bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing Restoration Strategies for Dynamic Population Changes of Plant-Pollinator Networks in a Warming Climate
Authors: Datta Adrija , Dubey Sarth , Bhatia Udit
Published: March 2024

Ensuring robust pollination service is vital for sustainable food production, as three-quarters of crops require insect pollinators to reproduce, but many insect populations are rapidly declining.  Yet, it is widely reported that insect pollinators face increased extinction risk due to habitat loss and warming climate. The biological impact of global mean temperature projections on individual terrestrial ectotherms is often predicted to increase with the rate of warming. However, it also depends on the interdependence of the plant-pollinator network and the physiological sensitivity of ectotherms to temperature change over time. Here, we have used sampled plant-pollinator network data from different climatic zones and the Earth system model projected temperature data of different future projection scenarios. In this study, we present a mathematical framework for modeling species population dynamics using the Lotka-Volterra model, where parameters are integrated from empirical fitness curves of terrestrial insects at different latitudes. This approach also investigates how species abundance evolves in the twenty-first century with and without species management, focusing on maintaining a constant abundance of generalist species to avert sudden ecosystem collapses over declining environmental health. The results show that tropical networks are more sensitive in abundance and extinction to future temperature increase as they live very close to their optimal temperature. In contrast, species of temperate regions have broader thermal tolerance, so the warming may increase their abundance. This study offers insights into how different future temperature projections influence species management, thereby restoring the functional integrity of the entire ecosystem. Also, this study provides region-specific restoration guidelines, offers insights for agro-advisory services, informs sustainable cropping patterns, and optimizes resource allocation. 
Development of framework for decision support integrated impact assessment platform and application technology for climate change adaptation
Authors: Park Songmi , Song Young-Il , Park Jinhan , Kim Ara , Lee Eunbi , Park Joohyun
Published: March 2024

Climate change is having simultaneous impacts on various sectors such as health, ecology, and agriculture, increasing the demand for assessment and technology development for each sector and their interactions. South Korea's climate change is progressing more rapidly than the global average, leading to an increasing trend in natural disasters such as heatwaves, cold snaps, floods, and droughts due to high climate variability. The damages caused by the four major disasters (heatwaves, cold snaps, floods, and droughts) are interconnected with the occurrence of vector-borne diseases, infectious diseases, and food supply issues, leading to an increased demand for integrated impact assessments on these interactions.The need for policy decision support in evaluating climate policies and developing robust plans for climate change response is increasing in South Korea. To address this, a research team is currently developing a climate change integrated assessment platform that takes into account both internal and external factors related to climate change. Specifically, they are in the process of developing an integrated assessment model based on interconnections between sectors to evaluate the impact and vulnerability of climate change. Furthermore, work is underway to develop climate change impact assessment models for health, water management, agriculture, forestry, behavior, and the marine and fisheries sectors. Additionally, they are considering the development of climate change impact assessment models for environmental policy coordination.AcknowledgementThis work was supported by Korea Environment Industry &Technology Institute(KEITI) through "Climate Change R&D Project for New Climate Regime." , funded by Korea Ministry of Environment(MOE) (2022003570007)
On the sensitivity and robustness of Austrian-wide water balance components & groundwater recharge: A regional-scale evaluation of objective functions in calibration 
Authors: Zeitfogel Hanna , Herrnegger Mathew , Schulz Karsten
Published: March 2024

