bluuebunny/crossref_metadata_2025 huggingface dataset:
Freeze-thaw processes regulate microbial controls on soil organic carbon decomposition in Qingzang alpine grasslands
Authors: Qi Shanshan , Wang Gangsheng
Published: March 2024

Freeze-thaw cycling can influence microbial physiological states including microbial dormancy and resuscitation, and enzyme activities. These factors are essential to the mechanisms that control soil carbon and nutrition dynamics mediated by microbes. Warming-induced thawing may also cause changes in microbial functional diversity and stability. However, it remains a significant challenge to integrate these responses within microbial ecological models, which impedes the precision of carbon-nutrient-climate feedback projections. Here, we depict the dynamics of freezing and thawing soil, as well as the microbial and enzymatic functions in response to freeze-thaw processes within the Microbial-ENzyme Decomposition (MEND) model. The simulation was conducted in the Qingzang alpine grassland with field observations and comprehensive parameterization. Our findings suggest that microbial data potentially enhance confidence in model simulations. We also demonstrate that the relative substrate availability affects the trade-off between enzyme synthesis and metabolic flux. The results can deepen our understanding of microbial acclimation to freeze-thaw cycling and how they respond to soil organic carbon decomposition in permafrost ecosystems. 
Geochemical Implications for Tertiary Lower Crustal Melting in Northern Menderes Massif (Western Anatolia): Preliminary results
Authors: Kamacı Ömer , Ünal Alp , Altunkaynak Şafak
Published: March 2024

Tertiary migmatizations are pivotal events in the geologic history of the Menderes Massif, one of the world's most extensively studied core complexes. In northern Menderes Massif (Gördes Submassif) several granitic intrusions were emplaced into the migmatitic core rocks. They are mostly monzogranitic and granodioritic in composition and cut by associated pegmatitic dikes. These granitoids exhibit holocrystalline granular and porphyritic textures, characterized by plagioclase and, occasionally, biotite phenocrysts. The mineral composition of the granodiorites comprises 35–45% plagioclase, 30–35% quartz, 15–25% K-feldspar, and 5–10% biotite, with ± 5–8% muscovite. In contrast, the monzogranites are distinguished by a reduced plagioclase/K-feldspar ratio. Secondary phases include opaque minerals and sericite, with muscovite also observed. Accessory phases are zircon minerals. The granites exhibit an ASI index between 1 and 1.1, classifying them as slightly peraluminous I-type granites. They predominantly display high-K calc-alkaline characteristics and, less frequently, calc-alkaline nature. The Eu/Eu* ratio of these granites varies from 0.8 to 1.4. Trace element patterns suggest a possible derivation from basaltic and greywacke source rocks. Notably, high LaN/YbN ratios (reaching up to 107 ppm) and elevated Sr/Y ratios (up to 108 ppm) imply the presence of garnet or amphibole in the source. DyN/YbN and LaN/YbN ratios and their relationships specifically indicate the presence of garnet, rather than amphibole in the mafic source region. These data imply the crucial role of lower crustal melting in the formation of granitoids and the evolutionary history of the Menderes Core Complex.
Delineating Hydraulic Heterogeneity Using Fiber Bragg Grating Multi-Level Well and Hydraulic Tomography – A Case Study in Taiwan
Authors: Tsai Jui-Pin , Yeh Tian-Chyi , Wang Bo-Tsen , Chang Chia‐Hao , Liang Che-Wei
Published: March 2024

Hydraulic tomography (HT) is an innovative method for characterizing the heterogeneous properties of aquifers. This technique involves sequential pumping/injection tests using a network of wells, with simultaneous measurement of groundwater pressure variations. The resulting pressure data is then transformed into hydraulic heterogeneity using a geostatistical approach. Traditional HT tests utilize wells with screens at a single target depth, limiting pressure data collection to specific depth ranges. In contrast, a multilevel well-monitoring system (MLMS) employs multiple open screens at different depths, separated by packers, to prevent vertical flow connections. This configuration significantly increases the amount of pressure data compared to traditional wells. In this study, we implemented a novel multilevel well system based on fiber Bragg grating (FBG) technology for conducting HT at a contaminated site in Taiwan. A comparative analysis of hydraulic conductivity profiles obtained from HT with FBG MLMS and electrical resistivity was undertaken to validate the effectiveness of the FBG MLMS in HT applications. The results demonstrate the reliability and practicality of using an FBG multilevel well system for hydraulic tomography, highlighting its potential for enhanced data collection in heterogeneous aquifer characterization.
The compound effect of acute respiratory infections and temperatures on mortality in the Czech Republic, 1982–2019
Authors: Borisova Ekaterina , Urban Aleš , Hanzlíková Hana , Plavcová Eva , Kyselý Jan , Kynčl Jan , Ballester Joan
Published: March 2024

