10 citations · 28 across the 15 of their papers we have counts for
15 papers
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…
TRACE: A Multi-Agent System for Autonomous Physical Reasoning for Seismology
Feng Liu, Jian Xu, Xin Cui +11
Modern seismic networks resolve earthquake sequences in unprecedented detail, yet explaining how large earthquakes emerge from evolving fault systems remains difficult. We introduc…
OpenEarth-Agent: From Tool Calling to Tool Creation for Open-Environment Earth Observation
Sijie Zhao, Feng Liu, Xueliang Zhang +11
Earth Observation (EO) is essential for perceiving dynamic land surface changes, yet deploying autonomous EO in open environments is hindered by the immense diversity of multi-sour…
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…
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…
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…
WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning
Xiangyu Zhao, Zhiwang Zhou, Wenlong Zhang +9
The Earth's weather system encompasses intricate weather data modalities and diverse weather understanding tasks, which hold significant value to human life. Existing data-driven m…
DiffSR: Learning Radar Reflectivity Synthesis via Diffusion Model from Satellite Observations
Xuming He, Zhiwang Zhou, Wenlong Zhang +4
Weather radar data synthesis can fill in data for areas where ground observations are missing. Existing methods often employ reconstruction-based approaches with MSE loss to recons…
VegeDiff: Latent Diffusion Model for Geospatial Vegetation Forecasting
Sijie Zhao, Hao Chen, Xueliang Zhang +3
In the context of global climate change and frequent extreme weather events, forecasting future geospatial vegetation states under these conditions is of significant importance. 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…
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…
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…
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…