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APCC Researchers Received the Best Paper Presentation Award at the 2019 KMS Spring Conference of Climate Division.

Ms. Gayoung Kim (Researcher), Dr. Yun-Young Lee (Research Fellow), Mr. Soonjo Yoon (Researcher) and Dr. Ji-Hyun Oh (Research Fellow) from the APEC Climate Center (APCC) received the Best Paper Presentation Award at the 2019 Korean Meteorological Society (KMS) Spring Conference of Climate Division, held between the 22th and 25th April, 2019 at EXCO, Daegu, Korea. 


They presented the contents of their research paper entitled “ Assessment of Intraseasonal Multi-Model Ensemble (MME) Prediction Skill Using Subseasonal to Seasonal (S2S) Models” during the poster presentation at the 2019 KMS Spring Conference of Climate Division, and was awarded the Best Paper Presentation Award. The four researchers coauthored the paper. 

Intraseasonal prediction information refers to the climate forecast information for the period between 2 weeks (15 days) and 2 months (60 days). Extreme hydrological events such as droughts and floods occur often and cause great harm to the population and infrastructure during this period. So far, it is well known that there are many challenges to improving the reliability of intraseasonal prediction information.

In this context, the four APCC researchers conducted the research on the ‘ Assessment of Intraseasonal MME Prediction Skill Using S2S Models’ as the 1st phase in developing technology for improving the reliability of intraseasonal MME prediction.  

The researchers found that El Nino-Southern Oscillation (ENSO) has an deep impact on the reliability of intraseasonal MME prediction. In addition, the reliability of the intraseasonal MME prediction are found to be affected  by Quasi-Biennial Oscillation (QBO) at the upper layers of the atmosphere. Their research discovered that especially when the east wind of QBO is dominant, the reliability of intraseasonal MME prediction is rapidly improved. 

APCC has been producing and providing reliable seasonal prediction information based on analysis using the MME technique since 2005. 



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