23 citations · 96 across the 25 of their papers we have counts for
19 papers · 1 filter
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…
WorldSimBench: Towards Video Generation Models as World Simulators
Yiran Qin, Zhelun Shi, Jiwen Yu +10
Recent advancements in predictive models have demonstrated exceptional capabilities in predicting the future state of objects and scenes. However, the lack of categorization based…
PostCast: Generalizable Postprocessing for Precipitation Nowcasting via Unsupervised Blurriness Modeling
Junchao Gong, Siwei Tu, Weidong Yang +6
Precipitation nowcasting plays a pivotal role in socioeconomic sectors, especially in severe convective weather warnings. Although notable progress has been achieved by approaches…
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…
CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient Variational Transformer
Tao Han, Zhenghao Chen, Song Guo +2
The advent of data-driven weather forecasting models, which learn from hundreds of terabytes (TB) of reanalysis data, has significantly advanced forecasting capabilities. However,…
Instruct-ReID++: Towards Universal Purpose Instruction-Guided Person Re-identification
Weizhen He, Yiheng Deng, Yunfeng Yan +7
Human intelligence can retrieve any person according to both visual and language descriptions. However, the current computer vision community studies specific person re-identificat…
Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction
Zijie Guo, Pumeng Lyu, Fenghua Ling +8
Accurate ocean dynamics modeling is crucial for enhancing understanding of ocean circulation, predicting climate variability, and tackling challenges posed by climate change. Despi…
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…
RS-Mamba for Large Remote Sensing Image Dense Prediction
Sijie Zhao, Hao Chen, Xueliang Zhang +3
Context modeling is critical for remote sensing image dense prediction tasks. Nowadays, the growing size of very-high-resolution (VHR) remote sensing images poses challenges in eff…
HVDistill: Transferring Knowledge from Images to Point Clouds via Unsupervised Hybrid-View Distillation
Sha Zhang, Jiajun Deng, Lei Bai +3
We present a hybrid-view-based knowledge distillation framework, termed HVDistill, to guide the feature learning of a point cloud neural network with a pre-trained image network in…
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…
CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
Junchao Gong, Lei Bai, Peng Ye +5
Precipitation nowcasting based on radar data plays a crucial role in extreme weather prediction and has broad implications for disaster management. Despite progresses have been mad…
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…
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method
Zili Liu, Hao Chen, Lei Bai +6
Downscaling (DS) of meteorological variables involves obtaining high-resolution states from low-resolution meteorological fields and is an important task in weather forecasting. Pr…
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…