Two techniques suitable for detecting non-periodic backscatter structures in the SAR images are presented: the Variable Interval Space Averaging (VISA) and the two-dimensional Continuous Wavelet Transform (CWT2) analyses. Both methods have been tested over SAR images taken under different geophysical situations. Despite these techniques require the definition of subjective parameters and the knowledge of the spatial scales of interest, the results indicate that they succeed in the identification of the non-periodic backscatter structures present in the SAR images, which may be referred to the imprint of the atmospheric boundary layer. This will allow the quantitative estimate of the size, number and orientation of the backscatter structures. On the contrary, when periodic structures as the wind rolls are present, only the CWT2 yields good results. An interesting development of these technique will consist of the possibility to distinguish atmospheric from oceanographic features.
Abstract 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 τ fields show that the values falling in the top range 0.15 < τ < 0.20 N m−2 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 τ. 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.
SAR images of sea surface often show roll-vortex structures, which have multiscale character. The present work investigates this aspect, using the two dimensional continuous wavelet transform (CWT2), which appears suitable to extract quantitative information about the structures present in SAR images. CWT2 analysis has been applied to ERS SAR images showing wind rolls, to evaluate the horizontal and vertical scales of the highest backscatter cells. The possibility to produce a SAR-like image at given scale lengths has permitted to evidence the backscatter cells. They have been characterised in terms of the orientation, size of their principal axes, area as well as of the spatial structure of the probability density function. The results may be used to study the inner structure of the atmospheric wind rolls.
Sea surface wind forecasts in the Adriatic Sea often suffer for unadequate modelling, especially for the wind speed. This has detrimental effects on the accuracy of sea level and storm surge predictions. We present a numerical method to reduce the bias between the sea surface wind observed by the scatterometers and that supplied by the European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric model, for storm surge forecasting applications. The method, called “wind bias mitigation”, relies on scatterometer observations to determine a multiplicative factor ∆ws which modulates the standard model wind in order to decrease the bias between scatterometer and model. We compare four different mathematical approaches to this method, for a total of eight different formulations of the multiplicative factor ∆ws. Four datasets are used for the assessment of the eight different bias mitigation methods: a collection of 29 Storm Surge Events (SEVs) cases in the years 2004-2014, a collection of 48 SEVs in the years 2013-2016, a collection of 364 cases of random sea level conditions in the same period, and a collection of the seven SEVs in 2012-2016 that were worst predicted by the Centro Previsioni e Segnalazioni Maree, Comune di Venezia (Tide Forecast and Early Warning Centre of the Venice Municipality - CPSM). The statistical analysis shows that the bias mitigation procedures supplies a mean wind speed more accurate than the standard forecast, when compared with scatterometer observations, in more than 70% of the analyzed cases.
AbstractThe paper investigates the possibility of integrating satellite observations and limited-area atmospheric model simulations in the study of the meso-scale processes in the Mediterranean Sea. A tropical-like cyclone, which occurred on 9 and 10 December 1996 over the central Mediterranean Sea, has been used as a case study. The main features of the cyclone, derived from satellite wind and vertically integrated liquid water content (LWC) fields, have been compared with the results of a limited-area model, obtained with and without scatterometer data assimilation. The results indicate an acceptable comparability of the wind fields, despite the model‐scatterometer wind bias and the misplacement of the cyclone position in the simulations. The vertically integrated quantities, such as the LWC and the model vertically integrated cloud mixing ratio (CWINT), do not show the same degree of comparability. This is because they reflect only large-scale features, whereas the meso-scale features are only detected by the satellite observations. As expected, the results of assimilating the scatterometer data into the model show an improvement over the cyclone positioning but do not provide a better description of its meso-scale features. The lack of improvement in the determination of the CWINT horizontal structure after scatterometer data assimilation indicates the need to assimilate the LWC fields in future studies.Dans cet article, on explore la possibilité d'intégrer les observations satellitaires et les simulations des modèles atmosphériques à surface limitée dans l'étude des processus à méso-échelle en mer Méditerranée. Un cyclone de type tropical, observé entre le 9 et le 10 décembre 1996 au-dessus de la partie centrale de la mer Méditerranée, a servi de cas d'espèce. Les principales caractéristiques du cyclone, dérivées des champs de vent satellitaire et du contenu en eau liquide intégré verticalement (LWC), ont été comparées aux résultats d'un modèle de surface limitée dérivés avec et sans assimilation des données de scattérométrie. Les résultats indiquent une correspondance acceptable dans les champs de vent en dépit du biais modèle-vent de scattérométrie et de la localisation erronée de la position du cyclone dans les simulations. Les quantités intégrées verticalement, telles que le LWC et le ratio du mélange de nuages intégré verticalement du modèle (CWINT), ne montrent pas le même degré de correspondance. Ceci est dû au fait que ces valeurs ne reflètent que les caractéristiques à grande échelle alors que les phénomènes à méso-échelle ne peuvent être décelés qu'au moyen des observations satellitaires. Comme prévu, les résultats de l'assimilation des données de scattérométrie dans le modèle montrent une amélioration dans le positionnement du cyclone mais ne fournit pas une meilleure description de ses caractéristiques à méso-échelle. L'absence d'amélioration dans la détermination de la structure horizontale de la CWINT après assimilation des données de scattérométrie souligne la nécessité d'intégrer également les champs de LWC dans les études futures.[Traduit par la Rédaction]
