Geneva, May 31 (Prensa Latina) Machine learning and artificial intelligence can benefit early warning systems and the prediction of natural disasters in developing countries, experts agreed today at the World Congress of Meteorology.
They are an opportunity for joint efforts at global and local levels to improve predictions of natural phenomena on a global scale by not requiring a huge supercomputer, they said.
They added that machine learning is crucial for improving current and short-term forecasts, as it enables automatic detection and offers various applications, such as air quality assessment.
In this regard, the experts emphasized that the private sector, especially technology companies, can play a leading role in the implementation of early warning for everyone.
An example of what can be achieved with artificial intelligence and high-resolution satellites is mapping vulnerable populations and assessing damage after a disaster like this year’s earthquake in Turkey.
Elena At the same time, we must respond to changing needs and priorities in this area.
The goal is to support the “Early Warnings for All” initiative, particularly in vulnerable regions and climate change hotspots, which require scientific efforts with specific research on areas and threats, he explained.
Xoplaki said a new project will provide novel solutions to ensure timely, accurate and practical financial and impact forecasting of extreme weather events and natural hazards.
ro/crc