Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Validation of OMI HCHO with EOF and SVD over Tropical Africa

EOF와 SVD을 이용한 아프리카 지역에서 관측된 OMI HCHO 자료의 검증

  • Kim, J.H. (Department of Atmospheric Science, Pusan National University) ;
  • Baek, K.H. (Department of Atmospheric Science, Pusan National University) ;
  • Kim, S.M. (Global Environment System Research Lab., National Institute of Meteorological Research)
  • Received : 2014.03.13
  • Accepted : 2014.06.12
  • Published : 2014.08.31
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Abstract

We have found an error in the operational OMI HCHO columns, and corrected it by applying a background parameterization derived on a 4th order polynomial fit to the time series of monthly average OMI HCHO data. The corrected OMI HCHO agrees with this understanding as well as with the other sensors measurements and has no unrealistic trends. A new scientific approach, statistical analyses with EOF and SVD, was adapted to reanalyze the consistency of the corrected OMI HCHO with other satellite measurements of HCHO, CO, $NO_2$, and fire counts over Africa. The EOF and SVD analyses with MOPITT CO, OMI $NO_2$, SCIAMAHCY, and OMI HCHO show the overall spatial and temporal pattern consistent with those of biomass burning over these regions. However, some discrepancies were observed from OMI HCHO over northern equatorial Africa during the northern biomass burning seasons: The maximum HCHO was found further downwind from where maximum fire counts occur and the minimum was found in January when biomass burning is strongest. The statistical analysis revealed that the influence of biogenic activity on HCHO wasn't strong enough to cause the discrepancies, but it is caused by the error in OMI HCHO from using the wrong Air Mass Factor (AMF) associated with biomass burning aerosol. If the error is properly taken into consideration, the biomass burning is the strongest source of HCHO seasonality over the regions. This study suggested that the statistical tools are a very efficient method for evaluating satellite data.

본 연구는 현재 NASA에서 제공되는 operational OMI HCHO 관측 값에서 에러를 발견하여, 월평균 HCHO 자료의 시계열에 4 차 다항식을 피팅함으로써 구한 배경 모수화(parameterization)값을 이용하여 OMI HCHO 자료의 보정을 수행하였다. 보정후의 OMI HCHO는 동태평양과 서태평양 지역에서 -1.48%, 0.65%/year 경향성을 보였으며 이 수치는 GOME(-0.99%, 1.1%/year)과 SCAIMACHY(-0.92%, 0.03%/year)의 경향성과 유사한 결과이며 적절하게 비정상적인 배경 HCHO 농도의 증가가 제거되었음을 나타낸다. 이 자료의 검증과 분석은 EOF와 SVD 통계적 분석 방법을 사용하여 아프리카 지역에서 다양한 위성 관측 값과의 (HCHO, CO, $NO_2$ 그리고 firecount) 시공간 변동성의 일치성을 비교 분석함으로써 수행되었다. 아프리카에서 MOPITT CO, OMI $NO_2$, SCIAMAHCY 그리고 OMI HCHO의 EOF와 SVD 분석 결과는 생태계화재(biomass burning)의 시공간 변동성 분포와 매우 높은 일치성을 보여준다. 그러나 OMI HCHO 관측 값은 화재가 가장 강하게 발생하는 지역의 풍하측에서 최대 값이 보이며, 화재 발생이 가장 높은 1월에 다소 낮은 HCHO 값이 보이는 등 시공간적으로 생태계 화제 분포와 차이를 보인다. 이것의 원인으로 우리는 이 지역의 열대우림의 식물활동(biogenic activity)영향으로는 설명할 수 없고, biomass burning 에어로졸에 의한 잘못된 AMF 계산이 OMI HCHO 산출에 사용됨으로써 발생한 오차라는 것을 밝혔다. AMF와 관련된 오차가 적절하게 보정된다면, 아프리카 지역의 HCHO 시공간 변동성은 생태계 화제의 변동성을 따를 것이라 예상된다. 따라서 본 연구는 통계적 기법이 위성 자료를 평가하는데 매우 효율적인 방법임을 제안한다.

Keywords

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