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	[-]	452.
bcc-csm1-1	[-]	464.		11.5	14.1	0.00		0.150	0.700	1.00	0.638
BCC-CSM2-MR	[-]	466.		14.3	15.5	2.00		0.00	0.685	0.756	0.532
CanESM2	[-]	448.		-4.12	6.94	3.05		0.696	0.535	0.498	0.566
CanESM5	[-]	459.		7.22	9.41	0.00		0.467	0.756	1.00	0.745
CESM1-BGC	[-]	454.		2.21	6.95	2.03		0.837	0.633	0.749	0.713
CESM2	[-]	467.		14.4	16.1	2.03		0.00	0.624	0.749	0.499
GFDL-ESM2G	[-]	460.		7.51	10.7	1.02		0.446	0.644	0.933	0.667
GFDL-ESM4	[-]	465.		12.9	14.7	0.00		0.0467	0.703	1.00	0.613
IPSL-CM5A-LR	[-]	455.		2.72	5.49	0.00		0.799	0.765	1.00	0.832
IPSL-CM6A-LR	[-]	462.		10.3	12.0	1.02		0.239	0.709	0.933	0.647
MeanCMIP5	[-]	454.		2.06	6.04	1.02		0.848	0.715	0.933	0.803
MeanCMIP6	[-]	463.		11.1	12.8	1.02		0.181	0.781	0.933	0.669
MIROC-ESM	[-]	442.		-10.1	13.2	2.03		0.255	0.572	0.749	0.537
MIROC-ESM2L	[-]	452.		-0.289	7.98	0.00		0.979	0.540	1.00	0.764
MPI-ESM-LR	[-]	457.		4.99	10.8	1.02		0.632	0.497	0.933	0.640
MPI-ESM1.2-HR	[-]	444.		-7.73	9.46	0.00		0.430	0.657	1.00	0.686
NorESM1-ME	[-]	449.		-3.37	5.69	1.02		0.751	0.643	0.933	0.743
NorESM2-LM	[-]	474.		21.4	22.2	1.02		0.00	0.631	0.933	0.549
UK-HadGEM2-ES	[-]	466.		13.9	16.5	1.02		0.00	0.650	0.933	0.558
UKESM1-0-LL	[-]	463.		11.3	13.0	1.02		0.165	0.746	0.933	0.647

	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	[-]	362.
bcc-csm1-1	[-]	377.		-0.522	23.0	0.329		0.299	0.146	0.974	0.391
BCC-CSM2-MR	[-]	378.		-1.61	22.1	0.502		0.333	0.112	0.951	0.377
CanESM2	[-]	385.		9.26	30.7	0.619		0.194	0.0740	0.928	0.318
CanESM5	[-]	382.		5.22	24.8	0.484		0.319	0.148	0.954	0.392
CESM1-BGC	[-]	382.		5.10	22.8	0.601		0.238	0.178	0.945	0.385
CESM2	[-]	390.		11.7	27.6	0.697		0.182	0.162	0.937	0.361
GFDL-ESM2G	[-]	380.		-0.0299	21.5	0.522		0.370	0.177	0.951	0.419
GFDL-ESM4	[-]	376.		-4.92	20.4	0.427		0.360	0.147	0.963	0.404
IPSL-CM5A-LR	[-]	371.		-5.98	21.0	0.503		0.376	0.159	0.955	0.412
IPSL-CM6A-LR	[-]	378.		0.504	25.5	0.542		0.348	0.114	0.952	0.382
MeanCMIP5	[-]	379.		0.0547	18.9	0.524		0.272	0.269	0.952	0.440
MeanCMIP6	[-]	381.		2.69	19.9	0.445		0.362	0.241	0.959	0.451
MIROC-ESM	[-]	380.		5.75	24.3	0.504		0.199	0.193	0.956	0.385
MIROC-ESM2L	[-]	383.		5.89	24.8	0.426		0.284	0.124	0.961	0.373
MPI-ESM-LR	[-]	378.		1.31	20.4	0.561		0.344	0.166	0.951	0.407
MPI-ESM1.2-HR	[-]	377.		-2.95	19.8	0.582		0.400	0.143	0.951	0.409
NorESM1-ME	[-]	375.		-2.35	20.6	0.445		0.389	0.183	0.959	0.429
NorESM2-LM	[-]	390.		12.1	27.3	0.620		0.189	0.165	0.946	0.366
UK-HadGEM2-ES	[-]	385.		4.33	27.2	0.557		0.279	0.109	0.947	0.361
UKESM1-0-LL	[-]	377.		-0.660	22.5	0.445		0.363	0.115	0.959	0.388

