Thus far, methods that give quantitative information about lateral interactions in membranes have been restricted peptides or simplified protein constructs studied in detergents, lipid vesicles or bacterial membranes. None of the available methods have been extended to complex or full length membrane proteins. Here we show how free energies of membrane protein dimerization can be measured in mammalian plasma membrane-derived vesicles. The measurements, performed in single vesicles, utilize the Quantitative Imaging FRET (QI-FRET) method. The experiments are described in a step-by-step protocol. The protein characterized is the transmembrane domain of Glycophorin A, the most extensively studied membrane protein, known to form homodimers in hydrophobic environments. The results suggest that molecular crowding in cellular membranes has a dramatic effect on the strength of membrane protein interactions.

Winds and waves in marine boundary layers are often in an unsettled state when fast-running swell generated by distant storms propagates into local regions and modifies the overlying turbulent fields. A large-eddy simulation (LES) model with the capability to resolve a moving sinusoidal wave at its lower boundary is developed to investigate this low-wind/fast-wave regime. It is used to simulate idealized situations with wind following and opposing fast-propagating waves (swell), and stationary bumps. LES predicts momentum transfer from the ocean to the atmosphere for wind following swell, and this can greatly modify the turbulence production mechanism in the marine surface layer. In certain circumstances the generation of a low-level jet reduces the mean shear between the surface layer and the PBL top, resulting in a near collapse of turbulence in the PBL. When light winds oppose the propagating swell, turbulence levels increase over the depth of the boundary layer and the surface drag increases by a factor of 4 compared to a flat surface. The mean wind profile, turbulence variances, and vertical momentum flux are then dependent on the state of the wave field. The LES results are compared with measurements from the Coupled Boundary Layers Air-Sea Transfer (CBLAST) field campaign. A quadrant analysis of the momentum flux from CBLAST verifies a wave age dependence predicted by the LES solutions. The measured bulk drag coefficient C D then depends on wind speed and wave state. In situations with light wind following swell, C D is approximately 50% lower than values obtained from standard bulk parameterizations that have no sea state dependence. In extreme cases with light wind and persistent swell, C D Ͻ 0.

Observations from a suite of platforms deployed in the coastal ocean are being combined with numerical models and simulations to investigate the processes that couple the atmosphere and ocean.

Understanding the physical mechanisms behind the generation of ocean waves by wind has been a longstanding challenge. Previous studies have assumed that ocean waves induce fluctuations in velocity and pressure of the overlying air that are synchronized with the waves, and numerical models have supported this assumption. In a complex feedback, these fluctuations provide the energy for wave generation. The spatial and temporal structure of the wave-induced airflow therefore holds the key to the physics of wind-wave coupling, but detailed observations have proved difficult. Here we present an analysis of wind velocities and ocean surface elevations observed over the open ocean. We use a linear filter to identify the wave-induced air flow from the measurements and find that its structure is in agreement with 'critical-layer' theory. Considering that the wave-induced momentum flux is then controlled by the wave spectrum and that it varies considerably in vertical direction, a simple parameterization of the total air-sea momentum flux is unlikely to exist.

We present a method to study the coupling and synchronization of two chaotic systems -the surface gravity waves in the open ocean and the turbulent air flow above. Our approach employs an eikonallike representation of the wave field based on the concept of an analytic signal and the Hilbert transform. We identify a wave-coherent component in the air flow which is phase locked with the waves and deeply buried in turbulence. That component contributes most of the wind-wave energy and momentum exchange, so its identification from actual data is of primary interest. We define and obtain the phase shifts of the wave-coherent fields and discuss their roles in the wind wave exchange.[S0031-9007(98)07829-6] PACS numbers: 92.10. Hm, 47.27.Eq, 47.35. + i, 47.52. + j Cooperative behavior plays a major role in a variety of chaotic systems, but it may be hard to identify and quantify. A good example is the coupling between ocean surface waves (which are not periodic) and the randomly fluctuating turbulent wind above, where a small (relative to the turbulent fluctuations) wave-coherent component in the wind is believed to carry most of the wind-wave interaction. Today's climate and weather forecasting models are built on assumptions (many of which are untested experimentally, [1]) about the mechanisms and intensity of the exchange of kinetic energy and momentum between the ocean and the atmosphere. In spite of decades-long efforts, starting from Jeffreys in 1924 [2], expanded by Miles [3] and Phillips [4], and recent advances in [5,6], current knowledge regarding wind-wave interactions is limited due to experimental and theoretical difficulties [1,7,8]. The wide inconsistency among the experimental estimates for the wind-wave energy exchange [8], possibly amplified by the lack of technique to extract the wave-coherent component in the air flow, as well as the absence of field data for the wave-induced Reynolds stresses (which impedes the closure modeling) are some of those difficulties. Laboratory experiments on wind-wave coupling do not reproduce the scales and conditions over the open ocean [9], so the field experiments remain as relevant and necessary components of this research. In this study we use data from the marine boundary layers experiment, which took place 50 kilometers off the coast of California on the stable floating instrument platform (FLIP). The instruments were positioned at fixed heights from 2.7 to 18.1 m above the interface and the wave height was registered directly beneath them.Intuitively, one might expect that the fluctuations of velocity and pressure in the air flow over waves are of two kinds, originating either from the shear-driven turbulence, or induced by the underlying waves. Assuming that the two kinds of fluctuations are weakly coupled, the flow velocity u ϵ ͑u, y, w͒ and pressure p can be decomposed into mean, turbulent, and wave-induced components, u u 1 u 0 1ũ and p p 1 p 0 1p. The turbulent pressure fluctuations p 0 can lead to wave growth through a random walk process [4], but their c...