韩威，博导，二级研究员，国家“万人计划”科技创新领军人才，现任中国气象局地球系统数值预报中心副总工程师、风云气象卫星工程应用系统副总设计师、风云四号卫星数值预报应用首席专家、国际辐射委员会（International Radiation Commission）委员，《Monthly Weather Review》，《Advances in Atmospheric Sciences》、《地球科学进展》和《气象学报》等期刊编委。

主要研究方向为数据同化算法、卫星数据同化及人工智能与数值预报的结合，欢迎大气科学、应用数学、计算数学、流体力学、人工智能等相关专业毕业并热爱科研的同学报考，也欢迎对数据同化和卫星数据定量应用有兴趣的本科生联系，可以从本科阶段进行针对性指导。【走近卫星数据同化，为气象强国贡献同化力量-韩威】https://www.bilibili.com/video/BV1Ex4y1H7CX/?share_source=copy_web

长期致力于我国自主研发的数值天气预报系统GRAPES，解决了全球业务同化多项核心技术难题，为我国全球同化预报系统GRAPES业务化做出了突出贡献；在卫星资料同化领域取得多项创新成果，并在中国气象局业务数值预报系统GRAPES和ECMWF数值预报系统中得到业务应用。曾三次应欧洲气象卫星组织邀请到欧洲中期天气预报中心（ECMWF）访问工作，两次应邀到美国开展合作研究。提出并在业务资料同化系统中实现了有约束观测偏差订正原创性方法（CBC,2014；CVarBC，2016），系统解决了国际上卫星资料同化领域困扰多年的观测偏差订正向模式 “偏差漂移”难题；提出了大气化学卫星红外高光谱辐射率资料直接同化中“锚定通道”的方法，首次在业务数值预报系统中成功实现了红外资料臭氧通道辐射率资料的直接同化(2010)，解决了臭氧分析中极区冬半年卫星观测应用缺失问题，应用于ECMWF IFS 系统，显著改善了对流层上层臭氧分析的质量；国际上率先实现了静止轨道红外高光谱大气探测仪FY-4A GIIRS观测同化（2018），提高了台风、暴雨等灾害性天气预报精度，在业务工程应用中发挥了静止卫星高光谱大气探测仪高时间分辨率的应用优势，确认了世界气象组织对静止高光谱探测仪的预期价值；发展了红外高光谱大气探测仪在轨参数快速最优估计技术（2021），发现了卫星仪器关键参数在复杂空间环境下的热形变规律，提高了光谱定标精度。

2017年获中国气象学会气象科学技术进步成果一等奖，2018年获第六届邹竞蒙气象科技人才奖，2021年获国家科技进步二等奖和第23届国际TOVS会议最佳报告奖，2024年获首届国家卓越工程师团队奖等奖励。

2005.08-2008.03 中国气象科学研究院数值预报创新基地 博士后

2008.03-2010.04 中国气象科学研究院数值预报研究中心 同化组组长

2010.04-2021.09 中国气象局数值预报中心模式研发室，研发室副主任

2021.09-2024.12 中国气象局地球系统数值预报中心卫星资料同化室，副主任

2024.12-现在      中国气象局地球系统数值预报中心副总工程师

其间： 

2008.05-2008.08 欧洲中期天气预报中心（ECMWF），NWP/SAF资助访问学者

2009.07-2010.01 欧洲中期天气预报中心（ECMWF）, NWP/SAF资助访问学者

2012.06-2013.06 美国马里兰大学，JPSS资助访问学者

2015.08-2016.02 欧洲中期天气预报中心（ECMWF）, NWP/SAF资助访问学者

2019.09-2021.09 美国卫星资料同化联合中心(JCSDA)+Wisconsin大学，   项目科学家

===========2026年============

[1] K. Chen, Y. Chen, Z. Suo and W. Han*, 2026,"Hybrid Observing System Simulation Experiment for the FY-4 Geostationary Orbit Microwave Satellite based on CMA-GFS," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2025.3649828

[2]Hong, J., Chang, W., Han, W.*, Zhuang, Z., Wang, H., Bi, L., Shen, X., 2026. Data assimilation of aerosol optical depth (AOD) in CMA-MESO/CUACE model to improve weather predictions in China. Atmospheric Research 108780. https://doi.org/10.1016/j.atmosres.2026.108780

[4]Jie He, Xulin Ma*, Wei Han*, Hua Deng, Yang Shi, Hong Wang, Weiyu Ding, Siqi Chen. (2026). Assimilating satellite clear-sky infrared radiances in the CMA-MESO model using variational quality control, Quart. J. Roy. Meteor. Soc. https://doi.org/10.1002/qj.70142

==============2025年============

[1] 韩威, 尹若莹, 李俊, 刘永柱, 王金成, 李永辉, 秦晓昊, 张志清, 沈学顺. 2025. 静止气象卫星大气廓线目标观测及在高影响天气预报中的影响. 中国科学: 地球科学, 55(4): 991–1005.  doi: 10.1360/N072024-0021

(PDF:https://pan.baidu.com/s/12U1Y8T010GP3hjJa761zlw?pwd=bz77）

[2] Han W, Yin R, Li J, Liu Y, Wang J, Li Y, Qin X, Zhang Z, Shen X. 2025. Targeted sounding observations from geostationary satellite and impacts on high impact weather forecasts. Science China Earth Sciences, 68(4): 963–976, https://doi.org/10.1007/s11430-024-1489-5

(PDF:https://pan.baidu.com/s/1qGsUpOqjMW_wvejKVw1-AA?pwd=hkvn）

[3] Sun, X., Zhong, X., Xu, X., Huang, Y., Li, H.*, Neelin, J.D.*, Chen, D., Feng, J., Han, W.*, Wu, L.*, Qi, Y.*, 2025. A data-to-forecast machine learning system for global weather. Nature Communications 16,6658. https://doi.org/10.1038/s41467-025-62024-1

