En avancerad databas av effekterna av extrema klimathändelser i Europa från nättexter

Extreme climate events routinely cause adverse environmental and socio-economic impacts. Mitigating these impacts requires understanding how they link to climatic drivers.

However, existing freely-available climate hazard impact databases are often designed for rapid reporting and have limitations in terms of completeness and accuracy.

While a wealth of detailed climate impact information is available from online text sources such as news websites and reports, its extraction by human experts is time-consuming, and they are thus not typically used in impact databases.We seek to overcome this gap by producing a holistic European multi-sector impacts database of climate extremes, from mining of online text sources.

We will consider extreme events such as windstorms, droughts, floods and temperatures extremes.

The project’s feasibility is backed by the combined expertise of the PIs in natural hazard impact assessment, climate extremes, and natural language processing (NLP).

By using NLP techniques, each extreme event will be assigned a date range, location and socio-economic and environmental impacts.

These will then be cross-checked against climate data.This effort is timely: recently released global high-resolution climate datasets, increased online news coverage and key advances in machine learning and NLP have opened up previously unforeseen opportunities for building a state-of-the-art climate impacts database.

We seek to exploit these rapidly and systematically.