tropical_PODS

Installation

1.) Clone the "tropical_PODS" repo from Github

2.) Install environment using attached YAML file (tropicaldiagnosticsenvironment1130_2023.yml)

3.) Download data from NCAR GLADE (/glade/scratch/bwolding/GitHubTropicalPODs_Data) or email brandon.wolding@noaa.gov for data

4.) Move all data from the "GitHubTropicalPODsData" folder to your local repo folder "/tropicalPODS/data/"

5.) Run a simple test case to make sure everything is working, before moving on to the more complicated plume model. To start, open and run "/tropicalPODS/examples/jupyternotebookexamples/CSFprecipitationdiagnosticERA5_example.ipynb"

6.) If everything is running correctly to this point, then it is time to try to tackle the plume model, which requires additional installation.

7.) Navigate to "/tropicalPODs/plumemodelmasterbwoldingmod062222/" and delete the "thermofunctionsbwolding.cpython-311-darwin.so" file. You will need to create a ".so" file specific to your own architecture.

8.) In order to build your architecture specific .so file, navigate to "/tropicalPODs/plumemodelmasterbwoldingmod062222/" and then run "python setup.py build_ext --inplace" which should result in a ".so" file in that directory.

9.) Once you see a ".so" file in the "/tropicalPODs/plumemodelmasterbwoldingmod062222/" directory, you should be ready to run the plume model. Navigate to "/tropicalPODS/examples/jupyternotebookexamples/" and run "plumemodelDYNAMONSA_example.ipynb".

PODs

Contains the functions and modules necessary to compute various diagnostics. The main diagnostics included are:

Entraining plume buoyancy

As documented in Wolding et al. 2022, and citations therewithin. Idealized model for computing plume thermodynamic properties upon lifting and mixing. The notebook "plumemodelDYNAMONSAexample.ipynb" provides an example workflow.

The version of the plume model here has been slightly modified from previous versions (e.g. Ahmed and Neelin 2021), primarily in how the mixing coefficient is used to update plume properties.

The most relevant starting points for understanding the plume model are:

1.) The "numericalplumemodel" function in "/tropicalPODS/PODs/PODutils.py" shows how the mixing coefficient is defined, and has several comments that I have added.

2.) To really understand the "numericalplumemodel" function and the indexing conventions, look at how cmix is defined and used in the "plumelifting" function of "thermo_functions.pyx" in lines 485 - 495.

Temporal Co-Evolution of Column Saturation Fraction (CSF) and Precipitation

As documented in Wolding et al. 2020. The notebook "CSFprecipitationdiagnosticERA5example.ipynb" provides an example workflow.

This diagnostic also contains methods for compositing and plotting additional variables in CSF-P space.

Temporal Co-Evolution of Lower Tropospheric Vertically Integrated Buoyancy (VIB) and Precipitation

As documented in Wolding et al. 2022. The notebook "BDIBprecipitationdiagnosticERA5_example.ipynb" provides an example workflow.

This diagnostic also contains methods for compositing and plotting additional variables in VIB-P space.