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The KALION Automated Aerosol Type Classification and Mass Concentration Calculation Algorithm

한반도 에어로졸 라이다 네트워크(KALION)의 에어로졸 유형 구분 및 질량 농도 산출 알고리즘

  • Yeo, Huidong (School of Earth and Environmental Sciences, Seoul National University) ;
  • Kim, Sang-Woo (School of Earth and Environmental Sciences, Seoul National University) ;
  • Lee, Chulkyu (Climate Change Monitoring Division, Korea Meteorological Administration) ;
  • Kim, Dukhyeon (School of Basic Sciences, Hanbat National University) ;
  • Kim, Byung-Gon (Department of Atmospheric Environmental Sciences, Gangneung-Wonju National University) ;
  • Kim, Sewon (Climate Change Monitoring Division, Korea Meteorological Administration) ;
  • Nam, Hyoung-Gu (High-impact Weather Research Center, Observational Research Division, National Institute of Meteorological Sciences) ;
  • Noh, Young Min (Environmental Science and Engineering, Gwangju Institute of Science and Technology) ;
  • Park, Soojin (School of Earth and Environmental Sciences, Seoul National University) ;
  • Park, Chan Bong (Department of Electronic Engineering, Mokwon University) ;
  • Seo, Kwangsuk (Seoul Metropolitan Government Research Institute of Public Health and Environment) ;
  • Choi, Jin-Young (National Institute for Environmental Research) ;
  • Lee, Myong-In (School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology) ;
  • Lee, Eun hye (Climate Change Monitoring Division, Korea Meteorological Administration)
  • 여희동 (서울대학교 지구환경과학부) ;
  • 김상우 (서울대학교 지구환경과학부) ;
  • 이철규 (기상청 기후변화감시과) ;
  • 김덕현 (한밭대학교 기초과학부) ;
  • 김병곤 (강릉원주대학교 대기환경과학과) ;
  • 김세원 (기상청 기후변화감시과) ;
  • 남형구 (국립기상과학원 재해기상연구센터) ;
  • 노영민 (광주과학기술원 환경공학부) ;
  • 박수진 (서울대학교 지구환경과학부) ;
  • 박찬봉 (목원대학교 전자공학과) ;
  • 서광석 (서울특별시 보건환경연구원) ;
  • 최진영 (국립환경과학원 기상재해연구센터) ;
  • 이명인 (울산과학기술원 도시환경공학부) ;
  • 이은혜 (기상청 기후변화감시과)
  • Received : 2016.03.27
  • Accepted : 2016.04.04
  • Published : 2016.04.30

Abstract

Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.

한반도 에어로졸 라이다 관측 네트워크(Korea Aerosol Lidar Observation Network; KALION)의 라이다 관측자료 처리 및 실시간 표출을 위한 표준 알고리즘을 개발하였다. KALION 표준 알고리즘은 라이다 관측으로부터 얻어진 후방산란강도와 편광소멸도 자료를 이용하여 (1) 에어로졸과 구름 구분, (2) 에어로졸 유형 구분, (3) 에어로졸 소산계수 그리고 (4) 에어로졸 질량농도를 산출하는 단계로 구성이 되어 있다. 에어로졸의 유형은 후방산란강도와 편광소멸도 자료에 근거하여, (대륙 기원) 청정기단 에어로졸(clean continental aerosol), 황사(dust aerosol) 그리고 오염 입자(polluted continental/urban pollution aerosol)로 구별된다. 에어로졸 소산계수에 필요한 라이다 상수는 약 9년간의 라이다와 스카이 라디오미터 자료로부터 도출된 63.31 sr을, 에어로졸 질량소산효율은 약 9년간의 라이다와 기상청 Particulate Matter($PM_{10}$) 질량농도 자료를 이용하여 도출된 $3.36m^2\;g^{-1}$ (황사는 $1.39m^2\;g^{-1}$)을 적용한다. 2015년 3월 28일부터 30일까지 라이다 관측 사례(서울 관악)에서 KALION 표준 알고리즘을 통해 산출된 에어로졸 유형 구분, 특히 황사 판별 결과는 기상청의 황사 보고와 잘 일치하였으며, 2006년 6월부터 약 9년 동안의 라이다 관측자료로부터 산출된 에어로졸 질량농도 역시 지상 $PM_{10}$ 농도와 약 $3{\mu}g\;m^{-3}$ 내에서 잘 일치하였다. 향후 에어로졸의 유형에 따른 서로 다른 라이다 상수 및 에어로졸 질량소산효율 적용 알고리즘, 빙정 구름(ice cloud)과 물방울 구름(water droplet cloud) 구분 알고리즘, 그리고 운저 고도와 혼합고 판별 알고리즘을 개발할 계획에 있다.

Keywords

References

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