Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
권호 표지
DOI QR코드

DOI QR Code

Estimating Stability Indices from the MODIS Infrared Measurements over the Korean Peninsula

MODIS 적외 자료를 이용한 한반도 지역의 대기 안정도 지수 산출

  • Park, Sung-Hee (School of Earth and Environmental Sciences, Seoul National University) ;
  • Chung, Eui-Seok (School of Earth and Environmental Sciences, Seoul National University) ;
  • Koenig, Marianne (EUMETSAT, Darmstadt, Germany) ;
  • Sohn, B.J. (School of Earth and Environmental Sciences, Seoul National University)
  • 박성희 (서울대학교 지구환경과학부) ;
  • 정의석 (서울대학교 지구환경과학부) ;
  • ;
  • 손병주 (서울대학교 지구환경과학부)
  • Published : 2006.12.30
Download PDF
⟨ Previous Next ⟩

Abstract

An algorithm was developed to estimate stability indices (SI) over the Korean peninsula using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) infrared brightness temperatures (TBs). The SI is defined as the stability of the atmosphere in the hydrostatic equilibrium with respect to the vertical displacements and is used as an index for the potential severe storm development. Using atmosphere temperature and moisture profiles from Regional Data Assimilation and Prediction System (RDAPS) as initial guess data for a nonlinear physical relaxation method, K index (KI), KO Index (KO), lifted index (LI), and maximum buoyancy (MB) were estimated. A fast radiative transfer model, RTTOV-7, is utilized for reducing the computational burden related to the physical relaxation method. The estimated TBs from the radiative transfer simulation are in good agreement with observed MODIS TBs. To test usefulness for the short-term forecast of severe storms, the algorithm is applied to the rapidly developed convective storms. Compared with the SIs from the RDAPS forecasts and NASA products, the MODIS SI obtained in this research predicts the instability better over the pre-convection areas. Thus, it is expected that the nowcasting and short-term forecast can be improved by utilizing the algorithms developed in this study.

Terra 위성에 탑재된 MODIS 적외채널의 밝기온도 자료를 이용하여 한반도 지역에 대해 안정도 지수를 산출하는 알고리즘을 개발하였다. 안정도 지수는 정역학 평형 상태하에서 연직 변위에 대한 대기의 안정도로 정의되며, 대류성 폭풍우의 가능성을 나타내는 지수로 사용된다. RDAPS의 온도와 습도 연직분포 자료를 비선형 물리적 방법에 필요한 초기 추정 자료로 사용하여 KI, KO, LI, MB 지수를 산출하였고, RTTOV-7을 이용하여 물리적 복원 방법에 요구되는 긴 계산 시간을 단축하였다. 복사전달 모의를 통해 추정된 밝기온도는 관측값과 잘 일치하는 것으로 나타났다 단기 예보에 대한 유용성을 살펴보기 위해 안정도 지수 산출 알고리즘을 급격히 발달하는 대류성 폭풍우 사례에 적용하였다. RDAPS로부터 계산된 안정도 지수와 NASA에서 산출한 안정도_ 지수에 비해 대류운의 발달이 예상되는 지역을 보다 정확하게 예측하는 것으로 나타났다. 따라서 본 연구에서 개발된 알고리즘을 사용하여 순간 예보와 단기 예보를 향상시킬 수 있을 것으로 판단된다.

Keywords

References

  1. 신도식, 박윤호, 2004. 장마 후 집중호우 메커니즘 분석과 예보 가이던스 개발. 2004년도 가을 학술대회 초록, 한국기상학회, 326-327
  2. Dostalek, J. F. and T. J. Schmit, 2001. Total precipitable water measurements from GOES sounder derived product imagery. Wea. Forecasting, 16: 573-587 https://doi.org/10.1175/1520-0434(2001)016<0573:TPWMFG>2.0.CO;2
  3. Hayden, C. M., 1988. GOES-VAS simultaneous temperature-moisture retrieval algorithm. J. Appl. Meteor., 27: 705-733 https://doi.org/10.1175/1520-0450(1988)027<0705:GVSTMR>2.0.CO;2
  4. Kitzmiller, D. H. and W. E. McGovern, 1989. VAS retrievals as a source of information for convective weather forecasts: An objective assessment and comparison with other sources of upper-air observations. Mon. Wea. Rev., 117: 2095-2109 https://doi.org/10.1175/1520-0493(1989)117<2095:VRAASO>2.0.CO;2
  5. Koenig, M., 2002. Atmospheric instability parameters derived from MSG SEVIRI observations. EUMETSAT Tech. Memo., 9: 27
  6. Lee, T.-H., D. Chesters, and A. Mostek, 1983. The impact of conventional surface data upon VAS regression retrievals in the lower tropopause. J. Climate Appl. Meteor., 22: 1853-1874 https://doi.org/10.1175/1520-0450(1983)022<1853:TIOCSD>2.0.CO;2
  7. Ma, X. L., T. J. Schmit, and W. L. Smith, 1999. A nonlinear physical retrieval altorithm-its application to the GOES-8/9 sounder. J. Appl. Meteor., 38: 501-513 https://doi.org/10.1175/1520-0450(1999)038<0501:ANPRAI>2.0.CO;2
  8. McClatchey, R. A., R. W. Fenn, J. E. A. Selby, F. E. Volz, and J. S. Garing, 1972. Optical properties of the atmosphere. 3rd ed. AFCRL-72-0497, AD 753075. Air Force Geophysical Laboratory, L.G. Hanscom Field, Massachusetts, 108 pp
  9. Menzel, W. P., F. C. Holt, T. J. Schmit, R. M. Aune, A. J. Schreiner, G. S. Wade, and D. G. Gray, 1998. Application of GOES-8/9 soundings to weather forecasting and nowcasting. Bull. Amer. Meteor. Soc., 79: 2059-2078 https://doi.org/10.1175/1520-0477(1998)079<2059:AOGSTW>2.0.CO;2
  10. Rao, P. A. and H. E. Fuelberg, 1997. Diagnosing convective instability from GOES-8 radiances. J. Appl. Meteor., 36: 350-364 https://doi.org/10.1175/1520-0450(1997)036<0350:DCIFGR>2.0.CO;2
  11. Saunders, R., M. Matricard, and P. Brunel, 1999. An improved fast radiative transfer model for assimilation of satellite radiance observations. Q. J. R. Met. Soc., 125: 1407-1425 https://doi.org/10.1256/smsqj.55614
  12. Seemann, S. W, J. Li, W. P. Menzel, and L. E. Gumley, 2003. Operational retrieval of atmospheric temperature, moisture, and ozone from MODIS infrared radiances. J. Appl. Meteor., 42: 1072-1091 https://doi.org/10.1175/1520-0450(2003)042<1072:OROATM>2.0.CO;2
  13. Smith, W. L., H. M. Woolf, and A. J. Schreiner, 1985. Simultaneous retrieval of surface atmospheric parameters: A physical and analytically direct approach. Advances in Remote Sensing Retrieval Methods, A. Deepak, H. E. Fleming, and M. T. Chahine, Eds., A. Deepak publishing, 221-232