How to implement a new model

How to implement a new model#

In the CIF, a given numerical model has two main components:

  1. a black-box:

    it includes physical, chemical, transport processes, etc.; in most cases it is an executable compiled from Fortran or C sources; it computes outputs (concentration fields, footprints, etc.) from prescribed inputs (fluxes, meteorological fields, boundary conditions, etc.)

  2. a Python interface to the model:

    it produces the model inputs, reads the outputs and runs the executable properly.

The Python interface to a model is implemented as a pyCIF model class.

Prior to starting to implement your model, please make sure you have the following elements:

  1. a working version of your model (compilable sources), in forward mode, and if applicable in adjoint and tangent-linear modes

  2. a test directory with compatible inputs and outputs for your model

  3. (optional) an observation file you use to compare with your model; it is also possible to generate random observations with pyCIF

In the following, you will learn how to implement a model to pyCIF step-by-step.