Trish Nowak
I am a PhD student with a background in Physical Geography (BSc hons 1st) and Oceanography (MSc, Phys & Bio). My current project focuses on utilising machine learning methods to gain better understanding of environmental processes. This method offers possible clues on causality of processes, rather than just correlation between parameters. In particular my research will focus on a journey of Saharan mineral dust and its further impact on: displacement of West African Monsoon system, biogeochemical cycles and productivity of central Atlantic Ocean, and biogeochemical cycles and the productivity of the Amazon rainforest. For example, the Amazon rainforest's soils are found to be nutrient poor, with no clear sources of essential micro- and macronutrients (phosphorous and iron in particular). Current theory of Saharan mineral dust enriching Amazon rainforest soils is fairly well known. However, annual quantity estimates of transported dust (and thus the nutrients) yield large uncertainties and vary between the studies. The power of machine learning may provide us with reduced uncertainties, better estimates and perhaps suggest missing links. ML's ability to analyse dozens of parameters over decades of data sets may unveil new or previously overlooked causalities. The possibility of solving a long standing scientific question is what inspires me to do my research.