FLUXNET Variable Codes


Variables in the HALF-HOURLY FULLSET Data Product (all variables)

Source: FLUXNET_variable_codes_FULLSET_20200504.csv, downloaded from here on 16 Dec 2022.

Note that this list contains abbreviations and units from the half-hourly dataset.

 

wdt_ID LABEL DESCRIPTION UNIT (preferred) or FORMAT CATEGORY TIME RESOLUTION
511 TIMESTAMP ISO timestamp - short format YYYYMMDDHHMM TIMEKEEPING half-hourly
811 TIMESTAMP_START ISO timestamp start of averaging period - short format YYYYMMDDHHMM TIMEKEEPING half-hourly
812 TIMESTAMP_END ISO timestamp end of averaging period - short format YYYYMMDDHHMM TIMEKEEPING half-hourly
813 TA_F_MDS Air temperature, gapfilled using MDS method deg C MICROMETEOROLOGICAL half-hourly
814 TA_F_MDS_QC Quality flag for TA_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL half-hourly
815 TA_ERA Air temperature, downscaled from ERA, linearly regressed using measured only site data deg C MICROMETEOROLOGICAL half-hourly
816 TA_F Air temperature, consolidated from TA_F_MDS and TA_ERA; TA_F_MDS used if TA_F_MDS_QC is 0 or 1 deg C MICROMETEOROLOGICAL half-hourly
817 TA_F_QC Quality flag for TA_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
818 SW_IN_POT Shortwave radiation, incoming, potential (top of atmosphere); W m-2 MICROMETEOROLOGICAL half-hourly
819 SW_IN_F_MDS Shortwave radiation, incoming, gapfilled using MDS (negative values set to zero, e.g., negative values from instrumentation noise); W m-2 MICROMETEOROLOGICAL half-hourly
820 SW_IN_F_MDS_QC Quality flag for SW_IN_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL half-hourly
821 SW_IN_ERA Shortwave radiation, incoming, downscaled from ERA, linearly regressed using measured only site data (negative values set to zero); W m-2 MICROMETEOROLOGICAL half-hourly
822 SW_IN_F Shortwave radiation, incoming consolidated from SW_IN_F_MDS and SW_IN_ERA (negative values set to zero); SW_IN_F_MDS used if SW_IN_F_MDS_QC is 0 or 1 W m-2 MICROMETEOROLOGICAL half-hourly
823 SW_IN_F_QC Quality flag for SW_IN_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
824 LW_IN_F_MDS Longwave radiation, incoming, gapfilled using MDS; W m-2 MICROMETEOROLOGICAL half-hourly
825 LW_IN_F_MDS_QC Quality flag for LW_IN_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL half-hourly
826 LW_IN_ERA Longwave radiation, incoming, downscaled from ERA, linearly regressed using measured only site data; W m-2 MICROMETEOROLOGICAL half-hourly
827 LW_IN_F Longwave radiation, incoming, consolidated from LW_IN_F_MDS and LW_IN_ERA; LW_IN_F_MDS used if LW_IN_F_MDS_QC is 0 or 1 W m-2 MICROMETEOROLOGICAL half-hourly
828 LW_IN_F_QC Quality flag for LW_IN_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
829 LW_IN_JSB Longwave radiation, incoming, calculated from TA_F_MDS, SW_IN_F_MDS, VPD_F_MDS and SW_IN_POT using the JSBACH algorithm (Sonke Zaehle); W m-2 MICROMETEOROLOGICAL half-hourly
830 LW_IN_JSB_QC Quality flag for LW_IN_JSB; highest from TA_F_MDS_QC, SW_IN_F_MDS_QC, and VPD_F_MDS_QC, poorest quality prevails nondimensional MICROMETEOROLOGICAL half-hourly
831 LW_IN_JSB_ERA Longwave radiation, incoming, downscaled from ERA, linearly regressed using site level LW_IN_JSB calculated from measured only drivers; W m-2 MICROMETEOROLOGICAL half-hourly
832 LW_IN_JSB_F Longwave radiation, incoming, consolidated from LW_IN_JSB and LW_IN_JSB_ERA; LW_IN_JSB used if LW_IN_JSB_QC is 0 or 1 W m-2 MICROMETEOROLOGICAL half-hourly
833 LW_IN_JSB_F_QC Quality flag for LW_IN_JSB_F; 0 = calculated from measured drivers; 1 = calculated from good quality gapfilled drivers; 2: downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
834 VPD_F_MDS Vapor Pressure Deficit, gapfilled using MDS; hPa MICROMETEOROLOGICAL half-hourly
835 VPD_F_MDS_QC Quality flag for VPD_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL half-hourly
836 VPD_ERA Vapor Pressure Deficit, downscaled from ERA, linearly regressed using measured only site data; hPa MICROMETEOROLOGICAL half-hourly
837 VPD_F Vapor Pressure Deficit consolidated from VPD_F_MDS and VPD_ERA; VPD_F_MDS used if VPD_F_MDS_QC is 0 or 1 hPa MICROMETEOROLOGICAL half-hourly
