Inertia-gravity wave energy and instability drive turbulence: evidence from a near-global high-resolution radiosonde dataset

Zhang, Jian; Guo, Jianping; Zhang, Shaodong; Shao, Jia

doi:10.1007/s00382-021-06075-2

Cited by 14 publications

(16 citation statements)

References 74 publications

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“…The measurements of the drift and descent stages were used to fill the gap left by operational radiosonde measurements, which were typically conducted twice per day. The measurement uncertainties of operational radiosonde measurements have been well verified and thus can be reliable enough to be used here [57][58][59][60][61]. Compared with the operational radiosonde data, which were only available for 00:00 and 12:00 UTC, the observational time of the dropsonde seemed more flexible (theoretically, the dropsonde can be deployed at any time), thereby giving us a unique opportunity to characterize the internal structures of the typhoon during its evolutionary stages or at various storm-relative positions.…”

Section: Methodsmentioning

confidence: 88%

Investigation of Atmospheric Dynamic and Thermodynamic Structures of Typhoon Sinlaku (2020) from High-Resolution Dropsonde and Two-Way Rawinsonde Measurements

et al. 2022

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Profiling the vertical atmospheric structure for typhoons remains challenging. Here, the atmospheric dynamic and thermodynamic structures were investigated during the passage of Typhoon Sinlaku (2020) over Xisha Islands in the South China Sea for the period 28 July to 2 August 2020, mainly based on two-way rawinsonde and dropsonde measurements in combination with surface-based automatic weather station observations, disdrometer measurements, and Himawari-8 geostationary satellite images. The study period was divided to three stages: the formation stage of tropical depression (pre-TD), tropical depression (TD), and tropical storm (TS). The wind speed and local vertical wind shear reached the maximum value at 3 km above mean sea level (AMSL) before the typhoon approached the Xisha islands. Pseudo-equivalent potential temperature (θse) was found to decrease with the altitude below 2 km AMSL; temperature inversions occurred frequently within this altitude range, particularly during the TS stage. This seemed a typical capping inversion that indicated a downward motion above 2 km AMSL. The temperature increased slightly with the development of Typhoon Sinlaku (2020) at altitudes of 8–10 km AMSL. This indicated that our observations presumably captured the air mass warmed by the condensation, which was a good signature of an upper air in the tropical cyclone. In addition, wind speed (particularly in the lower stratosphere), specific humidity, and equivalent potential temperature escalated significantly when the tropical depression strengthened into Typhoon Sinlaku (2020), which indicated that the typhoon constantly obtained energy from the sea surface during its passage over the study region. The thermodynamic and dynamic structures of atmosphere advance our understanding of the inner structure of typhoons during the different evolutionary stages.

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Section: Methodsmentioning

confidence: 88%

Investigation of Atmospheric Dynamic and Thermodynamic Structures of Typhoon Sinlaku (2020) from High-Resolution Dropsonde and Two-Way Rawinsonde Measurements

et al. 2022

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“…As described in Guo et al (2021) and Zhang et al (2022), a high vertical resolution radiosonde (HVRRS) dataset gained from several organizations was adopted, spanning January 2017 to October 2022, in a total of 5.8 years. The organizations include the China Meteorological Administration (CMA), the U.S National Oceanic and Atmospheric Administration (NOAA), the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN), the Centre for Environmental Data Analysis of the United Kingdom (CEDA), University of Wyoming, Deutscher Wetterdienst, and ECMWF.…”

Section: High-resolution Radiosonde Datasetmentioning

confidence: 99%

“…The GW energy is extracted based on the broad spectral method, according to Wang and Geller (2003). In this method, the magnitude of measured zonal wind (u), meridional wind (v), and temperature (T) consisting of background states (𝑢 0 , 𝑣 0 and 𝑇 0 ) that are determined by applying a second-order polynomial fit (Chen et al, 2018;Zhang et al, 2022) and perturbations. Therefore, total perturbations are derived as:…”

Section: Gravity Wave Energymentioning

confidence: 99%

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Occurrence frequency of Kelvin‐Helmholtz instability assessed by global high-resolution radiosonde and ERA5 reanalysis