(PDF: https://pan.baidu.com/s/1jRqhFRBKmk_tERgoxCHUeQ?pwd=wvqi）

[4] Xu, X., Sun, X., Han, W.*, Zhong, X., Chen, L., Gao, Z., Li, H.*, 2025. FuXi-DA: a generalized deep learning data assimilation framework for assimilating satellite observations. npj Clim Atmos Sci 8, 156.https://doi.org/10.1038/s41612-025-01039-3

(PDF:https://pan.baidu.com/s/1sa8f7fT7X0cU4yTW-Lam-g?pwd=n1ec）

[5] F. Liu, W. Han*, H. Li and Q. Liu, "Unraveling High-Resolution Temporal–Spatial Variability of Raindrop Size Distributions in Extreme Rainfall Events With Dual-Polarization Radar Optimal Estimates," in IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1-15, 2025, Art no. 4107415, doi: 10.1109/TGRS.2025.3588966

(PDF:https://pan.baidu.com/s/1hPZP3X60LeLLrO7pRV2Gog?pwd=zxxk）

[6] Song, L., and Han, W.* (2025). The impact of assimilating radar reflectivity observations based on the 1D Bayesian retrieval and valid-time-shifting method on the short-term severe weather forecasts. Atmospheric Research, 108370.

(PDF:https://pan.baidu.com/s/1ktob9_UOCnc8OIlRo2vAiw?pwd=kv8d）

[7] Li,Z.,and W Han*,2025:Impact of Implementing All-Sky Radiance Assimilation for FY-3E MWHS-2 in the CMA-GFS.Mon.Wea.Rev.,153,847-863,https://doi.org/10.1175/MWE-D-24-0093.1.

[8] Wang, H., W. Han*, J. Li, H. Chen, and R. Y. Yin, 2025: Impact of assimilation of FY-4A GIIRS three dimensional horizontal wind observations on typhoon forecasts. Adv. Atmos. Sci., 42(3), 467−485, https://doi.org/10.1007/s00376-024-4051-8 

(PDF:https://pan.baidu.com/s/19EhAv3OGfejhz9UzQxoOUQ?pwd=kb4u）

[9] Xiao, H., Shi, Y.-N., Han, W.*, Zhao, B., Bai, Y., 2025. Toward All-Surface Assimilation of Microwave Sounding Data in the CMA-GFS 4D-Var System. Journal of Geophysical Research: Atmospheres 130, e2025JD043458. https://doi.org/10.1029/2025JD043458

(PDF:https://pan.baidu.com/s/1xUUJg3wPmQD09lCG3v7v0g?pwd=djuk）

[10] Liu, C., Han, W*., Zhang, F., Jin, J., Wu, Q., Li, W., Gao, C.Y., 2025. Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan. Geophysical Research Letters 52, e2025GL116397. https://doi.org/10.1029/2025GL116397

(PDF:https://pan.baidu.com/s/1rMq9uGHV49rkmMRLz-70-Q?pwd=35jg）

[11] Pang, M., Jin, J.*, Yang, T., Chen, X., Segers, A., Buyantogtokh, B., Gu, Y., Li, J., Lin, H. X., Liao, H., and Han, W.*: The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2, Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, 2025.

(PDF:https://pan.baidu.com/s/1AIGLX0iLUc7zaGSbrOcGhw?pwd=ugqc）

[12] L. -H. Sun, L. Bi* and W. Han, "Global Polarized Radiance of Ice Clouds in the Visible and Near-Infrared Bands and Optimal Ice Crystal Model Parameters," IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1-14, 2025, doi: 10.1109/TGRS.2025.3581298. 

(PDF: https://pan.baidu.com/s/1Bwd1AYuUQnwXmIzSne8Asw?pwd=etri）

[13] Song, X., Han, W.*, Sun, H., Wang, H., & Xu, X. ,2025. Correcting Forecast Time Biases in CMA-MESO Using Himawari-9 and Time-Shift Method. Remote Sensing, 17(4), 617. https://doi.org/10.3390/rs17040617

(PDF:https://pan.baidu.com/s/1r62UOc8fQ7SRWH1DdW5jWA?pwd=u6xn）

[14] Wang, X., Bi, L., Wang, H., Wang, Y., Han, W., Shen, X., Zhang, X., 2025. AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE. Geoscientific Model Development 18, 117–139. https://doi.org/10.5194/gmd-18-117-2025

（PDF:https://pan.baidu.com/s/1wpboGE1hSgFMSsUL5NCBQA?pwd=38wi）

[15] Wu Zheng, Han Wei*, Xie Hejun,Ye Mao & Gu Jianfeng (2025) Assimilation of FY-3G Ku-band radar observations with 1D Bayesian retrieval and 3DVAR in CMA-MESO. Quarterly Journal of the Royal Meteorological Society, e4964. Available from: https://doi.org/10.1002/qj.4964

(PDF: https://pan.baidu.com/s/1IcpkkULKVZwCU_oxW1MVBg?pwd=rjv9 )

[16] Li, Y., Han, W.*, Duan, W., Li, Z., & Li, H.(2025). A machine learning‐based observation operator for FY‐4B GIIRS brightness temperatures considering the uncertainty of label data. Journal of Geophysical Research: Machine Learning and Computation, 2, e2024JH000449. https://doi.org/10.1029/2024JH000449

(PDF:https://pan.baidu.com/s/1NtMzYmy5MulSIOroYEmLQg?pwd=kx2u)

[17] Xie, H., Bi, L.*, & Han, W.* (2025). Efficientforward radar operator simulations inmelting layer scenarios and evaluations of melting layer scheme in ZJU‐AERO basedon ground‐based and spaceborne radarobservations. Journal of Geophysical Research: Atmospheres, 130,e2024JD043140. https://doi.org/10.1029/2024JD043140

(PDF:https://pan.baidu.com/s/1E6cXcF3xrSZJ0vhi9avWXQ?pwd=a317）

[18] Xu, X., Han, W.*, Wang, J., Gao, Z., Li, F., Cheng, Y., and Fu, N.: Quality assessment of YUNYAO radio occultation data in the neutral atmosphere, Atmos. Meas. Tech., 18, 1339–1353, https://doi.org/10.5194/amt-18-1339-2025, 2025.

