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1. Leng, W., Wang, T., Yan, X., Huang, H., Letu, H., and Zhang, Z., 2026. A scheme to quantify the adjacency effect of shortwave radiation from highly reflective surfaces. Remote Sensing of Environment, 345, 115601.
https://doi.org/10.1016/j.rse.2026.115601

2. Xian, Y., Wang, T., Wang, G., Yu, P., Du, Y., Letu, H., Bian, J., Leng, W., and Yang, H., 2026. Satellite-derived daily shortwave radiation over the Tibetan Plateau considering topographic effects: Method and products. Remote Sensing of Environment, 344, 115547.
https://doi.org/10.1016/j.rse.2026.115547

3. Ma, R., Letu, H., Wang, S., and Chen, M., 2026. Estimation of Solar Radiation and Its Direct and Diffuse Components from the FY-4A Based on the Transfer Learning Method. Journal of Remote Sensing, 6, 1044.
https://doi.org/10.34133/remotesensing.1044

4. Ma, R., and Letu, H., 2026. Cloud, Atmospheric Radiation and Renewal Energy Application (CARE) Version 1.2 Shortwave Cloud Radiative Forcing From Himawari-8 and FY-4A: Algorithm Development and Preliminary Validation. IEEE Transactions on Geoscience and Remote Sensing, 64, 1–10.
https://doi.org/10.1109/tgrs.2026.3669180

5. Letu, H., Shang, H., Ma, R., Shi, C., Nakajima, T.Y., Ishimoto, H., Riedi, J., Wei, L., Xu, R., Ji, D., Sun, Q., Bilige, S., Wang, T., An, N., Bao, F., Lei, Y., Wang, H., Wang, W., Xu, J., Wang, Z., Bao, S., Baran, A.J., Feng, J., Chen, L., Shi, J., Nakajima, T., and Shi, G., 2026. CARE: a next-generation high resolution cloud and radiation remote sensing product and its Earth system applications. Science Bulletin, 71(7), 1831–1842.
https://doi.org/10.1016/j.scib.2026.02.046

6. Shi, C., Wang, T., Li, Z., Li, D., and Letu, H., 2026. Towards an easy-to-use algorithm to estimate longwave cloud radiative forcing: algorithm development and preliminary evaluation. Remote Sensing of Environment, 333, 115107.
https://doi.org/10.1016/j.rse.2025.115107

7. Letu, H., 2026. Surface solar radiation products based on new-generation geostationary satellite. Handbook of Satellite Land Products, 21–26 [Book chapter].
https://doi.org/10.1016/b978-0-443-21485-1.00003-0

8. Bao, F., Letu, H., and Xu, R., 2026. How Cloud Feedbacks Modulate the Tibetan Plateau Thermal Forcing: A Lead–Lag Perspective. Remote Sensing, 18(1), 122.
https://doi.org/10.3390/rs18010122

9. Xian, Y., Wang, T., Du, Y., Yu, P., and Letu, H., 2025. A strategy to estimate daily shortwave downward radiation in rugged regions from a few satellite observations. GIScience & Remote Sensing, 62(1), 2557700.
https://doi.org/10.1080/15481603.2025.2557700

10. Wang, S., Huang, G., Dai, T., Cao, J., Husi, L., Ma, R., and Li, C., 2025. Investigating the role of aerosol wet scavenging on global horizontal irradiance simulation in the WRF-Chem-solar model. Applied Energy, 396, 126062.
https://doi.org/10.1016/j.apenergy.2025.126062

11. Shi, C., Wang, T., Wang, G., and Letu, H., 2025. The net warming effect of clouds on global surface temperature may be weakening or even disappearing. Geoscience Frontiers, 16(5), 102107.
https://doi.org/10.1016/j.gsf.2025.102107

12. Wang, S., Huang, G., Dai, T., Xia, X.A., Husi, L., Ma, R., and Li, C., 2025. Online-Coupled Aerosol Effects on Cloud Microphysics and Surface Solar Irradiance in WRF-Solar. Remote Sensing, 17(16), 2829.
https://doi.org/10.3390/rs17162829

13. Xu, K., Shi, H., Chen, H., Letu, H., Li, J., He, W., Fan, X., Chen, Y., Ma, S., and Zhang, X., 2025. Marine Unmanned Surface Vehicle Measurements of Solar Irradiance Under Typhoon Conditions. Drones, 9(6), 395.
https://doi.org/10.3390/drones9060395

