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DOI | 10.1029/2020GL091287 |
An Atmospheric Signal Lowering the Spring Predictability Barrier in Statistical ENSO Forecasts | |
Dmitry Mukhin; Andrey Gavrilov; Aleksei Seleznev; Maria Buyanova | |
2021-03-10 | |
发表期刊 | Geophysical Research Letters |
出版年 | 2021 |
英文摘要 | The loss of autocorrelations of tropical sea surface temperatures (SST) during late spring, also called the spring predictability barrier (SPB), is a factor that strongly limits the predictability of El Nino Southern Oscillation (ENSO), and especially the statistical SST‐based ENSO forecasts starting from the winter‐spring season. Recent studies show that Pacific atmospheric circulation anomalies in winter‐spring may have a long‐term impact on the summer tropical climate via the SST footprint. Here, we infer an index based on sea level pressure (SLP) data from February‐March in a single area surrounding Hawaii, and show that this area is the most informative part of the large SLP pattern initiating the SST footprinting mechanism. We then construct a statistically optimal linear model of the Nino 3.4 index taking this atmospheric index as a forcing. We find that this forcing efficiently lowers the SPB and provides significant improvements of interseasonal Niño 3.4 forecasts. |
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/318640 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | Dmitry Mukhin,Andrey Gavrilov,Aleksei Seleznev,et al. An Atmospheric Signal Lowering the Spring Predictability Barrier in Statistical ENSO Forecasts[J]. Geophysical Research Letters,2021. |
APA | Dmitry Mukhin,Andrey Gavrilov,Aleksei Seleznev,&Maria Buyanova.(2021).An Atmospheric Signal Lowering the Spring Predictability Barrier in Statistical ENSO Forecasts.Geophysical Research Letters. |
MLA | Dmitry Mukhin,et al."An Atmospheric Signal Lowering the Spring Predictability Barrier in Statistical ENSO Forecasts".Geophysical Research Letters (2021). |
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