Luca Monaco

Ph.D. in Ingegneria Civile E Ambientale , 37th cycle (2021-2024)

Ph.D. obtained in 2025

Dissertation:

Novel post-processing applications in weather science (Abstract)

Tutors:

Francesco Laio

Profile

Research topic

Post-processing in hydrology: from limited area precipitation forecast to global moisture tracking.

Research interests

Numerical Modelling and Simulation

Biography

I graduated with a degree in Environmental Physics from the University of Turin, where I developed a deep understanding of the physical principles that govern the environment and the intricate interactions between the atmosphere, hydrosphere, and biosphere. During my academic journey, I became particularly interested in meteorology and climatology, leading me to pursue further research in this field.
Following my graduation, I had the opportunity to work as a research fellow at ARPA Piemonte, the regional environmental protection agency. My role involved the development of meteorological verification products aimed at supporting civil protection efforts. In this capacity, I was responsible for analyzing meteorological data, developing verification methods, and creating tools that could be used in real-time to assess the accuracy and reliability of weather forecasts. This work was crucial in enhancing the preparedness and response strategies for natural disasters, particularly those related to extreme weather events.
Currently, I am pursuing a PhD where I focus on the post-processing of meteorological forecasts using advanced machine learning techniques. My research aims to improve the accuracy of weather predictions by refining raw forecast data through sophisticated algorithms. Additionally, I work on models that track global moisture flows, analyzing how water vapor is transported from regions of evapotranspiration to areas of precipitation. This research is essential for understanding the global water cycle and its implications for climate change, agriculture, and water resource management.
In parallel with my research, I also conduct training courses in Python and Machine Learning, specifically tailored for applications in meteorology and climate science. These courses are designed to equip professionals and students with the skills necessary to leverage computational tools in their work, fostering a new generation of scientists who can effectively tackle the challenges posed by climate change and environmental degradation.
Through my work, I aim to contribute to the scientific community's understanding of the Earth's atmosphere and climate system, providing valuable insights that can aid in the development of more accurate and reliable weather forecasts. My ultimate goal is to apply this knowledge to mitigate the impacts of climate change and to help build a more resilient and sustainable future.

Publications

Works published during the Ph.D. View all publications in Porto@Iris

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