Predicting rain, spotting droughts before they strike, and knowing the right moment to sow are no longer just matters of farmers’ intuition. Today, our alumnus Jakob Schloer works to extend reliable weather forecasts further into the future — from weeks to a season ahead. At the European Centre for Medium-Range Weather Forecasts, one of the world’s leading centers for weather prediction, he builds data-driven machine learning models for sub-seasonal forecasting, giving decision-makers like farmers and electricity providers more time to plan.
Jakob Schloer’s journey began at our Cluster of Excellence in Tübingen in September 2020, when he joined Bedartha Goswami’s lab as a PhD student to study El Niño and improve our understanding of this climate phenomenon. He completed his PhD in summer 2024. In our video interview, Jakob talks about his time here at the Cluster. He shares his memories of the Tübingen machine learning community, offers advice to current PhD researchers, and explains how machine learning is transforming weather forecasting.
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