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1. Department of Atmospheric Sciences, Yonsei University

Downscaled current climate of the Asian Monsoon using a Regional Spectral Model. E- Hyung Park 1 , Song-You Hong 1 and Hyun- Suk Kang 2. 1. Department of Atmospheric Sciences, Yonsei University 2. Meteorological Research Institute, Korea. Model domain & Model Setup.

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1. Department of Atmospheric Sciences, Yonsei University

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  1. Downscaled current climate of the Asian Monsoon using a Regional Spectral Model E-Hyung Park1, Song-You Hong1 and Hyun-Suk Kang2 1. Department of Atmospheric Sciences, Yonsei University 2. Meteorological Research Institute, Korea

  2. Model domain & Model Setup Spectral Tendency Damping (STD) Analysis Area 1Jul 1988~31Dec 1998 (10-yr)

  3. Precipitation (mm) b) RSM JJA d) RSM-CMAP JJA a) CMAP JJA f) RSM DJF g) RSM-CMAP DJF e) CMAP DJF

  4. 10-yr Summer mean difference b) 200 hPa Zonal Wind JJA a) 500 hPa GPH JJA c) 500 hPa Temp. JJA d) 850 hPa Wind & RH JJA

  5. Vertical profile for Temperature & RH b) Relative Humidity (%) a) Temperature (K)

  6. Sensible Heat Flux & Latent Heat Flux (W/m2) 10 10 10 a) Whole domain JJA 9 9 9 8 8 8 7 7 7 6 6 6 6.24 Precipitation (mm/d) 5 5 5 Flux (W/m**2) 5.37 4 4 4 5.50 3 3 3 ■ SHFL■LHFL ■ SHFL+LHFL 8.43 b) Land JJA c) Ocean JJA 7.93 Precipitation (mm/d) Flux (W/m**2) Precipitation (mm/d) Flux (W/m**2) 5.47 5.49 5.34 3.97 CMAP Precipitation CMAP Precipitation

  7. Skill Score

  8. EOF Analysis for Precipitation 20.16% 17.32% a) CMAP 1st EOF b) RSM 1st EOF c) 1st TC CMAP RSM Corr : 0.15

  9. EOF Analysis for 2m Temperature 35.07% 30.53% a) RA2 1st EOF b) RSM 1st EOF c) 1st TC RA2 RSM Corr : 0.91

  10. EOF Analysis for 200 hPa Zonal Wind 48.21 % 47.64 % a) RA2 1st EOF b) RSM 1st EOF c) 1st TC RA2 RSM Corr : 0.99

  11. Spectral Tendency Damping Experiment

  12. Spectral Tendency Damping • Scale Selective Bias Correction method is developed to reduce the large-scale error in the regional downscaling analysis. • Spectral tendency damping suppresses large-scale errors within the regional domain and nudges the regional field toward large-scale field from the driving global coarse analysis. • Reducing the tendency of zonal and meridional wind over the scale of 1000 km • Zeroing the area-mean perturbation of temperature and humidity • Reference • Kanamaru, H. and M. Kanamitsu, 2007: Scale-Selective Bias Correction in a Downscaling of Global Analysis using a Regional Model. Monthly Weather Review, 135 (2), 334–350.

  13. Experiment Design Exp. I : CPS experiment SAS, RAS and CCM SAS, RAS and CCM + STDAMP Exp. II : LSM experiment OSULSM and NOALSM OSULSM and NOALSM+ STDAMP Exp III. PBL experiment MRFPBL and YSUPBL MRFPBL and YSUPBL + STDAMP 1Jun~31Aug 1998 (3 month)

  14. Exp. I : CPS experiment b) SAS a) GPCP d) CCM c) RAS

  15. Exp. I : CPS experiment b) SAS_STD a) GPCP d) CCM_STD c) RAS_STD

  16. Exp. I : Skill Score for Precipitation

  17. Exp. II : LSM experiment b) OSU c) NOA a) GPCP d) OSU_STD e) NOA_STD

  18. Exp. II : Precipitaion Diff. & Skill Score a) OSU-NOA b) OSU_STD-NOA_STD

  19. Exp. III : PBL experiment c) YSU a) GPCP b) MRF d) MRF_STD e) YSU_STD

  20. Exp. III : Precipitaion Diff. & Skill Score a) MRF -YSU b) MRF_STD –YSU_STD

  21. Summary • The 10-year-long simulations were conducted starting from 1988 to 1998. • The downscaled 10-year summer regional climate captures well the current climate for seasonal, intra-seasonal feature • However, the RSM underestimate the precipitation over the ocean • The Spectral Tendency Damping scheme significantly reduced the temperature and wind bias • The Spectral Tendency Damping effect more predominates in LSM and PBL than CPSs •  So, we have to carefully use the Spectral Tendency Damping scheme.

  22. Thank You !

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