838 VPD_F_QC Quality flag for VPD_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
839 PA Atmospheric pressure; kPa MICROMETEOROLOGICAL half-hourly
840 PA_ERA Atmospheric pressure, downscaled from ERA, linearly regressed using measured only site data; kPa MICROMETEOROLOGICAL half-hourly
841 PA_F Atmospheric pressure consolidated from PA and PA_ERA; PA used if measured kPa MICROMETEOROLOGICAL half-hourly
842 PA_F_QC Quality flag for PA_F; 0 = measured; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
843 P Precipitation; mm MICROMETEOROLOGICAL half-hourly
844 P_ERA Precipitation, downscaled from ERA, linearly regressed using measured only site data; (mm per dataset resolution: either hour or half-hour) mm MICROMETEOROLOGICAL half-hourly
845 P_F Precipitation consolidated from P and P_ERA; P used if measured (mm per dataset resolution: either hour or half-hour) mm MICROMETEOROLOGICAL half-hourly
846 P_F_QC Quality flag for P_F; 0 = measured; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
847 WS Wind speed; m s-1 MICROMETEOROLOGICAL half-hourly
848 WS_ERA Wind speed, downscaled from ERA, linearly regressed using measured only site data; m s-1 MICROMETEOROLOGICAL half-hourly
849 WS_F Wind speed, consolidated from WS and WS_ERA; WS used if measured m s-1 MICROMETEOROLOGICAL half-hourly
850 WS_F_QC Quality flag of WS_F; 0 = measured; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL half-hourly
851 WD Wind direction; Decimal degrees MICROMETEOROLOGICAL half-hourly
852 RH Relative humidity, range 0-100; % MICROMETEOROLOGICAL half-hourly
853 USTAR Friction velocity; m s-1 MICROMETEOROLOGICAL half-hourly
854 NETRAD Net radiation; W m-2 MICROMETEOROLOGICAL half-hourly
855 PPFD_IN Photosynthetic photon flux density, incoming; µmolPhoton m-2 s-1 MICROMETEOROLOGICAL half-hourly
856 PPFD_DIF Photosynthetic photon flux density, diffuse incoming; µmolPhoton m-2 s-1 MICROMETEOROLOGICAL half-hourly
857 PPFD_OUT Photosynthetic photon flux density, outgoing; µmolPhoton m-2 s-1 MICROMETEOROLOGICAL half-hourly
858 SW_DIF Shortwave radiation, diffuse incoming; W m-2 MICROMETEOROLOGICAL half-hourly
859 SW_OUT Shortwave radiation, outgoing; W m-2 MICROMETEOROLOGICAL half-hourly
860 LW_OUT Longwave radiation, outgoing; W m-2 MICROMETEOROLOGICAL half-hourly
861 CO2_F_MDS CO2 mole fraction, gapfilled with MDS; µmolCO2 mol-1 MICROMETEOROLOGICAL half-hourly
862 CO2_F_MDS_QC Quality flag for CO2_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL half-hourly
863 TS_F_MDS_# Soil temperature, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest); deg C MICROMETEOROLOGICAL half-hourly
864 TS_F_MDS_#_QC Quality flag for TS_F_MDS_#; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL half-hourly
865 SWC_F_MDS_# Soil water content, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest); % MICROMETEOROLOGICAL half-hourly
866 SWC_F_MDS_#_QC Quality flag for SWC_F_MDS_#; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL half-hourly
867 G_F_MDS Soil heat flux; W m-2 ENERGY PROCESSING half-hourly
868 G_F_MDS_QC Quality flag of G_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ENERGY PROCESSING half-hourly
869 LE_F_MDS Latent heat flux, gapfilled using MDS method; W m-2 ENERGY PROCESSING half-hourly
870 LE_F_MDS_QC Quality flag for LE_F_MDS, LE_CORR, LE_CORR25, and LE_CORR75.; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ENERGY PROCESSING half-hourly
871 LE_CORR Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor; W m-2 ENERGY PROCESSING half-hourly
872 LE_CORR_25 Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor, 25th percentile; W m-2 ENERGY PROCESSING half-hourly
873 LE_CORR_75 Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor, 75th percentile; W m-2 ENERGY PROCESSING half-hourly
874 LE_RANDUNC Random uncertainty of LE, from measured only data; uses only data point where LE_F_MDS_QC is 0 and two hierarchical methods (see header and LE_RANDUNC_METHOD) W m-2 ENERGY PROCESSING half-hourly
875 LE_RANDUNC_METHOD Method used to estimate the random uncertainty of LE; 1 = RANDUNC Method 1 (direct SD method), 2 = RANDUNC Method 2 (median SD method) nondimensional ENERGY PROCESSING half-hourly
