bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparing AROME assimilation experiments for cloud-affected satellite observations
Authors: Chkeir Sandy , Weissmann Martin , Griewank Philipp , Meier Florian , Neduncheran Adhithiyan
Published: March 2024

Despite the abundance of satellite observations, their assimilation in all-sky scenarios remains difficult, which hinders the use of high-resolution information in forecast models. In this work, we focus on the direct assimilation of satellite radiances (visible 0.6 μm, infrared IR 6.2 and 7.3 μm of the Seviri instrument) under all-sky conditions into the convection-permitting Numerical Weather Prediction (NWP) model AROME, which is in operation at Geosphere Austria, the Austrian weather service. Our research aims to exploit the potential of assimilating visible and IR channels under all-sky conditions making use of convection-permitting weather models that can explicitly resolve deep convection. In particular, we are looking at the use of the Radiative Transfer for TOVS (RTTOV), as an observational operator, to generate synthetic images for each channel. We endeavor to optimize the operator settings for running simulations within the convective-scale AROME model. Our first experiment focuses on testing IR synthetic images generated under all-sky conditions during a summer period (August) over Austria. 
Perspectives on dynamic water quality modeling across continental and watershed scales
Authors: Miller Olivia , Ator Scott , Hess Mike , Jones Daniel , Longley Patrick , McDonnell Morgan , Miller Matthew , Putman Annie , Robertson Dale , Saad David , Schmadel Noah , Schwarz Gregory , Sekellick Andrew , Skinner Kenneth , Smith Richard , Wise Daniel
Published: March 2024

Stream water-quality and its drivers vary across time and space, but we only monitor a small fraction of streams consistently over long periods of time. Such limited monitoring necessitates the development and application of spatially explicit and dynamic models to predict water quality at unmonitored locations. Historically, data and computational limitations have hindered temporally variable prediction efforts across large spatial scales. However, hybrid statistical and process models, such as Spatially Referenced Regression on Watershed attributes (SPARROW), can provide spatially explicit, accurate predictions of water quality constituents with substantially lower computational cost than process-only models while retaining process-level information that can be obscured within machine learning models. An emerging next generation of such hybrid models moves beyond temporally static predictions into dynamic predictions. Here, we present regional- and continental-scale dynamic SPARROW models developed across the United States to simulate annual salinity and seasonal nutrient loads and concentrations over decades. Dynamic SPARROW models account for temporal variability of constituent sources and processes that deliver constituents from the landscape to streams. In addition, dynamic SPARROW models quantify lagged delivery of contaminants to streams that may have accumulated in soils, groundwater, and vegetation. Results quantify that legacy sources can vary by constituent, location, and time, and provide inference into river responses and lags to management activities. For example, groundwater storage contributes between 66 and 82% of the dissolved solids load to streams in the Upper Colorado River Basin, while lagged storage contributes on average between 20% to nearly 50% of the total nutrient load to Illinois River Basin streams.  Ongoing work to expand dynamic representation of loading up to the continental United States will provide further insight into the continually evolving impacts of legacy and other sources on riverine water quality. Dynamic representation of key processes across spatial scales provides new opportunities for more informed management that can improve water quality for human and ecosystem uses.
Report on In Situ Observations of the Anti-Correlated Variations in Freeze-in Temperatures of Heavy Ions in the Solar Wind
Authors: Gu Chaoran , Heidrich-Meisner Verena , Wimmer-Schweingruber Robert F.
Published: March 2024

When solar wind plasma propagates outward, the electron density decreases rapidly with solar distance, and charge states of heavy ions freeze in at 1 to 5 solar radii. Thus, charge states of heavy ions carry important information about the temperature profile in the lower corona. Oxygen and Iron ions are the most abundant heavy ions in the solar wind, and their data quality is relatively higher than that of other heavy ion species.Statistically, the averaged charge states of O and Fe in the solar wind usually maintain a weak positive correlation, sometimes exhibiting a strong positive correlation in solar wind associated with Coronal Mass Ejections (CMEs). The averaged charge states of O and Fe also correlate with solar wind speed and the solar cycle.In this study, we use ten years of in-situ solar wind Oxygen and Iron ion data obtained from the Solar Wind Ion Composition Spectrometer (SWICS) aboard the Advanced Composition Explorer (ACE). The data set is derived from Pulse Height Analysis (PHA) data, ensuring high time resolution (12 minutes).We identify around one hundred structures (time periods) where the averaged charge states of Fe and O exhibit significant anti-correlations (Spearman rank correlation coefficient lower than -0.5). These structures have distinct signatures. We analyze the time scales of these structures, the magnitudes of the averaged charge state variations for O and Fe, the temporal lags between the onset and end of those variations , the distribution of structures in the solar wind (e.g., whether they are associated with Interplanetary Coronal Mass Ejections (ICMEs) and their relative position within ICMEs), and their distribution in the solar cycle.Compared to more widely occurring positive correlation structures, anti-correlation structures are rarer and more interesting, reflecting the complex variations in the radial temperature profile and electron density profile of the lower corona. Large-scale anti-correlation structures suggest the presence of a relatively stable radial energy transfer process within 1 to 5 solar radii.
Influence of snow microstructure on the compressive strength of weak layers
Authors: Schöttner Jakob , Walet Melin , Adam Valentin , Rheinschmidt Florian , Rosendahl Philipp , Weißgraeber Philipp , Schweizer Jürg , van Herwijnen Alec
Published: March 2024

