Variable Abbreviations


This list gives an overview of variables commonly used in eddy covariance ecosystem research.

Note: use the search bar above the table to find specific items.

 

wdt_ID Label Description Units (preferred) or format Category Used In
1 #gfRF Gap-filled using random forest same as input var DIIVE
520 #odAL Outliers were removed using outlier detection: absolute limits same as input var DIIVE
521 (footprint) model Model for footprint estimation - EddyPro (_full_output_ file)
522 (z-d)/L Monin-Obukhov stability parameter # EddyPro (_full_output_ file)
523 _CUT_ constant USTAR threshold across years
524 f (suffix) Original values and gaps filled with mean of selected datapoints (condition depending on gap filling method) ReddyProc
525 fall (suffix) All values considered as gaps (for uncertainty estimates) ReddyProc
526 fall_qc (suffix) All values considered as gaps (for uncertainty estimates) ReddyProc
527 fmeth / FMETH (suffix) Method used for gap filling: 1 = similar meteo condition (sFillLUT with Rg, VPD, Tair) 2 = similar meteo (sFillLUT with Rg only) 3 = mean diurnal course (sFillMDC)) ReddyProc
528 fnum (suffix) Number of datapoints used for gap filling # ReddyProc
529 fqc / FQC (suffix) Quality flag assigned depending on gap filling method and window length: 0 = original, 1 = most reliable, 2 = medium, 3 = least reliable # ReddyProc
530 _fsd / _FSD (suffix) Standard deviation of datapoints used for gap filling (uncertainty) ReddyProc
531 _fsdu (suffix) Standard deviation across uStar thresholds (uncertainty, bias) ReddyProc
532 _fsdug (suffix) Combination of random uncertainty and uncertainty due to USTAR: sqrt(fsd^2 + fsdu^2) ReddyProc
533 _fwin (suffix) Full window length used for gap filling ReddyProc
534 _orig (suffix) Original values used for gap filling ReddyProc
535 _QCF0 (suffix) measured (not gap-filled) data of highest quality DIIVE
536 _QCF01 (suffix) measured (not gap-filled) data of highest and OK quality DIIVE
537 _SCF (suffix) Spectral correction factor for the respective flux #
538 _sd / _SD (suffix) Standard deviation ReddyProc
539 _SUT_ seasonal USTAR threshold, seasons are specified by the user
540 _Thres (suffix) the threshold of uStar values used to mark insufficient conditions m s-1 ReddyProc
541 _U05 (suffix) low estimate (5% quantile of the bootstrapped uncertainty distribution) ReddyProc
542 _U50 (suffix) median estimate (50% quantile of the bootstrapped uncertainty distribution) ReddyProc
543 _U95 (suffix) high estimate (95% quantile of the bootstrapped uncertainty distribution) ReddyProc
544 _uStar (suffix) estimate on the original unbootstrapped data ReddyProc
545 _VUT_ variable USTAR threshold for each year
546 abs_lim Hard flags for individual variables for absolute limits HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
547 AGC Automatic Gain Control LI-7500 % EC raw data files (ASCII)
548 AGC Mean value of AGC for LI‑7500RS or LI‑7200RS % EddyPro (_full_output_ file)
549 air_density Density of ambient air kg m-3 EddyPro (_full_output_ file)
550 air_heat_capactiy Specific heat at constant pressure of ambient air J K-1 kg-1 EddyPro (_full_output_ file)
551 air_molar_volume Molar volume of ambient air m3 mol-1 EddyPro (_full_output_ file)
552 air_pressure Mean pressure of ambient air, either calculated from high frequency air pressure readings, or estimated based on site altitude (barometric pressure) Pa EddyPro (_full_output_ file)
553 air_temperature Mean temperature of ambient air, either calculated from high frequency air temperature readings, or estimated from sonic temperature K EddyPro (_full_output_ file)
554 ALB Albedo, range 0-100 % Ameriflux
555 amp_res Hard flags for individual variables for amplitude resolution HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
556 APAR Absorbed PAR µmolPhoton m-2 s-1 Ameriflux
557 ATM Atmospheric -
558 attack_angle Hard flag for attack angle test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
559 AVG Average -
560 AW All-wave radiation
561 AW_IN All-wave incoming radiation without correction (Pyrradiometer) W m–2
562 AW_OUT All-wave outgoing radiation without correction (Pyrradiometer) W m–2
563 BAK Backup measurement, e.g. used at ICOS station CH-DAV
564 BC Below Canopy -
565 BD Bulk density g cm-3
566 BICO Python script for BInary COnversion of EC raw data binary files to ASCII format - BICO
567 bowen_ratio Sensible heat flux to latent heat flux ratio # EddyPro (_full_output_ file)
568 BV_EC Battery Voltage EC system V
569 BV_iDL Internal Battery Voltage Logger V (location and replicate number is essential)
570 CH4 CH4 molar fraction (in humid air), wet mole fraction nmol mol-1, µmol mol-1
571 CH4_DRY CH4 dry mole fraction (in dry air), mixing ratio, ppb nmol mol-1 EC raw data files (ASCII)
572 CH4_MIXING_RATIO Methane (CH4) in mole fraction of dry air nmolCH4 mol-1 Ameriflux
573 CH4_QCL_CMB CH4 concentration from QCL for chamber system ppb (nmol CH4 mol-1)
574 CH4_QCL_EC CH4 concentration from QCL for eddy system ppb (nmol CH4 mol-1)
575 CH4_QCL_PRF CH4 concentration from QCL for profile system ppb (nmol CH4 mol-1)
576 CM Chamber -
577 CMB Chamber -
578 CNT Suffix for counts -
579 CO Carbon Monoxide (CO) mole fraction in wet air nmolCO mol-1 Ameriflux
580 CO2 Carbon Dioxide (CO2) in mole fraction of wet air umolCO2 mol-1 ICOS / Ameriflux
581 CO2_BOLE tree stem CO2 vol%
582 CO2_CONC CO2 concentration density, molar density mmol m-3 EC raw data files (ASCII)
583 CO2_DRY CO2 dry mole fraction (in dry air), mixing ratio, ppm (parts per million) µmol CO2 mol-1 EC raw data files (ASCII)
584 CO2_DRY Carbon Dioxide (CO2) in mole fraction of dry air umolCO2 mol-1 ICOS
585 CO2_DRY_n Profile level-specific carbon dioxide in mole fraction of dry air averaged over the whole respective half-hour (_n is an integer number going from 1 to n top-down) umolCO2 mol-1 ICOS
586 CO2_DRY_n_SE Standard error of profile level-specific carbon dioxide in mole fraction of dry air as estimenated over the whole respective half-hour (_n is an integer number going from 1 to n top-down) umolCO2 mol-1 ICOS
587 CO2_F_MDS CO2 mole fraction, gapfilled with MDS; µmolCO2 mol-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
588 CO2_F_MDS CO2 mole fraction, gapfilled with MDS µmolCO2 mol-1 ICOS / FLUXNET
589 CO2_F_MDS_QC Quality flag for CO2_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
590 CO2_F_MDS_QC Quality flag for CO2_F_MDS. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
591 CO2_HD10_FLAG Flag for the homogeneity test applied on differenced carbon dioxide 0: negligible evidences of error, IF HD10_STAT1) nondimensional ICOS
592 CO2_HD10_STAT Statistic of the homogeneity test applied on differenced carbon dioxide (percentage of data exceeding ñ10?) % ICOS
593 CO2_HD5_FLAG Flag for the homogeneity test applied on differenced carbon dioxide (0: negligible evidences of error, IF HD5_STAT4) nondimensional ICOS
594 CO2_HD5_STAT Statistic of the homogeneity test applied on differenced carbon dioxide (percentage of data exceeding ñ5?) % ICOS
595 CO2_HF10_FLAG Flag for the homogeneity test applied on carbon dioxide fluctuations (0: negligible evidences of error, IF HF10_STAT1) nondimensional ICOS
596 CO2_HF10_STAT Statistic of the homogeneity test applied on carbon dioxide fluctuations (percentage of data exceeding ñ10?) % ICOS
597 CO2_HF5_FLAG Flag for the homogeneity test applied on carbon dioxide fluctuations (0: negligible evidences of error, IF HF5_STAT4) nondimensional ICOS
598 CO2_HF5_STAT Statistic of the homogeneity test applied on carbon dioxide fluctuations (percentage of data exceeding ñ5?) % ICOS
599 CO2_IRGA70_CMB CO2 concentration from IRGA Li-7000 for chamber system µmol CO2 mol-1
600 CO2_IRGA70_EC CO2 concentration from IRGA Li-7000 for eddy system µmol CO2 mol-1
601 CO2_IRGA70_PRF CO2 concentration from IRGA Li-7000 for profile µmol CO2 mol-1
602 CO2_IRGA70_STM CO2 concentration from IRGA Li-7000, in stem µmol CO2 mol-1
603 CO2_IRGA72_CMB CO2 concentration from IRGA Li-7200 for chamber system µmol CO2 mol-1
604 CO2_IRGA72_EC CO2 concentration from IRGA Li-7200 for eddy system µmol CO2 mol-1
605 CO2_IRGA72_PRF CO2 concentration from IRGA Li-7200 for profile µmol CO2 mol-1
606 CO2_IRGA72_STM CO2 concentration from IRGA Li-7200, in stem µmol CO2 mol-1
607 CO2_IRGA75_CMB CO2 concentration from IRGA Li-7500 for chamber system µmol CO2 mol-1
608 CO2_IRGA75_EC CO2 concentration from IRGA Li-7500 for eddy system µmol CO2 mol-1
609 CO2_IRGA75_PRF CO2 concentration from IRGA Li-7500 for profile µmol CO2 mol-1
610 CO2_IRGA75_STM CO2 concentration from IRGA Li-7500, in stem µmol CO2 mol-1
611 CO2_KID_FLAG Flag for the CO2_KID_STAT (0: negligible evidences of error, IF KID_STAT50) nondimensional ICOS
612 CO2_KID_STAT Kurtosis Index of Differenced carbon dioxide nondimensional ICOS
613 CO2_MIXING_RATIO Carbon Dioxide (CO2) in mole fraction of dry air µmolCO2 mol-1 Ameriflux
614 CO2_SIGMA Standard deviation of carbon dioxide mole fraction in wet air µmolCO2 mol-1 Ameriflux
615 CO2_SIGMA Standard deviation of carbon dioxide in mole fraction of wet air umolCO2 mol-1 ICOS
616 CO2C13 Stable isotopic composition of CO2 - C13 (i.e., d13C of CO2) ‰ (permil) Ameriflux
617 COND_WATER Conductivity (i.e., electrical conductivity) of water µS cm-1 Ameriflux
618 COOLER_V Cooler voltage V EC raw data files (ASCII)
619 CUP Cup Anemometer -
620 D Depth -
621 D_SNOW Snow depth cm, m Ameriflux
622 DATA_SIZE Data size of instrument data block, number of bytes in instrument record bytes EC raw data files (ASCII)
623 DATE date yyyy-mm-dd
624 date Date of the end of the averaging period yyyy-mm-dd EddyPro (_full_output_ file)
625 DAY 2 digit day of month dd
626 DBH diameter of tree measured at breast height(1.3 m) cm
627 DBH Diameter of tree measured at breast height (1.3m) with continuous dendrometers cm Ameriflux
628 DENDRO Dendrometer mm
629 DIF Diffuse -
630 discontinuities Hard flags for individual variables for discontinuities test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
631 discontinuities Soft flags for individual variables for discontinuities test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
632 DNTP Time Difference between NTP Clock and Clock msec
633 DO Dissolved oxygen in water µmol L-1 Ameriflux
634 DOC Dissolved organic carbon mg l-1
635 DOY 3 digit day of year ddd
636 drop_out Hard flags for individual variables for drop-out test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
637 DT Daytime (used in partitioning) - Fluxes
638 e Ambient water vapor partial pressure Pa EddyPro (_full_output_ file)
639 E0 activation energy parameter (K) in relationship between temperature and nighttime NEE from night-time partitioning ReddyProc
640 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 FLUXNET HH (half-hourly)