14. Shi, C., Letu, H., Nakajima, T.Y., Nakajima, T., Wei, L., Xu, R., Lu, F., Riedi, J., Ichii, K., Zeng, J., Shang, H., Ma, R., Yin, S., Shi, J., Baran, A.J., Xu, J., Li, A., Tana, G., Wang, W., Na, Q., Sun, Q., Yang, W., Chen, L., and Shi, G., 2025. Near-global monitoring of surface solar radiation through the construction of a geostationary satellite network observation system. The Innovation, 6(5), 100876.
https://doi.org/10.1016/j.xinn.2025.100876

15. Li, A., Shi, C., Yin, S., Li, N., Letu, H., and Shi, G., 2024. Variation of surface solar radiation components from 2016 to 2020 in China: Perspective from geostationary satellite observation with a high spatiotemporal resolution. Science of The Total Environment, 954, 176264.
https://doi.org/10.1016/j.scitotenv.2024.176264

16. Chen, J., Shi, C., Zhao, B., Yin, S., Tang, C., Letu, H., Xu, J., and Ma, R., 2024. Assessment of Ocean Color Products From the New Generation Himawari-8 AHI Geostationary Satellite and Its Application in the Calculation of the Photosynthetically Active Radiation. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–13.
https://doi.org/10.1109/tgrs.2024.3494797

17. Xian, Y., Wang, T., Du, Y., Letu, H., Qi, J., and Li, D., 2024. A dataset of topographic correction coefficients for shortwave downward radiation over the Pan-Third Pole. Scientific Data, 11(1), 779.
https://doi.org/10.1038/s41597-024-03616-2

18. Du, Y., Wang, T., Zhou, Y., Letu, H., Li, D., and Xian, Y., 2024. Toward User-Friendly All-Sky Surface Longwave Downward Radiation from Space: General Scheme and Product. Bulletin of the American Meteorological Society, 105(7), E1303–E1319.
https://doi.org/10.1175/bams-d-23-0126.1

19. Xian, Y., Wang, T., Leng, W., Letu, H., Shi, J., Wang, G., Yan, X., and Yuan, H., 2024. Can Topographic Effects on Solar Radiation Be Ignored: Evidence From the Tibetan Plateau. Geophysical Research Letters, 51(6), e2024GL108653.
https://doi.org/10.1029/2024gl108653

20. Wang, G., Wang, T., Yuan, H., Leng, W., Letu, H., and Xian, Y., 2024. Surface Shortwave Net Radiation Estimation From Space: Emphasizing the Effects of Aerosol, Solar Zenith Angles, and DEM. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–21.
https://doi.org/10.1109/tgrs.2024.3350027

21. Zhang, T., Letu, H., Dai, T., Shi, C., Lei, Y., Peng, Y., Lin, Y., Chen, L., Shi, J., Tian, W., and Shi, G., 2024. Estimating hourly surface shortwave radiation over northeast of the Tibetan Plateau by assimilating Himawari-8 cloud optical thickness. Geoscience Letters, 11(1), 1.
https://doi.org/10.1186/s40562-023-00312-8

22. Ma, R., and Husi, L.T., 2024. CARE product: Cloud microphysics and shortwave radiation forcing algorithms and applications. National Remote Sensing Bulletin, 28(9), 2320–2334.
https://doi.org/10.11834/jrs.20232450

23. Leng, W., Wang, T., Wang, G., Letu, H., Wang, S., Xian, Y., Yan, X., and Zhang, Z., 2023. All-sky surface and top-of-atmosphere shortwave radiation components estimation: Surface shortwave radiation, PAR, UV radiation, and TOA albedo. Remote Sensing of Environment, 298, 113830.
https://doi.org/10.1016/j.rse.2023.113830

24. Cui, Y., Husi, L., Li, T., Ji, D., Zhang, H., and Shi, J., 2023. Spatio-temporal Changes in Surface Net Radiation in the Qinghai-Tibet Plateau from 2000 to 2021. Chinese Journal of Space Science, 43(6), 1150–1159.
https://doi.org/10.11728/cjss2023.06.2023-0080