876 LE_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of LE; nondimensional ENERGY PROCESSING half-hourly
877 LE_CORR_JOINTUNC Joint uncertainty estimation for LE; [SQRT(LE_RANDUNC^2 + ((LE_CORR75 - LE_CORR25) / 1.349)^2)] W m-2 ENERGY PROCESSING half-hourly
878 H_F_MDS Sensible heat flux, gapfilled using MDS method; W m-2 ENERGY PROCESSING half-hourly
879 H_F_MDS_QC Quality flag for H_F_MDS, H_CORR, H_CORR25, and H_CORR75.; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ENERGY PROCESSING half-hourly
880 H_CORR Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor; W m-2 ENERGY PROCESSING half-hourly
881 H_CORR_25 Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor, 25th percentile; W m-2 ENERGY PROCESSING half-hourly
882 H_CORR_75 Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor, 75th percentile; W m-2 ENERGY PROCESSING half-hourly
883 H_RANDUNC Random uncertainty of H, from measured only data; uses only data point where H_F_MDS_QC is 0 and two hierarchical methods (see header and H_RANDUNC_METHOD) W m-2 ENERGY PROCESSING half-hourly
884 H_RANDUNC_METHOD Method used to estimate the random uncertainty of H; 1 = RANDUNC Method 1 (direct SD method), 2 = RANDUNC Method 2 (median SD method) nondimensional ENERGY PROCESSING half-hourly
885 H_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of H; nondimensional ENERGY PROCESSING half-hourly
886 H_CORR_JOINTUNC Joint uncertainty estimation for H; [SQRT(H_RANDUNC^2 + ((H_CORR75 - H_CORR25) / 1.349)^2)] W m-2 ENERGY PROCESSING half-hourly
887 EBC_CF_N Number of data points used to calculate energy closure balance correction factor. Driver data points within sliding window (ECB_CF Method 1) or number of ECB_CF data points (for ECB_CF Methods 2 and 3); for ECB_CF Method 1 (minimum 5, maximum 93) nondimensional ENERGY PROCESSING half-hourly
888 EBC_CF_METHOD Method used to calculate the energy balance closure correction factor; 1 = ECB_CF Method 1, 2 = ECB_CF Method 2, 3 = ECB_CF Method 3. See general description for details nondimensional ENERGY PROCESSING half-hourly
889 NIGHT Flag indicating nighttime interval based on SW_IN_POT; 0 = daytime, 1 = nighttime nondimensional NET ECOSYSTEM EXCHANGE half-hourly
890 NEE_CUT_REF Net Ecosystem Exchange, using Constant Ustar Threshold (CUT) across years, reference selected on the basis of the model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
891 NEE_VUT_REF Net Ecosystem Exchange, using Variable Ustar Threshold (VUT) for each year, reference selected on the basis of the model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
892 NEE_CUT_REF_QC Quality flag for NEE_CUT_REF; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE half-hourly
893 NEE_VUT_REF_QC Quality flag for NEE_VUT_REF; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE half-hourly
894 NEE_CUT_REF_RANDUNC Random uncertainty for NEE_CUT_REF, from measured only data; uses only data points where NEE_CUT_REF_QC is 0 and two hierarchical methods - see header and NEE_CUT_REF_RANDUNC_METHOD µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
895 NEE_VUT_REF_RANDUNC Random uncertainty for NEE_VUT_REF, from measured only data; uses only data points where NEE_VUT_REF_QC is 0 and two hierarchical methods - see header and NEE_VUT_REF_RANDUNC_METHOD µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
896 NEE_CUT_REF_RANDUNC_METHOD Method used to estimate the random uncertainty of NEE_CUT_REF; 1 = RANDUNC Method 1 (direct SD method), 2 = RANDUNC Method 2 (median SD method) nondimensional NET ECOSYSTEM EXCHANGE half-hourly
897 NEE_VUT_REF_RANDUNC_METHOD Method used to estimate the random uncertainty of NEE_VUT_REF; 1 = RANDUNC Method 1 (direct SD method), 2 = RANDUNC Method 2 (median SD method) nondimensional NET ECOSYSTEM EXCHANGE half-hourly
898 NEE_CUT_REF_RANDUNC_N Number of data points used to estimate the random uncertainty of NEE_CUT_REF; nondimensional NET ECOSYSTEM EXCHANGE half-hourly
