Dr. Jeffrey N. A. Aryee is a Senior Lecturer at the Department of Meteorology and Climate Science, Kwame Nkrumah University of Science and Technology (KNUST), Ghana, and a foundational Senior Fellow of the Microsoft AI Economy Institute. His academic journey began with a PhD in Meteorology and Climate Science at KNUST, undertaken through the European Union’s DACCIWA project, where he explored the interactions between aerosols, clouds, and atmospheric dynamics in West Africa.

Jeffrey’s research bridges traditional climate science and emerging technologies. He works at the interface of boundary-layer dynamics, atmospheric measurement, and climate variability, while also advancing the use of artificial intelligence and data science in weather and climate applications. This dual focus reflects both a deep respect for physical processes and a commitment to innovation in tools and methods that can transform how climate knowledge is produced and used.

His project work reflects this philosophy of blending science with real-world impact. Through ANDeL (Advancing Nowcasting with Deep Learning), he is pioneering the use of deep learning techniques for rainfall nowcasting across West Africa. With RetAIn (Microsoft AI Economy Institute Fellowship), he is contributing to a wider conversation on inclusive AI education and its role in Africa’s climate and development agenda. TechAir is building and validating low-cost air quality sensor networks tailored for African contexts, while EW4Energy strengthens storm and lightning early warning systems to support Ghana’s energy sector. In parallel, he has collaborated on RAGA (Rapid Assessment of Groundwater Availability) which focuses on water security, and TIDEKIT which applies geophysical methods to protect the vulnerable coastline and cultural heritage of Keta. His work also supports the establishment of the Ghana Air Quality Data Hub, a national platform designed to improve air quality monitoring and decision-making. Most recently, he is engaged in the Cumulus project under the Nimbus Consortium, which is developing bespoke AI forecasting systems to support farming communities in West Africa.

Jeffrey’s research interests include AI and weather, climate data reconstruction, boundary-layer meteorology, atmospheric measurement techniques, upper atmosphere monitoring, and the socio-economic impacts of climate extremes. He is also interested in the social dimensions of AI uptake, particularly in climate and environmental applications. His work is widely published in international peer-reviewed journals, and he serves as a reviewer for several high-impact titles.

Alongside his research, Jeffrey is committed to mentorship and capacity building. He leads PY4CA, a scientific computing team that develops problem-solving tools for climate applications, and continues to support students and young researchers in building careers at the intersection of science, technology, and society. Beyond academia, he maintains a passion for nature, music, and computing, bringing balance to a career dedicated to advancing climate science and its practical impact on communities.