641 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 ICOS / FLUXNET
642 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 FLUXNET HH (half-hourly)
643 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). nondimensional ICOS / FLUXNET
644 EC Eddy covariance - Fluxes
645 EP EddyPro Flux Calculation Software -
646 es Ambient water vapor partial pressure at saturation Pa EddyPro (_full_output_ file)
647 ET Evapotranspiration flux mm hour-1 EddyPro (_full_output_ file)
648 ET_f Gap-filled evapotranspiration flux, calculated from gap-filled LE mmol H20 m-2 s-1 ReddyProc
649 EXT External -
650 extravar_mean Mean value of extravar (‡) EddyPro (_full_output_ file)
651 FAPAR Fraction of absorbed PAR, range 0-100 % Ameriflux
652 FC Carbon Dioxide (CO2) turbulent flux (no storage correction) umolCO2 m-2 s-1 ICOS / Ameriflux
653 FC_FMR_FLAG Flag for the FMR test for FC (0: negligible evidences of error, IF FMR15) nondimensional ICOS
654 FC_FMR_STAT Fraction of Missing Records in raw, high-frequency, data used for FC flux estimation % ICOS
655 FC_LGD_FLAG Flag for the LGD test for FC (0: negligible evidences of error, IF LGD180) nondimensional ICOS
656 FC_LGD_STAT Longest Gap Duration in raw, high-frequency, data used for FC flux estimation seconds ICOS
657 FC_LSR_FLAG Flag for the LSR test for FC (0: negligible evidences of error, IF LSR_STAT>0.995; 1: moderate evidences of error, IF 0.99?LSR_STAT?0.995; 2: severe evidences of error, IF LSR_STAT nondimensional ICOS
658 FC_LSR_STAT Statistic of the Low Signal Resolution test for FC nondimensional ICOS
659 FC_M98_FLAG Flag of the FC_M98_STAT (0: negligible evidences of error, IF M_98_STAT3) nondimensional ICOS
660 FC_M98_STAT Statistic of the nonstationarity ratio test by Mahrt (1998) for FC nondimensional ICOS
661 FC_SCF_STAT Spectral correction factor for NEE nondimensional ICOS
662 FC_SSITC_TEST Results of the quality flagging for FC according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
663 FC_SSITC_TEST Quality flagging for FC according to classification scheme by Foken et al (2004) and based on the combination of the results of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (0: high quality; 1:intermediate quality; 2: low quality). Currently not used in the data cleaning procedure. nondimensional ICOS
664 FCH4 Methane (CH4) turbulent flux (no storage correction) nmolCH4 m-2 s-1 Ameriflux
665 FCH4_SSITC_TEST Results of the quality flagging for FCH4 according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
666 FETCH_70 Distance at which footprint cumulative probability is 70% m
667 FETCH_70 Distance at which cross-wind integrated footprint cumulative probability is 70% m ICOS
668 FETCH_80 Distance at which footprint cumulative probability is 80% m
669 FETCH_80 Distance at which cross-wind integrated footprint cumulative probability is 80% m ICOS
670 FETCH_90 Distance at which footprint cumulative probability is 90% m
671 FETCH_90 Distance at which cross-wind integrated footprint cumulative probability is 90% m ICOS
672 FETCH_FILTER Footprint quality flag (i.e., 0, 1): 0 and 1 indicate data measured when wind coming from direction that should be discarded and kept, respectively nondimensional Ameriflux
673 FETCH_MAX Distance at which footprint contribution is maximum m
674 FETCH_MAX Distance at which cross-wind integrated footprint contribution is maximum m ICOS
675 file_records Number of valid records found in the raw file (or set of raw files) # EddyPro (_full_output_ file)
676 filename Name of the raw file (or the first of a set) from which the dataset for the current averaging interval was extracted - EddyPro (_full_output_ file)
677 FIPAR Fraction of intercepted PAR, range 0-100 % Ameriflux
678 FIT_FLAG Fit flag flag EC raw data files (ASCII)
679 FLOW_VOLRATE Volume flow rate in the sampling line L min-1 EC raw data files (ASCII)
680 FN2O Nitrous oxide (N2O) turbulent flux (no storage correction) nmolN2O m-2 s-1 Ameriflux
681 FN2O_SSITC_TEST Results of the quality flagging for FN2O according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
682 FNO Nitric oxide (NO) turbulent flux (no storage correction) nmolNO m-2 s-1 Ameriflux
683 FNO_SSITC_TEST Results of the quality flagging for FNO according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
684 FNO2 Nitrogen dioxide (NO2) turbulent flux (no storage correction) nmolNO2 m-2 s-1 Ameriflux
685 FNO2_SSITC_TEST Results of the quality flagging for FNO2 according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
686 FO3 Ozone (O3) turbulent flux (no storage correction) nmolO3 m-2 s-1 Ameriflux
687 FO3_SSITC_TEST Results of the quality flagging for FO3 according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
688 FOG Fog presence
689 FOOTPRINT_80_SURF 2D footprint 80% isoplethe area m2 ICOS
690 FOOTPRINT_FLAG Footprint flag (0, 1, 2, 3). 0 = data used for footprint, 1 = 2D footprint model flag error, 2 = not all 2D footprint model isoplethes within specified domain, 3 = data removed because of invalid conditions for footprint model nondimensional ICOS
691 FOOTPRINT_TA_CONTR Cumulative footprint contribution of the footprint/target area intersection % ICOS
692 FOOTPRINT_TA_SURF Area of footprint/target area intersection m2 ICOS
693 FP Flux partitioning ReddyProc
694 FP__sd estimated standard devation of X ReddyProc
695 FP_alpha canopy light utilization efficiency and represents the initial slope of the light–response curve (daytime partitioning) ReddyProc
696 FP_beta maximum CO2 uptake rate of the canopy at light saturation (μmol m-2 s-1) (daytime partitioning) μmol m-2 s-1 ReddyProc
697 FP_dRecPar records until or after closest record that has a parameter estimate associated (daytime partitioning) ReddyProc
698 FP_E0 activation energy parameter (K) in relationship between temperature and nighttime NEE from day-time partitioning ReddyProc
699 FP_GPP2000 GPP at incoming radiation of 2000 Wm-2, more robust alternative to saturation FP_k ReddyProc
700 FP_k parameter controlling the VPD limitation of GPP (daytime partitioning) (daytime partitioning) ReddyProc
701 FP_qc quality flag of the estimated parameters: 0: good parameter fit, 1: some parameters out of range, required refit, 2: next parameter estimate is more than two weeks away (daytime partitioning) ReddyProc
702 FP_RRef respiration at reference temperature parameter (μmol m-2 s-1 as NEE) in relationship between temperature and nighttime NEE from day-time partitioning μmol m-2 s-1 ReddyProc
703 FP_RRef_Night same as FP_RRef using the same FP_E0, but from intermedate step based on night-time data ReddyProc
704 G Soil heat flux W m-2 Ameriflux
705 G_F_MDS Soil heat flux; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
706 G_F_MDS Soil heat flux W m-2 ICOS / FLUXNET
707 G_F_MDS_QC Quality flag of G_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ENERGY PROCESSING FLUXNET HH (half-hourly)
708 G_F_MDS_QC Quality flag of G_F_MDS. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
709 G_SF calibration/sensitivity factor of G uV (W m-2)-1
710 GA_DIAG_CODE GA diagnostic value # EC raw data files (ASCII)
711 GA_DIAG_FLAG Flag for gas analyzer (GA) instrumental diagnostics (0: negligible evidences of error; 2: severe evidences of error) nondimensional ICOS
712 gas_def_timelag Flag: whether the reported time lag is the default (T) or calculated (F) T/F EddyPro (_full_output_ file)
713 gas_flux Corrected gas flux µmol m-2 s-1(†) EddyPro (_full_output_ file)
714 gas_mixing_ratio Measured or estimated mixing ratio of gas µmol mol-1(†) EddyPro (_full_output_ file)
715 gas_molar_density Measured or estimated molar density of gas mmol m-3 EddyPro (_full_output_ file)
716 gas_mole_fraction Measured or estimated mole fraction of gas µmol mol-1(†) EddyPro (_full_output_ file)
717 gas_scf Spectral correction factor for gas flux # EddyPro (_full_output_ file)
718 gas_strg Estimate of storage gas flux µmol s-1 m-2(†) EddyPro (_full_output_ file)
719 gas_time_lag Time lag used to synchronize gas time series s EddyPro (_full_output_ file)
720 gas_v-adv Estimate of vertical advection flux µmol s-1 m-2(†) EddyPro (_full_output_ file)
721 GPP Gross Primary Productivity (nighttime-based) µmolCO2 m-2 s-1 Ameriflux
722 GPP_CUT_16_f Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) (nighttime-based), modelled from NEE_CUT_16_f μmol CO2 m-2 s-1
723 GPP_CUT_84_f Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) (nighttime-based), modelled from NEE_CUT_84_f μmol CO2 m-2 s-1
724 GPP_CUT_REF_f Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) (nighttime-based), modelled from NEE_CUT_REF_f μmol CO2 m-2 s-1
725 GPP_DT Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) estimated by day-time partitioning μmol m-2 s-1 ReddyProc
726 GPP_DT_CUT_05 Gross Primary Production, from Daytime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
727 GPP_DT_CUT_16 Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) estimated by day-time partitioning, modelled from NEE_CUT_16_f μmol m-2 s-1
728 GPP_DT_CUT_16 Gross Primary Production, from Daytime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
729 GPP_DT_CUT_25 Gross Primary Production, from Daytime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
730 GPP_DT_CUT_50 Gross Primary Production, from Daytime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
731 GPP_DT_CUT_75 Gross Primary Production, from Daytime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
732 GPP_DT_CUT_84 Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) estimated by day-time partitioning, modelled from NEE_CUT_84_f μmol m-2 s-1
733 GPP_DT_CUT_86 Gross Primary Production, from Daytime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
734 GPP_DT_CUT_95 Gross Primary Production, from Daytime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
735 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 FLUXNET HH (half-hourly)
736 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 ICOS / FLUXNET
737 GPP_DT_CUT_REF Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) estimated by day-time partitioning, modelled from NEE_CUT_REF_f μmol m-2 s-1
738 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 FLUXNET HH (half-hourly)
739 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 ICOS / FLUXNET
740 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 FLUXNET HH (half-hourly)
741 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 ICOS / FLUXNET
742 GPP_DT_CUT_USTAR50 Gross Primary Production, from Daytime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING FLUXNET HH (half-hourly)
743 GPP_DT_CUT_USTAR50 Gross Primary Production, from Daytime partitioning method, based on NEE_CUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
744 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 FLUXNET HH (half-hourly)
745 GPP_DT_VUT_05 Gross Primary Production, from Daytime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