(PDF:https://pan.baidu.com/s/1PuRXJeZdWHjz1AwMyQSrAw?pwd=gfdh）

[19] Xu Xiaoze , Xiuyu Sun, Wei Han*, Xiaohui Zhong, Lei Chen, Zhiqiu Gao,Hao Li. Fu Xi-DA: a generalized deep learning data assimilation framework for assimilating satellite observation[J]. npj Climate and Atmospheric Science, 2025, 8(1): 156. https://doi.org/10.1038/s41612-025-01039-3.

(PDF:https://pan.baidu.com/s/1a9lCqW3OMZfwXjU5zW0lhA?pwd=pdb3)

[20] Li, Y., Duan, W.*, Han, W.*, Li, H., & Qin,X. (2025). Improving tropical cyclone track forecast skill through assimilating target observation achieved by AI‐based conditional nonlinear optimal perturbation. Journal of Geophysical Research: Atmospheres, 130, e2024JD043261,http://dx.doi.org/10.1029/2024JD043261

(PDF:https://pan.baidu.com/s/17H7im7i2gFoQG341xCnxzw?pwd=qm4w）

[21] Yang, Y., Han, W.*, Sun, H., Li, J., Yan, J., and Gao, Z.: Reconstruction of 3D precipitation measurements from FY-3G MWRI-RM imaging and sounding channels, Atmos. Meas. Tech., 18, 4249–4269, https://doi.org/10.5194/amt-18-4249-2025

[22] Yin, R., Han, W.*, Zhao, Z., Gong, X., Kong, S., Zhang, F., Li, J., 2025. The Preliminary Assimilation and Impacts of FY-4B Geostationary Interferometric Infrared Sounder (GIIRS) Cloud-Cleared Radiances. Journal of Geophysical Research: Atmospheres 130, e2025JD043520. https://doi.org/10.1029/2025JD043520

[23] Zhang, Z. P., W. Han*, L. Chen, et al., 2025: Fine-tuning FuXi with CMA’s reanalysis data to improve forecasting. J. Meteor. Res., 39(6), 1411–1424,  https://doi.org/10.1007/s13351-025-5052-y.

[24] Pan, X., Li, D., Han, W. et al. Enhancing Rainfall Prediction Affected by the Northeast China Cold Vortex Using FY-4B GIIRS Radiance Data in CMA-MESO. Adv. Atmos. Sci. 43, 769–787 (2026). https://doi.org/10.1007/s00376-025-4526-2

==============2024年============

[1] Li, Z., Han, W.*, Xu, X., Sun, X., Li, H., 2024. All-Sky Microwave Radiance Observation Operator Based on Deep Learning With Physical Constraints. Journal of Geophysical Research: Atmospheres 129, e2024JD042436. https://doi.org/10.1029/2024JD042436

（PDF:https://pan.baidu.com/s/1mgW6_WnxPbWL2necPkMU9w?pwd=fg2g ）

[2] Li, Y., Han, W.*, Li, H., Duan, W., Chen,L., Zhong, X., et al. (2024). Fuxi‐en4dvar:An assimilation system based on machine learning weather forecasting model ensuring physical constraints. Geophysical Research Letters, 51, e2024GL111136. https://doi.org/10.1029/2024GL111136

（PDF:https://pan.baidu.com/s/1xFtReQmL5MeUKapT_JbxpQ?pwd=5w4m ）

[3] Yin, R., Han, W.*, 2024. Impact of Targeted Sounding Observations from FY-4B GIIRS on two Super Typhoon Forecasts in 2024. IEEE Geoscience and Remote Sensing Letters 1–1. https://doi.org/10.1109/LGRS.2024.3516004

（PDF:https://pan.baidu.com/s/1E3DtQ-s6GiYYf4A3ccfmOA?pwd=d964）

[4] Fang, L., Jin, J., Segers, A., Li, K., Xia, J., Han, W., Li, B., Lin, H.X., Zhu, L., Liu, S., Liao, H., 2024. Observational operator for fair model evaluation with ground NO₂ measurements. Geoscientific Model Development 17, 8267–8282. https://doi.org/10.5194/gmd-17-8267-2024

（PDF:https://pan.baidu.com/s/1PK0eeT_su6LoslzbG99r7w?pwd=55q2）

[5] Xie, H., Bi, L.*, Wang, Z., Han, W.*, 2024. Modeling of Melting Layer in Cross-Platforms Radar Observation Operator ZJU-AERO: Multi-Stage Melting Particle Model, Scattering Computation, and Bulk Parameterization. Journal of Geophysical Research: Atmospheres 129, e2024JD040725. https://doi.org/10.1029/2024JD040725

（PDF:https://pan.baidu.com/s/1iwIysgseEx3OgQxER54RPQ?pwd=gn55）

[6] Chen, K., Suo, Z.,Han, W.*, Cai, B., 2024. OSSEs on the FY-4M Geostationary Microwave Satellite Based on CMA-GFS and CMA-MESO. IEEE Transactions on Geoscience and Remote Sensing 1–1. https://doi.org/10.1109/TGRS.2024.3487859

（PDF:https://pan.baidu.com/s/1tXzX_TVL4MflU61k8R-iMQ?pwd=up3d）

[7] Chen, K., Cai, B., Han, W.*, Suo, Z., 2024. Matching of Observation Footprints in the FY-3G MWRI-RM Using BGI. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17, 17794–17805. https://doi.org/10.1109/JSTARS.2024.3468437

（PDF:https://pan.baidu.com/s/1g0fhcO6J2AlwJeb51fMARQ?pwd=5zdq）

[8] Zhou, Y., Liu, Y., Han, W., Zeng, Y., Sun, H., Yu, P., and Zhu, L., 2024: Exploring the characteristics of Fengyun-4A Advanced Geostationary Radiation Imager (AGRI) visible reflectance using the China Meteorological Administration Mesoscale (CMA-MESO) forecasts and its implications for data assimilation, Atmos. Meas. Tech., 17, 6659–6675, https://doi.org/10.5194/amt-17-6659-2024.

