ALBERT

Description: Sources of geophysical noise (such as wind, sea waves and earthquakes) or of anthropogenic noise impact ground-based gravitational-wave interferometric detectors, causing transient sensitivity worsening and gaps in data taking. During the one year-long third observing run (O3: from April 01, 2019 to March 27, 2020), the Virgo Collaboration collected a statistically significant dataset, used in this article to study the response of the detector to a variety of environmental conditions. We correlated environmental parameters to global detector performance, such as observation range, duty cycle and control losses. Where possible, we identified weaknesses in the detector that will be used to elaborate strategies in order to improve Virgo robustness against external disturbances for the next data taking period, O4, currently planned to start at the end of 2022. The lessons learned could also provide useful insights for the design of the next generation of ground-based interferometers.

Description: Published

Description: 235009

Description: 5T. Sismologia, geofisica e geologia per l'ingegneria sismica

Description: JCR Journal

Description: Atmospheric predictability is fundamentally limited by the upscale growth of initial small-scale, small-amplitude errors. Studying upscale error growth mechanism is essential to better understand this fundamental limitation. Upscale error growth is frequently investigated by spectral analysis. By design, however, spectral analysis is non-local. A local investigation of error growth in different flow configurations is desirable, though, to study the well-known flow dependence of error growth.We take an approach complementary to spectral analysis and apply a feature-based perspective. We have developed an automated algorithm to identify error features in gridded data and track their spatial and temporal evolution. Errors are considered in terms of potential vorticity (PV) and near the tropopause, where they maximize. A previously derived PV-error tendency equation is evaluated to quantify the different contributions to error growth in previously published upscale error growth experiments with the global prediction Model ICON from the German Weather Service. Errors in these experiments grow from very small initial-condition uncertainty (three orders of magnitude smaller than current-day uncertainty) and due to differences in the seeding of a stochastic convection scheme.Evaluation of the process specific error growth rates allows the detailed quantification of the upscale growth mechanisms. For this purpose, we integrate the growth rates over the respective area associated with an error feature. Examination of the combined growth rates of all features reproduces the previously found three-phased multi-scale upscale growth paradigm. The growth rates from a single feature, however, can substantially differ from the mean picture.

Description: Forward modeling in potential field data interpretation is a valuable tool for improving the significance of geophysical interpretations since decades. It allows for model validation and discrimination, parameter and depth estimations, and accommodation of complex subsurface structures, as well as topographic corrections in both Geophysics and Geodesy. Three tasks relevant to forward modelling are in our focus: “model validation” – testing accuracy and reliability of a geological model by comparing predicted/modelled data with field observations, “inversion optimization” – improvement of the accuracy of inversion results by incorporating constraints from forward modeling, and “sensitivity analysis” – evaluation of the sensitivity of the modeled data to changes in the model parameters, which can be used to make a more informed decision on the most likely underground model. While in the early days forward modeling was characterized using simple solids, such as spheres or rectangular prisms, to represent the subsurface structure, nowadays flexible polyhedra are available to deal with complicated subsurface structures for plane and spherical model calculations. Combined with modern computer graphics, interactive forward processing is possible “on the fly” and accompanied by the visualization of the broad spectrum of diverse model constraints. This enables an interdisciplinary “model discrimination” which assists in differentiating between multiple possible forward models by comparing the predicted data from each model with the observed data. Modeling case studies on small and large (global) scales will demonstrate these workflows by the aid of a software the team developed over the last decade.

Description: The next frontier in radiation science is to resolve cloud-aerosol-radiation interactions at the so-called process scale, which means at one kilometer or better – a significant advance from monitoring radiation at the 20 km footprint scale as done by the NASA’s Earth Observing System radiometers. Consequently, recent missions pursue a different radiation approach. Both EarthCARE and NASA’s AOS employ radiative transfer calculations that ingest imagery-based and active remote sensing products at their native resolution to calculate radiation fields. The imagery-scale calculations are then evaluated using independent radiance observations. In a process called radiance closure, discrepancies between calculations and observations for select observation angles and wavelength ranges are used to quantify and attribute errors, and perhaps even to nudge the remote sensing products towards higher fidelity. We will explain how this approach may address remote sensing biases of aerosol and cloud parameters for inhomogeneous scenes, which are fairly small at the 20 km scale, but can no longer be ignored at 1 km. Part of the solution will likely be convolutional neural networks, which are outgrowing the stigma to be merely qualitative tools without quantitative use for atmospheric remote sensing – to the point that they are now fueling the necessary transition from single-pixel to context-aware imagery retrieval algorithms. They are starting to outperform so-called physics-based algorithms when assessed through the lens of radiance closure. We will illustrate this with real-world examples, and lay out a vision for future cloud-aerosol-radiation interaction studies from aircraft and satellites.

