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Korean Meteorological Society (한국기상학회)
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Investigation of Analysis Effects of ASCAT Data Assimilation within KIAPS-LETKF System

앙상블 자료동화 시스템에서 ASCAT 해상풍 자료동화가 분석장에 미치는 효과 분석

  • Jo, Youngsoon (Korea Institute of Atmospheric Prediction Systems) ;
  • Lim, Sujeong (Korea Institute of Atmospheric Prediction Systems) ;
  • Kwon, In-Hyuk (Korea Institute of Atmospheric Prediction Systems) ;
  • Han, Hyun-Jun (Korea Institute of Atmospheric Prediction Systems)
  • 조영순 ((재) 한국형수치예보모델개발사업단) ;
  • 임수정 ((재) 한국형수치예보모델개발사업단) ;
  • 권인혁 ((재) 한국형수치예보모델개발사업단) ;
  • 한현준 ((재) 한국형수치예보모델개발사업단)
  • Received : 2018.04.06
  • Accepted : 2018.07.10
  • Published : 2018.09.30
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Abstract

The high-resolution ocean surface wind vector produced by scatterometer was assimilated within the Local Ensemble Transform Kalman Filter (LETKF) in Korea Institute of Atmospheric Prediction Systems (KIAPS). The Advanced Scatterometer (ASCAT) on Metop-A/B wind data was processed in the KIAPS Package for Observation Processing (KPOP), and a module capable of processing surface wind observation was implemented in the LETKF system. The LETKF data assimilation cycle for evaluating the performance improvement due to ASCAT observation was carried out for approximately 20 days from June through July 2017 when Typhoon Nepartak was present. As a result, we have found that the performance of ASCAT wind vector has a clear and beneficial effect on the data assimilation cycle. It has reduced analysis errors of wind, temperature, and humidity, as well as analysis errors of lower troposphere wind. Furthermore, by the assimilation of the ASCAT wind observation, the initial condition of the model described the typhoon structure more accurately and improved the typhoon track prediction skill. Therefore, we can expect the analysis field of LETKF will be improved if the Scatterometer wind observation is added.

Keywords

References

  1. de Chiara, G., P. Janssen, H. Hersbach, and N. Bormann, 2012: Assimilation of scatterometer winds at ECMWF. IWW11, Shinfield Park, Reading, UK, ECMWF, 1-14.
  2. Figa-Saldana, J., J. J. W. Wilson, E. Attema, R. Gelsthorpe, M R Drinkwater, and A. Stoffelen, 2002: The advanced scatterometer (ASCAT) on the meteorological operational (MetOp) platform: A follow on for European wind scatterometers. Can. J. Remote Sensing, 28, 404-412. https://doi.org/10.5589/m02-035
  3. Hong, S.-Y., and Coauthors, 2018: The Korean Integrated Model (KIM) System for Global Weather Forecasting. Asia-Pac. J. Atmos. Sci., 54, 267-292, doi:10.1007/s13143-018-0028-9.
  4. Hunt, B. R., E. Kostelich, and I. Szunyogh, 2007: Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D, 230, 112-126, doi:10.1016/j.physd.2006.11.008.
  5. Jo, Y., J.-S. Kang, and H. Kwon, 2015: Optimization of Vertical Localization Scale for GPS-RO Data Assimilation within KIAPS-LETKF System. Atmosphere, 25, 529-541, doi:10.14191/Atmos.2015.25.3.529 (in Korean with English abstract).
  6. Kang, J.-H., and Coauthors, 2018: Development of an observation processing package for data assimilation in KIAPS. Asia-Pac. J. Atmos. Sci., 54, 303-318, doi:10.1007/s13143-018-0030-2.
  7. Klaes, K., and Coauthors, 2007: An introduction to the EUMETSAT Polar System. Bull. Amer. Meteor. Soc., 88, 1085-1096. https://doi.org/10.1175/BAMS-88-7-1085
  8. Kleist, D. T., and K. Ide, 2015: An OSSE-based evaluation of hybrid variational-ensemble data assimilation for the NCEP GFS. Part I: System description and 3D-hybrid results. Mon. Wea. Rev., 143, 433-451, doi:10.1175/MWR-D-13-00351.1.
  9. OSI SAF, 2016: ASCAT Wind Product User Manual. SAF/OSI/CDOP/KNMI/TEC/MA/126, Version 1.14, 23 pp.
  10. Shin, S., J.-S. Kang, and Y. Jo, 2016: The local ensemble transform Kalman filter (LETKF) with a global NWP model on the cubed sphere. Pure Appl. Geophys., 173, 2555-2570 doi:10.1007/s00024-016-1269-0.
  11. Stoffelen, A., and D. Anderson, 1997: Ambiguity removal and assimilation of scatterometer data. Quart. J. Roy. Meteor. Soc., 123, 491-518. https://doi.org/10.1002/qj.49712353812
  12. Szunyogh, I., E. J. Kostelich, G. Gyarmati, E. Kalnay, B. R. Hunt, E. Ott, E. Satterfield, and J. A. Yorke, 2008: A Local Ensemble Transform Kalman Filter data assimilation system for the NCEP global model. Tellus A, 60, 113-130. https://doi.org/10.1111/j.1600-0870.2007.00274.x
  13. Verspeek, J., A. Stoffelen, M. Portabella, H. Bonekamp, C. Anderson, and J. F. Saldana, 2010: Validation and Calibration of ASCAT Using CMOD5.n. IEEE Trans. Geosci. Remote Sens., 48, 386-395, doi:10.1109/TGRS.2009.2027896.
  14. Yu, Y., W. Zhang, Z. Wu, X. Yang, X. Cao, and M. Zhu, 2015: Assimilation of HY-2A scatterometer sea surface wind data in a 3DVAR data assimilation system-A case study of Typhoon Bolaven. Front. Earth Sci., 9, 192-201, doi:10.1007/s11707-014-0461-8.