Regional water resource management requires adaptation measures to cope with a changing environment and climate. Large- and regional-scale hydrological models can provide information on water cycle components and their future projections for designing these measures. Here, the plausible and consistent spatial distribution of the simulated water balance components is essential, not only when communicating the results to the relevant stakeholders.Spatially consistent simulation results depend on the spatially distributed parameters estimated for the hydrological model. This task, however, remains a challenging step in the model set-up, especially for larger modeling domains with varying hydrometeorological conditions like Austria, ranging from high alpine areas with high rainfall sums, snow, and glaciers to low-lying areas, with semi-arid conditions exhibiting negative climatic water balances.The main objective of this study is to analyze the impact of different objective functions (OFs) on the simulated water balance components of a regional hydrological model. The distributed rainfall-runoff model COSERO is set up for the area of Austria (89 000 km²) with a monthly temporal resolution and a target spatial resolution of 1 x 1 km². Initially estimated spatially distributed model parameters are optimized using different OFs, e.g., Nash-Sutcliffe efficiency (NSE), log-transformed NSE, Kling-Gupta efficiency (KGE), and combinations thereof.The resulting simulations are analyzed based on the spatial distribution of simulated runoff, evapotranspiration, and groundwater recharge across the study area. Furthermore, time-series analysis of the water cycle components is performed, and selected statistical characteristics are derived.
Using large microseismicity catalogs to constrain subduction zone processes – examples from the Chilean margin
Authors: Sippl Christian
Published: March 2024

The use of machine-learning based tools for phase picking and association is in the process of revolutionizing the field of seismicity analysis, leading to the simplified creation of “deep” seismicity catalogs often containing 10s or 100s of thousands of events. Having such catalogs as an available resource opens the field for novel ways of combining seismicity information with other types of datasets. At the same time, the sheer amount of data poses challenges for the visualization as well as joint analysis with other constraints.In this contribution, I want to explore different ways of using and visualizing large seismicity catalogs, using a range of different recently compiled earthquake catalogs from the Chilean margin as showcase examples. Moreover, I attempt to find efficient ways of cross-plotting seismicity data from “deep” catalogs with other datasets such as interplate coupling maps, seismic velocity distributions, temperature models or inferred mineralogy maps.
Decay of seismic noise at shallow boreholes: Observations from Groningen.
Authors: Kalinichenko Oleh , Eisner Leo , Stanek Frantisek , Waheed Umair , Hanafy Sherif , Jechumtalova Zuzana
Published: March 2024

Long-term seismic monitoring arrays are often deployed to shallow boreholes to reduce the seismic noise. We investigate noise level decay in shallow boreholes. A large number of publicly available data with such deployment is available at the seismic monitoring array near the town of Groningen, which allows also characterization of the seismic noise decay in shallow boreholes in urban environments. We study noise distribution at 4 sites from this array. Each site includes 5 receivers deployed in shallow vertical boreholes with 50 meters intervals between the surface and 200 m depth. We show there is no difference between noise levels during the summer and winter at the borehole instruments. However, we observe diurnal variation at all depth levels. We also show there are higher noise levels throughout weekdays and lower during weekends and state holidays. These changes are not only observed at the surface but also at the deepest receivers. This implies that the dominant source of this noise is anthropogenic and it penetrates to depths of 200 meters even at frequencies exceeding 5 Hz. This observation is contradicting the common assumption that the seismic noise consists of the surface waves.
Towards the construction of regional marine radiocarbon calibration curves: an unsupervised machine learning approach
Authors: Mârza Ana-Cristina , Menviel Laurie , Skinner Luke
Published: March 2024