Slab avalanches result from the failure of a weak snowpack layer buried underneath a cohesive slab. Determining the material properties of different weak layer morphologies is therefore necessary to better understand and model slab avalanche formation. Natural weak layers exhibit a variety of different microstructures and densities, and thus show different mechanical behavior. Up to now, mechanical properties of snow have been mainly evaluated based on bulk proxies such as snow density, while relevant microstructural characteristics have not been accounted for.To establish a link between the microstructure of weak layers and their mechanical properties, we performed displacement-controlled laboratory experiments using a uniaxial testing machine. The compression experiments were recorded using a high-speed camera, allowing us to derive the strain within the weak layer. The microstructure of each batch of specimens was analyzed using micro-tomography to obtain density, specific surface area, anisotropy and correlation lengths. As testing a wide range of microstructural morphologies is difficult due to seasonal availability and the need to transport the fragile samples to the laboratory, we used both natural and artificially grown weak layers. We tested weak layers composed of facetted grains, depth hoar, surface hoar, precipitation particles and rounded grains.  The compressive strength of more than 200 tested samples covered two orders of magnitude (0.5 kPa to 150 kPa) for weak layer densities ranging from 110 kg/m3 to 380 kg/m3. As expected, our results show a strong correlation between weak layer density and compressive strength, but also a dependence on other microstructural quantities. These results will help us improve our understanding of the mechanical properties of weak snowpack layers and will ultimately allow us to better forecast avalanche release probability.
Unveiling subduction-related seismicity: towards a new global database
Authors: Brizzi Silvia , Heuret Arnauld , Piromallo Claudia , Corbi Fabio , Funiciello Francesca , Lallemand Serge
Published: March 2024

Subduction zones host the world’s largest earthquakes. Recent studies suggest complex interactions between megathrust, upper plate and intraslab seismicity. Understanding the spatio-temporal relationships of seismicity within subduction zones is challenging, yet essential for accurate seismic hazard assessment. A prerequisite for conducting these analyses involves the availability of a reliable and readily updatable dataset that classifies subduction seismicity into the three categories above.In this work, we compile a comprehensive global database of subduction-related earthquakes from 1976 to 2023, using the ISC-GEM catalog (Storchak et al., 2013; 2015; Di Giacomo et al., 2018) for events with magnitude Mw ≥ 5.5. Building on Heuret et al. (2011), we define 505 trench-normal transects across all active subduction zones, spaced at 1-degree intervals along the trench, partially overlapping and extending 120 km on both sides of a vertical plane. The seismicity in each transect is initially categorized into shallow (≤ 70 km) and deep (> 70 km) events. We then focus on the megathrust region, identifying earthquakes exhibiting a thrust focal mechanism with the  azimuth and dip of the focal planes aligning with the strike and dip of the megathrust along the transect. Subsequent steps involve categorizing the remaining earthquakes in the transect as either upper or subducting plate events. The classification uses the Slab 2.0 model (Hayes et al. 2018) when available, determining whether each earthquake occurs above or below the slab top surface.  In regions lacking Slab 2.0 data, geometric criteria are applied, considering the distance of the hypocenter to the trench. For each transect, this workflow yields three distinct seismicity classes: megathrust, upper plate, and intraslab earthquakes. Subsequently, seismicity from individual transects is merged into 62 broader segments (Heuret et al., 2011), ensuring the uniqueness of earthquakes in each segment.This automated workflow ensures the application of objective classification criteria and facilitates efficient analyses with each update of the ISC-GEM catalog. We compare key seismic parameters (e.g., maximum magnitude, number of events, cumulated seismic moment, recurrence time) across the different categories and segments. Additionally, we evaluate the correlation with a wide range of geological, geophysical, and geodynamical factors. This process not only provides an overview of the global behavior of subduction-related seismicity but also allows for the statistical identification of the combination of factors influencing subduction seismicity.
Fostering Community Governance of Nature-Based Solutions for Urban Stormwater Management: A System Dynamics Analysis of Power Decentralization
Authors: Muwafu Simon Peter , Manez Costa Maria
Published: March 2024

