The Multi-Scale Layering-Structure of Thermal Microscale Profiles

Thermal microstructure profiling is an established technique for investigating turbulent mixing and stratification in lakes and oceans. However, it provides only quasi-instantaneous, 1-D snapshots. Other approaches to measuring these phenomena exist, but each has logistic and/or quality weaknesses. Hence, turbulent mixing and stratification processes remain greatly under-sampled. This paper contributes to addressing this problem by presenting a novel analysis of thermal microstructure profiles, focusing on their multi-scale stratification structure. Profiles taken in two small lakes using a Self-Contained Automated Micro-Profiler (SCAMP) were analysed. For each profile, buoyancy frequency (N), Thorpe scales (LT), and the coefficient of vertical turbulent diffusivity (KZ) were determined. To characterize the multi-scale stratification, profiles of d2T/dz2 at a spectrum of scales were calculated and the number of turning points in them counted. Plotting these counts against the scale gave pseudo-spectra, which were characterized by the index D of their power law regression lines. Scale-dependent correlations of D with N, LT and KZ were found, and suggest that this approach may be useful for providing alternative estimates of the efficiency of turbulent mixing and measures of longer-term averages of KZ than current methods provide. Testing these potential uses will require comparison of field measurements of D with time-integrated KZ values and numerical simulations.

Uncertainties on plastic concentration estimates at sea

<p>The large difference between the estimates of global plastic input in mass in the oceans (Jambeck et al., Science <strong>347</strong>, 2015) and current global predictions from numerical models (van Sebille et al., Environ. Res. Lett. <strong>10</strong>, 2015) or observations (Cózar et al., P. Natl. Acad. Sci., <strong>111</strong>, 2014) is one of the most important issue regarding oceanic plastic litter. Yet, global predictions are based on observations, and uncertainties on the latter are rarely considered to provide error bounds on the former.</p><p>We discuss here the sources of uncertainties on plastic concentrations estimates (in number and mass), based on a recent model presented in (Poulain et al., Environ. Sci. Technol. <strong>53</strong>, 2019). The two main sources of error are the plastic rise velocity and the model for the turbulent diffusivity, although they do not have the same importance. We validated the model with controlled laboratory experiments. Applying this model to global predictions provides us with more realistic encompassing values for the mass of plastic at sea, with a more important correction concerning small microplastics (with characteristic dimensions smaller than ~1mm).</p>

LES Informed Data-Driven Modelling of a Spatially Varying Turbulent Diffusivity Coefficient in Film Cooling Flows

A novel data-driven approach is used to describe a spatially varying turbulent diffusivity coefficient for the Higher Order Generalised Gradient Diffusion Hypothesis (HOGGDH) closure of the turbulent heat flux to improve upon RANS cooling predictions in film cooling flows. Machine learning algorithms are trained on two film cooling flows and tested on a case of a different density and blowing ratio. The Random Forests and Neural Network algorithms successfully reproduced the LES described coefficient and the magnitude of the turbulent heat flux vector. The Random Forests model was implemented in a steady RANS solver with a k-ω SST turbulence model and applied to four cases. All cases saw improvements in the predicted Adiabatic Cooling Effectiveness (ACE) over the cooled surface compared to the standard Gradient Diffusion Hypothesis (GDH) approach, but only minor improvements in the centreline and lateral spread are seen compared to a HOGGDH model with a constant cθ of 0.6. Further improvements to cooling predictions are highlighted by extending these data-driven approaches into turbulence modelling to improve flow field predictions.

Effects of large scale advection and small scale turbulence on vertical phytoplankton dynamics

<p>When studying the life cycle of phytoplankton frequently one is interested in the survival or death conditions of a population (bloom/no bloom). These dynamics have been studied extensively in the literature through a range of modelling scenarios but in summary the main factors affecting the vertical dynamics are: Water column mixing intensity, solar energy distribution, nutrients availability and predatory activity. The later two can be represented by different biological models whereas the vertical mixing is usually parameterized by a diffusive process. Even though turbulence has been recognized as a paramount factor in the survival dynamics of sinking phytoplankton species, dealing with the multi scale nature of turbulence is a formidable challenge from the modelling point of view. In addition, convective motions are being recognized to play a role in the survival of phytoplankton throughout winter stocking. With this in mind, in this work we revisit a theoretically appealing  model for phytoplankton vertical dynamics with turbulent diffusivity and numerically study how large-scale fluid motions affect its survival and extinction conditions. To achieve this and to work with realistic parameter values, we adopt a kinematic flow field to account for the different spatial and temporal scales of turbulent motions. The dynamics of the population density are described by a reaction-advection-diffusion model with a growth term proportional to sun light availability. Light depletion is modelled accounting for water turbidity and plankton self-shading; advection is represented by a sinking speed and a two-dimensional, multiscale, chaotic flow. Preliminary results show that under appropriate conditions for the flow, our model reproduces past results based on turbulent diffusivity. Furthermore, the presence of large scale vortices (such as those one might expect during winter convection) seems to hinder survival, an effect that is partially mitigated by turbulent  diffusion.</p>

Avaliação da dependência dos parâmetros de ajuste de um modelo E − l com a estratificação térmica estável

One of the main challenges of the atmospheric model is the proper determination of the turbulent diffusivity. In this sense, variousboundary layer parametrization have been developed along of the years. For the same closure order, many times, the bigger differences between them, are concentrated in the adjustment parameters. From the adequate physical description, to find the real value of each constant is the great challenge of the models. Them, the present work compare three different parametrization for the non-dimensional relation u2 ∗=E, that is used as a constant in the momentum diffusion coefficient in the E - l models. In the comparison with the GABLS experiment, the results show that the constant does not have a great influence over the windcomponents and over the temperature. On the other hand, the constant have a fundamental role in the behavior of the turbulence kinetic energy. This is due the fact of the constant is also present in the turbulence viscous dissipation term. Finally, it is important to stress that this is a work that is in its beginning and it aims the construction of a boundary layer parameterization for climate and weather forecasting models.