13 citations · 50 across the 19 of their papers we have counts for
20 papers
MetaCtrl: Your Large Language Models Can Reason Better and More Concisely with a Metacognitive Controller
Zhibin Wen, Tao Han, Lei Bai +2
Large reasoning models improve performance on challenging problems by allocating additional computation before answering, but longer reasoning does not always lead to better result…
UniGIO: Unified Generative Global In-situ Weather Modeling from Spatiotemporal Incomplete Observations
Songru Yang, Zili Liu, Tao Han +7
Global In-situ Observation (GIO) provides fine-scale, direct records of the global weather system from sparse point stations, making it an indispensable source for capturing locali…
TSSM: Triaxial State Space Model for Global Station Weather Forecasting with Temporal-Variable-Historical Modeling
Songru Yang, Zili Liu, Tao Han +7
Global Station Weather Forecasting (GSWF) is pivotal for localized and extreme weather prediction over key regions. Despite efforts to exploit look-back windows, existing methods s…
RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges
Ruize Li, Zhibin Wen, Tao Han +5
Accurate evaluation of weather forecasting models is critical for their reliable deployment in real-world applications. However, existing benchmarks predominantly rely on reanalysi…
Earth-o1: A Grid-free Observation-native Atmospheric World Model
Junchao Gong, Kaiyi Xu, Wangxu Wei +22
Despite the unprecedented volume of multimodal data provided by modern Earth observation systems, our ability to model atmospheric dynamics remains constrained. Traditional modelin…
Transforming Weather Data from Pixel to Latent Space
Sijie Zhao, Feng Liu, Xueliang Zhang +7
The increasing impact of climate change and extreme weather events has spurred growing interest in deep learning for weather research. However, existing studies often rely on weath…
VQLTI: Long-Term Tropical Cyclone Intensity Forecasting with Physical Constraints
Xinyu Wang, Lei Liu, Kang Chen +3
Tropical cyclone (TC) intensity forecasting is crucial for early disaster warning and emergency decision-making. Numerous researchers have explored deep-learning methods to address…
VA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather Forecasting
Hao Chen, Han Tao, Guo Song +4
This paper presents Variables Adaptive Mixture of Experts (VAMoE), a novel framework for incremental weather forecasting that dynamically adapts to evolving spatiotemporal patterns…
FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere
Fenghua Ling, Kang Chen, Jiye Wu +4
Seamless forecasting that produces warning information at continuum timescales based on only one system is a long-standing pursuit for weather-climate service. While the rapid adva…
WeatherFormer: Empowering Global Numerical Weather Forecasting with Space-Time Transformer
Junchao Gong, Tao Han, Kang Chen +1
Numerical Weather Prediction (NWP) system is an infrastructure that exerts considerable impacts on modern society.Traditional NWP system, however, resolves it by solving complex pa…
Benchmarking AI-based data assimilation to advance data-driven global weather forecasting
Wuxin Wang, Weicheng Ni, Ben Fei +7
Research on Artificial Intelligence (AI)-based Data Assimilation (DA) is expanding rapidly. However, the absence of an objective, comprehensive, and real-world benchmark hinders th…
FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation
Kun Chen, Tao Chen, Peng Ye +5
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…
Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
Tao Han, Zhibin Wen, Zhenghao Chen +3
The development of Time-Series Forecasting (TSF) models is often constrained by the lack of comprehensive datasets, especially in Global Station Weather Forecasting (GSWF), where e…
Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling
Wanghan Xu, Fenghua Ling, Wenlong Zhang +4
Data-driven artificial intelligence (AI) models have made significant advancements in weather forecasting, particularly in medium-range and nowcasting. However, most data-driven we…
Global Tropical Cyclone Intensity Forecasting with Multi-modal Multi-scale Causal Autoregressive Model
Xinyu Wang, Kang Chen, Lei Liu +3
Accurate forecasting of Tropical cyclone (TC) intensity is crucial for formulating disaster risk reduction strategies. Current methods predominantly rely on limited spatiotemporal…
ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast
Wanghan Xu, Kang Chen, Tao Han +3
Data-driven weather forecast based on machine learning (ML) has experienced rapid development and demonstrated superior performance in the global medium-range forecast compared to…
FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting
Tao Han, Song Guo, Fenghua Ling +7
Kilometer-scale modeling of global atmosphere dynamics enables fine-grained weather forecasting and decreases the risk of disastrous weather and climate activity. Therefore, buildi…
Improving Global Weather and Ocean Wave Forecast with Large Artificial Intelligence Models
Fenghua Ling, Lin Ouyang, Boufeniza Redouane Larbi +4
The rapid advancement of artificial intelligence technologies, particularly in recent years, has led to the emergence of several large parameter artificial intelligence weather for…
Towards an end-to-end artificial intelligence driven global weather forecasting system
Kun Chen, Lei Bai, Fenghua Ling +9
The weather forecasting system is important for science and society, and significant achievements have been made in applying artificial intelligence (AI) to medium-range weather fo…
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
Yi Xiao, Lei Bai, Wei Xue +3
Weather forecasting is a crucial yet highly challenging task. With the maturity of Artificial Intelligence (AI), the emergence of data-driven weather forecasting models has opened…