25. Letu, H., Ma R., T.Y. Nakajima, C. Shi, M. Hashimoto, T.M. Nagao, A.J. Baran, T. Nakajima, J. Xu, T.X. Wang, L. et al., 2023. Surface solar radiation compositions observed from Himawari-8/-9 and Fengyun-4 series. Bulletin of the American Meteorological Society.
https://doi.org/10.1175/bams-d-22-0154.1

26. Shao, J., Letu, H., Ri, X., Tana, G., Wang, T., and Shang, H., 2023. Estimation of Surface Downward Longwave Radiation and Cloud Base Height Based on Infrared Multichannel Data of Himawari-8. Atmosphere, 14(3), 493.
https://doi.org/10.3390/atmos14030493

27. Letu, H., Nakajima, T.Y., Wang, T., Shang, H., Ma, R., Yang, K., Baran, A.J., Riedi, J., Ishimoto, H., Yoshida, M., Shi, C., Khatri, P., Du, Y., Chen, L., Shi, J., 2022. A new benchmark for surface radiation products over the East Asia-Pacific region retrieved from the Himawari-8/AHI next-generation geostationary satellite. Bulletin of the American Meteorological Society, 1–40.
https://doi.org/10.1175/bams-d-20-0148.1

28. Letu, H., Yang, K., Nakajima, T.Y., Ishimoto, H., Nagao, T.M., Riedi, J., Baran, A.J., Ma, R., Wang, T., Shang, H., Khatri, P., Chen, L., Shi, C., and Shi, J., 2020. High-resolution retrieval of cloud microphysical properties and surface solar radiation using Himawari-8/AHI next-generation geostationary satellite. Remote Sensing of Environment, 239, 111583.
https://doi.org/10.1016/j.rse.2019.111583

29. Wang, T., Shi, J., Ma, Y., Letu, H., and Li, X., 2020. All-sky longwave downward radiation from satellite measurements: General parameterizations based on LST, column water vapor and cloud top temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 161, 52-60.
https://doi.org/10.1016/j.isprsjprs.2020.01.011

30. Wang, T., Shi, J., Ma, Y., Husi, L., Comyn‐Platt, E., Ji, D., and Xiong, C. ,2019. Recovering land surface temperature under cloudy skies considering the solar‐cloud‐satellite geometry: Application to MODIS and Landsat‐8 data. Journal of Geophysical Research: Atmospheres, 124(6), 3401-3416.
https://doi.org/10.1029/2018jd028976

云掩码

1. An, N., Shang, H., Lesi, W., Ri, X., Shi, C., Tana, G., Bao, Y., Zheng, Z., Xu, N., Chen, L., Zhang, P., Ye, L., and Letu, H., 2023. A Cloud Detection Algorithm for Early Morning Observations from the FY-3E Satellite, IEEE Transactions on Geoscience and Remote Sensing.
https://doi.org/10.1109/tgrs.2023.3304985

2. Wang, T., Shi, J., Letu, H., Ma, Y., Li, X., and Zheng, Y., 2019. Detection and removal of clouds and associated shadows in satellite imagery based on simulated radiance fields. Journal of Geophysical Research: Atmospheres, 124(13), 7207-7225.
https://doi.org/10.1029/2018jd029960

3. Shang, H., Chen, L., Letu, H., Zhao, M., Li, S., and Bao, S., 2017. Development of a daytime cloud and haze detection algorithm for Himawari‐8 satellite measurements over central and eastern China. Journal of Geophysical Research: Atmospheres, 122(6), 3528-3543.
https://doi.org/10.1002/2016jd025659

4. Letu, H., T. M. Nagao, T. Y. Nakajima, and Y. Matsumae, 2014. Method for validating cloud mask obtained from satellite measurements using ground-based sky camera. Applied optics, 53(31), 7523-7533.
https://doi.org/10.1364/ao.53.007523

云分类和云相态

1. Li, Q., Shi, H., Xie, Y., Jiang, R., Wang, C., Teng, Y., Jia, S., Wen, J., Fu, D., Yang, J., Fan, X., Zhang, J., Zhen, X., Liu, M., Letu, H., Chen, H., and Xia, X.A., 2026. Revealing the lifecycle evolution of hail-producing deep convective clouds by synergy of multi-source data. Atmospheric Research, 336, 108845.
https://doi.org/10.1016/j.atmosres.2026.108845

