Description Globally static atmospheric models, such as ISA and US-76, are commonly used to model the flight, aero- and aerothermal dynamics of transatmopheric vehicles such as launchers and spaceplanes. These models approximate the atmospheric temperature, pressure and density as a function of altitude. However, these models are very simplified relative to  reality. This project looks at classifying the uncertainty of the these models based on published experimental data, and higher fidelity atmospheric models that account for many more parameters. Key Objectives 1- Literature review and build an understanding of atmospheric modelling and its use in the design and analysis of space transportation systems (e.g., trajectory optimisation, CFD, etc.) 2- Write a software program for US-76 and ISA in Matlab (or Python) 3- Import and adapt other higher fidelity models, such as DTM-13 and NRLMSISE-00 along with any experimental datasets to create a database of equivalent globally static models 4- Determine a probability model for the uncertainty of the nominal model