q_vector¶
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metpy.calc.
q_vector
(u, v, temperature, pressure, dx, dy, static_stability=1)[source]¶ Calculate Q-vector at a given pressure level using the u, v winds and temperature.
\[\vec{Q} = (Q_1, Q_2) = - \frac{R}{\sigma p}\left( \frac{\partial \vec{v}_g}{\partial x} \cdot \nabla_p T, \frac{\partial \vec{v}_g}{\partial y} \cdot \nabla_p T \right)\]This formula follows equation 5.7.55 from [Bluestein1992], and can be used with the the below form of the quasigeostrophic omega equation to assess vertical motion ([Bluestein1992] equation 5.7.54):
\[\left( \nabla_p^2 + \frac{f_0^2}{\sigma} \frac{\partial^2}{\partial p^2} \right) \omega = - 2 \nabla_p \cdot \vec{Q} - \frac{R}{\sigma p} \beta \frac{\partial T}{\partial x}.\]Parameters: - u ((M, N) ndarray) – x component of the wind (geostrophic in QG-theory)
- v ((M, N) ndarray) – y component of the wind (geostrophic in QG-theory)
- temperature ((M, N) ndarray) – Array of temperature at pressure level
- pressure (pint.Quantity) – Pressure at level
- dx (float) – The grid spacing in the x-direction
- dy (float) – The grid spacing in the y-direction
- static_stability (pint.Quantity, optional) – The static stability at the pressure level. Defaults to 1 if not given to calculate the Q-vector without factoring in static stability.
Returns: tuple of (M, N) ndarrays – The components of the Q-vector in the u- and v-directions respectively
See also