Frontogenesis2D#
- class rojak.turbulence.diagnostic.Frontogenesis2D(u_wind: DataArray, v_wind: DataArray, potential_temperature: DataArray, geopotential: DataArray, vector_derivatives: dict[VelocityDerivative, DataArray])[source]#
Bases:
DiagnosticTwo-dimensional frontogenesis CAT diagnostic
Assuming a constant pressure surface and that the atmosphere is adiabatic, the frontogenesis function can be defined in two dimensions. It is defined in [Bluestein1993] (p. 242) as,
\[F = - \frac{1}{\left| \nabla_{p} \theta \right|} \left[\left( \frac{ \partial \theta }{ \partial x } \right)^{2} \frac{ \partial u }{ \partial x } + \frac{ \partial \theta }{ \partial y }\frac{ \partial \theta }{ \partial x } \frac{ \partial v }{ \partial x } + \frac{ \partial \theta }{ \partial x }\frac{ \partial \theta }{ \partial y } \frac{ \partial u }{ \partial y } + \left( \frac{ \partial \theta }{ \partial y } \right)^{2} \frac{ \partial v }{ \partial y }\right]\]where the subscript \(p\) indicates that the gradient is taken on a constant pressure surface.
- Parameters:
u_wind (DataArray) – Zonal wind speeds in m/s
v_wind (DataArray) – Meridional wind speeds in m/s
potential_temperature (DataArray) – Potential temperature
geopotential (DataArray) – Geopotential in m^2/s
vector_derivatives (dict[VelocityDerivative, DataArray]) – Dictionary containing all 4 velocity derivatives
- __init__(u_wind: DataArray, v_wind: DataArray, potential_temperature: DataArray, geopotential: DataArray, vector_derivatives: dict[VelocityDerivative, DataArray]) None[source]#
Methods
__init__(u_wind, v_wind, ...)Attributes
computed_valuename