899 NEE_VUT_REF_RANDUNC_N Number of data points used to estimate the random uncertainty of NEE_VUT_REF; nondimensional NET ECOSYSTEM EXCHANGE half-hourly
900 NEE_CUT_REF_JOINTUNC Joint uncertainty estimation for NEE_CUT_REF, including random uncertainty and USTAR filtering uncertainty; [SQRT(NEE_CUT_REF_RANDUNC^2 + ((NEE_CUT_84 - NEE_CUT_16) / 2)^2)] for each half-hour µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
901 NEE_VUT_REF_JOINTUNC Joint uncertainty estimation for NEE_VUT_REF, including random uncertainty and USTAR filtering uncertainty; [SQRT(NEE_VUT_REF_RANDUNC^2 + ((NEE_VUT_84 - NEE_VUT_16) / 2)^2)] for each half-hour µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
902 NEE_CUT_USTAR50 Net Ecosystem Exchange, using Constant Ustar Threshold (CUT) across years, from 50 percentile of USTAR threshold; µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
903 NEE_VUT_USTAR50 Net Ecosystem Exchange, using Variable Ustar Threshold (VUT) for each year, from 50 percentile of USTAR threshold; µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
904 NEE_CUT_USTAR50_QC Quality flag for NEE_CUT_USTAR50; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE half-hourly
905 NEE_VUT_USTAR50_QC Quality flag for NEE_VUT_USTAR50; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE half-hourly
906 NEE_CUT_USTAR50_RANDUNC Random uncertainty for NEE_CUT_USTAR50, from measured only data; uses only data points where NEE_CUT_USTAR50_QC is 0 and two hierarchical methods - see header and NEE_CUT_USTAR50_RANDUNC_METHOD µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
907 NEE_VUT_USTAR50_RANDUNC Random uncertainty for NEE_VUT_USTAR50, from measured only data; uses only data points where NEE_VUT_USTAR50_QC is 0 and two hierarchical methods see header and NEE_VUT_USTAR50_RANDUNC_METHOD µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
908 NEE_CUT_USTAR50_RANDUNC_METHOD Method used to estimate the random uncertainty of NEE_CUT_USTAR50; 1 = RANDUNC Method 1 (direct SD method), 2 = RANDUNC Method 2 (median SD method) nondimensional NET ECOSYSTEM EXCHANGE half-hourly
909 NEE_VUT_USTAR50_RANDUNC_METHOD Method used to estimate the random uncertainty of NEE_VUT_USTAR50; 1 = RANDUNC Method 1 (direct SD method), 2 = RANDUNC Method 2 (median SD method) nondimensional NET ECOSYSTEM EXCHANGE half-hourly
910 NEE_CUT_USTAR50_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of NEE_CUT_USTAR50; nondimensional NET ECOSYSTEM EXCHANGE half-hourly
911 NEE_VUT_USTAR50_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of NEE_VUT_USTAR50; nondimensional NET ECOSYSTEM EXCHANGE half-hourly
912 NEE_CUT_USTAR50_JOINTUNC Joint uncertainty estimation for NEE_CUT_USTAR50, including random uncertainty and USTAR filtering uncertainty; [SQRT(NEE_CUT_USTAR50_RANDUNC^2 + ((NEE_CUT_84 - NEE_CUT_16) / 2)^2)] for each half-hour µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
913 NEE_VUT_USTAR50_JOINTUNC Joint uncertainty estimation for NEE_VUT_USTAR50, including random uncertainty and USTAR filtering uncertainty; [SQRT(NEE_VUT_USTAR50_RANDUNC^2 + ((NEE_VUT_84 - NEE_VUT_16) / 2)^2)] for each half-hour µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
914 NEE_CUT_MEAN Net Ecosystem Exchange, using Constant Ustar Threshold (CUT) across years, average from 40 NEE_CUT_XX versions; average from 40 half-hourly NEE_CUT_XX µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
915 NEE_VUT_MEAN Net Ecosystem Exchange, using Variable Ustar Threshold (VUT) for each year, average from 40 NEE_VUT_XX versions; average from 40 half-hourly NEE_CUT_XX µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
916 NEE_CUT_MEAN_QC Quality flag for NEE_CUT_MEAN, fraction between 0-1 indicating percentage of good quality data; average of percentages of good data (NEE_CUT_XX_QC is 0 or 1) from 40 NEE_CUT_XX_QC nondimensional NET ECOSYSTEM EXCHANGE half-hourly
917 NEE_VUT_MEAN_QC Quality flag for NEE_VUT_MEAN, fraction between 0-1 indicating percentage of good quality data; average of percentages of good data (NEE_VUT_XX_QC is 0 or 1) from 40 NEE_VUT_XX_QC nondimensional NET ECOSYSTEM EXCHANGE half-hourly