2. Li, S., Liu, L., Hu, S., Zhao, J., Zhuo, Y., Liu, Y., and Letu, H., 2025. Cloud Identification and Phase Classification by Submillimeter and Infrared Synergistic Observations in the Arctic. IEEE Transactions on Geoscience and Remote Sensing, 63, 1–10.
https://doi.org/10.1109/tgrs.2025.3617890

3. Ri, X., Letu, H., Shi, C., Nakajima, T.Y., Shang, H., Bao, F., Sude, B., Atsushi, H., Yang, W., Kazuhito, I., Lei, Y., Zhao, J., and Shi, J., 2024. Cloud Top Temperature and Cloud Optical Thickness Can Effectively Identify Convective Clouds Over the Tibetan Plateau. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–11.
https://doi.org/10.1109/tgrs.2024.3486463

4. Bao, F., Letu, H., Shang, H., Ri, X., Chen, D., Yao, T., Wei, L., Tang, C., Yin, S., Ji, D., Lei, Y., Shi, C., Peng, Y., and Shi, J., 2024. Advancing Cloud Classification Over the Tibetan Plateau: A New Algorithm Reveals Seasonal and Diurnal Variations. Geophysical Research Letters, 51(13), e2024GL109590.
https://doi.org/10.1029/2024gl109590

5. Wang, Z., Letu, H., Shang, H., and Bugliaro, L., 2024. Technical note: Retrieval of the supercooled liquid fraction in mixed-phase clouds from Himawari-8 observations. Atmospheric Chemistry and Physics, 24(13), 7559–7574.
https://doi.org/10.5194/acp-24-7559-2024

6. Shang, H., Letu, H., Xu, R., Wei, L., Wu, L., Shao, J., Nagao, T.M., Nakajima, T.Y., Riedi, J., He, J., and Chen, L., 2024. A hybrid cloud detection and cloud phase classification algorithm using classic threshold-based tests and extra randomized tree model. Remote Sensing of Environment, 302, 113957.
https://doi.org/10.1016/j.rse.2023.113957

7. Wang, Z., Letu, H., Shang, H., Zhao, C., Li, J., and Ma, R. 2019. A Supercooled Water Cloud Detection Algorithm Using Himawari‐8 Satellite Measurements. Journal of Geophysical Research: Atmospheres, 124(5), 2724-2738.
https://doi.org/10.1029/2018jd029784

云微物理特性

1. Letu, H., Shang, H., Wang, H., Duan, B., Peng, C., Jiang, R., Qie, X., Wang, J., Liu, L., Zhang, T., Wu, G., Gao, J., Chen, L., Zhang, P., Zhao, C., Chen, D., Yao, T., and Wu, Y., 2026. Exploring Cloud Microphysics and Electric Fields in Non-Lightning Clouds over the Third Pole: First Results from a Tethered-Balloon Campaign. Advances in Atmospheric Sciences, advance online publication.
https://doi.org/10.1007/s00376-026-6361-5

2. Zhuo, Y., Li, S., Liu, L., Hu, S., Letu, H., Zeng, Q., and Liu, Y., 2026. A Novel Approach to Enhancing Spatial Resolution in Submillimeter‐Wave Ice Cloud Parameter Retrieval. Atmospheric Science Letters, 27(3), e70012.
https://doi.org/10.1002/asl2.70012

3. Yang, Y., Dou, T., Xu, G., Zhou, R., Li, B., Husi, L., Wang, W., and Xiao, C., 2026. FYAI: a Fengyun satellite-based dataset for atmospheric ice water path. Earth System Science Data, 18(2), 1287–1305.
https://doi.org/10.5194/essd-18-1287-2026

4. Wang, Y., Shang, H., Tang, C., Xu, J., Ji, T., Wang, W., Wei, L., Lei, Y., Shi, J., and Letu, H., 2025. Characterization of liquid cloud profiles using global collocated active radar and passive polarimetric cloud measurements. Atmospheric Chemistry and Physics, 25(22), 16167–16187.
https://doi.org/10.5194/acp-25-16167-2025

5. Wang, H., Peng, Y., Di Noia, A., Shang, H., Letu, H., van Diedenhoven, B., Hasekamp, O.P., Liu, Y., and Quaas, J., 2025. Global quantification of the dispersion effect with POLDER satellite data. Nature Communications, 16(1), 7087.
https://doi.org/10.1038/s41467-025-62238-3

