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| Content Provider | Springer Nature Link |
|---|---|
| Author | Lee, Dong Kyou Eom, Dae Yong Kim, Joo Wan Lee, Jae Bok |
| Copyright Year | 2010 |
| Abstract | The WRF-based real-time forecast system (http://jhwc.snu.ac.kr/weather) of the Joint Center for High-impact Weather and Climate Research (JHWC) has been in operation since November 2006; this system has three nested model domains using GFS (Global Forecast System) data for its initial and boundary conditions. In this study, we evaluate the improvement in daily and hourly weather prediction, particularly the prediction of summer rainfall over the Korean Peninsula, in the JHWC WRF (Weather Research and Forecasting) model system by 3DVAR (three-Dimensional Variational) data assimilation using the data obtained from KEOP (Korea Enhanced Observation Program). KEOP was conducted during the period June 15 to July 15, 2007, and the data obtained included GTS (Global Telecommunication System) upper-air sounding, AWS (Automatic Weather System), wind profiler, and radar observation data. Rainfall prediction and its characteristics should be verified by using the precipitation observation and the difference field of each experiment. High-resolution (3 km in domain 3) summer rainfall prediction over the Korean peninsula is substantially influenced by improved synoptic-scale prediction in domains 1 (27 km) and 2 (9 km), in particular by data assimilation using the sounding and wind profiler data. The rainfall prediction in domain 3 was further improved by radar and AWS data assimilation in domain 3. The equitable threat score and bias score of the rainfall predicted in domain 3 indicated improvement for the threshold values of 0.1, 1, and 2.5 mm with data assimilation. For cases of occurrence of heavy rainfall (7 days), the equitable threat score and bias score improved considerably at all threshold values as compared to the entire period of KEOP. Radar and AWS data assimilation improved the temporal and spatial distributions of diurnal rainfall over southern Korea, and AWS data assimilation increased the predicted rainfall amount by approximately 0.3 mm 3hr$^{−1}$. |
| Starting Page | 341 |
| Ending Page | 353 |
| Page Count | 13 |
| File Format | |
| ISSN | 19767633 |
| Journal | Asia-Pacific Journal of Atmospheric Sciences |
| Volume Number | 46 |
| Issue Number | 3 |
| e-ISSN | 19767951 |
| Language | English |
| Publisher | Korean Meteorological Society |
| Publisher Date | 2010-08-26 |
| Publisher Place | Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | WRF-3DVAR WRF model real-time operation KEOP summer rainfall prediction diurnal variation of rainfall Geophysics/Geodesy Meteorology/Climatology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Atmospheric Science |
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