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6.3.4.3. 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)

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

Parameters:

• df_fc_suews (pandas.DataFrame) – DataFrame in SuPy forcing format

• ser_ra (pandas.Series) – Series with RA, aerodynamic resistance, [s m-1]

• g_max (float) – Maximum surface conductance [mm s-1]

• lai_max (float) – Maximum LAI [m2 m-2]

• wp_smd (float) – 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

• debug (bool, optional) – Option to output final calibrated ModelResult, by default False

Returns:

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)

Return type:

dict, or ModelResult if debug==True

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.