Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2021GL093447 |
Enhancing Subseasonal Temperature Prediction by Bridging a Statistical Model with Dynamical Arctic Oscillation Forecasting | |
Minju Kim; Changhyun Yoo; Jung Choi | |
2021-07-30 | |
发表期刊 | Geophysical Research Letters |
出版年 | 2021 |
英文摘要 | This study proposes a hybrid approach to improving subseasonal prediction skills by bridging a conventional statistical model and a dynamical ensemble forecast system. Based on the perfect prognosis method, the phase of the Arctic Oscillation (AO) from the ECMWF ensemble forecast system is used as a predictor in a composite based statistical model to predict the wintertime surface air temperature in the Northern Hemisphere. The hybrid model, which employs AO phases predicted by the dynamical model for weeks 1–4, generally outperforms the conventional statistical model for lead times of weeks 2–6. The improved skill score is due to the high accuracy of the AO forecast from the dynamical model and the strong lagged connection between the AO and temperature. This study thus lays the groundwork for the potential use of combining climate variability, statistical relation, and dynamical forecasting. |
领域 | 气候变化 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/335349 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | Minju Kim,Changhyun Yoo,Jung Choi. Enhancing Subseasonal Temperature Prediction by Bridging a Statistical Model with Dynamical Arctic Oscillation Forecasting[J]. Geophysical Research Letters,2021. |
APA | Minju Kim,Changhyun Yoo,&Jung Choi.(2021).Enhancing Subseasonal Temperature Prediction by Bridging a Statistical Model with Dynamical Arctic Oscillation Forecasting.Geophysical Research Letters. |
MLA | Minju Kim,et al."Enhancing Subseasonal Temperature Prediction by Bridging a Statistical Model with Dynamical Arctic Oscillation Forecasting".Geophysical Research Letters (2021). |
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