（PDF:https://pan.baidu.com/s/1XlSr5NJik5aZihiyl2D5tQ?pwd=sb7b）

[9] Xiao, H.,  Han, W.*, Han,Y., Hu, H., Shi, Y., Bai, Y. et al. (2024) First trial for the assimilation of radiance data from MTVZA-GY onboard the new Russian satellite meteor-M N2-2 in the CMA-GFS 4D-VAR system. Quarterly Journal of the Royal Meteorological Society, 1–20. Available from: https://doi.org/10.1002/qj.4853

（PDF:https://pan.baidu.com/s/1_G4gGpmEwU1GAXZUaDV3Eg?pwd=m779 ）

[10] 田伟红 , 庄照荣 , 韩威 , 沈学顺. 葵花-8 卫星AOD资料在CMA-MESO/CUACE CW 3DVar同化系统中的个例应用研究. 高原气象. 2024, 43(5): 1259-1270 https://doi.org/10.7522/j.issn.1000-0534.2024.00016

（PDF:https://pan.baidu.com/s/1nWri8M8NSePwoZgcyRO4kg?pwd=7jjm）

[11] Gong, X., Li, Z., Li, J., Yin, R., Han, W., Chen, L., Di, D., 2024. Cloud-cleared radiances from collocated observations of hyperspectral IR sounder and advanced imager onboard the same geostationary platform. IEEE Transactions on Geoscience and Remote Sensing 1–1. https://doi.org/10.1109/TGRS.2024.3458093

（PDF:https://pan.baidu.com/s/1XwsHjixDiozjgHzBMLsYvw?pwd=xjwv) 

[12] Xie, H., Bi, L.*, Han, W.*, 2024. ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors. Geoscientific Model Development 17, 5657–5688. https://doi.org/10.5194/gmd-17

5657-2024

(PDF:https://pan.baidu.com/s/1cV-DcKSuYtHtBJ7b58RAMA?pwd=33uv）

[13] Li Yonghui, Han Wei* & Duan Wansuo(2024) A dynamic channel selection based on vertical sensitivities for the assimilation of FY-4A GIIRS targeted observations, Quarterly Journal of the Royal Meteorological Society, DOI: 10.1002/qj.4760

（PDF:https://pan.baidu.com/s/1sNW57dlk55YEg1nCe0X36g?pwd=3r99）

[14] Xu, X., Han, W.*, Gao, Z., Li, J., Yin, R., 2024. Retrieval of Atmospheric Temperature Profiles from FY-4A/GIIRS Hyperspectral Data Based on TPE-MLP: Analysis of Retrieval Accuracy and Influencing Factors. Remote Sensing 16, 1976. https://doi.org/10.3390/rs16111976

（PDF:https://pan.baidu.com/s/1ttofpJqtMdmWNM2prQzQrg?pwd=rqna）

[15] Xu, X., Sun, X., Han, W.*, Zhong, X., Chen, L., Li, H., 2024. Fuxi-DA: A Generalized Deep Learning Data Assimilation Framework for Assimilating Satellite Observations (No. arXiv:2404.08522). arXiv. https://doi.org/10.48550/arXiv.2404.08522

（PDF:https://pan.baidu.com/s/1exN3Z7GYVVZYny3xW97Kyg?pwd=expd）

[16] Sun, X., Zhong, X., Xu, X., Huang, Y., Li, H.*, Neelin, J.D.*, Chen, D., Feng, J., Han, W.*, Wu, L., Qi, Y.*, 2024. FuXi Weather: A data-to-forecast machine learning system for global weather.  https://doi.org/10.48550/arXiv.2408.05472

（PDF:https://pan.baidu.com/s/1vF_heVwXUYtLCv-LhN0ITw?pwd=qe6w）

[17] Sun, H., Wang, D., Han, W.*, Yang, Y., 2024. Quantifying the Impact of Aerosols on Geostationary Satellite Infrared Radiance Simulations: A Study with Himawari-8 AHI. Remote Sensing 16, 2226. https://doi.org/10.3390/rs16122226

（PDF:https://pan.baidu.com/s/1OB99qzq125i_OQ3xtFB3ow?pwd=dgj8)

[18] Yang, Y., Han, W.*, Sun, H., Xie, H., & Gao, Z. (2024). Reconstruction of 3D DPR observations using GMI radiances. Geophysical Research Letters, 51, e2023GL106846. https://doi.org/10.1029/2023GL106846

(PDF: https://pan.baidu.com/s/15nKR5alNCeFPZHIFxSdGXA?pwd=d7dv) 

[19] Li, Z. & Han, W.* (2024) Impact of HY-2B SMR radiance assimilation on CMA global medium-range weather forecasts. Quarterly Journal of the Royal Meteorological Society, 150(759), 937–957. Available from:https://doi.org/10.1002/qj.4630

(PDF:https://pan.baidu.com/s/1mTqfNtYU-mJ0uhr1EOs1hw?pwd=nuhm)

[20] Wang Gen, Han Wei*, Yuan Song, Wang Jing, Yin Ruoying,Ye Song, Xie Feng, 2024: Retrieval of High-Frequency Temperature Profiles by FY-4A/GIIRS Based on Generalized Ensemble Learning [J].Journal of the Meteorological Society of Japan, 102, https://doi.org/10.2151/jmsj.2024-011.

(PDF:https://pan.baidu.com/s/1I5Sh7UxrDrSiCGrEIfd6hA?pwd=ed2n) 

[21] Wang Gen, Han Wei*, Ye Song, Yuan Song, Wang Jing, Xie Feng,2024:  FY-4A/AGRI infrared brightness temperature estimation of precipitation based on multi-model ensemble learning [J]. Earth and Space Science,2024,11, e2023EA003311. https://doi.org/10.1029/2023EA003311. 

