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Feasibility Study for Detecting the Tropopause Folding Turbulence Using COMS Geostationary Satellite

천리안 위성 자료를 이용한 대류권계면 접힘 난류 탐지 가능성 연구

  • Kim, Mijeong (Department of Atmosphere Sciences, Division of Earth Environmental System, Pusan National University) ;
  • Kim, Jae Hwan (Department of Atmosphere Sciences, Division of Earth Environmental System, Pusan National University)
  • 김미정 (부산대학교 지구환경시스템학부 대기과학전공) ;
  • 김재환 (부산대학교 지구환경시스템학부 대기과학전공)
  • Received : 2016.10.13
  • Accepted : 2017.03.10
  • Published : 2017.06.30

Abstract

We present and discuss the Tropopause Folding Turbulence Detection (TFTD) algorithm for the Korean Communication, Ocean, Meteorological Satellite (COMS) which is originally developed for the Tropopause Folding Turbulence Product (TFTP) from the Geostationary Operational Environmental Satellite (GOES)-R. The TFTD algorithm assumes that the tropopause folding is linked to the Clear Air Turbulence (CAT), and thereby the tropopause folding areas are detected from the rapid spatial gradients of the upper tropospheric specific humidity. The Layer Averaged Specific Humidity (LASH) is used to represent the upper tropospheric specific humidity calculated using COMS $6.7{\mu}m$ water vapor channel and ERA-interim reanalysis temperature at 300, 400, and 500 hPa. The comparison of LASH with the numerical model specific humidity shows a strong negative correlation of 80% or more. We apply the single threshold, which is determined from sensitivity analysis, for cloud-clearing to overcome strong gradient of LASH at the edge of clouds. The tropopause break lines are detected from the location of strong LASH-gradient using the Canny edge detection based on the image processing technique. The tropopause folding area is defined by expanding the break lines by 2-degree positive gradient direction. The validations of COMS TFTD is performed with Pilot Reports (PIREPs) filtered out Convective Induced Turbulence (CIT) from Dec 2013 to Nov 2014 over the South Korea. The score test shows 0.49 PODy (Probability of Detection 'Yes') and 0.64 PODn (Probability of Detection 'No'). Low POD results from various kinds of CAT reported from PIREPs and the characteristics of high sensitivity in edge detection algorithm.

Keywords

References

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