746 GPP_DT_VUT_16 Gross Primary Production, from Daytime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
747 GPP_DT_VUT_25 Gross Primary Production, from Daytime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
748 GPP_DT_VUT_50 Gross Primary Production, from Daytime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
749 GPP_DT_VUT_75 Gross Primary Production, from Daytime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
750 GPP_DT_VUT_86 Gross Primary Production, from Daytime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
751 GPP_DT_VUT_95 Gross Primary Production, from Daytime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
752 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 FLUXNET HH (half-hourly)
753 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 ICOS / FLUXNET
754 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 FLUXNET HH (half-hourly)
755 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 ICOS / FLUXNET
756 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 FLUXNET HH (half-hourly)
757 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 ICOS / FLUXNET
758 GPP_DT_VUT_USTAR50 Gross Primary Production, from Daytime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING FLUXNET HH (half-hourly)
759 GPP_DT_VUT_USTAR50 Gross Primary Production, from Daytime partitioning method, based on NEE_VUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
760 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 FLUXNET HH (half-hourly)
761 GPP_f Gross primary production, i.e. influx to the land surface (μmol m-2 s-1 as NEE) (nighttime-based) μmol m-2 s-1 ReddyProc
762 GPP_NT_CUT_05 Gross Primary Production, from Nighttime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
763 GPP_NT_CUT_16 Gross Primary Production, from Nighttime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
764 GPP_NT_CUT_25 Gross Primary Production, from Nighttime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
765 GPP_NT_CUT_50 Gross Primary Production, from Nighttime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
766 GPP_NT_CUT_75 Gross Primary Production, from Nighttime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
767 GPP_NT_CUT_86 Gross Primary Production, from Nighttime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
768 GPP_NT_CUT_95 Gross Primary Production, from Nighttime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
769 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 FLUXNET HH (half-hourly)
770 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 ICOS / FLUXNET
771 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 FLUXNET HH (half-hourly)
772 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 ICOS / FLUXNET
773 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 FLUXNET HH (half-hourly)
774 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 ICOS / FLUXNET
775 GPP_NT_CUT_USTAR50 Gross Primary Production, from Nighttime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING FLUXNET HH (half-hourly)
776 GPP_NT_CUT_USTAR50 Gross Primary Production, from Nighttime partitioning method, based on NEE_CUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
777 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 FLUXNET HH (half-hourly)
778 GPP_NT_VUT_05 Gross Primary Production, from Nighttime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
779 GPP_NT_VUT_16 Gross Primary Production, from Nighttime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
780 GPP_NT_VUT_25 Gross Primary Production, from Nighttime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
781 GPP_NT_VUT_50 Gross Primary Production, from Nighttime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
782 GPP_NT_VUT_75 Gross Primary Production, from Nighttime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
783 GPP_NT_VUT_86 Gross Primary Production, from Nighttime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
784 GPP_NT_VUT_95 Gross Primary Production, from Nighttime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
785 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 FLUXNET HH (half-hourly)
786 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 ICOS / FLUXNET
787 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 FLUXNET HH (half-hourly)
788 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 ICOS / FLUXNET
789 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 FLUXNET HH (half-hourly)
790 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 ICOS / FLUXNET
791 GPP_NT_VUT_USTAR50 Gross Primary Production, from Nighttime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING FLUXNET HH (half-hourly)
792 GPP_NT_VUT_USTAR50 Gross Primary Production, from Nighttime partitioning method, based on NEE_VUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
793 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 FLUXNET HH (half-hourly)
794 GS Stomatal Conductance mmol H2O m-2 s-1
795 GWL Ground Water Level m
796 H Corrected sensible heat flux (no storage correction) W m-2
797 H Corrected sensible heat flux W m-2 EddyPro (_full_output_ file)
798 H Sensible heat turbulent flux (no storage correction, cleaned) W m-2 ICOS
799 H_CORR Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
800 H_CORR Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor W m-2 ICOS / FLUXNET
801 H_CORR_25 Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor, 25th percentile; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
802 H_CORR_25 Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor, 25th percentile W m-2 ICOS / FLUXNET
803 H_CORR_75 Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor, 75th percentile; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
804 H_CORR_75 Sensible heat flux, corrected H_F_MDS by energy balance closure correction factor, 75th percentile W m-2 ICOS / FLUXNET
805 H_CORR_JOINTUNC Joint uncertainty estimation for H; [SQRT(H_RANDUNC^2 + ((H_CORR75 - H_CORR25) / 1.349)^2)] W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
806 H_CORR_JOINTUNC Joint uncertainty estimation for H. [SQRT(H_RANDUNC^2 + ((H_CORR75 - H_CORR25) / 1.349)^2)] W m-2 ICOS / FLUXNET
807 H_DATA_FLAG Flag for H (0: observed flux for which any quality control (QC) tests provided negligible evidences of error; 1: outlying flux rejected because at least one of the QC tests provided a moderate evidence of error; 2: flux removed because at least one of the QC test provided a severe evidence of error) nondimensional ICOS
808 H_F_MDS Sensible heat flux, gapfilled using MDS method; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
809 H_F_MDS Sensible heat flux, gapfilled using MDS method W m-2 ICOS / FLUXNET
810 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 FLUXNET HH (half-hourly)
811 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 ICOS / FLUXNET
812 H_FMR_FLAG Flag for the FMR test for H (0: negligible evidences of error, IF FMR15) nondimensional ICOS
813 H_FMR_STAT Fraction of Missing Records in raw, high-frequency, data used for H flux estimation % ICOS
814 H_LGD_FLAG Flag for the LGD test for H (0: negligible evidences of error, IF LGD180) nondimensional ICOS
815 H_LGD_STAT Longest Gap Duration in raw, high-frequency, data used for H flux estimation seconds ICOS
816 H_LSR_FLAG Flag for the LSR test for H (0: negligible evidences of error, IF LSR_STAT>0.995; 1: moderate evidences of error, IF 0.99?LSR_STAT?0.995; 2: severe evidences of error, IF LSR_STAT nondimensional ICOS
817 H_LSR_STAT Statistic of the Low Signal Resolution test for H nondimensional ICOS
818 H_M98_FLAG Flag of the H_M98_STAT (0: negligible evidences of error, IF M_98_STAT3) nondimensional ICOS
819 H_M98_STAT Statistic of the nonstationarity ratio test by Mahrt (1998) for H nondimensional ICOS
820 H_OOR_FLAG Flag for H denoting values out of the physically plausible range (0: within range; 2: out of range). nondimensional ICOS
821 H_OUTLYING_FLAG Flag for H denoting outliers (0: no outlying flux; 1: outlying flux) nondimensional ICOS
822 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 FLUXNET HH (half-hourly)
823 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 ICOS / FLUXNET
824 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 FLUXNET HH (half-hourly)
825 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 ICOS / FLUXNET
826 H_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of H; nondimensional ENERGY PROCESSING FLUXNET HH (half-hourly)
827 H_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of H nondimensional ICOS / FLUXNET
828 H_scf Spectral correction factor for sensible heat flux # EddyPro (_full_output_ file)
829 H_SCF_STAT Spectral correction factor for H nondimensional ICOS
830 H_SSITC_TEST Results of the quality flagging for H according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
831 H_SSITC_TEST Quality flagging for H according to classification scheme by Foken et al (2004) and based on the combination of the results of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (0: high quality; 1:intermediate quality; 2: low quality). Currently not used in the data cleaning procedure. nondimensional ICOS
832 H_strg Estimate of storage sensible heat flux W m-2 EddyPro (_full_output_ file)
833 H_UNCLEANED Sensible heat turbulent flux (no storage correction, uncleaned) W m-2 ICOS
834 H2O H2O molar fraction (in humid air), wet mole fraction umol mol-1 EC raw data files (ASCII)
835 H2O Water (H2O) vapor in mole fraction of wet air mmolH2O mol-1 ICOS
836 H2O_CONC H2O concentration density, molar density mmol m-3 EC raw data files (ASCII)
837 H2O_DRY H2O dry mole fraction (in dry air), mixing ratio, ppt (parts per THOUSAND) mmol mol-1 EC raw data files (ASCII)
838 H2O_DRY Water (H2O) vapor in mole fraction of dry air mmolH2O mol-1 ICOS
839 H2O_HD10_FLAG Flag for the homogeneity test applied on differenced water vapor 0: negligible evidences of error, IF HD10_STAT1) nondimensional ICOS
840 H2O_HD10_STAT Statistic of the homogeneity test applied on differenced water vapor (percentage of data exceeding ñ10?) % ICOS
841 H2O_HD5_FLAG Flag for the homogeneity test applied on differenced water vapor (0: negligible evidences of error, IF HD5_STAT4) nondimensional ICOS
842 H2O_HD5_STAT Statistic of the homogeneity test applied on differenced water vapor (percentage of data exceeding ñ5?) % ICOS
843 H2O_HF10_FLAG Flag for the homogeneity test applied on water vapor fluctuations (0: negligible evidences of error, IF HF10_STAT1) nondimensional ICOS
844 H2O_HF10_STAT Statistic of the homogeneity test applied on water vapor fluctuations (percentage of data exceeding ñ10?) % ICOS
845 H2O_HF5_FLAG Flag for the homogeneity test applied on water vapor fluctuations (0: negligible evidences of error, IF HF5_STAT4) nondimensional ICOS