6. Shang, H., Letu, H., Wei, L., Ma, R., Wang, Y., Cai, Z., Yin, S., and Shi, C., 2025. Remote sensing of liquid cloud profiles based on an analytical cloud profiling model. Science China Earth Sciences, 68(4), 998–1012.
https://doi.org/10.1007/s11430-024-1532-2

7. Tana, G., Lesi, W., Shang, H., Xu, J., Ji, D., Shi, J., Letu, H., and Shi, C., 2025. A New Cloud Water Path Retrieval Method Based on Geostationary Satellite Infrared Measurements. IEEE Transactions on Geoscience and Remote Sensing, 63, 1–10.
https://doi.org/10.1109/tgrs.2025.3526262

8. Li, S., Li, X., Liu, L., Letu, H., Hu, S., Zeng, Q., Dong, P., and Zhuo, Y., 2024. Synergistic Retrievals of Ice Cloud Microphysics by Spaceborne Submillimeter and Infrared Observations. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–10.
https://doi.org/10.1109/tgrs.2024.3453248

9. Li, W., Zhang, F., Guo, B., Fu, H., and Letu, H., 2024. Physics-Driven Machine Learning Algorithm Facilitates Multilayer Cloud Property Retrievals From Geostationary Passive Imager Measurements. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–18.
https://doi.org/10.1109/tgrs.2024.3369621

10. Wang, W., Xu, J., Letu, H., Zhang, L., Wang, Z., and Shi, J., 2024. A New Deep-Learning-Based Framework for Ice Water Path Retrieval From Microwave Humidity Sounder-II Aboard FengYun-3D Satellite. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–14.
https://doi.org/10.1109/tgrs.2024.3352654

11. Wang, Y., Shang, H., Letu, H., Wei, L., Chen, F., Hong, J., Wang, Z., and Chen, L., 2023. Impact of Orbital Characteristics and Viewing Geometry on the Retrieval of Cloud Properties From Multiangle Polarimetric Measurements. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–17.
https://doi.org/10.1109/tgrs.2023.3329305

12. Li, J., Zhang, F., Li, W., Tong, X., Pan, B., Li, J., Lin, H., Letu, H., and Mustafa, F., 2023. Transfer-Learning-Based Approach to Retrieve the Cloud Properties Using Diverse Remote Sensing Datasets. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–10.
https://doi.org/10.1109/tgrs.2023.3318374

13. Tana, G., Ri, X., Shi, C., Ma, R., Letu, H., Xu, J., and Shi, J. 2023. Retrieval of cloud microphysical properties from Himawari-8/AHI infrared channels and its application in surface shortwave downward radiation estimation in the sun glint region. Remote Sensing of Environment, 290, 113548.
https://doi.org/10.1016/j.rse.2023.113548

14. Li, M., Letu, H., Peng, Y., Ishimoto, H., Lin, Y., Nakajima, T. Y., ... and Shi, J. 2022. Investigation of ice cloud modeling capabilities for the irregularly shaped Voronoi ice scattering models in climate simulations. Atmospheric Chemistry and Physics, 22(7), 4809-4825.
https://doi.org/10.5194/acp-22-4809-2022

15. Letu, H., T. M. Nagao, T. Y. Nakajima, J. Riedi, H. Ishimoto, A. J. Baran, Shang, H., M. Sekiguchi, and M. Kikuchi, 2019. Ice cloud properties from Himawari-8/AHI next-generation geostationary satellite: Capability of the AHI to monitor the DC cloud generation process. IEEE Transactions on Geoscience and Remote Sensing, 57(6), 3229-3239.
https://doi.org/10.1109/tgrs.2018.2882803

16. Letu, H., H. Ishimoto, J. Riedi, T. Y. Nakajima, L. C.-Labonnote, A. J. Baran, T. M. Nagao, and M. Sekiguchi, 2016. Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission. Atmospheric Chemistry and Physics, 16(18), 12287-12303.
https://doi.org/10.5194/acp-16-12287-2016

云宏观物理特性

1. Ji, T., Shang, H., Wei, L., Bao, F., Liu, Z., Wang, Y., Bao, S., Yin, S., Shi, C., Wang, H., Liu, Z., and Letu, H., 2026. Retrieval of the base heights and geometric thicknesses of clouds based on the PARASOL measurement. Remote Sensing of Environment, 342, 115477.
https://doi.org/10.1016/j.rse.2026.115477