(PDF:https://pan.baidu.com/s/1AJ3Pk-oJrS1UP-0SyxIZJw?pwd=a3cf) 

[22] Bi, L., Xi, Y., Han, W., Du, Z., 2024. How machine learning approaches are useful in computing the optical properties of non spherical particles across a broad range of size parameters? Journal of Quantitative Spectroscopy and Radiative Transfer 109057. https://doi.org/10.1016/j.jqsrt.2024.109057

(PDF:https://pan.baidu.com/s/1cN5Ib6v1Oqs5GxzY6pZq5A?pwd=dj1w)

==============2023年============

(PDF:https://pan.baidu.com/s/1XrBTXek1re7EM0x8B1KI1A?pwd=ijtx) 

[2] Xie, H., Han, W.* & Bi, L.*(2023) Assimilating FY3D-MWRI 23.8 GHz observations in the CMA-GFS 4DVAR system based on a pseudo All-Sky data assimilation method. Quarterly Journal of the Royal Meteorological Society, 149(756), 3014–3043. Available from:https://doi.org/10.1002/qj.4544

(PDF:https://pan.baidu.com/s/1qpRRKTETAnnJ0w1jHev63g?pwd=t3sp)

[3] Wang, X., Bi, L., Han, W., & Zhang, X. (2023). Single-scattering properties of encapsulated fractal black carbon particles computed using the invariant imbedding T-matrix method and deep learning approaches. Journal of Geophysical Research: Atmospheres, 128, e2023JD039568. https://doi.org/10.1029/2023JD039568

(PDF:https://pan.baidu.com/s/1iNv6lNIO8zX6cocOvjykXQ?pwd=gx3p) 

[4] H. Chen, Y. Song, W. Han*, C. Pan, H. Wang and G. -M. Jiang, 2023,"Effect of Axisymmetrical Spectral Response Function on Microwave Radiance Simulation of Quadruple-Sideband Channel," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2023.3309139.

(PDF:https://pan.baidu.com/s/1VbGsoRWGnLqDuAL-l4V3lw?pwd=g55j) 

[5] Xiao, H., Han, W.*, Zhang, P., & Bai, Y. (2023). Assimilation of data from the MWHS-II onboard the first early morning satellite FY-3E into the CMA global 4D-Var system. Meteorological Applications, 30(3), e2133. https://doi.org/10.1002/met.2133

(PDF:https://pan.baidu.com/s/1sEtvaFbzpov_nFFmNIQDNA?pwd=yv43) 

[6] Zhou, Y., Y. Liu, and W. Han, 2023: Demonstrating the Potential Impacts of Assimilating FY-4A Visible Radiances on Forecasts of Cloud and Precipitation with a Localized Particle Filter. Mon. Wea. Rev., 151, 1167–1188, https://doi.org/10.1175/MWR-D-22 0133.1.

(PDF:https://pan.baidu.com/s/1ud0TBAY7lELKFB7I4uOhXw?pwd=ngy8)

[7] Li Z., Han W.*, Xu H., Xie H., Zou J. Biases’ Characteristics Assessment of the HY-2B Scanning Microwave Radiometer (SMR)’s Observations. Remote Sensing. 2023; 15(4):889. https://doi.org/10.3390/rs15040889

(PDF:https://pan.baidu.com/s/1Ds6OIwFvKC0cdIPFEDwn6w?pwd=w35a) 

[8] Jin, J., Feng, L., Li, B., Liao, H., Wang, Y., Han, W., Li, K., Pang, M., Wu, X., Lin, H.X., 2023. 4DEnVar-based inversion system for ammonia emission estimation in China through assimilating IASI ammonia retrievals. Environ. Res. Lett. https://doi.org/10.1088/17489326/acb835

(PDF:https://pan.baidu.com/s/1T4tnc116gmxZcrLmJs2xpQ?pwd=2aqy) 

[9] Chan, P.-W., W. Han, B. Mak, X. H. Qin, Y. Z. Liu, R. Y. Yin, and J. C. Wang, 2023: Ground–space–sky observing system experiment during tropical cyclone Mulan in August 2022. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-022-2267-z

(PDF:https://pan.baidu.com/s/1OeLPDzHX2tiemE6CZoG4rg?pwd=8bwf ) 

==============2022年============

[1] Yin, R.; Han, W.*; Wang, H.;Wang, J. 2022, Impacts of FY-4A GIIRS Water Vapor Channels Data Assimilation on the Forecast of“21·7”   Extreme Rainstorm in Henan,China with CMA-MESO. Remote Sens. 2022, 14, 5710. https://doi.org/10.3390/rs14225710

(PDF:https://pan.baidu.com/s/1iCSzw1T8l3AKeFo8vOcRrw?pwd=rfx5) 

[2] Ma, Z., Han, W.*, Zhao, C., Zhang, X., Yang, Y., Wang, H., Cao, Y., Li, Z., Chen, J., Jiang, Q., Sun, J., Shen, X., 2022. A case study of evaluating the GRAPES_Meso V5.0 forecasting performance utilizing observations from South China Sea Experiment 2020 of the “Petrel Project.” Atmospheric Research 280, 106437.https://doi.org/10.1016/j.atmosres.2022.106437

(PDF:https://pan.baidu.com/s/1hlw3CJ1-gdm6VGIcPTciaQ?pwd=biak) 

[3] Yu, J., Bi, L., Han, W.*, Zhang, X., 2022. Application of a Neural Network to Store and Compute the Optical Properties of Non

Spherical Particles. Adv. Atmos. Sci. https://doi.org/10.1007/s00376-021-1375-5

(PDF:https://pan.baidu.com/s/1O9vkkODoCPyNV2BkntbkdQ?pwd=6ndk) 

(PDF:https://pan.baidu.com/s/1sc1X-spo3gVkm82Yqf5SVw?pwd=awwi）

[5] Wang, Z., Bi, L., Wang, H., Wang, Y., Han, W., Zhang, X., 2022. Evaluation of a new internally-mixed aerosol optics scheme in the weather research and forecasting model. Journal of Quantitative Spectroscopy and Radiative Transfer 283, 108147. https://doi.org/10.1016/j.jqsrt.2022.108147

(PDF:https://pan.baidu.com/s/1IIezdIPIxgP5oppXvfPhJg?pwd=6h8b）

[6] Jin, J., Pang, M., Segers, A., Han, W., Fang, L., Li, B., Feng, H., Lin, H.X., Liao, H., 2022. Inverse modeling of the 2021 spring super dust storms in East Asia. Atmospheric Chemistry and Physics 22, 6393–6410.

