bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Low-Temperature Dolomite as a Biosignature
Authors: Sánchez-Román Mónica
Published: March 2024

Carbonates are prevalent in the geologic record throughout Earth's history and are also found on Mars and within meteorites. The chemical and isotopic compositions of carbonates have been used to elucidate the composition of ancient oceans and the prevailing conditions during the development of life and its subsequent rapid evolution1-5. Carbonate mineral compositions reflect the environmental conditions under which they were formed4,5 . Dolomite is particularly abundant in ancient rock formations but is scarce in modern sedimentary environments. Many ancient dolomites are suspected of being alteration products of preexisting dolomite phases rather than being originally formed, unaltered dolomites6. The geochemical and neomorphic alteration of dolomite have been studied extensively, with the principal driving forces for neomorphism being the inherent thermodynamic instability of non-stoichiometric dolomites and the surface free energy-driven recrystallization of fine crystalline mosaics to coarser crystalline6.  Recent studies have demonstrated that microorganisms can produce dolomite with a geochemical signature distinct from those formed abiotically1-4. Our research integrates field studies, state-of-the-art laboratory experiments, mineralogical, and geochemical analyses to investigate the processes and environmental conditions that control the chemical composition of low-temperature carbonates. The role of inorganic-organic interactions is evaluated in natural field laboratories and carefully controlled laboratory experiments performed under abiotic and biotic conditions. In summary, the research focuses on understanding the processes and environmental conditions that control the chemical composition of low-temperature dolomite. A multidisciplinary approach, integrating field studies, laboratory experiments, microscopic, mineralogical, and geochemical analyses, is employed to investigate the role of inorganic-organic interactions in the formation of these carbonates. This work has the potential to provide insights into the development of life on Earth and the evolution of terrestrial and Martian carbonates. References:[1] Sánchez-Román M., et al. (2011) Chemical Geology 281, 143 - 150.[2] Sánchez-Román M., et al. (2014) Scientific Reports 4, 4767.[3] Sanchez-Roman M., et al (2023) Geochimica et Cosmochimica Acta 356, 66-82.[4] Sánchez-Román M., et al. (2011) Geochimica et Cosmochimica Acta 75, 887-904.[5] Li M., et al. (2021) Geology 49, 698–702.[6] Mazzullo, S.J., et al. (1991) Carbonates Evaporites 7, 21–37.  
The mobile Finnish Seismic Instrument Pool
Authors: Courbis Roméo , Hillers Gregor , Koivisto Emilia , Haapanala Päivi , Kukkonen Ilmo , Ding Yinshuai , Fordell Thomas , Heinonen Suvi , Junno Niina , Juntunen Anssi , Komminaho Kari , Kozlovskaya Elena , Leveinen Jussi , Moisio Kari , Näränen Jyri , Oksanen Tahvo , Skyttä Pietari , Tanskanen Eija , Tiira Timo
Published: March 2024

We report on establishing the Finnish mobile seismic instrument pool that is owned and operated by seven Finnish academic and research institutions. The pool infrastructure is funded by the Research Council of Finland, through the FLEX-EPOS project and under the FIN-EPOS umbrella. It is financing the build-up stage and started in 2021 with an end in 2024. By then the seismic instrumentation is anticipated to include 46 Güralp broadband seismometers, 5 Güralp accelerometers, and 1197 and 70 Geospace and SmartSolo self-contained geophone units, respectively. It is making this probably the largest coherent mobile seismic instrument pool in Europe in the public sector. The pool supports domestic and international collaborative projects of temporary deployments to enhance data-driven subsurface and environmental applications. Those deployments are for active or passive experiments and can last a few days up to a few years. The acquisition of such pool is motivated and facilitated by the advent of efficient data storage and transmission and powerful computing systems; progress in the understanding of the seismic wavefield coupled with the development of new types of analysis techniques and algorithms; and the manufacturing of sensitive, affordable data-dense sensor systems. Despite these game-changing and promising developments, the access to many seismic sensors for large-N deployments is not pervasive. Even in developed countries, it is challenging for a single institution to acquire and maintain a sufficiently large mobile pool of instruments and ensure sustainable data production and distribution. Our report on the equipment, facilities, ownership, and governance structure, project management, and data systems is essential background information for the access to and utilization of the pool instruments, and the interaction with the support community. A discussion about best practices for establishing and maintaining a mobile pool infrastructure can benefit from our experience of building such an extensive public seismic infrastructure from the ground up, and it provides relevant information for communities considering similar research infrastructure projects. Among the many challenges and opportunities associated with establishing effective pool management and operations, we highlight the lack of a coherent community protocol to store, find, disseminate, and analyze the associated large datasets. The Finnish mobile seismic instrument pool actively engages with ORFEUS/EIDA and the Geo-INQUIRE project to contribute to developing community solutions for data discovery and accessibility.
A comprehensive study on the causes of Global Dimming and Brightening using a radiative transfer model and satellite and reanalysis input data 
Authors: Stamatis Michael , Hatzianastassiou Nikolaos , Korras Carraca Marios Bruno , Matsoukas Christos , Wild Martin , Vardavas Ilias
Published: March 2024

