The Signal‐to‐Noise Paradox for Interannual Surface Atmospheric Temperature Predictions
The Signal‐to‐Noise Paradox for Interannual Surface Atmospheric Temperature Predictions
复制标题
年际表面大气温度预测的信噪悖论
DOI：
10.1029/2019gl083855
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发表时间：
2019
影响因子：
5.2
通讯作者：
S. Drijfhout
中科院分区：
文献类型：
--
作者：
F. Sévellec;S. Drijfhout
“信噪比悖论”意味着气候模型比气候模型本身更能预测观测结果。在这里，研究表明，当模型中预测信号的相对水平弱于观测值时，就会出现这种明显的悖论。在存在模型误差的情况下，悖论仅发生在模型的小信噪比范围内，并且随着模型误差的增加，模型信噪比更小也会出现这种悖论。这种悖论始终是预测不可靠的标志。假设预测技能与持久性相关，将此概念应用于 CMIP5 数据库表面大气温度 (SAT) 的非初始化模拟，表明全球平均 SAT 在模型中的持久性略低于在观测中的持久性。然而，在局部范围内，分析表明，全球约 70% 的地区在当地 SAT 年际预报中表现出信噪比悖论，并且信噪比悖论尤其发生在海洋上。
The “signal‐to‐noise paradox” implies that climate models are better at predicting observations than themselves. Here, it is shown that this apparent paradox is expected when the relative level of predicted signal is weaker in models than in observations. In the presence of model error, the paradox only occurs in the range of small signal‐to‐noise ratio of the model, occurring for even smaller model signal‐to‐noise ratio with increasing model error. This paradox is always a signature of the prediction unreliability. Applying this concept to noninitialized simulations of Surface Atmospheric Temperature (SAT) of the CMIP5 database, under the assumption that prediction skill is associated with persistence, shows that global mean SAT is marginally less persistent in models than in observations. However, at a local scale, the analysis suggests that ∼70% of the globe exhibits the signal‐to‐noise paradox for local SAT interannual forecasts and that the Signal‐to‐Noise Paradox occurs especially over the oceans.
影响因子：
16.6
作者：
Su Z;Wang J;Klein P;Thompson AF;Menemenlis D
通讯作者：
Menemenlis D
影响因子：
5.2
作者：
Ho, Chun Kit;Hawkins, Ed;Eade, Rosie
通讯作者：
Eade, Rosie