846 H2O_HF5_STAT Statistic of the homogeneity test applied on water vapor fluctuations (percentage of data exceeding ñ5?) % ICOS
847 H2O_IRGA70_CMB H2O concentration from IRGA Li-7000 for chamber system mmol H2O mol-1
848 H2O_IRGA70_EC H2O concentration from IRGA Li-7000 for eddy system mmol H2O mol-1
849 H2O_IRGA70_PRF H2O concentration from IRGA Li-7000 for profile mmol H2O mol-1
850 H2O_IRGA72_CMB H2O concentration from IRGA Li-7200 for chamber system mmol H2O mol-1
851 H2O_IRGA72_EC H2O concentration from IRGA Li-7200 for eddy system mmol H2O mol-1
852 H2O_IRGA72_PRF H2O concentration from IRGA Li-7200 for profile mmol H2O mol-1
853 H2O_IRGA75_CMB H2O concentration from IRGA Li-7500 for chamber system mmol H2O mol-1
854 H2O_IRGA75_EC H2O concentration from IRGA Li-7500 for eddy system mmol H2O mol-1
855 H2O_IRGA75_PRF H2O concentration from IRGA Li-7500 for profile mmol H2O mol-1
856 H2O_KID_FLAG Flag for the H2O_KID_STAT (0: negligible evidences of error, IF KID_STAT50) nondimensional ICOS
857 H2O_KID_STAT Kurtosis Index of Differenced water vapor nondimensional ICOS
858 H2O_MIXING_RATIO Water (H2O) vapor in mole fraction of dry air mmolH2O mol-1 Ameriflux
859 H2O_n Profile level-specific water vapor in mole fraction of wet air averaged over the whole respective half-hour (_n is an integer number going from 1 to n top-down) mmolH2O mol-1 ICOS
860 H2O_n_SE Standard error of profile level-specific water vapor in mole fraction of wet air as estimenated over the whole respective half-hour (_n is an integer number going from 1 to n top-down) mmolH2O mol-1 ICOS
861 H2O_QCL_EC H2O concentration from QCL for eddy system ppb (nmol H2O mol-1)
862 H2O_SIGMA Standard deviation of water vapor mole fraction mmolH2O mol-1 ICOS / Ameriflux
863 HEAT_ Heating (prefix, e.g. for sonic heating)
864 HOUR 2 digit hour of the day HH
865 HS100 Sonic anemometer Gill HS-100 -
866 HS50 Sonic anemometer Gill HS-50 -
867 IN Incoming -
868 INC_X Inclinometer x ° EC raw data files (ASCII)
869 INC_XY Inclinometer, alternatively x (odd record numbers) and y (even record numbers) ° EC raw data files (ASCII)
870 INC_Y Inclinometer y ° EC raw data files (ASCII)
871 INT Internal -
872 IRGA Infrared Gas Analyzer -
873 IRGA62 Closed-path IRGA LI-6262 -
874 IRGA70 IRGA LI-7000 -
875 IRGA72 Enclosed-path IRGA Li-7200
876 IRGA75 Open-path IRGA Li-7500 -
877 ITC_FLAG Flag for the ITC test (0: negligible evidences of error, IF ITC_STAT50) nondimensional ICOS
878 ITC_STAT Statistic of the Integral Turbulence Characteristics test (Foken and Wichura, 1996) % ICOS
879 L Monin-Obukhov length M EddyPro (_full_output_ file)
880 LE Corrected latent heat flux W m-2 EddyPro (_full_output_ file)
881 LE Latent heat turbulent flux (no storage correction, cleaned) W m-2 ICOS
882 LE_CORR Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
883 LE_CORR Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor W m-2 ICOS / FLUXNET
884 LE_CORR_25 Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor, 25th percentile; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
885 LE_CORR_25 Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor, 25th percentile W m-2 ICOS / FLUXNET
886 LE_CORR_75 Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor, 75th percentile; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
887 LE_CORR_75 Latent heat flux, corrected LE_F_MDS by energy balance closure correction factor, 75th percentile W m-2 ICOS / FLUXNET
888 LE_CORR_JOINTUNC Joint uncertainty estimation for LE; [SQRT(LE_RANDUNC^2 + ((LE_CORR75 - LE_CORR25) / 1.349)^2)] W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
889 LE_CORR_JOINTUNC Joint uncertainty estimation for LE. [SQRT(LE_RANDUNC^2 + ((LE_CORR75 - LE_CORR25) / 1.349)^2)] W m-2 ICOS / FLUXNET
890 LE_DATA_FLAG Flag for LE (0: observed flux for which any quality control (QC) tests provided negligible evidences of error; 1: outlying flux rejected because at least one of the QC tests provided a moderate evidence of error; 2: flux removed because at least one of the QC test provided a severe evidence of error) nondimensional ICOS
891 LE_f gapfilled latent heat flux, filtered by all quality checks W m-2
892 LE_F_MDS Latent heat flux, gapfilled using MDS method; W m-2 ENERGY PROCESSING FLUXNET HH (half-hourly)
893 LE_F_MDS Latent heat flux, gapfilled using MDS method W m-2 ICOS / FLUXNET
894 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 FLUXNET HH (half-hourly)
895 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 ICOS / FLUXNET
896 LE_FMR_FLAG Flag for the FMR test for LE (0: negligible evidences of error, IF FMR15) nondimensional ICOS
897 LE_FMR_STAT Fraction of Missing Records in raw, high-frequency, data used for LE flux estimation % ICOS
898 LE_LGD_FLAG Flag for the LGD test for LE (0: negligible evidences of error, IF LGD180) nondimensional ICOS
899 LE_LGD_STAT Longest Gap Duration in raw, high-frequency, data used for LE flux estimation seconds ICOS
900 LE_LSR_FLAG Flag for the LSR test for LE (0: negligible evidences of error, IF LSR_STAT>0.995; 1: moderate evidences of error, IF 0.99?LSR_STAT?0.995; 2: severe evidences of error, IF LSR_STAT nondimensional ICOS
901 LE_LSR_STAT Statistic of the Low Signal Resolution test for LE nondimensional ICOS
902 LE_M98_FLAG Flag of the LE_M98_STAT (0: negligible evidences of error, IF M_98_STAT3) nondimensional ICOS
903 LE_M98_STAT Statistic of the nonstationarity ratio test by Mahrt (1998) for LE nondimensional ICOS
904 LE_OOR_FLAG Flag for LE denoting values out of the physically plausible range (0: within range; 2: out of range). nondimensional ICOS
905 LE_orig_QCF0 measured (not gap-filled) latent heat flux of highest quality W m-2
906 LE_OUTLYING_FLAG Flag for LE denoting outliers (0: no outlying flux; 1: outlying flux) nondimensional ICOS
907 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 FLUXNET HH (half-hourly)
908 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 ICOS / FLUXNET
909 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 FLUXNET HH (half-hourly)
910 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 ICOS / FLUXNET
911 LE_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of LE; nondimensional ENERGY PROCESSING FLUXNET HH (half-hourly)
912 LE_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of LE nondimensional ICOS / FLUXNET
913 LE_scf Spectral correction factor for latent heat flux # EddyPro (_full_output_ file)
914 LE_SCF_STAT Spectral correction factor for LE nondimensional ICOS
915 LE_SSITC_TEST Results of the quality flagging for LE according to Foken et al 2004, based on a combination of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (i.e., 0, 1, 2) nondimensional Ameriflux
916 LE_SSITC_TEST Quality flagging for LE according to classification scheme by Foken et al (2004) and based on the combination of the results of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (0: high quality; 1:intermediate quality; 2: low quality). Currently not used in the data cleaning procedure. nondimensional ICOS
917 LE_strg Estimate of storage latent heat flux W m-2 EddyPro (_full_output_ file)
918 LE_UNCLEANED Latent heat turbulent flux (no storage correction, uncleaned) W m-2 ICOS
919 LEAF_WET Leaf wetness, range 0-100 % Ameriflux
920 LGR Los Gatos laser (instrument) EC raw data files (ASCII)
921 LS Lightning strike unitless
922 LSD Lightning strike distance km
923 LW Longwave radiation W m-2
924 LW _IN_RAW Longwave Incoming Radiation without blackbody correction W m-2
925 LW _OUT_RAW Longwave Incoming Radiation without blackbody correction W m-2
926 LW_BC_IN Longwave radiation, below canopy incoming W m-2 Ameriflux
927 LW_BC_OUT Longwave radiation, below canopy outgoing W m-2 Ameriflux
928 LW_IN Longwave radiation, incoming W m-2 Ameriflux
929 LW_IN_ERA Longwave radiation, incoming, downscaled from ERA, linearly regressed using measured only site data; W m-2 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
930 LW_IN_ERA Longwave radiation, incoming, downscaled from ERA, linearly regressed using measured only site data W m-2 ICOS / FLUXNET
931 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 FLUXNET HH (half-hourly)
932 LW_IN_F Longwave radiation, incoming, consolidated from LW_IN_F_MDS and LW_IN_ERA W m-2 ICOS / FLUXNET
933 LW_IN_F_MDS Longwave radiation, incoming, gapfilled using MDS; W m-2 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
934 LW_IN_F_MDS Longwave radiation, incoming, gapfilled using MDS W m-2 ICOS / FLUXNET
935 LW_IN_F_MDS_QC Quality flag for LW_IN_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
936 LW_IN_F_MDS_QC Quality flag for LW_IN_F_MDS. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
937 LW_IN_F_QC Quality flag for LW_IN_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
938 LW_IN_F_QC Quality flag for LW_IN_F. 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional ICOS / FLUXNET
939 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 FLUXNET HH (half-hourly)
940 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 ICOS / FLUXNET
941 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 FLUXNET HH (half-hourly)
942 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 ICOS / FLUXNET
943 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 FLUXNET HH (half-hourly)
944 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 ICOS / FLUXNET
945 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 FLUXNET HH (half-hourly)
946 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 ICOS / FLUXNET
947 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 FLUXNET HH (half-hourly)
948 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 ICOS / FLUXNET
949 LW_OUT Longwave radiation, outgoing W m-2 Ameriflux
950 LW_OUT Longwave radiation, outgoing; W m-2 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
951 LW_OUT Longwave radiation, outgoing W m-2 ICOS / FLUXNET
952 MAX Maximum -
953 max_wind_speed Maximum instantaneous wind speed m s-1 EddyPro (_full_output_ file)
954 MDS Marginal distribution sampling (Reichstein et al., 2005) - Fluxes
955 MET Meteorological Data -
956 MIN Minimum -
957 MIN Minute -
958 MINUTE 2 digit minute of the day MM
959 MIRROR_RINGDOWNTIME Mirror ring-down time µs EC raw data files (ASCII)
960 MO_LENGTH Monin-Obukhov length m ICOS / Ameriflux
961 MONTH 2 digit month of year mm
962 MSW MeteoSwiss
963 N2O N2O molar fraction (in humid air), wet mole fraction nmol mol-1, µmol mol-1 EC raw data files (ASCII)
964 N2O_DRY N2O dry mole fraction (in dry air), mixing ratio, ppb nmol mol-1 EC raw data files (ASCII)
965 N2O_MIXING_RATIO Nitrous Oxide (N2O) in mole fraction of dry air nmolN2O mol-1 Ameriflux
966 N2O_QCL_CMB N2O concentration from QCL for chamber system ppb (nmol N2O mol-1)
967 N2O_QCL_EC N2O concentration from QCL for eddy system ppb (nmol N2O mol-1)