Shao

Zhang

Wang

et al. 2023

Preprint

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Abstract. Kelvin Helmholtz instability (KHI) is most likely to be the primary source for clear-air turbulence that is of importance in pollution transfer and diffusion and aircraft safety. It is exemplarily indicated by the critical value of Richardson (Ri) number, which is typically taken as 1/4. However, Ri is fairly sensitive to the vertical resolution of the dataset: a higher resolution systematically leads to a finer structure. The study aims to evaluate the performance of ERA5 reanalysis (137 model levels) in determining KHI spatial-temporal variabilities, by comparing it against a near-global high-resolution (10-m) radiosonde dataset during years 2017 to 2022, and to further highlight the global climatology and dynamical environment of KHIs. Overall, the occurrence frequency of Ri < 1/4 in the free atmosphere is inevitably underestimated by the ERA5 reanalysis over all climate zones, compared to radiosonde, due largely to the severe underestimation in wind shears. Otherwise, the occurrence frequency of KHI indicated by Ri < 1 in ERA5 is climatologically consistent with that from radiosondes in the free troposphere, especially over the midlatitude and subtropics in the Northern/Southern Hemisphere. Therefore, we infer that the threshold value of Ri should be approximated as 1, rather than 1/4, when using ERA5 for the KHI estimation. KHI occurrence frequencies revealed by both datasets exhibit significant seasonal cycles over polar, midlatitude, and subtropics regions, and they are consistently strong at heights of 10–15 km in the tropic region. In addition, the frequency at low-levels is positively correlated with the standard derivation of orography, and it is exceptionally strong over the Niño 3 region at heights of 6–13 km. Furthermore, the dynamical environment of KHI favors strong wind shears probably induced by the mean flows and the propagation of orographic or non-orographic gravity waves.

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“…The atmospheric boundary layer (ABL) connects the lowest layer of the Earth's atmosphere, the surface layer, to the rest of the troposphere. Its dynamics is fundamental for the transport and exchange of moisture, heat and momentum with the underlying surface [1][2][3]. Several studies have examined turbulence in the ABL, showing that its structure can be extremely complex and characterized by multiscale fluctuations [4,5], with turbulent eddies ranging from mesoscales, L ∈ [10 2 , 10 3 ] m, related to the instability of the mean flow shear, and buoyancy effects [6][7][8][9][10][11], down to smaller scales, L ∈ [10 −2 , 10 2 ] m, related to the energy-cascade process or fine-scale turbulent bursts [6,10,[12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Local dimensionality and inverse persistence analysis of atmospheric turbulence in the stable boundary layer

et al. 2022

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The dynamics across different scales in the stable atmospheric boundary layer has been investigated by means of two metrics, based on instantaneous fractal dimensions, and grounded in dynamical systems theory. The wind velocity fluctuations obtained from data collected during the CASES-99 experiment were analyzed to provide a local (in terms of scales), and an instantaneous (in terms of time) description of the fractal properties and predictability of the system. By analyzing the phase space projections of the continuous turbulent, intermittent and radiative regimes, a progressive transformation, characterized by the emergence of multiple low-dimensional clusters embedded in a high-dimensional shell and a 2-lobe mirror symmetrical structure of the inverse persistence, have been found. The phase space becomes increasingly complex and anisotropic as the turbulent fluctuations become uncorrelated. The phase space is characterized by a three-dimensional structure for the continuous turbulent samples in a range of scales compatible with the inertial sub-range, where the phase space-filling turbulent fluctuations dominate the dynamics, and is low-dimensional in the other regimes. Moreover, lower dimensional structures present a stronger persistence than the higher dimensional structures. Eventually, all samples recover a three-dimensional structure and higher persistence level at large scales, far from the inertial sub-range. The two metrics obtained in the analysis can be considered as proxies for the decorrelation time and the local anisotropy in the turbulent flow.

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Inertia-gravity wave energy and instability drive turbulence: evidence from a near-global high-resolution radiosonde dataset

Cited by 14 publications

References 74 publications

Investigation of Atmospheric Dynamic and Thermodynamic Structures of Typhoon Sinlaku (2020) from High-Resolution Dropsonde and Two-Way Rawinsonde Measurements

Investigation of Atmospheric Dynamic and Thermodynamic Structures of Typhoon Sinlaku (2020) from High-Resolution Dropsonde and Two-Way Rawinsonde Measurements

Occurrence frequency of Kelvin‐Helmholtz instability assessed by global high-resolution radiosonde and ERA5 reanalysis

Local dimensionality and inverse persistence analysis of atmospheric turbulence in the stable boundary layer

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