Measurements of the Free Troposphere (FT) are important for the study of Climate Change and understanding the Earth’s atmosphere in general. Ground-based, high altitude measurement stations are useful for their ability to collect consistent in situ FT measurements over years at relatively low cost. There is very little exchange between the FT and the underlying Atmospheric Boundary Layer (ABL), however this exchange is highest in mountainous areas where these high altitude measurement stations are typically located. The complex mountainous topography enables the development of flow structures that can transport ABL air masses to higher altitudes and inject the aerosols into the FT. Historically, the basic rule of thumb that higher altitude stations will collect less-ABL-influenced (i.e. better) FT measurements has been relied upon to guide how this data can be used, however a recent study demonstrated that this rule can be misleading. That study developed the ABL-TopoIndex, a combination of multiple topographic parameters, to estimate the overall level of ABL influence that can be expected to affect a typical FT measurement at a specified mountainous location (Collaud Coen et al., 2018). This study expands upon their work by developing a new index, the Mountainous ABL-Influence (MABLI) Index. This study is split into three parts. In the first part, multiple novel techniques are developed for detecting and characterising valleys from Digital Elevation Models. The second part of the study develops a large set of parameters potentially relevant for estimating ABL influence. The third part of the study compares these parameters to aerosol measurements and determines which parameters are the most important for accurately estimating ABL influence. These parameters are linearly combined to constitute the MABLI Index. The index primarily depends on an estimation of upslope and up-valley wind strength as represented by the valley volume effect, the average valley cross-sectional area, and the absolute latitude of the station. The stronger these winds, the stronger the ABL influence. The station altitude, the strength of the large-scale sea breeze, and the protuberance of the station relative to its surroundings within 10km all serve to reduce the ABL influence. The MABLI Index can be used to estimate how representative a given ground-based FT measurement is of the FT over the broader area, affecting how such measurements should be used in models and simulations for Climate Change research and forecasting.