Global Dimming and Brightening (GDB), which refers to the decrease/increase of incoming total solar radiation at the Earth's surface (or surface solar radiation, SSR) due to natural or anthropogenic composition changes of the Earth’s atmosphere, plays an important role in the Earth’s climate. According to the literature, the main drivers of the phenomenon are aerosols and clouds, contributing to GDB to different degrees depending on the world region and time period. This study aims, using a detailed spectral radiation transfer model (RTM), to identify and quantify the causes of GDB worldwide on a climatological scale. Specifically, it intends to determine their contribution to GDB as well as their spatio-temporal variability, performing detailed analyses on a monthly basis and a spatial latitude/longitude resolution of 0.5°x0.625°, all over the globe and for the 35-year period 1984-2018. The RTM required input data, such as those for cloud and aerosol optical properties, are taken from a synergy of satellite and reanalysis databases, namely the EUMETSAT’s CLARA-A2 and the NASA’s ISCCP-H and MERRA-2. Model runs, which are the main/base runs, are performed at the aforementioned spatial and temporal resolution and coverage to accurately calculate solar fluxes and GDB. Τhe contribution of clouds (cloud amount-CA and cloud optical thickness-COT of low, middle, high and total clouds), aerosol optical properties (aerosol optical depth-AOD, single scattering albedo-SSA and asymmetry parameter-AP), water vapor and ozone to GDB during the 35-year period 1984-2018 are calculated through RTM computations in which each parameter is kept ‘frozen’ at its initial conditions, namely the first year of the study period (namely 1984). Then, the contribution of a parameter P to the overall GDB is estimated from the difference between the GDB of the main RTM run, with all parameters being activated, and the GDB of the run with ‘frozen’ P parameter. In addition to the overall 35-year investigation, the study is also conducted on a decadal time scale, as well as on global, hemispherical, regional, and land/ocean spatial scales, in order to investigate the contribution of each parameter to GDB in more detail.
Carbon diagenesis in dolomite- and calcite-bearing limnic sediments: A multi-phase stable isotope geochemical perspective on Lake Constance
Authors: Roeser Patricia , Böttcher Michael , Liebezeit Alina , Harms Ulrich , Epp Laura , Raschke Ulli , Schleheck David , Schmiedinger Iris , Anselmetti Flavio , Wessels Martin , Schwalb Antje
Published: March 2024

Placed in a carbonate-rich catchment at the northern foot of the Alps, Lake Constance is one of the largest lakes in Central Europe, and the hard water lake chemistry makes it a natural laboratory to investigate in detail the carbonate formation, preservation, and the interactions with the detrital carbonate fraction, the latter with a major dolomite component. The highly reactive lacustrine carbonates are great paleoenvironment archives - due to the climate sensitivity in their formation either as erosional sources of suspended matter or through lake internal processes; still, they are prone to diagenetic overprints that shall be considered in a major context. For that, the (post-)glacial sediment deposits were investigated up to 24 m long cores recovered from the northernmost deep portions of Lake Constance, at approximately 200 mwd. The benthic carbon cycle and mineral sources and (trans)formations, were investigated through porewaters and sedimentary solid phases analyses for stable isotope signatures (CHOS), and major- and trace element compositions.The water isotope signatures display a trend towards lighter data with depth, indicating the development in the lake water composition with time, superimposed by diffusion processes in the sediments. The dissolved inorganic carbon (DIC) concentrations increase below the sediment-water interface and are generally higher in the postglacial sediments, indicating that mineralization rates followed the enhancement of lake productivity under milder climate conditions. The δ13C-DIC shows the lightest values in the glacial sediments and displays an enrichment in Holocene sediments, together with pore water hydrochemistry, indicative of organic matter (OM) oxidation, carbonate dissolution, and potential involvement of methane. The sulfur isotope record indicates that minor dissimilatory sulfate reduction is involved in OM degradation. Bulk carbonate C and O isotope signatures show strong variations partly induced by non-authigenic dolomite. Vertical variations in the composition of porewaters, bulk, and acid-soluble phases, in combination with SEM investigations, allow insights about the (trans)formation of authigenic mineral phases and the destruction of allochthonous carbonates, as possible modifiers of the sedimentary record.
We Are the Possible: New Narratives Connecting Science, Health, Education and the Arts
Authors: Manosa Nyblon Cecilia , Flint Sally
Published: March 2024

