Researchers have developed an AI-based method to increase the precision of global climate models in forecasting extreme events caused by strong precipitation. The method improves spatial and temporal resolution of precipitation fields, enabling better prediction of future natural disasters.
Strong precipitation may cause natural disasters , such as floodings or landslides. Global climate models are required to forecast the frequency of these extreme events , which is expected to change as a result of climate change. Researchers have now developed a first method based on artificial intelligence (AI), by means of which the precision of coarse precipitation fields generated by global climate models can be increased.
The researchers succeeded in improving spatial resolution of precipitation fields from 32 to two kilometers and temporal resolution from one hour to ten minutes. This higher resolution is required to better forecast the more frequent occurrence of heavy local precipitation and the resulting natural disasters in future. Strong precipitation may cause natural disasters, such as flooding or landslides. Global climate models are required to forecast the frequency of these extreme events, which is expected to change as a result of climate chang
Precipitation Natural Disasters Global Climate Models Artificial Intelligence Extreme Events Spatial Resolution Temporal Resolution Forecasting
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