Mean State

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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 [-] 409.
ACCESS-ESM1-5 [-] 415. 5.88 14.3 5.57 0.463 0.296 0.0316 0.272
BCC-CSM2-MR [-] 418. 8.68 13.5 3.02 0.370 0.353 0.500 0.394
BGCLND [-] 403. -5.42 9.96 5.07 0.519 0.347 0.122 0.334
BGCLNDATM_progCO2 [-] 413. 3.64 8.64 2.55 0.529 0.439 0.532 0.485
CanESM5 [-] 421. 12.0 18.8 5.57 0.215 0.256 0.0316 0.190
CNRM-ESM2-1 [-] 418. 8.95 12.5 6.05 0.321 0.407 7.41e-05 0.284
EC-Earth3-CC [-] 407. -1.84 15.1 3.06 0.780 0.159 0.498 0.399
MeanCMIP6 [-] 417. 7.85 13.1 5.57 0.366 0.335 0.0316 0.267
MIROC-ES2L [-] 414. 5.03 10.5 0.508 0.595 0.382 0.966 0.581
MPI-ESM1-2-LR [-] 410. 0.698 9.00 5.07 0.808 0.335 0.0674 0.387
MRI-ESM2-0 [-] 412. 2.99 14.0 3.06 0.467 0.232 0.498 0.357
NorESM2-LM [-] 420. 11.1 14.8 2.55 0.289 0.348 0.532 0.379
UKESM1-0-LL [-] 415. 6.08 12.1 6.05 0.503 0.341 7.41e-05 0.297
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 [-] 419.
ACCESS-ESM1-5 [-] 428. 9.20 12.4 6.05 0.122 0.204 7.41e-05 0.132
BCC-CSM2-MR [-] 422. 2.83 7.43 6.05 0.523 0.224 7.41e-05 0.243
BGCLND [-] 414. -5.26 7.17 6.05 0.300 0.287 7.41e-05 0.218
BGCLNDATM_progCO2 [-] 419. 0.203 4.99 6.05 0.955 0.320 7.41e-05 0.399
CanESM5 [-] 423. 4.31 7.69 0.00 0.373 0.279 1.00 0.483
CNRM-ESM2-1 [-] 412. -6.33 7.88 6.05 0.235 0.271 7.41e-05 0.194
EC-Earth3-CC [-] 410. -9.09 11.2 6.05 0.125 0.260 7.41e-05 0.161
MeanCMIP6 [-] 422. 3.50 7.09 6.05 0.449 0.297 7.41e-05 0.261
MIROC-ES2L [-] 419. -0.222 15.4 6.05 0.950 0.0298 7.41e-05 0.253
MPI-ESM1-2-LR [-] 409. -10.3 12.5 5.10 0.0955 0.190 0.0631 0.135
MRI-ESM2-0 [-] 426. 7.19 10.7 6.05 0.193 0.173 7.41e-05 0.135
NorESM2-LM [-] 429. 10.2 12.8 6.05 0.0969 0.197 7.41e-05 0.123
UKESM1-0-LL [-] 423. 3.84 8.00 6.05 0.415 0.225 7.41e-05 0.217
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 [-] 312.
ACCESS-ESM1-5 [-] 320. 7.91 23.2 0.531 0.690 0.593 0.949 0.707
BCC-CSM2-MR [-] 310. -2.09 21.5 0.416 0.738 0.584 0.957 0.716
BGCLND [-] 310. -2.32 21.2 0.407 0.739 0.596 0.957 0.722
BGCLNDATM_progCO2 [-] 319. 6.80 21.5 0.431 0.691 0.629 0.961 0.728
CanESM5 [-] 310. -2.75 21.6 0.492 0.720 0.579 0.959 0.709
CNRM-ESM2-1 [-] 309. -3.24 20.0 0.552 0.738 0.608 0.950 0.726
EC-Earth3-CC [-] 310. -2.78 21.0 0.555 0.749 0.587 0.943 0.717
MeanCMIP6 [-] 312. -0.144 17.6 0.476 0.740 0.669 0.954 0.758
MIROC-ES2L [-] 318. 5.59 23.3 0.416 0.694 0.588 0.962 0.708
MPI-ESM1-2-LR [-] 316. 3.30 22.2 0.516 0.718 0.584 0.948 0.709
MRI-ESM2-0 [-] 314. 1.50 20.9 0.421 0.715 0.605 0.963 0.722
NorESM2-LM [-] 319. 6.62 21.9 0.508 0.700 0.594 0.955 0.711
UKESM1-0-LL [-] 309. -3.65 21.6 0.536 0.726 0.593 0.946 0.714
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 [-] 284.
ACCESS-ESM1-5 [-] 290. 6.76 22.0 0.0608 0.770 0.600 0.996 0.742
BCC-CSM2-MR [-] 281. -3.03 21.4 0.101 0.817 0.581 0.993 0.743
BGCLND [-] 279. -4.05 21.8 0.0422 0.808 0.585 0.997 0.744
BGCLNDATM_progCO2 [-] 297. 13.9 23.8 0.295 0.692 0.633 0.980 0.735
CanESM5 [-] 283. -0.840 19.8 0.344 0.833 0.609 0.977 0.757
CNRM-ESM2-1 [-] 282. -1.36 18.9 0.243 0.833 0.616 0.984 0.762
EC-Earth3-CC [-] 279. -4.91 18.8 0.0405 0.837 0.627 0.997 0.772
