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 [-] 139.
ACCESS-ESM1-5 [-] 219. 80.6 84.3 0.00 0.0599 0.398 1.00 0.464
BCC-CSM2-MR [-] 175. 35.8 36.5 0.983 0.286 0.415 0.937 0.513
BGCLND [-] 179. 40.6 46.9 0.983 0.242 0.496 0.937 0.543
BGCLNDATM_progCO2 [-] 183. 44.0 52.5 0.00 0.215 0.498 1.00 0.553
CanESM5 [-] 211. 72.0 78.3 0.983 0.0809 0.378 0.937 0.444
CNRM-ESM2-1 [-] 195. 56.0 57.0 0.00 0.141 0.516 1.00 0.544
EC-Earth3-CC [-] 200. 61.3 63.7 0.00 0.117 0.539 1.00 0.549
MeanCMIP6 [-] 189. 50.5 52.4 0.983 0.171 0.549 0.937 0.552
MIROC-ES2L [-] 210. 70.9 76.4 0.983 0.0840 0.490 0.937 0.500
MPI-ESM1-2-LR [-] 222. 83.3 86.7 0.00 0.0545 0.547 1.00 0.537
MRI-ESM2-0 [-] 204. 65.5 65.9 0.983 0.102 0.518 0.937 0.519
NorESM2-LM [-] 192. 53.0 54.9 0.00 0.157 0.573 1.00 0.576
UKESM1-0-LL [-] 194. 55.6 58.8 1.02 0.143 0.392 0.933 0.465
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 [-] 176.
ACCESS-ESM1-5 [-] 201. 25.8 30.4 1.02 0.198 0.363 0.933 0.464
BCC-CSM2-MR [-] 192. 15.9 25.5 1.02 0.369 0.269 0.933 0.460
BGCLND [-] 171. -5.16 13.7 0.00 0.723 0.457 1.00 0.659
BGCLNDATM_progCO2 [-] 175. -0.666 26.4 1.02 0.959 0.190 0.933 0.568
CanESM5 [-] 173. -2.55 19.8 1.02 0.852 0.298 0.933 0.595
CNRM-ESM2-1 [-] 158. -17.8 24.4 1.02 0.328 0.317 0.933 0.474
EC-Earth3-CC [-] 182. 6.81 17.3 0.00 0.652 0.358 1.00 0.592
MeanCMIP6 [-] 178. 2.66 17.8 1.02 0.846 0.327 0.933 0.608
MIROC-ES2L [-] 179. 3.68 33.7 1.02 0.794 0.124 0.933 0.493
MPI-ESM1-2-LR [-] 194. 18.3 29.0 0.00 0.317 0.244 1.00 0.451
MRI-ESM2-0 [-] 153. -22.6 31.7 1.02 0.242 0.217 0.933 0.402
NorESM2-LM [-] 185. 9.57 23.3 1.02 0.548 0.251 0.933 0.496
UKESM1-0-LL [-] 169. -7.07 21.0 1.02 0.641 0.279 0.933 0.533
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 [-] 140.
ACCESS-ESM1-5 [-] 153. 13.2 34.2 0.570 0.740 0.623 0.951 0.734
BCC-CSM2-MR [-] 139. -0.874 31.8 0.662 0.810 0.604 0.944 0.741
BGCLND [-] 138. -1.85 22.2 0.473 0.841 0.706 0.958 0.803
BGCLNDATM_progCO2 [-] 138. -1.84 28.1 0.559 0.839 0.630 0.951 0.763
CanESM5 [-] 145. 5.65 29.3 0.584 0.807 0.640 0.952 0.760
CNRM-ESM2-1 [-] 147. 6.70 29.5 0.577 0.782 0.661 0.946 0.762
EC-Earth3-CC [-] 140. 0.274 26.4 0.591 0.819 0.662 0.949 0.773
MeanCMIP6 [-] 140. 0.415 23.0 0.555 0.847 0.693 0.952 0.796
MIROC-ES2L [-] 145. 5.14 27.8 0.519 0.818 0.650 0.953 0.768
MPI-ESM1-2-LR [-] 142. 1.89 28.6 0.563 0.812 0.640 0.955 0.762
MRI-ESM2-0 [-] 135. -4.64 26.8 0.591 0.790 0.668 0.950 0.769
NorESM2-LM [-] 144. 4.40 28.8 0.569 0.807 0.640 0.948 0.759
UKESM1-0-LL [-] 140. 0.425 27.0 0.662 0.820 0.655 0.947 0.769
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 [-] 94.5
ACCESS-ESM1-5 [-] 103. 8.81 31.8 0.308 0.818 0.655 0.970 0.775
