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Advances in Atmospheric Sciences

, Volume 34, Issue 1, pp 16–25 | Cite as

A cloud detection scheme for the Chinese Carbon Dioxide Observation Satellite (TANSAT)

  • Xi Wang
  • Zheng Guo
  • Yipeng Huang
  • Hongjie Fan
  • Wanbiao Li
Open Access
Original Paper
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Accepted:

Abstract

Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite (TANSAT), a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager (CAPI), which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloudscreening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer (VIRR) onboard the Chinese FengYun-3A Polar-orbiting Meteorological Satellite (FY-3A), which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas (desert, snow, ocean, forest) for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.

Keywords

TANSAT CAPI cloud detection regrouping scheme 
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Notes

Acknowledgments

This research was sponsored by the National Basic Research (973) Program of China from the Ministry of Science and Technology of China (Grant No. 2013CB430104) and the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA05040201).

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© Authors 2017

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Xi Wang
    • 1
    • 2
  • Zheng Guo
    • 2
  • Yipeng Huang
    • 1
  • Hongjie Fan
    • 1
  • Wanbiao Li
    • 1
  1. 1.Laboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of PhysicsPeking UniversityBeijingChina
  2. 2.National Satellite Meteorological CenterChina Meteorological AdministrationBeijingChina

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