GloSea5 모형의 성층권 예측성 검증

This study explores the 6-month lead prediction skill of stratospheric temperature and circulations in the Global Seasonal forecasting model version 5 (GloSea5) hindcast experiment over the period of 1996 similar to 2009. Both the tropical and extratropical circulations are considered by analyzing t...

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Bibliographic Details
Published in:Atmosphere
Main Authors: 정명일, 손석우, 임유나, 송강현, 원덕진, 강현석
Format: Article in Journal/Newspaper
Language:unknown
Published: 한국기상학회 2018
Subjects:
QBO
Online Access:https://hdl.handle.net/10371/206990
https://doi.org/10.14191/Atmos.2016.26.1.203
Description
Summary:This study explores the 6-month lead prediction skill of stratospheric temperature and circulations in the Global Seasonal forecasting model version 5 (GloSea5) hindcast experiment over the period of 1996 similar to 2009. Both the tropical and extratropical circulations are considered by analyzing the Quasi-Biennial Oscillation (QBO) and Northern Hemisphere Polar Vortex (NHPV). Their prediction skills are quantitatively evaluated by computing the Anomaly Correlation Coefficient (ACC) and Mean Squared Skill Score (MSSS), and compared with those of El Nino-Southern Oscillation (ENSO) and Arctic Oscillation (AO). Stratospheric temperature is generally better predicted than tropospheric temperature. Such improved prediction skill, however, rapidly disappears in a month, and a reliable prediction skill is observed only in the tropics, indicating a higher prediction skill in the tropics than in the extratropics. Consistent with this finding, QBO is well predicted more than 6 months in advance. Its prediction skill is significant in all seasons although a relatively low prediction skill appears in the spring when QBO phase transition often takes place. This seasonality is qualitatively similar to the spring barrier of ENSO prediction skill. In contrast, NHPV exhibits no prediction skill beyond one month as in AO prediction skill. In terms of MSSS, both QBO and NHPV are better predicted than their counterparts in the troposphere, i.e., ENSO and AO, indicating that the GloSea5 has a higher prediction skill in the stratosphere than in the troposphere. N 2