Our future is unwritten, it will be shaped by who we choose to be and the actions we take now individually and collectively. At the University of Exeter (UoE) we have pioneered a new way of communicating climate science that really engages people intellectually and emotionally in the lead up to and at major international negotiations to feel the drive to respond to the call to action. Building on the long term legacy, narrative, and impact of our UoE’s  We Are the Possible (UAE 2023), We Still Have a Chance (Egypt 2022) and One Chance Left  (UK 2021), delivered successfully at the diplomatic and public spaces at COP, we have connected the UK and our global partners at the heart of the international conversation on confronting the climate crisis with determination, imagination, and hope, bridging the gap between science and the public. Our purpose is to use the platform of COP to communicate new climate narratives, linking science, health, arts, and education and build strategic partnerships to raise awareness of the urgent need for collective climate action among children, young people, policy makers and the public. To achieve our purpose, we co-create new narratives underpinned by world-class science. These new narratives are the bedrock for translation into sustainable theatre performances, large scale murals, music and soundscapes, digital visualisations and animation, education toolkits, workshops, storytelling events, and more. We will discuss the power of linking storytelling and new media possibilities to catalyse climate action and solutions with diverse audiences locally and globally.
Impact of climate change on coffee agrosystems and potential of adaptation measures
Authors: Della Peruta Raniero , Mereu Valentina , Spano Donatella , Marras Serena , Trabucco Antonio
Published: March 2024

Coffee is one of the most economically important agri-food systems globally, and is the main source of income for many rural households in several developing countries. Ongoing climate change could cause problems for sustainable coffee production, with greater instability from year to year and lower average yields. To overcome these problems, possible adaptation measures and agronomic practices should be evaluated, such as intercropping with other tree species that can provide more shade for coffee plants and promote resilience and environmental sustainability. To study the effectiveness of such options, the use of process-based models can be very useful.The DynACof model was developed specifically to simulate coffee agrosystems, including phenological development, physiological processes related to flower and fruit production, carbon allocation, the effect of water availability, light and temperature, and management. We validated the yields modeled by DynACof with productivity data available from some sites and areas included in previous evaluation studies in Mexico, Rwanda, Brazil, Ethiopia, and Costa Rica. We then developed and established a modeling framework in which the model can be applied spatially on a continental or pan-tropical scale, using extended climate projection ensemble and soil geodata.Our modelling tool was then used to simulate potential yields in Latin America and Africa for both 1985-2014 and 2036-2065, using an ensemble of statistically downscaled and bias adjusted climate projections for two different shared socioeconomic pathways. Comparing the two periods, the model predicts a decrease in yields between 23 and 35 percent in Latin America and between 16 and 21 percent in Africa. The spatial representation of these changes indicates a likely future shift of suitable production areas to higher elevations, possibly impacting fragile mountain ecosystems. We simulated a specific management option, namely increased agroforestry shading, to evaluate its effectiveness in improving resilience to climate risks. The results suggest that increased tree shading could partially reverse the trend of declining yields due to climate change in some lowland areas. However, these preliminary results must be confirmed by further analyses. Impact analysis and adaptation modeling of coffee agrosystems, together with socioeconomic indicators, have the potential to delineate realistic integrated risk assessments and support effective adaptation recommendations.
Verification of seasonal forecast for facilitating agricultural applications
Authors: Takaya Yuhei , Iizumi Toshichika , Masutomi Yuji , Nakaegawa Toshiyuki
Published: March 2024

Seasonal forecasting has the potential to support agricultural activities by offering crop-yield forecasts and facilitating measures to mitigate weather-related damages. This study aims to enhance the application of subseasonal to seasonal (S2S) forecasts in agriculture by evaluating them through tailored verification methods that consider crop calendars and areas.The verification employs the so-called 1-norm continuous ranked probability score (CRPS), which utilizes the absolute norm instead of a square to quantify forecast errors. While the 1-norm CRPS is not a proper score and does not suit for ensemble forecast verification, it offers an advantage in terms of user-friendliness. Specifically, the score is proportional to the expectation of the absolute error, and thus, it is easier to relate the outcomes of crop models under the assumption of linearity compared to other scores like the ordinal CRPS.Crop regions and seasons for major commodity crops such as wheat, rice, and maize were identified using global datasets of crop yields and crop calendars. Using the crop calendar information, we can assess the within-season forecast performance in relation to crop growth stages globally. Reforecast data from seasonal forecasts archived by the EU-funded Copernicus Climate Change Service (C3S) were evaluated, allowing for a multi-model comparison of forecast skill. The presentation illustrates a set of example verification products targeted to the common commodity crops. A comprehensive overview of forecast skill for the target crops is anticipated to facilitate a dialogue between meteorological and agricultural experts, thereby enhancing the usability of the seasonal forecast.
The PhilEO Geospatial Foundation Model Suite
Authors: Le Saux Bertrand , Fibaek Casper , Camilleri Luke , Luyts Andreas , Dionelis Nikolaos , Cascarano Giacomo Donato , Bagaglini Leonardo , Pasquali Giorgio
Published: March 2024

