84 research outputs found

    The assessment of temperature and salinity sampling strategies in the Mediterranean Sea: idealized and real cases

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    International audienceTemperature and salinity sampling strategies are studied and compared by means of the Observing System Simulation Experiment technique in order to assess their usefulness for data assimilation in the framework of the Mediterranean Forecasting System. Their impact in a Mediterranean General Circulation Model is quantified in numerical twin experiments via bivariate data assimilation of temperature and salinity profiles in summer and winter conditions, using the optimal interpolation algorithm implemented in the System for Ocean Forecasting and Analysis. The data impact is quantified by the error reduction in the assimilation run relative to the free run. The sampling strategies studied here include various combinations of temperature and salinity profiles collected along Volunteer Observing Ship (VOS) tracks, by Mediterranean Multi-sensor Moored Arrays (M3A), a Glider and ARGO floating profilers. Idealized sampling strategies involving VOS data allow to recognize the impact of individual tracks. As a result, the most effective tracks are those crossing regions characterized by high mesoscale variability and the presence of frontal structures between water masses. Sampling strategies adopted in summer?autumn 2004 and winter 2005 are studied to assess the impact of VOS and ARGO data in real conditions. The combination of all available data allows to achieve up to 30% error reductions. ARGO data produce a small impact when alone, but represent the only continuous coverage of the basin and are useful as a complement to VOS data sets. Localized data sets, as those obtained by M3As and the Glider, seem to have an almost negligible impact in the basin-scale assessment, and are expected to be more effective at regional scale

    Time variability of atmospheric and marine parameters over the Adriatic region

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    The time evolution of atmospheric and marine parameters over the Adriatic region is studied for the period 1946-1996 on different time-scales. On the interannual and interdecadal time-scales evidence is found of the inverted barometer effect on sea level and the strong connection between air and sea temperatures. By contrast, opposite relationships are found on longer (secular) time-scales, which might be explained as different results of global climatic fluctuations on the atmospheric and marine parameters involved. On the interannual time-scale a correlation is found between sea-level pressure gradient along the basin and the water inflow/outflow through the Otranto Channel, in terms of sea level and sea temperature

    Observing System Simulation Experiments for the assessment of temperature sampling strategies in the Mediterranean Sea

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    International audienceFor the first time in the Mediterranean Sea various temperature sampling strategies are studied and compared to each other by means of the Observing System Simulation Experiment technique. Their usefulness in the framework of the Mediterranean Forecasting System (MFS) is assessed by quantifying their impact in a Mediterranean General Circulation Model in numerical twin experiments via univariate data assimilation of temperature profiles in summer and winter conditions. Data assimilation is performed by means of the optimal interpolation algorithm implemented in the SOFA (System for Ocean Forecasting and Analysis) code. The sampling strategies studied here include various combinations of eXpendable BathyThermograph (XBT) profiles collected along Volunteer Observing Ship (VOS) tracks, Airborne XBTs (AXBTs) and sea surface temperatures. The actual sampling strategy adopted in the MFS Pilot Project during the Targeted Operational Period (TOP, winter-spring 2000) is also studied. The data impact is quantified by the error reduction relative to the free run. The most effective sampling strategies determine 25?40% error reduction, depending on the season, the geographic area and the depth range. A qualitative relationship can be recognized in terms of the spread of information from the data positions, between basin circulation features and spatial patterns of the error reduction fields, as a function of different spatial and seasonal characteristics of the dynamics. The largest error reductions are observed when samplings are characterized by extensive spatial coverages, as in the cases of AXBTs and the combination of XBTs and surface temperatures. The sampling strategy adopted during the TOP is characterized by little impact, as a consequence of a sampling frequency that is too low. Key words. Oceanography: general (marginal and semi-enclosed seas; numerical modelling

    Interannual variability of gps heights and environmental parameters over europe and the mediterranean area

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    Vertical deformations of the Earth’s surface result from a host of geophysical and geological processes. Identification and assessment of the induced signals is key to addressing outstanding scientific questions, such as those related to the role played by the changing climate on height variations. This study, focused on the European and Mediterranean area, analyzed the GPS height time series of 114 well-distributed stations with the aim of identifying spatially coherent signals likely related to variations of environmental parameters, such as atmospheric surface pressure (SP) and terrestrial water storage (TWS). Linear trends and seasonality were removed from all the time series before applying the principal component analysis (PCA) to identify the main patterns of the space/time interannual variability. Coherent height variations on timescales of about 5 and 10 years were identified by the first and second mode, respectively. They were explained by invoking loading of the crust. Single-value decomposition (SVD) was used to study the coupled interannual space/time variability between the variable pairs GPS height–SP and GPS height–TWS. A decadal timescale was identified that related height and TWS variations. Features common to the height series and to those of a few climate indices—namely, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the East Atlantic (EA), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI)—were also investigated. We found significant correlations only with the MEI. The first height PCA mode of variability, showing a nearly 5-year fluctuation, was anticorrelated (– 0.23) with MEI. The second mode, characterized by a decadal fluctuation, was well correlated (+0.58) with MEI; the spatial distribution of the correlation revealed, for Europe and the Mediterranean area, height decrease till 2015, followed by increase, while Scandinavian and Baltic countries showed the opposite behavior

    The sea level time series of Trieste, Molo Sartorio, Italy (1869–2021)

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    The sea level observations carried out at Trieste, Molo Sartorio, from 1869 to 2021 have been revised and updated. Information on the tide gauges and on the geodetic benchmarks on Molo Sartorio during that period have been collected. Basic quality checks have been applied. The hourly data for the 1917–1938 period, digitized from the original charts, have allowed us to build a time series of hourly sea level heights from 1905 to 2021. Gaps of up to 24 h have been filled by interpolation. The errors affecting the monthly and annual mean sea levels have been estimated. The availability of monthly and annual means prior to 1904 allowed us to build a mean sea level time series spanning 153 years, characterized by linear trends of an observed sea level of 1.36 ± 0.17 mm yr−1 and of an inverse-barometer-corrected sea level of 1.45 ± 0.13 mm yr−1. A significant acceleration of 0.008 ± 0.004 mm yr−2 was estimated from the inverse-barometer-corrected sea level time series. This data set represents the most up-to-date data set of sea level observations and ancillary information relative to the tide-gauge station of Trieste, Molo Sartorio. The data are available through SEANOE (https://doi.org/10.17882/62758, Raicich, 2022).</p

    Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

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    Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns
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