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Benchmark | [-] | 26.3 | ||||||||||||||
CLM4.0 | [-] | 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 | 33.0 | 58.4 | 26.4 | 16.7 | 7.77 | 19.1 | 0.633 | 0.62 | 0.34 | 0.93 | 0.95 | 0.64 | ||
CLM5.0 | [-] | 32.2 | 30.9 | 59.4 | 26.4 | 16.7 | 5.93 | 16.6 | 0.709 | 0.67 | 0.40 | 0.93 | 0.92 | 0.67 |
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Benchmark | [-] | 21.5 | ||||||||||||||
CLM4.0 | [-] | 16.9 | 16.9 | 15.9 | 21.7 | 3.43 | -4.90 | 12.3 | 0.180 | 0.80 | 0.69 | 0.99 | 0.92 | 0.82 | ||
CLM4.5 | [-] | 21.2 | 21.3 | 16.9 | 21.7 | 3.43 | -0.563 | 10.3 | 0.285 | 0.89 | 0.70 | 0.98 | 0.98 | 0.85 | ||
CLM5.0 | [-] | 21.2 | 21.3 | 17.2 | 21.7 | 3.43 | -0.553 | 11.8 | 0.217 | 0.89 | 0.66 | 0.99 | 0.95 | 0.83 |
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Benchmark | [-] | 17.2 | ||||||||||||||
CLM4.0 | [-] | 16.5 | 17.1 | 7.58 | 17.5 | 2.66 | -0.685 | 11.6 | 0.152 | 0.79 | 0.66 | 1.0 | 0.93 | 0.81 | ||
CLM4.5 | [-] | 22.3 | 23.1 | 9.50 | 17.5 | 2.66 | 5.07 | 13.8 | 0.189 | 0.78 | 0.59 | 1.0 | 0.95 | 0.78 | ||
CLM5.0 | [-] | 20.4 | 21.2 | 7.04 | 17.5 | 2.66 | 3.08 | 13.3 | 0.302 | 0.83 | 0.57 | 0.99 | 0.96 | 0.78 |
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Benchmark | [-] | 51.8 | ||||||||||||||
CLM4.0 | [-] | 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 | [-] | 62.5 | 61.8 | 69.8 | 52.7 | 19.3 | 10.8 | 26.8 | 1.04 | 0.51 | 0.28 | 0.86 | 0.96 | 0.58 | ||
CLM5.0 | [-] | 57.6 | 56.7 | 65.7 | 52.7 | 19.3 | 5.71 | 20.4 | 0.854 | 0.55 | 0.42 | 0.90 | 0.97 | 0.65 |
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Benchmark | [-] | 22.7 | ||||||||||||||
CLM4.0 | [-] | 25.9 | 26.1 | 19.5 | 22.8 | 12.1 | 3.65 | 13.2 | 0.717 | 0.76 | 0.59 | 0.95 | 0.97 | 0.77 | ||
CLM4.5 | [-] | 26.0 | 26.3 | 18.3 | 22.8 | 12.1 | 3.88 | 13.6 | 0.758 | 0.77 | 0.58 | 0.95 | 0.97 | 0.77 | ||
CLM5.0 | [-] | 23.4 | 23.6 | 16.0 | 22.8 | 12.1 | 1.16 | 13.8 | 0.729 | 0.76 | 0.57 | 0.94 | 0.94 | 0.76 |
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Benchmark | [-] | 74.5 | ||||||||||||||
CLM4.0 | [-] | 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 | 0.10 | 0.63 | 0.33 | 0.27 | ||
CLM5.0 | [-] | 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 | ||||||||||||||
CLM4.0 | [-] | 34.8 | 35.0 | 36.9 | 31.6 | 7.59 | 3.47 | 15.3 | 0.469 | 0.80 | 0.61 | 0.97 | 0.96 | 0.79 | ||
CLM4.5 | [-] | 36.3 | 36.4 | 37.9 | 31.6 | 7.59 | 4.90 | 15.5 | 0.463 | 0.81 | 0.60 | 0.97 | 0.81 | 0.76 | ||
CLM5.0 | [-] | 33.2 | 33.2 | 34.3 | 31.6 | 7.59 | 1.68 | 15.6 | 0.346 | 0.79 | 0.60 | 0.98 | 0.69 | 0.73 |
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Benchmark | [-] | 39.1 | ||||||||||||||
CLM4.0 | [-] | 39.0 | 46.5 | 8.21 | 39.4 | 16.4 | 7.49 | 20.0 | 0.928 | 0.52 | 0.37 | 0.84 | 0.92 | 0.60 | ||
CLM4.5 | [-] | 36.4 | 43.3 | 8.23 | 39.4 | 16.4 | 4.35 | 18.1 | 0.926 | 0.58 | 0.38 | 0.85 | 0.97 | 0.63 | ||
