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Korean Meteorological Society (한국기상학회)
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Designing of Conceptual Models on Typhoon and Changma Utilizing GK-2A Satellite Data

GK-2A 위성자료 활용을 위한 태풍 및 장마 개념모형의 도안

  • Moon, Suyeon (Department of Atmospheric Sciences, Pusan National University) ;
  • Ha, Kyung-Ja (Department of Atmospheric Sciences, Pusan National University) ;
  • Moon, Mincheol (Department of Atmospheric Sciences, Pusan National University) ;
  • Jhun, Jong-Ghap (School of Earth and Environmental Sciences, Seoul National University) ;
  • Moon, Ja-Yeon (International Pacific Research Center, University of Hawaii at Manoa)
  • 문수연 (부산대학교 지구환경시스템학부) ;
  • 하경자 (부산대학교 지구환경시스템학부) ;
  • 문민철 (부산대학교 지구환경시스템학부) ;
  • 전종갑 (서울대학교 지구환경과학부) ;
  • 문자연 (하와이대학교 국제태평양연구소)
  • Received : 2015.11.02
  • Accepted : 2016.03.30
  • Published : 2016.06.30
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Abstract

Conceptual models to analyze both typhoon and Changma using products extracted by the GEO-KOMPSAT-2A (GK-2A) are suggested in this study. The GK-2A which is scheduled to be launched in 2018 has a high resolution, 16 channels, and 52 products. This means GK-2A is expected to obtain high quality images and products, which can detect severe weather earlier than the Communications, Ocean and Meteorological Satellite (COMS). Since there are not enough conceptual models for typhoon and Changma using satellite images and products, our conceptual model can increase both the applicability of satellite data and the accuracy of analysis. In the conceptual model, typhoons are classified as three types by prevailing factors; 1) heavy-rainfall type, 2) wind type, and 3) complex type. For Changma, two types are divided by the characteristics; band type and heavy-rainfall type. Among the high resolution 52 products, each type of typhoon and Changma are selected. In addition, the numerical products and dynamic factors are considered in order to improve conceptual models.

