SOURCE-LINKED INTELLIGENCE

Improving Mediterranean CYCLOnes Predictions in Seasonal forecasts with artificial intelligence

CORDIS · observation · Publication date unknown

Improving Mediterranean CYCLOnes Predictions in Seasonal forecasts with artificial intelligence Cyclones form frequently over the Mediterranean Sea. The most intense systems cause extensive damage in the region and beyond. The ability to make climate predictions several months in advance of such extreme events has a large number of crucial socio-economic applications for disaster risk reduction. State-of the-art Seasonal Prediction Systems exhibit a good skill in predicting anomalies in the seasonal mean of meteorological fields such as temperature and precipitation. The models’ ability to reproduce variations in the occurrence of extreme events tends to be however much lower. This is particularly true in regions such as the Mediterranean, where extreme events are often driven by small scale processes that are not well reproduced at the resolution at which SPS typically run. The use of artificial intelligence techniques such as machine learning in the study

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recordType

award

status

CLOSED

region

EU

value

181088.08

unit

EUR