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.

  • 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.


array_like – The corresponding kinematic flux

Other Parameters

axis (int, optional) – The index of the time axis, along which the calculations will be performed. Defaults to -1


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].