NDLI: Detection of Deep Convective Clouds Using AMSU-B and GOES-9 Data

Content Provider	IEEE Xplore Digital Library
Author	Zhu Yaping Liu Jianwen Cheng Zhoujie
Copyright Year	2008
Description	Author affiliation: Inst. of Aviation Meteorol., Beijing (Zhu Yaping; Liu Jianwen; Cheng Zhoujie)
Abstract	Methods to detect the deep convective clouds using NOAA-16/AMSU-B and GOES-9 data are provided, and a serial of algorithms of detection and discrimination are presented and tested, which include the microwave brightness temperatures detection from the two window channels, water vapor channel microwave brightness differences identification based on the AMSU-B data, infrared brightness thresholds detection of cloud top temperatures, the water vapor and infrared window temperature differences determination, and the classification of cumulonimbus clouds correlating with deep convective clouds with infrared/water vapor spectral features. By detecting and analyzing deep convective clouds in the images on 16 June in 2004, the techniques are investigated, and by matching surface conventional data the results of various methods are validated. The results show that microwave brightness temperatures from window channels can discriminate deep convective clouds efficiently, differences between three water vapor channels can identify the deep convective clouds well and depend on the thresholds less. The GOES-9 different infrared brightness thresholds are given the detection regions are more or less. The water vapor and infrared window temperature differences determination areas are smaller. The stepwise cluster can identify cumulonimbus clouds correlating with deep convective clouds applying with infrared/water vapor spectral features, the detection areas are coincident with AMSU-B detection areas, and the surface conventional data can validate the results, which include hazards weather and cumulonimbus clouds.
Starting Page	278
Ending Page	281
File Size	3393694
Page Count	4
File Format	PDF
ISBN	9781424438211
DOI	10.1109/CJMW.2008.4772425
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Shanghai Univ.
Subject Keyword	Infrared detectors deep convective cloud Clouds Weather forecasting Infrared spectra optical remote sensing microwave remote sensing Storms Infrared imaging Microwave theory and techniques Brightness temperature Optical sensors Testing
Content Type	Text
Resource Type	Article

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