No abstract

The tropical region is a key area for the interaction between the stratosphere and troposphere. The strong convective activity in the troposphere produces a series of gravity wave activities, which result in strong and widespread turbulence over the region. Therefore, studying the turbulent activity in the western Pacific is essential for understanding the characteristics of atmospheric disturbance over this region, which has the world’s most complex circulation system. In this paper, we explore the characteristics of atmospheric turbulence distribution over Guam in this region, and the Thorpe sorting method is used to study one-second resolution radiosonde data from the US. On the basis of the background field and local instability, the turbulence generation mechanism is discussed in detail. Results show that the US high-resolution balloon data are efficacious for tropospheric turbulence retrieval but increasingly affected by instrument noise as altitude increases. It is also found that there is a strong turbulent mixing band caused by both shear instability and static instability near the tropopause, where the turbulence activity is markedly enhanced and characterized by annual oscillation, reaching the maximum from July to September.

In this article, Thorpe analysis, which often retrieves the characteristics of mixing in the free atmosphere from balloon sounding data, is applied to the data of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC). We find that the COSMIC data can well retrieve the strongest mixed layer in the troposphere (SMLT) altitude, and can reveal the basic variation trend of the SMLT thickness and Thorpe scale L T . We use COSMIC data to reveal the global spatial and temporal distribution of the SMLT from 2007 to 2015 and analyze the fluctuation period of the SMLT altitude with Hilbert-Huang transform (HHT), we find that the variation of the SMLT altitude is influenced by the dual effects of terrain and solar radiation.Atmosphere 2020, 11, 264 2 of 14 number of this data in the dataset), then the Thorpe displacement will be D = z n − z m . The root mean square of all D in the entire inversion is the Thorpe scale,