Mean State

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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 [-] 49.7
CMIP6 ens [-] 31.3 49.1 49.7 12.4 44.7 -0.637 14.4 1.14 0.574 0.547 0.879 0.713 0.652
E3SMv3 default [-] 44.4 44.9 49.7 30.0 -4.77 19.1 1.83 0.475 0.425 0.729 0.659 0.543
E3SMv3 highECS [-] 40.7 41.2 49.7 27.4 -8.50 18.8 1.80 0.491 0.437 0.735 0.768 0.574
E3SMv3 lowECS [-] 38.3 38.9 49.7 22.7 -10.8 20.7 1.54 0.416 0.466 0.788 0.646 0.557
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 [-] 35.3
CMIP6 ens [-] 15.0 22.9 35.3 12.7 -12.3 13.3 1.57 0.266 0.637 0.776 0.842 0.631
E3SMv3 default [-] 25.1 27.2 35.3 20.9 -8.13 13.0 2.01 0.412 0.488 0.700 0.852 0.588
E3SMv3 highECS [-] 22.5 23.5 35.3 20.3 -11.7 14.7 1.74 0.299 0.526 0.742 0.888 0.596
E3SMv3 lowECS [-] 17.3 19.2 35.3 13.2 -16.1 18.3 2.21 0.224 0.491 0.656 0.832 0.539
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 [-] 40.6
CMIP6 ens [-] 30.9 37.0 40.6 16.7 41.5 -3.59 15.0 0.965 0.648 0.593 0.901 0.912 0.730
E3SMv3 default [-] 33.3 37.7 40.6 19.8 15.3 -2.94 16.5 1.01 0.616 0.555 0.889 0.884 0.700
E3SMv3 highECS [-] 32.2 36.5 40.6 19.1 15.3 -4.09 16.1 0.993 0.622 0.562 0.890 0.907 0.708
E3SMv3 lowECS [-] 31.0 35.1 40.6 18.5 15.3 -5.54 16.7 0.929 0.603 0.560 0.899 0.923 0.709
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 [-] 24.8
CMIP6 ens [-] 13.6 12.5 24.8 14.7 10.9 -12.3 19.1 0.827 0.647 0.649 0.924 0.943 0.762
E3SMv3 default [-] 11.0 13.7 24.8 -3.90 14.4 -11.1 18.0 0.744 0.680 0.637 0.931 0.894 0.756
E3SMv3 highECS [-] 11.1 13.8 24.8 -3.73 14.4 -11.0 17.5 0.721 0.679 0.651 0.932 0.916 0.766
E3SMv3 lowECS [-] 11.4 14.0 24.8 -3.55 14.4 -10.8 17.6 0.635 0.689 0.643 0.944 0.899 0.764
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 [-] 35.9
CMIP6 ens [-] 42.3 43.6 35.9 24.6 7.73 13.5 1.35 0.465 0.423 0.826 0.756 0.579
E3SMv3 default [-] 42.1 41.8 35.9 52.1 5.91 15.4 1.27 0.502 0.357 0.840 0.612 0.533
E3SMv3 highECS [-] 39.0 38.7 35.9 48.9 2.82 14.3 1.35 0.529 0.352 0.825 0.685 0.549
E3SMv3 lowECS [-] 42.3 42.0 35.9 50.1 6.15 19.0 1.20 0.403 0.279 0.849 0.486 0.459
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 [-] 30.4
CMIP6 ens [-] 23.5 23.3 30.4 23.8 29.4 -7.07 15.4 0.890 0.717 0.662 0.910 0.891 0.768
E3SMv3 default [-] 23.8 23.8 30.4 23.9 12.1 -6.62 15.5 0.892 0.716 0.643 0.916 0.894 0.762
E3SMv3 highECS [-] 23.6 23.5 30.4 23.9 12.1 -6.85 15.1 0.859 0.711 0.655 0.919 0.907 0.769
E3SMv3 lowECS [-] 23.5 23.5 30.4 23.3 12.1 -6.89 14.9 0.794 0.720 0.654 0.927 0.920 0.775

Temporally integrated period mean

BENCHMARK MEAN
Data not available
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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
Data not available
MODEL COLORS
Data not available

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
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CMIP6 ens
Data not available
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E3SMv3 default
Data not available
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E3SMv3 highECS
Data not available
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E3SMv3 lowECS
Data not available
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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-sh-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