The Impacts of Gustiness on Air–Sea Momentum Flux

The exchange of momentum across the air–sea boundary is an integral component of the earth system and its parametrization is essential for climate and weather models. This study focuses on the impact of gustiness on the momentum flux using three months of direct flux observations from a moored surface buoy. Gustiness, which quantifies the fluctuations of wind speed and direction, is shown to impact air–sea momentum fluxes. First, we put forward a new gustiness formula that simultaneously evaluates the impact of fluctuations in wind direction and speed. A critical threshold is established using a cumulative density function to classify runs as either gusty or non-gusty. We find that, during runs classified as gusty, the aerodynamic drag coefficient is increased up to 57% when compared to their non-gusty counterparts. This is caused by a correlated increase in vertical fluctuations during gusty conditions and explains variability in the drag coefficient for wind speeds up to 20 m/s. This increase in energy is connected with horizontal fluctuations through turbulent interactions between peaks in the turbulent spectra coincident with peaks in the wave spectra. We discus two potential mechanistic explanations. The results of this study will help improve the representation of gustiness in momentum flux parameterizations leading to more accurate ocean models.

Multiscale Solar Wind Turbulence Properties inside and near Switchbacks measured by Parker Solar Probe

<p>Parker Solar Probe (PSP) routinely observes magnetic field deflections in the solar wind at distances less than 0.3 au from the Sun. These deflections are related to structures commonly called 'switchbacks' (SBs), whose origins and characteristic properties are currently debated. Here, we use a database of visually selected SB intervals - and regions of solar wind plasma measured just before and after each SB - to examine plasma parameters, turbulent spectra from inertial to dissipation scales, and intermittency effects in these intervals. We find that many features, such as perpendicular stochastic heating rates and turbulence spectral slopes are fairly similar inside and outside of SBs. However, important kinetic properties, such as the characteristic break scale between the inertial to dissipation ranges differ inside and outside these intervals, as does the level of intermittency, which is notably enhanced inside SBs and in their close proximity, most likely due to magnetic field and velocity shears observed at the edges. We conclude that the plasma inside and outside of a SB, in most of the observed cases, belongs to the same stream, and that the evolution of these structures is most likely regulated by kinetic processes, which dominate small scale structures at the SB edges. </p>

Low-Altitude Atmospheric Turbulence Sounding on the Basis of Unmanned Aerial Vehicle

Based on the theory of turbulence, equations are derived for estimations of turbulent fluctuations of the longitudinal and transverse components of the wind velocity during ideal hovering of a quadcopter in a turbulent atmosphere. We present the results of experiments which were carried out on the territory of the Geophysical Observatory of Institute of Monitoring of Climatic and Ecological Systems, Siberian Branch, Russian Academy of Sciences, located in Tomsk Akademgorodok on the territory with complex orography, in a parkland zone with buildings of research institutes and motorways. Time series of turbulent fluctuations of the longitudinal and transverse components of wind velocity fluctuations were received with the use of an automated weather station, and time series of estimates of these components, from data of a DJI Phantom 4 Pro quadcopter during hovering. According to the automated weather station data, anisotropy was observed in one experiment during measurements in the atmosphere, but this phenomenon was not observed in the other experiment: the fluctuation spectra of all components of wind speed fluctuations coincide. The spectra of fluctuations of the longitudinal and transverse wind velocity components based on the automated weather station data and UAV telemetry are presented. The fluctuation spectra of these components for the automated weather station data and quadcopter generally coincide. The behavior of the spectra coincides with the spectrum which corresponds to Kolmogorov–Obukhov “–5/3” law within the inertial range. The turbulent spectra of the wind velocity fluctuations obtained with the use of the automatic weather station and with the unmanned aerial vehicle differ in the high-frequency spectral region.