The integration of Nature-Based Solutions (NBS) in urban stormwater management holds transformative potential, promising enhanced adaptive capacities and numerous benefits for community well-being. Acknowledging the localized nature of NBS projects, primarily managed at the community level, this study delves into the prospects of integrating community governance into the planning, implementation, and success of NBS initiatives, especially in the context of urban flooding.With the overarching goal of identifying strategic leverage points for enhancing community governance structures in urban NBS implementation, the research employs a System Dynamics modeling approach, to investigate the impact of decentralizing decision-making authority to local communities on the scalability and sustainability of NBS in urban stormwater management. The analysis probes dynamic interactions and causal relationships among decentralized decision-making structures and critical variables such as community participation, institutional frameworks, and resource allocation that define community governance. Emphasizing a comprehensive understanding of feedback mechanisms, the study seeks to unravel processes shaping the adaptive capacities of NBS over time, particularly within the intricate context of adapting to the impacts of climate change.The study strives to provide insights into the mechanisms governing scalable integration, underscoring the vital role of community involvement and participatory governance in Nature-based flood solutions and in doing so, offering a crucial foundation for fostering sustainable and resilient urban development amid the escalating challenges posed by urban flooding and climate change. 
Investigating the water quality of rivers entering the Anzali Wetland
Authors: Ojani Mohammadreza , Ebrahimi Eisa , Kougir Chegini Zeynab , Szabó Szilárd
Published: March 2024

The Anzali wetland, a crucial water ecosystem in Iran, has been receiving water input from various rivers over the years and is currently facing a critical condition. We aimed to determine the proportional contribution of biogeochemical loads of anthropogenic origin by the rivers supplying the wetland. Accordingly, we analyzed monthly data from 2013 to 2015, encompassing discharge, total dissolved solids, calcium, magnesium, potassium, sulfate, chloride, bicarbonate, electrical conductivity, and water acidity in the primary river feeding into Anzali wetland. We found that the Pasikhan River exhibited the highest and Chafrood River the lowest average daily water flow, with 48 m3/s and 0.42 m3/s, respectively. The annual average of total soluble solids introduced into Anzali wetland through Pirbazar and Pasikhan rivers was 164,760 and 205,713 tons, respectively. Additionally, the inflow of other substances such as chloride and sulfate into the wetland is substantial. Overall, more than half of the wetland's water originates from the Pasikhan and Pirbazar rivers in the eastern region, where Pasikhan and Pirbazar rivers are dominantly utilized for agricultural and urban purposes, respectively. Based on the multivariate analysis we quantified the contribution of the rivers and the role of land use in the region as main factors of water quality. To rejuvenate the Anzali Wetland, effective catchment area management and governmental support are imperative, with particular emphasis on prioritizing the Pasikhan and Pirbazar rivers.Mohammadreza Ojani is funded by the Stipendium Hungarian scholarship under the joint executive program between Hungary and Iran.The study was elaborated under the research project NKFI K138079.Keywords: Water Pollution, Anzali Wetland, Water Analyze, Rivers, Water chemical parameters
Towards improved spatio-temporal selection of training data for LSTM-based flow forecasting models in Canadian basins
Authors: Snieder Everett , Khan Usman
Published: March 2024

Machine learning has extensively been applied to for flow forecasting in gauged basins. Increasingly, models generating forecasts in some basin(s) of interest are trained using data from beyond the study region. With increasingly large hydrological datasets, a new challenge emerges: given some region of interest, how do you select which basins to include among the training dataset?There is currently little guidance on selecting data from outside the basin(s) under study. An intuitive approach might be to select data from neighbouring basins, or basins with similar hydrological characteristics. However, a growing body of research suggests that including hydrologically dissimilar basins can in fact produce greater improvements to model generalisation. In this study, we use clustering as a simple yet effective method for identifying temporal and spatial hydrological diversity within a large hydrological dataset. The clustering results are used to generate information-rich subsets of data, that are used for model training. We compare the effects that basin subsets, that represent various hydrological characteristics, have on model generalisation.Our study shows that data within individual basins, and between hydrologically similar basins, contain high degrees of redundancy. In such cases, training data can be heavily undersampled with no adverse effects – or even moderate improvements to model performance. We also show that spatial hydrological diversity can hugely benefit model training, providing improved generalisation and a regularisation effect.
Investigating Vienna’s methane budget with local observations of turbulent fluxes and total column mole fractions
Authors: Matthews Bradley , Luther Andreas , Fasano Enrichetta , Tang Haoyue , Meeran Kathiravan , Leitner Simon , Watzinger Andrea , Chen Jia , Schume Helmut
Published: March 2024

Like other cities across the globe, Vienna has announced an ambitious climate target of reaching net zero emissions of greenhouse gases (GHG) by 2040. Developing and implementing appropriate urban polices and measures to reach this goal requires robust understanding and quantification of the emissions of all GHGs, including Methane (CH4). According to the Austrian provincial emission inventory (Bundesländer Luftschadstoff-Inventur) that sets the current baseline for Vienna’s planned emission reductions, CH4 emissions contribute only ca. 1% of the city’s total GHG budget (87 of 8387 kt CO2eq in 2021; 100-year global warming potential). However, urban sources of methane are associated with large uncertainties (e.g. leaks from gas distribution networks, post-meter fugitive emissions) with inventories often producing substantial underestimations of these emissions. The Vienna Urban Carbon Laboratory is currently investigating the CH4 budget of Austria’s capital city with local atmospheric observations of turbulent fluxes and total column mole fractions. Since May 2022, CH4 fluxes are being measured at the Arsenal radio tower using an eddy covariance system installed 144 m above the city.  Furthermore, between May and July 2022, a parallel measurement campaign with four ground-based, sun-viewing FTIR spectrometers (EM27/SUN) was conducted to measure horizontal gradients in total column CH4 mole fractions. This conference contribution will discuss the temporal and spatial patterns in the CH4 fluxes derived directly from eddy covariance observations so far, as well as the inverse estimates of summer CH4 emissions from the EM27/SUN observations. The two independent, observation-based methods will provide robust, and policy-relevant indications on the potential accuracy (or potential bias) in Vienna’s CH4 inventory.
Soil gas CO2 concentration, isotopic ratio and efflux measurements for geothermal exploration in La Palma, Canary Islands.
Authors: Martín Lorenzo Alba , Copete-Murillo Karen , Reyes Ángel , Gironés Ana , Melián Gladys V. , Asensio-Ramos María , Rodríguez Fátima , Padrón Eleazar , Padilla Germán D. , Hernández Pedro A. , Pérez Nemesio M.
Published: March 2024

