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

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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Remote Sensing of Environment 2020-03, Vol.239, p.111583, Article 111583
Hauptverfasser: Letu, Husi, Yang, Kun, Nakajima, Takashi Y., Ishimoto, Hiroshi, Nagao, Takashi M., Riedi, Jérôme, Baran, Anthony J., Ma, Run, Wang, Tianxing, Shang, Huazhe, Khatri, Pradeep, Chen, Liangfu, Shi, Chunxiang, Shi, Jiancheng
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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. •The AHI official cloud algorithm (version 1.0) is developed for the JAXA P-Tree system.•The Voronoi ice crystal scattering model is used to develop the ice cloud product.•High-accuracy SSR is estimated using the AHI cloud parameters.
ISSN:0034-4257
1879-0704
DOI:10.1016/j.rse.2019.111583