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Bias Score [1] |
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Overall Score [1] |
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Benchmark | [-] | 26.3 | ||||||||||||||
CLM4 | [-] | 34.8 | 33.6 | 60.7 | 26.4 | 16.7 | 8.49 | 18.8 | 0.591 | 0.61 | 0.35 | 0.94 | 0.92 | 0.63 | ||
CLM4.5 | [-] | 34.2 | 33.1 | 58.5 | 26.4 | 16.7 | 7.84 | 19.1 | 0.619 | 0.62 | 0.34 | 0.93 | 0.95 | 0.64 | ||
CLM5 | [-] | 31.9 | 31.0 | 52.1 | 26.4 | 16.7 | 6.02 | 16.8 | 0.705 | 0.67 | 0.40 | 0.93 | 0.92 | 0.66 |
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Benchmark | [-] | 21.5 | ||||||||||||||
CLM4 | [-] | 16.9 | 16.9 | 15.9 | 21.7 | 3.43 | -4.89 | 12.3 | 0.180 | 0.80 | 0.69 | 0.99 | 0.92 | 0.82 | ||
CLM4.5 | [-] | 21.1 | 21.2 | 16.7 | 21.7 | 3.43 | -0.643 | 10.3 | 0.285 | 0.89 | 0.70 | 0.98 | 0.98 | 0.85 | ||
CLM5 | [-] | 21.2 | 21.3 | 16.5 | 21.7 | 3.43 | -0.545 | 11.8 | 0.217 | 0.89 | 0.66 | 0.99 | 0.95 | 0.83 |
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Benchmark | [-] | 17.2 | ||||||||||||||
CLM4 | [-] | 16.5 | 17.1 | 7.58 | 17.5 | 2.66 | -0.686 | 11.6 | 0.153 | 0.79 | 0.66 | 1.0 | 0.93 | 0.81 | ||
CLM4.5 | [-] | 22.3 | 23.0 | 9.54 | 17.5 | 2.66 | 5.00 | 13.7 | 0.193 | 0.78 | 0.59 | 1.0 | 0.95 | 0.78 | ||
CLM5 | [-] | 20.4 | 21.2 | 7.03 | 17.5 | 2.66 | 3.09 | 13.3 | 0.302 | 0.83 | 0.57 | 0.99 | 0.96 | 0.78 |
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Benchmark | [-] | 51.8 | ||||||||||||||
CLM4 | [-] | 62.9 | 62.2 | 70.1 | 52.7 | 19.3 | 11.1 | 26.1 | 0.964 | 0.51 | 0.31 | 0.88 | 0.96 | 0.59 | ||
CLM4.5 | [-] | 62.6 | 61.9 | 69.9 | 52.7 | 19.3 | 10.9 | 26.8 | 1.03 | 0.51 | 0.29 | 0.86 | 0.95 | 0.58 | ||
CLM5 | [-] | 57.7 | 56.9 | 65.5 | 52.7 | 19.3 | 5.82 | 20.4 | 0.849 | 0.55 | 0.41 | 0.90 | 0.97 | 0.65 |
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Benchmark | [-] | 22.7 | ||||||||||||||
CLM4 | [-] | 25.9 | 26.1 | 19.5 | 22.8 | 12.1 | 3.64 | 13.2 | 0.717 | 0.76 | 0.59 | 0.95 | 0.97 | 0.77 | ||
CLM4.5 | [-] | 26.0 | 26.3 | 18.2 | 22.8 | 12.1 | 3.88 | 13.6 | 0.748 | 0.77 | 0.58 | 0.95 | 0.97 | 0.77 | ||
CLM5 | [-] | 23.4 | 23.7 | 15.9 | 22.8 | 12.1 | 1.20 | 13.8 | 0.727 | 0.76 | 0.57 | 0.94 | 0.94 | 0.76 |
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Benchmark | [-] | 74.5 | ||||||||||||||
CLM4 | [-] | 131. | 133. | 123. | 78.7 | 30.8 | 51.9 | 55.8 | 2.38 | 0.019 | 0.051 | 0.62 | 0.60 | 0.27 | ||
