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Observations of turbulence-induced new particle formation in the residual layer
Aerosol particle measurements in the atmospheric boundary layer performed by a helicopter-borne measurement payload and by a lidar system from a case study during the IMPACT field campaign in Cabauw (NL) are presented. Layers of increased number concentrations of ultrafine particles were observed in the residual layer, indicating relatively recent new-particle formation. These layers were characterized by a sub-critical Richardson number and concomitant increased turbulence. Turbulent mixing is likely to lead to local supersaturation of possible precursor gases which are essential for new particle formation. Observed peaks in the number concentrations of ultrafine particles at ground level are connected to the new particle formation in the residual layer by boundary layer development and vertical mixing.
Observation of a Self-Limiting, Shear-Induced Turbulent Inversion Layer Above Marine Stratocumulus
High-resolution measurements of thermodynamic, microphysical, and turbulence properties inside a turbulent inversion layer above a marine stratocumulus cloud layer are presented. The measurements are performed with the helicopter-towed measurement payload Airborne Cloud Turbulence Observation System (ACTOS), which allows for sampling with low true air speeds and steep profiles through cloud top. Vertical profiles show that the turbulent inversion layer consists of clear air above the cloud top, with nearly linear profiles of potential temperature, horizontal wind speed, absolute humidity, and concentration of interstitial aerosol. The layer is turbulent, with an energy dissipation rate nearly the same as that in the lower cloud, suggesting that the two are actively coupled, but with significant anisotropic turbulence at the large scales within the turbulent inversion layer. The turbulent inversion layer is traversed six times and the layer thickness is observed to vary between 37 and 85 m, whereas the potential temperature and horizontal wind speed differences at the top and bottom of the layer remain essentially constant. The Richardson number therefore increases with increasing layer thickness, from approximately 0. 2 to 0. 7, suggesting that the layer develops to the point where shear production of turbulence is sufficiently weak to be balanced by buoyancy suppression. This picture is consistent with prior numerical simulations of the evolution of turbulence in localized stratified shear layers. It is observed that the large eddy scale is suppressed by buoyancy and is on the order of the Ozmidov scale, much less than the thickness of the turbulent inversion layer, such that direct mixing between the cloud top and the free troposphere is inhibited, and the entrainment velocity tends to decrease with increasing turbulent inversion-layer thickness. Qualitatively, the turbulent inversion layer likely grows through nibbling rather than engulfment.
The Turbopause experiment: Atmospheric stability and turbulent structure spanning the turbopause altitude
Very few sequences of high resolution wind and temperature measurements in the lower thermosphere are available in the literature, which makes it difficult to verify the simulation results of models that would provide better understanding of the complex dynamics of the region. To address this problem the Turbopause experiment used four rockets launched over a period of approximately two hours from Poker Flat Research Range, Alaska (64° N, 147° W) on the night of 17–18 February 2009. All four rocket payloads released trimethyl aluminum trails for neutral wind and turbulence measurements, and two of the rockets carried ionization gauges and fixed-bias Langmuir probes measuring neutral and electron densities, small-scale fluctuations and neutral temperatures. Two lidars monitored temperature structure and sodium densities. The observations were made under quiet geomagnetic conditions and show persistence in the wind magnitudes and shears throughout the observing period while being modulated by inertia-gravity waves. High resolution temperature profiles show the winter polar mesosphere and lower thermosphere in a state of relatively low stability with several quasi-adiabatic layers between 74 and 103 km. Temperature and wind data were combined to calculate Richardson number profiles. Evidence for turbulence comes from simultaneous observations of density fluctuations and downward transport of sodium in a mixed layer near 75 km; the observation of turbulent fluctuations and energy dissipation from 87–90 km; and fast and irregular trail expansion at 90–93 km, and especially between 95 to 103 km. The regions of turbulent trails agree well with regions of quasi-adiabatic temperature gradients. Above 103 km, trail diffusion was mainly laminar; however, unusual features and vortices in the trail diffusion were observed up to 118 km that have not been as prevalent or as clearly evident in earlier trail releases.
CFD modelling of an animal occupied zone using an anisotropic porous medium model with velocity depended resistance parameters
The airflow in dairy barns is affected by many factors, such as the barn’s geometry, weather conditions, configurations of the openings, cows acting as heat sources, flow obstacles, etc. Computational fluids dynamics (CFD) has the advantages of providing detailed airflow information and allowing fully-controlled boundary conditions, and therefore is widely used in livestock building research. However, due to the limited computing power, numerous animals are difficult to be designed in detail. Consequently, there is the need to develop and use smart numerical models in order to reduce the computing power needed while at the same time keeping a comparable level of accuracy. In this work the porous medium modeling is considered to solve this problem using Ansys Fluent. A comparison between an animal occupied zone (AOZ) filled with randomly arranged 22 simplified cows’ geometry model (CM) and the porous medium model (PMM) of it, was made. Anisotropic behavior of the PMM was implemented in the porous modeling to account for turbulence influences. The velocity at the inlet of the domain has been varied from 0.1 m s−1 to 3 m s−1 and the temperature difference between the animals and the incoming air was set at 20 K. Leading to Richardson numbers Ri corresponding to the three types of heat transfer convection, i.e. natural, mixed and forced convection. It has been found that the difference between two models (the cow geometry model and the PMM) was around 2% for the pressure drop and less than 6% for the convective heat transfer. Further the usefulness of parametrized PMM with a velocity adaptive pressure drop and heat transfer coefficient is shown by velocity field validation of an on-farm measurement.