Mean State

Download Data
Period Mean (original grids) [watt/m2]
Model Period Mean (intersection) [watt/m2]
Benchmark Period Mean (intersection) [watt/m2]
Model Period Mean (complement) [watt/m2]
Benchmark Period Mean (complement) [watt/m2]
Bias [watt/m2]
RMSE [watt/m2]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 76.3
ACCESS-ESM1-5 [-] 94.1 94.1 76.3 101. 17.8 28.8 2.05 0.374 0.505 0.723 0.835 0.589
BCC-CSM2-MR [-] 80.8 79.7 76.9 121. 3.42 19.5 2.22 0.610 0.562 0.685 0.954 0.675
BGCLND [-] 71.4 71.0 76.3 81.0 -5.35 16.1 1.63 0.655 0.579 0.744 0.939 0.699
BGCLNDATM_progCO2 [-] 78.2 77.6 76.3 95.2 1.24 16.1 1.40 0.669 0.567 0.802 0.994 0.720
CanESM5 [-] 88.4 88.2 76.3 104. 12.3 28.9 2.63 0.440 0.420 0.589 0.818 0.537
CNRM-ESM2-1 [-] 55.2 52.6 76.3 95.6 -22.5 36.6 3.23 0.375 0.395 0.457 0.792 0.483
EC-Earth3-CC [-] 94.6 74.7 76.3 116. -1.17 26.0 2.28 0.569 0.402 0.657 0.858 0.577
MeanCMIP6 [-] 74.8 73.2 76.3 94.0 -2.99 16.7 2.16 0.685 0.562 0.662 0.985 0.691
MIROC-ES2L [-] 103. 104. 76.3 108. 27.7 35.1 2.43 0.306 0.498 0.574 0.858 0.547
MPI-ESM1-2-LR [-] 80.5 77.6 76.3 72.5 2.46 32.2 2.30 0.441 0.428 0.637 0.595 0.506
MRI-ESM2-0 [-] 86.7 86.4 76.9 96.4 9.34 27.3 2.69 0.503 0.432 0.553 0.809 0.546
NorESM2-LM [-] 66.4 64.0 76.3 91.1 -11.1 24.4 2.79 0.516 0.466 0.511 0.943 0.580
UKESM1-0-LL [-] 77.2 75.0 76.3 104. -0.670 22.3 2.70 0.511 0.526 0.558 0.789 0.582
Download Data
Period Mean (original grids) [watt/m2]
Model Period Mean (intersection) [watt/m2]
Benchmark Period Mean (intersection) [watt/m2]
Model Period Mean (complement) [watt/m2]
Benchmark Period Mean (complement) [watt/m2]
Bias [watt/m2]
RMSE [watt/m2]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 109.
ACCESS-ESM1-5 [-] 124. 123. 109. 127. 16.0 21.5 2.97 0.281 0.355 0.501 0.997 0.498
BCC-CSM2-MR [-] 122. 121. 109. 127. 13.9 19.6 2.77 0.361 0.367 0.546 0.968 0.522
BGCLND [-] 110. 110. 109. 111. 0.975 11.1 1.51 0.549 0.591 0.776 0.995 0.700
BGCLNDATM_progCO2 [-] 114. 113. 109. 115. 4.14 13.0 1.66 0.464 0.481 0.763 0.994 0.636
CanESM5 [-] 120. 118. 109. 122. 11.4 17.5 2.46 0.383 0.375 0.610 0.995 0.548
CNRM-ESM2-1 [-] 98.2 96.3 109. 105. -9.66 19.0 3.24 0.307 0.378 0.449 0.909 0.484
EC-Earth3-CC [-] 121. 120. 109. 121. 11.1 22.0 2.04 0.305 0.350 0.680 0.930 0.523
MeanCMIP6 [-] 101. 99.9 109. 104. -8.51 15.4 2.36 0.322 0.481 0.629 0.592 0.501
MIROC-ES2L [-] 130. 132. 109. 126. 20.3 25.8 2.35 0.203 0.395 0.630 0.976 0.520
MPI-ESM1-2-LR [-] 127. 128. 109. 120. 17.0 28.9 2.45 0.215 0.249 0.608 0.594 0.383
MRI-ESM2-0 [-] 114. 115. 109. 109. 4.25 18.2 2.73 0.328 0.413 0.551 0.812 0.503
NorESM2-LM [-] 108. 105. 109. 115. -0.330 15.6 2.62 0.398 0.409 0.573 0.992 0.556
UKESM1-0-LL [-] 113. 112. 109. 116. 4.81 14.2 2.36 0.551 0.435 0.624 0.996 0.608
Download Data
