A Priori Identification of Skillful Extratropical Subseasonal Forecasts
A Priori Identification of Skillful Extratropical Subseasonal Forecasts
复制标题
熟练的温带次季节预报的先验识别
DOI：
10.1029/2019gl085270
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发表时间：
2019
影响因子：
5.2
通讯作者：
M. Newman
中科院分区：
文献类型：
--
作者：
J. Albers;M. Newman
当前一代的次季节业务模式预报，平均而言，对于3周以上的预报时效技能较低。这很可能是气候系统的一个基本特性，因为与潜在可预测但通常较弱的气候信号相比，不可预测的天气变率幅度相对较高。因此，要使次季节预报有用，就应该在预报时识别出其高技能和低技能事件。我们表明，一个线性逆模型（LIM），一个由冬季（12月 - 3月）每周平均观测分析的协变统计构建的经验 - 动力模型，可用于先验地识别预期的温带次季节地表和对流层中层预报技能。LIM预测的信噪比确定了第3 - 6周预报的子集（10% - 30%）——LIM以及来自美国国家环境预报中心和欧洲中期天气预报中心的两个业务模式——这些预报具有相对较高的技能，而其余大部分预报的技能与随机概率无异。
The current generation of subseasonal operational model forecasts has, on average, low skill for leads beyond 3 weeks. This is likely a fundamental property of the climate system, due to the relative high amplitude of unpredictable weather variability compared to potentially predictable, but generally weaker, climate signals. Thus, for subseasonal forecasts to be useful, their high versus low skill events should be identified at time of forecast. We show that a linear inverse model (LIM), an empirical‐dynamical model constructed from covariability statistics of wintertime (December–March) weekly averaged observational analyses, can be used to identify, a priori, the expected extratropical subseasonal surface and midtropospheric forecast skill. The LIM's predicted signal‐to‐noise ratio identifies the subset (10%–30%) of Weeks 3–6 forecasts—of the LIM and two operational models from the National Centers for Environmental Prediction and the European Centre for Medium‐Range Weather Forecasts—with relatively higher skill versus the much larger remainder of forecasts whose skill cannot be distinguished from random chance.
影响因子：
3.1
作者：
Fuqing Zhang;Y. Q. Sun;L. Magnusson;R. Buizza;Shian‐Jiann Lin;Jan‐Huey Chen;K. Emanuel
通讯作者：
Fuqing Zhang;Y. Q. Sun;L. Magnusson;R. Buizza;Shian‐Jiann Lin;Jan‐Huey Chen;K. Emanuel
影响因子：
1.9
作者：
Birner, Thomas;Albers, John R.
通讯作者：
Albers, John R.
影响因子：
4.9
作者：
Kim, Hyemi;Vitart, Frederic;Waliser, Duane E.
通讯作者：
Waliser, Duane E.