Journal
REMOTE SENSING
Volume 9, Issue 12, Pages -Publisher
MDPI AG
DOI: 10.3390/rs9121294
Keywords
clear sky atmospheric profile retrieval; Himawari AHI; optimal estimation; next generation geostationary imager; information contents; total precipitable water
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Funding
- Development of AAP Algorithms project
- ETRI - NMSC (National Meteorological Satellite Center) of KMA (Korea Meteorological Administration) [NMSC-2016-01]
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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 similar to 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.
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