Numerous studies have thoroughly documented the contribution of non-optimal temperatures and acute respiratory infections (ARIs) to increased mortality. However, there is still a gap in understanding how these factors interact together to affect human mortality during the cold season, and how this impacts population susceptibility to heat waves in the summer.In this study we conduct an analysis over a period spanning 38 years (1982–2019), utilizing: a) daily all-cause mortality counts across the Czech Republic, b) daily proxies of acute respiratory infections (ARIs) incidence, interpolated from weekly healthcare surveillance data, and distinguished regarding three dominant influenza viruses (A/H3N2, A/H1N1, and B), and c) a suite of weather variables, sourced from E-OBS gridded data, including daily mean, maximum, and minimum temperatures, daily precipitation, daily mean sea level pressure, daily mean wind speed, daily mean relative humidity, and radiation level.To investigate the complex associations between mortality rates, ARI incidence, and weather variability, we employ a distributed lag non-linear model (DLNM) with multiple cross-bases. This approach facilitates the adjustment for confounding meteorological variables and provides a better understanding of their impact as fluctuating confounders. From these refined models, we derived the fraction of mortality attributable to ARIs and low temperatures, offering a quantification of their impact on excess mortality in the cold season. Additionally, we analyse changes in seasonal patterns of mortality according to the meteorological and epidemiological characteristics and assess temporal associations between air temperature and mortality in summer considering factors like intensity of ARI outbreaks and the mean winter temperature in the previous cold season. Our results contribute to better understanding of the links between temperature variability, respiratory infection dynamics and the seasonal variations in mortality.
Project SoMMet - Metrology for multi-scale monitoring of soil moisture
Authors: Zboril Miroslav , Millán Callado María de los Ángeles ,   SoMMet Consortium
Published: March 2024

Soil moisture is one of the Essential Climate Variables as defined by the WMO Global Climate Observing System. Several soil moisture observation systems exist on multiple scales, however, poorly harmonized due to the lack of interlinks. There is a need to establish the chain of traceability, the metrological assessment of uncertainties and the harmonisation of soil moisture measurements within the hydrological cycle, on multiple scales ranging from point-scale sensors to satellite remote sensing techniques. In addition, there is an urgent need for real-time, continuous, high-quality, high-resolution and metrologically traceable and harmonised data on soil moisture.To address these needs, the project SoMMet (Soil Moisture Metrology) has been set up in the framework of the European Partnership on Metrology of EURAMET. The aim of the project is to develop sound metrological tools and establish a metrological foundation for soil moisture measurement methods on multiple scales, supporting the traceability and harmonisation initiatives.On the point scale (10-1 m – 101 m), novel primary and secondary standards of humidity measurement will be developed specifically for soil samples. On the intermediate range (102 m – 103 m), the metrological basis of the cosmic-ray neutron sensing (CRNS) method will be established. On the large scale (103 m – 104 m), satellite-based remote sensing techniques will be utilized to derive the soil moisture products. Based on dedicated comparison measurement campaigns, tools for cross-disciplinary harmonisation of the individual methods will be developed. Furthermore, soil moisture data fusion approaches will be researched, aiming at integrating the multi-scale soil moisture measurements to provide new schemes and recommendations to facilitate the generation of high-quality, temporally and spatially consistent soil moisture information useful for land surface sciences and applications.The project consortium consists of nine National and Designated Metrology Institutes and nine research institutions. It cooperates with other projects and networks currently dealing with soil moisture monitoring and open issues of missing soil moisture harmonisation. The project 21GRD08 SoMMet has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States.
Navigating climate risk in humanitarian action: The potential of storyline approaches
Authors: Vogel Martha Marie , Jack Christopher David
Published: March 2024

The humanitarian community has a long history of attempting to reduce the human impact of extreme weather and climate events. Over the past decade there has been an increasing shift in the humanitarian community towards using climate science to better anticipate climate impacts on vulnerable communities and hence guide humanitarian planning and responses. However, large uncertainties, climate and non-climate, and complex compounding risks pose significant challenges to integrating climate information into humanitarian planning.In the glossary of the IPCC Working Group I contribution to the Sixth Assessment Report storylines are defined as “A way of making sense of a situation or a series of events through the construction of a set of explanatory elements” and “can be used to describe plural, conditional possible futures or explanations of a current situation, in contrast to single, definitive futures or explanations”.With this they are valuable for the humanitarian sector as storylines related approaches including impact pathways and complex risk frameworks offer the potential to provide robust and valuable understanding of risk, as well as supporting the development of effective interventions. They do not remove the underlying uncertainty, however, they do help to shift the questions asked from “What is going to happen”, to “What would unfold if this storyline occurred".  This shift has the potential to connect with decision making options and processes far more effectively than presentations of aggregate uncertainty ranges.We explore the potential value  of storylines for climate risk management within the humanitarian sector, we present practical examples of effectively applying them to estimate and describe  systemic climate-related risks, especially in vulnerable regions.
Ice Nucleation Activity of Atmospheric Asian Dust Particles
Authors: Wu Zhijun , Chen Jingchuan , Hu Min
Published: March 2024

