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Bias [W/m2] |
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Phase Shift [months] |
Bias Score [1] |
RMSE Score [1] |
Seasonal Cycle Score [1] |
Spatial Distribution Score [1] |
Overall Score [1] |
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Benchmark | [-] | 26.3 | ||||||||||||||
CRUNCEPv7 | [-] | 32.3 | 31.4 | 50.4 | 26.4 | 16.7 | 6.46 | 15.0 | 0.551 | 0.65 | 0.46 | 0.95 | 0.86 | 0.68 | ||
GSWP3v1 | [-] | 32.2 | 31.4 | 50.3 | 26.4 | 16.7 | 6.33 | 13.7 | 0.513 | 0.67 | 0.50 | 0.95 | 0.91 | 0.70 | ||
WFDEI | [-] | 32.1 | 31.3 | 50.2 | 26.4 | 16.7 | 6.34 | 16.0 | 0.614 | 0.66 | 0.43 | 0.94 | 0.89 | 0.67 |
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Bias Score [1] |
RMSE Score [1] |
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Overall Score [1] |
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Benchmark | [-] | 21.5 | ||||||||||||||
CRUNCEPv7 | [-] | 21.1 | 21.3 | 11.6 | 21.7 | 3.43 | -0.630 | 10.5 | 0.337 | 0.89 | 0.68 | 0.98 | 0.97 | 0.84 | ||
GSWP3v1 | [-] | 20.3 | 20.4 | 15.0 | 21.7 | 3.43 | -1.44 | 11.5 | 0.373 | 0.90 | 0.66 | 0.97 | 0.97 | 0.83 | ||
WFDEI | [-] | 16.0 | 16.1 | 10.3 | 21.7 | 3.43 | -5.72 | 11.3 | 0.472 | 0.79 | 0.70 | 0.97 | 0.98 | 0.83 |
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Benchmark | [-] | 17.2 | ||||||||||||||
CRUNCEPv7 | [-] | 17.8 | 18.5 | 5.34 | 17.5 | 2.66 | 0.442 | 11.2 | 0.196 | 0.82 | 0.63 | 1.0 | 0.96 | 0.81 | ||
GSWP3v1 | [-] | 18.2 | 18.9 | 6.54 | 17.5 | 2.66 | 0.843 | 11.5 | 0.253 | 0.84 | 0.63 | 0.99 | 0.92 | 0.80 | ||
WFDEI | [-] | 14.6 | 15.2 | 3.57 | 17.5 | 2.66 | -2.78 | 11.5 | 0.386 | 0.79 | 0.64 | 0.99 | 0.94 | 0.80 |
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Benchmark | [-] | 51.8 | ||||||||||||||
CRUNCEPv7 | [-] | 64.6 | 63.3 | 76.1 | 52.7 | 19.3 | 13.2 | 28.5 | 0.797 | 0.44 | 0.32 | 0.89 | 0.85 | 0.56 | ||
GSWP3v1 | [-] | 61.1 | 60.4 | 67.7 | 52.7 | 19.3 | 9.18 | 21.9 | 0.746 | 0.51 | 0.41 | 0.91 | 0.95 | 0.64 | ||
WFDEI | [-] | 61.2 | 60.1 | 72.5 | 52.7 | 19.3 | 9.69 | 23.2 | 0.739 | 0.54 | 0.36 | 0.91 | 0.96 | 0.62 |
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Benchmark | [-] | 22.7 | ||||||||||||||
CRUNCEPv7 | [-] | 23.7 | 23.9 | 17.6 | 22.8 | 12.1 | 1.51 | 11.3 | 0.508 | 0.78 | 0.64 | 0.97 | 0.97 | 0.80 | ||
GSWP3v1 | [-] | 22.0 | 22.2 | 15.5 | 22.8 | 12.1 | -0.221 | 10.3 | 0.547 | 0.78 | 0.68 | 0.97 | 0.93 | 0.81 | ||
