High-resolution retrieval of cloud microphysical properties and surface solar radiation using Himawari-8/AHI next-generation geostationary satellite

Husi Letu, Kun Yang, Takashi Y. Nakajima, Hiroshi Ishimoto, Takashi M. Nagao, Jérôme Riedi, Anthony J. Baran, Run Ma, Tianxing Wang, Huazhe Shang, Pradeep Khatri, Liangfu Chen, Chunxiang Shi, Jiancheng Shi

研究成果: Article査読

30 被引用数 (Scopus)

抄録

Optical properties of clouds and heavy aerosol retrieved from satellite measurements are the most important elements for calculating surface solar radiation (SSR). The Himawari-8/Advanced Himawari Imager (AHI) satellite measurements receive high spatial, temporal and spectral signals, which provides an opportunity to estimate cloud, aerosol and SSR accurately. In this study, we developed the AHI official cloud property product (version 1.0) for JAXA P-Tree system. A look-up table (LUT) method was used to calculate high-temporal (10 min) and high-spatial (5 km) SSR from AHI cloud properties. First, the LUT of the SSR estimation was optimized through a radiative transfer model to account for solar zenith angle, cloud optical thickness (COT), effective particle radius (CER), aerosol optical thickness and surface albedo. Following this, COT and CER were retrieved from the AHI data, with ice cloud parameters being retrieved from an extended Voronoi ice crystal scattering database and water cloud parameters being retrieved from the Mie–Lorenz scattering model. The retrieved COT and CER for water clouds were compared well with MODIS collection 6 cloud property products, with correlation coefficients of 0.77 and 0.82, respectively. The COT of ice cloud also shows good consistency, with a correlation coefficient of 0.85. Finally, the SSR was calculated based on the SSR LUT and the retrieved cloud optical parameters. The estimated SSR was validated at 122 radiation stations from several observing networks covering the disk region of Himawari-8. The root-mean-square error (RMSE) at CMA (China Meteorological Administration) stations was 101.86 Wm 2 for hourly SSR and 31.42 Wm 2 for daily SSR; RMSE at non-CMA stations was 119.07 Wm 2 for instantaneous SSR, 81.10 Wm 2 for hourly SSR and 26.58 Wm 2 for daily SSR. Compared with the SSR estimated from conventional geostationary satellites, the accuracy of the SSR obtained in this study was significantly improved.

本文言語English
論文番号111583
ジャーナルRemote Sensing of Environment
239
DOI
出版ステータスPublished - 2020 3 15

ASJC Scopus subject areas

  • 土壌科学
  • 地質学
  • 地球科学におけるコンピュータ

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