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Apply now for the 2026 African Summer School on Artificial Intelligence for Weather and Climate Modelling (scholarships available)

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Closing Date: 20 August 2026

Apply now for the 2026 African Summer School on Artificial Intelligence for Weather and Climate Modelling (scholarships available)

Call for Applications is now open for the African Summer School on AI for Weather and Climate Modelling

A regional summer school for young scientists, forecasters, researchers, and climate-service professionals building practical skills for climate action across Africa

ACMAD, in partnership with African Institute for Mathematical Sciences (AIMS), Rwanda Meteorology Agency METEO RWANDA, and other partners, invites applications for the 2026 African Summer School on Artificial Intelligence for Weather and Climate Modelling.

The Summer School will introduce participants to AI and Machine Learning applications in weather and climate, combining expert sessions, hands-on coding, real African datasets and group projects.

Introduction in Artificial Intelligence for Weather and Climate Modelling

The African Summer School on Artificial Intelligence for Weather and Climate Modelling is an annual ACMAD programme that builds capacity in African weather, climate, research and early-warning institutions. It introduces AI and machine learning for weather forecasting, climate modelling, downscaling, bias correction, extreme-event detection and impact-based early warning.

These approaches offer significant opportunities for Africa by complementing numerical models, improving forecast post-processing, and enhancing local-scale predictions despite limited computing resources, expertise and observational networks. The 2026 Summer School will build practical AI skills for weather and climate modelling using African datasets, enabling participants to evaluate, adapt and responsibly integrate AI into institutional and operational workflows.

Details

Dates: 19th to 23rd October 2026

Location: Kigali, Rwanda

Format: In person

Language: English

Contact: [email protected]

Background

The programme contributes to the development of an African-led AI and climate-modelling community working closely with NMHSs, RCCs, universities, research institutions, relevant sectors and the global AI and climate community.

Overall purpose

_{To strengthen Africa’s capacity to apply artificial intelligence in weather and climate modelling in order to improve climate information services, early warning and disaster risk reduction.}

_Objectives

_{The Summer School will help participants understand, evaluate and apply AI and machine-learning approaches in African weather and climate-service contexts.}

Understand

_{Introduce the concepts and principles of artificial intelligence and machine learning for weather and climate modelling.}

Connect

_{Explain how AI can complement numerical prediction systems, climate models, observations and expert forecasting.}

Explore

_{Examine practical applications in forecasting, bias correction, downscaling, nowcasting and extreme-event monitoring.}

Apply

_{Provide hands-on experience with AI and machine-learning workflows using African weather and climate datasets.}

Evaluate

_{Build participants’ ability to assess model accuracy, bias, uncertainty, limitations and operational suitability.}

Collaborate

_{Promote sustained collaboration among NMHSs, RCCs, universities, researchers and relevant climate-service sectors.}

Eligibility

This programme is designed for early- to mid-career professionals working at the intersection of climate science and data. AIMS welcome applicants from National Meteorological and Hydrological Services (NMHSs), universities, and research institutions across Africa who are ready to apply machine learning methods to real climate and weather challenges.

Affiliation with an NMHS, RCC, university, school, research institution or climate-related technical agency.
Background in meteorology, climatology, hydrology, computer science, data science, geography or a related field.
Basic knowledge of Python, or willingness to complete a pre-course Python module
Demonstrated interest in AI applications for weather, climate or early-warning services.
Institutional support or a clear plan for applying the training after the Summer School.
Commitment to participate in all sessions, practical exercises and group project activities

Target Participants:

The Summer School will target 30 trainees drawn from African NMHSs, RCCs, universities, and relevant climate sectors. Participation may be supported through scholarships, institutional sponsorship, partner support or self-funding, depending on available resources. Selection will prioritize gender balance, regional representation, early-career professionals and applicants with a clear institutional role in weather, climate or early warning services.