968 N2O_QCL_PRF N2O concentration from QCL for profile ppb (nmol N2O mol-1)
969 NDVI Normalized Difference Vegetation Index nondimensional Ameriflux
970 NEE Net ecosystem exchange of CO2 µmol CO2 m-2 s-1 Fluxes
971 NEE Net Ecosystem Exchange (cleaned) umolCO2 m-2 s-1 ICOS
972 NEE_CUT_05 NEE CUT 05 percentile calculated from the 40 NEE_CUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
973 NEE_CUT_05_QC Quality flag for NEE_CUT_05. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
974 NEE_CUT_16 NEE CUT 16 percentile calculated from the 40 NEE_CUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
975 NEE_CUT_16_f gap-filled NEE, filtered by all quality checks and the 16th percentile USTAR threshold (constant for all years) from FLUXNET analyses µmol CO2 m-2 s-1
976 NEE_CUT_16_orig measured (not gap-filled NEE), filtered by all quality checks and the 16th percentile USTAR threshold (constant for all years) from FLUXNET analyses µmol CO2 m-2 s-1
977 NEE_CUT_16_QC Quality flag for NEE_CUT_16. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
978 NEE_CUT_25 NEE CUT 25 percentile calculated from the 40 NEE_CUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
979 NEE_CUT_25_QC Quality flag for NEE_CUT_25. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
980 NEE_CUT_50 NEE CUT 50 percentile calculated from the 40 NEE_CUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
981 NEE_CUT_50_QC Quality flag for NEE_CUT_50. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
982 NEE_CUT_75 NEE CUT 75 percentile calculated from the 40 NEE_CUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
983 NEE_CUT_75_QC Quality flag for NEE_CUT_75. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
984 NEE_CUT_84_f gap-filled NEE, filtered by all quality checks and the 84th percentile USTAR threshold (constant for all years) from FLUXNET analyses µmol CO2 m-2 s-1
985 NEE_CUT_84_orig measured (not gap-filled NEE), filtered by all quality checks and the 84th percentile USTAR threshold (constant for all years) from FLUXNET analyses µmol CO2 m-2 s-1
986 NEE_CUT_86 NEE CUT 86 percentile calculated from the 40 NEE_CUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
987 NEE_CUT_86_QC Quality flag for NEE_CUT_86. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
988 NEE_CUT_95 NEE CUT 95 percentile calculated from the 40 NEE_CUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
989 NEE_CUT_95_QC Quality flag for NEE_CUT_95. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
990 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 FLUXNET HH (half-hourly)
991 NEE_CUT_MEAN Net Ecosystem Exchange, using Constant Ustar Threshold (CUT) across years, average from 40 NEE_CUT_XX versions µmolCO2 m-2 s-1 ICOS / FLUXNET
992 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 FLUXNET HH (half-hourly)
993 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 ICOS / FLUXNET
994 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 FLUXNET HH (half-hourly)
995 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 ICOS / FLUXNET
996 NEE_CUT_REF_f gap-filled NEE, filtered by all quality checks and the CUT_REF USTAR threshold (constant for all years) from FLUXNET analyses µmol CO2 m-2 s-1
997 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 FLUXNET HH (half-hourly)
998 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 ICOS / FLUXNET
999 NEE_CUT_REF_orig_QCF0 measured (not gap-filled) NEE of highest quality, filtered by all quality checks and the CUT_REF percentile USTAR threshold (constant for all years) from FLUXNET analyses µmol CO2 m-2 s-1
1000 NEE_CUT_REF_QC Quality flag for NEE_CUT_REF; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE FLUXNET HH (half-hourly)
1001 NEE_CUT_REF_QC Quality flag for NEE_CUT_REF. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1002 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 FLUXNET HH (half-hourly)
1003 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 ICOS / FLUXNET
1004 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 FLUXNET HH (half-hourly)
1005 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 ICOS / FLUXNET
1006 NEE_CUT_REF_RANDUNC_N Number of data points used to estimate the random uncertainty of NEE_CUT_REF; nondimensional NET ECOSYSTEM EXCHANGE FLUXNET HH (half-hourly)
1007 NEE_CUT_REF_RANDUNC_N Number of data points used to estimate the random uncertainty of NEE_CUT_REF nondimensional ICOS / FLUXNET
1008 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 FLUXNET HH (half-hourly)
1009 NEE_CUT_SE Standard Error for NEE_CUT, calculated as SD(NEE_CUT_XX) / SQRT(40) from 40 half-hourly NEE_CUT_XX µmolCO2 m-2 s-1 ICOS / FLUXNET
1010 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 FLUXNET HH (half-hourly)
1011 NEE_CUT_USTAR50 Net Ecosystem Exchange, using Constant Ustar Threshold (CUT) across years, from 50 percentile of USTAR threshold µmolCO2 m-2 s-1 ICOS / FLUXNET
1012 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 FLUXNET HH (half-hourly)
1013 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 ICOS / FLUXNET
1014 NEE_CUT_USTAR50_QC Quality flag for NEE_CUT_USTAR50; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE FLUXNET HH (half-hourly)
1015 NEE_CUT_USTAR50_QC Quality flag for NEE_CUT_USTAR50. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1016 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 FLUXNET HH (half-hourly)
1017 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 ICOS / FLUXNET
1018 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 FLUXNET HH (half-hourly)
1019 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 ICOS / FLUXNET
1020 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 FLUXNET HH (half-hourly)
1021 NEE_CUT_USTAR50_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of NEE_CUT_USTAR50 nondimensional ICOS / FLUXNET
1022 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 FLUXNET HH (half-hourly)
1023 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 FLUXNET HH (half-hourly)
1024 NEE_DATA_FLAG Flag for NEE (i.e., 0: observed flux for which any quality control (QC) tests provided negligible evidences of error; 1: outlying flux rejected because at least one of the QC tests provided a moderate evidence of error; 2: flux removed because at least one of the QC test provided a severe evidence of error) nondimensional ICOS
1025 NEE_OOR_FLAG Flag for NEE denoting values out of the physically plausible range (0: within range; 2: out of range). nondimensional ICOS
1026 NEE_OUTLYING_FLAG Flag for NEE denoting outliers (0: no outlying flux; 1: outlying flux) nondimensional ICOS
1027 NEE_U50_QCF0 measured (not gap-filled) NEE of highest quality, filtered by all quality checks and the median (50th percentile) USTAR threshold umol CO2 m-2 s-1 DIIVE
1028 NEE_UNCLEANED Net Ecosystem Exchange (uncleaned) umolCO2 m-2 s-1 ICOS
1029 NEE_VUT_05 NEE VUT 05 percentile calculated from the 40 NEE_VUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
1030 NEE_VUT_05_QC Quality flag for NEE_VUT_05. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1031 NEE_VUT_16 NEE VUT 16 percentile calculated from the 40 NEE_VUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
1032 NEE_VUT_16_QC Quality flag for NEE_VUT_16. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1033 NEE_VUT_25 NEE VUT 25 percentile calculated from the 40 NEE_VUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
1034 NEE_VUT_25_QC Quality flag for NEE_VUT_25. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1035 NEE_VUT_50 NEE VUT 50 percentile calculated from the 40 NEE_VUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
1036 NEE_VUT_50_QC Quality flag for NEE_VUT_50. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1037 NEE_VUT_75 NEE VUT 75 percentile calculated from the 40 NEE_VUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
1038 NEE_VUT_75_QC Quality flag for NEE_VUT_75. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1039 NEE_VUT_86 NEE VUT 86 percentile calculated from the 40 NEE_VUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
1040 NEE_VUT_86_QC Quality flag for NEE_VUT_86. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1041 NEE_VUT_95 NEE VUT 95 percentile calculated from the 40 NEE_VUT estimates µmolCO2 m-2 s-1 ICOS / FLUXNET
1042 NEE_VUT_95_QC Quality flag for NEE_VUT_95. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1043 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 FLUXNET HH (half-hourly)
1044 NEE_VUT_MEAN Net Ecosystem Exchange, using Variable Ustar Threshold (VUT) for each year, average from 40 NEE_VUT_XX versions µmolCO2 m-2 s-1 ICOS / FLUXNET
1045 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 FLUXNET HH (half-hourly)
1046 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 ICOS / FLUXNET
1047 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 FLUXNET HH (half-hourly)
1048 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 ICOS / FLUXNET
1049 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 FLUXNET HH (half-hourly)
1050 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 ICOS / FLUXNET
1051 NEE_VUT_REF_QC Quality flag for NEE_VUT_REF; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE FLUXNET HH (half-hourly)
1052 NEE_VUT_REF_QC Quality flag for NEE_VUT_REF. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1053 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 FLUXNET HH (half-hourly)
1054 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 ICOS / FLUXNET
1055 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 FLUXNET HH (half-hourly)
1056 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 ICOS / FLUXNET
1057 NEE_VUT_REF_RANDUNC_N Number of data points used to estimate the random uncertainty of NEE_VUT_REF; nondimensional NET ECOSYSTEM EXCHANGE FLUXNET HH (half-hourly)
1058 NEE_VUT_REF_RANDUNC_N Number of data points used to estimate the random uncertainty of NEE_VUT_REF nondimensional ICOS / FLUXNET
1059 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 FLUXNET HH (half-hourly)
1060 NEE_VUT_SE Standard Error for NEE_VUT, calculated as SD(NEE_VUT_XX) / SQRT(40) from 40 half-hourly NEE_VUT_XX µmolCO2 m-2 s-1 ICOS / FLUXNET
1061 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 FLUXNET HH (half-hourly)
1062 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 ICOS / FLUXNET
1063 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 FLUXNET HH (half-hourly)
1064 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 ICOS / FLUXNET
1065 NEE_VUT_USTAR50_QC Quality flag for NEE_VUT_USTAR50; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional NET ECOSYSTEM EXCHANGE FLUXNET HH (half-hourly)
1066 NEE_VUT_USTAR50_QC Quality flag for NEE_VUT_USTAR50. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1067 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 FLUXNET HH (half-hourly)
