Welcome, Visiting Graduate Student Jasmin Haupt

September 18, 2026 · 2 min read
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We are delighted to welcome Jasmin Haupt to Boulder as a visiting graduate student. Jasmin is a doctoral researcher in the Meteorological Data Science Young Investigator Group, led by Julian Quinting, at the Institute of Meteorology and Climate Research (IMKTRO), Karlsruhe Institute of Technology (KIT). During her stay she is hosted jointly by our group at CU Boulder and by Maria Gehne and Juliana Dias in the Atmosphere-Ocean Processes and Predictability Lab at the NOAA Physical Sciences Laboratory (PSL).

Jasmin Haupt

Background

Jasmin earned both her Bachelor’s and Master’s degrees in Physics at KIT, with her Master’s studies concentrating on theoretical solid-state physics and meteorology. Her Bachelor’s thesis was completed in the Magnetism and Spin Electronics group at Trinity College Dublin. For her Master’s thesis, supervised by Peter Knippertz and Andreas Fink, she examined the influence of sea surface temperature on the land-sea breeze along the Guinea Coast using sensitivity experiments with the ICON model.

Her doctoral work at KIT continues in tropical atmospheric dynamics, combining process-based modelling with the machine learning methods that characterise the Meteorological Data Science group’s research on predictability across weather and subseasonal timescales.

During the Visit

Jasmin’s interests in tropical convection, coupled ocean-atmosphere processes, and data-driven prediction align closely with ongoing work in our group and at NOAA PSL on tropical variability and subseasonal-to-seasonal forecast skill. We look forward to the exchange of ideas and to the collaborations that emerge from her stay.

Welcome, Jasmin!

More about Jasmin: KIT IMKTRO profile

Aneesh Subramanian
Authors
Aneesh Subramanian (he/him)
Associate Professor
Associate Professor in the Department of Atmospheric and Oceanic Sciences at CU Boulder. Research spans weather and climate prediction, subseasonal-to-seasonal forecasting, atmospheric river dynamics, machine learning for Earth system modeling, and data assimilation in coupled ocean-atmosphere systems.