def l3qc(cf, ds2): """ """ # make a copy of the L2 data ds3 = copy.deepcopy(ds2) # set some attributes for this level qcutils.UpdateGlobalAttributes(cf, ds3, "L3") # put the control file name into the global attributes ds3.globalattributes['controlfile_name'] = cf['controlfile_name'] # check to see if we have any imports qcgf.ImportSeries(cf, ds3) # apply linear corrections to the data qcck.do_linear(cf, ds3) # ************************ # *** Merge humidities *** # ************************ # merge whatever humidities are available qcts.MergeHumidities(cf, ds3, convert_units=True) # ************************** # *** Merge temperatures *** # ************************** # get the air temperature from the CSAT virtual temperature qcts.TaFromTv(cf, ds3) # merge the HMP and corrected CSAT data qcts.MergeSeries(cf, ds3, "Ta", convert_units=True) qcutils.CheckUnits(ds3, "Ta", "C", convert_units=True) # *************************** # *** Calcuate humidities *** # *************************** # calculate humidities (absolute, specific and relative) from whatever is available qcts.CalculateHumidities(ds3) # ******************************** # *** Merge CO2 concentrations *** # ******************************** # merge the 7500 CO2 concentration # PRI 09/08/2017 possibly the ugliest thing I have done yet # This needs to be abstracted to a general alias checking routine at the # start of the L3 processing so that possible aliases are mapped to a single # set of variable names. if "CO2" in cf["Variables"]: CO2 = "CO2" elif "Cc" in cf["Variables"]: CO2 = "Cc" else: msg = "Label for CO2 ('CO2','Cc') not found in control file" logger.error(msg) return qcts.MergeSeries(cf, ds3, CO2, convert_units=True) # ****************************************** # *** Calculate meteorological variables *** # ****************************************** # Update meteorological variables qcts.CalculateMeteorologicalVariables(ds3) # ************************************************* # *** Calculate fluxes from covariances section *** # ************************************************* # check to see if the user wants to use the fluxes in the L2 file if not qcutils.cfoptionskeylogical(cf, Key="UseL2Fluxes", default=False): # check the covariance units and change if necessary qcts.CheckCovarianceUnits(ds3) # do the 2D coordinate rotation qcts.CoordRotation2D(cf, ds3) # do the Massman frequency attenuation correction qcts.MassmanStandard(cf, ds3) # calculate the fluxes qcts.CalculateFluxes(cf, ds3) # approximate wT from virtual wT using wA (ref: Campbell OPECSystem manual) qcts.FhvtoFh(cf, ds3) # correct the H2O & CO2 flux due to effects of flux on density measurements qcts.Fe_WPL(cf, ds3) qcts.Fc_WPL(cf, ds3) # ************************************** # *** Calculate Monin-Obukhov length *** # ************************************** qcts.CalculateMoninObukhovLength(ds3) # ************************** # *** CO2 and Fc section *** # ************************** # convert CO2 units if required qcutils.ConvertCO2Units(cf, ds3, CO2=CO2) # calculate Fc storage term - single height only at present qcts.CalculateFcStorageSinglePoint(cf, ds3, Fc_out='Fc_single', CO2_in=CO2) # convert Fc and Fc_storage units if required qcutils.ConvertFcUnits(cf, ds3) # merge Fc and Fc_storage series if required merge_list = [ label for label in cf["Variables"].keys() if label[0:2] == "Fc" and "MergeSeries" in cf["Variables"][label].keys() ] for label in merge_list: qcts.MergeSeries(cf, ds3, label, save_originals=True) # correct Fc for storage term - only recommended if storage calculated from profile available qcts.CorrectFcForStorage(cf, ds3) # ************************* # *** Radiation section *** # ************************* # merge the incoming shortwave radiation qcts.MergeSeries(cf, ds3, 'Fsd') # calculate the net radiation from the Kipp and Zonen CNR1 qcts.CalculateNetRadiation(cf, ds3, Fn_out='Fn_KZ', Fsd_in='Fsd', Fsu_in='Fsu', Fld_in='Fld', Flu_in='Flu') qcts.MergeSeries(cf, ds3, 'Fn') # **************************************** # *** Wind speed and direction section *** # **************************************** # combine wind speed from the Wind Sentry and the SONIC