Asimilacija podataka o temperaturi i salinitetu u jadranskom regionalnom modelu

Temperature and salinity data collected during the October 2002 - October 2003 period have been assimilated into a version of the Princeton Ocean Model implemented over the entire Adriatic Sea. The scheme used is SOFA (System for Ocean Forecast and Analysis, DE MEY & BENKIRAN, 2002) and this is the first coastal application of this scheme. The CTD data were collected in 4 coastal areas (Emilia-Romagna coastal strip, the Gulf of Trieste, the Rovinj and Pelješac-Vis-Drvenik coastal strips) while temperature profiles were acquired with XBT in the southern Adriatic Sea deep ocean areas. The analysis skill scores are examined in order to evaluate the assimilation performance. The results of the assimilation are first compared with independent analyses of satellite Sea Surface Temperature (SST) and it is found that assimilation of profiles improves the SST model estimate. Furthermore, the Root Mean Square (RMS) difference between model and temperature and salinity profiles before data insertion is analysed. The range of RMS temperature error is less than 1 0C for the entire area and decreases with time, indicating a positive impact of the assimilation. The RMS of salinity is less than 1 psu and it also shows a decreasing trend during the assimilation period.Podaci temperature i saliniteta, prikupljeni u razdoblju listopad 2002. - listopad 2003., su asimilirani u Princeton oceanski model koji je primijenjen na cijeli Jadran. Upotrijebljena shema je bila SOFA (Sys-tem for Ocean Forecast and Analysis, DE MEY & BENKIRAN, 2002), što je prva primjena ove sheme na obalno more. CTD podaci su prikupljeni na četiri obalna područja (obalni pojas Emilia–Romagna, Tršćanski zaljev, obalno područje kod Rovinja i obalno područje Pelješac-Vis-Drvenik) dok su podaci XBT-a prikupljeni u dubokim područjima južnog Jadrana. Ispitane su modelske analize, kako bi se procijenila uspješnost asimilacije. Rezultati asimilacije su najprije uspoređeni s nezavisnim analizama površinske tem-perature mora (SST) iz satelita te je nađeno da asimilacija profila poboljšava procjenu površinske tempera-ture iz modela. Nadalje je analiziran kvadratni korjen razlike (RMS) između modela te profila temperature i saliniteta prije uključivanja podataka. Raspon RMS pogreške temperature je ispod 1 0C na čitavom području i opada s vremenom, ukazujući na pozitivni utjecaj asimilacije. RMS razlika saliniteta je ispod 1 psu i pokazu-je trend opadanja za vrijeme razdoblja asimilacije

Multisource Bayesian Probabilistic Tsunami Hazard Analysis for the Gulf of Naples (Italy)

