| Clear sky irradiances using REST2 and MODIS X Zhong, J Kleissl Solar Energy 116, 144-164, 2015 | 45 | 2015 |
| FuXi: a cascade machine learning forecasting system for 15-day global weather forecast L Chen, X Zhong, F Zhang, Y Cheng, Y Xu, Y Qi, H Li npj Climate and Atmospheric Science 6 (1), 190, 2023 | 25 | 2023 |
| WRF inversion base height ensembles for simulating marine boundary layer stratocumulus X Zhong, DK Sahu, J Kleissl Solar Energy 146, 50-64, 2017 | 13 | 2017 |
| WRF–ML v1. 0: a bridge between WRF v4. 3 and machine learning parameterizations and its application to atmospheric radiative transfer X Zhong, Z Ma, Y Yao, L Xu, Y Wu, Z Wang Geoscientific Model Development 16 (1), 199-209, 2023 | 11 | 2023 |
| Dissecting surface clear sky irradiance bias in numerical weather prediction: Application and corrections to the New Goddard Shortwave Scheme X Zhong, JA Ruiz-Arias, J Kleissl Solar Energy 132, 103-113, 2016 | 11 | 2016 |
| A Physics‐Incorporated Deep Learning Framework for Parameterization of Atmospheric Radiative Transfer Y Yao, X Zhong, Y Zheng, Z Wang Journal of Advances in Modeling Earth Systems 15 (5), e2022MS003445, 2023 | 10 | 2023 |
| Two deep learning-based bias-correction pathways improve summer precipitation prediction over China F Ling, Y Li, JJ Luo, X Zhong, Z Wang Environmental Research Letters 17 (12), 124025, 2022 | 6 | 2022 |
| Comprehensive physics testing and adaptive weather research and forecasting physics for day‐ahead solar forecasting R Huva, G Song, X Zhong, Y Zhao Meteorological Applications 28 (4), e2017, 2021 | 5 | 2021 |
| FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model X Zhong, L Chen, J Liu, C Lin, Y Qi, H Li arXiv preprint arXiv:2310.19822, 2023 | 4 | 2023 |
| Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model … X Zhong, X Yu, H Li Geoscientific Model Development 17 (9), 3667-3685, 2024 | 2 | 2024 |
| Assimilating in-situ observations over Southern California for improved solar forecasting DK Sahu, CK Kim, X Zhong, J Kleissl 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC), 1007-1012, 2016 | 2 | 2016 |
| FuXi-S2S: An accurate machine learning model for global subseasonal forecasts L Chen, X Zhong, J Wu, D Chen, S Xie, Q Chao, C Lin, Z Hu, B Lu, H Li, ... arXiv preprint arXiv:2312.09926, 2023 | 1 | 2023 |
| Investigating transformer‐based models for spatial downscaling and correcting biases of near‐surface temperature and wind speed forecast X Zhong, F Du, L Chen, Z Wang, H Li Quarterly Journal of the Royal Meteorological Society, 2023 | 1 | 2023 |
| Comparisons of Initial Condition Perturbation Methods for Regional Ensemble Forecasts of Wind Speed in Gansu of China Z Han, D Hu, Q Lv, X Zhong Preprints, 2023 | 1 | 2023 |
| Advancing solar irradiance/marine layer stratocumulus forecasting in California X Zhong University of California, San Diego, 2017 | 1 | 2017 |
| Fuxi-DA: A Generalized Deep Learning Data Assimilation Framework for Assimilating Satellite Observations X Xu, X Sun, W Han, X Zhong, L Chen, H Li arXiv preprint arXiv:2404.08522, 2024 | | 2024 |
| A machine learning model that outperforms conventional global subseasonal forecast models H Li, L Chen, X Zhong, J Wu, D Chen, SP Xie, Q Chao, C Lin, Z Hu, B Lu, ... | | 2024 |
| Comparisons of the added value of dynamical downscaling of ECMWF EPS and NCEP GEFS for wind forecast in the complex terrain of Sichuan and Yunnan in China X Zhong, Z Han, B Zhang, J Zhang, J Long Authorea Preprints, 2024 | | 2024 |
| Is Artificial Intelligence Providing the Second Revolution for Weather Forecasting? F Ling, L Ouyang, BR Larbi, JJ Luo, T Han, X Zhong, L Bai arXiv preprint arXiv:2401.16669, 2024 | | 2024 |
| WRF Model Moisture Adjustment Method: A Case Study with Wintertime Cloudy Biases in Xinjiang, China G Song, R Huva, Y Xing, X Zhong Weather and Forecasting 36 (2), 487-497, 2021 | | 2021 |
Hao LiFUDAN UNIVERSITY，DAMO@ALIBABAVerified email at alibaba-inc.com