Airborne mineral dust triggers ice formation in clouds and alters cloud microphysical properties by acting as ice-nucleating particles (INPs), potentially influencing weather and climate at regional and global scales. Asian dust is an important source of atmospheric INPs. However, the ice nucleation activity (INA) of Asian dust, especially its sensitivity to particle size and anthropogenic pollution aging, remains poorly understood. In this study, we investigated the immersion mode ice nucleation properties and particle chemical characterizations of collected size-resolved Asian dust samples, covering eight particle size classes ranging from 0.18 to 10.0 μm. We also examined the chemical modification of aged dust particles via particle chemistry and morphology analyses. The measured total INP concentrations in the immersion mode ranged from 10-2 to 102 L-1 in dust events at temperatures between -25 and -5 ℃. An explicit size dependence of both INP concentration and surface ice active density was observed. The nucleation efficiency of dust particles increased with increasing particle size, while the INP concentration first increased rapidly and then levelled, due to the significant decrease in the number concentration of larger particles. The mass fraction of Ca2+ in element Ca and the mean relative mass proportions of supermicron Ca2+ increased by 67.0% and 3.5-11.2% in aged Asian dust particles, respectively, suggesting the occurrence of heterogeneous reactions. On the other hand, the total INP concentrations and total ice nucleation active site densities were consistent between aged and normal dust particles (0.62-1.18 times) without a statistically significant difference. And the INP concentrations and surface active site densities of chemically aged supermicron dust (1.0-10.0 μm) in each particle size class were nearly equal to or slightly higher than those of normal Asian dust, which were 0.70-2.45 times and 0.64-4.34 times at -18 ℃, respectively. These results reveal that anthropogenic pollution does not notably change the INP concentrations and does not impair the INA of Asian dust. Our work provides direct observational evidence and clarifies the non-suppression effect of anthropogenic pollution on the INA of East Asian dust, advancing the understanding of the ice nucleation of airborne aged mineral dust.
Evaluation of soil moisture droughts under climate change in Germany
Authors: Boeing Friedrich , Marx Andreas , Wagener Thorsten , Samaniego Luis , Rakovec Oldrich , Kumar Rohini , Attinger Sabine
Published: March 2024

It is projected that the likelyhood and duration of extreme soil moisture (SM) droughts will increase in Germany under future warming scenarios. Annual precipitation changes are small under climate change in Germany with increases in winter and decreasing precipitation in summer for some parts of Germany. Generally, the climate ensemble spread in the future precipitation signal is large. Furthermore, impacts of SM droughts depend largely on the soil volume evaluated. We identified a gradient of stronger soil drying in shallow SM compared to deeper SM under global warming, leading to different effects on shallow-rooted vegetation compared to deep-rooted vegetation (agriculture versus forestry). In addition, spatial characteristics such as soil properties can strongly influence the dynamics of SM and thus shape the response of SM drought to changing meteorological conditions. In this work we evaluate the impact of the considered soil depth and spatial features on simulated changes in SM droughts in Germany. We compare this influence to the uncertainty in meteorological changes. We use a large climate ensemble based on Euro-Cordex regional climate model simulations, which were bias-adjusted and spatially disaggregated to run the mesoscale hydrological model (mHM) (mhm-ufz.org) with a high spatial resolution of 1.2x1.2km. This work aims to expand the picture of climate change impacts on SM droughts in Germany. The results can contribute to an improved definition of sector-specific drought indicators that will support national efforts to ensure climate change resilient water management.
Disentangling carbonyl sulphide ecosystem relative uptake using (inverse) canopy modelling 
Authors: Bosman Peter , Krol Maarten
Published: March 2024

Carbonyl sulphide (COS) has been used in earlier studies as a proxy for determining photosynthesis. To this end, the concepts of leaf relative uptake (LRU, ratio of COS and CO2 deposition velocities at leaf scale) and ecosystem relative uptake (ERU, ratio of COS and CO2 deposition velocities at ecosystem scale) are often used. We have constructed a new canopy model that simulates LRU and ERU. This model consists of multiple layers, each having its own air temperature, COS, CO2 and H2O mixing ratio. Sunlit and shaded leaves are modelled separately. We coupled this model to the Chemistry-Land Surface Soil Slab (CLASS) model to simulate the atmospheric mixed layer and surface layer above the canopy. An inverse modelling framework is built around these models, allowing for an optimisation of model parameters. In our presentation we will mostly focus on using this framework to analyse the differences in leaf relative uptake in the model, that together influence the overall ERU. We find large differences in LRU between sunlit and shaded leaves, to a large extent caused by differences in stomatal conductance.
Grain size distributions, from a single grain size to well-graded distributions, on dry and immersed flows
Authors: Polanía Oscar , Azéma Emilien , Renouf Mathieu , Estrada Nicolas , Cabrera Miguel
Published: March 2024