Located in the northwest of Canary Islands, La Palma is one of the most volcanically active islands in the archipelago. The island experienced a volcanic eruption from 19 September to 13 December 2021, which had significant social, economic, and scientific impacts. This event serves as a reminder of the island's potential as a host for geothermal resources. Therefore, geochemical prospection of soil gases at Cumbre Vieja can provide valuable information for investigating the presence of permeable areas and potential upflow for degassing of geothermal systems at depth. This study was carried out between July and September 2023 and presents the results of a soil gas study located southwest of the 2021 lava flow. The survey aimed to identify permeable areas by conducting in-situ measurements of diffuse CO2 emissions and sampling and analyzing CO2 concentration and isotopic composition (δ13C-CO2). A total of 766 sampling sites were selected over an area of approximately 25 km2, with an average distance of 100 m between sites. Soil CO2 concentrations ranged from typical atmospheric values (≈ 400 ppm) up to 40,000 ppm. The average CO2 concentration measured was 1,700 ppm. The δ13C-CO2 isotopic composition revealed the presence of three distinct end-members: biogenic, atmospheric and deep-seated CO2, defined by isotopic compositions of 25‰>δ13C-CO2>-15‰, -8‰ and 2.1‰>δ13C-CO2>-8‰ and CO2 concentrations of 100%, 0.04% and 100%, respectively. Results show that, with a mean of -13.7‰, a minimum of -28.9‰ and a maximum of -4.8‰, CO2 at most sampling sites is composed of various mixtures of atmospheric and biogenic CO2, with some contributions from deep-seated CO2. The accumulation chamber method was used to measure soil CO2 efflux at each sampling site using a portable non-dispersive CO2 sensor, model LICOR-Li-820. The measured CO2 efflux values ranged from non-detectable to 160.3 g·m-2·d-1, with an average value of 4.7 g·m-2·d-1. For the estimation of the total diffuse CO2 emission from the study area, we calculated the average of 100 sequential Gaussian simulations. This gave a value of 100.8 ± 2.8 t·d-1, corresponding to a standardized emission rate of 4.1 t·km-2-d-1. The results show a significant correlation between the distribution of 222Rn gas activity anomalies and the highest CO2 efflux values in the eastern part of the study area. Soil gas measurements of CO2 concentration, isotopic ratio and efflux are a valuable and non-invasive technique for surface exploration, helping to define permeable areas and potential upflow zones of potential geothermal system structures and enabling an efficient subsequent subsurface exploration phase.
The Varsom Regobs System: Enhancing Natural Hazard Forecasting, Community Preparedness and Recreational Outdoor Activities through In-situ Crowd-Sourcing Observations 
Authors: Winsvold Solveig Havstad , Kvalberg Jørgen Loe , Widforss Aron , Myhre Øystein , Engeset Rune Verpe , Humstad Tore
Published: March 2024

The Varsom platform has been a success in Norway for more than a decade, with users from organizations and the public. It fosters a participatory approach encompassing recreational activities, hazard assessments, emergency preparedness, search and rescue, and forecasting. Here, we will present Varsom Regobs (Registering of Observations), an innovative crowd-sourced system within Varsom enabling registration, sharing, querying, and real-time storage and publication of field observations. Varsom Regobs aids decision-making for the warning services on snow avalanches, landslides, lake ice, and floods at the Norwegian Water Resources and Energy Directorate (NVE). Users utilize the Varsom app, website (www.regobs.no), and API to submit and retrieve diverse in-situ observations on the categories snow, ice, water, and soil, tailoring the level of detail. The app has gained widespread recognition within the community, boasting over 120,000 unique visitors between October 2023 and January 2024. In 2023 alone, a total of 22,000 observations across all categories were submitted. The app and website, available in multiple languages, have gained traction in numerous European countries, recording 500 observations outside Norway in 2023 thanks to the open-access policy.One successful aspect of enhancing natural hazard and hydrology monitoring has been the reciprocal engagement with users, and specific examples showcasing this will be provided. To address trust issues regarding non-academic observers, a star-based quality system has been implemented, aligning with an observer's training courses. Moreover, all users must possess an NVE-account login to submit their observations. Other challenges, such as managing spam-like entries and delicately targeting and engaging specific user groups for each category, will also be highlighted.Examples demonstrating the combined usage of the in-situ Varsom Regobs component, NVE's forecasting models, and NVE’s operational products derived from Copernicus satellite data will be showcased. The Regobs API v.5 ensures the utilization of observations in scientific projects by research institutes and universities. Varsom Regobs stands as a sustained citizen science initiative due to its integration into Norway's operational warning services, serving as an exemplary model for long-term engagement and collaboration.
Retracker-dependent radar freeboard correction methods for satellite radar altimetry-based sea ice thickness estimation
Authors: Shi Hoyeon , Dybkjær Gorm , Singha Suman , Lee Sang-Moo , Tonboe Rasmus , Baordo Fabrizio
Published: March 2024

