一、 自我介绍

我的研究兴趣主要集中在卫星遥感和卫星资料同化的关键理论和技术问题上，目前专注于国产数值预报模式中卫星微波仪器的资料同化技术研究。自2018年以来，我已发表各类学术论文10余篇，曾担任《Nature Communication》、《IEEE TGRS》等SCI期刊的审稿人。

目前，我主持国家重点研发计划青年科学家项目1项，国家自然科学基金面上项目和青年项目各1项，同时作为子课题负责人参与国家重点研发计划项目1项，并作为课题负责人参与湖南省自然科学基金重点项目1项。2022年，我荣幸入选中国气象局“青年英才计划”。

我目前参加了多个国际工作组，包括国际空间科学研究所（ISSI）积雪/海冰发射和后向散射建模工作组、国际气象卫星研讨会（ITSC）数值预报工作组、辐射传输工作组，并定期与国内外专家学者开展线上线下技术交流。

二、你能得到什么

1. 直面数值预报实际问题的机会。如果你的研究成果具有实用性，将有机会直接引入业务数值预报模式中，并在其中留下你的名字，成为解决实际问题的英雄！
2. 充足的科研资源。你将拥有国家级超算资源支持，保证数值试验的顺利运行。同时，我们提供海量的气象数据，包括历史和实时的国内外卫星数据、再分析数据等，减轻你下载数据的压力（特殊情况除外）。
3. 优秀的研究团队。我的团队成员都非常优秀，性格热情、和善。我们提供充分的机会，让每位成员展示成果并讨论遇到的难题。团队内有多元化的科学研讨，大家共同进步，也能开阔你的学术视野。
4. 开放的学术氛围。我们不限制研究课题的具体内容，除了与我们现有的研究方向相关之外，你完全可以根据自己的兴趣去探索有意义的课题。但要确保方向大致符合我们的研究大框架，否则我可能没办法给你提供精准的指导。

三、你需要具备哪些能力

1. 独立思考的能力。如果你不理解这一条，那么请先花点时间独立思考一下。
2. 扎实的专业基础。不要求你能背诵大段的概念和定义，但要对基本概念有清晰的理解，遇到不懂的可以主动查找答案，且懂得如何求解。
3. 计算机能力。FORTRAN语言是我们工作的基础，SHELL/PYTHON/MATLAB/NCL等都是你可能用到的工具。如果你已经非常熟练这些编程语言，那你会觉得在我们团队如鱼得水。如果不太熟悉，但有学习和提升的渴望，那也是大欢迎的态度！
4. 语言文字能力。包括听、说、读、写。
• 听：能从学术报告中抓住重点，迅速吸收关键信息。
• 说：能清晰、流畅地表达自己的观点与问题。
• 读：能独立阅读学术论文，抓住核心内容并进行总结。
• 写：能够撰写逻辑严谨、条理清晰的学术论文。

以上语言文字能力包括中文和英文。

工作经历

教育经历

1.       Dong, C. J., H. Hu*, and F. Z. Weng, 2024: Optimal assimilation of microwave upper-level sounding data in CMAGFS. Adv. Atmos. Sci., 41(10), 2043−2060, https://doi.org/10.1007/s00376-024-3323-7.

2.       Y. Han, H. Hu, Y. Shi and J. Yang, Identification and Correction of Radio Frequency Interference of Fengyun-3 Microwave Radiation Imager Using a Machine-Learning Method, in IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-13, 2023, Art no. 5301213, doi: 10.1109/TGRS.2023.3268678.

3.       J. Xu, Z. Ma, H. Hu* and F. Weng, A Cloud-Dependent 1DVAR Precipitation Retrieval Algorithm for FengYun-3D Microwave Soundings: A Case Study in Tropical Cyclone Mekkhala, in IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1-5, 2023, Art no. 1000605, doi: 10.1109/LGRS.2023.3243934.

4.       Hu H., F. Weng, 2022: Influences of 1DVAR Background Covariances and Observation Operators on Retrieving Tropical Cyclone Thermal Structures. Remote Sensing. 14(5):1078. https://doi.org/10.3390/rs14051078

5.       Kan, W., Hu, H.*, Weng, F. 2022: An All-Sky Scattering Index Derived from Microwave Sounding Data at Dual Oxygen Absorption Bands. Remote Sens. 14, 5332. https://doi.org/10.3390/rs14215332

6.       Hu, H., and Y. Han, 2021: Comparing the Thermal Structures of Tropical Cyclones Derived from Suomi NPP ATMS and FY-3D Microwave Sounders [J]. IEEE Transactions on Geoscience and Remote Sensing, 59(10), 8073-8083, doi: 10.1109/TGRS.2020.3034262.

7.       Hu, H., F. Weng, Y. Han, and Y. Duan, 2019: Remote Sensing of Tropical Cyclone Thermal Structure from Satellite Microwave Sounding Instruments: Impacts of Background Profiles on Retrievals [J]. Journal of Meteorological Research, 33, 89-103, doi: 10.1007/s13351-019-8094-1.