A methodology for a comprehensive probabilistic tsunami hazard analysis is presented for the major sources of tsunamis (seismic events, landslides, and volcanic activity) and preliminarily applied in the Gulf of Naples (Italy). The methodology uses both a modular procedure to evaluate the tsunami hazard and a Bayesian analysis to include the historical information of the past tsunami events. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0001 the submarine earthquakes and the submarine mass failures are initially identified in a gridded domain and defined by a set of parameters, producing the sea floor deformations and the corresponding initial tsunami waves. Differently volcanic tsunamis generate sea surface waves caused by pyroclastic density currents from Somma‐Vesuvius. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0002 the tsunami waves are simulated and propagated in the deep sea by a numerical model that solves the shallow water equations. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0003 the tsunami wave heights are estimated at the coast using the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0004's amplification law. The selected tsunami intensity is the wave height. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0005 the probabilistic tsunami analysis computes the long‐term comprehensive Bayesian probabilistic tsunami hazard analysis. In the prior analysis the probabilities from the scenarios in which the tsunami parameter overcomes the selected threshold levels are combined with the spatial, temporal, and frequency‐size probabilities of occurrence of the tsunamigenic sources. The urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0006 probability density functions are integrated with the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0007 derived from the historical information based on past tsunami data. The urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0008 probability density functions are evaluated to produce the hazard curves in selected sites of the Gulf of Naples. Plain Language Summary Probabilistic analyses are essential to estimate the natural hazards caused by infrequent and devastating events and to elaborate risk assessments aiming to mitigate and reduce the impact of the natural disasters on society. Probabilistic tsunami hazard analyses use procedures that trace and weight the different tsunami sources (submarine earthquakes, aerial/submarine slides, volcanic activity, meteorological events, and asteroid impacts) with varying probability of occurrence. The scope of the present methodology is the reduction of possible biases and underestimations that arise by focusing on a single tunamigenic source. The multisource probabilistic tsunami hazard analysis is applied to a real case study, the Gulf of Naples (Italy), where relevant threats due to natural events exist in a high densely populated district. The probabilistic hazard procedure takes into account multiple tsunamigenic sources in the region and provides a first‐order prioritization of the different sources in a long‐term comprehensive analysis. The methodology is based on a Bayesian approach that merges computational hazard quantification (based on source‐tsunami simulations) and past data, appropriately including in the quantification the epistemic uncertainty. For the first time a probabilistic analysis of the tsunami hazard in the region is presented taking into consideration multiple tsunamigenic sources

Probability Analysis Improves Hazard Assessment

Many of the world’s natural events from earthquakes and volcanoes to tornados and landslides affect human populations. Estimating the likelihood of occurrence and frequency is an important science to help people plan and prepare for future events. An article recently published in Reviews in Geophysics, Grezio et al. [2017] (http://onlinelibrary.wiley.com/doi/10.1002/2017RG000579/full) considered one type of infrequent but often devastating natural event: tsunamis. They gave an overview of a method for analyzing and preparing for tsunamis. The editor asked one of the authors to explain more about methods of hazard analysis and recent developments in this field.Editors’ Vox Perspectives on Earth and space science: A blog from AGU’s journal editorsPublished6T. Studi di pericolosità sismica e da maremotoN/A or not JC

The dynamical controls on the antarctic circumpolar current with the use of general circulation models

Three general circulation models (FRAM, OCCAM and POP) are used in order to investigate the dynamics of the Antarctic Circumpolar Current (ACC) at the Drake Passage latitudes (ACCB) where the ACC is unbounded. In these models bottom form stress balances the wind stress in the momentum budgets. In the vorticity budgets the main balance is between wind curl and bottom pressure torque in FRAM and OCCAM. In the higher resolution model (POP) the non linear advection is one of the main terms. Whereas standing eddies mainly decelerate the flow in the ACCB, transient eddies play a different role in the three models. In the upper levels transient eddies accelerate the flow in POP and FRAM, but decelerate the flow in OCCAM. The behaviour of standing and transient eddies changes throughout the water column in the ACCB and eddies have a dragging effect on the flow below the levels where the topography starts to obstruct the flow. The crucial role of topography is investigated using a set of numerical experiments. In the coarse version of OCCAM Kerguelen Plateau is lowered and the Drake Passage Region and the Antarctic-Pacific Ridge are removed. Results from the analysis in the ACCB indicate that changing topography has a local effect. The complete investigation of the ACC dynamics is extended to the ACC Path (ACCP). The vorticity budgets show that the Drake Passage Region affects all of the ACC flow. Removing Drake Passage reduces the contributions of the bottom pressure torque to the vorticity balance and the region of Sverdrup-like balance is extended. The key role for all the ACC is played by Drake Passage but not from other topographic features.</p

