“I enjoy the challenge of finding ways to derive meaningful conclusions from raw data. Numbers do not lie, but they can easily deceive when used incorrectly. Part of my job is to always question the validity of what I am doing.”
Aran joined StormGeo in 2017 as a Data Scientist. His work focuses on finding patterns and condensing large amounts of data into valuable insights. His areas of interest include data quality control and forecast verification and improvement.
Prior to joining StormGeo, Aran accrued many years of experience analyzing data sets from fields such as nuclear physics, environmental monitoring and meteorology.
“I see each research project as new territory that need to be explored. A systematic approach is essential, but in the end, it's the result you get that will determine the way forward.”
While working in New Zealand, Aran designed and developed the New Zealand Drought Monitor, which combines a variety of meteorological and hydrological models to estimate soil moisture conditions over the entire country. This has become a valuable tool to support decision making for authorities and farmers, amongst others. His work at StormGeo has been continuation of this — contributing to the tools that help customers make the right decisions.
Recent research includes:
Statistical Modeling; Machine Learning; Meteorology; Data Science; Time series; Quality Control
A Mol, A. Tail and G. Macara, An automated drought monitoring system for New Zealand, Weather and Climate, 37(1), 23-36 (2017)
A. Mol and D. Wratt, Diurnal variations in precipitation frequency in New Zealand, Weather and Climate, 37(1), 2-10 (2017)
F. Caraffini, F. Neria, G. Iacca, A. Mol, Parallel memetic structures, Information Sciences, 227, 60-82 (2013)
Aran holds an MSc degree in Physics from the University of Groningen.