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The north Adriatic basin experiences notable sea level variability induced by the atmospheric forcing on different time scales. The occurrence of sea level extreme events has increased over the last decades in connection with the mean sea level rising trend, and the coastal communities are becoming more and more sensitive to sea level changes.The observed sea level is the result of the superposition of contributions connected with different forcing factors. The sea level extreme events can be determined mainly by one of such components or by the interaction of some of them. On the basis of characteristic time scales, we identify and extract the sea level components connected with: the astronomical tide; the meteorological forcing, that is synoptic-scale atmospheric variations, mesoscale atmospheric disturbances, meteotsunamis, and planetary atmospheric waves; seasonal to inter-decadal variability, that is changes of large-scale atmospheric and oceanic circulations. The main Adriatic seiches, generally triggered by storm surges, and the long-term sea level variations, related to climate change, are also taken into account.Recent sea level archaeology activity has allowed to extend and revise the sea level time series of the tide-gauge station of Trieste, Molo Sartorio. As a result, hourly sea level elevations for the 1905-2022 period are now available.Thanks to this long time series, we study the variability of the sea level extreme events and their components during more than a century, with focus on the time variability and the relative importance of the components during major events., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

While confidence in estimating air-sea CO? fluxes in open sea environments is increasing, a large uncertainty remains in defining the role played by coastal ecosystems as CO? sinks or sources. This is due to their highly variable oceanographic and climatic characteristics and to the effects of continental inputs. Within ICOS-OTC network, the PALOMA station, (Northern Adriatic Sea), is continuously collecting sea surface pCO? data since 2012. In the framework of JERICO-NEXT project, PALOMA is working together with several stations located in European coastal seas to explore the role of biological and atmospheric drivers in determining the observed pCO? variability. In this work, we present and discuss the effects of meteorological conditions on CO? air-sea fluxes, using the data collected in four wintry seasons from 2012 to 2016. In winter 2012-2013, the presence of lower temperatures and the occurrence of several events of Bora (wind speed > 15 ms?¹) produced a decrease of the SST down to 8.3 C leading to more favorable conditions for CO? absorption. The following winter was characterized by a higher air temperature, weaker winds, intense precipitation and river discharges larger than the average of the previous decade. These distinct hydrological and meteorological conditions significantly affected the sea surface pCO? that was lower in 2012-2013 (median pCO? ? 324 ± 8.9 ?atm) than in 2013-2014 (median pCO? ? 343 ± 9.0 ?atm). Sea always absorbed CO? from the atmosphere, but average daily fluxes were almost doubled during the colder winter 2012-2013 (F ? - 6.4 mmol-CO? m²d?¹) than in the milder winter 2013-2014 (F ? -3.7 mmol-CO? m²d?¹). Our results highlight the sensitivity of the CO? sink in the northern Adriatic to changes in the meteorological conditions and suggest that its capability of sequestering CO? could dramatically decrease in the next decades under a climate change scenario.

The Northern Adriatic is a shallow, semi-enclosed sub-basin surrounded by an industrialized area in the northernmost part of the Mediterranean. The basin can be affected by intense air sea fluxes (gas, heat and water) and significant ecosystem changes. Dense water may form during winter (Northern Adriatic Dense Water, density anomalies > 29.2 kg m?³) and spread to the South along the Italian coast. Consequently the North Adriatic Sea seems interesting to the ICOS targets and the site in Gulf of Trieste, equipped for marine CO? measurements, was included in the ICOS Italy network. In the last few decades, ocean acidification of locally formed dense waters was estimated by non continuous data, spanning 25 years (Luchetta et al. 2010), thus indicating the area is prone to absorb CO? during winter. Then (2008), time series of the main physical and biogeochemical parameters (T, S, DO, nutrients, pH, TA, TOC) started being collected once per month by the fixed station (PALOMA) in the centre of the Gulf of Trieste. Gathered data indicate that dissolved CO? is driven by the sea temperature, the Gulf of Trieste is under saturated (290