Landslides and debris flows are massive geophysical processes that could occur in subaerial or submerged conditions. They involve granular materials in a wide range of Grain Size Distributions (GSD). In such processes, granular materials are subjected to large deformations, reaching a state where strains accumulate at constant shear stress. This state is known in the geotechnical community as the residual or critical state. The influence of the GSD on the residual state has been a matter of discussion between conflicting experimental and numerical observations. In this work, we confirm, at a grain scale and in dry conditions, that the residual shear strength is independent of the GSD. Moreover, we experimentally validate this result on dry granular flows, comparing the influence from monodisperse materials (materials with one grain size) to well-graded materials (materials with multiple grain sizes) on the mobility of a granular column. In this configuration, a granular column is let to collapse by self-weight and spread horizontally. The column mobility can be interpreted as a macro representation of the material's effective shear strength. Furthermore, we explore the effect of the GSD in immersed columns, finding a strong dependence of the GSD on the flow dynamics arising from the evolution of basal pore pressure P. At the flow initiation, negative P changes beneath the column produce a temporary increase in the column strength. This positive change lasts longer and with a larger amplitude in granular flows with well graded materials than in monodisperse ones. Then, during the column horizontal spreading, positive changes of P provoke a decrease in shear strength. For column collapses of graded materials, the excess of P lasts longer, allowing the collapses to reach farther distances compared with collapses of monodisperse materials. Finally, considering the relevance of mobility in granular flows, we propose a mobility model that scales the final runout with the collapse kinetic energy. This model works for both dry and immersed flows with different GSDs and has been validated for results from different authors, methodologies, and grain characteristics. Our results offer a novel perspective on the influence of GSD on the complex relationships between solid and fluid phases in granular flows, highlighting features that can be extended to massive natural processes.
Retrieval of vertical concentration profiles of SO2 using the IASI satellite instrument
Authors: Lo Nga Ying , Schneider Matthias , Shahzadi Kanwal , Hase Frank , Braesicke Peter , Caspart René , Streit Achim
Published: March 2024

The development of MUSICA IASI processing was initiated as part of the MUSICA (Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) project funded by the European Research Council. This processor works with IASI (Infrared Atmospheric Sounding Interferometer) radiances measured under cloud-free conditions, and, using optimal estimation, derives vertical distributions of water vapor, ratios between water vapor isotopologues, and several trace gases including greenhouse gases, methane and nitrous oxide. In accordance with the FAIR (findable, accessible, interoperable, reusable) principles, all MUSICA IASI products are freely available together with their observation specific averaging kernels and uncertainty covariances. Recently, retrievals of sulfur dioxide (SO2), peroxyacetyl nitrate (PAN), acetic acid and acetone have been included, in order to account for their important spectroscopic signals in case of volcanic eruptions and biomass burning events, respectively.  Here, we present the MUSICA IASI SO2 retrieval setup. A particularity is the use of a logarithmic SO2 concentration scale, which facilitates a reliable detection of the altitude where the SO2 plume is situated (retrieved from the spectral signal, no a priori assumptions of an SO2 plume height required). We document the superiority of this retrieval setup compared to a retrieval on a linear SO2 concentration scale. In addition, we empirically demonstrate the quality of the SO2 profile data in the preliminary results of three different volcano eruption events at three different latitude regions: 2019 Raikoke (48°N), 2021 La Palma (Cumbre Vieja, 29°N), and 2022 Hunga Tonga-Hunga Ha’apai (20°S). The amount of SO2 and the SO2 plume height are different for the three events. We show that the MUSICA IASI product is able to correctly capture these differences. The availability of individual averaging kernels allows a quantitative inter-comparison to other SO2 data products. For SO2 plumes in the low and middle troposphere, we will explore respective comparison possibilities to data obtained from Ticosonde in-situ measurements. For SO2 plumes in the upper troposphere or stratosphere, we plan to use data provided by MLS (Microwave Limb Sounder instrument aboard the NASA/Aura satellite). IASI SO2 products generated by other processors and TROPOMI/S5P SO2 products will also be potential candidates for inter-comparison studies.
Proximal Gamma Ray Spectroscopy for monitoring Soil Water Content in vineyards
Authors: Franceschi Michele , Alberi Matteo , Antoni Marco , Baldi Ada , Barbagli Alessio , Beltramone Luisa , Carnevali Laura , Castellano Alessandro , Collodi Giovanni , Chiarelli Enrico , Colonna Tommaso , De Lucia Vivien , Ermini Andrea , Maino Andrea , Gallorini Fabio , Guastaldi Enrico , Lopane Nicola , Manes Antonio , Mantovani Fabio , Messeri Samuele , Petrone Dario , Pierini Silvio , Raptis Kassandra Giulia Cristina , Rindinella Andrea , Salvini Riccardo , Silvestri Daniele , Strati Virginia , Xhixha Gerti
Published: March 2024