qcts.MergeSeries(cf, ds3, 'Ws') # combine wind direction from the Wind Sentry and the SONIC qcts.MergeSeries(cf, ds3, 'Wd') # ******************** # *** Soil section *** # ******************** # correct soil heat flux for storage # ... either average the raw ground heat flux, soil temperature and moisture # and then do the correction (OzFlux "standard") qcts.AverageSeriesByElements(cf, ds3, 'Ts') qcts.AverageSeriesByElements(cf, ds3, 'Sws') if qcutils.cfoptionskeylogical(cf, Key='CorrectIndividualFg'): # ... or correct the individual ground heat flux measurements (James' method) qcts.CorrectIndividualFgForStorage(cf, ds3) qcts.AverageSeriesByElements(cf, ds3, 'Fg') else: qcts.AverageSeriesByElements(cf, ds3, 'Fg') qcts.CorrectFgForStorage(cf, ds3, Fg_out='Fg', Fg_in='Fg', Ts_in='Ts', Sws_in='Sws') # calculate the available energy qcts.CalculateAvailableEnergy(ds3, Fa_out='Fa', Fn_in='Fn', Fg_in='Fg') # create new series using MergeSeries or AverageSeries qcck.CreateNewSeries(cf, ds3) # re-apply the quality control checks (range, diurnal and rules) qcck.do_qcchecks(cf, ds3) # coordinate gaps in the three main fluxes qcck.CoordinateFluxGaps(cf, ds3) # coordinate gaps in Ah_7500_Av with Fc qcck.CoordinateAh7500AndFcGaps(cf, ds3) # check missing data and QC flags are consistent qcutils.CheckQCFlags(ds3) # get the statistics for the QC flags and write these to an Excel spreadsheet qcio.get_seriesstats(cf, ds3) # write the percentage of good data as a variable attribute qcutils.get_coverage_individual(ds3) # write the percentage of good data for groups qcutils.get_coverage_groups(ds3) return ds3
def l3qc(cf, ds2): """ Corrections Generates L3 from L2 data Functions performed: qcts.AddMetVars (optional) qcts.CorrectSWC (optional*) qcck.do_linear (all sites) qcutils.GetMergeList + qcts.MergeSeries Ah_EC (optional)x qcts.TaFromTv (optional) qcutils.GetMergeList + qcts.MergeSeries Ta_EC (optional)x qcts.CoordRotation2D (all sites) qcts.MassmanApprox (optional*)y qcts.Massman (optional*)y qcts.CalculateFluxes (used if Massman not optioned)x qcts.CalculateFluxesRM (used if Massman optioned)y qcts.FhvtoFh (all sites) qcts.Fe_WPL (WPL computed on fluxes, as with Campbell algorithm)+x qcts.Fc_WPL (WPL computed on fluxes, as with Campbell algorithm)+x qcts.Fe_WPLcov (WPL computed on kinematic fluxes (ie, covariances), as with WPL80)+y qcts.Fc_WPLcov (WPL computed on kinematic fluxes (ie, covariances), as with WPL80)+y qcts.CalculateNetRadiation (optional) qcutils.GetMergeList + qcts.MergeSeries Fsd (optional) qcutils.GetMergeList + qcts.MergeSeries Fn (optional*) qcts.InterpolateOverMissing (optional) AverageSeriesByElements (optional) qcts.CorrectFgForStorage (all sites) qcts.Average3SeriesByElements (optional) qcts.CalculateAvailableEnergy (optional) qcck.do_qcchecks (all sites) qcck.gaps (optional) *: requires ancillary measurements for paratmerisation +: each site requires one pair, either Fe_WPL & Fc_WPL (default) or Fe_WPLCov & FcWPLCov x: required together in option set y: required together in option set """ # make a copy of the L2 data ds3 = copy.deepcopy(ds2) # set some attributes for this level qcutils.UpdateGlobalAttributes(cf, ds3, "L3") # initialise the global attribute to document the functions used ds3.globalattributes['Functions'] = '' # put the control file name into the global attributes ds3.globalattributes['controlfile_name'] = cf['controlfile_name'] # check to see if we have any imports qcgf.ImportSeries(cf, ds3) # correct measured soil water content using empirical relationship to collected samples qcts.CorrectSWC(cf, ds3) # apply linear corrections to the data qcck.do_linear(cf, ds3) # merge whatever humidities are available qcts.MergeHumidities(cf, ds3, convert_units=True) # get the air temperature from the CSAT virtual temperature qcts.TaFromTv(cf, ds3) # merge the HMP and corrected CSAT data qcts.MergeSeries(cf, ds3, 'Ta', [0, 10], convert_units=True) qcutils.CheckUnits(ds3, "Ta", "C", convert_units=True) # calculate humidities (absolute, specific and relative) from whatever is available qcts.CalculateHumidities(ds3) # merge the 7500 CO2 concentration qcts.MergeSeries(cf, ds3, 'Cc', [0, 