Effect of Length Scale Tuning of Background Error in WRF-3DVAR System on Assimilation of High-Resolution
Surface Data for Heavy Rainfall Simulation |
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Authors: | Ji-Hyun HA and Dong-Kyou LEE |
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Institution: | 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 |
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Abstract: | We investigated the impact of tuning the length scale of the background
error covariance in the Weather Research and Forecasting (WRF)
three-dimensional variational assimilation (3DVAR) system. In particular, we
studied the effect of this parameter on the assimilation of high-resolution
surface data for heavy rainfall forecasts associated with mesoscale
convective systems over the Korean Peninsula. In the assimilation of
high-resolution surface data, the National Meteorological Center method
tended to exaggerate the length scale that determined the shape and extent
to which observed information spreads out. In this study, we used the
difference between observation and background data to tune the length scale
in the assimilation of high-resolution surface data. The resulting
assimilation clearly showed that the analysis with the tuned length scale
was able to reproduce the small-scale features of the ideal field
effectively. We also investigated the effect of a double-iteration method
with two different length scales, representing large and small-length scales
in the WRF-3DVAR. This method reflected the large and small-scale features
of observed information in the model fields. The quantitative accuracy of
the precipitation forecast using this double iteration with two different
length scales for heavy rainfall was high; results were in good agreement
with observations in terms of the maximum rainfall amount and equitable
threat scores. The improved forecast in the experiment resulted from the
development of well-identified mesoscale convective systems by intensified
low-level winds and their consequent convergence near the rainfall area. |
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Keywords: | WRF 3DVAR tuning surface data heavy rainfall |
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