	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.
bcc-csm1-1	[-]	331.		-7.44	17.4	0.362		0.498	0.191	0.969	0.462
BCC-CSM2-MR	[-]	332.		-7.65	18.1	0.484		0.506	0.127	0.950	0.428
CanESM2	[-]	344.		2.20	25.4	0.843		0.223	0.0315	0.881	0.292
CanESM5	[-]	338.		-2.40	15.6	0.484		0.504	0.184	0.950	0.455
CESM1-BGC	[-]	344.		2.67	21.8	0.302		0.173	0.164	0.973	0.368
CESM2	[-]	346.		5.09	20.8	0.362		0.233	0.234	0.969	0.417
GFDL-ESM2G	[-]	336.		-3.46	17.9	0.783		0.456	0.177	0.909	0.430
GFDL-ESM4	[-]	334.		-7.84	16.3	0.484		0.501	0.161	0.950	0.443
IPSL-CM5A-LR	[-]	332.		-6.47	19.2	0.544		0.507	0.124	0.946	0.425
IPSL-CM6A-LR	[-]	339.		-2.58	20.7	0.484		0.675	0.0624	0.950	0.437
MeanCMIP5	[-]	339.		-2.96	14.1	0.388		0.429	0.309	0.974	0.505
MeanCMIP6	[-]	338.		-2.80	13.6	0.363		0.498	0.300	0.958	0.514
MIROC-ESM	[-]	345.		3.60	19.8	0.484		0.226	0.211	0.950	0.399
MIROC-ESM2L	[-]	339.		-1.22	20.4	0.484		0.352	0.0988	0.950	0.375
MPI-ESM-LR	[-]	339.		-3.59	15.2	0.483		0.580	0.201	0.950	0.483
MPI-ESM1.2-HR	[-]	334.		-5.73	15.8	0.543		0.366	0.133	0.946	0.394
NorESM1-ME	[-]	336.		-6.71	17.0	0.484		0.548	0.185	0.950	0.467
NorESM2-LM	[-]	344.		2.58	17.8	0.361		0.318	0.253	0.969	0.448
UK-HadGEM2-ES	[-]	344.		-1.59	23.1	0.449		0.395	0.0818	0.970	0.382
UKESM1-0-LL	[-]	333.		-8.86	16.5	0.424		0.613	0.132	0.954	0.457

	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	[-]	453.
bcc-csm1-1	[-]	467.		16.2	27.3	1.02		0.00	0.127	0.933	0.297
BCC-CSM2-MR	[-]	465.		18.7	26.3	1.02		0.00	0.363	0.933	0.415
CanESM2	[-]	496.		67.2	76.7	0.00		0.00	0.00	1.00	0.250
CanESM5	[-]	495.		71.9	86.7	0.00		0.00	0.00	1.00	0.250
CESM1-BGC	[-]	457.		-3.44	5.92	0.00		0.746	0.711	1.00	0.792
CESM2	[-]	466.		11.4	14.8	0.00		0.160	0.631	1.00	0.605
GFDL-ESM2G	[-]	462.		13.9	26.8	0.00		0.00	0.00	1.00	0.250
GFDL-ESM4	[-]	467.		8.57	29.1	0.00		0.368	0.00	1.00	0.342
IPSL-CM5A-LR	[-]	465.		19.0	25.5	1.02		0.00	0.279	0.933	0.373
IPSL-CM6A-LR	[-]	461.		9.14	10.6	1.02		0.326	0.730	0.933	0.680
MeanCMIP5	[-]	464.		14.0	19.5	0.00		0.00	0.484	1.00	0.492
MeanCMIP6	[-]	465.		15.8	22.5	0.00		0.00	0.375	1.00	0.438
MIROC-ESM	[-]	451.		-2.54	10.1	1.02		0.813	0.405	0.933	0.639
MIROC-ESM2L	[-]	452.		2.82	12.4	2.03		0.792	0.364	0.749	0.567
MPI-ESM-LR	[-]	475.		22.5	35.1	1.02		0.00	0.0288	0.933	0.248
MPI-ESM1.2-HR	[-]	461.		7.69	24.9	0.00		0.433	0.00	1.00	0.358
NorESM1-ME	[-]	447.		-12.3	10.7	0.00		0.0934	0.676	1.00	0.611
NorESM2-LM	[-]	462.		10.3	11.8	0.00		0.244	0.671	1.00	0.647
UK-HadGEM2-ES	[-]	459.		4.52	6.98	0.00		0.667	0.643	1.00	0.738
UKESM1-0-LL	[-]	467.		18.4	26.1	0.00		0.00	0.212	1.00	0.356

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: LW_OUT