10], convert_units=True) qcutils.CheckUnits(ds3, "Cc", "mg/m3", convert_units=True) # add relevant meteorological values to L3 data qcts.CalculateMeteorologicalVariables(ds3) # check to see if the user wants to use the fluxes in the L2 file if not qcutils.cfoptionskeylogical(cf, Key="UseL2Fluxes", default=False): # check the covariancve units and change if necessary qcts.CheckCovarianceUnits(ds3) # do the 2D coordinate rotation qcts.CoordRotation2D(cf, ds3) # do the Massman frequency attenuation correction qcts.MassmanStandard(cf, ds3) # calculate the fluxes qcts.CalculateFluxes(cf, ds3) # approximate wT from virtual wT using wA (ref: Campbell OPECSystem manual) qcts.FhvtoFh(cf, ds3) # correct the H2O & CO2 flux due to effects of flux on density measurements qcts.Fe_WPL(cf, ds3) qcts.Fc_WPL(cf, ds3) # convert CO2 units if required qcutils.ConvertCO2Units(cf, ds3, Cc='Cc') # calculate Fc storage term - single height only at present qcts.CalculateFcStorage(cf, ds3) # convert Fc and Fc_storage units if required qcutils.ConvertFcUnits(cf, ds3, Fc='Fc', Fc_storage='Fc_storage') # correct Fc for storage term - only recommended if storage calculated from profile available qcts.CorrectFcForStorage(cf, ds3) # merge the incoming shortwave radiation qcts.MergeSeries(cf, ds3, 'Fsd', [0, 10]) # calculate the net radiation from the Kipp and Zonen CNR1 qcts.CalculateNetRadiation(cf, ds3, Fn_out='Fn_KZ', Fsd_in='Fsd', Fsu_in='Fsu', Fld_in='Fld', Flu_in='Flu') qcts.MergeSeries(cf, ds3, 'Fn', [0, 10]) # combine wind speed from the Wind Sentry and the CSAT qcts.MergeSeries(cf, ds3, 'Ws', [0, 10]) # combine wind direction from the Wind Sentry and the CSAT qcts.MergeSeries(cf, ds3, 'Wd', [0, 10]) # correct soil heat flux for storage # ... either average the raw ground heat flux, soil temperature and moisture # and then do the correction (OzFlux "standard") qcts.AverageSeriesByElements(cf, ds3, 'Ts') qcts.AverageSeriesByElements(cf, ds3, 'Sws') if qcutils.cfoptionskeylogical(cf, Key='CorrectIndividualFg'): # ... or correct the individual ground heat flux measurements (James' method) qcts.CorrectIndividualFgForStorage(cf, ds3) qcts.AverageSeriesByElements(cf, ds3, 'Fg') else: qcts.AverageSeriesByElements(cf, ds3, 'Fg') qcts.CorrectFgForStorage(cf, ds3, Fg_out='Fg', Fg_in='Fg', Ts_in='Ts', Sws_in='Sws') # calculate the available energy qcts.CalculateAvailableEnergy(ds3, Fa_out='Fa', Fn_in='Fn', Fg_in='Fg') # create new series using MergeSeries or AverageSeries qcck.CreateNewSeries(cf, ds3) # create a series of daily averaged soil moisture interpolated back to the time step #qcts.DailyAverageSws_Interpolated(cf,ds3,Sws_out='Sws_daily',Sws_in='Sws') # re-apply the quality control checks (range, diurnal and rules) qcck.do_qcchecks(cf, ds3) # coordinate gaps in the three main fluxes qcck.CoordinateFluxGaps(cf, ds3) # coordinate gaps in Ah_7500_Av with Fc qcck.CoordinateAh7500AndFcGaps(cf, ds3) # get the statistics for the QC flags and write these to an Excel spreadsheet qcio.get_seriesstats(cf, ds3) # write the percentage of good data as a variable attribute qcutils.get_coverage_individual(ds3) # write the percentage of good data for groups qcutils.get_coverage_groups(ds3) return ds3
def l3qc(cf, ds2): """ Corrections Generates L3 from L2 data Functions performed: qcts.AddMetVars (optional) qcts.CorrectSWC (optional*) qcck.do_linear (all sites) qcutils.GetMergeList + qcts.MergeSeries Ah_EC (optional)x qcts.TaFromTv (optional) qcutils.GetMergeList + qcts.MergeSeries Ta_EC (optional)x qcts.CoordRotation2D (all sites) qcts.MassmanApprox (optional*)y qcts.Massman (optional*)y qcts.CalculateFluxes (used if Massman not optioned)x qcts.CalculateFluxesRM (used if Massman optioned)y qcts.FhvtoFh (all sites) qcts.Fe_WPL (WPL computed on fluxes, as with Campbell algorithm)+x qcts.Fc_WPL (WPL computed on fluxes, as with Campbell algorithm)+x qcts.Fe_WPLcov (WPL computed on kinematic fluxes (ie, covariances), as with WPL80)+y qcts.Fc_WPLcov (WPL computed on kinematic fluxes (ie, covariances), as with WPL80)+y qcts.CalculateNetRadiation (optional) qcutils.GetMergeList + qcts.MergeSeries Fsd (optional) qcutils.GetMergeList + qcts.MergeSeries Fn (optional*) qcts.InterpolateOverMissing (optional) AverageSeriesByElements (optional) qcts.CorrectFgForStorage (all sites) qcts.Average3SeriesByElements (optional) qcts.CalculateAvailableEnergy (optional) qcck.do_qcchecks (all sites) qcck.gaps (optional) *: requires ancillary measurements for paratmerisation +: each site requires one pair, either Fe_WPL & Fc_WPL (default) or Fe_WPLCov & FcWPLCov x: required together in option set y: required together in option set """ # make a copy of the L2 data ds3 = copy.deepcopy(ds2) ds3.globalattributes['nc_level'] = 'L3' ds3.globalattributes['EPDversion'] = sys.version ds3.globalattributes['QC_version_history'] = cfg.__doc__ # put the control file name into the global attributes ds3.globalattributes['controlfile_name'] = cf['controlfile_name'] # calculate NDVI if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='NDVI') and cf['Functions']['NDVI'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', calculateNDVI' except: ds3.globalattributes['L3Functions'] = 'calculateNDVI' log.info(' Calculating NDVI from component reflectances ...') qcts.CalculateNDVI(cf, ds3) # bypass soil temperature correction for Sws (when Ts bad) if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='BypassSwsTcorr' ) and cf['Functions']['BypassSwsTcorr'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', BypassSwsTcorr' except: ds3.globalattributes['L3Functions'] = 'BypassSwsTcorr' log.info(' Re-computing Sws without temperature correction ...') qcts.BypassTcorr(cf, ds3) # correct measured soil water content using empirical relationship to collected samples if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='CorrectSWC') and cf['Functions']['CorrectSWC'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CorrectSWC' except: ds3.globalattributes['L3Functions'] = 'CorrectSWC' log.info(' Correcting soil moisture data ...') qcts.CorrectSWC(cf, ds3) # apply linear corrections to the data if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', do_linear' except: ds3.globalattributes['L3Functions'] = 'do_linear' log.info(' Applying linear corrections ...') qcck.do_linear(cf, ds3) # determine HMP Ah if not output by datalogger if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='CalculateAh' ) and cf['Functions']['CalculateAh'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CalculateAh' except: ds3.globalattributes['L3Functions'] = 'CalculateAh' log.info(' Adding HMP Ah to database') qcts.CalculateAhHMP(cf, ds3) # merge the HMP and corrected 7500 data if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='MergeSeriesAhTa' ) and cf['Functions']['MergeSeriesAhTa'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', MergeSeriesAhTaCc' except: ds3.globalattributes['L3Functions'] = 'MergeSeriesAhTaCc' qcts.MergeSeries(cf, ds3, 'Ah', [0, 10]) qcts.MergeSeries(cf, ds3, 'Cc', [0, 10]) # get the air temperature from the CSAT virtual temperature try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', TaFromTv' except: ds3.globalattributes['L3Functions'] = 'TaFromTv' qcts.TaFromTv(cf, ds3) # merge the HMP and corrected CSAT data qcts.MergeSeries(cf, ds3, 'Ta', [0, 10]) # add relevant meteorological values to L3 data if (qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections') and cf['Functions']['Corrections'] == 'True') or (qcutils.cfkeycheck( cf, Base='Functions', ThisOne='CalculateMetVars') and cf['Functions']['CalculateMetVars'] == 'True'): try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CalculateMetVars' except: ds3.globalattributes['L3Functions'] = 'CalculateMetVars' log.info(' Adding standard met variables to database') qcts.CalculateMeteorologicalVariables(ds3) # do the 2D coordinate rotation if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CoordRotation2D' except: ds3.globalattributes['L3Functions'] = 'CoordRotation2D' qcts.CoordRotation2D(cf, ds3) # do the Massman frequency attenuation correction if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', Massman' except: ds3.globalattributes['L3Functions'] = 'Massman' qcts.MassmanStandard(cf, ds3) # calculate the fluxes if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CalculateFluxes' except: ds3.globalattributes['L3Functions'] = 'CalculateFluxes' qcts.CalculateFluxes(cf, ds3) # approximate wT from virtual wT using wA (ref: Campbell OPECSystem manual) if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', FhvtoFh' except: ds3.globalattributes['L3Functions'] = 'FhvtoFh' qcts.FhvtoFh(cf, ds3) # correct the H2O & CO2 flux due to effects of flux on density measurements if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='WPLcov') and cf['Functions']['WPLcov'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', WPLcov' except: ds3.globalattributes['L3Functions'] = 'WPLcov' qcts.do_WPL(cf, ds3, cov='True') else: try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', WPL' except: ds3.globalattributes['L3Functions'] = 'WPL' qcts.do_WPL(cf, ds3) # calculate the net radiation from the Kipp and Zonen CNR1 if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='CalculateNetRadiation' ) and cf['Functions']['CalculateNetRadiation'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CalculateNetRadiation' except: ds3.globalattributes['L3Functions'] = 'CalculateNetRadiation' qcts.MergeSeries(cf, ds3, 'Fsd', [0, 10]) qcts.CalculateNetRadiation(ds3, 'Fn_KZ', 'Fsd', 'Fsu', 'Fld', 'Flu') qcts.MergeSeries(cf, ds3, 'Fn', [0, 10]) # combine wind speed from the CSAT and the Wind Sentry if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='MergeSeriesWS' ) and cf['Functions']['MergeSeriesWS'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', MergeSeriesWS' except: ds3.globalattributes['L3Functions'] = 'MergeSeriesWS' qcts.MergeSeries(cf, ds3, 'Ws', [0, 10]) # average the soil temperature data if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': if 'SoilAverage' not in ds3.globalattributes['L3Functions']: try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', SoilAverage' except: ds3.globalattributes['L3Functions'] = 'SoilAverage' # interpolate over any ramaining gaps up to 3 hours in length qcts.AverageSeriesByElementsI(cf, ds3, 'Ts') qcts.AverageSeriesByElementsI(cf, ds3, 'Sws') # correct the measured soil heat flux for storage in the soil layer above the sensor if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CorrectFgForStorage' except: ds3.globalattributes['L3Functions'] = 'CorrectFgForStorage' if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='IndividualFgCorrection' ) and cf['Functions']['IndividualFgCorrection'] == 'True': qcts.CorrectIndividualFgForStorage(cf, ds3) qcts.AverageSeriesByElementsI(cf, ds3, 'Fg') else: qcts.AverageSeriesByElementsI(cf, ds3, 'Fg') qcts.CorrectGroupFgForStorage(cf, ds3) # calculate the available energy if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='CalculateAvailableEnergy' ) and cf['Functions']['CalculateAvailableEnergy'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CalculateAvailableEnergy' except: ds3.globalattributes['L3Functions'] = 'CalculateAvailableEnergy' qcts.CalculateAvailableEnergy(ds3) if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='DiagnosticMode'): if cf['Functions']['DiagnosticMode'] == 'False': qcutils.prepOzFluxVars(cf, ds3) else: qcutils.prepOzFluxVars(cf, ds3) # calculate specific humidity and saturated specific humidity profile if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='qTprofile') and cf['Functions']['qTprofile'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', qTprofile' except: ds3.globalattributes['L3Functions'] = 'qTprofile' qcts.CalculateSpecificHumidityProfile(cf, ds3) # calculate Penman-Monteith inversion if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='PenmanMonteith' ) and cf['Functions']['PenmanMonteith'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', PenmanMonteith' except: ds3.globalattributes['L3Functions'] = 'PenmanMonteith' qcts.do_PenmanMonteith(cf, ds3) # calculate bulk Richardson numbers if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='bulkRichardson' ) and cf['Functions']['bulkRichardson'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', bulkRichardson' except: ds3.globalattributes['L3Functions'] = 'bulkRichardson' qcts.do_bulkRichardson(cf, ds3) # re-apply the quality control checks (range, diurnal