Soil Water Content (SWC) is a key information in precision agriculture for obtaining high levels of efficiency and health of crops, while reducing water consumption. In particular, for the case of vineyards, due to the recent extreme temperature fluctuations, the knowledge of the SWC of the entire field becomes crucial to allow a timely intervention with emergency irrigation to preserve plant health and yield.Unlike electromagnetic SWC measurements, that are punctual and gravimetric measurements, that are punctual and also time-consuming, the Proximal Gamma Ray Spectroscopy (PGRS) technique can provide field-scale, non-invasive, and real-time measurements of SWC. This is achievable through an in-situ NaI detector, continuously recording photons resulting from the radioactive decay of 40K in the soil, which are attenuated proportionally based on the amount of stored water. Given the inverse proportionality between soil moisture and photons detected by the gamma ray sensor, the SWC value can be easily obtained.In this study we investigate the performance of PGRS applied to the case of study of a vineyard at the farm “Il Poggione” located in Montalcino (Siena, Italy).The effectiveness of the results obtained is supported by different tests: first the validation allowed to compare the PGRS measurement (5.8 ± 1.5)% with a gravimetric measurement (9.0 ± 2.5)%, highlighting a 1-σ agreement; then by the rainfall recognition capability indeed, in correspondence to the most significant rainfall event (18 mm) the SWC value before and after the rain increased of 7.8%.Moreover, the integration of the in-situ system with an agrometeorological station resulted in a Web App, allowing for real time data storage and thus facilitating data management, spectrum analysis, and display for both gamma ray sensor and agrometeorological station results, enabling comprehensive studies of environmental parameters (e.g., temperature, air humidity).This research underlines the potential of PGRS as a precise, real-time, and field scale SWC monitoring tool not only in vineyards but for cultivated fields in general. Further refinements concerning the gamma ray spectra analysis and broader applications in environmental monitoring are envisaged for improved agricultural practices.This study was supported by the project STELLA (Sistema inTEgrato per Lo studio del contenuto d'acqua in agricoLturA) (CUP: D94E20002180009) funded by the Tuscany region under the program POR FESR 2014/2020.
How Observation Noise impacts the Estimation of Codephase- and Phase-Center Correction with a Robot in the Field
Authors: Breva Yannick , Kröger Johannes , Kersten Tobias , Schön Steffen
Published: March 2024

To ensure an accurate and precise position in GNSS applications, phase center corrections (PCC) have to be taken into account. PCC are antenna and frequency dependent correction values. They describe the distance along the line-of-sight direction between the electrical phase center, where the GNSS signal is received, and the antenna reference point. In Melbourne-Wübenna or code-minus-carrier linear combinations, which are often used in highly precise GNSS applications, the codephase of the GNSS signal plays a key role. Similar to the PCC, also correction values for the codephase observation exist, called codephase center corrections (CPC), also known as group delay variations (GDV). The definition of CPC as well as their estimation process with a robot in the field is similar as for PCC.The team at Institut für Erdmessung is optimizing the established absolute antenna calibration approach for estimating CPC and PCC for multi GNSS signals in terms of repeatability, noise reduction and multipath impact. In this calibration process, an antenna under test (AUT) is precisely tilted and rotated around a fixed point in space by using a robot. A nearby reference station allows the calculation of time differenced single differences (dSD), which are used to estimate absolute CPC and PCC with spherical harmonics of degree and order 8. The pattern quality and also the repeatability of this approach depends, among other effects, on the observation noise of the GNSS signals.In this contribution, a detailed study about the influence of observation noise on the estimated patterns is presented. To this end, dSD are simulated based on an existing pattern and the robot positioning. The dSD are modified before the estimation process by polluting them with different kind and magnitude of noise. The estimated patterns are compared using e.g. the root-mean-square or the absolute difference between two runs. Our analysis shows, that 18% of the white noise magnitude is reflected in the repeatability of the pattern estimation in terms of absolute differences between two calibration runs. 
A Novel Bias-Adjustment Methodology for Streaming Global Climate Models
Authors: Sharifi Ehsan , Grayson Katherine , Müller Sebastian , Thober Stephan
Published: March 2024

Projections generated by global climate models (GCMs) are increasingly utilized to inform climate adaptation policies. It is known that climate models simplify the real climate system, leading to biases between simulated and observed climates. The spatial and temporal resolution of GCMs is ever increasing to provide a better representation of the Earth system and in turn, also provide higher quality information for users. To effectively handle the substantial climate data produced by these models, which can reach Terabytes to Petabytes, the Destination Earth (DestinE) initiative is exploring data streaming—a new approach that enables user applications to run Earth system models in an end-to-end workflow directly downstream of the climate simulations, eliminating the need to store entire time-series of variables to disk.Traditional methods for quantile or percentile calculation typically involve sorting the data and directly computing the specific value corresponding to the desired quantile. These methods can be computationally intensive, especially for large datasets, as it necessitates storing and processing the entire dataset. While traditional bias-adjustment (BA) algorithms rely on data being fully available, a further challenge lies in developing bias-adjustment procedures capable of accommodating streamed data on-the-fly. In the DestinE Climate Digital Twin (CDT), we extend the quantile-mapping technique used in the ISI-MIP project (isimip.org) because it is a well-established method and preserves the trend of the original data. The technique involves aligning the CDFs of the model data with those of the observed data by adjusting the model's cumulative distribution to match that of the observed data. The enhancements of the BA method in DestinE-CDT is making use of the T-Digest algorithm, a sophisticated strategy that dynamically clusters data points into small groups, which is used to generate a summarized representation of the data distribution from streamed data and accurately calculate percentiles. This clustering technique offers an accurate estimate of percentiles while efficiently managing large and unbounded data streams where new data points are continuously added.We apply the developed quantile-mapping BA for different variables on a global scale and compare it with the parametric distribution functions used in quantile-mapping BA from the ISI-MIP project.
Modeling the along-fault variability of slow earthquakes in subduction zones based on a combined Maxwell Viscoelastic and damaging rheology
Authors: Massoumi Sina , Dansereau Véronique , Weiss Jérôme , Campillo Michel , Shapiro Nikolai M.
Published: March 2024

