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 [-] 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

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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SurfaceUpwardLWRadiation / 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: LW_OUT

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