Radiocarbon may serve as a powerful dating tool in palaeoceanography, but its accuracy is severely limited by the need to calibrate radiocarbon dates to calendar ages. A key problem is that marine radiocarbon dates must be corrected for past offsets from either the contemporary atmosphere (i.e. ‘reservoir age’ offsets) or a modelled estimate of the global average surface ocean (i.e. delta-R offsets). This presents a challenge because the spatial distribution of reservoir ages and delta-R offsets can vary significantly, particularly over periods of major marine hydrographic and/or carbon cycle change such as the last deglaciation. Modern reservoir age/delta-R estimates therefore have limited applicability.  The construction of regional marine calibration curves could provide a solution to this challenge, if coherent regions could be defined. Here, we use unsupervised machine learning techniques to define distinct regions of the surface ocean that exhibit coherent behaviour in terms of their radiocarbon age offsets from the contemporary atmosphere (R-ages). We investigate the performance of different clustering algorithms applied to outputs from different numerical models. Comparisons between the cluster assignments across model runs confirm some robust regional patterns that likely arise from constraints imposed by large-scale ocean and atmospheric physics. At the coarsest scale, regions of coherent R-age variability are associated with the major ocean basins. By further dividing basin-scale shape-based clusters into amplitude-based subclusters, we recover regional associations that cohere with known modern oceanographic processes, such as increased high latitude R-ages, or the propagation of R-age anomalies from the Southern Ocean to the Eastern Equatorial Pacific. We show that the medoids for these regional sub-clusters provide significantly better approximations of simulated local R-age variability than constant offsets from the global surface average. The proposed clusters are also found to be broadly consistent with existing reservoir age reconstructions that span the last ~30 ka. We therefore propose that machine learning provides a promising approach to the problem of defining regions for which marine radiocarbon calibration curves may eventually be generated.
Combined application of single grain and cobble luminescence dating to Alpine glaciofluvial deposits
Authors: Serra Elena , Mueller Daniela , Gegg Lukas , Preusser Frank
Published: March 2024

Dating glaciofluvial deposits is fundamental to reconstruct paleoglacial and paleoclimatic dynamics. However, partial bleaching and lack of suitable sediments make the application of luminescence dating to such deposits challenging. Single grain and cobble luminescence dating have been successfully used to tackle these problematics [e.g. 1, 2] and are combined in this study on glaciofluvial deposits from the northern Alpine foreland (Finsterhennen, Switzerland).Previous chronological investigations at the study site [3, 4, 5] suggest that the deposition of the glaciofluvial gravel lying directly underneath the till from the regional Last Glacial Maximum (LGM) occurred ca. 29 kyr ago, in response to the LGM glacial advance. By comparison with the existing age constraints, the present study aims (1) to test the combined application of single grain and cobble luminescence dating to Alpine glaciofluvial deposits and (2) to refine the two methodologies.Samples were collected from well sorted sand lenses and moderately sorted gravel at approximately the same depth within the pre-LGM glaciofluvial gravel. Single grain (SG) feldspar luminescence measurements were conducted on sand lens and gravel sandy matrix samples, while luminescence depth profiles were measured in individual crystalline cobbles. Preliminary results show good agreement between SG ages from the sand lens and previous chronological constraints. SG results from the sandy matrix of the gravel horizon are instead underestimated, potentially because of challenges in dosimetry estimation, due to the heterogeneous lithology and grain size of the gravel layer. Heterogeneous dosimetry appears less problematic for burial age estimation of cobbles, since the variation of dose rate with depth into the cobble is dominated by the dosimetry of the cobble itself. Preliminary cobble luminescence depth profiles show shallow bleaching fronts, with large variability between cores and surfaces of the same cobble. The limited luminescence signal resetting can be explained by the proximity of the glaciofluvial deposits to the advancing LGM ice front and by sediment transportation in turbid water. The intra cobble variability is instead potentially related to the cobbles’ heterogeneous lithology, implying differences in dosimetry and light attenuation within the clasts.References[1] Duller, 2006, Quaternary Geochronology 1.[2] Jenkins et al., 2018, Quaternary Science Review 192.[3] Schlüchter, 2004, Quaternary Sciences 2.[4] Preusser et al., 2007, Boreas 36.[5] Pfander et al., 2022, Swiss Journal of Geosciences 115.
Structural controllability and management of cascading regime shifts
Authors: Rocha Juan , Crépin Anne-Sophie
Published: March 2024

Abrupt transitions in ecosystems can be interconnected, raising challenges for science and management in identifying sufficient interventions to prevent them or recover from undesirable shifts. Here we use principles of network controllability to explore how difficult it is to manage coupled regime shifts. We find that coupled regime shifts are easier to manage when they share drivers, but can become harder to manage if new feedbacks are formed when coupled. Simulation experiments showed that both network structure and coupling strength matter in our ability to manage interconnected systems. This theoretical insights calls for an empirical assessment of cascading regime shifts in ecosystems and warns about our limited ability to control cascading effects.
Faster P cycling upon permafrost collapse
Authors: Li Ziliang , Yang Yuanhe
Published: March 2024