The alternation of extreme events is a source of great stress on the territory and forces us to adopt solutions to help mitigate their consequences. In this study, an attempt is made to exploit Earth Observation from space as a means to point out the interaction of inland waters and the coastal areas during hydrological extreme events, i.e. floods and droughts. During a flood event, large volume of water from the river reaches the coast, adding a considerable volume of freshwater. Conversely, during a drought event salt water from the sea enters inland causing severe damage to agriculture and the local population. With this study we attempt to investigate how the systems of sea and river interact during particularly intense events using satellite optical (Sentinel-2 and Sentinel-3) and altimeter (Sentinel-3, Cryosat-2, Icesat-2) sensor data. The area selected is the Po River delta (up to 200 km from the mouth), which in recent years has been exposed to severe events: in November 2019, the Po River was subject to a copious flood that had not occurred since 2000, while in the summer of 2022, it experienced the worst drought in the last 70 years. The analysis aims at evaluating three fundamental aspects: 1) the ability of satellite altimetry to identify extreme events in the river; 2) the potential of satellite altimetry to detect salt wedge intrusion in the Po River delta; and 3) the potential correlation between the altimetry observations and optical imagery of the river’s plume along the Adriatic coast. The analysis was conducted by analysing long time series (of about 10 years) for the first objective and by focusing on the drought event of 2022 and the flood events that occurred in the last 5 years for the other two objectives. The results of the analysis confirm that the satellite observed the significant increase and decrease in water levels in correspondence of the extreme events. In addition, the analysis of the data at the virtual stations in the downstream part of the Po River, together with the data along the tracks crossing the plume closer to the mouth of the river, showed the interaction between the sea and the river. In particular, the temporal series of the river clearly highlight the influence of the sea water several km upstream the river (more than 40 km as reported in the news), probably related to the salt wedge intrusion, which has caused significant damage to agriculture and drinking water aquifers for a long time after the event. The study qualitatively shows that extreme hydrological events can also be captured in the open sea in this region. The analysis illustrates the great potential of satellite sensors to monitor extreme events and the interaction of inland and coastal waters.
<p>The relationship between satellite-derived absolute sea level change rates, tide gauge (TG) observations of relative sea level change and global positioning system (GPS) measurements of vertical land motion (VLM) at local scale has been investigated in previous studies [eg. Vignudelli et al., 2018]. The paucity of collocated TG-GPS data and the lack of a well-established mathematical frame in which simultaneous and optimal solutions can be derived, have emphasized the difficulty of deriving spatially-consistent information on the sea level rates. Other studies have claimed the possibility to set locally isolated information into a coherent regional framework using a constrained linear inverse problem approach [Kuo et al., 2004; W&#246;ppelmann and Marcos, 2012].</p><p>The approach cited in the above papers has been recently improved in De Biasio et al. [2020]. A step in advance is now to develop an effective synergistic use of global positioning system (GPS) data, tide gauge measurements and satellite altimetry observations. In this study GPS data are used as a real source of information on the relative Vertical Land Motion (VLM) between pairs of tide gauges, and not as mere term of comparison of the results obtained by differencing relative and absolute sea level observations time series.</p><p>Long, consistent and collocated tide gauge and GPS observations time series are extracted for a handful of suitable coastal locations, and used in the original formulation of the constrained linear inverse problem, together with satellite altimetry data. Some experiments are conducted without GPS observations (traditional setup), and with GPS observations (the new proposed approach) Results are compared in order to assess the impact of GPS observations directly into the formulation of the constrained linear inverse problem.</p><p>The satellite altimetry data-set used in this study is that offered by the European Copernicus Climate Change Service (C3S) through its Climate Data Store archive. It covers the global ocean since 1993 to present, with spatial resolution of 0.25 x 0.25 degrees. This data set is constantly updated and relies only on a couple of simultaneous altimetry missions at a time to provide stable long-term variability estimates of sea level. Tide gauge data are extracted from the Permanent Service for Mean Sea Level archive and from other local sea level monitoring services. GPS vertical position time series and/or VLM rates are taken from the Nevada Geodetic Laboratory and other public GPS repositories.</p><p>REFERENCES</p><p>Vignudelli, S.; De Biasio, F.; Scozzari, A.; Zecchetto, S.; Papa, A. In Proceedings of the International Association of Geodesy Symposia; Mertikas, S.P., Pail, R., Eds.; Springer: Cham, Switzerland, 2020; Volume 150, pp. 65&#8211;74. DOI: 10.1007/1345_2018_51</p><p>Kuo, C.Y.; Shum, C.K.; Braun, A.; Mitrovica, J.X. Geophys. Res. Lett. 2004, 31. DOI: 10.1029/2003GL019106</p><p>W&#246;ppelmann, G.; Marcos, M. J. Geophys. Res. Ocean. 2012, 117. DOI: 10.1029/2011JC007469</p><p>De Biasio, F.; Baldin, G.; Vignudelli, S. J. Mar. Sci. Eng. 2020, 8, 949. DOI: 10.3390/jmse8110949</p>
The northern Adriatic Sea is affected by storm surges, which often cause the flooding in Venice and the surrounding areas. We present the results of the eSurge-Venice project, funded by the European Space Agency (ESA) in the framework of its Data User Element programme: the project was aimed to demonstrate the potential of satellite data in improving storm surge forecasting, with focus on the Gulf of Venice. The satellite data used were scatterometer wind and altimeter sea level height. Hindcast experiments were conducted to assess the sensitivity of a storm surge model to a model wind forcing modified with scatterometer data and to altimeter retrievals assimilated with a dual 4D-Var system. The modified model wind forcing alone was responsible for a reduction of the mean difference between modelled and observed maximum surge peaks from −15.1 to −8.2 cm, while combining together scatterometer and altimeter data the mean difference further reduced to −6.0 cm. In terms of percent, the improvements in the reduction on the mean differences between modelled and observed surge peaks reaches 46% using only the scatterometer data, and 60% using both scatterometer and altimeter data.
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