Mean State

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Period Mean (original grids) [g m-2 d-1]
Bias [g m-2 d-1]
RMSE [g m-2 d-1]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Overall Score [1]
Benchmark [-] -1.08
ACCESS-ESM1-5 [-] -0.756 0.327 1.62 3.06 0.394 0.254 0.684 0.396
BCC-CSM2-MR [-] -0.374 0.709 1.99 3.54 0.302 0.183 0.661 0.332
BGCLND [-] -0.115 0.968 1.85 2.55 0.280 0.243 0.716 0.371
BGCLNDATM_progCO2 [-] 0.0153 1.10 1.89 2.55 0.247 0.331 0.716 0.406
CanESM5 [-] -0.00364 1.08 2.14 2.04 0.248 0.138 0.903 0.357
CNRM-ESM2-1 [-] -0.0946 0.988 1.82 3.54 0.276 0.297 0.473 0.336
EC-Earth3-CC [-] -0.323 0.760 1.64 2.02 0.320 0.252 0.561 0.346
MeanCMIP6 [-] -1.37 -0.291 1.45 1.53 0.606 0.295 0.772 0.492
MIROC-ES2L [-] -0.497 0.586 1.37 2.02 0.440 0.293 0.561 0.397
MPI-ESM1-2-LR [-]
MRI-ESM2-0 [-] -0.0508 1.03 1.67 3.52 0.264 0.262 0.293 0.270
NorESM2-LM [-] -0.269 0.814 1.69 5.57 0.314 0.315 0.00818 0.238
UKESM1-0-LL [-] 0.00232 1.09 1.78 2.03 0.249 0.316 0.877 0.439
Download Data
Period Mean (original grids) [g m-2 d-1]
Bias [g m-2 d-1]
RMSE [g m-2 d-1]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Overall Score [1]
Benchmark [-] -2.71
ACCESS-ESM1-5 [-] -2.07 0.644 0.939 0.00 0.331 0.334 1.00 0.500
BCC-CSM2-MR [-] -0.452 2.26 2.49 6.05 0.0207 0.135 7.41e-05 0.0725
BGCLND [-] -0.208 2.50 2.73 4.02 0.0136 0.171 0.259 0.154
BGCLNDATM_progCO2 [-] -0.422 2.29 2.32 3.00 0.0197 0.233 0.511 0.249
CanESM5 [-] 0.0721 2.78 3.03 2.03 0.00843 0.0823 0.749 0.230
CNRM-ESM2-1 [-] -0.0307 2.68 2.78 3.00 0.0101 0.254 0.511 0.257
EC-Earth3-CC [-] -0.475 2.24 2.57 0.983 0.0215 0.0347 0.937 0.257
MeanCMIP6 [-] 0.454 3.16 3.33 4.02 0.00438 0.264 0.259 0.198
MIROC-ES2L [-] -0.328 2.38 2.58 4.02 0.0167 0.181 0.259 0.159
MPI-ESM1-2-LR [-] -0.583 2.13 2.34 5.10 0.0259 0.138 0.0631 0.0912
MRI-ESM2-0 [-] 0.241 2.95 2.97 0.00 0.00631 0.296 1.00 0.399
NorESM2-LM [-] -0.356 2.36 2.47 3.05 0.0176 0.210 0.498 0.234
UKESM1-0-LL [-] -0.649 2.06 2.48 6.05 0.0291 0.0716 7.41e-05 0.0431
Download Data
Period Mean (original grids) [g m-2 d-1]
Bias [g m-2 d-1]
RMSE [g m-2 d-1]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Overall Score [1]
Benchmark [-] -0.666
ACCESS-ESM1-5 [-] -0.379 0.294 1.68 1.89 0.540 0.407 0.781 0.534
BCC-CSM2-MR [-] -0.0639 0.603 1.95 2.34 0.429 0.337 0.627 0.433
BGCLND [-] -0.122 0.546 1.90 2.03 0.447 0.387 0.797 0.504
BGCLNDATM_progCO2 [-] -0.0806 0.587 1.92 1.96 0.432 0.384 0.827 0.507
CanESM5 [-] -0.0296 0.637 1.98 2.19 0.416 0.357 0.740 0.468
CNRM-ESM2-1 [-] -0.158 0.509 1.76 1.98 0.465 0.400 0.694 0.490
EC-Earth3-CC [-] -0.378 0.288 1.85 1.95 0.541 0.349 0.645 0.471
MeanCMIP6 [-] -0.549 0.118 1.66 1.82 0.594 0.419 0.792 0.556
MIROC-ES2L [-] -0.292 0.374 1.80 1.84 0.512 0.395 0.759 0.515
MPI-ESM1-2-LR [-] -0.192 0.469 1.89 1.81 0.473 0.391 0.688 0.486
MRI-ESM2-0 [-] -0.178 0.489 1.93 2.26 0.461 0.363 0.576 0.441
NorESM2-LM [-] -0.185 0.481 1.69 2.03 0.474 0.423 0.790 0.527
UKESM1-0-LL [-] -0.137 0.524 1.81 2.27 0.457 0.379 0.579 0.449
Download Data
Period Mean (original grids) [g m-2 d-1]
Bias [g m-2 d-1]
RMSE [g m-2 d-1]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Overall Score [1]
Benchmark [-] -0.408
ACCESS-ESM1-5 [-] -0.226 0.182 1.36 1.29 0.731 0.462 0.862 0.629
BCC-CSM2-MR [-] -0.0298 0.375 1.54 2.09 0.631 0.379 0.688 0.519
BGCLND [-] -0.0463 0.357 1.47 1.47 0.618 0.479 0.818 0.599
