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The tropopause is an important transition layer and can be a diagnostic of upper-tropospheric and lower-stratospheric structures, exhibiting unique atmospheric thermal and dynamic characteristics. A comprehensive understanding of the evolution of fine tropopause structures is necessary and primary for the further study of complex multi-scale atmospheric physical–chemical coupling processes in the upper troposphere and lower stratosphere. A novel method utilizing the bi-Gaussian function is capable of identifying the characteristic parameters of vertical tropopause structures and providing information on double-tropopause (DT) structures. The new method improves the definition of the cold-point tropopause and detects one (or two) of the most significant local cold points by fitting the temperature profiles to the bi-Gaussian function, which defines the point(s) as the tropopause height(s). The bi-Gaussian function exhibits excellent potential for explicating the variation trends of temperature profiles. The results of the bi-Gaussian method and lapse rate tropopause, as defined by the World Meteorological Organization, are compared in detail for different cases. Results indicate that the bi-Gaussian method is able to more stably and obviously identify the spatial and temporal distribution characteristics of the thermal tropopauses, even in the presence of multiple temperature inversion layers at higher elevations. Moreover, 5 years of historical radiosonde data from China (from 2012 to 2016) revealed that the occurrence frequency and thickness of the DT, as well as the single-tropopause height and the first and second DT heights, displayed significant meridional monotonic variations. The occurrence frequency (thickness) of the DT increased from 1.07 % (1.96 km) to 47.19 % (5.42 km) in the latitude range of 16–50° N. The meridional gradients of tropopause height were relatively large in the latitude range of 30–40° N, essentially corresponding to the climatological locations of the subtropical jet and the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The tropopause is important as a diagnostic of the upper troposphere and lower stratosphere structures, with unique atmospheric thermal, dynamic structures. A comprehensive understanding of the evolution of the fine tropopause structures is necessary and primary to further study the complex multi-scale atmospheric physicochemical coupling processes in the upper troposphere and lower stratosphere. Utilizing the bi-Gaussian function, a novel method is capable of identifying the characteristic parameters of tropopause vertical structures, as well as providing the information of double tropopauses (DT) structures. The new method improves the definition of cold point tropopause, and detects one (or two) most significant local coldest point(s) in mathematical statistics by fitting the temperature profiles to the bi-Gaussian function, which is (are) defined as the tropopause height(s). The bi-Gaussian function exhibits remarkable potential for explicating the variation trend of temperature profiles. The recognition results of the bi-Gaussian method and lapse rate tropopause, as defined by World Meteorological Organization, are compared in detail for different cases. Results indicate that the bi-Gaussian method possesses a lower missed detection rate and false detection rate than lapse rate tropopause, because it is not restricted by thresholds, even in the presence of multiple temperature inversion layers at higher elevations. Five-year (from 2012 to 2016) historical radiosondes in China revealed that the occurrence frequency and thickness of DT, as well as the single tropopause height, and the first and second DT height displayed significant meridional monotonic variations. The occurrence frequency (thickness) of DT increased from 2.93 % (2.61 km) to 72.45 % (6.84 km) in the latitude range [16° N, 50° N]. At mid-latitudes [30° N, 40° N], the meridional gradients of tropopause height were relatively large, essentially corresponding to the climatological location of the subtropical jet and Tibetan Plateau. The average DT thickness reported in this study is approximately 1–2 km thicker than that in previous studies, particularly in the mid-high latitudes [45° N, 50° N], which may be related to the different vertical resolution of temperature profiles provided by various data sources. DT structure occurs most frequently and has the largest meridional gradient in the mid-latitudes, formatted by a combination of poleward advection in the low-latitude upper troposphere and equatorward advection in the high-latitude lower stratosphere. In addition, although DT is thick in winter, the DT temperature difference is small, even the case of the first tropopause temperature is lower than the second tropopause temperature happens occasionally. [ABSTRACT FROM AUTHOR]

Light undergoes attenuation due to scattering and refraction when propagating through aerosols. In foggy conditions, Aerosol particles in the troposphere exhibit high mobility introducing intricate non‐linear noise into images. Foggy image restoration represents an ill‐posed problem, where traditional physical models and image enhancement techniques often prove inadequate in delivering effective solutions. This paper introduces a novel deep sub‐pixel reconstruction algorithm for foggy image restoration, pioneering the application of sub‐pixel reconstruction modules to this domain. This model employs convolutional layers to extract low‐level features and dense‐connected layers for high‐level feature extraction. Furthermore, a specialized sub‐pixel reconstruction module tailored for the task of foggy image restoration is designed, with the purpose of reconstructing dehazed images from latent vectors. During training, a generative adversarial training framework is adopted, incorporating a purpose‐designed discriminator. Additionally, a fusion loss is implemented to facilitate model refinement. Quantitative and qualitative evaluation experiments conducted on synthetic and real‐world image datasets demonstrate the effectiveness of the proposed method in preserving finer details. The Structural Similarity Index (SSIM) is observed to improve by 2.5%, attesting to enhanced perceptual quality for grayscale foggy images. [ABSTRACT FROM AUTHOR]

Atmospheric turbulence and wind speed distributions are essential in determining the quality of astronomical sites and implementing adaptive optics systems. In this study, the optical turbulence with a general turbulence model and the wind speed characteristics at Lenghu are investigated by employing the 21-yr European Centre for Medium-Range Weather Forecasts' fifth set of reanalysis (ERA5) data. The vertical distributions and seasonal behaviours of the wind speed and atmospheric turbulence are analysed. The wind speed values at 200 hPa pressure level (V 200) are low in spring and summer except for June, and high in autumn and winter. The highest and lowest values of V 200 at Lenghu are 39.93 m s−1 in September and 27.48 m s−1 in April, respectively. Additionally, atmospheric conditions are relatively stable above 20 km throughout the year. The locations of the peaks in the |$C_n^2$| profiles correspond to the tropopause and the jet wind stream regions at the Lenghu site. Furthermore, the median seeing value from ERA5 is 0.72 arcsec, generally consistent with the statistically measured value of 0.75 arcsec. Moreover, the astronomical parameters (r 0, θAO, and τAO) were initially provided at the Lenghu site. The median values of r 0, ε, θAO, and τAO are 15.17 cm, 0.72 arcsec, 1.19 arcsec, and 2.83 ms, respectively, thus providing the potential reference for astronomical applications. [ABSTRACT FROM AUTHOR]