CLM4.5 | [-] | 108. | 108. | 107. | 78.7 | 30.8 | 29.8 | 35.6 | 2.32 | 0.18 | 0.11 | 0.63 | 0.33 | 0.27 | ||
CLM5 | [-] | 95.2 | 94.8 | 97.9 | 78.7 | 30.8 | 16.8 | 26.9 | 2.17 | 0.26 | 0.17 | 0.66 | 0.26 | 0.31 |
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Benchmark | [-] | 30.9 | ||||||||||||||
CLM4 | [-] | 34.8 | 34.9 | 36.9 | 31.6 | 7.59 | 3.47 | 15.3 | 0.469 | 0.80 | 0.62 | 0.97 | 0.96 | 0.79 | ||
CLM4.5 | [-] | 36.3 | 36.4 | 37.9 | 31.6 | 7.59 | 4.84 | 15.5 | 0.463 | 0.81 | 0.60 | 0.97 | 0.82 | 0.76 | ||
CLM5 | [-] | 33.3 | 33.4 | 34.0 | 31.6 | 7.59 | 1.83 | 15.6 | 0.346 | 0.79 | 0.60 | 0.98 | 0.70 | 0.73 |
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Period Mean (original grids) [W/m2] |
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Benchmark | [-] | 39.1 | ||||||||||||||
CLM4 | [-] | 38.9 | 46.5 | 8.21 | 39.4 | 16.4 | 7.49 | 20.0 | 0.929 | 0.52 | 0.37 | 0.84 | 0.92 | 0.60 | ||
CLM4.5 | [-] | 36.4 | 43.3 | 8.27 | 39.4 | 16.4 | 4.38 | 18.0 | 0.924 | 0.58 | 0.38 | 0.85 | 0.97 | 0.63 | ||
CLM5 | [-] | 33.9 | 40.2 | 7.50 | 39.4 | 16.4 | 1.20 | 16.5 | 0.894 | 0.61 | 0.42 | 0.85 | 0.97 | 0.66 |
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Benchmark | [-] | 10.8 | ||||||||||||||
CLM4 | [-] | 10.2 | 17.2 | 3.31 | 10.9 | 7.29 | 6.97 | 13.7 | 1.44 | 0.55 | 0.33 | 0.91 | 0.94 | 0.61 | ||
CLM4.5 | [-] | 10.2 | 17.1 | 3.57 | 10.9 | 7.29 | 6.96 | 14.0 | 1.51 | 0.55 | 0.32 | 0.90 | 0.94 | 0.61 | ||
CLM5 | [-] | 9.95 | 16.7 | 3.35 | 10.9 | 7.29 | 6.53 | 14.5 | 1.02 | 0.57 | 0.26 | 0.94 | 0.94 | 0.60 |
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Benchmark | [-] | 48.2 | ||||||||||||||
CLM4 | [-] | 52.9 | 58.6 | 8.84 | 48.3 | 16.9 | 10.1 | 25.3 | 1.60 | 0.51 | 0.30 | 0.68 | 0.97 | 0.55 | ||
CLM4.5 | [-] | 46.3 | 51.1 | 8.40 | 48.3 | 16.9 | 2.68 | 22.7 | 1.48 | 0.58 | 0.32 | 0.73 | 0.98 | 0.59 | ||
CLM5 | [-] | 43.6 | 48.3 | 7.84 | 48.3 | 16.9 | -0.121 | 20.5 | 1.41 | 0.57 | 0.35 | 0.75 | 0.97 | 0.60 |
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Benchmark | [-] | 84.4 | ||||||||||||||
CLM4 | [-] | 113. | 113. | 95.8 | 84.8 | 26.5 | 26.3 | 36.9 | 2.44 | 0.11 | 0.063 | 0.61 | 0.93 | 0.35 | ||
CLM4.5 | [-] | 95.6 | 95.2 | 92.5 | 84.8 | 26.5 | 9.80 | 24.4 | 2.38 | 0.27 | 0.094 | 0.62 | 0.97 | 0.41 | ||
CLM5 | [-] | 91.2 | 91.0 | 88.5 | 84.8 | 26.5 | 5.57 | 17.5 | 2.71 | 0.39 | 0.16 | 0.56 | 0.88 | 0.43 |
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Benchmark | [-] | 59.2 | ||||||||||||||