Permafrost collapse is expected to accelerate carbon (C) release and induce a positive C-climate feedback. As the frequently limiting key element in permafrost ecosystems, phosphorus (P) could mediate ecosystem C balance by modulating microbial decomposition and primary production. However, little is known about the changes in P cycling upon permafrost collapse. By combining sequential extraction, 31P NMR spectroscopy and metagenomic sequencing, we explored whether and how different soil P pools and microbial P transformation genes responded to permafrost thaw based on six thermokarst (abrupt collapse of ice-rich permafrost)-influenced sites on the Tibetan Plateau. We observed a significant decrease in soil labile P, NaOH-Po and residual P after permafrost collapse. The negative relationship between aboveground biomass P content and the soil labile P as well as NaOH-Po indicated that the reduction in these P pools were associated with the plant P uptake. Moreover, the increased relative abundance of the genes involved in inorganic P-solubilization and organic P-mineralization upon permafrost collapse reflected the potential increase in microbial P mobilization. These findings highlight a faster P cycling through plant P uptake and microbial P mobilization after permafrost collapse, which could impact the ecosystem C cycle and its feedback to climate warming. 
Fluvial aggradation and incision processes in eastern Tibetan plateau and their relationship to glacial activities
Authors: Shen Qinjing , Kang Huan , Tao Yaling , Zhang Huiping
Published: March 2024

Since the establishment of the classic Theory of Alpine Glacial Cycles, a close relationship between glacial activities and fluvial terrace development has been observed. However, problems such as the extent and mechanisms through which glacier advances influence downstream fluvial aggradation, are not fully understood. The Aba Basin, located on the eastern Tibetan Plateau, features well-developed river terraces. In conjunction with this, the upstream Nianbaoyeze Mountains have undergone intense glacial activities during glacial periods. The integration of these features make this source-to-sink system an ideal site to study these problems. In this work, we utilized Luminescence and Radiocarbon dating methods to reconstruct terrace sequences in the Aba Basin. Furthermore, geochemical analyses were undertaken to delineate trends in provenance variation during terrace aggradation periods, and subsequently to assess the impact of sediment supply from the Nianbaoyeze Mountains. Integrating our analysis of fluvial evolution in the Aba Basin with glacier activities from the Nianbaoyeze region and correlating them with regional and global paleoclimate data, we present detailed insights into how glacial activities have driven terrace formation in the Tibetan Plateau since the late Pleistocene. Our research offers new perspectives on the fluvial processes in periglacial regions, enhancing the understanding of the interplays between fluvial landform dynamics and glacial-interglacial cycles.
Re-experimentally constrained aluminum, lithium and phosphorus partitioning between zircon and melt: implication for early Earth’s crust evolution and possible habitability
Authors: Shang Sheng , Lin Yanhao
Published: March 2024

The aluminum (Al), lithium (Li) and phosphorus (P) in zircon, combining their partitioning coefficients between zircon and silicate melt, may show important insights into the evolution of Earth’s crust and habitability over geological timescales, but their partitioning coefficients have not been experimentally studied in detail. In this study, we conducted high-temperature experiments to constrain the partition coefficients of Al (DAl), Li (DLi) and P (DP) between zircon and silicate melt. Our experiments firstly show the amounts of P has the identifiable effects on DAl and DLi, but not on itself. The positive and negative correlations of DAl and DLi as P content in zircon increasing enables us to constrain the aluminum saturation index (ASI) and Li content of the parental melt of zircon, respectively, by comparing their contents in zircon. The re-evaluated ASI values over time yields two significant increases at 3.6 Ga and 1.0 Ga, whereas, the calculated Li content of Earth’s crust non-linearly decrease with time. Meanwhile, the P content of early Earth’s crust is constrained to 1779 ppm before 3.0 Ga, similar to the present-day crust level of 2052 ppm. These indicate that the global scale tectonic events occurred on the Earth around 3.6 Ga and 1.0 Ga, and that the early Earth could have had a life habitability, and it did not get receded during the terrestrial crust evolution.
Cloud climatologies from reanalysis datasets – an intercomparison
Authors: Lauer Axel , Bock Lisa , Hassler Birgit
Published: March 2024

