eSSENCE@LU 7:6 - AI tools of Deep Learning to improve simulation of clouds and climate

Clouds have an important influence on the climate, they can both reflect sunlight back to space and reflect heat radiation back to Earth, besides being integral to weather in the form of rain and other precipitation. Cloud formation is also linked to other climate-related processes, such as, carbon dioxide (CO2) emissions. To model the climate, it is therefore important to get these balances right. Furthermore, the weather itself is affecting other areas, not the least renewable energy sources, such as, solar, wind- and hydro-power, which depend on sun radiation, wind speeds, and precipitation.

Common global models lack the resolution to treat clouds with much accuracy and more detailed physical models become cumbersome on this scale. Artificial intelligence (AI) in the form of machine learning has the ability to create representations of data that are more efficient to use as models once they have been obtained than to re-calculate the physical processes all the time.

The purpose of this project is to accelerate a detailed model of clouds with AI technology so as to acquire insights into climate change. The project will simulate the response of climate to CO2 emissions. This will enable an assessment of how climate change during the rest of this century will affect solar, wind- and hydro-power in northern Europe.