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A Study on Improvement of High Resolution Regional NWP by Applying Ocean Mixed Layer Model

해양혼합층 모델 적용을 통한 고해상도 지역예측모델 성능개선에 대한 연구

  • Min, Jae-Sik (Weather Information Service Engine Institute, Hankuk University of Foreign Studies) ;
  • Jee, Joon-Bum (Weather Information Service Engine Institute, Hankuk University of Foreign Studies) ;
  • Jang, Min (Weather Information Service Engine Institute, Hankuk University of Foreign Studies) ;
  • Park, Jeong-Gyun (Weather Information Service Engine Institute, Hankuk University of Foreign Studies)
  • 민재식 (한국외국어대학교 차세대도시농림융합기상사업단) ;
  • 지준범 (한국외국어대학교 차세대도시농림융합기상사업단) ;
  • 장민 (한국외국어대학교 차세대도시농림융합기상사업단) ;
  • 박정균 (한국외국어대학교 차세대도시농림융합기상사업단)
  • Received : 2017.05.19
  • Accepted : 2017.07.25
  • Published : 2017.09.30

Abstract

Ocean mixed layer (OML) depth affects diurnal cycle of sea surface temperature (SST) induced by change of solar radiation absorption and heat budget in ocean. The diurnal SST variation can lead to convection over the ocean, which can impact on localized precipitation both over coastal and inland. In this study, we investigate the OML characteristics affecting the diurnal cycle of SST for the Korean Peninsula and surrounding areas. To analyze OML characteristics, HYCOM oceanic mixed layer depth (MLD) and wind field at 10 m from ERA-interim during 2008~2016 are used. In the winter, MLD is deeply formed when the strong wind field is located on perpendicular to continental slope over deep seafloor areas. Besides, cooling SST-induced vertical mixing in OML is reinforced by dry cold air originated from Siberia. The OML in summer is shallowly distributed about 20 m. In order to estimate the impact of OML model in high resolution NWP model, four experimental simulations are performed. At this time, the prognostic scheme of skin SST is applied in NWP to simulate diurnal SST. The simulation results show that CNTL (off-OML) overestimates diurnal cycle of SST, while EXPs (on-OML) indicate similar results to observations. The prediction performance for precipitation of EXPs shows improvement compared with CNTL over coastal as well as inland. This results suggest that the application of the OML model in summer season can contribute to improving the prediction for performance of SST and precipitation over coastal area and inland.

Keywords

References

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