8.       Hu, H., Y. Duan, Y. Wang, and X. Zhang, 2017: Diurnal Cycle of Rainfall Associated with Landfalling Tropical Cyclones in China from Rain Gauge Observations [J]. J. Appl. Meteor. Climatol., 56: 2595–2605.

9.       Zhang, Y., Hu, H., Weng, F. 2021. The Potential of Satellite Sounding Observations for Deriving Atmospheric Wind in All-Weather Conditions [J]. Remote Sensing. 13(15): 2947. https://doi.org/10.3390/rs13152947

10.   Li, S., Hu, H., Fang, C., Wang, S., Xun, S., He, B., Wu, W., Huo, Y. 2022: Hyperspectral Infrared Atmospheric Sounder (HIRAS) Atmospheric Sounding System. Remote Sens. 14, 3882. https://doi.org/10.3390/rs14163882

11.   Han, Y., J. Yang, H. Hu, P. Dong, 2020: Retrieval of Oceanic Total Precipitable Water Vapor and Cloud Liquid Water from Fengyun-3D Microwave Sounding Instruments. Journal of Meteorological Research [J]. doi: 10.1007/s13351-021-0084-4.

12.   Feng, J., Duan, Y., Wan, Q., Hu, H., & Pu, Z. 2020: Improved Prediction of Landfalling Tropical Cyclone in China Based on Assimilation of Radar Radial Winds with New Super-Observation Processing, Weather and Forecasting, 35(6), 2523-2539.

13.   Kan, W., Dong, P., Weng, F., Hu, H., Dong, C. Impact of Fengyun-3E Microwave Temperature and Humidity Sounder Data on CMA Global Medium Range Weather Forecasts. Remote Sens. 2022, 14, 5014. https://doi.org/10.3390/rs14195014

14.   Wei, N., X. Zhang, L. Chan, and H. Hu, 2018: Comparison of the effect of easterly and westerly vertical wind shear on tropical cyclone intensity change over the western North Pacific [J]. Environmental Research Letters, 13(3): 034020.

15.   Zhang, X., Y. Duan, Y. Wang, N. Wei, and H. Hu, 2017: A high-resolution simulation of Supertyphoon Rammasun (2014)—Part I: Model verification and surface energetics analysis [J]. Advances in Atmospheric Sciences, 34: 757-770.

16.   Deng, L., Feng, J., Zhao, Y., Bao, X., Huang, W., Hu, H., & Duan, Y. 2022: The remote effect of binary Typhoon Infa and Cempaka on the “21.7” heavy rainfall in Henan Province, China. Journal of Geophysical Research: Atmospheres, 127, e2021JD036260. https://doi.org/10.1029/2021JD036260

1.       Hu H., Weng F. Typhoon's Thermal and Hydrometeor Profiles Derived from Fengyun-3D Microwave Instruments. The Tenth Asia-Oceania Meteorological Satellite Users’ Conference (Oral Presentation). December 2-7, 2019, Melbourne, Australia.

2.       Hu H., Weng F., Huo Y., Han Y. FY-3D 1DVAR sounding system with scene-dependent error covariances and its applications for typhoon monitoring. The First Fengyun Satellite User Forum (Oral Presentation). November 15-17, 2019, Haikou, Hainan.

3.       Hu, H. and Weng, F., 2020. Estimation of Location and Intensity of Tropical Cyclones Based on Microwave Sounding Instruments (Oral Presentation). IEEE International Geoscience and Remote Sensing Symposium 2020, 5442-5445, doi: 10.1109/IGARSS39084.2020.9323785.

4.       Hu, H.; Weng F.; Yang J.; Han Y.; Shi Y., 2021. GSDART: A Global Scene-Dependent Atmospheric Retrieval Testbed for Passive Microwave Sounding Instruments (Oral Presentation). International TOVS Study Conferences XXIII.

5.       Weng F., H. Hu, Assessments of FY-3D MWTS on-orbit Performance Using Suomi NPP ATMS Data (Oral Presentation). AGU Fall Meeting 2018, December 10-14, 2018, Washington D. C., USA.

6.        Weng F., Hu H., Han Y. Comparing the Thermal Structures of Tropical Cyclones Derived from ATMS and MWHS. IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (Poster). IEEE, 2019: 7680-7682, Yokohama, Japan.

7.       Hu, H., Christopher Grassotti, et. al., Intercomparison of Rain Rates from NOAA's Microwave Integrated Retrieval System (MiRS) with Surface Gauge Observations over China during 2014-2017. 33^rd Conference on Hydrology (Poster), January 09, 2019, Phoenix, USA.

8.       Hu, H., Y. Duan, Environmental Thresholds of Tropical Cyclone Rapid Intensification in the South China Sea. 32^nd Conference on Hurricanes and Tropical Meteorology (Oral Presentation), April 17-22, 2016, San Juan, USA.

2022年中国气象局青年气象英才

2020年“新一代风云气象卫星科学算法创新大赛”特等奖（第一完成人）