	0.277		0.754	0.591	0.981	0.729

	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	[-]	409.
ACCESS-ESM1-5	[-]	418.		9.70	12.2	2.05		0.247	0.366	0.745	0.431
BCC-CSM2-MR	[-]	419.		10.1	13.4	1.03		0.234	0.354	0.930	0.468
CanESM5	[-]	418.		9.84	14.2	1.02		0.242	0.217	0.933	0.402
CESM2	[-]	424.		15.0	18.1	2.05		0.115	0.327	0.745	0.379
GFDL-ESM4	[-]	412.		3.51	9.55	2.05		0.603	0.310	0.745	0.492
IPSL-CM6A-LR	[-]	409.		0.681	5.07	1.02		0.906	0.492	0.933	0.706
MeanCMIP6	[-]	417.		8.23	10.2	2.05		0.305	0.499	0.745	0.512
MIROC-ESM2L	[-]	413.		4.83	6.55	1.02		0.499	0.435	0.933	0.575
MPI-ESM1.2-HR	[-]	411.		2.65	6.67	3.05		0.682	0.437	0.498	0.513
NorESM2-LM	[-]	421.		12.6	15.6	2.05		0.163	0.443	0.745	0.449
UKESM1-0-LL	[-]	418.		9.28	12.0	1.03		0.262	0.465	0.930	0.531

	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	[-]	392.
ACCESS-ESM1-5	[-]	398.		5.17	18.8	1.59		0.687	0.482	0.787	0.610
BCC-CSM2-MR	[-]	395.		2.69	17.2	1.58		0.655	0.510	0.753	0.607
CanESM5	[-]	394.		1.22	19.0	1.35		0.651	0.443	0.829	0.592
CESM2	[-]	403.		10.3	20.0	1.45		0.602	0.493	0.785	0.593
GFDL-ESM4	[-]	392.		-0.541	15.7	2.07		0.730	0.504	0.679	0.604
IPSL-CM6A-LR	[-]	395.		2.44	18.4	1.06		0.681	0.484	0.868	0.629
MeanCMIP6	[-]	395.		2.60	12.9	1.39		0.743	0.600	0.794	0.685
MIROC-ESM2L	[-]	397.		5.02	17.8	1.69		0.675	0.498	0.790	0.615
MPI-ESM1.2-HR	[-]	390.		-2.49	17.4	2.02		0.688	0.476	0.690	0.582
NorESM2-LM	[-]	403.		10.7	19.6	1.35		0.615	0.485	0.811	0.599
UKESM1-0-LL	[-]	388.		-3.95	16.2	1.87		0.690	0.523	0.706	0.610

	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	[-]	240.
ACCESS-ESM1-5	[-]	240.		-0.488	24.7	0.00		0.781	0.617	1.00	0.754
BCC-CSM2-MR	[-]	232.		-8.31	28.0	0.129		0.737	0.602	0.991	0.733
CanESM5	[-]	233.		-7.51	26.8	0.258		0.775	0.591	0.983	0.735
CESM2	[-]	249.		8.62	26.8	0.129		0.735	0.620	0.991	0.742
GFDL-ESM4	[-]	240.		0.380	24.3	0.00		0.766	0.635	1.00	0.759
IPSL-CM6A-LR	[-]	244.		3.47	27.5	0.258		0.761	0.599	0.983	0.735
MeanCMIP6	[-]	240.		-0.0372	21.3	0.00		0.778	0.682	1.00	0.786
MIROC-ESM2L	[-]	239.		-1.05	29.5	0.129		0.740	0.590	0.991	0.728
MPI-ESM1.2-HR	[-]	239.		-0.910	27.0	0.00		0.753	0.603	1.00	0.740
NorESM2-LM	[-]	248.		8.40	25.3	0.129		0.740	0.617	0.991	0.741
UKESM1-0-LL	[-]	230.		-10.5	27.9	0.00		0.723	0.610	1.00	0.736

	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	[-]	311.
ACCESS-ESM1-5	[-]	320.		9.21	23.1	0.344		0.683	0.587	0.977	0.708
BCC-CSM2-MR	[-]	308.		-3.11	21.3	0.343		0.694	0.584	0.977	0.710
CanESM5	[-]	305.		-6.31	21.8	0.540		0.661	0.581	0.964	0.697
CESM2	[-]	316.		4.75	20.9	0.409		0.703	0.591	0.973	0.714
GFDL-ESM4	[-]	310.		-0.676	20.5	0.507		0.711	0.587	0.966	0.713
IPSL-CM6A-LR	[-]	313.		1.52	21.2	0.654		0.679	0.597	0.956	0.707
MeanCMIP6	[-]	311.		-0.142	17.6	0.507		0.706	0.676	0.966	0.756
MIROC-ESM2L	[-]	314.		3.21	23.1	0.294		0.661	0.582	0.980	0.701
MPI-ESM1.2-HR	[-]	312.		0.459	20.3	0.507		0.698	0.602	0.966	0.717
NorESM2-LM	[-]	316.		4.52	22.3	0.508		0.673	0.581	0.966	0.700
UKESM1-0-LL	[-]	308.		-2.76	21.5	0.541		0.672	0.595	0.964	0.707

Boreal forest Global - Land Subtropical desert Temperate grassland/desert Temperate rain forest Temperate seasonal forest Tropical rain forest Tropical seasonal forest/savanna Tundra Woodland/shrubland 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_IN_F