2. Wang, Q., Zhu, Y., Liu, C., Husi, L., Zhou, R., and Zhou, C., 2026. Efficient Retrieval of Subpixel Cloud Fraction From Coarse Cloud Masks Using Dual‐Branch Deep Learning. Journal of Geophysical Research: Machine Learning and Computation, 3(2), e2025JH001112.
https://doi.org/10.1029/2025jh001112

3. Shang, H., Xu, R., Wang, X., Bao, F., Wei, L., Zhao, Y., Yin, S., Ji, D., Ma, R., Shi, C., Wang, H., Lei, Y., Zhang, T., Letu, H., and Shi, J., 2026. Developing Long-term Cloud Fraction Records from MODIS Data Considering Diurnal Cycle of Clouds. Journal of Geodesy and Geoinformation Science, 9(1), 1–10.
https://doi.org/10.11947/j.JGGS.2026.0101 (resolution pending)

4. Shi, C., Wang, T., Li, Z., Yan, X., and Letu, H., 2025. A general algorithm to retrieve cloud top properties by incorporating spectral characteristics and lidar measurements. International Journal of Applied Earth Observation and Geoinformation, 143, 104842.
https://doi.org/10.1016/j.jag.2025.104842

5. Wang, W., Shi, C., Xu, J., Yin, S., Shang, H., Wang, Y., Tang, C., Yao, R., Shi, G., and Letu, H., 2025. Passive Remote Sensing of Marine Liquid Cloud Geometric Thickness Using the O2–O2 Band: First Results From TROPOMI. Geophysical Research Letters, 52(3), e2024GL113222.
https://doi.org/10.1029/2024gl113222

6. Wang, W., Letu, H., Shang, H., Xu, J., Yan, H., Gao, L., Yu, C., Gu, J., Tao, J., Xu, N., Chen, L., and Chen, L., 2024. A novel physics-based cloud retrieval algorithm based on neural networks (CRANN) from hyperspectral measurements in the O2-O2 band. Remote Sensing of Environment, 311, 114267.
https://doi.org/10.1016/j.rse.2024.114267

7. Wang, W., Shi, C., Shang, H., Yin, S., Xu, J., Xu, N., Chen, L., and Letu, H., 2024. Development of an Algorithm for the Simultaneous Retrieval of Cloud-Top Height and Cloud Optical Thickness Combining Radiative Transfer and Multisource Satellite Information From O₄ Hyperspectral Measurements. IEEE Transactions on Geoscience and Remote Sensing, 62, 1–11.
https://doi.org/10.1109/tgrs.2024.3385030

8. Wei, L., Shang, H., Xu, J., Shi, C., Tana, G., Chao, K., Bao, S., Chen, L., and Letu, H., 2024. Cloud Top Pressure Retrieval Using Polarized and Oxygen A-band Measurements from GF5 and PARASOL Satellites. Advances in Atmospheric Sciences, 41(4), 680–700.
https://doi.org/10.1007/s00376-023-2382-5

9. Xu, R. Tana, G., Shi, C., Nakajima, T.Y., Shi, J., Zhao, J., Xu, J., Letu, H., 2022. Cloud, Atmospheric Radiation and Renewal Energy Application (CARE) Version 1.0 Cloud Top Property Product From Himawari-8/AHI: Algorithm Development and Preliminary Validation. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–11.
https://doi.org/10.1109/tgrs.2022.3172228

10. Nakajima, T. Y., Ishida, H., Nagao, T. M., Hori, M., Letu, H., Higuchi, R., and Yamazaki, A., 2019. Theoretical basis of the algorithms and early phase results of the GCOM-C (Shikisai) SGLI cloud products.Progress in Earth and Planetary Science, 6(1), 52.
https://doi.org/10.1186/s40645-019-0295-9

气溶胶

1. Ekpe, E.E., Shi, C., Yin, S., Wang, H., Zhao, Y., Letu, H., and Raihan, M.Z.U., 2026. A 25-year analysis of aerosol optical depth dynamics over Nigeria (2000–2024): spatial-temporal dynamics, seasonal regimes, and extreme event characterization. Air Quality, Atmosphere & Health, 19(10), 224.
https://doi.org/10.1007/s11869-026-02111-4

