The role of mathematical modelling and Artificial Intelligence (AI) is becoming increasingly crucial in strengthening climate information systems and predictions for resilience planning. This convergence, known as mathematical AI, offers the potential to generate comprehensive scenarios on climate risk, vulnerability patterns, and greenhouse gas emissions across various sectors. By analysing vast volumes of weather and climate data, mathematical AI provides more integrated and accurate predictions of climate change, ultimately guiding future actions.

The project, titled Leveraging Mathematical Sciences for Climate Resilience Solutions in Africa (Math4CCR), aims to harness the power of mathematical AI. It seeks to build a strong foundation of mathematical AI skills within academia and policy spaces. By strengthening and institutionalising action-oriented capacity, Math4CCR will empower early-career researchers and policymakers to address climate challenges effectively.

The project will be implemented through four phases. The first phase, Scoping, will involve a desk review of existing mathematical AI tools, frameworks, and models, alongside a capacity gap assessment. The second phase, Training, will focus on capacity development through e-learning modules, fellowship programmes, mini-grants, and internship opportunities. The third phase, Institutionalisation, will involve developing a regional master’s curriculum and fostering engagement through policy labs. Finally, the fourth phase, Community Building, will focus on outreach and engagement through sensitisation webinars, side events, and annual conferences. By the end of the project, we anticipate a significant enhancement in the use of mathematical sciences for climate change planning and response, as well as a reduction in the gender gap within these fields.

Project Goal

To build a cadre of mathematical AI skills in academia and policy spaces by strengthening and institutionalising action-oriented capacity among early-career researchers and policymakers.

Project Objectives

1. To strengthen the capacities of early-career researchers to apply mathematical sciences and AI for climate action.
2. To foster the institutionalisation of mathematical sciences and AI skills and expertise for climate action.

• To cultivate a cohort of AI specialists/champions proficient in applying mathematical sciences and AI to address climate change.

Outcomes and Outputs

Outputs

1. Evidence Synthesis Report: A comprehensive review of existing capacity-building initiatives, tools, and models in mathematical AI for climate change research, highlighting their strengths, applications, and weaknesses, as well as how those weaknesses can be addressed.
2. Capacity Gap Assessment Report: An in-depth analysis of the gaps in capacity for applying mathematical AI in climate change research, providing valuable insights for future interventions.

• Math4CCR Academy: An in-person academy to be conducted with selected Math4CCR champions drawn from the broader cohorts.

1. 100 Fellows trained from policy and research sectors.
2. Math4CCR Curriculum developed and piloted at the University of Nairobi and Makerere University.
3. Six Internship Placements offered to project fellows, providing hands-on mentorship and practical experience in addressing climate change challenges using mathematical AI techniques.

• Small Grants and Case Study Papers: Approximately 10 small research grants awarded to support innovative case study research in climate resilience, with resulting papers compiled into a book or special issue showcasing best practices.
• Book Volume/Special Issue on Math4CCR: A compilation of case study papers and other project outputs.

1. Outreach and Knowledge-sharing Events: Various outreach and lesson-sharing events, including side events during Africa Climate Week and global gatherings, aimed at disseminating project findings and fostering collaboration.

Long-term Outcome
Strengthened skill sets and decision-support systems for the application of mathematical AI in climate change resilience planning and action across Africa.

Intermediate Outcomes
a) A strengthened cohort of AI specialists/champions proficient in applying mathematical sciences and AI to address climate change.
b) Enhanced institutionalisation of mathematical sciences and AI skills and expertise for climate action.

Project Team Members

• Principal Investigator (PI): Joannes Atela, Executive Director, ARIN
• Project Coordinator: Humphrey Agevi, Research Associate, ARIN
• Fellowship Manager: Akinyi J. Eurallyah, Research Associate, ARIN
• Communication Coordinator: Florence Onyango, Communication Manager, ARIN
• Research Assistants: Benjamin Onyango(Public Policy), Gordon Gogo(GIS)

Funder

International Development Research Centre(Canada)

Partners

African Climate and Development Initiative                                                   University of Nairobi (ICCA)

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