The time series of GPS coordinates, in general, are affected by the superposition of different long- and short- period signals which shall be identified and their physical nature needs to be understood. Examples are long-period tectonic variations, effects of climatic origin and short- period seasonal fluctuations. In addition to these variations, discontinuities are commonly observed that impair the estimate of trends. These abrupt shifts can be originated by changes of the station equipment and/or the reference system, by the occurrence of earthquakes and, likely, by a number of unforeseen events. The magnitude of these jumps shall be estimated and the series corrected accordingly. There exists several methods allowing to detect discontinuities in the time series and to estimate their relevant magnitude. Typically, these adopt hypothesis-driven analyses, meaning, for example, that the detection of a jump resulting from a documented event (e.g. instrumentation change, earthquakes etc.) is accomplished through the a priori knowledge of the event timing. We have studied time series of GPS coordinates characterized by several jumps due to different reasons by means of a method known as Sequential t-Test Analysis of Regime Shift (STARS) developed by Rodionov (Geophys. Res. Lett., 31, L09204, 2004). This technique does not make any a priori assumption on the time series. A discontinuity or jump is detected, and its magnitude is estimated, when the time series mean value exhibits a significant change. Since the approach belongs to the sequential/exploratory type of statistical methods, jumps are detected as soon as they appear in the series. Two parameters are required, namely a cut-off length, which allows selecting the fluctuations time scales, and a significance level, used in the statistical t-test upon which the STARS algorithm is based. We have investigated the coordinates time series of several stations located in northeastern Italy, including those of the BOLG and MSEL Euref stations.

Hydrological mass variations are known to play a major role in the seasonal height and gravity variability. On longer time scales, climate-related variations of GPS height and gravity have not yet been clearly identified mainly because of the limited temporal extent of most of the continuous series and for the lack of information on spatial and temporal variability of groundwater storage. Continuously recording GPS stations with relatively long time series are available in northeastern Italy. This area is affected by both natural and human-induced subsidence; the natural rate decreases from the southern part, where even exceeds 2 mm/yr towards the north. At local scale, anthropogenic effects may enhance significantly the natural tendency. Additionally, the coastal areas are threatened by rising sea level. We have studied GPS height, gravity and hydrological time series by using the Empirical Orthogonal Functions and Singular Value Decomposition analyses. Significant common patterns in the spatial and temporal variability of these parameters have been identified. In particular, hydrology-induced variations are clearly observable starting 2002 in the southern part of the Po Plain for the longest time series, and from 2005 over the whole area. Observing and modeling long- and short-period signals in the height and gravity time series allows to better understand and quantify subsidence. This knowledge is important because of the relevant societal impacts of this phenomenon.

The effect of nontidal ocean loading (NTOL) is observed in the height series of four permanent GPS stations in the northern Adriatic. A validation of the ECCO model is performed by comparing model estimates of sea-level anomalies from tide-gauges with TOPEX/ POSEIDON data, and ECCO model estimates of bottom pressure with those derived from temperature and salinity observations. The amplitudes of theECCO sea-level anomaly are found to be 1.4 times smaller than observations; bottom pressure is 2 times smaller. Using a Green’s functions approach to determine elastic deformations, the ECCO ocean bottom pressure is used to estimate surface displacements at the GPS sites. Model results were compared with the height series and with the observed NTOL effect. The height series and the predicted NTOL are highly correlated at all four stations. The analysis performed on superconducting gravimeter data at the Medicina station also shows high correlation.

From late January to mid-February 2012 the Gulf of Trieste (North Adriatic Sea) was affected by a severe winter weather event characterized by cold air and strong northeasterly wind (Bora). The atmospheric forcing caused large surface heat fluxes which produced remarkable effects on the gulf, particularly the production of a very cold and dense water mass. Temperatures as low as 4 degrees C were observed in the deepest part of the gulf, similar to that which was observed in winter 1929, which was probably the most severe winter in the region over more than a century. The density anomaly attained values up to 30.58 kg m(-3), even greater than in 1929. Surface heat fluxes were estimated using bulk formulas and the meteorological and marine observations available at three stations. Mean daily heat losses exceeded 1000 W m(-2). A comparison of this event with similar past events was made using proxy heat fluxes, available since 1978, to account for the air-sea interactions and using temperature and salinity observations, performed since 1996, to account for the effect of heat fluxes on ocean properties. The 2012 Bora episode turned out to be the most severe event of this kind in the Gulf of Trieste for at least the last 35 years and is comparable to that which occurred in 1929. A significant linear correlation was also found between the total surface heat loss and the density increase of the waters in the part of the gulf deeper than 20 m.

