We describe a simple, green and controllable approach for electrochemical synthesis of a nanocomposite made up from electrochemically reduced graphene oxide (ERGO) and gold nanoparticles. This material possesses the specific features of both gold nanoparticles and graphene. Its morphology was characterized by scanning electron microscopy which reveals a homogeneous distribution of gold nanoparticles on the graphene sheets. Cyclic voltammetry was used to evaluate the electrochemical properties of this nanocomposite towards dopamine by modification of it on surface of glassy carbon electrode (GCE). Compared to the bare GCE, the electrode modified with gold nanoparticles, and the electrode modified with ERGO, the one modified with the nanocomposite displays better electrocatalytic activity. Its oxidation peak current is linearly proportional to the concentration of dopamine (DA) in the range from 0.1 to 10 μM, with a detection limit of 0.04 μM (at S/N03). The modified electrode also displays good storage stability, reproducibility, and selectivity.

This study provides the first detailed analysis of oceanic and atmospheric responses to the current-stress, wave-stress, and wave-current-stress interactions around the Gulf Stream using a high-resolution three-way coupled regional modeling system. In general, our results highlight the substantial impact of coupling currents and/or waves with wind stress on the air–sea fluxes over the Gulf Stream. The stress and the curl of the stress are crucial to mixed-layer energy budgets and sea surface temperature. In the wave-current-stress coupled experiment, wind stress increased by 15% over the Gulf Stream. Alternating positive and negative bands of changes of Ekman-related vertical velocity appeared in response to the changes of the wind stress curl along the Gulf Stream, with magnitudes exceeding 0.3 m/day (the 95th percentile). The response of wind stress and its curl to the wave-current-stress coupling was not a linear combination of responses to the wave-stress coupling and the current-stress coupling because the ocean and wave induced changes in the atmosphere showed substantial feedback on the ocean. Changes of a latent heat flux in excess of 20 W/m2 and a sensible heat flux in excess of 5 W/m2 were found over the Gulf Stream in all coupled experiments. Sensitivity tests show that sea surface temperature (SST) induced difference of air–sea humidity is a major contributor to latent heat flux (LHF) change. Validation is challenging because most satellite observations lack the spatial resolution to resolve the current-induced changes in wind stress curls and heat fluxes. Scatterometer observations can be used to examine the changes in wind stress across the Gulf Stream. The conversion of model data to equivalent neutral winds is highly dependent on the physics considered in the air–sea turbulent fluxes, as well as air–sea temperature differences. This sensitivity is shown to be large enough that satellite observations of winds can be used to test the flux parameterizations in coupled models.

A high‐resolution three‐dimensional Weather Research and Forecasting (WRF) model is used to investigate the coupled impact of lake surface temperature (LST) and surface wind on the lake effect snow (LES) over the Great Lakes region. A set of twin WRF simulations, with and without resolving LST spatial variations in the model's surface boundary condition, is performed to quantify the impact of LST variation on LES. Both observations and model results reveal a positive correlation between the downwind LST gradient and surface wind convergence over the Great Lakes region. Furthermore, model simulations show that resolving the spatial variation of LST increases the surface wind convergence, correspondingly enhances local vertical motions in the atmospheric boundary layer, and creates favorable conditions for the LES formation on the lee sides of the Great Lakes. The contribution of LST spatial variations to the increase in precipitation on the lee sides of the lakes varies between 5% and 30% in individual LES events. The increase in the winter‐mean snow water equivalent due to LST spatial variations is between 3% and 15%. The most significant impact of LST variation on the winter‐mean snow water equivalent is on the lee side of Lake Huron.

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