Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020GL092092 |
Subseasonal Forecasts of Opportunity Identified by an Explainable Neural Network | |
Kirsten J. Mayer; Elizabeth A. Barnes | |
2021-05-04 | |
发表期刊 | Geophysical Research Letters |
出版年 | 2021 |
英文摘要 | Midlatitude prediction on subseasonal timescales is difficult due to the chaotic nature of the atmosphere and often requires the identification of favorable atmospheric conditions that may lead to enhanced skill (“forecasts of opportunity”). Here, we demonstrate that an artificial neural network (ANN) can identify such opportunities for tropical‐extratropical circulation teleconnections within the North Atlantic (40°N, 325°E) at a lead of 22 days using the network’s confidence in a given prediction. Furthermore, layer‐wise relevance propagation, an ANN explainability technique, pinpoints the relevant tropical features the ANN uses to make accurate predictions. We find that layer‐wise relevance propagation identifies tropical hot spots that correspond to known favorable regions for midlatitude teleconnections and reveals a potential new pattern for prediction in the North Atlantic on subseasonal timescales. |
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/325863 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | Kirsten J. Mayer,Elizabeth A. Barnes. Subseasonal Forecasts of Opportunity Identified by an Explainable Neural Network[J]. Geophysical Research Letters,2021. |
APA | Kirsten J. Mayer,&Elizabeth A. Barnes.(2021).Subseasonal Forecasts of Opportunity Identified by an Explainable Neural Network.Geophysical Research Letters. |
MLA | Kirsten J. Mayer,et al."Subseasonal Forecasts of Opportunity Identified by an Explainable Neural Network".Geophysical Research Letters (2021). |
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