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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.

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; Wöppelmann and Marcos, 2012].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.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.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.REFERENCESVignudelli, 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. 65–74. DOI: 10.1007/1345_2018_51Kuo, C.Y.; Shum, C.K.; Braun, A.; Mitrovica, J.X. Geophys. Res. Lett. 2004, 31. DOI: 10.1029/2003GL019106Wöppelmann, G.; Marcos, M. J. Geophys. Res. Ocean. 2012, 117. DOI: 10.1029/2011JC007469De Biasio, F.; Baldin, G.; Vignudelli, S. J. Mar. Sci. Eng. 2020, 8, 949. DOI: 10.3390/jmse8110949

For the last century, tide gauges have been used to measure sea level change along the world’s coastline. However, tide gauges are heterogeneously distributed and sparse in coverage. The measured sea level changes are also affected by solid-Earth geophysics. Since 1992, satellite radar altimetry technique made possible to measure heights at sea independent of land changes. Recently various efforts started to improve the sea level record reprocessing past altimetry missions to create an almost 30 year-long combined record for sea level research studies. Moreover, coastal altimetry, i.e. the extension of altimetry into the oceanic coastal zone and its exploitation for looking at climate-scale variations of sea level, has had a steady progress in recent years and has become a recognized mission target for present and future satellite altimeters. Global sea level rise is today well acknowledged. On the opposite, the regional and local patterns are much more complicated to observe and explain. Sea level falls in some places and rises in others, as a consequence of natural cycles and anthropogenic causes. As relative sea level height continues to increase, many coastal cities can have the local elevation closer to the flooding line. It is evident that at land-sea interface a single technique is not enough to de-couple land and sea level changes. Satellite radar altimetry and tide gauges would coincide at coast if land had no vertical motion. By noting this fact, the difference of the two independent measurements is a proxy of land motion. In this chapter, we review recent advances in open ocean and coastal altimetry to measure sea level changes close to the coasts over the satellite radar altimetry era. The various methods to measure sea level trends are discussed, with focus on a more robust inverse method that has been tested in the Northern Adriatic Sea, where Global Positioning System (GPS) data are available to conduct a realistic assessment of uncertainties. The results show that the classical approach of estimating Vertical Land Motion (VLM) provides values that are almost half of those provided by the new Linear Inverse Problem With Constraints (LIPWC) method, in a new formulation which makes use of a change of variable (LIPWCCOV). Moreover, the accuracy of the new VLM estimates is lower when compared to the VLM estimated from GPS measurements. The experimental Sea Level Climate Change Initiative (SLCCI) data set (high resolution along track) coastal sea level product (developed within Climate Change Initiative (CCI project) that has been also assessed in the Gulf of Trieste show that the trends calculated with the gridded and along track datasets exhibit some differences, probably due to the different methodologies used in the generation of the products.

