PyTwThis repository contains Cython source code for calculating wet-bulb temperature (Tw) using the Davies-Jones (2008) [1] approach. It is ported from the Fortran code written by Buzan et al (2015) [2] (https://github.com/jrbuzan/HumanIndexMod_2020). The recently identified errors or inappropriate humidity approximations within the Fortran code have been corrected. What is in this repository?- Cython source files (wetbulb.pyx) for calculating Tw; Cython source file needs to be compiled first to generate shared object files (.so file) that can be directly imported in Python. Setup tools (setupwetbulb.py) are recommended for building Cython source file.- Calculate_Tw_with_CMIP6_data.ipynb: A jupyter nobtebook introducing the usage of the code. - environment.yml a YAML file that can be used to build conda environment containing all needed python packages. How to use the Jupyte notebooksBefore using the Jupyter notebook, users need to install dependent Python packages listed in environment.yml, and compile the Cython source file to generate the shared object file. Users can compile Cython source files with the following command:- for Intel compiler: - LDSHARED="icc -shared" CC=icc python setupTw.py develop; - for gcc compiler: - replace '-qopenmp' with '-fopenmp' in 'setupwetbulb.py' file - python setupTw.py build_ext --inplace; For introduction to Cython, please refer to https://cython.readthedocs.io/en/latest/ CitationIf you want to use our code, please consider cite `upcoming` References [1] Davies-Jones, R. An Efficient and Accurate Method for Computing the Wet-Bulb Temperature along Pseudoadiabats. Monthly Weather Review 136, 2764–2785 (2008). [2] Buzan, J. R., Oleson, K. & Huber, M. Implementation and comparison of a suite of heat stress metrics within the Community Land Model version 4.5. Geosci. Model Dev. 8, 151–170 (2015).