Slow earthquakes are transient events detected with geodetic (slow slip) and/or seismic (low-frequency earthquakes and tremors) observations that release energy over a period of hours to months, i.e., much longer than regular earthquakes. These events are observed in several subduction at a specific range of depths and with their properties, such as strength, duration, recurrence interval, and predominance of either slip or seismic components varying along the subduction interface. In this study, we investigate slow earthquakes based on numerical modeling by applying a combined Maxwell viscoelastic and damaging rheology. Unlike conventional rate and state modeling practices utilizing infinitely thin fault assumptions with fault friction laws, our approach incorporates a finite fault thickness through a damage mechanism and suitable failure criteria. Our model directly predicts a geodetically observable slow displacement, while rock damaging rate is considered as a proxy to seismic tremors.We run a set of numerical simulations to systematically explore the effects of model parameters such as viscosity, yield stress, and healing time on slow slip and tremors. We then incorporate along-fault variations in temperature, pore pressure, and permeability rate to infer changes in viscosity, yield stress, and healing time. The model successfully reproduces the observed synchronous episodes of slow slip and tremors in the initial stage. We show that decreasing strength and healing time results in reducing the recurrence intervals between these episodes and the amplitude of slow slip. Conversely, decreasing viscosity leads to a larger recurrence time and increased amplitude. After introducing the along-fault variability of main mechanical parameters, the model successfully predicts tremor concentration in the downdip zone which can be explained by the influence of high pore pressure in the yield stress profile as a function of depth. The capacity of the model to reproduce some patterns seen in observations underscores its capacity to capture the physics of slow earthquakes, emphasizing its potential to improve our understanding of seismic phenomena in subduction zones.
Formation and Kinematics of Basal Layer in Granular Flows Down Smooth and Rough Inclines
Authors: Wang Teng , Jing Lu , Kwok Fiona
Published: March 2024

Granular flow down a rough incline is a typical model case for geophysical mass flows. For insufficiently rough inclines, a strongly sheared basal layer can form below the less agitated bulk layer due to basal slip and particle collisions. However, the thickness and kinematic characteristics of the basal layer has not been well understood. Here, discrete element method (DEM) simulations are carried out to investigate the effects of base roughness on various kinematics profiles (i.e., velocity, shear rate and granular temperature) of the basal layer. The base roughness is varied systematically from geometrically smooth (i.e., a flat frictional plane) to moderately and sufficiently rough (formed by a layer of stationary particles). The base roughness is quantified by a dimensionless parameter, Ra, varying from 0 to 1, which has previously been found to control the transition from slip to non-slip regimes at around Ra=0.6. The present results show that, when basal slip occurs, the velocity profile deviates from the standard Bagnold’s profile, with an apparent basal slip and a basal layer where particles are highly agitated. The thickness of the basal layer, the slip velocity, and the level of velocity fluctuations (granular temperature) in the basal layer are all controlled by Ra. Intriguingly, the thickness of the basal layer, which is about several particle diameters, is insignificantly affected by other simulation conditions including the flow thickness and slope angle. Finally, the velocity profile is accurately described by a semi-empirical function based on the strong association between granular temperature and shear rate. Future work will focus on the rheology of the basal layer, which will potentially lead to more accurate predictions of geophysical granular flows.
Climate change fragments Mediterranean seagrasses landscapes: a regional analysis
Authors: Baldan Damiano , Gianni Fabrizio , Reale Marco , Bandelj Vinko
Published: March 2024