CLM4 | [-] | 67.2 | 66.7 | 81.8 | 60.2 | 25.2 | 7.75 | 23.6 | 1.10 | 0.63 | 0.42 | 0.85 | 0.97 | 0.66 | ||
CLM4.5 | [-] | 59.4 | 58.7 | 76.2 | 60.2 | 25.2 | -0.192 | 22.6 | 1.02 | 0.62 | 0.44 | 0.87 | 0.97 | 0.67 | ||
CLM5 | [-] | 55.9 | 55.2 | 73.6 | 60.2 | 25.2 | -3.80 | 23.9 | 1.38 | 0.57 | 0.44 | 0.79 | 0.96 | 0.64 |
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Benchmark | [-] | 56.3 | ||||||||||||||
CLM4 | [-] | 62.8 | 63.9 | 55.5 | 56.4 | 24.8 | 6.96 | 23.8 | 1.24 | 0.54 | 0.33 | 0.81 | 0.96 | 0.59 | ||
CLM4.5 | [-] | 54.3 | 55.1 | 52.3 | 56.4 | 24.8 | -1.65 | 21.1 | 1.19 | 0.54 | 0.36 | 0.82 | 0.98 | 0.61 | ||
CLM5 | [-] | 51.8 | 52.5 | 47.9 | 56.4 | 24.8 | -4.25 | 20.3 | 1.26 | 0.55 | 0.39 | 0.82 | 0.98 | 0.63 |
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Benchmark | [-] | 68.6 | ||||||||||||||
CLM4 | [-] | 81.4 | 82.8 | 50.2 | 68.9 | 9.65 | 13.0 | 27.2 | 1.45 | 0.33 | 0.22 | 0.80 | 0.95 | 0.50 | ||
CLM4.5 | [-] | 71.1 | 72.0 | 49.2 | 68.9 | 9.65 | 2.46 | 21.1 | 1.38 | 0.50 | 0.25 | 0.82 | 0.99 | 0.56 | ||
CLM5 | [-] | 67.0 | 67.9 | 46.6 | 68.9 | 9.65 | -1.56 | 16.7 | 1.13 | 0.55 | 0.34 | 0.86 | 0.99 | 0.61 |
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Benchmark | [-] | 36.3 | ||||||||||||||
CLM4 | [-] | 45.4 | 45.3 | 53.6 | 36.4 | 11.8 | 9.02 | 17.4 | 0.489 | 0.69 | 0.60 | 0.96 | 0.93 | 0.76 | ||
CLM4.5 | [-] | 44.4 | 44.3 | 46.2 | 36.4 | 11.8 | 8.07 | 17.0 | 0.534 | 0.71 | 0.60 | 0.96 | 0.97 | 0.77 | ||
CLM5 | [-] | 36.6 | 36.5 | 40.4 | 36.4 | 11.8 | 0.201 | 13.7 | 0.509 | 0.81 | 0.65 | 0.96 | 0.97 | 0.81 |
_NCProperties: version=1|netcdflibversion=4.4.1|hdf5libversion=1.8.17
creation_date: Thu Dec 5 00:02:00 PST 2013
Conventions: Please contact Prof. James Randerson (Email: jranders@uci.edu) or Dr. Mingquan Mu (mmu@uci.edu) for any question
source_file: This product is generated from monthly FluxNet MTE observations
title: derived FluxNet MTE in 0.5x0.5
Approach: I read this variable from data file, and then save the data in NetCDF format by each month and each year. Meanwhile, I also converted the unit from g C m-2 day-1 to Kg C m-2 s-1.
Temporal resolution: monthly
General information: This product was derived from Fluxnet-MTE originally from Monthly estimates of global biosphere-atmosphere fluxes from Biogeochemistry group at Max Planck Institute in Jena, Germany.
Spatial resolution: 0.5x0.5 degree
Derived data code: http://redwood.ess.uci.edu/mingquan/www/ILAMB/Download/CODES/CODES/subroutines/convert/convert-FluxNet-MTE.ncl