ALBERT

Description: The ability to adapt to social and environmental change is an increasingly critical feature of environmental governance. However, an understanding of how specific features of governance systems influence how they respond to change is still limited. Here we focus on how system features like diversity, heterogeneity, and connectedness impact stability, which indicates a system's capacity to recover from perturbations. Through a framework that combines agent-based modeling with "generalized"dynamical systems modeling, we model the stability of thousands of governance structures consisting of groups of resource users and non-government organizations interacting strategically with the decision centers that mediate their access to a shared resource. Stabilizing factors include greater effort dedicated to venue shopping and a greater fraction of non-government organizations in the system. Destabilizing factors include greater heterogeneity among actors, a greater diversity of decision centers, and greater interdependence between actors. The results suggest that while complexity tends to be destabilizing, there are mitigating factors that may help balance adaptivity and stability in complex governance. This study demonstrates the potential in applying the insights of complex systems theory to managing complex and highly uncertain human-natural systems in the face of rapid social and environmental change.

Description: Marine particles of different nature are found throughout the global ocean. The term "marine particles"describes detritus aggregates and fecal pellets as well as bacterioplankton, phytoplankton, zooplankton and nekton. Here, we present a global particle size distribution dataset obtained with several Underwater Vision Profiler 5 (UVP5) camera systems. Overall, within the 64 μm to about 50 mm size range covered by the UVP5, detrital particles are the most abundant component of all marine particles; thus, measurements of the particle size distribution with the UVP5 can yield important information on detrital particle dynamics. During deployment, which is possible down to 6000 m depth, the UVP5 images a volume of about 1 L at a frequency of 6 to 20 Hz. Each image is segmented in real time, and size measurements of particles are automatically stored. All UVP5 units used to generate the dataset presented here were inter-calibrated using a UVP5 high-definition unit as reference. Our consistent particle size distribution dataset contains 8805 vertical profiles collected between 19 June 2008 and 23 November 2020. All major ocean basins, as well as the Mediterranean Sea and the Baltic Sea, were sampled. A total of 19 % of all profiles had a maximum sampling depth shallower than 200 dbar, 38 % sampled at least the upper 1000 dbar depth range and 11 % went down to at least 3000 dbar depth. First analysis of the particle size distribution dataset shows that particle abundance is found to be high at high latitudes and in coastal areas where surface productivity or continental inputs are elevated. The lowest values are found in the deep ocean and in the oceanic gyres. Our dataset should be valuable for more in-depth studies that focus on the analysis of regional, temporal and global patterns of particle size distribution and flux as well as for the development and adjustment of regional and global biogeochemical models. The marine particle size distribution dataset is available at 10.1594/PANGAEA.924375.

Description: The incorporation of water isotopologues into the hydrology of general circulation models (GCMs) facilitates the comparison between modeled and measured proxy data in paleoclimate archives. However, the variability and drivers of measured and modeled water isotopologues, as well as the diversity of their representation in different models, are not well constrained. Improving our understanding of this variability in past and present climates will help to better constrain future climate change projections and decrease their range of uncertainty. Speleothems are a precisely datable terrestrial paleoclimate archives and provide well-preserved (semi-)continuous multivariate isotope time series in the lower latitudes and mid-latitudes and are therefore well suited to assess climate and isotope variability on decadal and longer timescales. However, the relationships of speleothem oxygen and carbon isotopes to climate variables are influenced by site-specific parameters, and their comparison to GCMs is not always straightforward. Here we compare speleothem oxygen and carbon isotopic signatures from the Speleothem Isotopes Synthesis and Analysis database version 2 (SISALv2) to the output of five different water-isotope-enabled GCMs (ECHAM5-wiso, GISSE2-R, iCESM, iHadCM3, and isoGSM) over the last millennium (850–1850 CE). We systematically evaluate differences and commonalities between the standardized model simulation outputs. The goal is to distinguish climatic drivers of variability for modeled isotopes and compare them to those of measured isotopes. We find strong regional differences in the oxygen isotope signatures between models that can partly be attributed to differences in modeled surface temperature. At low latitudes, precipitation amount is the dominant driver for stable water isotope variability; however, at cave locations the agreement between modeled temperature variability is higher than for precipitation variability. While modeled isotopic signatures at cave locations exhibited extreme events coinciding with changes in volcanic and solar forcing, such fingerprints are not apparent in the speleothem isotopes. This may be attributed to the lower temporal resolution of speleothem records compared to the events that are to be detected. Using spectral analysis, we can show that all models underestimate decadal and longer variability compared to speleothems (albeit to varying extents). We found that no model excels in all analyzed comparisons, although some perform better than the others in either mean or variability. Therefore, we advise a multi-model approach whenever comparing proxy data to modeled data. Considering karst and cave internal processes, e.g., through isotope-enabled karst models, may alter the variability in speleothem isotopes and play an important role in determining the most appropriate model. By exploring new ways of analyzing the relationship between the oxygen and carbon isotopes, their variability, and co-variability across timescales, we provide methods that may serve as a baseline for future studies with different models using, e.g., different isotopes, different climate archives, or different time periods.

