Python scripts for caculating the T-N Wave-Activity Flux derived by Takaya and Nakamura (JAS,2001).

• Coder: Lai Sheng @ College of Atmospheric Science, Chengdu University of Information Technology.
• E-mail: laish12@lzu.edu.cn

Takaya and Nakamura generalize the Plumb Wave-Activity Flux(Plumb,1985) so as to be applicable to small-amplitude Quasi-Geostrophic(QG) disturbances, either stationary or migratory, that are superimposed on a zonally varying basic flow, and introduced the T-N Wave-Activity Flux('TN01' for short).

TN01 is of great advantage in climate monitoring and diagnosis.

TN01 with improved meridional component based on Plumb Wave-Activity Flux is appropriate for analyzing Rossby waves in the zonally asymmetric westerly. And it reflect the evolution of long-waves which the E-P Flux can't.
(Shi Chunhua,2017)

These Python scripts use the TN01 diagnostic formula in Spherical coordinates,
which is the Eq.38 of Takaya's paper published in 2001:

We modified the GRADS script by Kazuaki Nishii into a Python3 version
(http://www.atmos.rcast.u-tokyo.ac.jp/nishii/programs/index.html)

• Python version
  • Python 3.6
• Data import
  • netCDF4
• Computation
  • numpy (1.16.1)
• Visualization
  • matplotlib (2.2.0)
  • basemap (1.1.0)

All computations are based on numpy arrays, which are very efficient.
Partial differential terms in the formula are calculated by numpy.gradient in the central difference method.
The library of Data import and Visualization could change in terms of requirements(PyNIO,PyNGL...).

Horizontal TN01 caltulation require the datas below:

• Climatology average background of windU_c & V_c and geopotentialphi_c.
• Geopotential in the analysis periodphi.

Geopotential anomalies will be used to compute pertubation stream-functionpsi_p in Quasi-Geostrophic(QG) assumption:

• psi_p=(phi-phi_c)/f
f is the Coriolis parameter: f=2*omega*sin(lat)

px for longitude direction
py for latitude direction

The script for TN01 3-Dimension is under development, it would be released in the coming months.

The output figures sample(Datas from ECMWF ERA-Interim)