Global - Land
CLM-CRUJRA
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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 [-] 31.2
CLM-CRUJRA [-] 36.8 6.16 27.4 0.977 0.659 0.438 0.896 0.608
CLM-GSWP3 [-] 31.6 0.964 24.4 0.972 0.672 0.450 0.893 0.616
CLM-Princeton [-] 32.2 0.879 25.0 1.01 0.640 0.428 0.862 0.589
ISBA-CTRIP-CRUJRA [-] 39.0 8.43 28.0 1.09 0.669 0.417 0.876 0.595
ISBA-CTRIP-GSWP3 [-] 35.7 5.04 28.0 0.997 0.631 0.407 0.893 0.584
ISBA-CTRIP-Princeton [-] 37.4 6.05 27.4 1.07 0.626 0.399 0.863 0.571
JSBACH-CRUJRA [-] 26.5 -3.88 30.8 1.09 0.617 0.363 0.873 0.554
JSBACH-GSWP3 [-] 23.5 -6.84 33.5 1.17 0.548 0.360 0.862 0.533
JSBACH-Princeton [-] 23.3 -7.08 33.0 1.09 0.583 0.346 0.872 0.537
Mean-CRUJRA [-] 34.5 3.89 25.7 1.05 0.695 0.441 0.883 0.615
Mean-GSWP3 [-] 31.7 1.07 25.7 0.952 0.660 0.438 0.894 0.607
Mean-Princeton [-] 32.1 0.582 25.0 1.06 0.664 0.418 0.869 0.592

Temporally integrated period mean click to collapse contents

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 click to collapse contents

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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SensibleHeat / FLUXNET2015 / 1991-2015 / global / MNAME

Benchmark
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CLM-CRUJRA
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CLM-GSWP3
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CLM-Princeton
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ISBA-CTRIP-CRUJRA
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ISBA-CTRIP-GSWP3
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ISBA-CTRIP-Princeton
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JSBACH-CRUJRA
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JSBACH-GSWP3
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JSBACH-Princeton
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Mean-CRUJRA
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Mean-GSWP3
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Mean-Princeton
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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: H_F_MDS

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