Foundation Models (FMs) are the latest big advancement in AI that build upon Deep Learning. They have the ability to analyse large volumes of unlabeled Earth Observation (EO) data by learning at scale, identifying complex patterns and trends that may be difficult or even impossible to detect through traditional methods. These models can then be used as a base to create powerful applications that automatically identify, classify, and analyse features in EO data, unlocking the full potential of AI in EO like never before, providing a paradigm shift in the field.The field of geospatial FMs is blooming with milestones such as Seasonal Contrast (SeCo) [1] or Prithvi [2]. We present the PhilEO Suite: a dataset (the PhilEO Globe), a series of models (the PhilEO Pillars), and an evaluation testbed (the PhilEO Bench).In particular, the PhilEO Bench [3] is a novel framework to evaluate the performances of the numerous EO FM propositions on a unified set of downstream tasks. Indeed, there is the need now to assess them with respect to their expected qualities in terms of generalisation, universality, label efficiency, and easiness to derive specialised models. The PhilEO Bench comprises a fair testbed bringing independence to external factors and a novel 400GB global, stratified Sentinel-2 dataset containing labels for the three downstream tasks of building density estimation, road segmentation, and land cover classification. References[1] Oscar Manas, et al., “Seasonal Contrast: Unsupervised pre-training from uncurated remote sensing data,” in Proc. ICCV, 2021.[2] Johannes Jakubik, Sujit Roy, et al., “Foundation Models for Generalist Geospatial Artificial Intelligence,” arxiv:2310.18660, 2023.[3] Casper Fibaek, Luke Camilleri, Andreas Luyts, Nikolaos Dionelis, and Bertrand Le Saux, “PhilEO Bench: Evaluating Geo-Spatial Foundation Models,” arXiv:2401.04464, 2024.
ESA Swarm mission after 10 years in Space: new opportunities through enhanced processors and data quality
Authors: Forte Roberta , Qamili Enkelejda , Comparetti Nicola , Tøffner-Clausen Lars , Buchert Stephan , Burchill Johnathan , Siemes Christian , Maltese Alessandro , Mizerska Anna , Brazal Aragón María José , Trenchi Lorenzo , Iorfida Elisabetta , Cerro Herrero Irene , Hoyos Ortega Berta , Albini Giuseppe , De la Fuente Antonio , Stromme Anja
Published: March 2024

On 22nd November 2023 Swarm ESA’s Earth Explorer mission celebrated 10 years in Space, characterizing Earth’s geomagnetic, ionospheric and electric fields, for a better understanding of our planet’s interior and its environment. After a decade in orbit, the mission is still in excellent shape and continues to contribute to a wide range of scientific studies, from the core of our planet, via the mantle and the lithosphere, to the ionosphere and interactions with Solar wind, opening the door for many innovating applications largely beyond its original scope.Moreover, the processing algorithms have been continuously improved since the beginning of the mission, to cope with the evolving needs of the scientific community, to keep providing excellent quality data and to maintain good instruments performances.In April 2023 a “Fast” processing chain has been transferred to operations, providing Swarm L1B products with a minimum delay respect to the acquisition. This Fast data production adds significant value to Swarm mission’s scientific purposes and applications, making it eligible for monitoring Space Weather phenomena, modelling and nowcasting the evolution of several geomagnetic and ionospheric events.This work provides an overview of the Swarm enhanced data processing chain, instruments performances, Fast chain applications and upcoming evolutions, together with other innovative Swarm-based data products and services.
Rock avalanche runout prediction for suggested failure scenarios. Case study of Cima del Simano rockslide (Switzerland)
Authors: Wolff Charlotte , Jaboyedoff Michel , Pedrazzini Andrea , Derron Marc-Henri
Published: March 2024

Rock avalanches events pose significant concerns in mountainous regions characterised by deep and narrow valleys. This has not deterred the ongoing development in these areas, where population settlements and infrastructure continue to expand, becoming increasingly susceptible to these risks. Cima del Simano instability in the Swiss Alps, located in the narrow Blenio Valley, is a deep-seated rockslide which could trigger such events in the future. A previous work outlined several scenarios for the rockslide failure defined by a specific area, volume (ranging from 2.30x105 m3 to 4.30x106 m3), and susceptibility to happen.Given the proximity of a major road and several villages on both sides of the Valley, there is a real need to evaluate the potential runout distance in the event of rupture and propagation of the different failure scenarios. Literature often presents two distinct approaches for estimating the runout distance and the impacted area, both based on the retrospective analysis of historical landslide occurrence. The first approach is through empirical equations linking volumes of failure V and Fahrböschung angles f (tanf=aV^(-b), with a and b two empirical parameters to determine). The second approach consists in numerically simulating the flow propagation by means of dedicated software and by applying specific rheological models. This present work suggests applying both those techniques to evaluate the area that would be affected in the case of a rock avalanche at Cima del Simano, triggered by one of the suggested scenarios. We evaluated the runout distance for different angles f estimated based on the empirical relationship, and Dan3D for simulating the propagation applying the Voellmy rheology. Four simulations were conducted by varying the friction coefficient μ [-] and the parameter of turbulence ξ [m.s-2] in order to assess the minimal and maximal possible propagation in terms of runout distance L and lateral spreading based on domain of validity of those parameters according to literature. The distances L obtained empirically are longer than the ones from the simulations. This can be explained by the frontal confinement of the flow slowing down the propagation. The study is completed by an evaluation for each scenario of the probability of exceeding a certain distance L using existing statistical models for f variations. Additionally, the numerical simulations highlight the areas in gullies where debris are deposited during the flow propagation. Those areas can be sources for subsequent debris flow events. In a second step, we conducted an analysis of areas susceptible to debris flow with Flow-R and compared them with former debris flow events for validation. This study aligns with risk management to assist in making informed decisions regarding the evacuation plan in the event of a rupture and propagation of an important volume at Cima del Simano. 
Sea-level storylines to inform coastal adaptation planning and decision-making for the UK, South Africa and Southeast Asia
Authors: Weeks Jennifer , Palmer Matthew D. , Horton Benjamin P. , Ng Trina , Parnell Susan M. , Payne Antony
Published: March 2024