Description: Following the Mw 6.0 Amatrice earthquake on 24 August 2016 in central Italy, the Emersito task force of the Istituto Nazionale di Geofisica e Vulcanologia installed a temporary seismic network focusing on the investigation of amplification effects at municipalities located on topographic reliefs. Fourteen stations were installed at three sites: Amandola, Civitella del Tronto, and Montereale. During the operational period, stations recorded about 150 earthquakes with Mw up to 4.7. Recorded signals were analyzed calculating the horizon- tal-to-vertical spectral ratios at single station, using both ambient noise and earthquake waveforms, as well as standard spectral ratios (SSRs) to a reference site. To robustly estimate site amplification at each station of the site amplification effect at each station, the influence of backazimuth and epicentral distance is investigated. With the aim of reproducing the observed amplification pattern, 2D numerical simulations were performed on a section orthogonal to the topography major axis, constrained through in situ geological investiga- tions and geophysical surveys. Although at Montereale site no clear amplification effects were observed, at Amandola site, all stations on the relief consistently detected significant peaks at about 4 Hz and along N120–150 azimuth. At Civitella del Tronto, a proper reference station is missing, implying a misleading of site response evaluation in terms of SSRs. Moreover, even if all stations show amplification in the frequency band 1–3 Hz, the direction of the maximum amplification varies from northeast to northwest. At the three sites, obser- vations were successfully reproduced by 2D numerical models, the latter suggesting that topography alone cannot reproduce data, and the interplay with subsoil velocity structure is needed to produce a clear amplification effect. We conclude that according to the previous articles, rather than the sole topography convex shape, the geophysical structure has often a predominant role in controlling the observed amplification pattern on topography.

Description: Published

Description: 1208–1229

Description: OST4 Descrizione in tempo reale del terremoto, del maremoto, loro predicibilità e impatto

Description: JCR Journal

Description: 〈jats:p〉Abstract. Understanding the future evolution of permafrost requires a better understanding of its climatological past. This requires permafrost models to efficiently simulate the thermal dynamics of permafrost over the past centuries to millennia, taking into account highly uncertain soil and snow properties. In this study, we present a computationally efficient numerical permafrost model which satisfactorily reproduces the current ground temperatures and active layer thicknesses of permafrost in the Arctic and their trends over recent centuries. The performed simulations provide insights into the evolution of permafrost since the 18th century and show that permafrost on the North American continent is subject to early degradation, while permafrost on the Eurasian continent is relatively stable over the investigated 300-year period. Permafrost warming since industrialization has occurred primarily in three “hotspot” regions in northeastern Canada, northern Alaska, and, to a lesser extent, western Siberia. We find that the extent of areas with a high probability (p3 m>0.9) of near-surface permafrost (i.e., 3 m of permafrost within the upper 10 m of the subsurface) has declined substantially since the early 19th century, with loss accelerating during the last 50 years. Our simulations further indicate that short-term climate cooling due to large volcanic eruptions in the Northern Hemisphere in some cases favors permafrost aggradation within the uppermost 10 m of the ground, but the effect only lasts for a relatively short period of a few decades. Despite some limitations, e.g., with respect to the representation of vegetation, the presented model shows great potential for further investigation of the climatological past of permafrost, especially in conjunction with paleoclimate modeling. 〈/jats:p〉

Description: Most earth system models (ESMs) neglect climate feedbacks arising from carbon release from thawing permafrost, especially from thawing of subsea permafrost (SSPF). To assess the fate of SSPF in the next 1000 years, we implemented SSPF into JSBACH, the land component of the Max Planck Institute Earth System Model (MPI-ESM). This is the first implementation of SSPF processes in an ESM component. We investigate three extended scenarios from the 6th phase of the Coupled Model Intercomparison Project (CMIP6). In the 21st century only small differences are found among the scenarios, but in the upper-end emission scenario SSP5-8.5 (shared socio-economic pathway), especially in the 22nd century, SSPF ice melting is more than 15 times faster than in the pre-industrial period. In this scenario about 35ĝ% of total SSPF volume and 34ĝ% of SSPF area are lost by the year 3000 due to climatic changes. In the more moderate scenarios, the melting rate maximally exceeds that of pre-industrial times by a factor of 4, and the climate change induced SSPF loss (volume and area) by the year 3000 does not exceed 14ĝ%. Our results suggest that the rate of melting of SSPF ice is related to the length of the local open-water season and thus that the easily observable sea ice concentration may be used as a proxy for the change in SSPF.