Keywords

References

  1. Arpe, K., 1991: The hydrological cycle in the ECMWF short-range forecasts. Dyn. Atmos. Oceans, 16, 33-60. https://doi.org/10.1016/0377-0265(91)90011-4
  2. Atlas, D., and O. W. Thiele, 1982: Precipitation measurement from space: Workshop summary. Bull. Amer. Meteor. Soc., 63, 59-63. https://doi.org/10.1175/1520-0477-63.1.59
  3. Carranza, M., A. De Smet, and J. Gustafsson, 2010: Atmospheric motion vectors derived from MSG rapid scanning service data at EUMETSAT. Proc. 10th Int. Winds Workshop, Tokyo, EUM 56, 10 pp.
  4. Cha, E. J., 2006: The meaning of Changma. J. Hydro-Environ. Res., 39, 69-72.
  5. Choi, Y., K.-S. Yoon, and K.-J. Ha, 2013: Effects of asymmetric SST distribution on straight-moving typhoon Ewiniar (2006) and recurving typhoon Maemi (2003). Mon. Wea. Rev., 141, 3950-3967. https://doi.org/10.1175/MWR-D-12-00207.1
  6. Ebert, E. E., J. E. Janowiak, and C. Kidd, 2007: Comparison of near-real-time precipitation estimates from satellite observations and numerical models. Bull. Amer. Meteor. Soc., 88, 47-64. https://doi.org/10.1175/BAMS-88-1-47
  7. Forsythe, M., and R. Saunders, 2008: AMV monitoring: results from the 3rd NWP SAF analysis. Proc. 9th Int. Winds Workshop, Annapolis, MD, EUM 51, 8 pp.
  8. Ginsberg, J., M.-H. Mohebbi, R.-S. Patel, L. Brammer, M.-S. Smolinski, and L. Brilliant, 2009: Detecting influenza epidemics using search engine query data. Nature, 457, 1012-1014. https://doi.org/10.1038/nature07634
  9. Grassotti, C., and L. Garand, 1994: Classification-based rainfall estimation using satellite data and numerical forecast model fields. J. Appl. Meteor., 33, 159-178. https://doi.org/10.1175/1520-0450(1994)033<0159:CBREUS>2.0.CO;2
  10. Gruber, A., 1973: Estimating rainfall in region of active convection. J. Appl. Meteor., 12, 110-118. https://doi.org/10.1175/1520-0450(1973)012<0110:ERIROA>2.0.CO;2
  11. Ha, K.-J., and S.-S. Lee, 2007: On the interannual variability of the Bonin high associated with the East Asian summer monsoon rain. Clim. Dyman., 28, 67-83.
  12. Ha, K.-J., S.-K. Park, and K.Y. Kim, 2003: Interannual variability in summer precipitation around the Korean peninsula and its associated East Asian summer circulation. Atmosphere, 39, 575-586 (in Korean).
  13. Ha, K.-J., K.-S. Yun, J.-G. Jhun, and C.-K. Park, 2005: Definition of onset/retreat and intensity of Changma during the boreal summer monsoon season. Atmosphere, 41, 927-942 (in Korean).
  14. Harats, N., B. Ziv, Y. Yair, V. Kotroni, and U. Dayan, 2010: Lightning and rain dynamic indices as predictors for flash floods events in the Mediterranean. Adv. Geosci., 23, 57-64. https://doi.org/10.5194/adgeo-23-57-2010
  15. Ho, C.-H., and I.-S. Kang, 1988: The variability of precipitation in Korea. J. Korean Meteor. Soc., 24, 38-48 (in Korean).
  16. Jeong, H., D. S. Kim, and H. Lee, 2013: Google god knows everything. Science books, 400 pp.
  17. Kar, S. K., and K.-J. Ha, 2003: Characteristic differences of rainfall and cloud-to-ground lightning activity over South Korea during the summer monsoon season. Mon. Wea. Rev., 131, 2312-2323. https://doi.org/10.1175/1520-0493(2003)131<2312:CDORAC>2.0.CO;2
  18. Kim, G.-S., 1992: The Dictionary of Meteorology. Hyangmun-sa, 735 pp.
  19. Kim, S., J.-H. Park, M.-L. Ou, H. Cho, and E.-H. Sohn, 2012: Optimization of mesoscale atmospheric motion vector algorithm using Geostationary Meteorological Satellite Data. Atmosphere, 22, 1-12 (in Korean). https://doi.org/10.14191/Atmos.2012.22.1.001
  20. Lee, K.-J., K.-Y. Heo, A.-S. Suh, J.-S. Park, and K.-J. Ha, 2010: Application of images and data of satellite to a conceptual model for heavy-rainfall analysis. Atmosphere, 20, 131-151 (in Korean).
  21. Lee, M.-S., K.-L. Kim, A.-S. Suh, and H.-H. Lee, 1994: Estimation of precipitation using radar and satellite data. Asia-Pac. J. Atmos. Sci., 11, 583-595.
  22. Lee, T.-Y., and Y.-H. Kim, 2007: Heavy precipitation systems over the Korean peninsula and their classification. J. Korean Meteor. Soc., 43, 367-396 (in Korean).
  23. Lim, J. S., and S.-U. Park, 1991: The moisture transport and budget over Korea during the 1988 Changma peroid. Atmosphere, 27, 221-240 (in Korean).
  24. Ministry of Public Safety and Security, 2014: Current state of Natural Disaster Declarations. [Available online at http://www.mpss.go.kr/home/policy/statistics/statisticsData].
  25. Oh, H., K.-J. Ha, and J.-S. Sim, 2014: Analysis for onset of Changma using Ieodo ocean research station data. Atmosphere, 24, 189-196 (in Korean). https://doi.org/10.14191/Atmos.2014.24.2.189
  26. Park, D.-S., C.-H. Ho, J.-H. Kim, and H.-S. Kim, 2011: Strong landfall typhoons in Korea and Japan in a recent decade. J. Geophys. Res., 116, D07105, doi:10.1029/2010JD014801.
  27. Park, S.-U., I.-H. Yoon, and S.-K. Chung, 1986: Heat and moisture sources associated with the Changma front during the summer of 1978. Atmosphere, 10, 1-17 (in Korean).
  28. Rha, D. K., C. H. Kwak, M.S. Suh, and Y. Hong, 2005: Analysis of the characteristics of precipitation over South Korea in terms of the associated synoptic patterns: A 30 years climatology (1973-2002). J. Korean Ear. Sci. Soc., 26, 732-744 (in Korean).
  29. Ryu, G.-H., and B. J. Sohn, 2012: Rain-rate characteristics over the Korean peninsula and improvement of the Goddard profiling (GPROF) Database for TMI rainfall retrievals. J. Appl. Meteor. Climatol., 51, 786-798. https://doi.org/10.1175/JAMC-D-11-094.1
  30. Ryu, S.-B., 2001: The meaning and etymology of Changma. Atmosphere, 11, 6-12 (in Korean).
  31. Seo, K.-H., J.-H. Son, and J.-Y. Lee, 2011: A new look at Changma. Atmosphere, 21, 109-121 (in Korean).
  32. Song, H.-J., and B.-J. Sohn, 2015: Two heavy rainfall types over the Korean peninsula in the humid East Asian summer environment: A satellite observation study. Mon. Wea. Rev., 143, 363-382. https://doi.org/10.1175/MWR-D-14-00184.1
  33. Tammy, M. W., and B. P. David, 2006: A review of convection initiation and motivation for IHOP_2002. Mon. Wea. Rev., 134, 5-22. https://doi.org/10.1175/MWR3067.1
  34. Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on guage observations, satellite estimates, and numerical model outputs. J. Appl. Meteor., 33, 159-178.
  35. Yang, Y., H. Lin, Z. Guo, and J. Jiang, 2005: A meteorological conceptual modeling approach based on spatial data mining and knowledge discovery. Innov. Appl. Artif. Int., 3533, 490-499. https://doi.org/10.1007/11504894_67
  36. Yun, K.-S., J. C. L. Chan, and K.-J. Ha, 2012: Effects of SST magnitude and gradient on typhoon tracks around East Asia: A case study for typhoon Maemi (2003). Atmos. Res., 109, 36-51.

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