This paper investigates the mean spatial features of the winds in the Mediterranean and Black Seas using the wind fields observed by the SeaWinds scatterometer. Five years (2000-04) of data have been analyzed on annual and seasonal basis, with particular attention paid to the meso-and local scales. The fields show the existence of structured regional wind systems-in particular, the mistral in the western Mediterranean and the etesians in the Levantine Basin, which are characterized, respectively, by high wind variability and moderate steadiness and by low wind variability and high steadiness. Estimated seasonal mean wind stress fields show that the values falling in the top range 0.15 Ͻ Ͻ 0.20 N m Ϫ2 affect a large portion of the Mediterranean Basin in winter, in the belt extending from the Gulf of Lion up to the Levantine Basin and the northern Black Sea. In the other seasons, only few regions experience such high values of . The analysis of the wind vorticity shows and quantifies the main cyclonic and anticyclonic circulations, and the study of the joint features of wind stress and vorticity has identified the strongest and most persisting local-scale wind circulations produced by the interaction between the wind flow and the orography. They occur at the lee side of Sardinia-Corse and Crete-Rhodos Islands and persist in all seasons, with some seasonal variation in strength and extent. The areas affected by the orographic disturbances are characterized by high values of wind stress and by a structure of vorticity showing alternating areas of cyclonic and anticyclonic circulations, whose strength is comparable to those of the regional-scale cyclones.
A light-like Wilson loop is computed in perturbation theory up to O(g 4 ) for pure Yang-Mills theory in 1+1 dimensions, using Feynman and light-cone gauges to check its gauge invariance. After dimensional regularization in intermediate steps, a finite gauge invariant result is obtained, which however does not exhibit abelian exponentiation. Our result is at variance with the common belief that pure YangMills theory is free in 1+1 dimensions, apart perhaps from topological effects.
We present the follow-up of our previously published work, where we described a wavelet-based method to characterize the sea surface backscatter structures in Synthetic Aperture Radar (SAR) images. The method relies on the ability of the 2-D continuous wavelet technique to detect the spatial structure of the Marine Atmospheric Boundary Layer (MABL) and to isolate wind-related cells and features. The analysis of the cells' geometry, molded by the radiometric characteristics of the sea surface, permits the identification of the wind direction inside the cells, due to the along-wind asymmetry of backscatter structures, and thus the computation of the wind speed through standard algorithms. Twenty-one SAR images (ERS-2 and Envisat ASAR Wide Swath) over the Mediterranean Sea have been analyzed, and the results are compared with satellite wind fields. The images cover a range of meteorological conditions from low to moderate winds. Comparison of the SAR-derived wind fields with those provided by satellite scatterometers indicates a good score of success (roughly 70%-80%). The developed methodology, once tested over an adequate number of images to derive statistically reliable results, could be routinely used to enrich SAR images with the wind field as well as to characterize the MABL in terms of size, distribution, and shape of the backscatter cells.
In this work we investigated the predictability of the wind‐induced sea surface transport in coastal areas. The wind fields predicted by two state‐of‐the‐art meteorological models, namely ECMWF and SKIRON, were used as forcing for a hydrodynamic and particle‐tracking model applied to reproduce a set of observed drifters trajectories in a coastal area of the Mediterranean Sea. A set of anemometric data derived by in situ measurements were also adopted as model forcing to reproduce the observed drifter paths. This approach provided a baseline that was used as a reference for evaluating the effects of the predicted wind accuracy on the numerical model solution. The accuracy of the simulation results obtained using, as model forcing, the observed wind data was fair and suitable for most of the operational oceanographic purposes. It decreased when using the wind data predicted by the two meteorological models. In particular, the results obtained using ECMWF data were about 3 times more accurate than the ones obtained using SKIRON ones. The uncertainties were strongly dependent on the range of observed wind speed classes with a different behavior depending on the type of adopted wind data. Finally, the amplification of the errors in predicting the sea surface transport generated by the inaccuracies of the predicted wind fields was quantified.
We propose a revisited approach to estimating sea level change trends based on the integration of two measuring systems: satellite altimetry and tide gauge (TG) time series of absolute and relative sea level height. Quantitative information on vertical crustal motion trends at six TG stations of the Adriatic Sea are derived by solving a constrained linear inverse problem. The results are verified against Global Positioning System (GPS) estimates at some locations. Constraints on the linear problem are represented by estimates of relative vertical land motion between TG couples. The solution of the linear inverse problem is valid as long as the same rates of absolute sea level rise are observed at the TG stations used to constrain the system. This requirement limits the applicability of the method with variable absolute sea level trends. The novelty of this study is that we tried to overcome such limitations, subtracting the absolute sea level change estimates observed by the altimeter from all relevant time series, but retaining the original short-term variability and associated errors. The vertical land motion (VLM) solution is compared to GPS estimates at three of the six TGs. The results show that there is reasonable agreement between the VLM rates derived from altimetry and TGs, and from GPS, considering the different periods used for the processing of VLM estimates from GPS. The solution found for the VLM rates is optimal in the least square sense, and no longer depends on the altimetric absolute sea level trend at the TGs. Values for the six TGs’ location in the Adriatic Sea during the period 1993–2018 vary from −1.41 ± 0.47 mm y−1 (National Research Council offshore oceanographic tower in Venice) to 0.93 ± 0.37 mm y−1 (Rovinj), while GPS solutions range from −1.59 ± 0.65 (Venice) to 0.10 ± 0.64 (Split) mm y−1. The absolute sea level rise, calculated as the sum of relative sea level change rate at the TGs and the VLM values estimated in this study, has a mean of 2.43 mm y−1 in the period 1974–2018 across the six TGs, a mean standard error of 0.80 mm y−1, and a sample dispersion of 0.18 mm y−1.
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