BCC-CSM2-MR [-] 87.8 -6.64 31.6 0.733 0.869 0.636 0.936 0.769
BGCLND [-] 94.4 0.0224 21.6 0.412 0.875 0.748 0.964 0.834
BGCLNDATM_progCO2 [-] 88.5 -5.91 27.2 0.460 0.886 0.669 0.958 0.795
CanESM5 [-] 96.1 1.65 26.9 0.379 0.886 0.679 0.972 0.804
CNRM-ESM2-1 [-] 109. 14.9 30.1 0.308 0.778 0.705 0.977 0.791
EC-Earth3-CC [-] 94.5 0.00874 23.8 0.473 0.876 0.714 0.955 0.815
MeanCMIP6 [-] 93.6 -0.826 21.4 0.331 0.899 0.725 0.975 0.831
MIROC-ES2L [-] 98.5 3.98 24.8 0.426 0.866 0.701 0.969 0.809
MPI-ESM1-2-LR [-] 91.4 -3.12 25.2 0.331 0.898 0.687 0.975 0.812
MRI-ESM2-0 [-] 92.3 -2.22 22.8 0.331 0.883 0.717 0.975 0.823
NorESM2-LM [-] 92.2 -2.25 26.3 0.402 0.884 0.686 0.964 0.805
UKESM1-0-LL [-] 94.9 0.443 24.7 0.450 0.892 0.692 0.965 0.811
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 [-] 175.
ACCESS-ESM1-5 [-] 229. 53.8 60.9 0.508 0.146 0.432 0.966 0.494
BCC-CSM2-MR [-] 222. 47.5 58.1 0.508 0.196 0.395 0.966 0.488
BGCLND [-] 186. 11.1 20.7 0.00 0.646 0.524 1.00 0.674
BGCLNDATM_progCO2 [-] 178. 3.09 29.7 0.00 0.805 0.317 1.00 0.610
CanESM5 [-] 219. 43.7 55.4 1.02 0.235 0.362 0.933 0.473
CNRM-ESM2-1 [-] 186. 10.7 27.4 0.00 0.655 0.383 1.00 0.605
EC-Earth3-CC [-] 204. 28.9 39.0 0.508 0.325 0.368 0.966 0.507
MeanCMIP6 [-] 206. 31.6 39.7 0.00 0.296 0.478 1.00 0.563
MIROC-ES2L [-] 180. 5.06 25.9 1.02 0.699 0.413 0.933 0.615
MPI-ESM1-2-LR [-] 207. 32.0 43.4 0.00 0.301 0.327 1.00 0.489
MRI-ESM2-0 [-] 205. 29.7 42.9 1.02 0.316 0.378 0.933 0.501
NorESM2-LM [-] 201. 26.2 35.9 0.00 0.362 0.413 1.00 0.547
UKESM1-0-LL [-] 208. 33.3 43.7 0.508 0.276 0.377 0.966 0.499
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 [-] 129.
ACCESS-ESM1-5 [-] 141. 12.1 33.9 0.393 0.789 0.665 0.972 0.773
BCC-CSM2-MR [-] 125. -3.50 31.2 0.594 0.868 0.644 0.956 0.778
BGCLND [-] 126. -2.52 21.6 0.458 0.874 0.749 0.964 0.834
BGCLNDATM_progCO2 [-] 124. -4.54 27.6 0.468 0.883 0.671 0.964 0.798
CanESM5 [-] 133. 4.68 28.3 0.453 0.847 0.691 0.969 0.799
CNRM-ESM2-1 [-] 136. 7.62 30.0 0.473 0.796 0.705 0.966 0.793
EC-Earth3-CC [-] 127. -1.31 26.4 0.503 0.852 0.701 0.962 0.804
MeanCMIP6 [-] 127. -1.07 22.7 0.503 0.886 0.731 0.962 0.828
MIROC-ES2L [-] 133. 4.11 27.2 0.423 0.858 0.694 0.968 0.803
MPI-ESM1-2-LR [-] 128. -0.764 27.2 0.413 0.866 0.691 0.972 0.805
MRI-ESM2-0 [-] 121. -7.69 25.6 0.403 0.827 0.720 0.971 0.809
NorESM2-LM [-] 134. 5.38 28.2 0.524 0.849 0.688 0.960 0.796
UKESM1-0-LL [-] 128. -0.948 27.3 0.524 0.863 0.690 0.963 0.802

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
Data not available
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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: SW_IN_F-SW_OUT