대기 (Atmosphere)

  • 제28권2호
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  • Pages.113-121
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  • 2018
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  • 1598-3560(pISSN)
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  • 2288-3266(eISSN)
한국기상학회 (Korean Meteorological Society)
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인버스 모델링을 이용한 지표면 이산화탄소 플럭스 추정 향상을 위한 항공기 관측 이산화탄소 자료동화 체계 개발

Development of the Aircraft CO2 Measurement Data Assimilation System to Improve the Estimation of Surface CO2 Fluxes Using an Inverse Modeling System

  • 김현정 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 김현미 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 조민광 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 박준 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 김대휘 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실)
  • Kim, Hyunjung (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Kim, Hyun Mee (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Cho, Minkwang (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Park, Jun (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Kim, Dae-Hui (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University)
  • 투고 : 2018.01.11
  • 심사 : 2018.04.11
  • 발행 : 2018.06.30
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초록

In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

키워드

참고문헌

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