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Bias Score [1] |
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Overall Score [1] |
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Benchmark | [-] | 26.3 | ||||||||||||||
CLM4 | [-] | 34.4 | 33.2 | 60.0 | 26.4 | 16.7 | 8.24 | 19.1 | 0.570 | 0.62 | 0.34 | 0.95 | 0.87 | 0.63 | ||
CLM4.5 | [-] | 34.1 | 33.0 | 57.7 | 26.4 | 16.7 | 7.83 | 19.7 | 0.588 | 0.63 | 0.33 | 0.95 | 0.91 | 0.63 | ||
CLM5 | [-] | 32.3 | 31.4 | 51.2 | 26.4 | 16.7 | 6.54 | 18.0 | 0.636 | 0.65 | 0.37 | 0.94 | 0.86 | 0.64 |
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Benchmark | [-] | 21.5 | ||||||||||||||
CLM4 | [-] | 17.1 | 17.2 | 12.7 | 21.7 | 3.43 | -4.64 | 12.1 | 0.116 | 0.81 | 0.69 | 0.99 | 0.88 | 0.81 | ||
CLM4.5 | [-] | 20.3 | 20.4 | 12.6 | 21.7 | 3.43 | -1.50 | 10.6 | 0.125 | 0.87 | 0.70 | 0.99 | 0.94 | 0.84 | ||
CLM5 | [-] | 23.1 | 23.3 | 13.4 | 21.7 | 3.43 | 1.35 | 12.2 | 0.212 | 0.86 | 0.65 | 0.99 | 0.95 | 0.82 |
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Benchmark | [-] | 17.2 | ||||||||||||||
CLM4 | [-] | 15.9 | 16.6 | 5.55 | 17.5 | 2.66 | -1.28 | 11.8 | 0.169 | 0.78 | 0.64 | 1.0 | 0.94 | 0.80 | ||
CLM4.5 | [-] | 19.4 | 20.2 | 6.22 | 17.5 | 2.66 | 2.14 | 12.7 | 0.201 | 0.78 | 0.60 | 1.0 | 0.94 | 0.78 | ||
CLM5 | [-] | 20.3 | 21.1 | 5.94 | 17.5 | 2.66 | 3.02 | 14.1 | 0.300 | 0.76 | 0.55 | 0.99 | 0.92 | 0.76 |
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Benchmark | [-] | 51.8 | ||||||||||||||
CLM4 | [-] | 64.2 | 62.9 | 77.3 | 52.7 | 19.3 | 13.0 | 28.2 | 0.900 | 0.46 | 0.30 | 0.88 | 0.90 | 0.57 | ||
CLM4.5 | [-] | 65.0 | 63.8 | 77.7 | 52.7 | 19.3 | 14.1 | 30.8 | 0.835 | 0.43 | 0.27 | 0.90 | 0.86 | 0.54 | ||
CLM5 | [-] | 62.6 | 61.3 | 75.2 | 52.7 | 19.3 | 11.5 | 26.2 | 0.807 | 0.46 | 0.34 | 0.90 | 0.87 | 0.58 |
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Benchmark | [-] | 22.7 | ||||||||||||||
CLM4 | [-] | 26.7 | 26.9 | 21.9 | 22.8 | 12.1 | 4.46 | 14.4 | 0.588 | 0.73 | 0.57 | 0.97 | 0.96 | 0.76 | ||
CLM4.5 | [-] | 26.9 | 27.2 | 20.0 | 22.8 | 12.1 | 4.83 | 14.7 | 0.655 | 0.74 | 0.56 | 0.96 | 0.96 | 0.76 | ||
CLM5 | [-] | 25.2 | 25.4 | 18.6 | 22.8 | 12.1 | 3.06 | 15.0 | 0.631 | 0.75 | 0.54 | 0.95 | 0.97 | 0.75 |
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Benchmark | [-] | 74.5 | ||||||||||||||
CLM4 | [-] | 141. | 142. | 136. | 78.7 | 30.8 | 61.9 | 64.2 | 2.38 | 0.0039 | 0.091 | 0.62 | 0.52 | 0.27 | ||
CLM4.5 | [-] | 121. | 121. | 121. | 78.7 | 30.8 | 41.9 | 45.6 | 2.48 | 0.039 | 0.086 | 0.60 | 0.34 | 0.23 | ||
CLM5 | [-] | 125. | 126. | 123. | 78.7 | 30.8 | 46.2 | 48.7 | 2.06 | 0.034 | 0.11 | 0.69 | 0.59 | 0.31 |
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Benchmark | [-] | 30.9 | ||||||||||||||
CLM4 | [-] | 36.9 | 37.0 | 39.4 | 31.6 | 7.59 | 5.39 | 17.0 | 0.386 | 0.78 | 0.58 | 0.97 | 0.97 | 0.78 | ||
CLM4.5 | [-] | 38.3 | 38.4 | 39.9 | 31.6 | 7.59 | 6.75 | 17.1 | 0.388 | 0.80 | 0.57 | 0.97 | 0.88 | 0.76 | ||
CLM5 | [-] | 38.6 | 38.7 | 38.8 | 31.6 | 7.59 | 7.00 | 20.1 | 0.352 | 0.77 | 0.51 | 0.98 | 0.78 | 0.71 |
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Benchmark | [-] | 39.1 | ||||||||||||||
CLM4 | [-] | 41.1 | 49.1 | 8.59 | 39.4 | 16.4 | 10.3 | 22.4 | 0.787 | 0.46 | 0.36 | 0.87 | 0.86 | 0.58 | ||