Sea ice thickness is derived from its freeboard measured by satellite radar altimeters. However, the radar freeboard, which is initially estimated freeboard by interpreting the observed waveform, needs correction before sea ice thickness estimation so that it coincides with the height of the snow-ice interface from the sea surface. The so-called radar freeboard correction is thus an essential procedure for sea ice thickness estimation from satellite radar altimeter data, such as those from the CryoSat-2 mission. Today, most studies do the correction taking into account a slower wave propagation speed in the snow layer on sea ice under the assumption that the main scattering horizon is the snow-ice interface. However, while several recent studies have raised questions on that assumption, there is also a possibility that a retracker, which is an algorithm that estimates radar freeboard from waveform, has systematic bias. Accordingly, this study revisits the conventional way of doing the radar freeboard correction. First, we directly compare the CryoSat-2-derived radar freeboards from different retrackers with reference airborne freeboard measurements to introduce alternative correction methods for each retracker. Then, those correction methods are combined with a recently developed methodology where snow depth, sea ice thickness, freeboard, and ice draft are retrieved simultaneously. In order to compare the performance of different correction methods, including the conventional light speed correction, retrievals are done using the updated methodology, and those results are assessed using various reference datasets. Those are snow depth and freeboard from airborne observation, ice draft from mooring observation, and freeboard from satellite laser altimeter observation. In addition, the correction methods are combined with another independent retrieval method that estimates snow depth and sea ice thickness by combining satellite laser and radar altimeter measurements. Lastly, the consistency between the results from the two retrieval methods is examined for each radar freeboard correction method.
The effect of the 18.6-year lunar nodal cycle on steric sea level changes
Authors: Le Bars Dewi , Bult Sterre , Haigh Ivan , Gerkema Theo
Published: March 2024

We show that steric sea-level varies with a period of 18.6 years along the western European coast. We hypothesize that this variation originates from the modulation of semidiurnal tides by the lunar nodal cycle and associated changes in ocean mixing. Accounting for the steric sea level changes in the upper 400 m of the ocean solves the discrepancy between the nodal cycle in mean sea level observed by tide gauges and the theoretical equilibrium nodal tide. Namely, by combining the equilibrium tide with the nodal modulation of steric sea level, we close the gap with the observations. This result supports earlier findings that the observed phase and amplitude of the 18.6-year cycle do not always correspond to the equilibrium nodal tide. This finding allows to better filter natural variability when estimating the current rate of sea level rise along the European coast. Practical applications include the detection of an acceleration of sea level rise and the comparison between tide gauge and satellite observations with sea level projections.
Deformation of Western Anatolia under the effect of the Hellenic Trench and the North Anatolian Fault
Authors: Kaya-Eken Tülay , Hashima Akinori , Özener Haluk
Published: March 2024

The Anatolian Plate, surrounded by the Eurasian, African and Arabian plates, represents a great laboratory for geoscientists with its all complicated tectonic settings. The region is located at a widely spread active tectonic deformation zone that has primarily been controlled by the African plate subduction beneath the Hellenic Trench and the movement of the North Anatolian Fault Zone (NAFZ). The effect of crustal thinning due to the extensional regime gave rise to the formations of horst and graben systems leading to large earthquakes (e.g. The Mw7.0 2020 Samos earthquake) with normal faulting mechanisms in western Türkiye. A precise evaluation of tectonic deformation process and the potential seismic risk in this area requires a comprehensive understanding of the quantitative impact of both the Hellenic subduction and the NAFZ to the surface movement. To distinguish these individual contributions, we examine the published regional GPS data along Greece-Türkiye region. Considering a basic elastic-viscoelastic layered earth model, our first step is to estimate the contribution of the NAFZ to the GPS velocity at each station under various average slip rare conditions. We then perform an inversion on the residual velocities obtained by subtracting the calculated velocity from the observed data. This inversion allows us to derive the subduction rate along the Hellenic Trench. Our modelling indicates an optimal slip rate of
Unveiling Risks and Leveraging the Knowledge Base Platform for Cultural Heritage sites in the Context of the TRIQUETRA Project
Authors: Sarris Apostolos , Zanis Prodromos , Martino Salvatore , Anastasiou Anastasia , Ioannidis Charalabos , Verykokou Styliani , Klinkenberg Victor , Polidorou Miltiadis
Published: March 2024