2. Yao, R., Shi, C., Letu, H., Yin, S., Nakajima, T., Sekiguchi, M., Xu, J., Rao, L., Wang, W., Tang, C., and Han, R., 2026. A physics-based AI algorithm integrating radiative transfer and machine learning for joint retrieval of aerosol layer height and optical thickness from hyperspectral satellite observations over the ocean. Remote Sensing of Environment, 338, 115379.
https://doi.org/10.1016/j.rse.2026.115379

3. Shi, C., Tang, C., Xu, J., Yin, S., Rao, L., and Letu, H., 2026. Remote Sensing of Tropospheric Aerosol Optical Depth From Multispectral Monodirectional Space-Based Observations. Comprehensive Remote Sensing, 184–208 [Book chapter].
https://doi.org/10.1016/b978-0-443-13220-9.00026-3

4. Tang, C., Shi, C., Letu, H., Yin, S., Nakajima, T., Sekiguchi, M., Xu, J., Zhao, M., Ma, R., and Wang, W., 2025. Development of a hybrid algorithm for the simultaneous retrieval of aerosol optical thickness and fine-mode fraction from multispectral satellite observation combining radiative transfer and transfer learning approaches. Remote Sensing of Environment, 319, 114619.
https://doi.org/10.1016/j.rse.2025.114619

5. Khatri, P., Hayasaka, T., Patra, P.K., Letu, H., Jethva, H., and Hayashida, S., 2025. Unveiling the effects of post-monsoon agricultural biomass burning on aerosols, clouds, and radiation in Northwest India. Progress in Earth and Planetary Science, 12(1), 11.
https://doi.org/10.1186/s40645-025-00685-8

6. Rao, L., Efremenko, D., Doicu, A., Shi, C., Yin, S., Letu, H., and Xu, J., 2025. Physics-Constrained Bayesian Neural Networks for Aerosol Retrieval From Hyperspectral Satellite Measurements With Integrated Uncertainty Quantification. IEEE Transactions on Geoscience and Remote Sensing, 63, 1–18.
https://doi.org/10.1109/tgrs.2025.3640712

7. Zhang, X., Shi, C., Si, Y., Letu, H., Wang, L., Tang, C., Xu, N., He, X., Yin, S., Zhang, Z., and Chen, L., 2023. Remote Sensing of Aerosols and Water-Leaving Radiance from Chinese FY-3/MERSI Based on a Simultaneous Method. Remote Sensing, 15(24), 5650.
https://doi.org/10.3390/rs15245650

8. Chen, Y., Fan, M., Li, M., Li, Z., Tao, J., Wang, Z., and Chen, L., 2022. Himawari-8/AHI Aerosol Optical Depth Detection Based on Machine Learning Algorithm. Remote Sensing, 14(13), 2967.
https://doi.org/10.3390/rs14132967

9. Shi, C., M. Hashimoto, and T. Nakajima, 2019. Remote sensing of aerosol properties from multi-wavelength and multi-pixel information over the ocean. Atmospheric Chemistry and Physics, 19, 2461-2475.
https://doi.org/10.5194/acp-19-2461-2019

水汽和降水

1. Sai, H., Xie, Y., Letu, H., Cui, M., Bao, S., Xu, N., Li, X., Zhu, J., Qiu, W., Shi, J., and Ji, D., 2026. A Geostationary Satellite Precipitation Estimation Machine Learning Model With Dynamic Sample Balancing for Fengyun-4B. IEEE Transactions on Geoscience and Remote Sensing, 64, 1–18.
https://doi.org/10.1109/tgrs.2026.3681960

2. Sun, Q., Letu, H., Wang, Y., Zhang, P., Liang, H., Shi, C., Yin, S., Shi, J., and Ji, D., 2026. An hourly 0.02° total precipitable water dataset for all-weather conditions over the Tibetan Plateau through the fusion of observations of geostationary and multi-source microwave satellites. Earth System Science Data, 18(1), 371–395.
https://doi.org/10.5194/essd-18-371-2026

3. Lei, Y., Letu, H., and Shi, J., 2025. Effect of Seasonality on Declining Snowfall over the Tibetan Plateau. Journal of Climate, 38(18), 4641–4652.
https://doi.org/10.1175/jcli-d-24-0503.1