Tsunamis: Bayesian Probabilistic Hazard Analysis

Tsunamis are low-frequency high-consequences major natural threats, rare events devastating vast coastal regions near and far from their generation areas. They may be caused by coseismic seafloor motions, subaerial and submarine mass movements, volcanic activities (like explosions, pyroclastic flows and caldera collapses), meteorological phenomena and meteorite ocean impacts. The probability of tsunami occurrence and/or impact on a given coast may be treated formally by combining calculations based on empirical observations and on models; this probability can be updated in light of new/independent information. This is the general concept of the Bayesian method applied to tsunami probabilistic hazard analysis, which also provides a direct quantification of forecast uncertainties. This entry presents a critical overview of Bayesian procedures with a primary focus on their appropriate and relevant applicability to tsunami hazard analyses.Published6T. Studi di pericolosità sismica e da maremot

A Methodology for a Comprehensive Probabilistic Tsunami Hazard Assessment: Multiple Sources and Short-Term Interactions

We propose a methodological approach for a comprehensive and total probabilistic tsunami hazard assessment (TotPTHA), in which many different possible source types concur to the definition of the total tsunami hazard at given target sites. In a multi-hazard and multi-risk perspective, the approach allows us to consider all possible tsunamigenic sources (seismic events, slides, volcanic eruptions, asteroids, etc.). In this respect, we also formally introduce and discuss the treatment of interaction/cascade effects in the TotPTHA analysis and we demonstrate how the triggering events may induce significant temporary variations in short-term analysis of the tsunami hazard. In two target sites (the city of Naples and the island of Ischia in Italy) we prove the feasibility of the TotPTHA methodology in the multi—source case considering near submarine seismic sources and submarine mass failures in the study area. The TotPTHA indicated that the tsunami hazard increases significantly by considering both the potential submarine mass failures and the submarine seismic events. Finally, the importance of the source interactions is evaluated by applying a triggering seismic event that causes relevant changes in the short-term TotPTHA

Quantification of source uncertainties in Seismic Probabilistic Tsunami Hazard Analysis (SPTHA)

This article has been accepted for publication in Geophysical Journal Internationa ©: 2016 Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.We propose a procedure for uncertainty quantification in Probabilistic Tsunami Hazard Analysis (PTHA), with a special emphasis on the uncertainty related to statistical modelling of the earthquake source in Seismic PTHA (SPTHA), and on the separate treatment of subduction and crustal earthquakes (treated as background seismicity). An event tree approach and ensemble modelling are used in spite of more classical approaches, such as the hazard integral and the logic tree. This procedure consists of four steps: (1) exploration of aleatory uncertainty through an event tree, with alternative implementations for exploring epistemic uncertainty; (2) numerical computation of tsunami generation and propagation up to a given offshore isobath; (3) (optional) site-specific quantification of inundation; (4) simultaneous quantification of aleatory and epistemic uncertainty through ensemble modelling. The proposed procedure is general and independent of the kind of tsunami source considered; however, we implement step 1, the event tree, specifically for SPTHA, focusing on seismic source uncertainty. To exemplify the procedure, we develop a case study considering seismic sources in the Ionian Sea (central-eastern Mediterranean Sea), using the coasts of Southern Italy as a target zone. The results show that an efficient and complete quantification of all the uncertainties is feasible even when treating a large number of potential sources and a large set of alternative model formulations. We also find that (i) treating separately subduction and background (crustal) earthquakes allows for optimal use of available information and for avoiding significant biases; (ii) both subduction interface and crustal faults contribute to the SPTHA, with different proportions that depend on source-target position and tsunami intensity; (iii) the proposed framework allows sensitivity and deaggregation analyses, demonstrating the applicability of the method for operational assessments.Italian Flagship Project RITMARE, EC FP7 ASTARTE (Grant agreement 603839) and STREST(Grant agreement 603389) projects, Italian FIRB-‘Futuro in Ricerca’ project ‘ByMuR’ (Ref. RBFR0880SR), INGV-DPC Agreement, Annex B2Published1780–18035T. Modelli di pericolosità sismica e da maremotoJCR Journa

Probabilistic Tsunami Hazard Analysis (PTHA): multiple sources and global applications

Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., runup or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including: (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms; (ii) developments in modeling the propagation and impact of tsunami waves; (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence and uncertainties in an integrated and consistent probabilistic framework