Automatic attribution: quick and reliable evaluation for improvement in public perception of climate changes

Climate change and its effects on everyday life are a global concern. A wide range of mathematical and computational studies on climate have provided a wealth of knowledge to understand the process and strategies for effective identification of key diagnostics related to weather extremes and atypical seasons. But there is still an urgent need to provide near real-time reliable information. In particular, weather extreme events and abnormal seasonal or yearly conditions are often invoked as a hallmark of climate change by the media and mass social media. However, this link between individual events and climate change is often made impulsively without verification of the underlying physical processes involved. We created a framework that performs an extreme event attribution focused on atmospheric circulation by identifying the sea level pressure patterns in their typicality in current (factual world defined as a sliding window from the day before to the day of the event, going back 30 years) and past (counterfactual world, from 1950 to 1980) climate conditions - defined using the ERA5 dataset (from slp for several variables: tas, tp, z800, etc). This new tool allows to broaden the dialogue and public perception on climate change topics through the production and provision of authentic (near) real time climate change information on a continuous basis. This will allow researchers and the general public, as well as policy makers, to access relevant results on a daily basis for further uses such as scientific research, as well as for general public knowledge creation, and other educational purposes, tweets, climate fact sheets, videos, etc.