Seagrasses meadows represent a key habitat of the Mediterranean Sea, since they host a significant biodiversity. Projected changes in seagrasses distributions driven, for instance, by climate change, could dramatically alter the structure of the Mediterranean seascape, with relevant cascading effects on the biodiversity of the basin. In this work, first we combined post-processed COPERNICUS-CMEMS physical and biogeochemical variables and seagrasses occurrences from the Ocean Biodiversity Information System (OBIS) to setup Species Distribution Models (SDMs) for Posidonia Oceanica and Cymodocea nodosa: two dominant mediterranean seagrasses. Then, future changes in their distribution along the 21st century using high resolution physical and biogeochemical projections under two Representative Concentration Pathways (RCP), namely 4.5 and 8.5, have been assessed. In particular, the future changes in the range contraction and distances between suitable habitat patches have been estimated. A significant change in both quantities was detected. The potential implication of an increased fragmentation for metapopulations and metacommunities relying on this habitat is discussed.
Wave Climate Analysis near the Irish Coast: SWAN-WAM Modeling from Present to the Future.
Authors: Kalayil Uthaman Ashly , Dabrowski Tomasz , McCarthy Gerard , Brune Sebastian , Düsterhus André
Published: March 2024

Coastal regions are dynamic environments influenced by various atmospheric and oceanic processes. Understanding the complex interplay of these forces is crucial for coastal management, navigation, and impact assessments. This becomes especially crucial when investigating climatological scale dynamics.In this study, two state-of-the-art third-generation wave models, WAM-Cycle 6 (Wave Action Model) and SWAN 41.45 (Simulating Waves Nearshore – Version 41.45) are utilized for numerical wave projection. The methodology involves nested modeling approach by configuring SWAN within WAM to simulate waves at finer resolution near the Irish coast. This setup involves WAM operating on a coarser grid (1.0 degree), an intermediate WAM grid with a resolution of 0.5 degree, and SWAN running on a finer grid (0.025 degree). Wind forcing (10 m wind speed) from climate reanalysis produced by ECMWF (ERA5) is used to drive the wave model. A comparison with wave buoys at different locations around Ireland showed that models agreed on the significant wave height with bias and RMSE differing at most 0.6m.Statistical techniques are utilized to connect the Max Planck Institute Earth System Model to ERA5 wind data, which is employed as forcing for the wave models to predict waves on climatological scales. The current model setup not only focuses on the present wave conditions but extends to provide future predictions and projections utilizing input data from climate models. By combining the insights from the present with the predictions and projections for the future, the current study aims to provide valuable information for decision-makers in the near and long-term future.
Alkenone-based sea surface salinity and temperature reconstructions across late Pliocene sapropels from the Eastern Mediterranean Sea
Authors: van der Hoeven Isabel , Hättig Katrin , Mol Eduard , van der Meer Marcel , Hennekam Rick , Reichart Gert-Jan
Published: March 2024

The Eastern Mediterranean sapropels were deposited during periods of increased monsoonal runoff, enhanced export productivity, salinity stratification and deep-sea anoxia since the Miocene. The most pronounced sapropels, with total organic carbon (TOC) contents up to 30%, formed during the late Pliocene (3.16-2.94 Ma). It remains enigmatic which environmental conditions caused the deposition of these high-TOC sapropels.Here, we aim to record spatiotemporal changes in sea surface salinity (SSS) and sea surface temperature (SST) associated with sapropel formation. We use compound-specific hydrogen isotope analysis of C37:2 alkenones (δ²Halkenone) as a proxy for SSS. This proxy is, in contrast to δ18Oforam, independent of temperature and can be applied to organic-rich samples that lack foraminifera. In addition, we use alkenone-based Uk'37 to estimate SSTs. We compare the δ²Halkenone signatures across the strongest late Pliocene sapropels from ODP sites 967 and 969 to that of a slightly younger, lower-TOC sapropel.The δ²Halkenone value in marls is comparable to modern-day Mediterranean δ²Halkenone values and across the strongest sapropels, the δ²Halkenone shift of 15-35‰ is comparable to that recorded in sapropel S5. This suggests that freshwater forcing was not exceptionally strong during the deposition of the late Pliocene sapropels. However, in the marls prior to the high-TOC sapropel at 2.95 Ma, δ²Halkenone is ~20‰ more depleted and reconstructed SSTs are higher.We discuss the salinity forcing on sapropel development and investigate if and how initial warmer and fresher surface waters could have affected the formation of this particularly high-TOC sapropel.
Assessing the correlation of Time-Series Soil Moisture and Ground Deformation At Petacciato Landslide, Italy
Authors: Rana Divyeshkumar , Mazzanti Prof. Paolo , Bozzano Prof. Francesca
Published: March 2024

Soil moisture is an important parameter in many fields, including agriculture, climatology, hydrology, and geohazards. Accurate and high spatial resolution soil moisture estimation can improve our understanding of hydrological processes, and climatic interaction, and a more complete view of the domain. Soil moisture estimation can enhance our understanding of preparedness for natural hazards such as landslides, sinkholes, and subsidence. Single-dual polarimetric data is widely used for assessing and monitoring soil moisture due to the availability of datasets. This research proposes a synergized approach using the change detection method based on backscatter information using SAOCOM L-Band Synthetic Aperture Radar (SAR) datasets from 2021 to 2023 to estimate soil moisture and ground deformation using Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) using CosmoSkyMED X-Band datasets from 2011 to 2022. We present a case study of the Petacciato landslide, Molise Region, Italy. The Petacciato landslide is a coastal area in Europe highly prone to mass movements. It is in the northwestern sector of the Molise region (central Italy) in the outermost portion of the central-southern Apennine chain. Timeseries soil moisture results were further compared with the historical open-source meteorological datasets. Precipitation events lead to the most soil moisture that is observed between November to February months. The average ground deformation (LOS velocity) observed on unstable slopes ranged from -1 mm/year to -20 mm/year in the study area.
Optimal Experimental Design strategies for geoelectrical monitoring of fluid transport processes
Authors: Menzel Nino , Uhlemann Sebastian , Wagner Florian M.
Published: March 2024

