METEO PROCESSING RESULTS DESCRIPTION

This file contain a set of meteorological variables gapfilled and/or downscaled from the ERA-Interim dataset aggregated at yearly time resolution. The downscaling both in space (from cell to tower) and time (6 hourly to half hourly) is applied to seven variables using regressions with the site measurements when available according to the method described in Vuichard and Papale 2015.
The gapfilling of the site level measurements have been done using the MDS method as described in Reichstein et al. 2005.
For the variables where the ERA-interim downscaling has been applied, a consolidated version using the MDS gapfilled and the downscaled is also provided.


VARIABLES DEFINITION:
LEGEND: HH (half-hourly or hourly), DD (daily), WW (weekly), MM (monthly), YY (yearly)

TIMESTAMP (YYYY): ISO timestamp - short format

TA_F_MDS (deg C) Air temperature, gapfilled using MDS method 
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_F_MDS_QC (adimensional) Quality flag for TA_F_MDS 
    HH: 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

TA_F_MDS_NIGHT (deg C) Average nighttime TA_F_MDS 
    HH: not produced
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_F_MDS_NIGHT_SD (deg C) Standard deviation for TA_F_MDS_NIGHT 
    HH: not produced
    DD: from half-hourly data
    WW-YY: average SD from daily data

TA_F_MDS_NIGHT_QC (adimensional) Quality flag for TA_F_MDS_NIGHT 
    HH: not produced
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

TA_F_MDS_DAY (deg C) Average daytime TA_F_MDS 
    HH: not produced
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_F_MDS_DAY_SD (deg C) Standard deviation for TA_F_MDS_DAY 
    HH: not produced
    DD: from half-hourly data
    WW-YY: average SD from daily data

TA_F_MDS_DAY_QC (adimensional) Quality flag for TA_F_MDS_DAY 
    HH: not produced
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

TA_ERA (deg C) Air temperature, downscaled from ERA, linearly regressed using measured only site data 
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_ERA_NIGHT (deg C) Average nighttime TA_ERA 
    HH: not produced
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_ERA_NIGHT_SD (deg C) Standard deviation for TA_ERA_NIGHT 
    HH: not produced
    DD: from half-hourly data
    WW-YY: average SD from daily data

TA_ERA_DAY (deg C) Average daytime TA_ERA 
    HH: not produced
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_ERA_DAY_SD (deg C) Standard deviation for TA_ERA_DAY 
    HH: not produced
    DD: from half-hourly data
    WW-YY: average SD from daily data

TA_F (deg C) Air temperature, consolidated from TA_F_MDS and TA_ERA 
    HH: TA_F_MDS used if TA_F_MDS_QC is 0 or 1
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_F_QC (adimensional) Quality flag for TA_F 
    HH: 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

TA_F_NIGHT (deg C) Average nighttime TA_F 
    HH: not produced
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_F_NIGHT_SD (deg C) Standard deviation for TA_F_NIGHT 
    HH: not produced
    DD: from half-hourly data
    WW-YY: average SD from daily data

TA_F_NIGHT_QC (adimensional) Quality flag for TA_F_NIGHT 
    HH: not produced
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

TA_F_DAY (deg C) Average daytime TA_F 
    HH: not produced
    DD: average from half-hourly data
    WW-YY: average from daily data

TA_F_DAY_SD (deg C) Standard deviation for TA_F_DAY 
    HH: not produced
    DD: from half-hourly data
    WW-YY: average SD from daily data

TA_F_DAY_QC (adimensional) Quality flag for TA_F_DAY 
    HH: not produced
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

SW_IN_POT (W m-2) Shortwave radiation, incoming, potential (top of atmosphere) 
    DD: average from half-hourly data
    WW-MM: average from daily data
    YY: not defined

SW_IN_F_MDS (W m-2) Shortwave radiation, incoming, gapfilled using MDS (negative values set to zero, e.g., negative values from instrumentation noise) 
    DD: average from half-hourly data
    WW-YY: average from daily data

SW_IN_F_MDS_QC (adimensional) Quality flag for SW_IN_F_MDS 
    HH: 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

SW_IN_ERA (W m-2) Shortwave radiation, incoming, downscaled from ERA, linearly regressed using measured only site data (negative values set to zero) 
    DD: average from half-hourly data
    WW-YY: average from daily data

SW_IN_F (W m-2) Shortwave radiation, incoming consolidated from SW_IN_F_MDS and SW_IN_ERA (negative values set to zero) 
    HH: SW_IN_F_MDS used if SW_IN_F_MDS_QC is 0 or 1
    DD: average from half-hourly data
    WW-YY: average from daily data

SW_IN_F_QC (adimensional) Quality flag for SW_IN_F 
    HH: 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

LW_IN_F_MDS (W m-2) Longwave radiation, incoming, gapfilled using MDS 
    DD: average from half-hourly data
    WW-YY: average from daily data

LW_IN_F_MDS_QC (adimensional) Quality flag for LW_IN_F_MDS 
    HH: 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

LW_IN_ERA (W m-2) Longwave radiation, incoming, downscaled from ERA, linearly regressed using measured only site data 
    DD: average from half-hourly data
    WW-YY: average from daily data

LW_IN_F (W m-2) Longwave radiation, incoming, consolidated from LW_IN_F_MDS and LW_IN_ERA 
    HH: LW_IN_F_MDS used if LW_IN_F_MDS_QC is 0 or 1
    DD: average from half-hourly data
    WW-YY: average from daily data

LW_IN_F_QC (adimensional) Quality flag for LW_IN_F 
    HH: 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

LW_IN_JSB (W m-2) 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) 
    DD: average from half-hourly data
    WW-YY: average from daily data