Through their significant impact on the short- and longwave radiation and their pivotal role in the hydrological cycle, clouds and their response to climate change are a key component in present-day and future climate. As part of the SPARC Reanalysis Intercomparison Project (S-RIP) phase 2, we analyze cloud climatologies from twelve reanalysis datasets including, for instance, ERA5, MERRA2 and JRA-55. The study focuses on parameters that are available from most reanalysis datasets such as cloud fraction, cloud liquid and ice water content as well as cloud radiative effects on monthly to multi-year time scales. Geographical distributions, variability and statistical properties of the cloud parameters from the reanalyses for specific cloud regimes and regions are compared and put into context with satellite observations. First results show that more recent reanalysis products are in closer agreement with the satellite data and that in contrast to multi-model means of models participating in the Coupled Model Intercomparison Project (CMIP), multi-reanalysis means do not outperform individual reanalyses. For a consistent processing of all reanalysis and satellite datasets, the Earth System Model Evaluation Tool (ESMValTool) is applied. ESMValTool is a community developed open-source software tool that provides common operations such regridding data onto the same grid, masking of missing values, area extraction, and basic statistics such as seasonal means, annual means, area means, etc. which facilitates analysis and a fair intercomparison of the datasets. For comparison with satellite data, multiple products for each parameter are used to estimate observational uncertainties.
Compound flood forecasting and climate adaptation Destination Earth digital twin
Authors: Yan Kun , Weerts Albrecht , Bovenschen Tycho , Cunningham Andrew , Muis Sanne , Roelvink Floortje , Sperna Weiland Frederiek , Zijlker Tammo
Published: March 2024

Coastal deltas are extremely susceptible to flooding from sea, rivers, heavy rain and even more severe combinations thereof. Many coastal deltas are densely populated, and flood risk forms a serious threat that will likely increase in the future. There are two main mechanisms to reduce the devastating impacts of these floods; (1) adaptation to the increasing climate risks and (2) improved early warning and emergency response. We will present the Destination Earth digital twin on coastal compound flood inundation forecasting and climate adaptation that provide information  to support reducing of impacts.Examples for 5 use cases are presented showing flood inundation and flood impact maps resulting from compound combinations of surge, waves, heavy rain and riverine flooding. The results are based on an automated complex but generic workflow that takes the high resolution meteorological forcing from Extremes DT or Climate DT as input to the high resolution hydrological model (Wflow_sbm), the hydrodynamic model (Delft3D-FM) and the wave models (hurrywave and snap wave). Those models provide the boundary condition of the 2D flood inundation model SFINCS. Based on the calculated flood maps, impacts (in flood damage and people affected) are being calculated with Delft-FIAT. Results of the modelling chain and model validation will be to end user. The insights we obtained from our end users will provide valuable inputs for design of the compound flood digital twin.
Impact of Swimmer Dynamics on Odor Transport by Mesoscale Swimmers in Turbulent Environments
Authors: James Martin , Viola Francesco , Seminara Agnese
Published: March 2024