918 NEE_CUT_SE Standard Error for NEE_CUT, calculated as SD(NEE_CUT_XX) / SQRT(40); SE from 40 half-hourly NEE_CUT_XX µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
919 NEE_VUT_SE Standard Error for NEE_VUT, calculated as SD(NEE_VUT_XX) / SQRT(40); SE from 40 half-hourly NEE_CUT_XX µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
920 NEE_CUT_XX NEE CUT percentiles (approx. percentile indicated by XX, see doc.) calculated from the 40 estimates aggregated at the different time resolutions -- XX = 05, 16, 25, 50, 75, 84, 95; XXth percentile from 40 half-hourly NEE_CUT_XX µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
921 NEE_VUT_XX NEE VUT percentiles (approx. percentile indicated by XX, see doc.) calculated from the 40 estimates aggregated at the different time resolutions -- XX = 05, 16, 25, 50, 75, 84, 95; XXth percentile from 40 half-hourly NEE_VUT_XX µmolCO2 m-2 s-1 NET ECOSYSTEM EXCHANGE half-hourly
922 NEE_CUT_XX_QC Quality flag for NEE_CUT_XX -- XX = 05, 16, 25, 50, 75, 84, 95; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE half-hourly
923 NEE_VUT_XX_QC Quality flag for NEE_VUT_XX -- XX = 05, 16, 25, 50, 75, 84, 95; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE half-hourly
924 RECO_NT_VUT_REF Ecosystem Respiration, from Nighttime partitioning method, reference selected from RECO versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
925 RECO_NT_VUT_USTAR50 Ecosystem Respiration, from Nighttime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
926 RECO_NT_VUT_MEAN Ecosystem Respiration, from Nighttime partitioning method, average from RECO versions, each from corresponding NEE_VUT_XX version; average from 40 half-hourly RECO_NT_VUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
927 RECO_NT_VUT_SE Standard Error for Ecosystem Respiration, calculated as (SD(RECO_NT_VUT_XX) / SQRT(40)); SE from 40 half-hourly RECO_NT_CUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
928 RECO_NT_VUT_XX Ecosystem Respiration, from Nighttime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
929 RECO_NT_CUT_REF Ecosystem Respiration, from Nighttime partitioning method, reference selected from RECO versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
930 RECO_NT_CUT_USTAR50 Ecosystem Respiration, from Nighttime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
931 RECO_NT_CUT_MEAN Ecosystem Respiration, from Nighttime partitioning method, average from RECO versions, each from corresponding NEE_CUT_XX version; average from 40 half-hourly RECO_NT_CUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
932 RECO_NT_CUT_SE Standard Error for Ecosystem Respiration, calculated as (SD(RECO_NT_CUT_XX) / SQRT(40)); SE from 40 half-hourly RECO_NT_CUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
933 RECO_NT_CUT_XX Ecosystem Respiration, from Nighttime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
934 GPP_NT_VUT_REF Gross Primary Production, from Nighttime partitioning method, reference selected from GPP versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
935 GPP_NT_VUT_USTAR50 Gross Primary Production, from Nighttime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
936 GPP_NT_VUT_MEAN Gross Primary Production, from Nighttime partitioning method, average from GPP versions, each from corresponding NEE_VUT_XX version; average from 40 half-hourly GPP_NT_VUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
937 GPP_NT_VUT_SE Standard Error for Gross Primary Production, calculated as (SD(GPP_NT_VUT_XX) / SQRT(40)); SE from 40 half-hourly GPP_NT_VUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
938 GPP_NT_VUT_XX Gross Primary Production, from Nighttime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
939 GPP_NT_CUT_REF Gross Primary Production, from Nighttime partitioning method, reference selected from GPP versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
940 GPP_NT_CUT_USTAR50 Gross Primary Production, from Nighttime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
941 GPP_NT_CUT_MEAN Gross Primary Production, from Nighttime partitioning method, average from GPP versions, each from corresponding NEE_CUT_XX version; average from 40 half-hourly GPP_NT_CUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
