kinematic_flux#
- metpy.calc.kinematic_flux(vel, b, perturbation=False, axis=-1)[source]#
Compute the kinematic flux from two time series.
Compute the kinematic flux from the time series of two variables vel and b. Note that to be a kinematic flux, at least one variable must be a component of velocity.
- Parameters:
vel (array-like) – A component of velocity
b (array-like) – May be a component of velocity or a scalar variable (e.g. Temperature)
perturbation (bool, optional) – True if the vel and b variables are perturbations. If False, perturbations will be calculated by removing the mean value from each variable. Defaults to False.
axis (int, optional) – The index of the time axis, along which the calculations will be performed. Defaults to -1
- Returns:
array-like – The corresponding kinematic flux
Notes
A kinematic flux is computed as
\[\overline{u^{\prime} s^{\prime}}\]where at the prime notation denotes perturbation variables, and at least one variable is perturbation velocity. For example, the vertical kinematic momentum flux (two velocity components):
\[\overline{u^{\prime} w^{\prime}}\]or the vertical kinematic heat flux (one velocity component, and one scalar):
\[\overline{w^{\prime} T^{\prime}}\]If perturbation variables are passed into this function (i.e. perturbation is True), the kinematic flux is computed using the equation above.
However, the equation above can be rewritten as
\[\overline{us} - \overline{u}~\overline{s}\]which is computationally more efficient. This is how the kinematic flux is computed in this function if perturbation is False.
For more information on the subject, please see [Garratt1994].