Consistent and long-term satellite-based data-sets to study climate-scale variations of sea level globally and in the coastal zone are available nowadays. Two altimetry data-sets were recently produced: the first one is generated by the European Space Agency’s (ESA) Sea Level Climate Change Initiative (SL_CCI) over a grid of 0.25 x 0.25 degrees, merging and homogenizing the various available satellite altimetry missions. The second one is a climate-oriented altimeter sea level product that started in the framework of the European Copernicus Climate Change Service (C3S), and is now released as daily-means over a grid of 0.25 x 0.25 degrees, covering the global ocean since 1993 to present. Both reach in the Arctic the latitude of 81.5 N degrees. Therefore, these new altimetry products cover the coastal area surrounding Ny-Ålesund (Svalbard Islands, Norway), where a tide gauge station is active since 1976. Near the Svalbard coasts also the along track surface elevations of the CryoSat-2 mission are made available through the European Space Agency’s Grid Processing on Demand (G-POD) for Earth Observation Applications facility.In this study, we compare sea level measurements from the Ny-Ålesund tide gauge with the climate-oriented altimeter sea level gridded products (SL_CCI and C3S) and with the along track data from the only CryoSat-2 mission. This study has three objectives: 1) to assess the performances of the gridded data moving from offshore to near coasts; 2) to explore how the synergy with along track high resolution CryoSat-2 data might help to detail the sea ice impact on the observation of relative and absolute sea level rise around Svalbard; 3) to verify if the differences between satellite altimetry and tide gauges can be used as a proxy of vertical ground movement in the study area by adopting the approaches elaborated in Vignudelli et al. [2018] and De Biasio et al. [2020] that can be validated with ground vertical displacements estimated using Global Positioning System (GPS) data from the stations close to Ny-Ålesund. REFERENCESVignudelli, S., De Biasio, F., Scozzari, A. Zecchetto, S., and Papa, A. (2019): Sea Level Trends and Variability in the Adriatic Sea and Around Venice, Proceedings of the International Review Workshop on Satellite Altimetry Cal/Val Activities and Applications, 23-26 April 2018, Chania, Crete, Greece. DOI:10.1007/1345_2018_51De Biasio, F.; Baldin, G.; Vignudelli, S. Revisiting Vertical Land Motion and Sea Level Trends in the Northeastern Adriatic Sea Using Satellite Altimetry and Tide Gauge Data. J. Mar. Sci. Eng. 2020, 8, 949. DOI:10.3390/jmse8110949

Consistent long-term satellite-based data-sets of sea surface elevation exist nowadays to study sea level variability, globally and at regional scales. Two of them are suitable for climate-related studies: one produced in the framework of the European Space Agency (ESA)-funded Sea Level Climate Change Initiative (SL_CCI); the other offered by the European Copernicus Climate Change Service (C3S). Both data-sets cover the global ocean since 1993 to 2015 (SL_CCI) and to present (C3S) at spatial resolution of 0.25 x 0.25 degrees. The first is obtained by merging data from all the available satellite altimetry missions. The second one relies only on a couple of simultaneous altimetry missions at a time to provide stable long-term variability estimates of sea level, is constantly updated and has resolution 0.125 x 0.125 degrees in the Mediterranean Sea.Previous studies have investigated the relationship between satellite-derived absolute sea level change rates and tide gauge observations of relative sea level change in littoral zones of the Mediterranean basin [Fenoglio-Mark, L., 2002; Fenoglio-Mark et al., 2012]. Other studies made use also of global positioning system measurements of vertical land motion in addition to tide gauge and satellite altimetry data [Rocco F.V., 2015; Zerbini et al., 2017]. Vignudelli et al., [2018] highlighted the difficulty of deriving spatially-consistent information on the sea level rates at regional scale in the Adriatic Sea. Other studies have claimed the possibility to merge locally isolated information into a coherent regional picture using a linear inverse problem approach [Wöppelmann and Marcos, 2012]: such approach has been successfully applied to a number of tide gauges in the Adriatic Sea [De Biasio et al., 2020]. The approach tested in the Adriatic Sea is going to be extended to the Mediterranean and major findings will be presented at conference.The motivation of this study is that industrial areas are widely spread along the littoral zone of the southern Europe, and residential settlements are densely scattered along the coasts of the Mediterranean Sea. Not least, a strongly rooted seaside tourism is one of the main economic resources of the region, which is particularly exposed to the sea level variability of both natural and anthropogenic origin. A well known example of such a exposition is Venice (northern Italy) which has been recently hit by the second-highest tide in recorded history (November 2019), and is being protected against storm surges by the MOSE barrier since October 2020. Therefore, a re-analyses of the actual sea level rates with novel methodologies that take into account a better usage of all available observations is key to understand the future coastal sea level changes and their relative importance.Fenoglio-Marc, L. 2002. DOI: 10.1016/S1474-7065(02)00084-0Fenoglio-Marc, L.; Braitenberg, C.; Tunini, L. 2012. DOI: 10.1016/j.pce.2011.05.014Rocco, F.V. Ph.D. Thesis, 2015. URI: https://amslaurea.unibo.it/id/eprint/10172Zerbini, S.; Raicich, F.; Prati, C.M.; Bruni, S.; Conte, S.D.; Errico, M.; Santi, E. 2017. DOI: 10.1016/j.earscirev.2017.02.009Vignudelli, S., De Biasio, F., Scozzari, A. Zecchetto, S., and Papa, A. 2019. DOI:10.1007/1345_2018_51Wöppelmann, G. and Marcos, M. 2012. DOI: 10.1029/2011JC007469De Biasio, F., Baldin, G. and Vignudelli, S. 2020. DOI:10.3390/jmse8110949