Implementing responses to sea-level rise requires accessible, credible and relevant sea-level information to facilitate effective use by practitioners and decision-makers. However, recent consultations have highlighted the need to better translate sea-level information to meet the physical and cultural diversity of decision-making and planning across the world. This includes communicating sea-level rise across a range of timescales, providing information tailored to different risk tolerances and better linking sea-level rise to impacts analysis to provide useful and usable metrics (e.g., Weeks et al., 2023, Environ. Res. Commun.). The presence of ambiguity in sea-level projections means there are limitations in the use of probabilistic approaches in coastal planning and decision-making (Kopp et al., 2023, Nature Climate Change). Storylines (physically consistent and plausible pathways of future climate events) are increasingly being used as a distillation tool presented alongside probabilistic sea level projections, for example to address the challenge of “deep uncertainty” associated with the future response of the ice sheets. Here, we focus on the regionalisation of sea-level projections into a set of discrete, actionable future pathways, to meet the needs of coastal adaptation planners and decision-makers. Building on the work of Palmer et al., (2020) (Earth’s Future), we generate a set of sea-level storylines for coastal city locations in the UK, South Africa and Southeast Asia, constrained by different emissions scenarios and high-end sea-level rise estimates. Locations are chosen based on their population density and geographical spread, whilst the regions allow consideration of the different risk profiles and contexts for decision-making. This work explores a range of decision-making contexts and how the storyline framework can be tailored to different user needs. 
Multi-temporal assessment of Groundwater Recharge Capacity in Protected Areas of Lithuania
Authors: Kalinauskas Marius , Pereira Paulo
Published: March 2024

Groundwater recharge is one of the key Ecosystem Services (ES) supplied by protected areas (PAs). However, such drivers as biodiversity loss, climate, and land use change affect the capacity for groundwater recharge (GRC). National-scale PA studies focused on GRC ES are scarce, thus leaving a knowledge gap on a global scale. Therefore, it is critical to map and assess the groundwater recharge spatiotemporal dynamics in supporting human wellbeing. In this study we mapped and assessed GRC at different timeframes (1990, 2000, 2012, 2018, 2022) in the PAs of Lithuania at national scale. For the model we used 15 indicators such as annual average evapotranspiration and precipitation, topographic properties (slope inclination, topographic position index, topographic wetness index, roughness index, curvature index, drainage density, lineament density), lithology, geomorphology, soil (texture, depth, imperviousness), land use (Corine Land Cover, Esri Land Cover). The results show that the highest GRC is observed in PAs to the west of the country, closer to the Baltic Sea, and PAs located in the eastern part of Lithuania with dense network of lakes, less intensive agriculture, fewer impervious areas, and soil properties more suitable for water infiltration. Lesser GRC is observed in urban PAs with higher imperviousness (Vilnius city). PAs in south and southwest of Lithuania with more intense agriculture practices, higher drainage density, and less water bodies also show lower GRC, as well as coastal PAs with sandy soils, no freshwater bodies, and higher roughness. The Kruskal-Wallis test showed no significant difference between GRC spatial distribution through different years due to low variation of evapotranspiration and precipitation values, and lesser land use changes within the PAs. Our findings contribute to a better understanding the spatiotemporal dynamics of one of the key provisioning ES in the Lithuanian PAs – the GRC. Mapping and assessing groundwater recharge support better management of the PAs, and contributes to achieving global and regional (e.g., Sustainable Development Goals, EU Biodiversity Strategy for 2030) policy targets.
Determination of the potential shear plane of a clay-rich, deep-seated landslide using spectral induced polarization and geotechnical approaches: case study Brandstatt, Lower Austria
Authors: Carraro Edoardo , Flores-Orozco Adrian , Monsalve Martinez Jorge , Marr Philipp , Glade Thomas
Published: March 2024

