Icon of a calendar with days

When

The school will take place on 23-27 February, 2026

Icon of a pin on a map

Where

Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina.

Applications will open soon - stay tuned!

Image of a building taken from the corner

About the School

Forecasts on sub-seasonal to inter-decadal timescales have a diverse range of applications in climate services, including disaster preparedness, and short- mid- and long-term planning. However, the complexity of methods, uncertainty assessment and ways to merge forecasts across timescales presents a significant knowledge and skill gap. The Summer School on Climate Prediction Across Timescales aims to address these gaps, and it is, designed for early-career researchers and advanced students interested in the science and application of climate predictions. The school will offer foundational and advanced lectures in the mornings and interactive, hands-on lab sessions in the afternoons.

Icon of a target with an arrow pointing the centre

Objectives and outcomes

  • Foster understanding of key concepts including predictability, forecast skill, sources of predictability, and cross-timescale interactions

  • Provide an overview of novel tools to determine the predictability and assess forecast skill.

  • Introduce emerging tools in machine learning and AI for forecasting.

  • Develop practical skills through interactive lab sessions focused on real data

Participants will:

  • Gain new theoretical and technical skills

  • Engage in group discussions and applied exercises with real (i.e. not synthetic) data.

Icon image of three people

Target Audience

The target audience of the school is: Graduate students and postdocs in atmospheric, climate, and data sciences; and junior researchers and professionals working in climate services or operational prediction. Participants are expected to have a basic background in climate science, statistics, or a related field; proficiency in Python is encouraged but not required.

Total n. of participants: 30
Icon image of a person with a stick pointing at a board or screen

Prospective Lecturers

  • Constantin Ardilouze, CNRM (Université de Toulouse, Météo-France, CNRS), France

  • Leandro Diaz, DCAO-CIMA-IFAECI (UBA-CONICET-CNRS-IRD), Argentina

  • Leon Hermanson, MetOffice, UK

  • Debbie Hudson, Bureau of Meteorology, Australia

  • Kirsten Mayer, NSF NCAR, USA

  • William Merryfield, ECCC, Canada

  • Andrea Molod, NASA, USA

  • Ángel Muñoz, Barcelona Supercomputing Center (BSC), Spain

  • Marisol Osman, DCAO-CIMA-IFAECI (UBA-CONICET-CNRS-IRD), Argentina

  • Yuhei Takaya, Meteorological Research Institute, Japan

  • Bimochan Niraula, ESMO IPO

  • Sara Pasqualetto, ESMO IPO