ecpet.ecpost module

EC-PeT Postprocessing Module

Advanced quality control and flux calculation routines for eddy-covariance data. Implements comprehensive postprocessing following established methodologies for surface-atmosphere exchange measurements, including flux quality assessment, meteorological variable derivation, and standardized output generation.

The module performs:

  • Derived meteorological variable calculations (potential temperature, Obukhov length, mixing ratios, density corrections)

  • Mean-value quality control tests following established protocols

  • Integral turbulence characteristic analysis (Foken & Wichura methods)

  • Stationarity assessment using multiple approaches

  • Wind sector exclusion and footprint analysis

  • Error threshold validation for flux measurements

  • Quality flag application with configurable rules

  • Flux interdependency assessment

ecpet.ecpost.derived_variables(intervals)

Calculate derived meteorological and flux variables.

Parameters:

intervals (pandas.DataFrame) – DataFrame with basic flux and meteorological measurements

Returns:

Updated DataFrame with derived variables

Return type:

pandas.DataFrame

Note:

Calculates potential temperature, virtual potential temperature, Obukhov length, CO2 mixing ratios, and density corrections. Temperature selection based on ‘whichtemp’ indicator.

ecpet.ecpost.qc_mean_run(conf, intervals)

Execute quality control tests on mean flux and meteorological values.

Parameters:

  • conf (object) – Configuration object with QC test parameters

  • intervals (pandas.DataFrame) – DataFrame with calculated mean values and fluxes

Returns:

Updated DataFrame with QC flags and quality measures

Return type:

pandas.DataFrame

Note:

Implements tests including mean vertical wind check, integral turbulence characteristics, excluded sectors, footprint analysis, and excessive error detection.

ecpet.ecpost.apply_flags(conf, intervals)

Apply quality control flag rules to flux measurements.

Parameters:

  • conf (object) – Configuration object with flagging rules and thresholds

  • intervals (pandas.DataFrame) – DataFrame with QC test results and flags

Returns:

Updated DataFrame with final flux flags and deleted bad values

Return type:

pandas.DataFrame

Note:

Uses configurable rules to combine individual test flags into final flux quality flags. Supports soft/hard flagging and flux interdependency rules.

ecpet.ecpost.flags2_to_file(conf, intervals)

Write second-level quality flags to output file.

Parameters:

  • conf (object) – Configuration object with output directory settings

  • intervals (pandas.DataFrame) – DataFrame containing second-level QC flags

Note:

Creates flags2.dat file with mean-value QC test results and quality measures for postprocessing analysis.

ecpet.ecpost.output_to_file(conf, intervals)

Write final quality-controlled flux data to output file.

Parameters:

  • conf (object) – Configuration object with output settings

  • intervals (pandas.DataFrame) – DataFrame with final QC results and flux values

Note:

Generates main output file with quality-controlled fluxes, flags, and supporting meteorological variables in standardized format.

ecpet.ecpost.itc_u(zeta, ust, f)

Calculate integral turbulence characteristic for horizontal wind component.

Parameters:

  • zeta (float) – Stability parameter (z-d)/L

  • ust (float) – Friction velocity [m/s]

  • f (float) – Coriolis parameter [s^-1]

Returns:

Integral turbulence characteristic for u-component

Return type:

float

Note:

Combined Thomas (2001) & Foken (1997) formulation. Uses different expressions for unstable, neutral, and stable conditions.

ecpet.ecpost.itc_w(zeta, ust, f)

Calculate integral turbulence characteristic for vertical wind component.

Parameters:

  • zeta (float) – Stability parameter (z-d)/L

  • ust (float) – Friction velocity [m/s]

  • f (float) – Coriolis parameter [s^-1]

Returns:

Integral turbulence characteristic for w-component

Return type:

float

Note:

Combined Thomas (2001) & Foken (1997) formulation. Accounts for atmospheric stability effects on vertical wind variance.

ecpet.ecpost.itc_t(zeta)

Calculate integral turbulence characteristic for scalar quantities.

Parameters:

zeta (float) – Stability parameter (z-d)/L

Returns:

Integral turbulence characteristic for temperature/scalars

Return type:

float

Note:

Thomas & Foken (2002) formulation for temperature and scalar variance scaling. Applied to both temperature and humidity.

ecpet.ecpost.postprocessor(conf, intervals)

Main postprocessing routine for eddy-covariance flux data.

Parameters:

  • conf (object) – Configuration object with all processing parameters

  • intervals (pandas.DataFrame) – DataFrame with preprocessed flux measurements

Returns:

DataFrame with final quality-controlled flux results

Return type:

pandas.DataFrame

Note:

Orchestrates complete postprocessing workflow: - Calculate derived meteorological variables - Execute mean-value quality control tests - Apply flux quality flagging rules - Generate output files