The TRIQUETRA EU research project embarks on a pioneering initiative aimed at enhancing climate change (CC) resilience in Cultural Heritage (CH) sites. Within the scope of TRIQUETRA, certain provisions have been made for studying the geological and historical climatic data towards risk identification that the pilot CH sites of the project are facing.  The geological risk quantification was based on monitoring and modelling approaches to classify the intensity of geohazards related to ground instabilities, earthquake-induced effects, coastal retreat, sea-waves, water runoff, wind storms, wildfires etc. Digital twins derived by in-filed monitoring and surveying are assumed at the basis of geohazard quantification. Similarly, the assessment of historical climatic information has been based on observations and a multi-model ensemble of high-resolution Regional Climatic Model (RCM) simulations, aiming to identify potential risks at the selected CH sites. The datasets will be used for further experimentation, and continuous collection of new data will take place throughout the course of the project, serving towards the proposal of mitigation action against the CC-induced risks. Similarly, emphasis was given to gather information from past initiatives and directives to create a node of reference for the future, crucial for understanding the vulnerabilities of CH sites in the face of CC. An extensive literature review on CC and other risks and mitigation measures for CH sites worldwide has been made, in addition to gathering of existing and historical site-specific data, identification of geological conditions at CH sites and classification of geological hazards associated with environmental and climatological data that pose direct or indirect risks to the pilot CH sites.The development of the TRIQUETRA Knowledge Base platform (an electronic repository) based on the retrieved data, accompanied by advanced search tools and a “Self Service Portal” hosted on the project website (https://triquetra-project.eu/), ensures that contents related to CC, geological conditions, historical data, site-specific information, as well as risks and mitigation measures for CH sites are discoverable for future decision-making actions. The Knowledge Base platform includes a dedicated database and a WEBGIS platform, which store collected data in a common geospatial database providing a secure environment, which has an open access policy and will offer further analysis beyond the end of the project.The above lay the groundwork for holistic research to CC resilience in CH sites. The findings presented herein not only advance the objectives of the TRIQUETRA project but also offer insights that can guide future research in the preservation of global CH in the face of an ever-evolving climate.
Understanding local and large-scale changes in the Arctic and the effect on Cyclone activity
Authors: Parker Chelsea , Webster Melinda , Mooney Priscilla , Valkonen Elina , Boisvert Linette
Published: March 2024

The Arctic is warming four times faster than the rest of the globe, with a concurrent rapid loss of sea ice extent and thickness. Cyclones are synoptic weather events that transport heat and moisture into the Arctic, and have complex impacts on sea ice, marine ecosystems, and socio-economic activities. However, the effect of a changing climate on Arctic cyclone behavior remains poorly understood. This study uses a combination of reanalysis data, cyclone tracking techniques, and high-resolution numerical modeling to explore the effect of recent and future climate change on Arctic cyclone behavior across seasons.This work first examines the relative importance of changes in local surface conditions and turbulent fluxes and broader changes in pressure patterns, steering flow, and baroclinicity with recent climate change in governing cyclone frequency, intensity, and trajectories. Our analysis suggests that cyclone activity is shifting throughout the autumn with competing effects of turbulent fluxes and large-scale conditions. With recent climate change, sea ice is declining, and surface temperatures and turbulent fluxes are increasing, resulting in slight increases in Autumn cyclone intensity. In early autumn, cyclone frequency and trajectories are strongly governed by the large-scale flow despite increases in surface turbulent fluxes and baroclinicity. By late autumn, land-sea temperature contrast is increasing with sea ice loss, and changes in baroclinicity and large-scale flow work in concert to increase cyclone activity in the Arctic.This work then uses regional, high resolution, convection-permitting Weather Research and Forecasting (WRF) model simulations to demonstrate the sensitivity of cyclone characteristics to recent and future climate change. Simulations with downscaled CMIP6 global climate projections reveal that future sea ice loss and increasing surface temperatures by the year 2100 drive large increases in the near-surface vertical temperature gradient, sensible and latent heat fluxes into the atmosphere, and deep convection during spring cyclone events. The changes in the future (warmer) climate alter cyclone trajectories and increase and prolong intensity, with significantly increased wind speeds, temperatures, and precipitation. Such changes in cyclone lifecycles and characteristics may exacerbate sea ice loss and Arctic warming through positive feedback mechanisms. The increasing extreme nature of weather events such as Arctic cyclones has important implications for atmosphere-ice-ocean interactions in the new Arctic.
Spatio-temporal modelling of wheel load carrying capacity (WLCC) to mitigate soil degradation at regional scale
Authors: Kuhwald Michael , Kuhwald Katja , Duttmann Rainer
Published: March 2024

