A new study led by the University of Vermont (UVM) uncovers a critical challenge in accurately classifying precipitation as rain or snow using surface weather data. Accurately identifying precipitation phase is critical for weather forecasting, hydrologic modeling, and climate research, with significant implications for transportation. At temperatures near freezing, however, all traditional methods struggle to accurately predict rain and snow due to the meteorological similarity of the two phases. Leveraging multi-source data integration rather than relying on surface weather data alone may offer improvements.

Tropical marine low clouds play a crucial role in regulating Earth’s climate. However, whether they mitigate or exacerbate global warming has long remained a mystery. Now, researchers from the School of Engineering at the Hong Kong University of Science and Technology (HKUST) have developed a groundbreaking method that significantly improves accuracy in climate predictions. This led to a major discovery – that tropical cloud feedback may have amplified the greenhouse effect by a staggering 71% more than previously known to scientists.