4. Ji, D., Letu, H., Ri, X., Xu, N., Li, X., Li, X., Zhang, G., Wang, Y., and Shi, J., 2025. A New Dynamically Updated Geostationary Satellite Precipitation Estimation Algorithm for Near Real-Time Condition. IEEE Transactions on Geoscience and Remote Sensing, 63, 1–22.
https://doi.org/10.1109/tgrs.2025.3583904

5. Sun, Q., Ji, D., Letu, H., Ni, X., Zhang, H., Wang, Y., Li, B., and Shi, J., 2024. A method for estimating high spatial resolution total precipitable water in all-weather condition by fusing satellite near-infrared and microwave observations. Remote Sensing of Environment, 302, 113952.
https://doi.org/10.1016/j.rse.2023.113952

6. Chen, X., Letu, H., Shang, H., Ri, X., Tang, C., Ji, D., Shi, C., and Teng, Y., 2024. Rainfall Area Identification Algorithm Based on Himawari-8 Satellite Data and Analysis of its Spatiotemporal Characteristics. Remote Sensing, 16(5), 747.
https://doi.org/10.3390/rs16050747

7. Ji, D., Shi, J., Xiong, C., Wang, T., and Zhang, Y., 2017. A total precipitable water retrieval method over land using the combination of passive microwave and optical remote sensing. Remote Sensing of Environment, 191, 313-327.
https://doi.org/10.1016/j.rse.2017.01.028

辐射传输

1. Shi, C., Letu, H., Nakajima, T., Sekiguchi, M., Wang, W., Yao, R., Shang, H., Yin, S., Xu, J., An, N., Jiang, W., Cui, Y., Su, L., Wu, Y., and Shi, G., 2026. CARE Radiative Transfer Model: A Tool for Supporting Polarization and Hyperspectral Radiative Transfer Simulation in the Coupled Atmosphere–Ocean System. Advances in Atmospheric Sciences, 43(9), 1775–1795.
https://doi.org/10.1007/s00376-026-5676-6

2. Zhang, H., Liu, L., Bi, L., Lin, W., Liu, C., Yi, B., Liu, L., Chen, Q., Wei, X., Letu, H., Li, Z., and Li, W., 2024. Advances in Atmospheric Radiation: Theories, Models, and Their Applications. Part I: Atmospheric Gas Absorption and Particle Scattering. Journal of Meteorological Research, 38(2), 151–182.
https://doi.org/10.1007/s13351-024-3091-4

3. Zhang, H., Zhang, F., Liu, L., Liu, Y., Letu, H., Yang, Y., Li, Z., Wu, K., Hu, S., Li, M., Dai, T., Wang, F., Wang, Z., Ling, Y., Shi, Y., and Liu, C., 2024. Advances in Atmospheric Radiation: Theories, Models, and Their Applications. Part II: Radiative Transfer Models and Related Applications. Journal of Meteorological Research, 38(2), 183–208.
https://doi.org/10.1007/s13351-024-3089-y

4. Shi, C., M. Hashimoto, K. Shiomi, and T. Nakajima, 2021. Development of an Algorithm to Retrieve Aerosol Optical Properties Over Water Using an Artificial Neural Network Radiative Transfer Scheme: First Result From GOSAT-2/CAI-2. IEEE Transactions on Geoscience and Remote Sensing, 59, 9861-9872.
https://doi.org/10.1109/tgrs.2020.3038892

5. Ma, R., Letu, H., Yang, K., Wang, T.X., Shi, C., Xu, j., Shi, J.C., Shi, C., and Chen, L.F., 2020. Estimation of Surface Shortwave Radiation From Himawari-8 Satellite Data Based on a Combination of Radiative Transfer and Deep Neural Network. IEEE Transactions on Geoscience and Remote Sensing, 1-13.
https://doi.org/10.1109/tgrs.2019.2963262

6. Letu, H., Nakajima, T. Y., and Matsui, T. N., 2012. Development of an ice crystal scattering database for the global change observation mission/second generation global imager satellite mission: investigating the refractive index grid system and potential retrieval error. Applied optics, 51(25), 6172-6178.
https://doi.org/10.1364/ao.51.006172

7. Nakajima, T., and Tanaka, M. (1986). Matrix formulations for the transfer of solar radiation in a plane-parallel scattering atmosphere. Journal of Quantitative Spectroscopy and Radiative Transfer, 35, 13-21.
https://doi.org/10.1016/0022-4073(86)90088-9