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Discussion papers
https://doi.org/10.5194/amt-2019-447
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-447
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 02 Dec 2019

Submitted as: research article | 02 Dec 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Retrieval of the total precipitable water vapor and cloud liquid water path over ocean from the Feng-Yun 3D microwave temperature and humidity sounders

Jun Yang, Fuzhong Weng, Hao Hu, and Peiming Dong Jun Yang et al.
  • State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China

Abstract. Feng-Yun 3D (FY-3D) satellite is the latest polar-orbiting meteorological satellite launched by China and carry 10 instruments onboard. Its microwave temperature sounder (MWTS) and microwave humidity sounder (MWHS) can acquire a total of 28 channels of brightness temperatures, providing rich information for profiling atmospheric temperature and moisture. However, due to a lack of two important frequencies at 23.8 and 31.4 GHz, it is difficult to retrieve the total precipitable water vapor (TPW) and cloud liquid water path (CLW) from FY-3D microwave sounder data as commonly done for other microwave sounding instruments. Using the channel similarity between Suomi NPP advanced technology microwave sounder (ATMS) and FY-3D microwave temperature and humidity sounders, a machine learning technique is used to generate the two missing low frequency channels of MWTS and MWHS. Then, a new data set named as a combined microwave sounder (CMWS) is obtained and has the same channel setting as ATMS but the spatial resolution is consistent with MWTS. It is shown that the mean absolute errors of the two simulated channels are both between 3 and 4 K. The simulation errors mainly distribute in the high latitude regions, coastlines and the boundaries of some heavy rainfall. A statistical inversion method is adopted to retrieve TPW and CLW over oceans from the FY-3D CMWS. The inter-comparison between different satellites shows that the inversion products of FY-3D CMWS and Suomi NPP ATMS have good consistency in magnitude and distribution.

Jun Yang et al.
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Short summary
A machine learning technique is used to generate the two missing low frequency channels of FY-3D microwave temperature and humidity sounders. A statistical inversion method is adopted to retrieve total precipitable water vapor and cloud liquid water path over ocean from the FY-3D microwave data. The inter-comparison between different satellites shows that the inversion products of FY-3D and Suomi NPP ATMS have good consistency in magnitude and distribution.
A machine learning technique is used to generate the two missing low frequency channels of FY-3D...
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