Preprints
https://doi.org/10.5194/essd-2023-414
https://doi.org/10.5194/essd-2023-414
15 Nov 2023
 | 15 Nov 2023
Status: this preprint is currently under review for the journal ESSD.

Introduction to the NJIAS Himawari-8/9 cloud feature dataset for climate and typhoon research

Xiaoyong Zhuge, Xiaolei Zou, Lu Yu, Xin Li, Mingjian Zeng, Yilun Chen, Bing Zhang, Bin Yao, Fei Tang, Fengjiao Chen, and Wanlin Kan

Abstract. The use of remote sensing method to accurately measure cloud properties and their spatiotemporal changes has been widely welcomed in many fields of atmospheric research. The Nanjing Joint Institute for Atmospheric Sciences (NJIAS) Himawari-8/9 Cloud Feature Dataset (HCFD) provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the 7 yr period from April 2016 to December 2022. Multiple cloud variables, such as cloud mask, phase/type, top height, optical thickness, and particle effective radius, as well as snow, dust and haze masks, were generated from the visible and infrared measurements of the Advanced Himawari Imager (AHI) onboard the Japanese geostationary satellites Himawari-8/9 using a series of cloud retrieval algorithms developed by Dr. Zhuge and his colleagues. Verifications with the Cloud–Aerosol Lidar with Orthogonal Polarization 1-km cloud layer product and the Moderate Resolution Imaging Spectroradiometer Level-2 cloud product (MYD06) demonstrates that the NJIAS HCFD gives higher skill scores than the Japanese Himawari-8/9 operational cloud product for all cloud variables except for the particle effective radius. The NJIAS HCFD even outperforms the MYD06 in the nighttime continental cloud detection and the infrared-only cloud-top phase determination. Then, two application examples are presented, to demonstrate the use of the NJIAS HCFD for climate and typhoon research. The NJIAS HCFD has been published at the Science Data Bank (https://doi.org/10.57760/sciencedb.09950, Zhuge 2023a; https://doi.org/10.57760/sciencedb.09953, Zhuge 2023b; https://doi.org/10.57760/sciencedb.09954, Zhuge 2023c; https://doi.org/10.57760/sciencedb.10158, Zhuge 2023d; https://doi.org/10.57760/sciencedb.09945, Zhuge 2023e).

Xiaoyong Zhuge et al.

Status: open (until 02 Jan 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Xiaoyong Zhuge et al.

Data sets

NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD)–0.04Deg. Part I: 2016–2017 (Version 3) Xiaoyong Zhuge https://doi.org/10.57760/sciencedb.09950

NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD)–0.04Deg. Part II: 2018–2019 (Version 3) Xiaoyong Zhuge https://doi.org/10.57760/sciencedb.09953

NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD)–0.04Deg. Part III: 2020–2021 (Version 3) Xiaoyong Zhuge https://doi.org/10.57760/sciencedb.09954

NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD)–0.04Deg. Part IV: 2022–2023 (Version 3) Xiaoyong Zhuge https://doi.org/10.57760/sciencedb.10158

NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD)–TyWNP (Version 3) Xiaoyong Zhuge https://doi.org/10.57760/sciencedb.09945

Xiaoyong Zhuge et al.

Viewed

Total article views: 28 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
22 5 1 28 0 0
  • HTML: 22
  • PDF: 5
  • XML: 1
  • Total: 28
  • BibTeX: 0
  • EndNote: 0
Views and downloads (calculated since 15 Nov 2023)
Cumulative views and downloads (calculated since 15 Nov 2023)

Viewed (geographical distribution)

Total article views: 27 (including HTML, PDF, and XML) Thereof 27 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 01 Dec 2023
Download
Short summary
The Himawari-8/9 level-2 operational cloud product has a low spatial resolution and is available only during the daytime. To supplement this official dataset, a new dataset named the NJIAS Himawari-8/9 Cloud Feature Dataset (HCFD) was constructed. The NJIAS HCFD provides a comprehensive description of cloud features over the East Asia and west North Pacific regions for the years 2016–2022, by 30 retrieved cloud variables. The NJIAS HCDF has been demonstrated to outperform the official dataset.
Altmetrics