Period Mean (original grids) [watt/m2]
Model Period Mean (intersection) [watt/m2]
Benchmark Period Mean (intersection) [watt/m2]
Model Period Mean (complement) [watt/m2]
Benchmark Period Mean (complement) [watt/m2]
Bias [watt/m2]
RMSE [watt/m2]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 48.9
ACCESS-ESM1-5 [-] 48.9 59.1 48.9 16.0 11.8 23.5 1.21 0.482 0.520 0.798 0.944 0.653
BCC-CSM2-MR [-] 41.4 49.3 48.9 15.4 2.05 18.2 1.20 0.638 0.528 0.799 0.955 0.690
BGCLND [-] 37.9 45.5 48.9 14.6 33.8 -3.43 12.6 0.862 0.713 0.638 0.874 0.989 0.770
BGCLNDATM_progCO2 [-] 45.4 53.7 48.9 20.1 33.8 4.79 15.0 0.876 0.681 0.601 0.859 0.985 0.745
CanESM5 [-] 44.0 52.0 48.9 17.9 5.85 23.9 1.41 0.525 0.463 0.763 0.919 0.626
CNRM-ESM2-1 [-] 37.7 44.3 48.9 15.8 -2.69 20.6 1.47 0.582 0.496 0.719 0.964 0.651
EC-Earth3-CC [-] 47.5 51.1 48.9 39.5 2.41 20.0 1.13 0.575 0.513 0.806 0.937 0.669
MeanCMIP6 [-] 37.4 44.1 48.9 16.5 -3.52 17.7 1.11 0.625 0.556 0.809 0.980 0.705
MIROC-ES2L [-] 55.9 65.9 48.9 25.4 18.4 27.6 1.32 0.400 0.531 0.759 0.865 0.617
MPI-ESM1-2-LR [-] 41.7 51.4 48.9 9.26 5.16 23.7 1.20 0.491 0.491 0.779 0.900 0.630
MRI-ESM2-0 [-] 46.2 55.6 48.9 14.8 7.75 20.6 1.18 0.556 0.531 0.800 0.940 0.671
NorESM2-LM [-] 39.0 45.6 48.9 16.8 -1.16 18.3 1.21 0.607 0.549 0.787 0.963 0.691
UKESM1-0-LL [-] 41.4 49.6 48.9 14.3 2.76 18.5 1.17 0.587 0.557 0.790 0.930 0.684
Download Data
Period Mean (original grids) [watt/m2]
Model Period Mean (intersection) [watt/m2]
Benchmark Period Mean (intersection) [watt/m2]
Model Period Mean (complement) [watt/m2]
Benchmark Period Mean (complement) [watt/m2]
Bias [watt/m2]
RMSE [watt/m2]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 25.2
ACCESS-ESM1-5 [-] 34.0 37.6 25.2 13.3 11.9 17.1 0.654 0.659 0.713 0.931 0.821 0.768
BCC-CSM2-MR [-] 22.2 24.5 25.2 9.54 -0.834 12.7 0.655 0.879 0.686 0.935 0.923 0.822
BGCLND [-] 20.8 22.8 25.2 9.12 26.3 -2.40 9.50 0.439 0.880 0.763 0.970 0.990 0.873
BGCLNDATM_progCO2 [-] 25.6 27.5 25.2 14.4 26.3 2.32 10.0 0.456 0.870 0.755 0.968 0.936 0.857
CanESM5 [-] 24.1 26.4 25.2 11.9 1.02 14.3 0.805 0.859 0.650 0.914 0.880 0.791
CNRM-ESM2-1 [-] 25.7 27.7 25.2 14.1 2.60 11.7 0.614 0.850 0.718 0.949 0.984 0.844
EC-Earth3-CC [-] 29.6 25.3 25.2 33.5 0.120 12.1 0.664 0.856 0.715 0.936 0.881 0.821
MeanCMIP6 [-] 18.2 19.5 25.2 10.7 -5.65 15.7 0.618 0.809 0.621 0.942 0.989 0.796
MIROC-ES2L [-] 32.8 35.7 25.2 20.0 10.2 17.1 0.745 0.694 0.693 0.923 0.661 0.733
MPI-ESM1-2-LR [-] 28.4 31.5 25.2 10.1 6.01 12.2 0.558 0.775 0.778 0.944 0.803 0.815
MRI-ESM2-0 [-] 28.2 30.8 25.2 12.5 5.49 13.2 0.686 0.808 0.718 0.936 0.838 0.804
NorESM2-LM [-] 20.7 21.9 25.2 9.99 -3.38 13.7 0.698 0.859 0.674 0.932 0.920 0.812
UKESM1-0-LL [-] 23.8 25.6 25.2 10.7 0.388 11.6 0.621 0.896 0.705 0.941 0.958 0.841