1068 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 ICOS / FLUXNET
1069 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 FLUXNET HH (half-hourly)
1070 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 ICOS / FLUXNET
1071 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 FLUXNET HH (half-hourly)
1072 NEE_VUT_USTAR50_RANDUNC_N Number of half-hour data points used to estimate the random uncertainty of NEE_VUT_USTAR50 nondimensional ICOS / FLUXNET
1073 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 FLUXNET HH (half-hourly)
1074 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 FLUXNET HH (half-hourly)
1075 NETRAD Net Radiation W m-2
1076 NETRAD Net radiation; W m-2 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1077 NETRAD Net radiation W m-2 ICOS / FLUXNET
1078 NH4
1079 NIGHT Flag indicating nighttime interval based on SW_IN_POT; 0 = daytime, 1 = nighttime nondimensional NET ECOSYSTEM EXCHANGE FLUXNET HH (half-hourly)
1080 NIGHT Flag indicating nighttime interval based on SW_IN_POT. 0 = daytime, 1 = nighttime nondimensional ICOS / FLUXNET
1081 NO Nitric oxide (NO) mole fraction in wet air nmolNO mol-1 Ameriflux
1082 NO2 Nitrogen dioxide (NO2) mole fraction in wet air nmolNO2 mol-1 Ameriflux
1083 NO3 Nitrate concentration µg g-1 soil
1084 non_steady_wind Hard flag for non-steady horizontal test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
1085 NT Nighttime (used in partitioning) - Fluxes
1086 NUMVALS Number of values #
1087 O2 Oxygen Has to be seen when we have the sensors
1088 O3 Ozone (O3) mole fraction in wet air nmolO3 mol-1 Ameriflux
1089 OSO On Site Operation -
1090 OUT Outgoing -
1091 P Precipitation mm FLUXNET
1092 P Precipitation; mm MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1093 P Precipitation mm ICOS / FLUXNET
1094 P_ERA Precipitation, downscaled from ERA, linearly regressed using measured only site data; (mm per dataset resolution: either hour or half-hour) mm MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1095 P_ERA Precipitation, downscaled from ERA, linearly regressed using measured only site data. (mm per dataset resolution: either hour or half-hour) mm ICOS / FLUXNET
1096 P_F Precipitation consolidated from P and P_ERA; P used if measured (mm per dataset resolution: either hour or half-hour) mm MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1097 P_F Precipitation consolidated from P and P_ERA. P used if measured (mm per dataset resolution: either hour or half-hour) mm ICOS / FLUXNET
1098 P_F_QC Quality flag for P_F; 0 = measured; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1099 P_F_QC Quality flag for P_F. 0 = measured; 2 = downscaled from ERA nondimensional ICOS / FLUXNET
1100 PA Atmospheric Pressure Pa, kPa, hPa or other
1101 PA Atmospheric pressure; kPa MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1102 PA Atmospheric pressure kPa ICOS / FLUXNET
1103 PA_ERA Atmospheric pressure, downscaled from ERA, linearly regressed using measured only site data; kPa MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1104 PA_ERA Atmospheric pressure, downscaled from ERA, linearly regressed using measured only site data kPa ICOS / FLUXNET
1105 PA_F Atmospheric pressure consolidated from PA and PA_ERA; PA used if measured kPa MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1106 PA_F Atmospheric pressure consolidated from PA and PA_ERA kPa ICOS / FLUXNET
1107 PA_F_QC Quality flag for PA_F; 0 = measured; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1108 PA_F_QC Quality flag for PA_F. 0 = measured; 2 = downscaled from ERA nondimensional ICOS / FLUXNET
1109 PA_PRF Atmospheric Pressure in Profile Pa, kPa, hPa or other
1110 PBLH Planetary boundary layer height m ICOS / Ameriflux
1111 PCH4
1112 pitch Second rotation angle ° (degrees) EddyPro (_full_output_ file)
1113 PPFD Photosynthetic photon flux density, without additional suffix it is typically incoming µmolPhoton m-2 s-1
1114 PPFD_DIF Photosynthetic photon flux density, diffuse incoming; µmolPhoton m-2 s-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1115 PPFD_DIF Photosynthetic photon flux density, diffuse incoming µmolPhoton m-2 s-1 ICOS / FLUXNET
1116 PPFD_IN Photosynthetic photon flux density, incoming µmolPhoton m-2 s-1
1117 PPFD_IN Photosynthetic photon flux density, incoming; µmolPhoton m-2 s-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1118 PPFD_IN Photosynthetic photon flux density, incoming µmolPhoton m-2 s-1 ICOS / FLUXNET
1119 PPFD_OUT Photosynthetic photon flux density, outgoing µmolPhoton m-2 s-1
1120 PPFD_OUT Photosynthetic photon flux density, outgoing; µmolPhoton m-2 s-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1121 PPFD_OUT Photosynthetic photon flux density, outgoing µmolPhoton m-2 s-1 ICOS / FLUXNET
1122 PREC Precipitation mm
1123 qc_gas_flux Quality flag for gas flux # EddyPro (_full_output_ file)
1124 qc_H Quality flag for sensible heat flux # EddyPro (_full_output_ file)
1125 qc_LE Quality flag latent heat flux # EddyPro (_full_output_ file)
1126 qc_Tau Quality flag for momentum flux # EddyPro (_full_output_ file)
1127 QCF_ (prefix) quality control flag for the respective variable #
1128 QCF_LE quality control flag for latent heat flux (0=best, 1=OK, 2=bad), typically for LE_f #
1129 QCF_NEE quality control flag for NEE (0=best, 1=OK, 2=bad), typically for NEE_CUT_REF_f #
1130 R_ref respiration at reference temperature parameter (μmol m-2 s-1 as NEE) in relationship between temperature and nighttime NEE from night-time partitioning μmol CO2 m-2 s-1 ReddyProc
1131 rand_err_gas_flux Random error for gas flux, if selected µmol s-1 m-2(†) EddyPro (_full_output_ file)
1132 rand_err_H Random error for momentum flux, if selected W m-2 EddyPro (_full_output_ file)
1133 rand_err_LE Random error for latent heat flux, if selected W m-2 EddyPro (_full_output_ file)
1134 rand_err_Tau Random error for momentum flux, if selected kg m-1 s-2 EddyPro (_full_output_ file)
1135 Reco_CUT_16 Ecosystem respiration, i.e. outflux from the land surface (μmol m-2 s-1 as NEE) (nighttime-based), modelled from NEE_CUT_16_f umol CO2 m-2 s-1
1136 Reco_CUT_84 Ecosystem respiration, i.e. outflux from the land surface (μmol m-2 s-1 as NEE) (nighttime-based), modelled from NEE_CUT_84_f umol CO2 m-2 s-1
1137 Reco_CUT_REF Ecosystem respiration, i.e. outflux from the land surface (μmol m-2 s-1 as NEE) (nighttime-based), modelled from NEE_CUT_REF_f umol CO2 m-2 s-1
1138 RECO_DT_CUT_05 Ecosystem Respiration, from Daytime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1139 Reco_DT_CUT_16 Ecosystem respiration, i.e. outflux from the land surface (μmol m-2 s-1 as NEE) estimated by day-time partitioning, modelled from NEE_CUT_16_f umol CO2 m-2 s-1
1140 RECO_DT_CUT_16 Ecosystem Respiration, from Daytime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1141 RECO_DT_CUT_25 Ecosystem Respiration, from Daytime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1142 RECO_DT_CUT_50 Ecosystem Respiration, from Daytime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1143 RECO_DT_CUT_75 Ecosystem Respiration, from Daytime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1144 Reco_DT_CUT_84 Ecosystem respiration, i.e. outflux from the land surface (μmol m-2 s-1 as NEE) estimated by day-time partitioning, modelled from NEE_CUT_84_f umol CO2 m-2 s-1
1145 RECO_DT_CUT_86 Ecosystem Respiration, from Daytime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1146 RECO_DT_CUT_95 Ecosystem Respiration, from Daytime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1147 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 FLUXNET HH (half-hourly)
1148 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 ICOS / FLUXNET
1149 Reco_DT_CUT_REF Ecosystem respiration, i.e. outflux from the land surface (μmol m-2 s-1 as NEE) estimated by day-time partitioning, modelled from NEE_CUT_REF_f umol CO2 m-2 s-1
1150 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 FLUXNET HH (half-hourly)
1151 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 ICOS / FLUXNET
1152 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 FLUXNET HH (half-hourly)
1153 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 ICOS / FLUXNET
1154 RECO_DT_CUT_USTAR50 Ecosystem Respiration, from Daytime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING FLUXNET HH (half-hourly)
1155 RECO_DT_CUT_USTAR50 Ecosystem Respiration, from Daytime partitioning method, based on NEE_CUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
1156 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 FLUXNET HH (half-hourly)
1157 RECO_DT_VUT_05 Ecosystem Respiration, from Daytime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1158 RECO_DT_VUT_16 Ecosystem Respiration, from Daytime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1159 RECO_DT_VUT_25 Ecosystem Respiration, from Daytime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1160 RECO_DT_VUT_50 Ecosystem Respiration, from Daytime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1161 RECO_DT_VUT_75 Ecosystem Respiration, from Daytime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1162 RECO_DT_VUT_86 Ecosystem Respiration, from Daytime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1163 RECO_DT_VUT_95 Ecosystem Respiration, from Daytime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1164 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 FLUXNET HH (half-hourly)
1165 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 ICOS / FLUXNET
1166 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 FLUXNET HH (half-hourly)
1167 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 ICOS / FLUXNET
1168 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 FLUXNET HH (half-hourly)
1169 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_CUT_XX µmolCO2 m-2 s-1 ICOS / FLUXNET
1170 RECO_DT_VUT_USTAR50 Ecosystem Respiration, from Daytime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 DAYTIME PARTITIONING FLUXNET HH (half-hourly)
1171 RECO_DT_VUT_USTAR50 Ecosystem Respiration, from Daytime partitioning method, based on NEE_VUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
1172 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 FLUXNET HH (half-hourly)
1173 Reco_f Ecosystem respiration, i.e. outflux from the land surface (μmol m-2 s-1 as NEE) (nighttime-based) μmol CO2 m-2 s-1 ReddyProc
1174 RECO_NT_CUT_05 Ecosystem Respiration, from Nighttime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1175 RECO_NT_CUT_16 Ecosystem Respiration, from Nighttime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1176 RECO_NT_CUT_25 Ecosystem Respiration, from Nighttime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1177 RECO_NT_CUT_50 Ecosystem Respiration, from Nighttime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1178 RECO_NT_CUT_75 Ecosystem Respiration, from Nighttime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1179 RECO_NT_CUT_86 Ecosystem Respiration, from Nighttime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1180 RECO_NT_CUT_95 Ecosystem Respiration, from Nighttime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1181 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 FLUXNET HH (half-hourly)
