Wind temperature probing in the atmospheric boundary layer in the coastal area of Lake Baikal. I. The Richardson number

Atmosphere ◽  
2018 ◽  
Vol 9 (2) ◽  
pp. 51 ◽  
Author(s):  
Zixuan Yang ◽  
Antoni Calderer ◽  
Sida He ◽  
Fotis Sotiropoulos ◽  
James Doyle ◽  
...  

2022 ◽  
Author(s):  
Gina Jozef ◽  
John Cassano ◽  
Sandro Dahlke ◽  
Gijs de Boer

Abstract. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed wing uncrewed aircraft system (UAS). Of particular interest is the atmospheric boundary layer (ABL) height, as ABL structure can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiation budget. The high temporal resolution of the UAS observations allows us to subjectively identify ABL height for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ABL height with the ABL heights identified by various previously published objective methods allows us to determine which objective methods are most successful at accurately identifying ABL height in the central Arctic environment. The objective methods we use are the Liu-Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ABL height determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ABL height, while the Liu-Liang method is least successful.


2020 ◽  
Vol 12 (6) ◽  
pp. 955 ◽  
Author(s):  
Viktor A. Banakh ◽  
Igor N. Smalikho ◽  
Andrey V. Falits

The paper presents the results of probing the stable atmospheric boundary layer in the coastal zone of Lake Baikal with a coherent Doppler wind lidar and a microwave temperature profiler. Two-dimensional height–temporal distributions of the wind velocity vector components, temperature, and parameters characterizing atmospheric stability and wind turbulence were obtained. The parameters of the low-level jets and the atmospheric waves arising in the stable boundary layer were determined. It was shown that the stable atmospheric boundary layer has an inhomogeneous fine scale layered structure characterized by strong variations of the Richardson number Ri. Layers with large Richardson numbers alternate with layers where Ri is less than the critical value of the Richardson number Ricr = 0.25. The channels of decreased stability, where the conditions are close to neutral stratification 0 < Ri < 0.25, arise in the zone of the low-level jets. The wind turbulence in the central part of the observed jets, where Ri > Ricr, is weak, increases considerably to the periphery of jets, at heights where Ri < Ricr. The turbulence may intensify at the appearance of internal atmospheric waves.


2020 ◽  
Vol 4 (1) ◽  
pp. 74-82
Author(s):  
Lyudmila I. Kurbatskaya

The changes in turbulent eddy mixing in the atmospheric boundary layer (ABL) are investigated with the use of the mesoscale RANS turbulence model with account for effects of internal gravitational waves, which support momentum transfer under condition of very stable stratification. A focus was put on analysis of behavior of the coefficients of vertical eddy diffusion of momentum and heat. The behavior of the turbulent eddy mixing parameters was found to be consistent with measurements in the laboratory and atmosphere. In particular, the flow Richardson number () during the transient flow to a strongly stable state can behave nonmonotonically, growing with increasing gradient Richardson number () to the state of saturation at a certain gradient Richardson number ( Ri@ 1 ), which separates two different turbulent regimes: strong mixing and weak mixing.


2021 ◽  
Author(s):  
Damao Zhang ◽  
Jennifer Comstock ◽  
Victor Morris

Abstract. Ceilometer measurements of aerosol backscatter profiles have been widely used to provide continuous PBLHT estimations. To investigate the robustness of ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using long term U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) ceilometer and balloon-borne sounding data at three ARM fixed-location atmospheric observatories and from three ARM mobile observatories deployed around the world for various field campaigns, which cover from Tropics to Polar regions and over both ocean and land surfaces. Statistical comparisons of ceilometer-estimated PBLHTs from the Vaisala CL31 ceilometer data with radiosonde-estimated PBLHTs from the ARM PBLHT-SONDE Value-added Product (VAP) are performed under different atmospheric conditions including stable and unstable atmospheric boundary layer, low-level cloud-free, and cloudy conditions at these ARM observatories. Under unstable atmospheric boundary layer conditions, good comparisons are found between ceilometer- and radiosonde-estimated PBLHTs at ARM low- and mid-latitude land observatories. However, it is still challenging to obtain reliable PBLHT estimations over ocean surfaces even using radiosonde data. Under stable atmospheric boundary layer conditions, ceilometer- and radiosonde-estimated PBLHTs have weak correlations. Among different PBLHT estimations utilizing the Heffter, the Liu-Liang, and the bulk Richardson number methods in the ARM PBLHT-SONDE VAP, ceilometer-estimated PBLHTs have better comparisons with the Liu-Liang method under unstable and with the bulk Richardson number method under stable atmospheric boundary layer conditions.


2007 ◽  
Vol 25 ◽  
pp. 49-55 ◽  
Author(s):  
S. Argentini ◽  
I. Pietroni ◽  
G. Mastrantonio ◽  
A. Viola ◽  
S. Zilitinchevich

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