Increasing knowledge about the landslide geometries is key to understand the factors driving the slope instability. Direct investigations can provide information about the soil properties or locate features that help to recognize the mechanism of the landslide failure. However, this information is punctual and requires the interpolation of the data, which may lead to uncertainties due to the complexity of the geological context. Geophysical methods offer the capability to broaden spatial information, covering extended depths, and do not require interpolation. In particular, the induced polarization (IP) method has proven to be a powerful technique for investigating the hydrogeological properties of landslides. This method offers advantages in discriminating between interfacial and electrolytic (electrical) conduction mechanisms, which is crucial for the accurate interpretation of imaging results in clay-rich landslides. This is attributed to the IP method's capability of extracting not only electrical conductive properties but also capacitive (i.e., polarization effect) properties of the subsurface and its frequency dependence.In this work, we present the results of an ongoing investigation in the Brandstatt landslide (Lower Austria). This is characterized by a complex, slow-moving earth slides system, located in a geological transition zone between the Flysch and the Klippen Units and the Molasse zone, which is known to be a landslide-prone area. We applied a combination of different geotechnical methods, e.g., inclinometric measurements and dynamic probing (DP) tests, which have been carried out on the slope. We have conducted four IP profiles across the active area, each consisting of 32 electrodes with a spacing of 10 m. IP measurements were collected within frequency ranges of 0.25 to 225 Hz to discern the frequency dependence of the electrical properties and facilitate the quantification of hydraulic properties. The results of the investigations indicate different displacement rates and the presence of slip surfaces varying within the shallower layers. Additionally, IP imaging reveals the presence of high conductivity (50 mS/m) and polarization anomalies (20 µS/m) located in the first 40 meters, which are associated with the clay-rich area susceptible to movement. Furthermore, the contact with low conductivity values at depth indicates the geometry of the potential sliding plane. To potentially strengthen the correlation between the shallow information obtained by the geotechnical data and deep IP images, we examine the possibility of incorporating the results from surveys using electromagnetic methods. These results demonstrate that the combined application of direct and indirect methods allows us to gain better insight into large-scale subsurface variations that control small-scale changes in the surface and near-surface.
The impact of thermokarst development on flow and transport processes in alpine rock glaciers
Authors: Seelig Simon , Seelig Magdalena , Krainer Karl , Winkler Gerfried
Published: March 2024

Active rock glaciers represent permafrost-affected aquifers that govern the response of many alpine headwater catchments. Their heterogeneous internal structure tends to channelize groundwater flowing along the permafrost table or within the frozen rock glacier core. This study derives the hydraulic properties of such thermokarst channel systems at three active rock glaciers in the Austrian Alps. Their basic configuration is assessed through spring flow analysis and dye tracer tests. Breakthrough curves are characterized by multiple peaks and strong tailing, implying flow path separation and partial retardation of the tracer cloud travelling through the rock glaciers. Individual channels can reach diameters up to several decimeters and are characterized by a convoluted, irregular geometry. Flow along the channels is fast, highly turbulent, and characterized by high frictional resistance. Heat transfer is predominantly advective, inducing a positive feedback loop that allows larger channels to grow at the expense of smaller ones, effectively increasing the hydraulic conductivity at the rock glacier scale. The preferential flow paths provided by the thermokarst channel networks dominate flow and transport through the rock glaciers in particular during the summer months, and thus govern spring flow dynamics, solute transport, permafrost degradation, thermokarst lake outburst hazard, and rock glacier front stability.
The Effect of Data Limitations on Earthquake Forecasting Model Selection
Authors: Han Marta , Mizrahi Leila , Wiemer Stefan
Published: March 2024

In our recent study, we have developed an ETAS-based (Epidemic-Type Aftershock Sequence; Ogata, 1988) time-dependent earthquake forecasting model for Europe. Aside from inverting a basic set of parameters describing aftershock behaviour on a highly heterogeneous dataset, we have proposed several model variants, focusing on implementing the knowledge about spatial variations in the background rate inferred by ESHM20 already during the inversion of ETAS parameters, fixing the term dictating the productivity law to specific values to balance the more productive triggering by high-magnitude events (productivity law) with their much rarer occurrence (GR law), and using the b-positive method for the estimation of the b-value.When testing the model variants, we apply the commonly used approach of performing retrospective tests on each model to check for self-consistency over long time periods and pseudo-prospective tests for comparison of models on one-day forecasting periods during seven years. While such pseudo-prospective tests reveal that some models indeed outperform others, for other model pairs, no significant performance difference was detected.Here, we investigate in more detail the conditions under which performance differences of two competing models can be detected with statistical significance. Using synthetic tests, we investigate the effects of a catalog’s size and the magnitude range it covers on the significance of model performance difference. This will provide insight into whether recording many small events can, in this sense, replace having a large enough dataset of higher-magnitude events. Furthermore, due to the underrepresentation (or absence) of high-magnitude earthquakes in both training and testing data, both the models and tests are prone to overfitting to small events, potentially resulting in forecasts that underestimate both productivity of sequences with a high-magnitude main event and probabilities that a larger earthquake will follow such an event. We focus on defining metrics that highlight these properties as they are often of interest when applying time-dependent forecasting models to issuing operational earthquake forecasts.
Heat-related mortality projections for 335 European NUTs3 regions
Authors: Loroño Leturiondo Ane , Markandya Anil , Sainz de Murieta Elisa
Published: March 2024