1182 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 ICOS / FLUXNET
1183 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 FLUXNET HH (half-hourly)
1184 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 ICOS / FLUXNET
1185 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 FLUXNET HH (half-hourly)
1186 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 ICOS / FLUXNET
1187 RECO_NT_CUT_USTAR50 Ecosystem Respiration, from Nighttime partitioning method, based on NEE_CUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING FLUXNET HH (half-hourly)
1188 RECO_NT_CUT_USTAR50 Ecosystem Respiration, from Nighttime partitioning method, based on NEE_CUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
1189 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 FLUXNET HH (half-hourly)
1190 RECO_NT_VUT_05 Ecosystem Respiration, from Nighttime partitioning method, percentile 05 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1191 RECO_NT_VUT_16 Ecosystem Respiration, from Nighttime partitioning method, percentile 16 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1192 RECO_NT_VUT_25 Ecosystem Respiration, from Nighttime partitioning method, percentile 25 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1193 RECO_NT_VUT_50 Ecosystem Respiration, from Nighttime partitioning method, percentile 50 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1194 RECO_NT_VUT_75 Ecosystem Respiration, from Nighttime partitioning method, percentile 75 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1195 RECO_NT_VUT_86 Ecosystem Respiration, from Nighttime partitioning method, percentile 86 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1196 RECO_NT_VUT_95 Ecosystem Respiration, from Nighttime partitioning method, percentile 95 of the 40 estimations µmolCO2 m-2 s-1 ICOS / FLUXNET
1197 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 FLUXNET HH (half-hourly)
1198 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 ICOS / FLUXNET
1199 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 FLUXNET HH (half-hourly)
1200 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 ICOS / FLUXNET
1201 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 FLUXNET HH (half-hourly)
1202 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 ICOS / FLUXNET
1203 RECO_NT_VUT_USTAR50 Ecosystem Respiration, from Nighttime partitioning method, based on NEE_VUT_USTAR50; µmolCO2 m-2 s-1 NIGHTTIME PARTITIONING FLUXNET HH (half-hourly)
1204 RECO_NT_VUT_USTAR50 Ecosystem Respiration, from Nighttime partitioning method, based on NEE_VUT_USTAR50 µmolCO2 m-2 s-1 ICOS / FLUXNET
1205 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 FLUXNET HH (half-hourly)
1206 RECO_SR Ecosystem Respiration, from Sundown Respiration partitioning method; µmolCO2 m-2 s-1 SUNDOWN FLUXNET HH (half-hourly)
1207 Rg Shortwave radiation, incoming W m-2 ReddyProc
1208 Rg_f Gap-filled shortwave radiation, incoming, typically gap-filled using MDS W m-2 ReddyProc
1209 Rg_orig Measured (not gap-filled) shortwave radiation, incoming, typically gap-filled using MDS W m-2 ReddyProc
1210 RH Relative humidity %
1211 RH Ambient relative humidity 0 EddyPro (_full_output_ file)
1212 RH Relative humidity, range 0-100; % MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1213 RH Relative humidity, range 0-100 % ICOS / FLUXNET
1214 roll Third rotation angle ° (degrees) EddyPro (_full_output_ file)
1215 RSSI Mean value of RSSI for LI‑7700, if present # EddyPro (_full_output_ file)
1216 SA_DIAG_FLAG Flag for Sonic Anemometer (SA) instrumental diagnostics (0: negligible evidences of error; 2: severe evidences of error) nondimensional ICOS
1217 SC Carbon Dioxide (CO2) storage flux umolCO2 m-2 s-1 ICOS
1218 SC_OOR_FLAG Flag for SC denoting values out of the physically plausible range (0: within range; 2: out of range) nondimensional ICOS
1219 SC_UNC Estimated uncertainty for SC umolCO2 m-2 s-1 ICOS
1220 SC_UNC_FLAG SC QC flag for uncertainty (0: none; 1: flux data for which the estimated uncertainty exceeds the respective NEE absolute value by 3 times) nondimensional ICOS
1221 SC_UNCLEANED Carbon dioxide storage flux (not QC filtered) umolCO2 m-2 s-1 ICOS
1222 SDP Soil Dielectric Permittivity unitless
1223 SH Sensible heat (H) storage flux (only if air temperature is measured along a profile) W m-2 ICOS
1224 skw_kur Hard flags for individual variables for skewness and kurtosis HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
1225 skw_kur Soft flags for individual variables for skewness and kurtosis test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
1226 SLE Latent heat (LE) storage flux (only if air temperature and H2O are measured along a profile) W m-2 ICOS
1227 SLE_OOR_FLAG Flag for SLE denoting values out of the physically plausible range (0: within range; 2: out of range) nondimensional ICOS
1228 SLE_UNC Estimated uncertainty for SLE W m-2 ICOS
1229 SLE_UNC_FLAG SLE QC flag for uncertainty (0: none; 1: flux data for which the estimated uncertainty exceeds the respective NEE absolute value by 3 times) nondimensional ICOS
1230 SLE_UNCLEANED Latent heat storage flux (not QC filtered) W m-2 ICOS
1231 sonic_temperature Mean temperature of ambient air as measured by the anemometer K EddyPro (_full_output_ file)
1232 specific_humidity Ambient specific humidity on a mass basis kg kg-1 EddyPro (_full_output_ file)
1233 spikes Hard flags for individual variables for spike test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
1234 SW Shortwave radiation W m-2
1235 SW_DIF Shortwave radiation, diffuse incoming; W m-2 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1236 SW_DIF Shortwave radiation, diffuse incoming W m-2 ICOS / FLUXNET
1237 SW_IN Shortwave radiation, incoming W m-2
1238 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 FLUXNET HH (half-hourly)
1239 SW_IN_ERA Shortwave radiation, incoming, downscaled from ERA, linearly regressed using measured only site data (negative values set to zero) W m-2 ICOS / FLUXNET
1240 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 FLUXNET HH (half-hourly)
1241 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 ICOS / FLUXNET
1242 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 FLUXNET HH (half-hourly)
1243 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 ICOS / FLUXNET
1244 SW_IN_F_MDS_QC Quality flag for SW_IN_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1245 SW_IN_F_MDS_QC Quality flag for SW_IN_F_MDS. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1246 SW_IN_F_QC Quality flag for SW_IN_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1247 SW_IN_F_QC Quality flag for SW_IN_F. 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional ICOS / FLUXNET
1248 SW_IN_POT Shortwave radiation, incoming, potential (top of atmosphere); W m-2 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1249 SW_IN_POT Shortwave radiation, incoming, potential (top of atmosphere) W m-2 ICOS / FLUXNET
1250 SW_OUT Shortwave radiation, outgoing W m-2
1251 SW_OUT Shortwave radiation, outgoing; W m-2 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1252 SW_OUT Shortwave radiation, outgoing W m-2 ICOS / FLUXNET
1253 SWC Soil water content %
1254 SWC_F_MDS_# Soil water content, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest); % MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1255 SWC_F_MDS_# Soil water content, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest) % ICOS / FLUXNET
1256 SWC_F_MDS_#_QC Quality flag for SWC_F_MDS_#; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1257 SWC_F_MDS_#_QC Quality flag for SWC_F_MDS_#. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1258 SWP Soil water potential kPa
1259 T* Scaling temperature K EddyPro (_full_output_ file)
1260 T_SONIC Sonic temperature deg C ICOS
1261 T_SONIC_HD10_FLAG Flag for the homogeneity test applied on differenced sonic temperature 0: negligible evidences of error, IF HD10_STAT1) nondimensional ICOS
1262 T_SONIC_HD10_STAT Statistic of the homogeneity test applied on differenced sonic temperature (percentage of data exceeding ñ10?) % ICOS
1263 T_SONIC_HD5_FLAG Flag for the homogeneity test applied on differenced sonic temperature (0: negligible evidences of error, IF HD5_STAT4) nondimensional ICOS
1264 T_SONIC_HD5_STAT Statistic of the homogeneity test applied on differenced sonic temperature (percentage of data exceeding ñ5?) % ICOS
1265 T_SONIC_HF10_FLAG Flag for the homogeneity test applied on sonic temperature fluctuations (0: negligible evidences of error, IF HF10_STAT1) nondimensional ICOS
1266 T_SONIC_HF10_STAT Statistic of the homogeneity test applied on sonic temperature fluctuations (percentage of data exceeding ñ10?) % ICOS
1267 T_SONIC_HF5_FLAG Flag for the homogeneity test applied on sonic temperature fluctuations (0: negligible evidences of error, IF HF5_STAT4) nondimensional ICOS
1268 T_SONIC_HF5_STAT Statistic of the homogeneity test applied on sonic temperature fluctuations (percentage of data exceeding ñ5?) % ICOS
1269 T_SONIC_KID_FLAG Flag for the T_SONIC_KID_STAT (0: negligible evidences of error, IF KID_STAT50) nondimensional ICOS
1270 T_SONIC_KID_STAT Kurtosis Index of Differenced sonic temperature nondimensional ICOS
1271 T_SONIC_SIGMA Standard deviation of sonic temperature deg C ICOS
1272 TA Air temperature °C
1273 TA_ERA Air temperature, downscaled from ERA, linearly regressed using measured only site data deg C MICROMETEOROLOGICAL ICOS / FLUXNET / FLUXNET HH (half-hourly)
1274 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 FLUXNET HH (half-hourly)
1275 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 ICOS / FLUXNET
1276 TA_F_MDS Air temperature, gapfilled using MDS method deg C MICROMETEOROLOGICAL ICOS / FLUXNET / FLUXNET HH (half-hourly)
1277 TA_F_MDS_QC Quality flag for TA_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1278 TA_F_MDS_QC Quality flag for TA_F_MDS. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1279 TA_F_QC Quality flag for TA_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1280 TA_F_QC Quality flag for TA_F. 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional ICOS / FLUXNET
1281 Tair Air temperature °C ReddyProc
1282 Tair_f Gap-filled air temperature, typically gap-filled using MDS °C ReddyProc
1283 Tair_orig Measured (not gap-filled) air temperature °C ReddyProc
1284 TAU Momentum flux kg m-1 s-2
1285 Tau Corrected momentum flux kg m-1 s-2 EddyPro (_full_output_ file)
1286 TAU Momentum flux kg m-1 s-2 ICOS
