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Korean Meteorological Society (한국기상학회)
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A Study on the Assimilation of High-Resolution Microwave Humidity Sounder Data for Convective Scale Model at KMA

국지예보모델에서 고해상도 마이크로파 위성자료(MHS) 동화에 관한 연구

  • Kim, Hyeyoung (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Lee, Eunhee (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Lee, Seung-Woo (Numerical Modeling Center, Korea Meteorological Administration) ;
  • Lee, Yong Hee (Numerical Modeling Center, Korea Meteorological Administration)
  • 김혜영 (기상청 수치모델링센터) ;
  • 이은희 (기상청 수치모델링센터) ;
  • 이승우 (기상청 수치모델링센터) ;
  • 이용희 (기상청 수치모델링센터)
  • Received : 2018.03.16
  • Accepted : 2018.05.26
  • Published : 2018.06.30
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Abstract

In order to assimilate MHS satellite data into the convective scale model at KMA, ATOVS data are reprocessed to utilize the original high-resolution data. And then to improve the preprocessing experiments for cloud detection were performed and optimized to convective-scale model. The experiment which is land scattering index technique added to Observational Processing System to remove contaminated data showed the best result. The analysis fields with assimilation of MHS are verified against with ECMWF analysis fields and fit to other observations including Sonde, which shows improved results on relative humidity fields at sensitive level (850-300 hPa). As the relative humidity of upper troposphere increases, the bias and RMSE of geopotential height are decreased. This improved initial field has a very positive effect on the forecast performance of the model. According to improvement of model field, the Equitable Threat Score (ETS) of precipitation prediction of $1{\sim}20mm\;hr^{-1}$ was increased and this impact was maintained for 27 hours during experiment periods.