Under climate change, heat waves are expected to become more frequent, more intense, and longer representing a risk factor in mortality and morbidity and a significant threat to public health [1]. In this study, we have performed a mortality impact assessment due to heat in European regions estimating the number of deaths related to mortality in each European country.Our dataset includes the relative risk of death related to high-temperature data, as well as baseline mortality (2013) and projections (2030, 2050, and 2070) for adults over 65 years. We have calculated the number of deaths attributed to heat using the World Health Organization (WHO) relative risk model [2]. Adaptation was partly incorporated into the assessment by adjusting the optimum temperature in future periods under 4 combinations of climate and socioeconomic scenarios (RCP2.6-SSP1, RCP4.5-SSP2, RCP7.0-SSP3 and RCP8.5-SSP5) based on the latest CMIP6 data.Preliminary results show that heat-related risk and the number of deaths increase with time, as expected. In the short term (2030), the increase in mortality measured as the ratio between projected and baseline mortality, does not change much across scenarios. The average rate of daily deaths for the EU27 is 2.054 (1.766,2.354) under SSP1-2.6 (the central estimate is the median, and percentiles 10 and 90 have been used for the interval), and 2.244 (1.853,2.694) in SSP5-8.5. Mortality increases over time, although it varies greatly depending on the scenario considered. By 2070 the number of fatalities reach 3.529 (2.849,4.88) in SSP1-2.6 and 7.658 (5.984,10.07) in SSP5-8.5. We also find significant differences across countries. By 2070, under a middle-row scenario (SSP2-4.5), countries such as Belgium, Bulgaria, Czechia, Denmark, Germany, Estonia, Croatia, Latvia, Lithuania, Finland, and Sweden present an increase in mortality between 2 and 3 fold baseline mortality. Others, mostly in Southern Europe such as Greece, France, Malta, Italy or Cyprus, but also Luxemburg and Slovenia, have a severe increase in mortality, 5 to 9 times baseline mortality.We also estimated the annual number of deaths in the EU27 due to extreme heat. In the baseline, our results are 72,955 annual deaths, which exceeds previous estimates, such as that obtained for the summer of 2022 [6], but this difference could be linked to the use of more recent CMIP6 data. In 2070, the number of heat-induced deaths in the EU could reach 211.039 (140.686,293.409) in SSP1-2.6 and 435.331 (283.927,671.089) in SSP5-8.5. Some studies [3] show that, under RCP8.5, annual mortality will possibly increase by up to 300,000 excess deaths by the last quarter of the 21st century, accounting for exposures above the minimum mortality temperature, including extremely hot temperatures, so our figures do not differ much of these estimates, even though they are higher than some others [4, 5].  
Near real-time retrieval of weak plume source parameters: Insights from physical modeling and Meteosat data
Authors: Michaud-Dubuy Audrey , Gouhier Mathieu , Guéhenneux Yannick
Published: March 2024

The prediction of the spatial and temporal evolution of ash dispersal and concentrations during an explosive volcanic eruption is crucial for crisis management. Satellite observations of volcanic ash clouds have enabled an important advance in the near-real-time quantification of the dynamic parameters of the volcanic umbrella propagating in the atmosphere. However, the link between these observations and the estimation of the eruptive source parameters (ESPs), such as the mass eruption rate (MER), remains a scientific obstacle to be overcome.Previous studies developed methods to estimate the MER based on the temporal evolution of the volcanic umbrella obtained by visible images. The accuracy of the predictions however strongly depends on the physical model used to link the measurements made on the umbrella to the source conditions. These methods are reliable for eruptions where the impact of wind is low on the vertical plume (i.e., producing “strong plumes”), but are less suitable for weaker eruptions and/or occurring under strong wind conditions (thus producing “weak plumes”), which are much more frequent. In this study, we use the 1-D volcanic column model PPM for the estimation of ESPs based on umbrella measurements from strong to weak plumes. PPM takes into account the precise effects of wind and particle sedimentation on the plume dynamics, and has already been validated with natural data on Plinian eruptions.The model allows predicting the plume geometry as seen from space, but close to the eruptive vent. These predictions are then used to link the MER to the umbrella geometry far from the source via an empirical factor  that connects the conditions at the neutral buoyancy height to those at the source of the umbrella cloud. The model is calibrated and tested using Meteosat-SEVIRI (MSG) images via the HOTVOLC system of paroxysms from Mt Etna (2015-2022) and from the Soufriere Saint Vincent (2021). The model allows estimating the temporal evolution of the MER during the Soufriere Saint Vincent eruption, with values consistent with those estimated in the field. The model also provides a theoretical framework to explain the geometry of weak plumes from Mt Etna. Ultimately, this study will provide a robust tool for a rapid interpretation of satellite data in terms of source conditions, which are necessary inputs for volcanic ash transport and dispersion models, such as those used by the Volcanic Ash Advisory Centers.
Watershed Resilience - Soil and Water Management in Arid Regions to Prevent Desertification
Authors: Haddad Mira , Worqlul Abeyou , Abu Hammour Doa’a , Hilali Muhi El-Dine , Gazal Osama
Published: March 2024

