Global - Land
bcc-csm1-1
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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 [-] 156.
bcc-csm1-1 [-] 162. -6.42 33.2 0.622 0.375 0.0195 0.952 0.342
BCC-CSM2-MR [-] 167. -1.40 32.4 0.544 0.489 0.0446 0.961 0.385
CanESM2 [-] 184. 18.4 35.7 0.481 0.198 0.0815 0.963 0.331
CanESM5 [-] 179. 13.0 29.8 0.457 0.348 0.113 0.969 0.386
CESM1-BGC [-] 179. 15.5 31.9 0.339 0.266 0.109 0.976 0.365
CESM2 [-] 175. 8.94 28.2 0.449 0.384 0.131 0.965 0.403
GFDL-ESM2G [-] 170. 2.37 28.2 0.276 0.493 0.0847 0.979 0.410
GFDL-ESM4 [-] 166. -1.70 26.2 0.354 0.561 0.134 0.977 0.451
IPSL-CM5A-LR [-] 184. 16.0 42.0 0.630 0.189 0.0313 0.955 0.301
IPSL-CM6A-LR [-] 173. 8.00 32.8 0.552 0.356 0.0495 0.959 0.354
MeanCMIP5 [-] 176. 8.08 25.1 0.400 0.369 0.241 0.967 0.454
MeanCMIP6 [-] 173. 6.37 22.4 0.370 0.493 0.287 0.975 0.510
MIROC-ESM [-] 182. 17.2 37.0 0.442 0.246 0.0469 0.963 0.326
MIROC-ESM2L [-] 173. 5.60 27.2 0.371 0.472 0.117 0.974 0.420
MPI-ESM-LR [-] 167. -0.467 31.0 0.284 0.445 0.0654 0.977 0.388
MPI-ESM1.2-HR [-] 173. 4.86 28.3 0.378 0.481 0.102 0.967 0.413
NorESM1-ME [-] 170. 5.65 27.7 0.441 0.424 0.116 0.970 0.406
NorESM2-LM [-] 174. 8.38 30.6 0.489 0.403 0.0930 0.966 0.389
UK-HadGEM2-ES [-] 184. 16.2 33.6 0.586 0.246 0.0801 0.958 0.341
UKESM1-0-LL [-] 178. 11.6 29.1 0.457 0.338 0.109 0.969 0.381

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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SurfaceDownwardSWRadiation / FLUXNET2015 / 1991-2015 / global / MNAME

Benchmark
Data not available
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bcc-csm1-1
Data not available
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BCC-CSM2-MR
Data not available
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CanESM2
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CanESM5
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CESM1-BGC
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CESM2
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GFDL-ESM2G
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GFDL-ESM4
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IPSL-CM5A-LR
Data not available
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IPSL-CM6A-LR
Data not available
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MeanCMIP5
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MeanCMIP6
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MIROC-ESM
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MIROC-ESM2L
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MPI-ESM-LR
Data not available
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MPI-ESM1.2-HR
Data not available
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NorESM1-ME
Data not available
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NorESM2-LM
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UK-HadGEM2-ES
Data not available
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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

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