21st Conference on Weather Analysis and Forecasting/17th Conference on Numerical Weather Prediction


Qualitative Evaluation of the KMA Regional Model Mixing-Depth Prediction Using Wind-Profiler Signal-to-Noise-Ratio Data

Seung-Jae Lee, NOAA/NWS/NCEP/EMC, Camp Springs, MD; and H. D. Yoo and H. Kawai

In this study, mixed layer (ML) heights are estimated from the signal-to-noise ratio (SNR) data of wind profilers operated by the Korea Meteorological Administration (KMA) and Japan Meteorological Agency (JMA). The ML heights obtained are then utilized to qualitatively verify mixing depths predicted by a KMA regional numerical weather prediction model. The frequency of the wind profiler is 1.29 GHz (1.36 GHz for sites in Japan) and the temporal resolution of the SNR data is 10 minutes. In the vertical, the resolutions are 70 m for the sites in Korea and 300 m for Japan. Evaluation of model-predicted ML heights against 10-minute SNR data sufficiently reflected the model PBL scheme's well known features of having faster development with greater depth for an ML. It is proposed that the ML heights estimated from wind profiler SNR data can be employed as an auxiliary tool for evaluating model-predicted ML heights on an operational basis.

extended abstract  Extended Abstract (1.6M)

Session 14B, Data Assimilation II
Thursday, 4 August 2005, 3:30 PM-5:30 PM, Ambassador Ballroom

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