In an era of frequent extreme weather and global warming, obtaining precise, fine-grained
near-surface weather forecasts is increasingly essential for human activities. Downscaling …

Accurately retrieving surface meteorological states at arbitrary locations is of great
application significance in weather forecasting and climate modeling. Since meteorological …

The rapid advancement of artificial intelligence technologies, particularly in recent years,
has led to the emergence of several large parameter artificial intelligence weather forecast …

Data-driven artificial intelligence (AI) models have made significant advancements in
weather forecasting, particularly in medium-range and nowcasting. However, most data …

Downscaling (DS) of meteorological variables involves obtaining high-resolution states from
low-resolution meteorological fields and is an important task in weather forecasting …

In the field of weather forecasting, traditional models often grapple with discretization errors
and time-dependent source discrepancies, which limit their predictive performance. In this …

Accurate short-term convective weather prediction is crucial for mitigating the impact of
natural disasters. Although radar echo extrapolation is a commonly employed forecasting …

Accurate and timely regional weather prediction is vital for sectors dependent on weather-
related decisions. Traditional prediction methods, based on atmospheric equations, often …

Accurate acquisition of surface meteorological conditions at arbitrary locations holds
significant importance for weather forecasting and climate simulation. Due to the fact that …

Physics-based numerical models have been the bedrock of atmospheric sciences for
decades, offering robust solutions but often at the cost of significant computational …