NDLI: Effect of length scale tuning of background Error in WRF-3DVAR system on assimilation of high-resolution surface data for heavy rainfall simulation

Content Provider	Springer Nature Link
Author	Ha, Ji Hyun Lee, Dong Kyou
Copyright Year	2012
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.
Starting Page	1142
Ending Page	1158
Page Count	17
File Format	PDF
ISSN	02561530
Journal	Advances in Atmospheric Sciences
Volume Number	29
Issue Number	6
e-ISSN	18619533
Language	English
Publisher	SP Science Press
Publisher Date	2012-10-19
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	WRF 3DVAR tuning surface data heavy rainfall Geophysics/Geodesy Meteorology/Climatology
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

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