942 GPP_NT_CUT_SE Standard Error for Gross Primary Production, calculated as (SD(GPP_NT_CUT_XX) / SQRT(40)); SE from 40 half-hourly GPP_NT_CUT_XX µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
943 GPP_NT_CUT_XX Gross Primary Production, from Nighttime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING half-hourly
944 RECO_DT_VUT_REF Ecosystem Respiration, from Daytime partitioning method, reference selected from RECO versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
945 RECO_DT_VUT_USTAR50 Ecosystem Respiration, from Daytime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
946 RECO_DT_VUT_MEAN Ecosystem Respiration, from Daytime partitioning method, average from RECO versions, each from corresponding NEE_VUT_XX version; average from 40 half-hourly RECO_DT_VUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
947 RECO_DT_VUT_SE Standard Error for Ecosystem Respiration, calculated as (SD(RECO_DT_VUT_XX) / SQRT(40)); SE from 40 half-hourly RECO_DT_VUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
948 RECO_DT_VUT_XX Ecosystem Respiration, from Daytime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
949 RECO_DT_CUT_REF Ecosystem Respiration, from Daytime partitioning method, reference selected from RECO versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
950 RECO_DT_CUT_USTAR50 Ecosystem Respiration, from Daytime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
951 RECO_DT_CUT_MEAN Ecosystem Respiration, from Daytime partitioning method, average from RECO versions, each from corresponding NEE_CUT_XX version; average from 40 half-hourly RECO_DT_CUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
952 RECO_DT_CUT_SE Standard Error for Ecosystem Respiration, calculated as (SD(RECO_DT_CUT_XX) / SQRT(40)); SE from 40 half-hourly RECO_DT_CUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
953 RECO_DT_CUT_XX Ecosystem Respiration, from Daytime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
954 GPP_DT_VUT_REF Gross Primary Production, from Daytime partitioning method, reference selected from GPP versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
955 GPP_DT_VUT_USTAR50 Gross Primary Production, from Daytime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
956 GPP_DT_VUT_MEAN Gross Primary Production, from Daytime partitioning method, average from GPP versions, each from corresponding NEE_VUT_XX version; average from 40 half-hourly GPP_DT_VUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
957 GPP_DT_VUT_SE Standard Error for Gross Primary Production, calculated as (SD(GPP_DT_VUT_XX) / SQRT(40)); SE from 40 half-hourly GPP_DT_VUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
958 GPP_DT_VUT_XX Gross Primary Production, from Daytime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
959 GPP_DT_CUT_REF Gross Primary Production, from Daytime partitioning method, reference selected from GPP versions using model efficiency (MEF). The MEF analysis is repeated for each time aggregation; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
960 GPP_DT_CUT_USTAR50 Gross Primary Production, from Daytime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
961 GPP_DT_CUT_MEAN Gross Primary Production, from Daytime partitioning method, average from GPP versions, each from corresponding NEE_CUT_XX version; average from 40 half-hourly GPP_DT_CUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
962 GPP_DT_CUT_SE Standard Error for Gross Primary Production, calculated as (SD(GPP_DT_CUT_XX) / SQRT(40)); SE from 40 half-hourly GPP_DT_CUT_XX µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
963 GPP_DT_CUT_XX Gross Primary Production, from Daytime partitioning method (with XX = 05, 16, 25, 50, 75, 84, 95); µmolCO2 m-2 s-1 DAYTIME PARTITIONING half-hourly
964 RECO_SR Ecosystem Respiration, from Sundown Respiration partitioning method; µmolCO2 m-2 s-1 SUNDOWN half-hourly
LABEL DESCRIPTION UNIT (preferred) or FORMAT CATEGORY TIME RESOLUTION

 

 

Last Updated on 27 Aug 2023 00:01