WFDEI | [-] | 22.7 | 22.9 | 18.1 | 22.8 | 12.1 | 0.476 | 11.8 | 0.645 | 0.76 | 0.64 | 0.96 | 0.92 | 0.79 |
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Period Mean (original grids) [W/m2] |
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Benchmark | [-] | 74.5 | ||||||||||||||
CRUNCEPv7 | [-] | 129. | 130. | 126. | 78.7 | 30.8 | 49.8 | 51.5 | 2.24 | 0.013 | 0.15 | 0.65 | 0.49 | 0.29 | ||
GSWP3v1 | [-] | 103. | 103. | 104. | 78.7 | 30.8 | 24.7 | 29.5 | 2.18 | 0.25 | 0.17 | 0.66 | 0.28 | 0.31 | ||
WFDEI | [-] | 105. | 104. | 112. | 78.7 | 30.8 | 26.9 | 32.0 | 2.31 | 0.23 | 0.16 | 0.63 | 0.45 | 0.32 |
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Benchmark | [-] | 30.9 | ||||||||||||||
CRUNCEPv7 | [-] | 36.6 | 36.9 | 35.6 | 31.6 | 7.59 | 4.97 | 14.8 | 0.328 | 0.81 | 0.62 | 0.98 | 0.88 | 0.78 | ||
GSWP3v1 | [-] | 33.5 | 33.7 | 33.5 | 31.6 | 7.59 | 2.00 | 12.3 | 0.326 | 0.82 | 0.69 | 0.98 | 0.84 | 0.80 | ||
WFDEI | [-] | 30.2 | 30.1 | 33.8 | 31.6 | 7.59 | -1.27 | 13.9 | 0.384 | 0.77 | 0.67 | 0.98 | 0.91 | 0.80 |
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Period Mean (original grids) [W/m2] |
Model Period Mean (intersection) [W/m2] |
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Benchmark | [-] | 39.1 | ||||||||||||||
CRUNCEPv7 | [-] | 38.5 | 45.7 | 8.34 | 39.4 | 16.4 | 6.84 | 17.9 | 0.760 | 0.52 | 0.42 | 0.86 | 0.92 | 0.63 | ||
GSWP3v1 | [-] | 35.0 | 41.6 | 7.58 | 39.4 | 16.4 | 2.55 | 14.6 | 0.783 | 0.62 | 0.46 | 0.87 | 0.98 | 0.67 | ||
WFDEI | [-] | 34.6 | 40.8 | 8.76 | 39.4 | 16.4 | 1.84 | 15.4 | 0.835 | 0.62 | 0.45 | 0.87 | 0.97 | 0.67 |
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Period Mean (original grids) [W/m2] |
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Benchmark | [-] | 10.8 | ||||||||||||||
CRUNCEPv7 | [-] | 8.93 | 15.5 | 2.59 | 10.9 | 7.29 | 5.34 | 10.1 | 0.908 | 0.63 | 0.47 | 0.95 | 0.94 | 0.69 | ||
GSWP3v1 | [-] | 9.09 | 15.1 | 3.27 | 10.9 | 7.29 | 4.91 | 9.68 | 0.952 | 0.63 | 0.48 | 0.95 | 0.93 | 0.70 | ||
WFDEI | [-] | 10.3 | 17.3 | 3.48 | 10.9 | 7.29 | 7.08 | 12.2 | 0.955 | 0.60 | 0.41 | 0.95 | 0.93 | 0.66 |
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Period Mean (original grids) [W/m2] |
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Benchmark | [-] | 48.2 | ||||||||||||||
CRUNCEPv7 | [-] | 49.6 | 55.2 | 6.47 | 48.3 | 16.9 | 6.90 | 21.1 | 1.41 | 0.53 | 0.35 | 0.70 | 0.97 | 0.58 | ||
