From the 1 of 7 linked papers with an AI index.
7 papers
TSSM: Triaxial State Space Model for Global Station Weather Forecasting with Temporal-Variable-Historical Modeling
Songru Yang, Zili Liu, Tao Han +7
The paper introduces a Triaxial State Space Model that leverages period‑aligned historical weather data and a temporal‑variable‑historical paradigm to improve global station weathe…
STCast: Adaptive Boundary Alignment for Global and Regional Weather Forecasting
Hao Chen, Tao Han, Jie Zhang +2
To gain finer regional forecasts, many works have explored the regional integration from the global atmosphere, e.g., by solving boundary equations in physics-based methods or crop…
Spatial-Temporal-Spectral Unified Modeling for Remote Sensing Dense Prediction
Sijie Zhao, Feng Liu, Enzhuo Zhang +5
The proliferation of multi-source remote sensing data has propelled the development of deep learning for dense prediction, yet significant challenges in data and task unification p…
Satellite Observations Guided Diffusion Model for Accurate Meteorological States at Arbitrary Resolution
Siwei Tu, Ben Fei, Weidong Yang +7
Accurate acquisition of surface meteorological conditions at arbitrary locations holds significant importance for weather forecasting and climate simulation. Due to the fact that m…
Kolmogorov Arnold Neural Interpolator for Downscaling and Correcting Meteorological Fields from In-Situ Observations
Zili Liu, Hao Chen, Lei Bai +3
Obtaining accurate weather forecasts at station locations is a critical challenge due to systematic biases arising from the mismatch between multi-scale, continuous atmospheric cha…
LWFNet: Coherent Doppler Wind Lidar-Based Network for Wind Field Retrieval
Ran Tao, Chong Wang, Hao Chen +9
Accurate detection of wind fields within the troposphere is essential for atmospheric dynamics research and plays a crucial role in extreme weather forecasting. Coherent Doppler wi…