The European Space Agency, in the framework of the Sea Level Climate Change Initiative (SL_CCI), is developing consistent and long-term satellite-based data-sets to study climate-scale variations of sea level globally and in the coastal zone. Two altimetry data-sets were recently produced. The first product is generated over a grid of 0.25x0.25 degrees, merging and homogenizing the various satellite altimetry missions. The second product that is still experimental is along track over a grid of 0.35 km. An operational production of climate-oriented altimeter sea level products has just started in the framework of the European Copernicus Climate Change Service (C3S) and a daily-mean product is now available over a grid of 0.125x0.125 degrees covering the global ocean since 1993 to present.We made a comparison of the SL_CCI satellite altimetry dataset with sea level time series at selected tide gauges in the Mediterranean Sea, focusing on Venice and Trieste. There, the coast is densely covered by civil settlements and industrial areas with a strongly rooted seaside tourism, and tides and storm-related surges reach higher levels than in most of the Mediterranean Sea, causing damages and casualties as in the recent storm of November 12th, 2019: the second higher water registered in Venice since 1872. Moreover, in the Venice area the ground displacements exhibit clear negative trends which deepen the effects of the absolute sea level rise.Several authors have pointed out the synergy between satellite altimetry and tide gauges to corroborate evidences of ground displacements. Our contribution aims at understanding the role played by subsidence, estimated by the diffence between coastal altimetry and in situ measurements, on the local sea level rise. A partial validation of these estimates has been made against GPS-derived values, in order to distinguish the contributions of subsidence and eustatism. This work will contribute to identify problems and challenges to extend the sea level climate record to the coastal zone with quality comparable to the open ocean, and also to assess the suitability of altimeter-derived absolute sea levels as a tool to estimate subsidence from tide gauge measurement in places where permanent GPS receivers are not available.

Satellite data are rarely used in storm surge models because of the lack of established methodologies. Nevertheless, they can provide useful information on surface wind and sea level, which can potentially improve the forecast. In this paper satellite wind data are used to correct the bias of wind originating from a global atmospheric model, while satellite sea level data are used to improve the initial conditions of the model simulations. In a first step, the capability of global winds (biased and unbiased) to adequately force a storm surge model are assessed against that of a high resolution local wind. Then, the added value of direct assimilation of satellite altimeter data in the storm surge model is tested. Eleven storm surge events, recorded in Venice from 2008 to 2012, are simulated using different configurations of wind forcing and altimeter data assimilation. Focusing on the maximum surge peak, results show that the relative error, averaged over the eleven cases considered, decreases from 13% to 7%, using both the unbiased wind and assimilating the altimeter data, while, if the high resolution local wind is used to force the hydrodynamic model, the altimeter data assimilation reduces the error from 9% to 6%. Yet, the overall capabilities in reproducing the surge in the first day of forecast, measured by the correlation and by the rms error, improve only with the use of the unbiased global wind and not with the use of high resolution local wind and altimeter data assimilation.

The potential of active microwave satellite observations of sea surface height (radar altimetry) and of sea surface wind (radar scatterometry) has been exploited for storm surge modeling purposes. The altimetry observations were assimilated into a storm surge model (SSM) with a dual 4D-Var system, in order to obtain the best possible surge level field as initial condition to reforecast runs. The scatterometer wind data were instead used to improve the accuracy of the wind fields of a global atmospheric model used as forcing to the SSM through a procedure that has been proved to be able to reduce the differences between the model winds and the scatterometer observations. Hindcast experiments were performed to test the sensitivity of the SSM to the altimetry data assimilation and to the modified wind forcing. Remarkable improvements of the storm surge level hindcast have been obtained for what concerns the modified model wind forcing, while encouraging results have been obtained with the altimeter data assimilation.

