New parameterizations for the spectral dissipation of wind-generated waves are proposed. The rates of dissipation have no predetermined spectral shapes and are functions of the wave spectrum, in a way consistent with observation of wave breaking and swell dissipation properties. Namely, swell dissipation is nonlinear and proportional to the swell steepness, and wave breaking only affects spectral components such that the non-dimensional spectrum exceeds the threshold at which waves are observed to start breaking. An additional source of short wave dissipation due to long wave breaking is introduced, together with a reduction of wind-wave generation term for short waves, otherwise taken from Janssen (J. Phys. Oceanogr. 1991). These parameterizations are combined and calibrated with the Discrete Interaction Approximation of Hasselmann et al. (J. Phys. Oceangr. 1985) for the nonlinear interactions. Parameters are adjusted to reproduce observed shapes of directional wave spectra, and the variability of spectral moments with wind speed and wave height. The wave energy balance is verified in a wide range of conditions and scales, from the global ocean to coastal settings. Wave height, peak and mean periods, and spectral data are validated using in situ and remote sensing data. Some systematic defects are still present, but the parameterizations probably yield the most accurate overall estimate of wave parameters to date. Perspectives for further improvement are also given.

No abstract

[1] Global observations of ocean swell, from satellite Synthetic Aperture Radar data, are used to estimate the dissipation of swell energy for a number of storms. Swells can be very persistent with energy e-folding scales exceeding 20,000 km. For increasing swell steepness this scale shrinks systematically, down to 2800 km for the steepest observed swells, revealing a significant loss of swell energy. This value corresponds to a normalized energy decay in time b = 4.2 Â 10 À6 s À1 . Many processes may be responsible for this dissipation. The increase of dissipation rate in dissipation with swell steepness is interpreted as a laminar to turbulent transition of the boundary layer, with a threshold Reynolds number of the order of 100,000. These observations of swell evolution open the way for more accurate wave forecasting models, and provide a constraint on swell-induced air-sea fluxes of momentum and energy.

[1] The median Doppler shift of radar echoes is analyzed in measurements by ENVISAT's Advanced Synthetic Aperture Radar (ASAR) over the ocean. This Doppler centroid differs from a predicted signal based on the predicted motion of the satellite and Earth. This anomaly, converted to a surface Doppler velocity U D , appears to be of geophysical origin. Two wide-swath images over the Gulf Stream around Cape Hatteras suggest that U D contains high-resolution information on surface currents, while on a global scale, U D is found to vary with the wind speed in the range direction. A simple quantitative forward model is proposed, based on a practical two-scale decomposition of the surface geometry and kinematics. The model represents the effect of the wind through the wave spectrum, and gives U D % gU 10k + U ck , with U 10k and U ck as the 10 m wind speed and quasi-Eulerian current in the line of sight of the radar projected on the sea surface, respectively, and g as a coefficient function of the wind speed, wave development, and radar geometry. It is found that for an incidence angle of 23°, g % 0.3 for moderate winds and fully developed seas. This model is validated with a global data set of ASAR Wave Mode observations, with colocated model winds, acquired over the global ocean during the years 2003 and 2004. The Doppler signal therefore provides the signed parameter U D that can be used to reduce the wind direction ambiguity in the inversion of high-resolution wind fields from SAR imagery. A qualitative validation of current effects is shown for the English Channel where tidal currents dominate. Thus it should be possible to combine this previously ignored geophysical Doppler signal with traditional information on sea surface roughness, in order to provide very high resolution wind and current fields.Citation: Chapron, B., F. Collard, and F. , Direct measurements of ocean surface velocity from space: Interpretation and validation,

The synthetic aperture radar (SAR) Doppler centroid has been used to estimate the scatter line-of-sight radar velocity. In weak to moderate ocean surface current environment, the SAR Doppler centroid is dominated by the directionality and strength of wave-induced ocean surface displacements. In this paper, we show how this sea state signature can be used to improve surface wind retrieval from SAR. Doppler shifts of C-band radar return signals from the ocean are thoroughly investigated by colocating wind measurements from the ASCAT scatterometer with Doppler centroid anomalies retrieved from Envisat ASAR. An empirical geophysical model function (CDOP) is derived, predicting Doppler shifts at both VV and HH polarization as function of wind speed, radar incidence angle, and wind direction with respect to radar look direction. This function is used into a Bayesian inversion scheme in combination with wind from a priori forecast model and the normalized radar cross section (NRCS). The benefit of Doppler for SAR wind retrieval is shown in complex meteorological situations such as atmospheric fronts or low pressure systems. Using in situ information, validation reveals that this method helps to improve the wind direction retrieval. Uncertainty of the calibration of Doppler shift from Envisat ASAR hampers the inversion scheme in cases where NRCS and model wind are accurate and in close agreement. The method is however very promising with respect of future SAR missions, in particular Sentinel-1, where the Doppler centroid anomaly will be more robustly retrieved.Index Terms-Doppler, surface wind, synthetic aperture radar (SAR).

[1] Satellite synthetic aperture radar (SAR) observations can provide a global view of ocean swell fields when using a specific ''wave mode'' sampling. A methodology is presented to routinely derive integral properties of the longer-wavelength (swell) portion of the wave spectrum from SAR level 2 products and both monitor and predict their evolution across ocean basins. SAR-derived estimates of swell height and energy-weighted peak period and direction are validated against buoy observations, and the peak directions are used to project the peak periods in one dimension along the corresponding great circle route, both forward and back in time, using the peak period group velocity. The resulting real-time data set of great circle-projected peak periods produces two-dimensional maps that can be used to monitor and predict the spatial extent and temporal evolution of individual ocean swell fields as they propagate from their source region to distant coastlines. The result is found to be consistent with the dispersive arrival of peak swell periods at a midocean buoy. The simple great circle propagation method cannot project the swell heights in space like the peak periods, because energy evolution along a great circle is a function of the source storm characteristics and the unknown swell dissipation rate. A more general geometric optics model is thus proposed for the far field of the storms. This model is applied here to determine the attenuation over long distances. For one of the largest recorded storms, observations of 15 s period swells are consistent with a constant dissipation rate that corresponds to a 3300 km e-folding scale for the energy. In this case, swell dissipation is a significant term in the wave energy balance at global scales.Citation: Collard, F., F. Ardhuin, and B. Chapron (2009), Monitoring and analysis of ocean swell fields from space: New methods for routine observations,

Banking crises are rare events that break out in the midst of credit intensive booms and bring about particularly deep and long-lasting recessions. This paper attempts to explain these phenomena within a textbook DSGE model that features a non-trivial banking sector. In the model, banks are heterogeneous with respect to their intermediation skills, which gives rise to an interbank market. Moral hazard and asymmetric information in this market may lead to sudden interbank market freezes, banking crises, credit crunches and, ultimately, severe recessions. The model can potentially generate various types of banking crises. But the typical crisis breaks out endogenously, during a credit boom generated by a sequence of small positive supply shocks; it does not result from a large negative exogenous shock. Simulations of a calibrated version of the model indicate that it can mimic the main dynamic patterns of banking crises.

No abstract