Electrical resistivity tomography (ERT) offers noninvasive monitoring capabilities for a wide range of environmentally relevant subsurface processes. Its sensitivity to fluid content and temperature changes positions it as an important tool for capturing dynamic processes such as the transport of groundwater pollutants, CO2 or radionuclides. Particularly crucial is its ability to achieve this without intrusively accessing to the site, making it highly valuable in closed repositories like high-level radioactive waste (HLW) storage sites.In highly sensitive and complex environments, as in the case of closed repositories, it is critical to maximize the information content of the planned (geo)physical measurements while keeping the costs to a minimum. Several past studies presented approaches to optimize both the sensor positions and the measurement configurations of ERT surveys for static or moving targets in the subsurface. This study extends Optimal Experimental Design (OED) strategies for geoelectrical measurements using information of active time-dependent transport processes in the subsurface. We present three different approaches for process monitoring and apply them to a simulated diffusive-advective transport process in a synthetic model over several time steps. The methods aim at focusing the survey only on the relevant part of the model, in this case the model region that is affected by the transport process. All presented approaches account for uncertain model input parameters by introducing an uncertainty factor in the ranking function. We present a purely model-driven and a purely data-driven active time-dependent OED approach. The first method utilizes the already acquired data from previous time steps to create predictive focusing masks for the next data set, the latter purely relies on model predictions to focus the survey. Moreover, we delineate a hybrid approach using both the simulated transport distance and the already acquired datasets. All three OED methods are compared to each other as well as to datasets that were acquired using standard electrode configurations.The results of our synthetic study show that the adaptively designed, time-dependent OED approaches result in increased image quality compared to both standard surveys as well as time-independent OED methods. For slow transport processes or small monitoring intervals, the purely data-driven approach is most suitable, since no model predictions, and thus no possible model parametrization uncertainties, are incorporated. For faster transport processes or monitoring strategies with larger acquisition intervals, the strategies that (partly) incorporate model predictions provide the most promising results.
How GIS tools and sensor-based data models are impacting the UAS civil missions: Identification of suitable vertical ports and optimal flight planning to quickly deliver defibrillators in alpine terrains
Authors: Mejia-Aguilar Abraham , Parin Riccardo , Ristorto Gianluca , Mayrguendter Sebastian , van Veelen Michiel
Published: March 2024

During the last decades, the introduction of Unmanned Aerial Systems (UASs) in civil applications has exponentially grown. Environmental monitoring, mapping, and surveying, agriculture and precision farming, (infra)structure inspection, and medical supplies delivery are some clear examples. For many of these applications, the organization and planning of the missions are very similar: the variables or phenomena are clearly identified, the area of interest is previously defined, the flight plans are meticulously prepared to extract the features of interest (e.g. overlap and constant elevation for high-quality orthomosaics), the payload and on-board instrumentation is previously configured, the crew is informed in advanced about the objective of the missions, and in general, all these missions are executed in really good weather conditions. However, for some applications, like UAS-assisted Mountain Emergency Medicine, these protocols are totally different, because of the type of emergency (search and rescue operation, first kit provision, avalanche search) resulting in a quick and efficient configuration of payloads, accuracy of the reported incident (accuracy of GPS and distress call), preparation and level of stress for the rescue teams operators and adverse weather conditions (poor visibility, unknown terrain, wind, snow, rain). In addition, the physical localization of the UASs is in regional stations, so it is necessary to mobilize equipment and crew in a very short time to guarantee the success of the missions or, ideally, standby at distributed sites for autonomous operation if cleared for take-off from remote. In order to attend any mountain emergency that requires the use of UASs inside of the Province of South Tyrol, Italy (alpine region) to identify the most suitable operations area (vertical port), to elaborate an efficient point-to-point flight plan maximizing the use of its batteries (considering changes of terrain, elevation, and possible obstacles), and delivering a defibrillator (specific use case), here we propose a basic data management system based on Geographic Information Systems (GIS) that create a distributed vertical port stations in the Province and identify the closest point to the distress call. The system is able to plan an efficient flight plan in a mountainous area using a sensor-based data model based on a commercial UAS system (MAVTech Q4X) to provide a dedicated payload (defibrillator). We used the system in two scenarios (winter and summer) and they showed a reduction of nearly 50% of the delivery time of the defibrillator by traditional means.