 Jordan faces a critical challenge of land degradation and water scarcity, primarily affecting the extensive natural rangeland (Badia), which covers over 80% of the country's area. The degradation of natural vegetation, adversely affects local agropastoral communities that are depending on livestock farming and triggeing downstream issues such as flash floods and sedimentation in dams. Water harvesting and increasing vegetation cover are promising technologies to adapt and reduce the impact.  The Badia Research Site (BRS), a confined watershed of approximately 1000 hectares, rainwater harvesting (RWH) and plantation techniques have shown promise in reducing soil erosion and runoff rates and enhancing various ecosystem services. The BRS research is mainly led by the International Center for Agricultural Research in the Dry Areas (ICARDA) and the Jordan National Agriculture Research Center (NARC), supported by the United States Forestry Service (USFS).  This study involves (1) scaling out two RWH techniques, namely the Vallerani and the Marab, on a larger basin. The scaling out utilises local and international datasets, incorporating biophysical parameters such as land use, digital elevation models, slope, topographic wetness index, soil texture, and climate data. Optimal ecological conditions for plants, including temperature and soil pH, are considered. (2) The Soil and Water Assessment Tool (SWAT) is employed to analyse and assess the impact on surface hydrological processes.  The focus is on the Wadi Al Mujib basin, covering 6584.37 km2 in the central part of Jordan. The semi-arid to arid environment comprises two principal wadies, Wadi Al Walah and Wadi Mujib, with distinct catchment surfaces. The basin's predominantly desert land, receiving varying levels of rainfall, poses challenges to 80% of its area, while the remaining 20% is dedicated to agricultural and residential use.  The study further employs the model to evaluate global climate change scenarios, assessing the impact and quantifying changes in ecosystem services with and without restoration efforts. These findings contribute to supporting the Jordanian government's restoration endeavours, offering a holistic approach to addressing land degradation and water scarcity challenges in the region. Keywords: Watershed assessment, Degraded land restoration, Suitability mapping, Water harvesting techniques, Sustainable land management, and Ecosystem Services
Predicting Global Seafloor Organic Carbon Burial Rates: A Deep Learning Approach with Uncertainty Quantification
Authors: Parameswaran Naveenkumar , Bur­wicz-Galerne Ewa , Gonzalez Everardo , Wallmann Klaus , Greenberg David , Braack Malte
Published: March 2024

Sediment accumulation rate is recognized as the primary parameter influencing the burial rate of organic carbon and other compounds in marine sediments. The prediction of a global map for burial rates is challenging due to the limited availability of measurements for total organic carbon (TOC) and sediment accumulation rates from the seafloor. Recent advancements in machine learning, including techniques such as K nearest Neighbours and Random Forests, have demonstrated promise in producing comprehensive predictions utilizing global maps of oceanic properties.
 
In this study, we introduce a sophisticated approach based on a newly developed deep neural network (DNN) model tailored for geospatial predictions. Employing few-shot learning techniques, such as the incorporation of prior physical knowledge into the model, along with strategies like multi-task learning and semi-supervised learning, enhances predictions amidst sparse data availability. Moreover, p​​​​​redictions of the global distribution of seafloor TOC and sediment accumulation rates presented here are coupled with uncertainty maps computed using Monte Carlo Dropout, a Bayesian approximation method that effectively inform about the degree of the model predictibility. With our results, we not only explore the global distribution of burial rates of organic carbon but also offer insights into the global carbon stocks in various marine regions.
Correlation between environmental variables and slope movements in the Ala Archa catchment, Kyrgyzstan
Authors: Gardeweg Rainer , Mathys Tamara , Hoelzle Martin , Allen Simon
Published: March 2024

In a time of increasing global warming and interconnected environmental changes, the assessment and detection of moving landforms are of growing importance for implementing successful adaptation and mitigation strategies concerning geohazards. Understanding the factors and processes governing slope movements, as well as their annual and seasonal variability, is of crucial significance. In recent years, advances in remote sensing applications and the availability of satellite data have been made, leading to an increased use of remotely sensed data for hazard monitoring and detection. Additionally, the use of machine learning enables the application of these methods to larger areas. Here, we concentrate on the Ala Archa catchment in Kyrgyzstan (Central Asia), located approximately 40 kilometres south of the capital city Bishkek, with a long history of glacier monitoring at Golubin Glacier.This study aims to identify the predominant environmental factors influencing slope movements within the Ala Arch catchment and investigates the contribution of variations in environmental conditions to annual fluctuations in slope movement. We first present an average velocity map for the area of interest using InSAR (Interferometric Synthetic Aperture Radar) with Sentinel-1 data from both ascending and descending orbits between 2018 and 2023. The data is processed using ISCE (InSAR Scientific Computing Environment) and MintPy (Miami InSAR Time-series software in Python). Additionally, we use statistical modelling to estimate the influence of selected environmental variables such as relief, permafrost distribution, vegetation cover and landform classification. To determine the influence on seasonal/annual variations, we incorporate fluctuating variables like air temperature, precipitation and the duration of snow cover. In a final step, we examine how the identified relationships can be applied to generate an upscaled regional susceptibility map for slope movement.In conclusion, our objective is to demonstrate the potential use of openly available satellite data for detecting hazardous or moving areas in regions where in-situ measurements are impractical or the necessary resources are unavailable.