CLM4.5 | [-] | 38.7 | 46.1 | 8.62 | 39.4 | 16.4 | 7.23 | 19.7 | 0.813 | 0.53 | 0.37 | 0.86 | 0.94 | 0.62 | ||
CLM5 | [-] | 38.6 | 45.8 | 8.48 | 39.4 | 16.4 | 6.99 | 19.5 | 0.843 | 0.52 | 0.38 | 0.85 | 0.94 | 0.61 |
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Benchmark | [-] | 10.8 | ||||||||||||||
CLM4 | [-] | 9.69 | 17.1 | 2.54 | 10.9 | 7.29 | 6.85 | 13.9 | 1.03 | 0.56 | 0.32 | 0.92 | 0.94 | 0.61 | ||
CLM4.5 | [-] | 9.98 | 17.4 | 2.81 | 10.9 | 7.29 | 7.31 | 14.4 | 1.08 | 0.56 | 0.31 | 0.91 | 0.94 | 0.61 | ||
CLM5 | [-] | 9.80 | 17.1 | 2.69 | 10.9 | 7.29 | 6.97 | 15.0 | 0.956 | 0.57 | 0.25 | 0.94 | 0.94 | 0.59 |
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Benchmark | [-] | 48.2 | ||||||||||||||
CLM4 | [-] | 53.6 | 59.7 | 6.95 | 48.3 | 16.9 | 11.4 | 25.8 | 1.37 | 0.46 | 0.30 | 0.72 | 0.92 | 0.54 | ||
CLM4.5 | [-] | 48.4 | 53.8 | 6.43 | 48.3 | 16.9 | 5.45 | 22.0 | 1.08 | 0.55 | 0.33 | 0.84 | 0.98 | 0.61 | ||
CLM5 | [-] | 46.5 | 51.7 | 6.22 | 48.3 | 16.9 | 3.37 | 20.8 | 1.41 | 0.54 | 0.35 | 0.71 | 0.98 | 0.59 |
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Benchmark | [-] | 84.4 | ||||||||||||||
CLM4 | [-] | 127. | 127. | 114. | 84.8 | 26.5 | 41.2 | 48.6 | 1.98 | 0.068 | 0.088 | 0.70 | 0.85 | 0.36 | ||
CLM4.5 | [-] | 110. | 110. | 111. | 84.8 | 26.5 | 24.5 | 34.8 | 2.47 | 0.10 | 0.086 | 0.60 | 0.99 | 0.37 | ||
CLM5 | [-] | 116. | 115. | 113. | 84.8 | 26.5 | 30.1 | 36.7 | 2.60 | 0.064 | 0.097 | 0.58 | 0.98 | 0.36 |
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Benchmark | [-] | 59.2 | ||||||||||||||
CLM4 | [-] | 80.6 | 79.8 | 99.4 | 60.2 | 25.2 | 21.2 | 33.9 | 0.769 | 0.42 | 0.33 | 0.90 | 0.89 | 0.58 | ||
CLM4.5 | [-] | 72.9 | 72.1 | 93.9 | 60.2 | 25.2 | 13.4 | 29.4 | 0.784 | 0.52 | 0.36 | 0.90 | 0.96 | 0.62 | ||
CLM5 | [-] | 71.1 | 70.3 | 92.4 | 60.2 | 25.2 | 11.6 | 25.7 | 0.891 | 0.57 | 0.41 | 0.89 | 0.96 | 0.65 |
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Benchmark | [-] | 56.3 | ||||||||||||||
CLM4 | [-] | 65.8 | 66.7 | 63.1 | 56.4 | 24.8 | 9.81 | 25.3 | 0.990 | 0.49 | 0.33 | 0.87 | 0.90 | 0.59 | ||
CLM4.5 | [-] | 58.8 | 59.6 | 59.1 | 56.4 | 24.8 | 2.89 | 21.1 | 0.976 | 0.57 | 0.37 | 0.88 | 0.97 | 0.63 | ||
CLM5 | [-] | 59.5 | 60.3 | 56.5 | 56.4 | 24.8 | 3.52 | 21.0 | 1.20 | 0.53 | 0.38 | 0.80 | 0.94 | 0.61 |
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Benchmark | [-] | 68.6 | ||||||||||||||
CLM4 | [-] | 87.4 | 88.9 | 54.7 | 68.9 | 9.65 | 19.1 | 31.9 | 1.23 | 0.25 | 0.23 | 0.83 | 0.86 | 0.48 | ||
CLM4.5 | [-] | 77.0 | 78.1 | 54.3 | 68.9 | 9.65 | 8.57 | 23.6 | 1.36 | 0.39 | 0.25 | 0.80 | 0.97 | 0.53 | ||
CLM5 | [-] | 78.2 | 79.4 | 53.8 | 68.9 | 9.65 | 9.87 | 23.7 | 1.19 | 0.31 | 0.28 | 0.83 | 0.94 | 0.53 |
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Benchmark | [-] | 36.3 | ||||||||||||||
CLM4 | [-] | 45.0 | 44.8 | 54.5 | 36.4 | 11.8 | 8.58 | 18.4 | 0.581 | 0.70 | 0.57 | 0.95 | 0.91 | 0.74 | ||
CLM4.5 | [-] | 44.0 | 44.0 | 46.0 | 36.4 | 11.8 | 7.72 | 17.6 | 0.634 | 0.71 | 0.57 | 0.95 | 0.94 | 0.75 | ||
CLM5 | [-] | 40.0 | 39.9 | 42.9 | 36.4 | 11.8 | 3.64 | 16.2 | 0.589 | 0.79 | 0.59 | 0.96 | 0.98 | 0.78 |
_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