LW_IN_JSB_QC (adimensional) Quality flag for LW_IN_JSB 
    HH: highest from TA_F_MDS_QC, SW_IN_F_MDS_QC, and VPD_F_MDS_QC, poorest quality prevails
    DD: fraction between 0-1, indicating percentage of calculated LW_IN starting from measured and good quality gapfill drivers data
    WW-YY: fraction between 0-1, indicating percentage ofcalculated LW_IN starting from measured and good quality gapfill drivers data (average from daily data)

LW_IN_JSB_ERA (W m-2) Longwave radiation, incoming, downscaled from ERA, linearly regressed using site level LW_IN_JSB calculated from measured only drivers 
    DD: average from half-hourly data
    WW-YY: average from daily data

LW_IN_JSB_F (W m-2) Longwave radiation, incoming, consolidated from LW_IN_JSB and LW_IN_JSB_ERA 
    HH: LW_IN_JSB used if LW_IN_JSB_QC is 0 or 1
    DD: average from half-hourly data
    WW-YY: average from daily data

LW_IN_JSB_F_QC (adimensional) Quality flag for LW_IN_JSB_F 
    HH: 0 = calculated from measured drivers; 1 = calculated from good quality gapfilled drivers; 2: downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

VPD_F_MDS (hPa) Vapor Pressure Deficit, gapfilled using MDS 
    DD: average from half-hourly data
    WW-YY: average from daily data

VPD_F_MDS_QC (adimensional) Quality flag for VPD_F_MDS 
    HH: 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

VPD_ERA (hPa) Vapor Pressure Deficit, downscaled from ERA, linearly regressed using measured only site data 
    DD: average from half-hourly data
    WW-YY: average from daily data

VPD_F (hPa) Vapor Pressure Deficit consolidated from VPD_F_MDS and VPD_ERA 
    HH: VPD_F_MDS used if VPD_F_MDS_QC is 0 or 1
    DD: average from half-hourly data
    WW-YY: average from daily data

VPD_F_QC (adimensional) Quality flag for VPD_F 
    HH: 0 = measured; 1 = good quality gapfill; 2 = downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

PA (kPa) Atmospheric pressure
    DD-YY: not defined

PA_ERA (kPa) Atmospheric pressure, downscaled from ERA, linearly regressed using measured only site data 
    DD: average from half-hourly data
    WW-YY: average from daily data

PA_F (kPa) Atmospheric pressure consolidated from PA and PA_ERA 
    HH: PA used if measured
    DD: average from half-hourly data
    WW-YY: average from daily data

PA_F_QC (adimensional) Quality flag for PA_F 
    HH: 0 = measured; 2 = downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured data
    WW-YY: fraction between 0-1, indicating percentage of measured data (average from daily data)

P (mm) Precipitation
    DD-YY: not defined

P_ERA (mm) Precipitation, downscaled from ERA, linearly regressed using measured only site data 
    DD: average from half-hourly data
    WW-YY: average from daily data

P_F (mm) Precipitation consolidated from P and P_ERA 
    HH: P used if measured
    DD: average from half-hourly data
    WW-YY: average from daily data

P_F_QC (adimensional) Quality flag for P_F 
    HH: 0 = measured; 2 = downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured data
    WW-YY: fraction between 0-1, indicating percentage of measured data (average from daily data)

WS (m s-1) Wind speed
    DD-YY: not defined

WS_ERA (m s-1) Wind speed, downscaled from ERA, linearly regressed using measured only site data 
    DD: average from half-hourly data
    WW-YY: average from daily data

WS_F (m s-1) Wind speed, consolidated from WS and WS_ERA 
    HH: WS used if measured
    DD: average from half-hourly data
    WW-YY: average from daily data

WS_F_QC (adimensional) Quality flag of WS_F 
    HH: 0 = measured; 2 = downscaled from ERA
    DD: fraction between 0-1, indicating percentage of measured data
    WW-YY: fraction between 0-1, indicating percentage of measured data (average from daily data)

CO2_F_MDS (umolCO2 mol-1) CO2 mole fraction, gapfilled with MDS 
    DD: average from half-hourly data
    WW-YY: average from daily data

CO2_F_MDS_QC (adimensional) Quality flag for CO2_F_MDS 
    HH: 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

TS_F_MDS_# (deg C) Soil temperature, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest) 
    DD: average from half-hourly data
    WW-YY: average from daily data

TS_F_MDS_#_QC (adimensional) Quality flag for TS_F_MDS_# 
    HH: 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)

SWC_F_MDS_# (%) Soil water content, gapfilled with MDS (numeric index "#" increases with the depth, 1 is shallowest) 
    DD: average from half-hourly data
    WW-YY: average from daily data

SWC_F_MDS_#_QC (adimensional) Quality flag for SWC_F_MDS_# 
    HH: 0 = measured; 1 = good quality gapfill; 2 = medium; 3 = poor
    DD: fraction between 0-1, indicating percentage of measured and good quality gapfill data
    WW-YY: fraction between 0-1, indicating percentage of measured and good quality gapfill data (average from daily data)


STATISTICS related to the ERA downscaling (regression between measured and ERA data, when not reported no relations have been used):

Var,Slope,Intercept,RMSE,Corr
TA,1.00,-0.02,2.09,0.98
PA,1.00,-0.33,0.27,0.93
VPD,1.03,-0.07,2.25,0.77
WS,0.79,0.70,0.86,0.77
P,0.28,-,-,-
SW_IN,1.01,-0.64,85.83,0.94
LW_IN,1.00,-0.00,21.69,0.93
LW_IN_JSB,1.00,-0.19,34.43,0.90