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Professor Filippo Osella presents his research at the workshop

This question was at the heart of a workshop entitled ‘AI for Improving Weather Warning Systems’, hosted by the Sussex Sustainability Research Programme (SSRP), Sussex AI, and Sussex Digital Humanities Lab (SHL) on Thursday 13 June.

Researchers from the three Centres of Excellence discussed the potential of AI to forecast extreme events attributed to human-caused climate change, such as drought, heatwaves, cyclones, and flooding.

Introducing the workshop, SSRP Director Professor Joseph Alcamo pointed out that 85 percent of people affected by extreme weather events live in Africa and Asia, in communities that are least well equipped to cope with such disasters.

There will be an increase in these events over many parts of the world in the years and decades to come, Professor Alcamo added. This means we need to shield populations and buy time – which is where early warning systems come in.

Professor Alcamo described early warning systems as the ‘first line of defence against climate change’, but not the ultimate solution.

The purpose of this workshop, Professor Alcamo said, was to find out what work is currently being done on warning systems, to consider how AI could improve them, and assess the potential areas of collaboration between researchers from SSRP, Sussex AI, and SHL.

Global South case studies

Experiences from two major Sussex early weather warning projects were presented at the workshop. Firstly, SSRP Fellow Professor Filippo Osella shared findings from his SSRP-funded project on developing weather warnings for fisherfolk in the state of Kerala on the South West coast of India.

The ability to accurately track cyclones – where they might hit, and to what degree of intensity – is crucial to ensuring the safety and livelihoods of local fisherpeople in this region. Efficient, localised warning systems would also allow for more sustainable fishing, as the fishers can be more careful and targeted in their work.

Using a forecasting algorithm tool developed by American universities, Professor Osella and his collaborators have produced focused forecasts, covering three villages, which had a high level of accuracy. The team also asked fisherfolk about the weather conditions on a daily basis, which refined the data set.

The forecast strategy employed by Professor Filippo Osella and his research team in Kerala

Professor Osella added that communication is also key in the development of warning systems. To this end, his team have introduced numerous channels designed to inform local fishers of weather risk, from alert screens in the three villages to WhatsApp groups and even a mobile app.

Discussing the desired next steps of the project, Professor Osella said a comprehensive and efficient forecasting service was needed for the coastal communities.

AI could be used to hone the existing forecast technology, making it more effective and sensitive to data. Different forms of weather could be factored into the model, including rain, storms and waves as well as wind, and forecasts could be tailored according to the sizes of fishing boats.

Lastly, Professor Osella stressed the need for the forecasting to incorporate the experiences and knowledge of local people, becoming a ‘bottom up’ rather than ‘top down’ system. This message would recur throughout the workshop. Trust is key, Professor Osella concluded – we must involve fishers in the production of forecasts.

SSRP fellow Dr Pedram Rowhani then presented work he, Professor Martin Todd and collaborators have been carrying out on early warning systems for extreme weather events – and particularly drought – in the greater Horn of Africa.

He highlighted the importance of ‘anticipatory action’; the ability to predict rather than merely react to the impacts of drought. Ideally, AI would enable researchers to create reliable forecasts that communicate risk to local people and ensure contingency plans are set before drought takes hold.

Dr Rowhani’s collaborative project is entitled PASSAGE: strengthening PAStoral livelihoodS in the African Greater horn through Effective anticipatory action’. The project encompasses Somalia, Ethiopia, South Sudan, Kenya and Uganda. Pastoral farmers in this region cross national borders all the time as they move sheep and goats to various grazing areas.