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 [-] 301.
bcc-csm1-1 [-] 311. 3.03 22.2 0.485 0.370 0.0970 0.952 0.379
BCC-CSM2-MR [-] 309. -0.0990 20.9 0.452 0.482 0.0914 0.954 0.405
CanESM2 [-] 309. 0.985 21.4 0.453 0.453 0.0598 0.960 0.383
CanESM5 [-] 308. 0.411 20.4 0.477 0.453 0.0885 0.957 0.397
CESM1-BGC [-] 308. -2.13 19.3 0.419 0.414 0.109 0.954 0.396
CESM2 [-] 317. 8.10 21.5 0.548 0.292 0.0851 0.948 0.353
GFDL-ESM2G [-] 312. 3.01 21.3 0.422 0.402 0.0925 0.960 0.387
GFDL-ESM4 [-] 312. 3.51 20.7 0.636 0.363 0.0823 0.940 0.367
IPSL-CM5A-LR [-] 295. -11.6 25.5 0.582 0.206 0.0801 0.952 0.329
IPSL-CM6A-LR [-] 313. 3.72 21.4 0.669 0.344 0.111 0.941 0.377
MeanCMIP5 [-] 309. -0.0857 16.7 0.405 0.441 0.269 0.965 0.486
MeanCMIP6 [-] 313. 4.30 16.7 0.430 0.391 0.283 0.963 0.480
MIROC-ESM [-] 315. 7.44 22.7 0.412 0.228 0.118 0.957 0.355
MIROC-ESM2L [-] 317. 9.76 25.1 0.381 0.253 0.0538 0.968 0.332
MPI-ESM-LR [-] 314. 5.95 21.0 0.476 0.343 0.0822 0.954 0.365
MPI-ESM1.2-HR [-] 312. 3.41 19.5 0.564 0.379 0.106 0.945 0.384
NorESM1-ME [-] 306. -3.71 21.3 0.422 0.275 0.0855 0.962 0.352
NorESM2-LM [-] 318. 8.59 21.2 0.510 0.269 0.117 0.954 0.364
UK-HadGEM2-ES [-] 308. -1.31 20.8 0.426 0.423 0.0869 0.963 0.390
UKESM1-0-LL [-] 308. -0.435 20.9 0.540 0.476 0.0906 0.948 0.401

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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SurfaceDownwardLWRadiation / FLUXNET2015 / 1991-2015 / global / MNAME

Benchmark
Data not available
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bcc-csm1-1
Data not available
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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
Data not available
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IPSL-CM6A-LR
Data not available
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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
Data not available
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NorESM2-LM
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UK-HadGEM2-ES
Data not available
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UKESM1-0-LL
Data not available
Data not available

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_IN_F

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