Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
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Parameter Optimization and Automation of the FLEXPART Lagrangian Particle Dispersion Model for Atmospheric Back-trajectory Analysis

공기괴 역궤적 분석을 위한 FLEXPART Lagrangian Particle Dispersion 모델의 최적화 및 자동화

  • Kim, Jooil (School of Earth and Environmental Sciences, Seoul National University) ;
  • Park, Sunyoung (Department of Oceanography, Kyungpook National University) ;
  • Park, Mi-Kyung (School of Earth and Environmental Sciences, Seoul National University) ;
  • Li, Shanlan (School of Earth and Environmental Sciences, Seoul National University) ;
  • Kim, Jae-Yeon (School of Earth and Environmental Sciences, Seoul National University) ;
  • Jo, Chun Ok (School of Earth and Environmental Sciences, Seoul National University) ;
  • Kim, Ji-Yoon (School of Earth and Environmental Sciences, Seoul National University) ;
  • Kim, Kyung-Ryul (School of Earth and Environmental Sciences, Seoul National University)
  • 김주일 (서울대학교 지구환경과학부) ;
  • 박선영 (경북대학교 생태환경대학 해양학과) ;
  • 박미경 (서울대학교 지구환경과학부) ;
  • 리선란 (서울대학교 지구환경과학부) ;
  • 김재연 (서울대학교 지구환경과학부) ;
  • 조춘옥 (서울대학교 지구환경과학부) ;
  • 김지윤 (서울대학교 지구환경과학부) ;
  • 김경렬 (서울대학교 지구환경과학부)
  • Received : 2012.12.11
  • Accepted : 2012.12.30
  • Published : 2013.03.31
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Abstract

Atmospheric transport pathway of an air mass is an important constraint controlling the chemical properties of the air mass observed at a designated location. Such information could be utilized for understanding observed temporal variabilities in atmospheric concentrations of long-lived chemical compounds, of which sinks and/or sources are related particularly with natural and/or anthropogenic processes in the surface, and as well as for performing inversions to constrain the fluxes of such compounds. The Lagrangian particle dispersion model FLEXPART provides a useful tool for estimating detailed particle dispersion during atmospheric transport, a significant improvement over traditional "single-line" trajectory models that have been widely used. However, those without a modeling background seeking to create simple back-trajectory maps may find it challenging to optimize FLEXPART for their needs. In this study, we explain how to set up, operate, and optimize FLEXPART for back-trajectory analysis, and also provide automatization programs based on the open-source R language. Discussions include setting up an "AVAILABLE" file (directory of input meteorological fields stored on the computer), creating C-shell scripts for initiating FLEXPART runs and storing the output in directories designated by date, as wells as processing the FLEXPART output to create figures for a back-trajectory "footprint" (potential emission sensitivity within the boundary layer). Step by step instructions are explained for an example case of calculating back trajectories derived for Anmyeon-do, Korea for January 2011. One application is also demonstrated in interpreting observed variabilities in atmospheric $CO_2$ concentration at Anmyeon-do during this period. Back-trajectory modeling information introduced in this study should facilitate the creation and automation of most common back-trajectory calculation needs in atmospheric research.

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References

  1. 박상진, 이종범, 김재철, 2008: GDAS와 MM5를 이용한 HYSPLIT_4 모델의 결과 비교. 한국대기환경학회 2008 춘계학술대회 논문집, 555-556
  2. Cooper, O. R. and Coauthors, 2010: Increasing springtime ozone mixing ratios in the free troposphere over western North America. Nature, 463(7279), 344-348. doi:10.1038/nature08708.
  3. Hirdman, D., K. Aspmo, J. F. Burkhart, S. Eckhardt, H. Sodemann, and A. Stohl, 2009: Transport of mercury in the Arctic atmosphere: Evidence for a spring-time net sink and summer-time source. Geophys. Res. Lett., 36(12), L12814. https://doi.org/10.1029/2009GL038345
  4. Kim, J. and Coauthors, 2010: Regional atmospheric emissions determined from measurements at Jeju Island, Korea: Halogenated compounds from China. Geophys. Res. Lett., 37(12), L12801.
  5. Li, S. and Coauthors, 2011: Emissions of Halogenated Compounds in East Asia Determined from Measurements at Jeju Island, Korea. Environ. Sci. Technol., 45(13), 5668-5675. https://doi.org/10.1021/es104124k
  6. Miller, J. B. and Coauthors, 2012: Linking emissions of fossil fuel $CO_2$ and other anthropogenic trace gases using atmospheric $^{14}CO_2$. J. Geophys. Res., 117(D8), D08302. https://doi.org/10.1029/2011JD017048
  7. Saito, T., Y. Yokouchi, A. Stohl, S. Taguchi, and H. Mukai, 2010: Large Emissions of Perfluorocarbons in East Asia Deduced from Continuous Atmospheric Measurements. Environ. Sci. Technol., 44(11), 4089- 4095. doi:10.1021/es1001488.
  8. Stohl, A., 1998: Computation, accuracy and applications of trajectories - A review and bibliography. Atmos. Environ., 32(6), 947-966. https://doi.org/10.1016/S1352-2310(97)00457-3
  9. Stohl, A., M. Hittenberger, and G. Wotawa, 1998: Validation of the Lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data. Atmos. Environ., 32(24), 4245-4264. https://doi.org/10.1016/S1352-2310(98)00184-8
  10. Stohl, A., C. Forster, A. Frank, P. Seibert, and G. Wotawa, 2005: Tech Note: The Lagrangian particle dispersion model FLEXPART version 6.2. Atmos. Chem. Phys., 5(9), 2461-2474. https://doi.org/10.5194/acp-5-2461-2005
  11. Stohl, A. and Coauthors, 2009: An analytical inversion method for determining regional and global emissions of greenhouse gases: Sensitivity studies and application to halocarbons. Atmos. Chem. Phys., 9(5), 1597-1620. https://doi.org/10.5194/acp-9-1597-2009
  12. Stohl, A. and Coauthors, 2010: Hydrochlorofluorocarbon and hydrofluorocarbon emissions in East Asia determined by inverse modeling. Atmos. Chem. Phys., 10(8), 3545-3560. doi:10.5194/acp-10-3545-2010.