近五年代表性論文
[1] W. Wang, C. Shi*, H. Shang, et al. (2024), Development of an algorithm for simultaneous retrieval of cloud top height and cloud optical thickness combining radiative transfer and multi-source satellite information from O4 hyperspectral measurement. IEEE Transactions on Geoscience and Remote Sensing, 10.1109/TGRS.2024.3385030
[2] J. Chen, C. Shi*, B. Zhao, et al. (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
[3] S. Yin, C. Shi*, H. Letu, et al. (2024), Reconstruction of PM2.5 concentration in East Asia based on wide-deep ensemble machine learning frameworks and estimation of the potential exposure level from 1981 to 2020, Engineering, https://doi.org/10.1016/j.eng.2024.09.025
[4] A. Li, C. Shi*, S. Yin, et al. (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, https://doi.org/10.1016/j.scitotenv.2024.176264
[5] H. Letu, R. Ma, T.Y. Nakajima, C. Shi*, et al. (2023) Surface Solar Radiation Compositions Observed from Himawari-8/9 and Fengyun-4 Series. Bulletin of the American Meteorological Society. 10.1175/BAMS-D-22-0154.1
[6] C.Q. Tang, C. Shi*, H. Letu, et al. (2023), Evaluation and uncertainty analysis of Himawari-8 hourly aerosol product version 3.1 and its influence on surface solar radiation before and during the COVID-19 outbreak. Science of the Total Environment, https://doi.org/10.1016/j.scitotenv.2023.164456.
[7] G. Tana, X. Ri, C. Shi*, et al. (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.
[8] C. Shi, M. Hashimoto, K. Shiomi, et al. (2020), 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, doi:10.1109/TGRS.2020.3038892.
[9] C. Shi, T. Nakajima, and M. Hashimoto (2019), Remote sensing of aerosol properties from multi-wavelength and multi-pixel information over the ocean. Atmospheric Chemistry and Physics, 19, 2461-2475.
[10] C. Shi, and T. Nakajima (2018), Simultaneous determination of aerosol optical thickness and water leaving radiance from multispectral measurements in coastal waters, Atmospheric Chemistry and Physics, 18, 3865-3884.
近五年代表性專著
[1] C. Shi, C. Tang, J. Xu, S. Yin, L. Rao, H. Letu (2024), Remote Sensing of Tropospheric Aerosol Optical Depth From Multispectral Monodirectional Space-Based Observations, Comprehensive Remote Sensing
[2] 石崇, 張曉涵, FY3/MERSI 海洋快速輻射傳輸模型及大氣訂正, 國家衛(wèi)星氣象中心, 2022-12
[3] M. Hashimoto, C. Shi, and T. Nakajima (2021), GOSAT-2 CAI-2 Level 2 aerosol retrieval Algorithm Theoretical Basis Document (ATBD), National Institute for Environmental Studies, Japan.
[4] M. Hashimoto, C. Shi, and T. Nakajima (2020), GOSAT-2/IBUKI-2 Data Users Handbook: CAI-2 Level 2 Aerosol Property Algorithm, National Institute for Environmental Studies, Japan.
[5] M. Hashimoto, C. Shi (2020), GOSAT-2 TANSO-CAI-2 L2 Pre-processing Algorithm Theoretical Basis Document (ATBD), National Institute for Environmental Studies & Japan Aerospace Exploration Agency, Japan.