CLM5.0 | [-] | 33.7 | 40.1 | 7.44 | 39.4 | 16.4 | 1.14 | 16.5 | 0.899 | 0.61 | 0.42 | 0.85 | 0.97 | 0.66 |
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Benchmark | [-] | 10.8 | ||||||||||||||
CLM4.0 | [-] | 10.2 | 17.2 | 3.31 | 10.9 | 7.29 | 6.96 | 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 | 6.95 | 14.0 | 1.51 | 0.55 | 0.32 | 0.90 | 0.94 | 0.61 | ||
CLM5.0 | [-] | 9.92 | 16.7 | 3.38 | 10.9 | 7.29 | 6.46 | 14.4 | 1.02 | 0.57 | 0.27 | 0.94 | 0.94 | 0.60 |
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Benchmark | [-] | 48.2 | ||||||||||||||
CLM4.0 | [-] | 52.9 | 58.6 | 8.84 | 48.3 | 16.9 | 10.1 | 25.3 | 1.59 | 0.51 | 0.30 | 0.68 | 0.97 | 0.55 | ||
CLM4.5 | [-] | 46.1 | 50.9 | 8.38 | 48.3 | 16.9 | 2.50 | 22.7 | 1.49 | 0.57 | 0.33 | 0.73 | 0.98 | 0.59 | ||
CLM5.0 | [-] | 43.5 | 48.2 | 7.85 | 48.3 | 16.9 | -0.239 | 20.6 | 1.43 | 0.57 | 0.35 | 0.74 | 0.97 | 0.60 |
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Benchmark | [-] | 84.4 | ||||||||||||||
CLM4.0 | [-] | 113. | 113. | 95.8 | 84.8 | 26.5 | 26.3 | 36.9 | 2.42 | 0.11 | 0.063 | 0.61 | 0.93 | 0.35 | ||
CLM4.5 | [-] | 95.5 | 95.1 | 92.4 | 84.8 | 26.5 | 9.70 | 24.5 | 2.39 | 0.27 | 0.093 | 0.62 | 0.97 | 0.41 | ||
CLM5.0 | [-] | 91.2 | 91.0 | 88.5 | 84.8 | 26.5 | 5.59 | 17.5 | 2.71 | 0.39 | 0.16 | 0.56 | 0.87 | 0.43 |
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Benchmark | [-] | 59.2 | ||||||||||||||
CLM4.0 | [-] | 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 | [-] | 59.3 | 58.7 | 76.0 | 60.2 | 25.2 | -0.277 | 22.6 | 1.03 | 0.62 | 0.44 | 0.87 | 0.97 | 0.67 | ||
CLM5.0 | [-] | 55.6 | 54.9 | 73.8 | 60.2 | 25.2 | -4.15 | 24.1 | 1.43 | 0.56 | 0.44 | 0.78 | 0.96 | 0.64 |
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Benchmark | [-] | 56.3 | ||||||||||||||
CLM4.0 | [-] | 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 | [-] | 54.2 | 54.9 | 52.2 | 56.4 | 24.8 | -1.78 | 21.1 | 1.17 | 0.54 | 0.36 | 0.83 | 0.98 | 0.61 | ||
CLM5.0 | [-] | 52.0 | 52.7 | 48.5 | 56.4 | 24.8 | -4.07 | 20.3 | 1.25 | 0.55 | 0.39 | 0.82 | 0.98 | 0.63 |
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Benchmark | [-] | 68.6 | ||||||||||||||
CLM4.0 | [-] | 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 | [-] | 71.0 | 71.9 | 49.2 | 68.9 | 9.65 | 2.37 | 21.2 | 1.38 | 0.50 | 0.25 | 0.82 | 0.99 | 0.56 | ||
CLM5.0 | [-] | 67.0 | 67.8 | 46.5 | 68.9 | 9.65 | -1.63 | 16.7 | 1.13 | 0.54 | 0.34 | 0.86 | 0.99 | 0.61 |
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Benchmark | [-] | 36.3 | ||||||||||||||
CLM4.0 | [-] | 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 | 44.4 | 46.2 | 36.4 | 11.8 | 8.11 | 17.0 | 0.534 | 0.71 | 0.60 | 0.96 | 0.97 | 0.76 | ||
CLM5.0 | [-] | 36.4 | 36.3 | 40.4 | 36.4 | 11.8 | 0.0504 | 13.6 | 0.512 | 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