Radar Data Assimilation for the Simulation of Mesoscale Convective Systems |
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| Authors: | Jo-Han LEE Dong-Kyou LEE Hyun-Ha LEE Yonghan CHOI and Hyung-Woo KIM |
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| Institution: | School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea,School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea,School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea,School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea,School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea |
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| Abstract: | A heavy rainfall case related to Mesoscale Convective Systems (MCSs) over
the Korean Peninsula was selected to investigate the impact of radar data
assimilation on a heavy rainfall forecast. The Weather Research and
Forecasting (WRF) three-dimensional variational (3DVAR) data assimilation
system with tuning of the length scale of the background error covariance
and observation error parameters was used to assimilate radar radial
velocity and reflectivity data. The radar data used in the assimilation
experiments were preprocessed using quality-control procedures and
interpolated/thinned into Cartesian coordinates by the SPRINT/CEDRIC
packages. Sensitivity experiments were carried out in order to determine the
optimal values of the assimilation window length and the update frequency
used for the rapid update cycle and incremental analysis update experiments.
The assimilation of radar data has a positive influence on the heavy
rainfall forecast. Quantitative features of the heavy rainfall case, such as
the maximum rainfall amount and Root Mean Squared Differences (RMSDs) of
zonal/meridional wind components, were improved by tuning of the length
scale and observation error parameters. Qualitative features of the case,
such as the maximum rainfall position and time series of hourly rainfall,
were enhanced by an incremental analysis update technique. The positive
effects of the radar data assimilation and the tuning of the length scale
and observation error parameters were clearly shown by the 3DVAR increment. |
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| Keywords: | WRF 3DVAR 3DVAR cycling initialization tuning heavy rainfall radar data |
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