Description: Clouds are one of the less understood Earth's system components. In the Arctic, clouds play a fundamental role in many processes, and their characterization is crucial for the understanding of regional climate, ice melting, radiative budget, and related processes. Arctic cloud optical properties are measured from ground-based and space-borne instruments, but high surface reflectance values, a widespread condition at high latitudes but in general for snow and ice-covered regions, pose severe limitations to the application of many retrieval algorithms. These aspects have been investigated based on measurements made with a UV-VIS-NIR (300-950 nm wavelength range) spectrometer at the Thule High Arctic Atmospheric Observatory (76.5° N, 68.8° W, http://www.thuleatmos-it.it/) on the northwestern coast of Greenland. Continuous measurements are available for the 2022 season (March to September). In combination with radiation transfer simulations carried out with the libRadtran package, different retrieval algorithms for estimating the cloud optical thickness (COT) have been tested and compared. In addition to the spectral measurements, the information on the cloud base height provided by a ceilometer has been included to address the challenges posed by the high reflectance surfaces. Sensitivity studies on COT retrievals in different atmospheric and surface conditions will be presented, along with a case study.

Description: Cryosphere-related hazards are a growing but largely neglected threat for rural settlements, agrarian land use and local livelihoods in the cold-arid Trans-Himalaya. Despite the growing number of studies on cryosphere-related hazards, the occurrence, frequency and magnitude of glacial lake outburst floods (GLOFs) are almost entirely overlooked for the region of Ladakh. Due to the small size and high elevational location of glaciers above 5200 m a.s.l. also the glacial lakes are of small size. In the recent past several GLOF events occurred which destroyed infrastructure and agricultural area. It becomes obvious that even these small glacial lakes might be a permanent threat for local livelihoods and socioeconomic development. This is even more problematic as the number and size of lakes has significantly increased over the past decades. A comprehensive inventory of glacial lakes for the entire Trans-Himalayan region of Ladakh was carried out. This includes several almost permanently ice-covered high altitude lakes. Changes in the extent and number of glacial lakes have been quantified since 1969 in order to assess the potential threat of future GLOFs in the region. The lake development of selected former reported GLOF events and disappeared glacial lakes were analysed in detail to reconstruct lake level changes which possibly indicate earlier GLOF events. Based on high temporal resolution remote sensing data, a sophisticated monitoring concept needs to be realized to indicate the development of short-lived lakes on glaciers or on debris landforms with buried ice or fast glacial lake growth.

Description: Hydrothermal alteration is a common process in active geothermal systems and can significantly change the physiochemical properties of rocks. To improve reservoir assessment and modeling of high-temperature geothermal resources linked to active volcanic settings, a detailed understanding of the reservoir is needed. The Los Humeros Volcanic Complex, hosting the third largest exploited geothermal field in Mexico, represents a natural laboratory to investigate the impact of hydrothermal processes on the rock properties through andesitic reservoir cores and outcropping analogs. Complementary petrographic and chemical analyses were used to characterize the intensities and facies of hydrothermal alteration. The alteration varies from argillic and propylitic facies characterized by no significant changes of the REE budget indicating an inert behavior to silicic facies and skarn instead showing highly variable REE contents. Unaltered outcrop samples predominantly feature low matrix permeabilities (〈 10–17 m2) as well as low to intermediate matrix porosities (〈 5–15%), thermal conductivities (0.89–1.49 W m−1 K−1), thermal diffusivities (~ 0.83 10–6 m2 s−1), and sonic wave velocities (VP: ~ 2800–4100 m s−1, VS: ~ 1600–2400 m s−1). Average magnetic susceptibility and specific heat capacity range between 2.4–7.0 10–3 SI and 752–772 J kg−1 K−1, respectively. In contrast, the hydrothermally altered reservoir samples show enhanced porosities (~ 7–23%), permeabilities (10–17–10–14 m2), and thermal properties (〉 1.67 W m−1 K−1; 〉 0.91 10–6 m2 s−1), but a significant loss of magnetic susceptibility (10–3–10–6 SI). In particular, this latter characteristic appears to be a suitable indicator during geophysical survey for the identification of hydrothermalized domains and possible pathways for fluids. The lack of clear trends between alteration facies, alteration intensity, and chemical indices in the studied samples is interpreted as the response to multiple and/or repeated hydrothermal events. Finally, the proposed integrated field-based approach shows the capability to unravel the complexity of geothermal reservoir rocks in active volcanic settings.