Soil compaction caused by intensive field traffic is one of the main threats to agricultural soils. Soil compaction occurs when the applied soil stress is higher than the soil strength. Both, soil strength and stress, are highly variable in space and time. While soil strength mainly depends on environmental conditions (e.g. weather, soil type, crop type), soil stress results from the used machinery. One key parameter for the applied soil stress is the wheel load which results from the machinery setup. The wheel load carrying capacity (WLCC) approach takes this into account and specifies the maximum wheel load until soil stress does not exceed the soil strength.The objective of this study is to model and analyse the dynamic variation of WLCC at regional scale for a 5-year period (2016-2020). We selected a study area (~2000 km²) with highly mechanized agriculture in Northern Germany where the main crops are cereals, maize and sugar beets. Sentinel-2 images were used to derive the crops for the 5-year period. We calculated the WLCC using an advanced version of the SaSCiA-model (Spatially explicit Soil Compaction risk Assessment) for each day of the 5 years.The results show a high temporal dynamic characteristic of the WLCC during the crop rotation at regional scale. The relatively dry years 2016 and 2018 increased the maximum allowable wheel load, especially during harvesting of maize and sugar beets in autumn. In all 5 years, spring was the time with the lowest WLCC. At this time, however, high soil stresses occur due to the application of slurry and digestates, which is associated with high soil compaction risk. The spatial variation of WLCC depends on the one hand on soil properties such as soil texture. On the other hand, the used crop has a high effect on the WLCC due to different soil water utilization.Based on the spatio-temporal analysis of WLCC at regional scale, an assessment can be performed to reduce the soil compaction risk either by increasing the soil strength or by decreasing the soil stress. We show exemplarily how the adjustment of tire inflation pressure affects the WLCC. Finally, this study may contribute to understand WLCC dynamics in crop rotations at regional scale and may help to mitigate further soil compaction.
Increasing root trait complementarity in species mixtures may be detrimental for soil carbon storage
Authors: Yin Shuang , Chen Xinli , Terrer César , Zhou Zhenghu , Chen Ji , Abalos Diego
Published: March 2024

Designing plant mixtures with potential to increase soil organic carbon (SOC) appears to be a powerful nature-based tool to restore some of the carbon lost in agroecosystems. However, we are uncertain about the best way to design such benign plant mixtures. Trait-based approaches are increasingly used to explain the relationship between plant diversity and ecosystem functions, offering a conceptual opportunity to address this knowledge gap. In this study, we combine a global meta-analysis of 407 paired SOC content observations with a root traits database from GRooT, to explore the optimum way for the design of plant mixtures to increase SOC. We found that specific root traits at the community level were important predictors of the response of SOC to plant mixtures. Species mixtures could increase SOC content when the overall plant community had low variation in root mycorrhizal colonization and root tissue density. The positive response of SOC content to species mixtures was linked to increases in soil microbial biomass carbon and root biomass. Additionally, the SOC enhancements by plant mixtures were often found in regions with high precipitation and low sand content. Our meta-analysis presents a framework based on plant traits to enhance SOC sequestration using plant mixtures, which will enable farmers to optimize plant mixtures towards soil carbon sequestration.
Minimum entropy constrained cooperative inversion with application to electrical resistivity, seismic and magnetic field and synthetic data
Authors: Ziegon Anton H. , Boxberg Marc S. , Wagner Florian M.
Published: March 2024

Interpreting independent geophysical data sets can be challenging due to ambiguity and non-uniqueness. To address this, joint inversion techniques have been developed to produce less ambiguous multi-physical subsurface images. Recently, a novel cooperative inversion approach that uses minimum entropy constraints has been proposed. The major feature of this approach is that it can produce sharper boundaries inside the model domain. We implemented this approach in an open-source software framework and systematically investigated its capabilities and applicability on electrical resistivity tomography (ERT), seismic refraction tomography (SRT), and magnetic data.First, we conducted a synthetic 2D ERT and SRT data study to demonstrate the approach and investigate the influence of the equations’ parameters that must be calibrated as well as to justify extensions of the method. The results show that the use of the joint minimum entropy (JME) stabilizer outclasses separate, conventional smoothness-constrained inversions and provides improved images.Next, we used the method to analyze 3D ERT and magnetic field data from Rockeskyller Kopf, Germany. Independent inversion of the magnetic field data already suggested a subsurface volcanic diatreme structure, but the joint inversion using JME not only confirmed the expected structure, but also provided improved details in the subsurface image. The multi-physical images of both methods are consistent in many regions of the model as they produce similar boundaries. Due to the sensitivity of the ERT measurements to hydrogeological conditions in the subsurface, some structures are only visible in the ERT data. These features seem not to be enforced on the magnetic susceptibility model, which highlights another advantage and the flexibility of the approach.However, the results of both the synthetic and field data use cases suggest that careful parameter tests are required prior to cooperative inversion to obtain a suitable hyperparameters and reference model. Our work implies that minimum entropy constrained cooperative inversion is a promising tool for geophysical imaging provided that proper settings are chosen while it also identifies some objectives for future research to improve the approach.
Implications of the rainfall spatial variability for the real-time modeling of runoff triggering stony debris flows
Authors: Boreggio Mauro , Barbini Matteo , Bernard Martino , Berti Matteo , Schiavo Massimiliano , Simoni Alessandro , Vesco Lopez Sandivel , Gregoretti Carlo
Published: March 2024