BGCLNDATM_progCO2 [-] -0.0429 0.360 1.48 1.37 0.619 0.492 0.832 0.609
CanESM5 [-] -0.0332 0.375 1.58 1.29 0.623 0.426 0.833 0.577
CNRM-ESM2-1 [-] -0.138 0.270 1.33 1.39 0.680 0.483 0.832 0.620
EC-Earth3-CC [-] -0.367 0.0414 1.39 1.52 0.806 0.459 0.818 0.636
MeanCMIP6 [-] -0.568 -0.160 1.37 1.11 0.856 0.497 0.864 0.678
MIROC-ES2L [-] -0.312 0.0965 1.54 1.47 0.779 0.468 0.827 0.636
MPI-ESM1-2-LR [-] -0.191 0.232 1.43 1.10 0.701 0.478 0.843 0.625
MRI-ESM2-0 [-] -0.317 0.0912 1.51 1.76 0.718 0.466 0.715 0.591
NorESM2-LM [-] -0.215 0.193 1.34 1.37 0.729 0.492 0.819 0.633
UKESM1-0-LL [-] -0.176 0.232 1.41 2.13 0.708 0.478 0.786 0.612
Download Data
Period Mean (original grids) [g m-2 d-1]
Bias [g m-2 d-1]
RMSE [g m-2 d-1]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Overall Score [1]
Benchmark [-] -0.355
ACCESS-ESM1-5 [-] -1.39 -1.04 2.03 4.08 0.369 0.185 0.346 0.271
BCC-CSM2-MR [-] -0.294 0.0611 1.49 3.74 0.904 0.228 0.316 0.419
BGCLND [-] -0.288 0.0664 1.46 4.08 0.823 0.257 0.245 0.396
BGCLNDATM_progCO2 [-] -0.157 0.198 1.36 3.40 0.727 0.262 0.392 0.411
CanESM5 [-] -0.0140 0.341 1.37 4.08 0.676 0.259 0.244 0.359
CNRM-ESM2-1 [-] -0.0846 0.270 1.91 3.40 0.726 0.161 0.452 0.375
EC-Earth3-CC [-] -0.293 0.0621 1.64 4.42 0.775 0.258 0.169 0.365
MeanCMIP6 [-] -0.285 0.0697 1.50 4.08 0.887 0.232 0.244 0.399
MIROC-ES2L [-] -0.107 0.247 1.28 2.04 0.731 0.293 0.747 0.516
MPI-ESM1-2-LR [-] -0.214 0.141 2.03 4.08 0.761 0.180 0.345 0.367
MRI-ESM2-0 [-] -0.106 0.248 1.93 4.76 0.756 0.151 0.138 0.299
NorESM2-LM [-] -0.188 0.167 1.03 1.36 0.797 0.376 0.855 0.601
UKESM1-0-LL [-] 0.0703 0.425 1.85 3.74 0.613 0.170 0.347 0.325
Download Data
Period Mean (original grids) [g m-2 d-1]
Bias [g m-2 d-1]
RMSE [g m-2 d-1]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Overall Score [1]
Benchmark [-] -0.664
ACCESS-ESM1-5 [-] -0.348 0.326 1.76 1.75 0.598 0.439 0.836 0.578
BCC-CSM2-MR [-] -0.0603 0.604 2.10 2.35 0.495 0.355 0.629 0.459
BGCLND [-] -0.111 0.555 1.91 1.84 0.509 0.444 0.844 0.560
BGCLNDATM_progCO2 [-] -0.0664 0.599 1.96 1.62 0.494 0.443 0.885 0.566
CanESM5 [-] -0.0345 0.630 2.06 1.86 0.487 0.400 0.788 0.519
CNRM-ESM2-1 [-] -0.166 0.498 1.82 1.89 0.537 0.438 0.735 0.537
EC-Earth3-CC [-] -0.414 0.250 1.93 1.83 0.620 0.387 0.716 0.527
MeanCMIP6 [-] -0.652 0.0116 1.75 1.66 0.688 0.456 0.858 0.615
MIROC-ES2L [-] -0.381 0.283 1.92 1.71 0.608 0.420 0.823 0.568
MPI-ESM1-2-LR [-] -0.216 0.464 1.96 1.62 0.536 0.419 0.804 0.544
MRI-ESM2-0 [-] -0.223 0.442 2.05 2.18 0.545 0.390 0.622 0.487
NorESM2-LM [-] -0.218 0.446 1.77 1.76 0.553 0.457 0.819 0.571
UKESM1-0-LL [-] -0.164 0.500 1.90 2.32 0.532 0.416 0.635 0.500

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
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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
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BGCLND
Data not available
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BGCLNDATM_progCO2
Data not available
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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
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NorESM2-LM
Data not available
Data not available
UKESM1-0-LL
Data not available
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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: NEE_VUT_REF