1287 Tau_scf Spectral correction factor for momentum flux # EddyPro (_full_output_ file)
1288 TAU_SSITC_TEST Quality flagging for TAU according to classification scheme by Foken et al (2004) and based on the combination of the results of Steady State and Integral Turbulence Characteristics tests by Foken and Wichura (1996) (0: high quality; 1:intermediate quality; 2: low quality). Currently not used in the data cleaning procedure. nondimensional ICOS
1289 TBIN body temperature of sensor measuring incoming signal deg C instrument metrics ETH raw data files
1290 TBOUT body temperature of sensor measuring outgoing signal deg C instrument metrics ETH raw data files
1291 Tdew Ambient dew point temperature K EddyPro (_full_output_ file)
1292 TG Grass temperature deg C
1293 time Time of the end of the averaging period HH:MM EddyPro (_full_output_ file)
1294 time_lag Hard flags for gas concentration for time lag test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
1295 time_lag Soft flags for gas concentration for time lag test HFu/v/w/ts/co2 /h2o/ch4/n2 EddyPro (_full_output_ file)
1296 TIMESTAMP ISO timestamp - short format YYYYMMDDHHMM TIMEKEEPING FLUXNET HH (half-hourly)
1297 TIMESTAMP_END ISO timestamp end of averaging period - short format YYYYMMDDHHMM TIMEKEEPING FLUXNET HH (half-hourly)
1298 TIMESTAMP_END ISO timestamp end of averaging period (up to a 12-digit integer as specified by the data's temporal resolution) yyyymmddHHMM ICOS
1299 TIMESTAMP_END ISO timestamp end of averaging period - short format YYYYMMDDHHMM ICOS / FLUXNET
1300 TIMESTAMP_START ISO timestamp start of averaging period - short format YYYYMMDDHHMM TIMEKEEPING FLUXNET HH (half-hourly)
1301 TIMESTAMP_START ISO timestamp start of averaging period (up to a 12-digit integer as specified by the data's temporal resolution) yyyymmddHHMM ICOS
1302 TIMESTAMP_START ISO timestamp start of averaging period - short format YYYYMMDDHHMM ICOS / FLUXNET
1303 TIR thermal infrared °C
1304 TKE Turbulent kinetic energy m2 s-2 EddyPro (_full_output_ file)
1305 TM tensiometer, measures soil moisture tension hPa
1306 TPANEL Panel temperature deg C
1307 TRH relative humidity temperature
1308 TS_F_MDS_# Soil temperature, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest); deg C MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1309 TS_F_MDS_# Soil temperature, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest) deg C ICOS / FLUXNET
1310 TS_F_MDS_#_QC Quality flag for TS_F_MDS_#; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1311 TS_F_MDS_#_QC Quality flag for TS_F_MDS_#. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1312 u* Friction velocity m s-1 EddyPro (_full_output_ file)
1313 u_rot Rotated u wind component (mean wind speed) m s-1 EddyPro (_full_output_ file)
1314 U_SIGMA Standard deviation of lateral velocity fluctuations (towards main-wind direction after coordinates rotation) m s-1 ICOS
1315 u_unrot Wind component along the u anemometer axis m s-1 EddyPro (_full_output_ file)
1316 un_gas_flux Uncorrected gas flux µmol s-1 m-2(†) EddyPro (_full_output_ file)
1317 un_H Uncorrected sensible heat flux W m-2 EddyPro (_full_output_ file)
1318 un_LE Uncorrected latent heat flux W m-2 EddyPro (_full_output_ file)
1319 un_Tau Uncorrected momentum flux kg m-1 s-2 EddyPro (_full_output_ file)
1320 used_records Number of valid records used for current the averaging period # EddyPro (_full_output_ file)
1321 USTAR Friction velocity m s-1
1322 USTAR Friction velocity; m s-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1323 USTAR Friction velocity m s-1 ICOS / FLUXNET
1324 Ustar_CUT_REF_Thres USTAR threshold used for _CUT_REF_ variables m s-1 ReddyProc
1325 v_rot Rotated v wind component (should be zero) m s-1 EddyPro (_full_output_ file)
1326 V_SIGMA Standard deviation of lateral velocity fluctuations (cross main-wind direction after coordinates rotation) m s-1 ICOS
1327 v_unrot Wind component along the v anemometer axis m s-1 EddyPro (_full_output_ file)
1328 var_spikes Number of spikes detected and eliminated for variable var # EddyPro (_full_output_ file)
1329 var_var Variance of variable var #NAME? EddyPro (_full_output_ file)
1330 VIN incoming signal in volts or millivolts V, mV ETH raw data files
1331 VOUT outgoing signal in volts or millivolts V, mV ETH raw data files
1332 VP vapor pressure
1333 VPD Vapor pressure deficit kPa or hPa
1334 VPD Ambient water vapor pressure deficit Pa EddyPro (_full_output_ file)
1335 VPD_ERA Vapor Pressure Deficit, downscaled from ERA, linearly regressed using measured only site data; hPa MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1336 VPD_ERA Vapor Pressure Deficit, downscaled from ERA, linearly regressed using measured only site data hPa ICOS / FLUXNET
1337 VPD_f Gap-filled vapor pressure deficit, typically gap-filled using MDS kPa or hPa
1338 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 FLUXNET HH (half-hourly)
1339 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 ICOS / FLUXNET
1340 VPD_F_MDS Vapor Pressure Deficit, gapfilled using MDS; hPa MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1341 VPD_F_MDS Vapor Pressure Deficit, gapfilled using MDS hPa ICOS / FLUXNET
1342 VPD_F_MDS_QC Quality flag for VPD_F_MDS; 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1343 VPD_F_MDS_QC Quality flag for VPD_F_MDS. 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor nondimensional ICOS / FLUXNET
1344 VPD_F_QC Quality flag for VPD_F; 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1345 VPD_F_QC Quality flag for VPD_F. 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA nondimensional ICOS / FLUXNET
1346 VPD_orig Vapor pressure deficit calculated (not gap-filled) from measured TA and measured RH kPa or hPa
1347 w/var_cov Covariance between w and variable var #NAME? EddyPro (_full_output_ file)
1348 W_HD10_FLAG Flag for the homogeneity test applied on differenced vertical wind velocity (0: negligible evidences of error, IF HD10_STAT1) nondimensional ICOS
1349 W_HD10_STAT Statistic of the homogeneity test applied on differenced vertical wind velocity (percentage of data exceeding æñ10?) % ICOS
1350 W_HD5_FLAG Flag for the homogeneity test applied on differenced vertical wind velocity (0: negligible evidences of error, IF HD5_STAT4) nondimensional ICOS
1351 W_HD5_STAT Statistic of the homogeneity test applied on differenced vertical wind velocity (percentage of data exceeding æñ5?) % ICOS
1352 W_HF10_FLAG Flag for the homogeneity test applied on vertical wind velocity fluctuations (0: negligible evidences of error, IF HF10_STAT1) nondimensional ICOS
1353 W_HF10_STAT Statistic of the homogeneity test applied on vertical wind velocity fluctuations (percentage of data exceeding æñ10?) % ICOS
1354 W_HF5_FLAG Flag for the homogeneity test applied on vertical wind velocity fluctuations (0: negligible evidences of error, IF HF5_STAT4) nondimensional ICOS
1355 W_HF5_STAT Statistic of the homogeneity test applied on vertical wind velocity fluctuations (percentage of data exceeding æñ5?) % ICOS
1356 W_KID_FLAG Flag for the W_KID_STAT (0: negligible evidences of error, IF KID_STAT50) nondimensional ICOS
1357 W_KID_STAT Kurtosis Index of Differenced vertical wind velocity nondimensional ICOS
1358 w_rot Rotated w wind component (should be zero) m s-1 EddyPro (_full_output_ file)
1359 W_SIGMA Standard deviation of vertical velocity fluctuations m s-1 ICOS
1360 w_unrot Wind component along the w anemometer axis m s-1 EddyPro (_full_output_ file)
1361 water_vapor_density Ambient mass density of water vapor kg m-3 EddyPro (_full_output_ file)
1362 WD Wind direction; Decimal degrees MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1363 WD Wind direction Decimal degrees ICOS / FLUXNET
1364 wind_dir Direction from which the wind blows, with respect to Geographic or Magnetic north ° (degrees) EddyPro (_full_output_ file)
1365 wind_speed Mean wind speed m s-1 EddyPro (_full_output_ file)
1366 WS Wind speed; m s-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1367 WS Wind speed m s-1 ICOS / FLUXNET
1368 WS_ERA Wind speed, downscaled from ERA, linearly regressed using measured only site data; m s-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1369 WS_ERA Wind speed, downscaled from ERA, linearly regressed using measured only site data m s-1 ICOS / FLUXNET
1370 WS_F Wind speed, consolidated from WS and WS_ERA; WS used if measured m s-1 MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1371 WS_F Wind speed, consolidated from WS and WS_ERA. WS used if measured m s-1 ICOS / FLUXNET
1372 WS_F_QC Quality flag of WS_F; 0 = measured; 2 = downscaled from ERA nondimensional MICROMETEOROLOGICAL FLUXNET HH (half-hourly)
1373 WS_F_QC Quality flag of WS_F. 0 = measured; 2 = downscaled from ERA nondimensional ICOS / FLUXNET
1374 WSECT_FLAG Footprint quality flag indicating periods when wind was blowing from directions known to significantly affect the turbulent flow (0: negligible evidences of error; 2: severe evidences of error) nondimensional ICOS
1375 WSG wind gust
1376 x_10% Along-wind distance providing 10% (cumulative) contribution to turbulent fluxes m EddyPro (_full_output_ file)
1377 x_30% Along-wind distance providing 30% (cumulative) contribution to turbulent fluxes m EddyPro (_full_output_ file)
1378 x_50% Along-wind distance providing 50% (cumulative) contribution to turbulent fluxes m EddyPro (_full_output_ file)
1379 x_70% Along-wind distance providing 70% (cumulative) contribution to turbulent fluxes m EddyPro (_full_output_ file)
1380 x_90% Along-wind distance providing 90% (cumulative) contribution to turbulent fluxes m EddyPro (_full_output_ file)
1381 x_offset Along-wind distance providing m EddyPro (_full_output_ file)
1382 x_peak Along-wind distance providing the highest (peak) contribution to turbulent fluxes m EddyPro (_full_output_ file)
1383 yaw First rotation angle ° (degrees) EddyPro (_full_output_ file)
1384 ZL Monin-Obukhov stability parameter nondimensional ICOS
1385 (FLUX)_QCF (suffix) measured (not gap-filled) data with the respective QCF flag applied
1386 FLAG_(FLUX)_QCF quality control flag, overall quality flag for the respective flux 0=best, 1=medium, 2=bad data DIIVE
1387 MEAS (suffix) measured
1388 VEGH vegetation height m VEGETATION
1389 SN2O Nitrous oxide (N2O) storage flux nmol m-2 s-1
1390 TLAG_ACTUAL actual time lag, typically between the turbulent departures of vertical wind and gas s EddyPro
1391 RF random forest
1392 IU instrument units, typically raw units e.g. mV ICOS
1393 BV Battery voltage V
1394 V Voltage V
Label Description Units (preferred) or format Category Used In

† Concentrations and fluxes for water vapor are provided as [mmol mol-1] and [mmol m-2 s-1] respectively.

‡ Units depend on the nature of the variable.

 

References

 

Last Updated on 5 Oct 2024 13:15