Odor transport in fluidic environments is a subject of great importance, holding implications for numerous scientific disciplines, including fluid dynamics, biological studies, and engineering disciplines. Odor tracking serves as the foundation for various natural processes, such as the navigation of marine organisms and the foraging behavior of insects. Turbulent fluctuations add another level of complexity to the problem of odor transport in fluidic environments. The odor emitted by swimmers is not only influenced by the environment but also by hydrodynamic fluctuations caused by their dynamics. This effect is evident in large swimmers, where the wakes caused by their swimming dynamics could potentially alter odor distribution. However, it is much less clear whether and how hydrodynamic interactions affect the odor distribution of mesoscale swimmers. In this work, we explore the coupling of chemical and mechanical signals from mesoscale swimmers (Reynolds number
Characterizing the 2022 South Atlantic fireball using infrasound recordings of the International Monitoring System
Authors: Hupe Patrick , Vergoz Julien , Pilger Christoph , Le Pichon Alexis
Published: March 2024

On 7 February 2022, around 20:00 UTC, a large meteoroid entered the Earth’s atmosphere around 500 km off the coast of Namibia and South Africa. NASA’s Center for Near Earth Object Studies (CNEOS) lists the event as a fireball with an impact energy of 7 kt of TNT equivalent. This energy estimate is about 60 times lower than for the 2013 Chelyabinsk fireball (440 kt, CNEOS), which was broadly covered in the media. Infrasound measurements can be an independent information source for fireball events. Their infrasonic signatures originate from either the hypersonic trajectory, which emits ablational waves, or the explosive fragmentation, which emits a ballistic shock wave. Relations such as ReVelle’s law can even be used for energy release estimates based on infrasound detection parameters such as the dominant period of the signal. The analysis of infrasound data from the International Monitoring System (IMS) for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) revealed that the Chelyabinsk fireball was the strongest event ever recorded by the IMS infrasound network at that time, when 20 out of 42 existing stations detected it. The second-strongest event of this type in the IMS era was the Bering Sea bolide that occurred on 18 December 2018 (49 kt, CNEOS), with a comparable portion of infrasound stations detecting it (25 out of 51, according to Pilger et al. 2019, doi: 10.3390/atmos11010083).For the 2022 South Atlantic fireball, we have found signatures at 20 infrasound stations of the IMS, too, out of 53 stations certified nowadays. We further characterize the event using the infrasound observations, model the infrasound propagation between the elevated source and the arrays, and assess the detection capability to explain the large number of detecting stations. We also use the IMS data for estimating an energy release, and revisit previous strong events such as Chelyabinsk using state-of-the-art array processing methods and enhanced configurations. These comprise the Multi-Channel Maximum-Likelihood (MCML) method or the one-third-octave band configuration within the Progressive Multi-Channel Correlation (PMCC) method, respectively.
An Open Platform for Validating Ambient Solar Wind Models
Authors: Perri Barbara , Reiss Martin , Muglach Karin , Samara Evangelia , Mullinix Richard , Wiegand Chiu ,   ISWAT Ambient Solar Wind Validation Team
Published: March 2024

To drive innovation in space weather research and prediction, we need to seek out promising strategies for unifying the validation of our modeling assets. Here we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. Our team's mission is to create an open online platform for validating ambient solar wind models at NASA's Community Coordinated Modeling Center. This open platform will allow the community to easily assess the accuracy of state-of-the-art solar wind model solutions in terms of unified metrics, and will thereby provide an unbiased assessment of progress over time. In this presentation, we will introduce the online platform, highlight our progress in developing unified metrics for both historical and near real-time validation, and discuss the current status and future perspectives of this community effort.
Micro- and mesoplastic pollution along the beaches in the open Baltic Sea and Gulf of Riga
Authors: Retike Inga , Dimante-Deimantovica Inta , Bebrite Alise , Skudra Māris , Viška Maija , Bikše Jānis , Barone Marta , Prokopovica Anda , Svipsta Sanda , Aigars Juris
Published: March 2024

