Ctrl+K

supy.util.calib_g

Contents

Tip

  1. Need help? Please let us know in the UMEP Community.

  2. Please report issues with the manual on the GitHub Issues.

  3. Please cite SUEWS with proper information from our Zenodo page.

6.1.3.2.5.3. supy.util.calib_g#

supy.util.calib_g(df_fc_suews, ser_ra, g_max, lai_max, wp_smd, method='cobyla', prms_init=None, debug=False)[source]#

Calibrate parameters for modelling surface conductance over vegetated surfaces using LMFIT.

6.1.3.2.5.3. Parameters#

df_fc_suewspandas.DataFrame

DataFrame in SuPy forcing format

ser_ra: pandas.Series

Series with RA, aerodynamic resistance, [s m-1]

g_maxnumeric

Maximum surface conductance [mm s-1]

lai_maxnumeric

Maximum LAI [m2 m-2]

wp_smdnumeric

Wilting point indicated as soil moisture deficit [mm]

method: str, optional

Method used in minimisation by lmfit.minimize: details refer to its method.

prms_init: lmfit.Parameters, optional

Initial parameters for calibration

debugbool, optional

Option to output final calibrated ModelResult, by default False

6.1.3.2.5.3. Returns#

dict, or ModelResult if debug==True

  1. dict: {parameter_name -> best_fit_value}

  2. ModelResult

Note:

Parameters for surface conductance: g_lai (LAI related), g2 (solar radiation related), g_dq_base (humidity related), g_dq_shape (humidity related), g_ta (air temperature related), g_smd (soil moisture related)

6.1.3.2.5.3. Note#

For calibration validity, turbulent fluxes, QH and QE, in df_fc_suews should ONLY be observations, i.e., interpolated values should be avoided. To do so, please place np.nan as missing values for QH and QE.

Contents