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References

  1. Atkinson, N., 2017: AAPP User Guide. NWPSAF-MFUD-036, 17 pp.
  2. Bauer, P., A. J. Geer, P. Lopez, and D. Salmond, 2010: Direct 4D-Var assimilation of all-sky radiances: Part I. Implementation. Quart. J. Roy. Meteor. Soc., 136, 1868-1885, doi:10.1002/qj.659.
  3. Bennartz, R., A. Thoss, A. Dybbroe, and D. B. Michelson, 2002: Precipitation analysis using the advanced microwave sounding unit in support of nowcasting applications. Meteorol. Appl., 9, 177-189. https://doi.org/10.1017/S1350482702002037
  4. Chang, D. E., T. K. Jang, Y.-H. Lee, and M.-J. Kim, 2002: The effect of assimilating ATOVS soundings on short-range forecast. Atmosphere, 12, 40-43.
  5. Eyre, J. R., 1989: Inversion of cloudy satellite sounding radiances by nonlinear optimal estimation. II: application to TOVS data. Quart. J. Roy. Meteor. Soc., 115, 1027-1037. https://doi.org/10.1002/qj.49711548903
  6. Geer, A. J., and Coauthors, 2017: All-sky satellite data assimilation at operational weather forecasting centres. Quart. J. Roy. Meteor. Soc., doi:10.1002/qj.3202.
  7. Geer, A. J., J. F. Baordo, N. Bormann, and S. English, 2014: All-sky assimilation of microwave humidity sounders. ECMWF Tech. Memo., 741 pp.
  8. Harris, B. A., and G. Kelly, 2001: A satellite radiance-bias correction scheme for data assimilation. Quart. J. Roy. Meteor. Soc., 127, 1453-1468. https://doi.org/10.1002/qj.49712757418
  9. Hilton F., N. C. Atkinson, S. J. English, and J. R. Eyre, 2009: Assimilation of IASI at the Met Office and assessment of its impact through observing system experiments. Quart. J. Roy. Meteor. Soc., 135, 495-505. https://doi.org/10.1002/qj.379
  10. Hong G., G. Heygster, J. Notholt, F. Weng, and Q. Liu, 2010: Simulations of microwave brightness temperatures at AMSU-B frequencies over a 3D convective cloud system. Int. J. Remote Sens., 31, 1781-1800, doi:10.1080/01431160902926640.
  11. Joo, S. W., E. J. Lee, and H. C. Shin, 2005: Development on the direct assimilation technique of ATOVS radiance in 3DVAR of the KMA global model. KMATN-2005-04, 48 pp (in Korean).
  12. Jung, J. H., and M. S. Seo, 2005: Characteristics and Types of the Diurnal Variation of Hourly Precipitation during Rainy Season over South Korea. Asia-Pac J. Atmos. Sci., 41, 533-546 (in Korean with English abstract).
  13. Karbou, F., E. Gérard, and F. Rabier, 2010: Global 4DVAR assimilation and forecast experiments using AMSU observations over land. Part I: Impacts of various land surface emissivity parameterizations. Wea. Forecasting, 25, 5-19, doi:10.1175/2009WAF2222243.1.
  14. Kim, S.-M., and H. M. Kim, 2017: Adjoint-based observation impact of Advanced Microwave Sounding Unit-A (AMSU-A) on the short-range forecast in East Asia. Atmosphere, 27, 93-104, doi:10.14191/Atmos.2017.27.1.093 (in Korean with English abstract).
  15. Lee, E. H., Y. S. Kim, H. C. Shin, and M. S. Lee, 2009: MetOp IASI data assimilation in Unified Model in KMA. Proc. Fall Meeting KMS, Daegu, Korea, Korean Meteorological Society, 300-301 (in Korean).
  16. Lee, Y. H., H. Y. Lee, J. Lee, K. H. Lee, and D. J. Kim, 2015: Evaluating the precipitation forecast by extension of variable grid area in KMA convective scale model(LDAPS). Proc. Spring Meeting KMS, Seoul, Korea, Korean Meteorological Society, 5-6 (in Korean).
  17. Lorenc, A. C., and F. Rawlins, 2005: Why does 4D-Var beat 3D-Var?. Quart. J. Roy. Meteor. Soc., 131, 3247-3257. https://doi.org/10.1256/qj.05.85
  18. Mesinger, F., and T. L. Black, 1992: On the impact on forecast accuracy of the step-mountain(eta) vs. sigma coordinate. Meteor. Atmos. Phys., 50, 47-60. https://doi.org/10.1007/BF01025504
  19. Muller, B. M., H. E. Fuelberg, and X. Xiang, 1994: Simulations of the effects of water vapor, cloud liquid water, and ice on AMSU moisture channel brightness temperatures. J. Appl. Meteorol., 33, 1133-1154. https://doi.org/10.1175/1520-0450(1994)033<1133:SOTEOW>2.0.CO;2
  20. Qin, Z. K., and X. L. Zou, 2016: Development and initial assessment of a new land index for microwave humidity sounder cloud detection. J. Meteor. Res., 30, 12-37, doi:10.1007/s13351-016-5076-4.
  21. Saunders, R., M. Matricardi, and A. Geer, 2010: RTTOV-9 Users Guide. NWPSAF-MO-UD-016, Exeter, UK, 57 pp.
  22. Sohn, B. J., G.-H. Ryu, H.-J. Song, and M.-L. Ou, 2013: Characteristic features of warm-type rain producing heavy rainfall over the Korean peninsula inferred from TRMM measurements. Mon. Wea. Rev., 141, 3873-3888, doi:10.1175/MWR-D-13-00075.1.
  23. 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, doi:10.1175/MWR-D-14-00184.1.
  24. Weston, P., 2014: Assimilating IASI data into the UKV. Met Office SA Technical Memo., 15, 30 pp.
  25. Zelinka, M. D., and D. L. Hartmann, 2009: Response of humidity and clouds to tropical deep convection. J. Climate, 22, 2389-2404. https://doi.org/10.1175/2008JCLI2452.1
  26. Zou, X. L., Z. K. Qin, and F. Z. Weng, 2013: Improved quantitative precipitation forecasts by MHS radiance data assimilation with a newly added cloud detection algorithm. Mon. Wea. Rev., 141, 3203-3221, doi:10.1175/MWR-D-13-00009.1.