Global Intermittency and Collapsing Turbulence in the Stratified Planetary Boundary Layer

Direct numerical simulation of the turbulent Ekman layer over a smooth wall is used to investigate bulk properties of a planetary boundary layer under stable stratification. Our simplified configuration depends on two non-dimensional parameters: a Richardson number characterizing the stratification and a Reynolds number characterizing the turbulence scale separation. This simplified configuration is sufficient to reproduce global intermittency, a turbulence collapse, and the decoupling of the surface from the outer region of the boundary layer. Global intermittency appears even in the absence of local perturbations at the surface; the only requirement is that large-scale structures several times wider than the boundary-layer height have enough space to develop. Analysis of the mean velocity, turbulence kinetic energy, and external intermittency is used to investigate the large-scale structures and corresponding differences between stably stratified Ekman flow and channel flow. Both configurations show a similar transition to the turbulence collapse, overshoot of turbulence kinetic energy, and spectral properties. Differences in the outer region resulting from the rotation of the system lead, however, to the generation of enstrophy in the non-turbulent patches of the Ekman flow. The coefficient of the stability correction function from Monin-Obukhov similarity theory is estimated as (Formula presented.) in agreement with atmospheric observations, theoretical considerations, and results from stably stratified channel flows. Our results demonstrate the applicability of this set-up to atmospheric problems despite the intermediate Reynolds number achieved in our simulations. © 2014 The Author(s)

The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAIC) Atmosphere Science Plan

U.S. Department of Energy, Office of ScienceOffice of Biological and Environmental ResearchU.S. Department of Energy, DOE/SC-ARM-18-00

Modelling atmospheric structure, cloud and their response to CCN in the central Arctic : ASCOS case studies

Observations made during late summer in the central Arctic Ocean, as part of the Arctic Summer Cloud Ocean Study (ASCOS), are used to evaluate cloud and vertical temperature structure in the Met Office Unified Model (MetUM). The observation period can be split into 5 regimes; the first two regimes had a large number of frontal systems, which were associated with deep cloud. During the remainder of the campaign a layer of low-level cloud occurred, typical of central Arctic summer conditions, along with two periods of greatly reduced cloud cover. The short-range operational NWP forecasts could not accurately reproduce the observed variations in near-surface temperature. A major source of this error was found to be the temperature-dependant surface albedo parameterisation scheme. The model reproduced the low-level cloud layer, though it was too thin, too shallow, and in a boundary-layer that was too frequently well-mixed. The model was also unable to reproduce the observed periods of reduced cloud cover, which were associated with very low cloud condensation nuclei (CCN) concentrations (< 1 cm(-3)). As with most global NWP models, the MetUM does not have a prognostic aerosol/cloud scheme but uses a constant CCN concentration of 100 cm(-3) over all marine environments. It is therefore unable to represent the low CCN number concentrations and the rapid variations in concentration frequently observed in the central Arctic during late summer. Experiments with a single-column model configuration of the MetUM show that reducing model CCN number concentrations to observed values reduces the amount of cloud, increases the near-surface stability, and improves the representation of both the surface radiation fluxes and the surface temperature. The model is shown to be sensitive to CCN only when number concentrations are less than 10-20 cm(-3)

Acquisition and consolidation of sequential footstep movements with physical and motor imagery practice

International audienceSleep‐dependent performance enhancement has been consistently reported after explicit sequential finger learning, even using motor imagery practice (MIP), but whether similar sleep benefits occur after explicit sequential gross motor learning with the lower limbs has been addressed less often. Here, we investigated both acquisition and consolidation processes in an innovative sequential footstep task performed either physically or mentally. Forty‐eight healthy young participants were tested before and after physical practice (PP) or MIP on the footstep task, following either a night of sleep (PPsleep and MIPsleep groups) or an equivalent daytime period (PPday and MIPday groups). Results showed that all groups improved motor performance following the acquisition session, albeit the magnitude of enhancement in the MIP groups remained lower relative to the PP groups. Importantly, only the MIPsleep group further improved performance after a night of sleep, while the other groups stabilized their performance after consolidation. Together, these findings demonstrate a sleep‐dependent gain in performance after MIP in a sequential motor task with the lower limbs but not after PP. Overall, the present study is of particular importance in the context of motor learning and functional rehabilitation

Fog Regime in Latvia and Factors Affecting it: Case Study-Riga Airport

Fog is a hazardous weather phenomenon, which can impact traffic (especially air traffic) and air quality. The aim of this study is to analyse fog climatology, the trends of long-term changes of fog events and factors affecting them in general, in Latvia, but especially in Riga airport. For a 50-year period of observations, the analysis of the fog frequencies, long-term changes and atmospheric conditions favourable for the occurrence of fog events in Latvia has been studied. During the analysis two inter-annual maxima of fog frequency were found in spring and autumn, and the seasonal differences in the formation of fog were also approved by the satellite data on low cloud cover.