Observation and Numerical Simulations with Radar and Surface Data Assimilation for Heavy Rainfall over Central Korea |
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Authors: | Ji-Hyun HA Hyung-Woo KIM and Dong-Kyou LEE |
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Affiliation: | Atmospheric Sciences Program, School of Earth and Environmental Sciences, Seoul National University, Seoul 151--747, Korea,Atmospheric Sciences Program, School of Earth and Environmental Sciences, Seoul National University, Seoul 151--747, Korea and Atmospheric Sciences Program, School of Earth and Environmental Sciences, Seoul National University, Seoul 151--747, Korea |
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Abstract: | This study investigated the impact of multiple-Doppler radar data and
surface data assimilation on forecasts of heavy rainfall over the central
Korean Peninsula; the Weather Research and Forecasting (WRF) model and its
three-dimensional variational data assimilation system (3DVAR) were used for
this purpose. During data assimilation, the WRF 3DVAR cycling mode with
incremental analysis updates (IAU) was used. A maximum rainfall of 335.0 mm
occurred during a 12-h period from 2100 UTC 11 July 2006 to 0900 UTC 12 July
2006. Doppler radar data showed that the heavy rainfall was due to the
back-building formation of mesoscale convective systems (MCSs). New
convective cells were continuously formed in the upstream region, which was
characterized by a strong southwesterly low-level jet (LLJ). The LLJ also
facilitated strong convergence due to horizontal wind shear, which resulted
in maintenance of the storms. The assimilation of both multiple-Doppler
radar and surface data improved the accuracy of precipitation forecasts and
had a more positive impact on quantitative forecasting (QPF) than the
assimilation of either radar data or surface data only. The back-building
characteristic was successfully forecasted when the multiple-Doppler radar
data and surface data were assimilated. In data assimilation experiments,
the radar data helped forecast the development of convective storms
responsible for heavy rainfall, and the surface data contributed to the
occurrence of intensified low-level winds. The surface data played a
significant role in enhancing the thermal gradient and modulating the
planetary boundary layer of the model, which resulted in favorable
conditions for convection. |
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Keywords: | radar and surface data data assimilation mesoscale convective system heavy rainfall |
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