This work describes a study of GPS heights, gravity and hydrological time series collected by stations located in northeastern Italy. During the last 12 years, changes in the long-term behaviors of the GPS heights and gravity time series are observed. In particular, starting in 2004-2005, a height increase is observed over the whole area. The temporal and spatial variability of these parameters has been studied as well as those of key hydrological variables, namely precipitation, hydrological balance and water table by using the Empirical Orthogonal Functions (EDF) analysis. The coupled variability between the GPS heights and the hydrological balance and precipitation data has been investigated by means of the Singular Value Decomposition (SVD) approach. Significant common patterns in the spatial and temporal variability of these parameters have been recognized. In particular, hydrology-induced variations are clearly observable starting in 2002-2003 in the southern part of the Po Plain for the longest time series, and from 2004-2005 over the whole area. These findings, obtained by means of purely mathematical approaches, are supported by sound physical interpretation suggesting that the climate-related fluctuations in the regional/local hydrological regime are one of the main contributors to the observed variations. A regional scale signal has been identified in the GPS station heights; it is characterized by the opposite behavior of the southern and northern stations in response to the hydrological forcing. At Medicina, in the southern Po Plain, the EOF analysis has shown a marked common signal between the GPS heights and the Superconducting Gravimeter (SG) data both over the long and the short period.

Estimates of extreme sea levels and return periods have been based mainly on hourly sampling rates. Technological development has enabled the sampling rates to increase and sampling rates of 5-10 mm are becoming increasingly common In this paper we explore the relationship between extreme sea levels and estimated return periods based on hourly and shorter sampling periods in three tide-gauges one at the Atlantic coasts of Spain (Coruna), one in the western Mediterranean (Malaga) and one in the N. Adriatic (Trieste). Significant differences of several centimetres are found in the hourly and 5 min extremes. These reflect in significant underestimation of the 50-year return levels which in Trieste reach 38 cm. A theoretical relationship between the high and the low sampling rate of extremes is also tested. Thus updated 50-year return levels for the Mediterranean and the coasts of the Iberian peninsula are produced assuming that the differences identified in the various stations generalise to other tide-gauge (hourly) records for which hourly values have been analysed earlier. (C) 2009 Elsevier Ltd. All rights reserved.

Weather descriptions are available from a diary written in Trieste by A. Scussa from 1732 to 1749, which allow to deduce some features of thermal conditions and precipitation regimes. Indices are defined on the basis of the subjective assessment of the degree of heat and cold provided by the writer. Monthly and annual standardized anomalies are computed, that enable to put in evidence the interannual variability of the thermal conditions and allow a comparison with Padova observed temperatures. Anomalies in physical units are also estimated. The prominent fluctuations agree with those observed in Padova, although inconsistencies remain in specific months. The Trieste precipitation regime in 1732–1749 is consistent with that of the twentieth century but the precipitation frequency seems lower. Several severe droughts are also reported. Despite the methodological limitations the reconstruction appears reliable.

Sea-level data from South Atlantic stations were quality-controlled and analysed. Eleven time series, longer than 20 years, were selected to study long-term variability. The main features of South Atlantic sea level were described by computing linear trends, mean seasonal cycles and power spectra for the selected time series. The data sparseness made it difficult to achieve a comprehensive description of the basin. The connection between sea-level variability and ENSO was studied using the composite time series obtained by merging data for Buenos Aires and Palermo, on the Argentinian side of Rio de la Plata. It was possible to recognize that sea-level variability is strongly connected with that of river discharge into Rio de la Plata, which in turn exhibits a lagged teleconnection with ENSO. The time lag between ENSO and sea-level anomalies is about 5 months.