and rules) if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', do_qccheck(RangeCheck, diurnalcheck, excludedates, excludehours)' qcck.do_qcchecks(cf, ds3) # quality control checks (range, diurnal and rules) without flux post-processing if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='QCChecks') and cf['Functions']['QCChecks'] == 'True': qcck.do_qcchecks(cf, ds3) # apply the ustar filter if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='ustarFilter' ) and cf['Functions']['ustarFilter'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', ustarFilter' except: ds3.globalattributes['L3Functions'] = 'ustarFilter' qcts.FilterFcByUstar(cf, ds3) # coordinate gaps in the three main fluxes if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='CoordinateFluxGaps' ) and cf['Functions']['CoordinateFluxGaps'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CoordinateFluxGaps' except: ds3.globalattributes['L3Functions'] = 'CoordinateFluxGaps' qcck.CoordinateFluxGaps(cf, ds3) # coordinate gaps in Ah_7500_Av with Fc if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CoordinateAh7500AndFcGaps' except: ds3.globalattributes['L3Functions'] = 'CoordinateAh7500AndFcGaps' qcck.CoordinateAh7500AndFcGaps(cf, ds3) # calcluate ET at observation interval if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='CalculateET' ) and cf['Functions']['CalculateET'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', CalculateET' except: ds3.globalattributes['L3Functions'] = 'CalculateET' log.info(' Calculating ET') qcts.CalculateET(cf, ds3, 'L3') # run MOST (Buckingham Pi) 2d footprint model (Kljun et al. 2004) if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='footprint') and cf['Functions']['footprint'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', footprint' except: ds3.globalattributes['L3Functions'] = 'footprint' qcts.do_footprint_2d(cf, ds3) if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Corrections' ) and cf['Functions']['Corrections'] == 'True': qcio.get_seriesstats(cf, ds3) # convert Fc [mgCO2 m-2 s-1] to Fc_co2 [mgCO2 m-2 s-1], Fc_c [mgC m-2 s-1], NEE [umol m-2 s-1] and NEP = - NEE if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='convertFc') and cf['Functions']['convertFc'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', convertFc' except: ds3.globalattributes['L3Functions'] = 'convertFc' qcts.ConvertFc(cf, ds3) # convert Fc [mgCO2 m-2 s-1] to Fc [umol m-2 s-1] if qcutils.cfkeycheck( cf, Base='Functions', ThisOne='JasonFc') and cf['Functions']['JasonFc'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', convertFc (umol only)' except: ds3.globalattributes['L3Functions'] = 'convertFc (umol only)' qcts.ConvertFcJason(cf, ds3) # write the percentage of good data as a variable attribute qcutils.get_coverage_individual(ds3) # write the percentage of good data for groups qcutils.get_coverage_groups(ds3) # compute water-use efficiency from flux-gradient similarity (appendix A, Scanlon & Sahu 2008) if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='wue') and cf['Functions']['wue'] == 'True': try: ds3.globalattributes[ 'L3Functions'] = ds3.globalattributes['L3Functions'] + ', wue' except: ds3.globalattributes['L3Functions'] = 'wue' log.info( ' Calculating water-use efficiency from flux-gradient similarity') qcts.CalculateWUEfromSimilarity(cf, ds3) # compute climatology for L3 data if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='climatology' ) and cf['Functions']['climatology'] == 'True': try: ds3.globalattributes['L3Functions'] = ds3.globalattributes[ 'L3Functions'] + ', climatology' except: ds3.globalattributes['L3Functions'] = 'climatology' qcts.do_climatology(cf, ds3) if qcutils.cfkeycheck(cf, Base='Functions', ThisOne='Sums') and cf['Functions']['Sums'] == 'L3': try: ds3.globalattributes[ 'L3Functions'] = ds3.globalattributes['L5Functions'] + ', Sums' except: ds3.globalattributes['L3Functions'] = 'Sums' qcts.do_sums(cf, ds3) try: ds3.globalattributes['Functions'] = ds3.globalattributes[ 'Functions'] + ', ' + ds3.globalattributes['L3Functions'] except: ds3.globalattributes['Functions'] = ds3.globalattributes['L3Functions'] return ds3