4.4 Article

Atmospheric Predictability of the Tropics, Middle Latitudes, and Polar Regions Explored through Global Storm-Resolving Simulations

期刊

JOURNAL OF THE ATMOSPHERIC SCIENCES
卷 77, 期 1, 页码 257-276

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/JAS-D-19-0116.1

关键词

Dynamics; Waves; atmospheric; Numerical analysis; modeling; Numerical weather prediction; forecasting; Numerical weather prediction; forecasting; Tropical variability

资金

  1. National Science Foundation

向作者/读者索取更多资源

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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