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Global Attributes:	nco_openmp_thread_number: 1 title: Biogenic carbon fluxes associated with global agriculture institution: Joint Global Change Research Institute references: Julie Wolf, Tristram O. West, Yannick L. Le Page, G. Page Kyle, Xuesong Zhang, G. James Collatz, Marc L. Imhoff. Biogenic carbon fluxes from global agricultural production and consumption. Submitted to Global Biogeochemical Cycles. NCO: 4.3.7 comment: These data represent gridded annual (2005 to 2011) carbon fluxes associated with global crop plant net primary productivity (NPP) and harvest (hvst), summed over all crop types. For derivation of crop carbon fluxes at the subnational level and distribution at the 0.05 degree x0.05 degree gridcell level, see Wolf et al. [in review]. Net Primary Productivity (NPP) for croplands was estimated using a statistical method that includes factors for dry weight, harvest indices, and root:shoot ratios multiplied by crop production data from the FAO. This method has been documented and published by West et al. [2011]. We expanded this method by including factors for more crops and by using variable carbon contents for agricultural crop harvests, residues, and roots. Additionally, we account for on-field harvest losses: food crop harvest losses were calculated following Gustavsson et al. [2011, 2013], and 2.5% harvest losses was applied to all hay, haylage, silage, and other fodder crops. Total crop plant NPP estimations are based on the sum of harvested production plus harvest losses. References:Gustavsson, J., C. Cederberg, U. Sonesson, R. van Otterdik, and A. Meybeck (2011), Global food losses and food waste: extent, causes, and prevention, Food and Agriculture Organization, Rome.Gustavsson, J., C. Cederberg, U. Sonesson, and A. Emanuelsson (2013), The methodology of the FAO study: global food losses and food waste - extent, causes, and prevention, SIK (Swedish Institute for Food and Biotechnology), Gteborg, Sweden.West, T. O., V. Bandaru, C. C. Brandt, A. E. Schuh, and S. M. Ogle (2011), Regional uptake and release of crop carbon in the United States, Biogeosciences, 8(8), 2037to2046, doi:10.5194/bg-8-2037-2011.Wolf, J., T. O. West, Y. Le Page, G. P. Kyle, X. Zhang, G. J. Collatz, and M. Imhoff (in review), Biogenic carbon fluxes from global agricultural production and consumption. Contacts: Julie Wolf, Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD 20740,Email: Julie.Wolf@pnnl.gov,Phone: 301-314-6707, Fax: 301-314-6719, Tristram O. West,Joint Global Change Research Institute, Pacific Northwest National Laboratory,College Park, MD 20740,Email: Tristram.West@pnnl.gov,Phone: 301-314-6705,Fax: 301-314-6719

Variables:	time: Array of 32 bit Reals [time = 0..6] time: bounds: time_bnds calendar: standard description: middle of each year units: years since 2005-01-01 00:00:00 _ChunkSizes: 7
	NPPMgC: Grid time: lat: lon: scale_factor: 1.0 add_offset: 0.0 long_name: Annual amount of crop NPP distributed to the gridcell, in megagrams carbon. _FillValue: -9999999.0 units: Mg yr-1 _ChunkSizes: 1, 554, 1395
	NPPSDMgC: Grid time: lat: lon: scale_factor: 1.0 add_offset: 0.0 long_name: Standard deviation of the annual crop NPP distributed to the gridcell, in megagrams carbon. _FillValue: -9999999.0 units: Mg yr-1 _ChunkSizes: 1, 554, 1395
	cropkm2: Grid time: lat: lon: scale_factor: 1.0 add_offset: 0.0 units: km2 yr-1 long_name: Annual total harvested crop area assigned to the gridcell, in square kilometers _FillValue: -9999999.0 _ChunkSizes: 1, 554, 1395
	hvstMgC: Grid time: lat: lon: scale_factor: 1.0 add_offset: 0.0 long_name: Annual amount of harvested crop biomass distributed to the gridcell, in megagrams carbon. _FillValue: -9999999.0 units: Mg yr-1 _ChunkSizes: 1, 554, 1395
	hvstSDMgC: Grid time: lat: lon: scale_factor: 1.0 add_offset: 0.0 long_name: Standard deviation of the annual harvested crop biomass distributed to the gridcell, in megagrams carbon. _FillValue: -9999999.0 units: Mg yr-1 _ChunkSizes: 1, 554, 1395
	lat: Array of 32 bit Reals [lat = 0..2861] lat: units: degrees_north standard_name: latitude bounds: lat_bnds _ChunkSizes: 2862
	lat_bnds: Array of 32 bit Reals [lat = 0..2861][nv = 0..1] lat: nv: units: degrees_north _ChunkSizes: 2862, 2
	lon: Array of 32 bit Reals [lon = 0..7199] lon: bounds: lon_bnds standard_name: longitude units: degrees_east _ChunkSizes: 7200
	lon_bnds: Array of 32 bit Reals [lon = 0..7199][nv = 0..1] lon: nv: units: degrees_east _ChunkSizes: 7200, 2
	time_bnds: Array of 32 bit Reals [time = 0..6][nv = 0..1] time: nv: _ChunkSizes: 7, 2

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DDS:

Dataset {
    Float32 time[time = 7];
    Grid {
     ARRAY:
        Float32 NPPMgC[time = 7][lat = 2862][lon = 7200];
     MAPS:
        Float32 time[time = 7];
        Float32 lat[lat = 2862];
        Float32 lon[lon = 7200];
    } NPPMgC;
    Grid {
     ARRAY:
        Float32 NPPSDMgC[time = 7][lat = 2862][lon = 7200];
     MAPS:
        Float32 time[time = 7];
        Float32 lat[lat = 2862];
        Float32 lon[lon = 7200];
    } NPPSDMgC;
    Grid {
     ARRAY:
        Float32 cropkm2[time = 7][lat = 2862][lon = 7200];
     MAPS:
        Float32 time[time = 7];
        Float32 lat[lat = 2862];
        Float32 lon[lon = 7200];
    } cropkm2;
    Grid {
     ARRAY:
        Float32 hvstMgC[time = 7][lat = 2862][lon = 7200];
     MAPS:
        Float32 time[time = 7];
        Float32 lat[lat = 2862];
        Float32 lon[lon = 7200];
    } hvstMgC;
    Grid {
     ARRAY:
        Float32 hvstSDMgC[time = 7][lat = 2862][lon = 7200];
     MAPS:
        Float32 time[time = 7];
        Float32 lat[lat = 2862];
        Float32 lon[lon = 7200];
    } hvstSDMgC;
    Float32 lat[lat = 2862];
    Float32 lat_bnds[lat = 2862][nv = 2];
    Float32 lon[lon = 7200];
    Float32 lon_bnds[lon = 7200][nv = 2];
    Float32 time_bnds[time = 7][nv = 2];
} ornldaac/1279/crop_2005_2011_MgC.nc4;

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