Download Data
Period Mean (original grids) [watt/m2]
Model Period Mean (intersection) [watt/m2]
Benchmark Period Mean (intersection) [watt/m2]
Model Period Mean (complement) [watt/m2]
Benchmark Period Mean (complement) [watt/m2]
Bias [watt/m2]
RMSE [watt/m2]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 99.9
ACCESS-ESM1-5 [-] 108. 109. 99.9 98.4 8.81 31.2 1.88 0.263 0.250 0.721 0.884 0.473
BCC-CSM2-MR [-] 101. 101. 99.9 107. 1.41 24.0 2.06 0.459 0.217 0.699 0.991 0.517
BGCLND [-] 99.6 99.8 99.9 91.5 -0.0352 12.0 0.979 0.584 0.492 0.878 0.983 0.686
BGCLNDATM_progCO2 [-] 104. 104. 99.9 102. 4.45 15.0 1.87 0.591 0.432 0.702 0.925 0.616
CanESM5 [-] 87.1 86.9 99.9 93.5 -12.5 43.2 2.27 0.223 0.121 0.652 0.784 0.380
CNRM-ESM2-1 [-] 90.9 90.9 99.9 89.3 -8.73 22.5 2.93 0.447 0.266 0.512 0.866 0.471
EC-Earth3-CC [-] 99.7 98.9 99.9 109. -1.13 32.0 2.24 0.270 0.239 0.636 0.775 0.432
MeanCMIP6 [-] 89.3 89.3 99.9 90.6 -10.7 19.8 2.11 0.358 0.379 0.681 0.951 0.550
MIROC-ES2L [-] 132. 132. 99.9 116. 32.0 38.3 2.51 0.115 0.364 0.602 0.960 0.481
MPI-ESM1-2-LR [-] 104. 105. 99.9 51.0 5.13 36.1 2.44 0.204 0.210 0.599 0.631 0.370
MRI-ESM2-0 [-] 122. 123. 99.9 90.1 22.4 31.6 1.51 0.157 0.341 0.784 0.806 0.486
NorESM2-LM [-] 96.0 95.4 99.9 104. -4.06 15.9 1.62 0.407 0.421 0.775 0.723 0.549
UKESM1-0-LL [-] 109. 109. 99.9 107. 9.23 24.3 2.34 0.309 0.305 0.617 0.983 0.504
Download Data
Period Mean (original grids) [watt/m2]
Model Period Mean (intersection) [watt/m2]
Benchmark Period Mean (intersection) [watt/m2]
Model Period Mean (complement) [watt/m2]
Benchmark Period Mean (complement) [watt/m2]
Bias [watt/m2]
RMSE [watt/m2]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 31.9
ACCESS-ESM1-5 [-] 43.7 44.1 31.9 41.0 12.6 19.1 0.772 0.640 0.671 0.908 0.871 0.752
BCC-CSM2-MR [-] 31.7 31.6 31.9 33.4 0.425 13.7 0.720 0.838 0.666 0.913 0.940 0.805
BGCLND [-] 28.3 28.2 31.9 29.2 35.3 -3.62 10.6 0.525 0.835 0.733 0.959 0.990 0.850
BGCLNDATM_progCO2 [-] 35.7 35.2 31.9 40.7 35.3 3.31 12.1 0.553 0.827 0.706 0.954 0.969 0.832
CanESM5 [-] 32.9 33.3 31.9 30.5 2.60 16.7 0.961 0.784 0.621 0.876 0.836 0.748
CNRM-ESM2-1 [-] 33.1 32.8 31.9 36.2 2.06 14.1 0.723 0.799 0.668 0.928 0.896 0.792
EC-Earth3-CC [-] 52.5 32.6 31.9 74.3 0.904 14.3 0.726 0.786 0.681 0.921 0.765 0.767
MeanCMIP6 [-] 25.8 25.3 31.9 30.5 -5.91 16.4 0.697 0.770 0.613 0.915 0.985 0.779
MIROC-ES2L [-] 44.6 44.5 31.9 46.8 13.3 20.8 0.804 0.622 0.650 0.898 0.724 0.709
MPI-ESM1-2-LR [-] 36.2 37.5 31.9 22.9 6.59 16.7 0.691 0.713 0.682 0.916 0.809 0.760
MRI-ESM2-0 [-] 38.4 39.4 31.9 28.6 7.99 16.3 0.690 0.734 0.675 0.927 0.870 0.776
NorESM2-LM [-] 29.1 28.3 31.9 31.1 -2.52 14.6 0.664 0.796 0.665 0.926 0.892 0.789
UKESM1-0-LL [-] 31.4 31.9 31.9 28.9 0.914 13.3 0.687 0.823 0.684 0.923 0.916 0.806