Description: Rossby Wave Packets (RWPs) are linked to extreme weather events and exert a strong influence on the predictability of weather systems in the midlatitudes. Considering the whole wave packet, in the sense of the packet envelope, RWPs can be viewed as entities that describe variability of the atmosphere beyond the synoptic scale. We here examine the predictability of RWPs as such entities. As a verification metric we used the so-called Displacement and Amplitude Score (DAS) applied to the envelope field of the midlatitude flow. The DAS is based on a field deforming method and, as one of its major advantages, avoids the “double-penalty” verification problem without the need to identify single RWP objects. We assess RWP predictability using NOAA GEFSV12 ensemble reforecasts for RWPs that have been previously tracked in reanalysis data. A prominent result is that RWP predictability depends on the stage of the RWP lifecycle: The propagation stage exhibits higher predictability than the decay or genesis stage. A small seasonal dependence is found, with summer being the least predicable season. No significant dependence is found on geographical (northern hemispheric) location. We will further discuss the link of RWP predictability to MJO activity and phases, and to the occurrence of North Atlantic-European weather regimes as one means to better understand the role of these large-scale, low-frequency phenomena on midlatitude predictability.

Description: IGMAS+ is a software combining 3-D forward and inverse modeling, interactive visualization and interdisciplinary interpretation of potential fields and their applications under geophysical and geological data constrains. The software has a long history starting 1988 and has seen continuous improvement since then with input by many contributors. Since 2019, IGMAS+ is maintained and developed at The Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences by the staff of Section 4.5 – Basin Modelling and Section 5.2 – eScience Centre with strong ongoing support by H.-J. Götze and S. Schmidt from CAU Kiel. The official webpage of IGMAS+ is available at https://www.gfz-potsdam.de/igmas. Each major version of IGMAS+ is assigned with a DOI. Intermediate releases including changelog can be found at https://git.gfz-potsdam.de/igmas/igmas-releases/-/releases/. This is a collection DOI referring to all versions of IGMAS+. Links to each published version are redundantly available via the "Files" section and the Related Work section ("includes").

Description: Data Terra’s main mission is to develop a structure for accessing and processing data, data-products and services geared towards observing, understanding and predicting in an integrated manner the history, mechanisms and evolution of the Earth system in response to global changes and extreme events. Data Terra federates four data and services hubs dedicated to the four physical compartments of the Earth System: Aeris for the atmosphere, Odatis for the oceans, Theia for land surfaces and ForM@Ter for the solid Earth. While aimed chiefly at the scientific community, the unique research e-infrastructure also serves public and socio-economic stakeholders and its multi-source data are accessible via coherent, one-stop portals. As a digital infrastructure in the field of earth and environmental science, Data Terra works closely with Earth-observation research infrastructures and space agencies. It is backed by a continuum of distributed and interconnected platforms, proposing services that span the full data cycle from access from repositories to value-added processing, thus enabling inter- and trans-disciplinarity studies as well as exploitation of large volumes of data. At national, European and international levels (EOSC Pillar, Fair impact, Phidias, Copernicus services, …), it is advancing the development of open science, implementation of FAIR approaches, contributing to space missions and applications and to the initiative to generate digital twins of the Earth. Data Terra federates four data and services hubs dedicated to the four physical compartments of the Earth System: Aeris for the atmosphere, Odatis for the oceans, Theia for land surfaces and ForM@Ter for the solid Earth. While aimed chiefly at the scientific community, the unique research e-infrastructure also serves public and socio-economic stakeholders and its multi-source data are accessible via coherent, one-stop portals. Data Terra’s main mission is to develop a structure for accessing and processing data, data-products and services geared towards observing, understanding and predicting in an integrated manner the history, mechanisms and evolution of the Earth system in response to global changes and extreme events. Data Terra federates four data and services hubs dedicated to the four physical compartments of the Earth System: Aeris for the atmosphere, Odatis for the oceans, Theia for land surfaces and ForM@Ter for the solid Earth. While aimed chiefly at the scientific community, the unique research e-infrastructure also serves public and socio-economic stakeholders and its multi-source data are accessible via coherent, one-stop portals. As a digital infrastructure in the field of earth and environmental science, Data Terra works closely with Earth-observation research infrastructures and space agencies. It is backed by a continuum of distributed and interconnected platforms, proposing services that span the full data cycle from access from repositories to value-added processing, thus enabling inter- and trans-disciplinarity studies as well as exploitation of large volumes of data. At national, European and international levels (EOSC Pillar, Fair impact, Phidias, Copernicus services, …), it is advancing the development of open science, implementation of FAIR approaches, contributing to space missions and applications and to the initiative to generate digital twins of the Earth.