GSWP3v1 | [-] | 48.0 | 53.3 | 8.10 | 48.3 | 16.9 | 4.78 | 18.3 | 1.29 | 0.59 | 0.38 | 0.77 | 0.99 | 0.62 | ||
WFDEI | [-] | 46.6 | 51.8 | 8.24 | 48.3 | 16.9 | 3.39 | 18.4 | 1.18 | 0.62 | 0.38 | 0.80 | 0.98 | 0.63 |
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Benchmark | [-] | 84.4 | ||||||||||||||
CRUNCEPv7 | [-] | 117. | 117. | 112. | 84.8 | 26.5 | 31.0 | 37.3 | 2.38 | 0.069 | 0.13 | 0.62 | 0.95 | 0.38 | ||
GSWP3v1 | [-] | 95.5 | 95.3 | 92.5 | 84.8 | 26.5 | 9.70 | 19.4 | 2.46 | 0.32 | 0.15 | 0.60 | 0.93 | 0.43 | ||
WFDEI | [-] | 90.3 | 90.2 | 93.7 | 84.8 | 26.5 | 5.06 | 18.0 | 2.42 | 0.37 | 0.17 | 0.60 | 0.89 | 0.44 |
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Benchmark | [-] | 59.2 | ||||||||||||||
CRUNCEPv7 | [-] | 72.6 | 71.8 | 93.0 | 60.2 | 25.2 | 13.2 | 25.5 | 0.737 | 0.56 | 0.43 | 0.91 | 0.92 | 0.65 | ||
GSWP3v1 | [-] | 58.6 | 58.0 | 75.4 | 60.2 | 25.2 | -0.995 | 20.6 | 1.04 | 0.60 | 0.48 | 0.86 | 0.98 | 0.68 | ||
WFDEI | [-] | 62.4 | 61.4 | 86.6 | 60.2 | 25.2 | 2.72 | 22.0 | 1.08 | 0.58 | 0.48 | 0.85 | 0.97 | 0.67 |
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Benchmark | [-] | 56.3 | ||||||||||||||
CRUNCEPv7 | [-] | 61.4 | 62.2 | 56.2 | 56.4 | 24.8 | 5.47 | 21.7 | 1.03 | 0.54 | 0.39 | 0.84 | 0.93 | 0.62 | ||
GSWP3v1 | [-] | 58.9 | 59.8 | 49.9 | 56.4 | 24.8 | 2.96 | 17.9 | 1.00 | 0.58 | 0.42 | 0.86 | 0.98 | 0.65 | ||
WFDEI | [-] | 58.0 | 58.4 | 56.5 | 56.4 | 24.8 | 1.76 | 18.0 | 1.32 | 0.62 | 0.42 | 0.80 | 0.98 | 0.65 |
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Benchmark | [-] | 68.6 | ||||||||||||||
CRUNCEPv7 | [-] | 79.1 | 80.3 | 50.7 | 68.9 | 9.65 | 10.7 | 23.9 | 1.07 | 0.31 | 0.30 | 0.85 | 0.91 | 0.53 | ||
GSWP3v1 | [-] | 70.1 | 71.2 | 44.3 | 68.9 | 9.65 | 1.57 | 16.1 | 1.09 | 0.55 | 0.33 | 0.87 | 0.99 | 0.61 | ||
WFDEI | [-] | 70.3 | 71.1 | 46.4 | 68.9 | 9.65 | 1.44 | 15.4 | 0.969 | 0.56 | 0.35 | 0.88 | 0.99 | 0.62 |
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Benchmark | [-] | 36.3 | ||||||||||||||
CRUNCEPv7 | [-] | 38.9 | 38.9 | 40.7 | 36.4 | 11.8 | 2.57 | 12.9 | 0.335 | 0.79 | 0.66 | 0.98 | 0.98 | 0.81 | ||
GSWP3v1 | [-] | 36.2 | 36.1 | 39.5 | 36.4 | 11.8 | -0.171 | 11.3 | 0.322 | 0.82 | 0.71 | 0.98 | 0.98 | 0.84 | ||
WFDEI | [-] | 37.6 | 37.6 | 39.7 | 36.4 | 11.8 | 1.27 | 13.4 | 0.380 | 0.83 | 0.64 | 0.98 | 0.98 | 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