Atmospheric Predictability of the Tropics, Middle Latitudes, and Polar Regions Explored through Global Storm-Resolving Simulations
Atmospheric Predictability of the Tropics, Middle Latitudes, and Polar Regions Explored through Global Storm-Resolving Simulations
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通过全球风暴解决模拟探索热带、中纬度和极地地区的大气可预测性
DOI：
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发表时间：
2019
影响因子：
3.1
通讯作者：
F. Judt
中科院分区：
文献类型：
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作者：
F. Judt
大气的可预测性对于天气预报具有重要意义，因为它决定了哪些预测问题可能是可以解决的。尽管我们对误差增长和可预测性的一般理解一直在增加，但对大气可预测性的详细结构知之甚少，例如它在气候区域之间的变化。本研究利用 Judt 于 2018 年发表的先前全球风暴解决可预测性实验的模型输出，通过探索三个纬度地区的误差增长和可预测性来解决这个问题。确定热带地区比中纬度和极地地区具有更长的可预测性（热带>20天；中纬度和极地地区略多于2周）。每个纬度区域都有独特的误差增长特征，并且误差增长与每个区域的潜在动态大致一致。有证据表明，赤道波在热带地区相对较长的可预测性中发挥着重要作用。具体而言，赤道波似乎比中纬度斜压扰动更不易出现误差增长。尽管这些发现的普遍性需要在未来的研究中进行评估，但总体结论与之前的工作一致，因为当前的数值天气预报程序尚未达到大气可预测性的极限，特别是在热带地区。利用热带可预测性的一种方法是减少模型误差，例如，使用全球风暴解析模型而不是参数化对流的传统模型。
The predictability of the atmosphere has important implications for weather prediction, because it determines what forecast problems are potentially tractable. Even though our general understanding of error growth and predictability has been increasing, relatively little is known about the detailed structure of atmospheric predictability, such as how it varies between climate regions. The present study addresses this issue by exploring error growth and predictability in three latitude zones, using model output from a previous global storm-resolving predictability experiment by Judt published in 2018. It was determined that the tropics have longer predictability than the middle latitudes and polar regions (tropics, >20 days; middle latitudes and polar regions, a little over 2 weeks). Each latitude zone had distinct error growth characteristics, and error growth was broadly consistent with the underlying dynamics of each zone. Evidence suggests that equatorial waves play a role in the comparatively long predictability of the tropics; specifically, equatorial waves seem to be less prone to error growth than middle-latitude baroclinic disturbances. Even though the generality of the findings needs to be assessed in future studies, the overall conclusions agree with previous work in that current numerical weather prediction procedures have not reached the limits of atmospheric predictability, especially in the tropics. One way to exploit tropical predictability is to reduce model error, for example, by using global storm-resolving models instead of conventional models that parameterize convection.
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影响因子：
3.1
作者：
M. Menchaca;D. Durran
通讯作者：
M. Menchaca;D. Durran
影响因子：
3.1
作者：
Y. Ying;Fuqing Zhang
通讯作者：
Y. Ying;Fuqing Zhang
影响因子：
3.2
作者：
O. Tripathi;M. Baldwin;A. Charlton-Perez;M. Charron;J. Cheung;S. Eckermann;E. Gerber;D. Jackson;Y. Kuroda;A. Lang;J. McLay;R. Mizuta;C. Reynolds;G. Roff;M. Sigmond;S. Son;T. Stockdale
通讯作者：
O. Tripathi;M. Baldwin;A. Charlton-Perez;M. Charron;J. Cheung;S. Eckermann;E. Gerber;D. Jackson;Y. Kuroda;A. Lang;J. McLay;R. Mizuta;C. Reynolds;G. Roff;M. Sigmond;S. Son;T. Stockdale
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