Description: This article presents the first publicly available version of the NExt STrOng Related Earthquake (NESTORE) software (NESTOREv1.0) designed for the statistical analysis of earthquake clusters. NESTOREv1.0 is a MATLAB (www.mathworks.com/products/ matlab , last accessed August 2022) package capable of forecasting strong aftershocks starting from the first hours after the mainshocks. It is based on the NESTORE algorithm, which has already been successfully applied retrospectively to Italian and California seismicity. The code evaluates a set of features and uses a supervised machine learning approach to provide probability estimates for a subsequent large earthquake during a seismic sequence. By analyzing an earthquake catalog, the software identifies clusters and trains the algorithm on them. It then uses the training results to obtain forecasting for a test set of independent data to estimate training performance. After appropriate testing, the software can be used as an Operational Earthquake Forecasting (OEF) method for the next stronger earthquake. For ongoing clusters, it provides near-real-time forecasting of a strong aftershock through a traffic light classification aimed at assessing the level of concern. This article provides information about the NESTOREv1.0 algorithm and a guide to the software, detailing its structure and main functions and showing the application to recent seismic sequences in California. By making the NESTOREv1.0 software available, we hope to extend the impact of the NESTORE algorithm and further advance research on forecasting the strongest earthquakes during seismicity clusters.

Description: Published

Description: 2003–2013

Description: OST4 Descrizione in tempo reale del terremoto, del maremoto, loro predicibilità e impatto

Description: OST5 Verso un nuovo Monitoraggio

Description: JCR Journal

Description: The region of central Italy is well known for its moderate-to-large earthquakes. Events such as 2016 Mw 6.2 Amatrice, generated in the shallow extensional tectonic regime, motivate numerical simulations to gain insights into source-related ground-motion complexities. We utilize a hybrid integral–composite kinematic rupture model by Gallovič and Brokešová (2007) to predict ground motions for other hypothetical Amatrice fault rupture scenarios (scenario events). The synthetic seismograms are computed in 1D crustal velocity models, including region-specific 1D profiles for selected stations up to 10 Hz. We create more than ten thousand rupture scenarios by varying source parameters. The resulting distributions of synthetic spectral accelerations at periods 0.2–2 s agree with the empirical nonergodic ground-motion model ofSgobbaetal.(2021)forcentral Italy in terms of the mean and total variability. However, statistical mixed-effect analysis of the residuals indicates that the between-eventvariability of the scenarios exceeds theempirical one significantly. We quan tify the role ofsourcemodelparametersinthemodelinganddemonstratethepivotalroleof theso-called stress parameterthatcontrols high-frequencyradiation. Weproposerestricting thescenariovariability tokeepthebetween-eventvariabilitywithintheempiricalvalue.The presented validation of the scenario variability can be generally utilized in scenario model ing for more realistic physics-based seismic hazard assessment.

Description: In press

Description: OST3 Vicino alla faglia

Description: JCR Journal

Description: Volcanic activity produces a broad spectrum of seismic and acoustic signals whose characteristics provide important clues on the underlying magmatic processes. Networks and arrays of seismic and acoustic sensors are the backbone of most modern volcano monitoring programs. Investigation of the signals gathered by these instruments requires efficient workflows and specialist software. The high sampling rates, typically 50 Hz or greater, at which seismic and acoustic waveforms are recorded by multistation networks and dense arrays leads to the rapid accumulation of large volumes of data, making the implementation of efficient data analysis workflows for volcano surveillance a challenging task. Here, we present an open‐source MATLAB graphical user interface, MISARA (Matlab Interface for Seismo‐Acoustic aRray Analysis), designed to provide a user‐friendly workflow for the analysis of seismoacoustic data in volcanic environments. MISARA includes efficient algorithm implementations of well‐established techniques for seismic and acoustic data analysis. It is designed to support visualization, characterization, detection, and location of volcano seismoacoustic signals. Its intuitive, modular, structure facilitates rapid, semiautomated, inspection of data and results, thus reducing user effort. MISARA was tested using seismoacoustic data recorded at Etna Volcano (Italy) in 2010, 2011, and 2019, and is intended for use in education and research, and to support routine data analysis at volcano observatories.

Description: Published

Description: 1689–1702

Description: OSV4: Preparazione alle crisi vulcaniche

Description: JCR Journal