Wet Bulb Temperature

The visualisation uses and CMIP6 climate data sourced from:

Population of the World: Population Count, v4.11
CMIP6 Climate: NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6)

The 2020 population is used for the visualisation. The CMIP6 climate datasets provide historical and future predictions of the climate earth system. Out of all the models provided, we use the model ACCESS-CM2. This dataset can be downloaded using the script provided in the following link. The variables used for the visualization are Near-Surface Specific Humidity (huss) and Daily Near-Surface Air Temperature (tas). We converted Specific Humidity into Relative Humidity, to then compute the dew point and the Wet-Bulb temperature using the Julia open source package Psychro.jl.

After downloading the data the post-processing was done with Julia and Python. We use several Python scientific libraries like Numpy, xarray, cmocean, and Matplotlib. Also, we use Julia packages Psychro.jl and NCDatasets.jl. The code to reproduce all the post-processing is available in the github repository Pale-Blue-Dot. Finally, the pre-processed data was used to create textures that we then used in Blender to create the visualisation and animation. The .blender files are also available in the github repository.