In a mountainous environment, high-intensity and short-duration precipitation can generate sudden and abundant runoff at the base of rocky cliffs. This runoff, upon impacting the debris deposits present there, can trigger debris-flow phenomena. In the province of Belluno, in the Boite River valley, a network of rain gauges has been set up to monitor precipitation in the Rovina di Cancia site, where 12 debris-flow events have occurred in the last 10 years. The rain gauges are strategically placed both upstream and downstream of the debris-flow initiation area. In most cases, the precipitation showed significant spatial variability in both planimetric and altimetric aspects. This variability is crucial when simulating the runoff that triggers stony debris flows. The simulation of the peak runoff that triggered the 12 occurred events using a single rain gauge presented a high scatter compared to the simulation performed with the spatially recorded rainfall, except when the chosen rain gauge was close to the rocky cliffs. Furthermore, modelling using radar estimates as rainfall input also displayed significant variability based on the rain gauge used to correct the radar data. Essentially, accurate real-time simulation of runoff triggering debris flows requires the presence of rain gauges upstream of the initiation area, particularly in close proximity to the rocky cliffs.
Orbital forcing over 3.5 billion years - Implications for cyclostratigraphy
Authors: Zeebe Richard , Lantink Margriet
Published: March 2024

Orbital (or Milankovic) forcing of the Earth system is key to understanding rhythmic climate change and its expression in stratigraphic sequences on time scales >10 kyr. Stratigraphic applications concerned with past orbital forcing rely on astronomical solutions, which represent the backbone of cyclostratigraphy and astrochronology. Here we present new deep-time astronomical solutions from state-of-the-art solar system integrations for orbital eccentricity, inclination, obliquity, and precession over the past 3.5 Gyr. We performed long-term ensemble integrations to explore the possible solution/phase space of the system. Our study provides multiple astronomical solutions and characteristic long-term features of Milankovic forcing. Importantly, we integrate the equations of motion for Earth's spin axis over 3.5 Gyr, yielding full solutions for Earth's obliquity and climatic precession. We found startling results regarding the primary astronomical cycle (405 kyr in the recent past) utilized in deep-time paleoclimate analyses and for constructing age models, aka the long eccentricity cycle. The widely accepted and long-held view is that the long eccentricity cycle was practically stable in the past and may hence be used as a "metronome" to reconstruct accurate chronologies. However, we found that the LONG ECCENTRICITY CYCLE CAN BECOME UNSTABLE over long time scales, rendering Earth's orbital eccentricity and climate-forcing spectrum unrecognizable compared to the recent past. Furthermore, our computations show that Earth's obliquity was lower and its amplitude (variation around the mean) significantly reduced in the past. We therefore predict weaker climate forcing at obliquity frequencies in deep time and a trend toward reduced obliquity power with age in stratigraphic records. Our findings have multiple, fundamental implications for cyclostratigraphy, astrochronology, and paleoclimatology, which will be discussed in this presentation.
Comparing extreme sub-daily rainfall projections from temperature-scaling and convection-permitting climate models across an Alpine gradient
Authors: Akbary Rashid , Marani Marco , Dallan Eleonora , Borga Marco
Published: March 2024

Understanding projected changes in sub-daily extreme rainfall in mountainous basins can help increase our capability to adapt to and mitigate against flash floods and debris flows. Here we compare the changes in extreme rainfall projections from apparent Clausius-Clapeyron (CC) temperature scaling against those obtained from convection-permitting climate model simulations. Temperature and precipitation projections are obtained from an ensemble of convection-permitting climate models (CPM), which are suitable to the task given their ability to explicitly represent deep convection and to resolve the mountainous topography. The CPM data provided by the CORDEX-FPS Convection project at 1-hour temporal and remapped to 3 km spatial resolution, cover historical and far-future (2090-2099) time periods under the extreme climate change scenario (RCP8.5). Due to the computational demands however, CPM simulations are still too short (typically 10-20 years) for analyzing extremes using conventional methods. We use a non-asymptotic statistical approach (the Metastatistical Extreme Value, MEVD, Marani and Ignaccolo, 2015) for the analysis of extremes from short time periods, such as the ones of CPM simulations. We use hourly precipitation and temperature data from 174 stations in an orographically complex area in northeastern Italy as a benchmark.Results from our analysis reveal that the apparent CC temperature scaling method demonstrates effective performance when applied to 1-hour extreme rainfall projections and for high return periods. However, its accuracy decreases as the precipitation duration increases, highlighting potential limitations in accurately predicting changes in longer-duration extreme rainfall. Variations in performance are also noted when considering different return periods, as we find CPM changes depending on them, contradicting traditional CC-scaling. Furthermore, we show that elevation is a key factor influencing temperature variations, with higher elevation locations experiencing more pronounced temperature increases with respect to lowland areas. This affects more the results for 1 hr extreme rainfall projections, whereas it is less relevant for 24-h duration. These findings identify some serious limitations of traditional CC scaling and emphasize the need for a nuanced understanding of the scaling method's applicability under various conditions.