(PDF:https://pan.baidu.com/s/1ZVozK5203Vn9Gs2a2wwT8w?pwd=a2ji) 

[7] Li, W., Zhang, F., Lin, H., Chen, X., Li, J., Han, W., 2022. Cloud detection and classification algorithms for Himawari-8 imager measurements based on deep learning. IEEE Transactions on Geoscience and Remote Sensing 1–1. https://doi.org/10.1109/TGRS.2022.3153129

(PDF:https://pan.baidu.com/s/1LbsRYQgMJubuppmvs7pM5Q?pwd=xy6a)

[8] Li, W., Zhang, F., Bao, F., Wu, K., Li, J., Zhang, P., Han, W., 2022. Polarized discrete ordinate adding approximation for infrared and microwave radiative transfer. Journal of Quantitative Spectroscopy and Radiative Transfer 293, 108368. https://doi.org/10.1016/j.jqsrt.2022.108368

(PDF:https://pan.baidu.com/s/1w0Yu36YAkc78H30K42Dxew?pwd=165q ) 

[9] Chen, K., Fan, X., Han, W.*, Xiao, H., 2022. A Remapping Technique of FY-3D MWRI Based on a Convolutional Neural Network for the Reduction of Representativeness Error. IEEE Transactions on Geoscience and Remote Sensing 60, 1–11. https://doi.org/10.1109/TGRS.2021.3138395

(PDF:https://pan.baidu.com/s/1Ak52Np6ebiMbk6cPVXpNBQ?pwd=vwzs)

[10] Li, J., Geer, A.J., Okamoto, K. Otkin, J., Liu,Z.Q., Han,W., & Wang,P. 2022: Satellite All-sky Infrared Radiance Assimilation: Recent Progress and Future Perspectives. Adv. Atmos. Sci. 39, 9–21 . https://doi.org/10.1007/s00376-021-1088-9

(PDF:https://pan.baidu.com/s/1LUzqBni5DxYzH9B3dUWqXg?pwd=inf2 ) 

(PDF:https://pan.baidu.com/s/1CD8Wl4tA-xHyRQ1MvjPwwQ?pwd=7vgy) 

==============2021年============

[1] Han W., R. Knuteson, J. Li, D. Dee and A. Thomas. 2021, Assimilation of Geostationary Hyperspectral InfraRed Sounders (GeoHIS): Opportunities and Challenges, JCSDA Quarterly Newsletter, Spring 2021 no.69, 1-11, https://doi.org/10.25923/KZKY-4383

(PDF:https://pan.baidu.com/s/1aHdWLsOjFHrIMs7tsGYCWA?pwd=va5f) 

[2] 陈柯，洪鹏飞，韩威*，李泽宇，王皓，王金成，陈昊，张志清，谢振超. 2021. 基于GRAPES四维变分的静止轨道微波观测 统模拟试验研究. 气象学报，79（5）：769-785 doi:  10.11676/qxxb2021.048

(PDF:https://pan.baidu.com/s/1ZWXgdHhOn7bZtvL67d48hw?pwd=upxd)

[3] Yin, R., Han, W.*, Gao, Z., Li, J., 2021. Impact of High Temporal Resolution FY-4A Geostationary Interferometric Infrared Sounder (GIIRS) Radiance Measurements on Typhoon Forecasts: Maria (2018) Case With GRAPES Global 4D-Var Assimilation System. Geophysical Research Letters 48, e2021GL093672. https://doi.org/10.1029/2021GL093672

(PDF:https://pan.baidu.com/s/1VzkZYkZH6btrDK3s1P3jEw?pwd=xbcu) 

[4] Chen, H., Han, W. *, Wang, H., Pan, C., An, D., Gu, S., Zhang, P., 2021. Why and How Does the Actual Spectral Response Matter for Microwave Radiance Assimilation? Geophysical Research Letters 48, e2020GL092306. https://doi.org/10.1029/2020GL092306

(PDF:https://pan.baidu.com/s/14jPJmfkKmZe-GR36ZU1XdA?pwd=wypt )

[5] Wang, G., Han, W.*, Lu, S., 2021. Precipitation retrieval by the L1-norm regularization: Typhoon Hagibis case. Quarterly Journal of the Royal Meteorological Society 147, 773–785. https://doi.org/10.1002/qj.3945

(PDF:https://pan.baidu.com/s/1obt3SfH4Xh6RxDgF1BCMdw?pwd=qit8) 

[6] Yin, J., Han, W.*, Gao, Z., Chen, H., 2021. Assimilation of Doppler radar radial wind data in the GRAPES mesoscale model with observation error covariances tuning. Quarterly Journal of the Royal Meteorological Society 147, 2087–2102. https://doi.org/10.1002/qj.4036

(PDF:https://pan.baidu.com/s/14pQb8tSNE3lFP-JmHR5RyA?pwd=byyr)

[7] Ma, Z., Li, J., Han, W., Li, Z., Zeng, Q., Menzel, W.P., Schmit, T.J., Di, D., Liu, C.-Y., 2021. Four-Dimensional Wind Fields From Geostationary Hyperspectral Infrared Sounder Radiance Measurements With High Temporal Resolution. Geophysical Research Letters 48, e2021GL093794. https://doi.org/10.1029/2021GL093794

(PDF:https://pan.baidu.com/s/1iTeXtb44DD3juXJe1fE-bw?pwd=kdfv） 

[8] Yin, J., Gao, Z., Han, W., 2021. Application of a Radar Echo Extrapolation-Based Deep Learning Method in Strong Convection Nowcasting. Earth and Space Science 8, e2020EA001621. https://doi.org/10.1029/2020EA001621

