Mean State

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Period Mean (original grids) [1]
Model Period Mean (intersection) [1]
Benchmark Period Mean (intersection) [1]
Model Period Mean (complement) [1]
Benchmark Period Mean (complement) [1]
Bias [1]
Phase Shift [months]
Bias Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 0.521
ACCESS-ESM1-5 [-] 0.604 0.623 0.521 0.546 0.421 0.103 1.98 0.370 0.678 0.886 0.645
CESM2 [-] 0.525 0.531 0.521 0.508 0.452 0.0111 1.61 0.491 0.761 0.951 0.734
ENSEMBLE-CMIP6 [-] 0.571 0.586 0.521 0.525 0.422 0.0650 1.83 0.479 0.711 0.965 0.718
NorESM2-LM [-] 0.524 0.534 0.521 0.494 0.433 0.0137 1.60 0.465 0.763 0.937 0.722
UKESM1-0-LL [-] 0.565 0.578 0.521 0.528 0.422 0.0579 1.49 0.394 0.777 0.864 0.678

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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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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CESM2
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ENSEMBLE-CMIP6
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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-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