Frontogenesis2D

class rojak.turbulence.diagnostic.Frontogenesis2D(u_wind, v_wind, potential_temperature, geopotential, vector_derivatives)

Two-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, v_wind, potential_temperature, geopotential, vector_derivatives)

Parameters:

• name – Name of the diagnostic

• u_wind (DataArray)

• v_wind (DataArray)

• potential_temperature (DataArray)

• geopotential (DataArray)

• vector_derivatives (dict[VelocityDerivative, DataArray])

Return type:

None

Methods

__init__(u_wind, v_wind, ...)
to_zarr(output_base_dir, *[, file_name])	Export computed_value to a zarr store

Attributes

computed_value	The diagnostic's computed value
name	Name of the diagnostic