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Turbulent Mechanisms for the Deep Convective Boundary Layer in the Taklimakan Desert


Zhang, Hongsheng; Zhang, Lu; Wei, Wei; Mamtimin, Ali (2022), Turbulent Mechanisms for the Deep Convective Boundary Layer in the Taklimakan Desert, Dryad, Dataset,


The deep convective boundary layer (CBL) in the Taklimakan Desert plays an important role in the climate system in East Asia. Based on the observation experiment and large-eddy simulation, turbulent mechanisms for its formation were revealed in this study. This explained why the daily maximum CBL depth was independent of surface heating. In the late-morning, there was a weak temperature inversion and a near-neutral residual layer (RL) above the CBL.   With the development of the CBL, stronger convection could penetrate the RL and even overshoot the top of the RL. The distinctive boundary-layer process entrained free-tropospheric air to warm the RL and then promoted the entrainment of the warmed air in the RL into the CBL. This extra energy supply effectively contributed to the growth of the CBL. With further positive feedback between the CBL and RL depths, a deeper CBL would form in consecutive fair-weather conditions.


The data were collected in July 2016 at the Tazhong meteorological station (39° 00'N, 83° 40'E), situated in the hinterland of the TD. The station is surrounded by relatively homogeneous shifting sand and dunes. The radiosonde data were collected from the GPS radiosonde system developed by the Beijing Institute of Radio Measurement. The variations of air density and specific heat capacity at constant pressure with height were empirically calculated using radiosondes. The turbulence data were obtained by the eddy covariance system (IGRASON, Campbell Scientific, Inc., USA) mounted on a mast, at a height of 3 m above the sand surface.


National Natural Science Foundation of China, Award: 42175092, 91837209, 41875023

Second Tibetan Plateau Scientific Expedition and Research (STEP) program, Award: 2019QZKK0105

Special Funds for Basic Scientific Research of Central-level Public Welfare Scientific Research Institutes, Award: IDM2021001

Flexible Talents Introducing Project of Xinjiang (2018)