(PDF:https://pan.baidu.com/s/1I1PE_fSXRF8Xi40jkhI3RA?pwd=c4c5 ） 

[9] Di, D., Li, J., Han, W., Yin, R., 2021. Geostationary Hyperspectral Infrared Sounder Channel Selection for Capturing Fast-Changing Atmospheric Information. IEEE Transactions on Geoscience and Remote Sensing 1 10. https://doi.org/10.1109/TGRS.2021.3078829

(PDF:https://pan.baidu.com/s/1VeHbm_m6o-KDcL8iAYY79A?pwd=deaq)

==============2020年============

[1] WANG Jin-cheng, GONG Jian-dong, and HAN Wei*. The impact of assimilating of FY-3C GNOS GPS radio occultation observations on GRAPES forecasts [J]. J Trop Meteor, 2020, 26(4): 390-401, https://doi.org/10.46267/j.1006-8775.2020.034.

(PDF:https://pan.baidu.com/s/1rGFu-tQcEDAvdHPO_hZiuw?pwd=9va6) 

[2] Xiao, H., Han, W.*, Wang, H. et al. Impact of FY-3D MWRI Radiance Assimilation in GRAPES 4DVar on Forecasts of Typhoon Shanshan. J Meteorol Res 34, 836–850 (2020). https://doi.org/10.1007/s13351-020-9122-x

(PDF： https://pan.baidu.com/s/1cg3Cvz1HFUSSCPBL81aydQ?pwd=utg7 ) 

[3] Yin Ruoying, Han Wei*, Gao Zhiqiu, Di Di. The evaluation of FY4A's Geostationary Interferometric Infrared Sounder (GIIRS) long wave temperature sounding channels using the GRAPES global 4D-Var. Q J R Meteorol Soc. 2020; 146:1459–1476. https://doi.org/10.1002/qj.3746

(PDF:https://pan.baidu.com/s/1GD2kqGJ8RkgcmYj7881lPQ?pwd=h2b6) 

[4] Xie, H., Bi, L., Han, W.*, Wang, J., 2020. Vertical Inhomogeneity Effect of Frozen Hydrometeor Habits in All-Sky Passive Microwave Simulations. Journal of Geophysical Research: Atmospheres 125, e2020JD032817. https://doi.org/10.1029/2020JD032817

(PDF:https://pan.baidu.com/s/1GLixZBaULQGUTMryTMHaTA?pwd=wqm9)

[5] 基于GRU神经网络的太阳辐照度短期预测--《中国科技论文》2020年01期 [WWW Document], n.d. URL http://www.cnki.com.cn/Article/CJFDTotal-ZKZX202001002.htm (accessed 1.11.21).

(PDF:https://pan.baidu.com/s/1M4ngcaC1ZivGygjRDSdWKQ?pwd=a8ak) 

[6] Li, W., Zhang, F., Zhang, F., Shi, Y.-N., Iwabuchi, H., Zhu, M., Li, J., Han, W., Letu, H., Ishimoto, H., 2020. Efficient radiative transfer model for thermal infrared brightness temperature simulation in cloudy atmospheres. Opt. Express, OE 28, 25730–25749. https://doi.org/10.1364/OE.400130

(PDF:https://pan.baidu.com/s/1W3z0UYIZ3N6OIXtDaM1G-g?pwd=3esm) 

[7] Wang, G., Wang, K., Han, W.*, Wang, D., Qiu, X., 2020. Typhoon Maria Precipitation Retrieval and Evolution Based on the Infrared Brightness Temperature of the Feng-Yun 4A/Advanced Geosynchronous Radiation Imager. Advances in Meteorology. https://doi.org/10.1155/2020/4245037

(PDF:https://pan.baidu.com/s/1sTWckG_tr7DpHrKnaz0Q8Q?pwd=t2ax ) 

==============2019年============

[1] Wang, G., Wang, D., Han, W.*, Yin, J., 2019. Typhoon Cloud System Identification and Forecasting Using the Feng-Yun 4A/Advanced Geosynchronous Radiation Imager Based on an Improved Fuzzy Clustering and Optical Flow Method. Advances in Meteorology. https://doi.org/10.1155/2019/5890794

(PDF:https://pan.baidu.com/s/1JcPs4ueJkN-ClNpTynPoVQ?pwd=ms2n) 

[2] Fan, Sihui, Han, Wei*, Gao, Zhiqiu, Yin, Ruoying, Zheng, Yu. Denoising Algorithm for the FY-4A GIIRS Based on Principal Component Analysis. Remote Sens. 2019, 11, 2710. https://doi.org/10.3390/rs11222710

(PDF:https://pan.baidu.com/s/1tI-kJCk8M8S0KwWzdQoNFg?pwd=2aa6 ) 

[3] 尹若莹,韩威*,高志球,王根. 2019. 基于FY-4A卫星探测区域模式背景误差和观测误差估计的长波红外通道选择研究[J]. 气象学报, 77(5):898-910, doi:10.11676/qxxb2019.051

(PDF:https://pan.baidu.com/s/1ilLQARLUvz8kaA8n2WnYIw?pwd=qct4) 

[4] 孟智勇, 张福青, 罗德海, 谈哲敏, 方娟, 孙建华, 沈学顺, 张云济, 汪曙光, 韩威, 赵坤, 朱磊, 胡永云, 薛惠文, 马亚平, 张丽娟, 聂绩, 周瑞琳, 李飒, 刘泓君, 朱宇宁. 2019. 新中国成立70年来的中国大气科学研究: 天气篇. 中国科学: 地球科学, 49: 1875–1918, doi: 10.1360/SSTe-2019-0175

(PDF:https://pan.baidu.com/s/14VDZQvF7A3QPNbvwcihLQQ?pwd=ga6e) 