This work deals with the spatial characteristics of the wind fields evaluated from synthetic aperture radar (SAR) images and simulated by the weather research and forecasting (WRF) atmospheric model in the Gulf of Oristano, a small coastal area about $10\;\text{km} \times 18\;\text{km}$ wide in western coast of Sardinia (Western Mediterranean Sea). The SAR-derived wind fields have been obtained analyzing images of the COSMO-SkyMed, Radarsat-2, and Sentinel-1A satellites through a fully two-dimensional continuous wavelet transform (2-D-CWT) method. The analysis of the wind directions has shown that the model variability is limited if compared to that inferred by 2-D-CWT method, which mostly respects the variability evidenced by in situ data. As the use of model directions to compute the SAR wind fields is a standard in many studies, the impact on the SAR wind speed retrieval of using the model instead of the SAR-derived directions has been assessed: differences of wind speed greater than $\pm$ 10% occur for about the 20% of data. The spatial variability of the SAR and model wind speed fields results quite different at both local and domain scales. The knowledge of the spatial variations of the surface wind fields can be very important for the oceanographic applications and constitutes the added value brought by SAR in the description of the coastal wind. For this reason, the SAR-derived wind fields should be taken as reference in many kind of applications.

The Adriatic Sea, a semi-enclosed sea extending about 900 km by 200 km and entirely surrounded by mountain chains, is subjected to high water levels produced essentially by the wind blowing along its major axis (sirocco). The operational storm surge models use the forecast fields produced by ECMWF atmospheric model as meteorological forcing. Recent works showed that in small basins surrounded by steep orography the ECMWF model underestimates the wind. This may introduce inaccuracies in forecasting the water level. Experiments conducted in the framework of the “Storm Surge for Venice” (eSurge-Venice) project, funded by the European Space Agency Data User Element program, were aimed to improve the operational forecasting of storm surge in the Northern Adriatic Sea by using satellite observations. The paper presents a methodology aimed to mitigate the ECMWF model underestimate of the sea surface wind by a tuning procedure based on the scatterometer-model wind speed and direction biases. The mitigation takes into account the spatial characteristics of the biases and is time dependent. This method globally reduces the model underestimate of the surface wind, handling the different areas of the basin differently, according to the spatial structure of the bias. The methodology is applied and verified over thirty-three test cases. It may be considered a tool to improve the present high water level forecast, waiting for the advent of convincing methodologies for scatterometer wind assimilation into the regional atmospheric models.

Two case studies of intense lee waves generated by the interaction of the atmospheric flow with the orography over an area in the eastern Mediterranean Sea, located east of Crete and south of Rhodes islands, are analyzed using the Weather Research and Forecasting (WRF) model. The model has been implemented in two different configurations, using distinct boundary layer parametrization schemes, the Yonsei University (YSU) and the Mellor–Yamada–Janjic (MYJ) schemes, and three 2-way nested domains, the inner one covering the area of interest with a horizontal resolution of 1 km. The model-derived wind fields have been compared with the sea surface wind extracted from Envisat Advanced Synthetic Aperture Radar (ASAR) images, from which the wind has been retrieved using a methodology based on the two-dimensional continuous wavelet transform. In the first case, the trains of atmospheric gravity waves, individuated by the signature in the ASAR image, extend downstream for more than 150 km and are realistically simulated in the two model configurations, although some appreciable differences are present. The wavelength spectra of the wind speed from ASAR and the two WRF runs have been calculated along different transects in the area affected by atmospheric gravity waves. The agreement is satisfactory, and the difference in wavelengths among the different wave trains generated by the orographic obstacles is well represented in the model runs. Among the two simulations, the YSU run performs better than MYJ. The latter result is consistent with the fact that the YSU experiment reproduces the observed wind profile and the Scorer parameter profile better than the MYJ run. The second case study is briefly analyzed to test the generality of the results of the first event. In this case, part of the wave energy is distributed at larger scales, due to the interaction of the flow with the Peloponnese. Again, both model configurations are able to reproduce correctly the wave patterns, but in this case the difference between the two model runs is negligible.

