Global - Land
bcc-csm1-1
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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 [-] 26.7
bcc-csm1-1 [-] 25.8 -3.54 14.0 1.49 0.336 0.342 0.798 0.454
BCC-CSM2-MR [-] 26.6 -2.91 14.2 1.50 0.301 0.360 0.778 0.450
CanESM2 [-] 33.8 4.89 18.0 1.15 0.161 0.195 0.842 0.348
CanESM5 [-] 31.5 2.98 14.6 1.36 0.301 0.309 0.805 0.431
CESM1-BGC [-] 26.4 -2.44 12.0 1.33 0.367 0.419 0.811 0.504
CESM2 [-] 27.9 -1.54 12.7 1.15 0.337 0.395 0.841 0.492
GFDL-ESM2G [-] 32.6 4.45 16.9 1.36 0.210 0.232 0.811 0.371
GFDL-ESM4 [-] 33.6 4.57 16.5 1.11 0.215 0.280 0.856 0.408
IPSL-CM5A-LR [-] 35.9 4.64 16.5 1.53 0.240 0.249 0.801 0.385
IPSL-CM6A-LR [-] 26.3 -1.79 14.1 1.54 0.327 0.335 0.783 0.445
MeanCMIP5 [-] 30.0 0.686 13.2 1.51 0.288 0.391 0.778 0.462
MeanCMIP6 [-] 29.4 0.283 12.5 1.22 0.307 0.418 0.825 0.492
MIROC-ESM [-] 29.9 3.26 19.1 1.36 0.196 0.206 0.795 0.351
MIROC-ESM2L [-] 25.2 -3.67 13.7 1.44 0.355 0.376 0.792 0.475
MPI-ESM-LR [-] 29.0 0.481 15.5 1.18 0.260 0.280 0.833 0.413
MPI-ESM1.2-HR [-] 28.4 -2.90 14.3 1.25 0.278 0.356 0.837 0.457
NorESM1-ME [-] 25.3 -3.03 13.1 1.19 0.382 0.404 0.830 0.505
NorESM2-LM [-] 26.9 -2.19 13.6 1.21 0.355 0.355 0.826 0.473
UK-HadGEM2-ES [-] 28.6 -0.912 15.0 1.42 0.229 0.318 0.796 0.415
UKESM1-0-LL [-] 36.9 7.64 17.2 1.32 0.209 0.246 0.817 0.380

Temporally integrated period mean click to collapse contents

BENCHMARK MEAN
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MODEL MEAN
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BIAS
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BIAS SCORE
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RMSE
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RMSE SCORE
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BENCHMARK MAX MONTH
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MODEL MAX MONTH
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DIFFERENCE IN MAX MONTH
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SEASONAL CYCLE SCORE
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Spatially integrated regional mean click to collapse contents

MODEL COLORS
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REGIONAL MEAN
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ANNUAL CYCLE
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MONTHLY ANOMALY
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ANNUAL CYCLE
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SurfaceUpwardSWRadiation / FLUXNET2015 / 1991-2015 / global / MNAME

Benchmark
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bcc-csm1-1
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BCC-CSM2-MR
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CanESM2
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CanESM5
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CESM1-BGC
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CESM2
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GFDL-ESM2G
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GFDL-ESM4
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IPSL-CM5A-LR
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IPSL-CM6A-LR
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MeanCMIP5
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MeanCMIP6
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MIROC-ESM
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MIROC-ESM2L
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MPI-ESM-LR
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MPI-ESM1.2-HR
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NorESM1-ME
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NorESM2-LM
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UK-HadGEM2-ES
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UKESM1-0-LL
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Data Information

  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_OUT

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