Abstract
Recognizing the importance and challenges inherent in the remote sensing of precipitation in typhoon monitoring, a study of the Advanced Geosynchronous Radiation Imager (AGRI) data from Feng-Yun 4A on typhoon precipitation was conducted. First, Typhoon Maria was selected to statistically analyze the AGRI infrared brightness temperature in the “precipitation” and “nonprecipitation” channels of the field of view. When there was precipitation, the brightness temperature of the AGRI channel changed significantly. Second, the shrunken locally linear embedding algorithm (SLLE) was adopted to carry out the retrieval of precipitation based on the brightness temperatures of AGRI infrared channels 8–14. The contribution rate of the brightness temperature at different channels to the objective function of precipitation retrieval model was obtained by the Bayesian model averaging (BMA). Based on the preliminary experimental “quantification” evaluation index, we concluded that the method adopted in this paper can be used to retrieve precipitation in infrared data and to retrieve the spiral cloud rain bands of a typhoon. Finally, based on the AGRI channel brightness temperature of a 10.8-micron window channel, we applied the membership degree information of a typhoon’s dominant cloud system from the fuzzy c-means (FCM) clustering method to modify precipitation retrieval results. The results were used to obtain the main morphological structure of typhoon precipitation. By further analyzing the temporal variation of dominant cloud system development using the FCM method, we concluded that the brightness temperature gradient can assist in the analysis of the variation of a typhoon’s intensity. This method can be applied to the continuous retrieval of large-scale precipitation. Precipitation retrieval via the AGRI can yield indicators for typhoon precipitation warnings and forecasts, thus providing a reliable reference tool for disaster prevention and mitigation.
Highlights
Precipitation plays an important role in the global energy and water cycle, and monitoring and forecasting it is crucial when a typhoon, rainstorm, or severe convection develops and occurs
In this study, infrared data from Typhoon Maria in 2018 were selected and applied to typhoon precipitation monitoring based on the statistical analysis of the brightness temperature gradient in different infrared channels of “precipitation” and “nonprecipitation” field of view (FOV) by using Feng-Yun 4A/Advanced Geosynchronous Radiation Imager (AGRI) infrared channel brightness temperature
(2) Retrieval of typhoon precipitation information based on the improved SLEE method: the L1 norm regularization in the retrieval model can promote sparsity; that is, the maximum amount of original information can be retained with fewer dictionary atoms
Summary
Precipitation plays an important role in the global energy and water cycle, and monitoring and forecasting it is crucial when a typhoon, rainstorm, or severe convection develops and occurs. Meteorological satellites can effectively obtain information such as brightness temperature in unattended areas, such as oceans, mountains, and deserts. E cloud top brightness temperature, which is located at the highest level of the atmospheric vertical layer and is provided by the stationary meteorological satellite, can reveal significant characteristics about the existence of clouds and the evolution stage of clouds and can reflect the distribution of rain areas of typhoons to a certain extent [1]. At 05:00 Coordinated Universal Time (UTC), July 8, 2018, Maria had developed into a supertyphoon in the northwest Pacific Ocean and was located approximately 1,930 km to the southeast of Yilan County, Taiwan. E brightness temperature of AGRI infrared channel in the region of Typhoon Maria on July 09, 2018, to July 11, 2018, was used to identify precipitation signals.
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