The ocean wind vector (OWV) fields retrieved on the Mediterranean and Black seas by satellite-borne microwave active and passive instruments (the ASCAT and QuikSCAT scatterometers and the WindSat polarimetric radiometers) are statistically compared each other. The periods of the comparison vary: from 2003 to 2009 for QuikSCAT and WindSat, and 2009 to 2010 for ASCAT and WindSat. Global and local statistics of the OWV comparisons are performed and shown. Trends are evidenced for some parameters, and a general agreement in the statistical description of the OWV is found. The reason for the study was the need to increase the number of available observations in the Mediterranean Sea to better describe meso-scale f3 (20-200 km, [1]) atmospheric processes and the characteristics of the interaction of the wind flow with the orography.

sull'Elevazione del Livello del Mare Adriatico (SCASELMA) prevede l'implementazione dell'interfaccia di estrazione e visualizzazione dati, gia' realizzata dallo scrivente in appendice al pregresso progetto Sistema per la raccolta ed il confronto dei dati di vento in Adriatico in tempo quasi reale (Vento Da Satellite)1, con la realizzazione di una funzione di ricerca ed estrazione sulla base dati riguardante il vento.

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.

The aim of this work is to evaluate the possibilities offered by the wavelet analysis in the study of the spatial structure of the radar backscatter, which is linked to the spatial structure of the marine atmospheric boundary layer. Continuous wavelet analysis has been applied to a SAR image of the sea surface, previously analysed by the more classical Conditional Sampling technique. The main problem coped with has been to select, among the large number of wavelet maps produced by the analysis (256), those containing the more energetic backscatter structures. Since the phenomenon imaged by SAR was the convective turbulence, a multiscale and quasi-periodic or intermittent process, a selection of wavelet maps according to their mean energy was unsuccessful. On the contrary, a method based on the calculation of the standard deviation of the less probable highest wavelet amplitudes led to a right selection of the wavelet maps and to a convincing reconstruction of the map of backscatter structures, which resulted similar to that provided through the Conditional Sampling.

The paper presents the results of the experiment CAPMOS'05 performed at an offshore oceanographic platform in the Black Sea. The experiment was aimed at air-sea coupling investigations by means of direct and remote measurements. A specialized research platform managed by the Marine Hydrophysical Institute is located on the shelf slope approximately 600m to the south of Crimea coast, Ukraine. Spectral parameters of wind and waves were estimated from direct and remote measurements. The peak frequency of the wind retrieved from radar measurements varied from 0.002 to 0.007 Hz, corresponding to wavelengths between 500 and 7000 m. The spectral peak frequency of gravity waves varied in the range from 0.2 to 0.7 Hz that corresponded to dominating wave lengths from 50 down to several meters. Comparison of two different techniques of wave spectrum retrieval from radar data, and also comparison of radar and radiometric data shows satisfactory agreement.

We present a discussion about the performances of two different methods to derive the wind field from SAR images. These are the method based on the Continuous Wavelet Transform (CWT2) (Zecchetto & De Biasio 2002, 2007) and on the estimation of the Local Gradient (LG) (Koch 2004). The CWT2 method extracts the backscatter signatures in the SAR image likely related to the structure of the marine atmospheric boundary layer; it derives the aliased wind direction from direction of the major axis of the cells-like detected structures and then resolves the ambiguity looking at the backscatter distribution inside them. The LG method divides the image into sub images, depending on the space grid over which the wind is requested; then it defines four image operators which are applied on the images to produce a map of valid points on which the local gradient directions are computed. The local wind direction is orthogonal to the more frequent gradient direction. The wind intensity is computed applying the CMOD4 or CMOD5 models for C-band scatterometer. The results of the two methods are compared with satellite scatterometer winds. They are relevant to ERS images taken over the Mediterranean Sea.