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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SPATIAL TAYLOR DIAGRAM
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MODEL COLORS
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Spatially integrated regional mean

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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All Models

Benchmark
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ACCESS-ESM1-5
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BCC-CSM2-MR
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BGCLND
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BGCLNDATM_progCO2
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CanESM5
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CNRM-ESM2-1
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EC-Earth3-CC
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MeanCMIP6
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MIROC-ES2L
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MPI-ESM1-2-LR
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MRI-ESM2-0
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NorESM2-LM
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UKESM1-0-LL
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Data Information

  Title:
FLUXCOM (RS+METEO) Global Land Energy Fluxes using GSWP3 climate data

  Version:
1

  Institutions:
Department Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Germany

  Source:
Data generated by machine learning to merge energy flux measurements from FLUXNET eddy covariance towers with MODIS remote sensing and GSWP3v1 meteorological data (RS+METEO)

  History:
2019-05-07: downloaded source from doi:10.17871/FLUXCOM_EnergyFluxes_v1
2019-06-28: converted to netCDF with https://github.com/mmu2019/Datasets/blob/master/read-le-fluxcom.py

  References:
Jung, M., S. Koirala, U. Weber, K. Ichii, F. Gans, G. Camps-Valls, D. Papale, C. Schwalm, G. Tramontana, M. Reichstein (2019), The FLUXCOM ensemble of global land-atmosphere energy fluxes, Scientific Data, submitted, 1-12, https://arxiv.org/abs/1812.04951

Tramontana, G., M. Jung, C.R. Schwalm, K. Ichii, G. Camps-Valls, B. Raduly, M. Reichstein, M.A. Arain, A. Cescatti, G. Kiely, L. Merbold, P. Serrano-Ortiz, S. Sickert, S. Wolf, and D. Papale (2016), Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms, Biogeosciences, 13, 4291-4313, doi:10.5194/bg-13-4291-2016

  Comments:
time_period: 1980-01 through 2014-12
original_temporal_resolution: monthly
original_spatial_resolution: 0.5 degree
original_units: MJ/m2/day
final_temporal_resolution: monthly
final_spatial_resolution: 0.5 degree
final_units: watt/m2

  Convention:
CF-1.7