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Fnp: Fourier neural processes for arbitrary-resolution data assimilation
Data assimilation is a vital component in modern global medium-range weather forecasting
systems to obtain the best estimation of the atmospheric state by combining the short-term …
systems to obtain the best estimation of the atmospheric state by combining the short-term …
Regional Weather Variable Predictions by Machine Learning with Near-Surface Observational and Atmospheric Numerical Data
Accurate and timely regional weather prediction is vital for sectors dependent on weather-
related decisions. Traditional prediction methods, based on atmospheric equations, often …
related decisions. Traditional prediction methods, based on atmospheric equations, often …
Kolmogorov Arnold Neural Interpolator for Downscaling and Correcting Meteorological Fields from In-Situ Observations
Obtaining accurate weather forecasts at station locations is a critical challenge due to
systematic biases arising from the mismatch between multi-scale, continuous atmospheric …
systematic biases arising from the mismatch between multi-scale, continuous atmospheric …
Satellite Observations Guided Diffusion Model for Accurate Meteorological States at Arbitrary Resolution
Accurate acquisition of surface meteorological conditions at arbitrary locations holds
significant importance for weather forecasting and climate simulation. Due to the fact that …
significant importance for weather forecasting and climate simulation. Due to the fact that …
WSSM: Geographic-enhanced hierarchical state-space model for global station weather forecast
Global Station Weather Forecasting (GSWF), a prominent meteorological research area, is
pivotal in providing timely localized weather predictions. Despite the progress existing …
pivotal in providing timely localized weather predictions. Despite the progress existing …