Atmospheric profile retrieval algorithm for next generation geostationary satellite of Korea and its application to the advanced Himawari Imager

Su Jeong Lee, Myoung Hwan Ahn, Sung Rae Chung

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

In preparation for the 2nd geostationary multi-purpose satellite of Korea with a 16-channel Advanced Meteorological Imager; an algorithm has been developed to retrieve clear-sky vertical profiles of temperature (T) and humidity (Q) based on a nonlinear optimal estimation method. The performance and characteristics of the algorithm have been evaluated using the measured data of the Advanced Himawari Imager (AHI) on board the Himawari-8 of Japan, launched in 2014. Constraints for the optimal estimation solution are provided by the forecasted T and Q profiles from a global numerical weather prediction model and their error covariance. Although the information contents for temperature is quite low due to the limited number of channels used in the retrieval; the study reveals that useful moisture information (2~3 degrees of freedom for signal) is provided from the three water vapor channels; contributing to the increase in the moisture retrieval accuracy upon the model forecast. The improvements are consistent throughout the tropospheric atmosphere with almost zero mean bias and 9% (relative humidity) of root mean square error between 100 and 1000 hPa when compared with the quality-controlled radiosonde data from 2016 August.

Original languageEnglish
Article number1294
JournalRemote Sensing
Volume9
Issue number12
DOIs
StatePublished - 1 Dec 2017

Keywords

  • Clear sky atmospheric profile retrieval
  • Himawari AHI
  • Information contents
  • Next generation geostationary imager
  • Optimal estimation
  • Total precipitable water

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