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 [-] 28.7
bcc-csm1-1 [-] 29.9 -3.44 31.4 1.60 0.327 0.0481 0.782 0.301
BCC-CSM2-MR [-] 28.6 -5.77 31.5 1.88 0.296 0.0567 0.717 0.281
CanESM2 [-] 37.4 4.60 31.0 1.63 0.378 0.0670 0.757 0.317
CanESM5 [-] 28.0 -4.32 26.4 1.50 0.373 0.128 0.813 0.360
CESM1-BGC [-] 29.1 -2.49 26.9 1.40 0.414 0.0930 0.822 0.356
CESM2 [-] 34.3 2.02 25.4 1.20 0.413 0.137 0.862 0.387
GFDL-ESM2G [-] 21.6 -11.5 29.7 1.25 0.188 0.0840 0.831 0.297
GFDL-ESM4 [-] 18.6 -15.6 30.2 1.72 0.118 0.111 0.749 0.272
IPSL-CM5A-LR [-] 31.6 -2.34 29.9 1.26 0.262 0.0753 0.831 0.311
IPSL-CM6A-LR [-] 29.4 -2.52 26.4 1.71 0.375 0.113 0.762 0.341
MeanCMIP5 [-] 29.5 -3.74 24.5 1.26 0.357 0.159 0.840 0.379
MeanCMIP6 [-] 28.0 -5.16 23.8 1.43 0.366 0.175 0.802 0.380
MIROC-ESM [-] 33.0 0.880 33.1 1.78 0.362 0.0377 0.748 0.296
MIROC-ESM2L [-] 21.1 -12.0 28.6 1.63 0.250 0.0939 0.751 0.297
MPI-ESM-LR [-] 23.5 -9.52 31.4 1.68 0.192 0.0744 0.748 0.272
MPI-ESM1.2-HR [-] 32.6 -3.03 31.6 1.67 0.314 0.0619 0.747 0.296
NorESM1-ME [-] 27.1 -4.54 25.9 1.42 0.384 0.0981 0.808 0.347
NorESM2-LM [-] 34.4 2.23 26.1 1.50 0.366 0.117 0.779 0.345
UK-HadGEM2-ES [-] 31.8 -1.12 27.8 1.51 0.378 0.0920 0.755 0.329
UKESM1-0-LL [-] 28.1 -5.24 25.1 1.30 0.343 0.133 0.818 0.357

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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SensibleHeat / FLUXNET2015 / 1991-2015 / global / MNAME

Benchmark
Data not available
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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: H_F_MDS

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