한국지구과학회지 (Journal of the Korean earth science society)

  • 제35권1호
  • /
  • Pages.19-28
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  • 2014
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  • 1225-6692(pISSN)
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  • 2287-4518(eISSN)
한국지구과학회 (The Korean Earth Science Society)
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두 복사전달모델 RTTOV와 CRTM으로부터 산출된 밝기온도와 관측된 밝기온도의 비교

A Comparison of Observed and Simulated Brightness Temperatures from Two Radiative Transfer Models of RTTOV and CRTM

  • 김주혜 (한국형수치예보모델개발사업단) ;
  • 강전호 (한국형수치예보모델개발사업단) ;
  • 이시혜 (한국형수치예보모델개발사업단)
  • Kim, Ju-Hye (Korea Institute of Atmospheric Prediction Systems) ;
  • Kang, Jeon-Ho (Korea Institute of Atmospheric Prediction Systems) ;
  • Lee, Sihye (Korea Institute of Atmospheric Prediction Systems)
  • 투고 : 2013.11.11
  • 심사 : 2014.01.19
  • 발행 : 2014.02.28
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초록

RTTOV와 CRTM은 복사관측자료에 대한 관측연산자로 수치예보에 활용되고 있는 빠른 속도의 복사전달모델이다. 본 연구에서는 두 모델의 기본구조 및 입력자료를 비교했다. 또한, 다양한 파장대를 가진 AMSU-A 마이크로파 센서에 대해 구름에 대한 정보를 포함할 때와 포함하지 않을 때 두 모델로부터 계산된 밝기온도와 관측된 밝기온도를 해양에 대해 비교했다. AMSU-A의 탐측채널(5-14)에 대해서는 두 모델로부터 계산된 밝기온도 값에 큰 차이가 존재하지 않았으나, 대기의 창 채널 및 지표근처의 탐측채널에서는 RTTOV로부터 계산된 밝기온도 값이 관측과 더 가까워 CRTM에 비해 상대적으로 작은 초기추정오차를 보였다. 한편 UM으로부터 제공된 구름물과 얼음의 정보를 추가적으로 활용하였을 때 두 모델로부터 계산된 밝기온도와 관측된 밝기온도의 차이가 감소함을 확인할 수 있었고, 특히 CRTM의 31.4 GHz와 89 GHz 채널에서 모의된 밝기온도와 관측된 밝기온도의 차이가 크게 감소했다.

The radiative transfer for TIROS operational vertical sounder (RTTOV) and the community radiative transfer model (CRTM) are two fast radiative transfer models (RTM) that are used as observation operators in numerical weather prediction (NWP) systems. This study compares the basic structure and input data of the two models. With data from Advanced Microwave Sounding Unit-A (AMSU-A), which has channels of various frequencies, observed brightness temperature ($T_B$) and simulated $T_B$s from the two models are compared over the ocean surface in two cases-one where cloud information is included and the other without it. Regarding AMSU-A sounding channels (5-14), the two models produce no large significant differences in their calculated $T_B$, but RTTOV produces smaller first guess (FG) departures (i.e., better results) in window and near-surface sounding channels than does CRTM. When adding cloud water and ice particles from Unified Model (UM), the $T_B$ bias between observations and simulations are reduced in both models and the bias at 31.4 and 89 GHz is substantially decreased in CRTM compared to those of RTTOV.

키워드

참고문헌

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