MeanCMIP6 [-] 284. 0.699 16.7 0.182 0.818 0.675 0.988 0.789
MIROC-ES2L [-] 286. 2.39 24.9 0.243 0.745 0.563 0.984 0.714
MPI-ESM1-2-LR [-] 291. 7.28 22.4 0.284 0.758 0.590 0.981 0.730
MRI-ESM2-0 [-] 291. 7.57 21.1 0.142 0.770 0.616 0.990 0.748
NorESM2-LM [-] 291. 7.25 20.2 0.182 0.772 0.627 0.988 0.753
UKESM1-0-LL [-] 279. -4.40 22.1 0.162 0.817 0.572 0.989 0.738
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 [-] 415.
ACCESS-ESM1-5 [-] 416. 0.884 7.00 1.34 0.668 0.314 0.874 0.542
BCC-CSM2-MR [-] 412. -3.55 8.04 4.70 0.534 0.266 0.133 0.300
BGCLND [-] 412. -3.46 7.88 3.68 0.584 0.307 0.341 0.385
BGCLNDATM_progCO2 [-] 414. -0.647 5.42 1.34 0.778 0.412 0.752 0.588
CanESM5 [-] 422. 6.45 13.6 1.68 0.353 0.141 0.791 0.356
CNRM-ESM2-1 [-] 405. -10.2 12.7 2.01 0.196 0.239 0.755 0.357
EC-Earth3-CC [-] 416. 1.15 11.6 5.04 0.718 0.141 0.0710 0.268
MeanCMIP6 [-] 415. 0.111 6.06 2.68 0.752 0.355 0.505 0.492
MIROC-ES2L [-] 423. 7.69 12.8 1.34 0.322 0.231 0.874 0.414
MPI-ESM1-2-LR [-] 412. -3.47 10.1 4.71 0.533 0.173 0.251 0.282
MRI-ESM2-0 [-] 422. 7.04 10.8 1.34 0.281 0.267 0.752 0.392
NorESM2-LM [-] 418. 2.38 8.52 1.34 0.612 0.259 0.752 0.470
UKESM1-0-LL [-] 415. -0.306 7.01 4.70 0.844 0.295 0.133 0.392
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 [-] 300.
ACCESS-ESM1-5 [-] 311. 10.8 24.2 0.392 0.691 0.611 0.970 0.721
BCC-CSM2-MR [-] 298. -1.87 22.1 0.246 0.763 0.592 0.983 0.733
BGCLND [-] 298. -1.63 21.7 0.171 0.760 0.608 0.988 0.741
BGCLNDATM_progCO2 [-] 309. 9.03 22.8 0.299 0.685 0.637 0.980 0.735
CanESM5 [-] 298. -1.70 21.5 0.394 0.747 0.606 0.974 0.733
CNRM-ESM2-1 [-] 298. -1.89 20.3 0.408 0.760 0.622 0.973 0.744
EC-Earth3-CC [-] 298. -1.78 21.1 0.351 0.769 0.611 0.976 0.742
MeanCMIP6 [-] 301. 1.06 18.1 0.323 0.749 0.684 0.978 0.774
MIROC-ES2L [-] 307. 6.99 24.5 0.246 0.695 0.602 0.983 0.721
MPI-ESM1-2-LR [-] 305. 5.40 22.8 0.309 0.727 0.601 0.979 0.727
MRI-ESM2-0 [-] 304. 3.51 21.0 0.288 0.745 0.623 0.981 0.743
NorESM2-LM [-] 307. 6.52 22.1 0.380 0.710 0.613 0.974 0.728
UKESM1-0-LL [-] 297. -2.66 22.4 0.359 0.742 0.601 0.976 0.730

Temporally integrated period mean

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
Data not available
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SEASONAL CYCLE SCORE
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Spatially integrated regional mean

MODEL COLORS
Data not available
REGIONAL MEAN
Data not available
ANNUAL CYCLE
Data not available
MONTHLY ANOMALY
Data not available
ANNUAL CYCLE
Data not available

All Models

Benchmark
Data not available
Data not available
ACCESS-ESM1-5
Data not available
Data not available
BCC-CSM2-MR
Data not available
Data not available
BGCLND
Data not available
Data not available
BGCLNDATM_progCO2
Data not available
Data not available
CanESM5
Data not available
Data not available
CNRM-ESM2-1
Data not available
Data not available
EC-Earth3-CC
Data not available
Data not available
MeanCMIP6
Data not available
Data not available
MIROC-ES2L
Data not available
Data not available
MPI-ESM1-2-LR
Data not available
Data not available
MRI-ESM2-0
Data not available
Data not available
NorESM2-LM
Data not available
Data not available
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