UK cities facing new risk of 'firewaves'

UK cities are increasingly at risk of experiencing multiple simultaneous urban wildfires triggered by extended periods of hot, dry weather, according to a recent study from researchers at Imperial College London.

The research, which analysed historical fire incident data from the London Fire Brigade and meteorological data from the Met Office, found that extended periods (10 days or more) of hot, dry weather can reduce moisture levels in green vegetation to the point that it becomes extremely flammable.

In urban environments with large amounts of green space bordering populated areas, such conditions can lead to so-called ‘firewaves’ in which multiple fires break out at the same time, potentially overwhelming emergency services and posing a significant threat to the built environment.

This happened in London in the summer of 2022, when multiple fires (including one in Wennington that destroyed 37 buildings) resulted in the London Fire Brigade experiencing its busiest day since World War II. Recent fires in Edinburgh and London further highlight the risk.

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Study links rising temperatures to declining moods

A new study from researchers at MIT suggests that extreme heat negatively affects people emotionally, not just physically.

After analysing 1.2 billion social media posts from 157 countries, the researchers found that moderate warming improves sentiment in cooler regions but that very hot days (35 degrees Celsius or above) are detrimental to wellbeing everywhere. The impacts were found to be largest in poorer countries.

They predict that continued climate change will lead to a '2.3 percent worsening' of people’s emotional wellbeing by 2100, highlighting the need to factor emotional resilience into adaptation strategies.

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Researchers use AI to ‘see’ landslides and target disaster response

Researchers from the University of Cambridge are using AI to speed up landslide detection following major earthquakes and extreme rainfall events.

In the aftermath of disasters that impact large and inaccessible areas, responders often use satellite data to identify where to prioritise relief efforts. However, manual reviews can be time consuming. By leveraging AI, the researchers hope to significantly speed-up the process of identifying landslides and, ultimately, more effectively predict future risks.

Landslides are typically triggered by earthquakes or intense rainfall but are often made worse by human activities such as deforestation and poor constriction. In certain environments, they can trigger additional hazards such as severe flooding, compounding their destructive impact.

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Simpler models can outperform deep learning at climate prediction

A new study from researchers at MIT suggests that state-of-the-art AI models often make less accurate climate predictions than simpler, physics-based models .

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