[5] Meng Z, Zhang F, Luo D, Tan Z, Fang J, Sun J, Shen X, Zhang Y, Wang S, Han W, Zhao K, Zhu L, Hu Y, Xue H, Ma Y, Zhang L, Nie J, Zhou R, Li S,Liu H, Zhu Y. 2019. Review of Chinese atmospheric science research over the past 70 years: Synoptic meteorology. Science China Earth Sciences,62: 1946–1991, https://doi.org/10.1007/s11430-019-9534-6

(PDF:https://pan.baidu.com/s/1eDrLRN3jLDJ0EG9KYibklg?pwd=kw5p) 

[6] 万晓敏, 龚建东, 韩威, 等, 2019. FY-4A云导风在GRAPES_RAFS中的同化应用评估. 气象, 45(4): 458-468. DOI: 10.7519/j.issn.1000 0526.2019.04.002. WAN Xiaomin, GONG Jiandong, HAN Wei, et al, 2019. The Evaluation of FY-4A AMVs in GRAPES_RAFS. Meteorological Monthly, 45(4): 458-468. DOI: 10.7519/j.issn.1000-0526.2019.04.002.

(PDF:https://pan.baidu.com/s/14nujYUp6Ys8wtt00ib6ZTw?pwd=tfsy) 

[7] Jin, J., Segers, A., Heemink, A., Yoshida, M., Han, W., Lin, H.-X., 2019. Dust Emission Inversion Using Himawari-8 AODs Over East Asia: An Extreme Dust Event in May 2017. Journal of Advances in Modeling Earth Systems 11, 446467. https://doi.org/10.1029/2018MS001491

==============2018年及以下============

[1] Di, D., Jun Li, Han Wei, W. Bai, C. Wu, and W. Paul Menzel, 2018: Enhancing the fast radiative transfer model for FengYun-4 GIIRS by using local training profiles, Journal of Geophysical Research - Atmospheres, DOI: 10.1029/2018JD029089

(PDF:https://pan.baidu.com/s/1d9gI4nf7L4VB-quRMFtkKQ?pwd=dukt) 

[2] 王金成, 陆慧娟, 韩威, 刘艳, 王瑞春, 张华, 黄静, 刘永柱, 郝民, 李娟, 田伟红,2017. GRAPES全球三维变分同化业务系统性能[ WWW Document]. URL http://html.rhhz.net/yyqxxb/html/20170102.htm (accessed 3.15.21)

(PDF:https://pan.baidu.com/s/1qMvS1PnazLRzazyQ1D0gQQ?pwd=b2ms) 

[3] Li Jun and Han Wei, 2017: A step forward toward Effectively using hyperspectral IR sounding information in NWP, Advances in Atmospheric Sciences, 34, 1263 - 1264.

(PDF: https://pan.baidu.com/s/1FxOduZ9doBlxqwJJ-vXojA?pwd=iar8 )

[4] Dong P., Han W., Li W., Jin S. (2017) Assessment of Radiative Effect of Hydrometeors in Rapid Radiative Transfer Model in Support of Satellite Cloud and Precipitation Microwave Data Assimilation. In: Park S., Xu L. (eds) Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III). Springer, Cham. https://doi.org/10.1007/978-3-319-43415-5_15

(PDF:https://pan.baidu.com/s/1BS18baq_WvxBSCDFJAEi3A?pwd=jx68)

[5] Han Wei and Niels Bormann, 2016: Constrained adaptive bias correction for satellite radiances assimilation in the ECMWF 4D-Var, ECMWF Technical Memorandum, 783. https://doi.org/10.21957/rex0omex

(PDF:https://pan.baidu.com/s/1EYOPvkKguVR6GNVZSR8fFQ?pwd=cqdn) 

[6] Han Wei and McNally AP. 2010: The 4D-Var assimilation of ozone-sensitive infrared radiances measured by IASI. Q. J. R. Meteorol. Soc. 136: 2025–2037. DOI:10.1002/qj.708

(PDF:https://pan.baidu.com/s/1WTajp0_gRl5RhDgXQ5qa9w?pwd=kpjx) 

[7] Han Wei and Huang Sixun, 2004：Equatorial trapped waves on the mean state with zonal slow variation，J. Hydrodynamics SER.B , 16(2),182-185.

（PDF：https://pan.baidu.com/s/1RT9t1gD21ije6MyKaypSeQ?pwd=b3n9）

[8] Huang, Sixun, Han Wei and Wu Rongsheng, 2004: Theoretical analyses and numerical experiments of variational assimilation for one dimensional ocean temperature model with techniques in inverse problems, Science in China (D),47(7), 630-638.

（PDF：https://pan.baidu.com/s/1ltreMPc8uZclbhE9CE4Jug?pwd=mtaj）

[9] Huang Sixun, Xiang Jie and Han Wei, 2004: Nonlinear analysis of equatorial eastern pacific air-sea coupling oscillation and a limit-cycle theory for ENSO cycle. Appl. Math. Mech. in China, 25(5), 518-527.

（PDF：https://pan.baidu.com/s/1UfB7grE0D8F6GnIWI03dmw?pwd=c3is）

[10] 黄思训，韩威，伍荣生，2003，结合反问题技巧对一维海温模式变分资料同化的理论分析及数值试验，中国科学（D辑） 33（9），903-911.

(PDF:https://pan.baidu.com/s/1saF5fr8olT9DhLeWyizwAw?pwd=c9n8 ) 

2024：国家“万人计划”科技创新领军人才

2024：首届国家卓越工程师团队奖（核心成员，全球数值天气预报系统工程技术团队）

2023：中国气象局优秀气象科技成果（风云四号卫星高光谱探测仪目标观测和同化应用）

2022:  中国气象局气象领军人才

2021：第23届国际TOVS会议最佳报告奖

2021：国家科学技术进步奖二等奖（区域/全球一体化数值天气预报业务系统）

2018：中国气象学会第六届邹竞蒙气象科技人才奖

2017：中国气象学会气象科学技术进步成果奖一等奖（GRAPES_GFS全球中期数值预报系统开发和业务应用）

2014：中国气象学会第八届全国优秀气象工作者