no code implementations • 9 May 2024 • Xiaohui Zhong, Lei Chen, Hao Li, Jie Feng, Bo Lu
Recent ML models, such as GenCast and SEEDS model, rely on the ERA5 Ensemble of Data Assimilations (EDA) or two operational NWP ensemble members for forecast generation.
no code implementations • 12 Apr 2024 • Xiaoze Xu, Xiuyu Sun, Wei Han, Xiaohui Zhong, Lei Chen, Hao Li
Data assimilation (DA), as an indispensable component within contemporary Numerical Weather Prediction (NWP) systems, plays a crucial role in generating the analysis that significantly impacts forecast performance.
no code implementations • 30 Jan 2024 • Fenghua Ling, Lin Ouyang, Boufeniza Redouane Larbi, Jing-Jia Luo, Tao Han, Xiaohui Zhong, Lei Bai
The rapid advancement of artificial intelligence technologies, particularly in recent years, has led to the emergence of several large parameter artificial intelligence weather forecast models.
no code implementations • 15 Dec 2023 • Lei Chen, Xiaohui Zhong, Jie Wu, Deliang Chen, Shangping Xie, Qingchen Chao, Chensen Lin, Zixin Hu, Bo Lu, Hao Li, Yuan Qi
Skillful subseasonal forecasts beyond 2 weeks are crucial for a wide range of applications across various sectors of society.
no code implementations • 7 Nov 2023 • Xiaohui Zhong, Xing Yu, Hao Li
The Weather Research and Forecast (WRF) model is used to generate training and testing data over South China at a horizontal resolution of 5 km.
1 code implementation • 30 Oct 2023 • Hengjia Li, Yang Liu, Linxuan Xia, Yuqi Lin, Tu Zheng, Zheng Yang, Wenxiao Wang, Xiaohui Zhong, Xiaobo Ren, Xiaofei He
Concretely, the distance loss blends the attributes of all target domains by reducing the distances from generated images to all target subspaces.
no code implementations • 25 Oct 2023 • Xiaohui Zhong, Lei Chen, Jun Liu, Chensen Lin, Yuan Qi, Hao Li
State-of-the-art ML-based weather forecast models, such as FuXi, have demonstrated superior statistical forecast performance in comparison to the high-resolution forecasts (HRES) of the European Centre for Medium-Range Weather Forecasts (ECMWF).
2 code implementations • 22 Jun 2023 • Lei Chen, Xiaohui Zhong, Feng Zhang, Yuan Cheng, Yinghui Xu, Yuan Qi, Hao Li
Over the past few years, due to the rapid development of machine learning (ML) models for weather forecasting, state-of-the-art ML models have shown superior performance compared to the European Centre for Medium-Range Weather Forecasts (ECMWF)'s high-resolution forecast (HRES) in 10-day forecasts at a spatial resolution of 0. 25 degree.