Estimation of Turbulent Kinetic Energy Dissipation Rate in the Bottom Boundary Layer of the Pearl River Estuary

A structure function approach is applied to estimate the turbulent kinetic energy （TKE） dissipation rate in the bottom boundary layer of the Pearl River Estuary （PRE）. Simultaneous measurements with an acoustic Doppler velocimeter （ADV） supplied independent data for the verification of the structure function method. The results show that, 1） the structure function approach is reliable and successfully applied method to estimate the TKE dissipation rate. The observed dissipation rates range between 8.3 ×10^-4 W/kg and 4.9× 10^-6 W/kg in YM01 and between 3.4×10^-4 W/kg and 4.8×10^-7 W/kg in YM03, respectively, while exhibiting a strong quarter-diurnal variation. 2） The balance between the shear production and viscous dissipation is better achieved in the straight river. This first-order balance is significantly broken in the estuary by non-shear production/dissipation due to wave-induced fluctuations.

Turbulent mixing above the Atlantic Water around the Chukchi Borderland in 2014

This study presents an analysis of the CTD data and the turbulent microstructure data collected in 2014, the turbulent mixing environment above the Atlantic Water（AW） around the Chukchi Borderland region is studied.Surface wind becomes more efficient in driving the upper ocean movement along with the rapid decline of sea ice,thus results in a more restless interior of the Arctic Ocean. The turbulent dissipation rate is in the range of4.60×10–10（–3.31×10–9 W/kg with a mean value of 1.33×10–9 W/kg, while the diapycnal diffusivity is in the range of1.45×10–6–1.46×10–5m2/s with a mean value of 4.84×10–6 m2/s in 200–300 m（above the AW）. After investigating on the traditional factors（i.e., wind, topography and tides） that may contribute to the turbulent dissipation rate, the results show that the tidal kinetic energy plays a dominating role in the vertical mixing above the AW. Besides, the swing of the Beaufort Gyre（BG） has an impact on the vertical shear of the geostrophic current and may contribute to the regional difference of turbulent mixing. The parameterized method for the double-diffusive convection flux above the AW is validated by the direct turbulent microstructure results.

Turbulent mixing in the upper ocean of the northwestern Weddell Sea, Antarctica

Turbulent mixing in the upper ocean（30-200 m） of the northwestern Weddell Sea is investigated based on profiles of temperature,salinity and microstructure data obtained during February 2014.Vertical thermohaline structures are distinct due to geographic features and sea ice distribution,resulting in that turbulent dissipation rates（ε） and turbulent diffusivity（K） are vertically and spatially non-uniform.On the shelf north of Antarctic Peninsula and Philip Ridge,with a relatively homogeneous vertical structure of temperature and salinity through the entire water column in the upper 200 m,both ε and K show significantly enhanced values in the order of O（10^（-7））-O（10^（-6）） W/kg and O（10^（-3））-O（10^（-2）） m^2/s respectively,about two or three orders of magnitude higher than those in the open ocean.Mixing intensities tend to be mild due to strong stratification in the Powell Basin and South Orkney Plateau,where s decreases with depth from O（10^（-8）） to O（10^（-9）） W/kg,while K changes vertically in an inverse direction relative to s from O（10^（-6）） to O（10^（-5）） m^2/s.In the marginal ice zone,K is vertically stable with the order of10^（-4） m^2/s although both intense dissipation and strong stratification occur at depth of 50-100 m below a cold freshened mixed layer.Though previous studies indentify wind work and tides as the primary energy sources for turbulent mixing in coastal regions,our results indicate weak relationship between K and wind stress or tidal kinetic energy.Instead,intensified mixing occurs with large bottom roughness,demonstrating that only when internal waves generated by wind and tide impinge on steep topography can the energy dissipate to support mixing.In addition,geostrophic current flowing out of the Weddell Sea through the gap west of Philip Passage is another energy source contributing to the local intense mixing.

On two distinct Reynolds number regimes of a turbulent square jet

The effects of Reynolds number on both large-scale and small-scale turbulence properties are investigated in a square jet issuing from a square pipe. The detailed velocity fields were measured at five different exit Reynolds numbers of 8 × 10^3 〈 Re 〈 5 × 10^4. It is found that both large-scale properties （e.g,, rates of mean velocity decay and spread） and small-scale properties （e.g., the dimensionless dissipation rate constant A = εL/（u^2）^3/2） are dependent on Re for Re ≤ 3 ×10^4 or Reλ ≤ 190, but virtually become Re-independent with increasing Re or Reλ. In addition, for Reλ 〉 190, the value ofA = εL/（u^2）^3/2 in the present square jet converges to 0.5, which is consistent with the observation in direct numerical simulations of box turbulence, but lower than that in circular jet, plate wake flows, and grid turbulence. The discrepancies in critical Reynolds number and A = εL/（u^2）^3/2 among different turbulent flows most likely result from the flow type and initial conditions.

Turbulence and Rainfall Microphysical Parameters Retrieval and Their Relationship Analysis Based on Wind Profiler Radar Data

Rainfall is triggered and mainly dominated by atmospheric thermo-dynamics and rich water vapor.Nonetheless, turbulence is also considered as an important factor influencing the evolution of rainfall microphysical parameters. To study such an influence, the present study utilized boundary layer wind profiler radar measurements. The separation point of the radar power spectral density data was carefully selected to classify rainfall and turbulence signals;the turbulent dissipation rate ε and rainfall microphysical parameters can be retrieved to analyze the relationship betweenε and microphysical parameters. According to the retrievals of two rainfall periods in Beijing 2016, it was observed that(1) ε in the precipitation area ranged from 10^(-3.5) to 10^(-1) m^(2) s^(-3) and was positively correlated with the falling velocity spectrum width;(2) interactions between turbulence and raindrops showed that small raindrops got enlarge through collision and coalescence in weak turbulence, but large raindrops broke up into small drops under strong turbulence, and the separation value of ε being weak or strong varied with rainfall attributes;(3) the variation of rainfall microphysical parameters(characteristic diameters, number concentration, rainfall intensity, and water content) in the middle stage were stronger than those in the early and the later stages of rainfall event;(4) unlike the obvious impacts on raindrop size and number concentration, turbulence impacts on rain rate and LWC were not significant because turbulence did not cause too much water vapor and heat exchange.

Robust Solution for Boundary Layer Height Detections with Coherent Doppler Wind Lidar

Although coherent Doppler wind lidar(CDWL)is promising in detecting boundary layer height(BLH),differences between BLH results are observed when different CDWL measurements are used as tracers.Here,a robust solution for BLH detections with CDWL is proposed and demonstrated:mixed layer height(MLH)is retrieved best from turbulent kinetic energy dissipation rate(TKEDR),while stable boundary layer height(SBLH)and residual layer height(RLH)can be retrieved from carrier-to-noise ratio(CNR).To study the cause of the BLH differences,an intercomparison experiment is designed with two identical CDWLs,where only one is equipped with a stability control subsystem.During the experiment,it is found that the CNR could be distorted by instrument instability because the coupling efficiency from free-space to the polarization-maintaining fiber of the telescope is sensitive to the surrounding environment.In the ML,a bias up to 2.13 km of the MLH from CNR is found,which is caused by the CNR deviation.In contrast,the MLH from TKEDR is robust as long as the accuracy of wind is guaranteed.In the SBL(RL),the CNR is found capable to retrieve SBLH and RLH simultaneously and robustly.This solution is tested during an observation period over one month.Statistical analysis shows that the root-mean-square errors(RMSE)in the MLH,SBLH,and RLH are 0.28 km,0.23 km,and 0.24 km,respectively.