We present a comprehensive assessment of micro- and mesoplastic pollution along 24 beaches of the Latvian coastline (Northern Europe, Baltic states) establishing a baseline for pollution distribution in the Baltic Sea Region. A detailed analysis of sand granulometry, hydrodynamic variables (waves and currents) and tourism intensity allowed us to understand better factors that drive plastic pollution distribution along beaches. Over 250 volunteers participated in the sample collection highlighting the importance of citizen science as a tool to support data collection.Our findings reveal a lower concentration of micro- and mesoplastic particles in the semi-closed Gulf of Riga (0.10 particles/kg dry sand) compared to the open Baltic Sea (0.16 particles/kg dry sand). The microplastic size fraction (1-5 mm) showed a distinct cluster with higher concentrations and fiber abundance in coarser beach sands of the open Baltic Sea and eastern Gulf of Riga. We emphasize hydrodynamics as a key factor in the distribution and accumulation of microplastics, while impacts are predominantly of local scale and vary considerably across existing studies. No clear pattern of recreational activities on plastic distribution was identified. Studies elaborating on aspects like sampling season, wave energy, wind, currents, sand granulometric properties, and pollution sources are encouraged to enhance result interpretation and move towards more comparable micro-litter case studies.Reference:Dimante-Deimantovica I, Bebrite A, Skudra M, Retike I, Viška M, Bikše J, Barone M, Prokopovica A, Svipsta S and Aigars J (2023) The baseline for micro- and mesoplastic pollution in open Baltic Sea and Gulf of Riga beach. Front. Mar. Sci. https://www.frontiersin.org/articles/10.3389/fmars.2023.1251068/fullThis work was supported by voluntary donations from the student sorority Selga, the European Regional Development Fund post-doctoral projects No.1.1.1.2/VIAA/2/18/359 and No.1.1.1.2/VIAA/4/20/733, ESF Project No. 8.2.2.0/20/I/003 “Strengthening of Professional Competence of Daugavpils University Academic Personnel of Strategic Specialization Branches 3rd Call”, and the European Economic Area (EEA) Financial Mechanism 2014–2021 Baltic Research Programme (grant EMP480).
Advances in Avalanche Monitoring in Norway: Insights from Distributed Acoustic Sensing
Authors: Turquet Antoine , Wuestefeld Andreas , Nyhammer Finn Kåre , Nilsen Espen , Refsum Vetle
Published: March 2024

Snow avalanches pose significant risks in mountainous regions. Traditional detection methods often lack the precision and timely responsiveness crucial for effective risk management. This study introduces an innovative approach using Distributed Acoustic Sensing (DAS) to detect snow avalanches in Norway. The monitoring site is located along a road in Holmbuktura in northern Norway, close to Tromsø. The cable path is composed of two segments: In segment one (0 – 850 m) an existing telecommunication cable is used, while for segment two (850 - 1450 m) a new cable was installed. The pilot road was frequently impacted by avalanches. Over three winters, the system captured both avalanche occurrences and anthropogenic noises (e.g., vehicles, wind, sea waves, etc.). 
The area is monitored with an OptoDAS interrogator with a sampling frequency of 500Hz and 10m gauge length. A 5m channel spacing results in 270 virtual channels along the monitored road stretch. Our automatic detection process distinguishes is based on classical signal processing techniques. We can confidently detect avalanches that hit road level, and additionally determine snow deposit on the road. Furthermore vehicles are detected with exact location and speed, which is used to alert emergency units in case of trapped vehicles. In this project, the focus of the installation is to detect avalanches that hit the road and determine whether any vehicles were trapped under the avalanches. For the winter season of 2022-2023 eight avalanches hit the road. The DAS-based monitoring system managed to successfully detect and classify these avalanches.
Compared to conventional methods like radar, infrared, and camera-based systems DAS offers distinct advantages in avalanche monitoring. DAS excels in providing real-time, continuous monitoring with high sensitivity and precision over extensive areas, unaffected by visual obstructions and less impacted by adverse weather conditions. Its robustness and low maintenance needs stand out, particularly when compared to radar systems' high installation costs and limited area coverage, camera's susceptibility to weather/light conditions.
The application of DAS technology offers a promising avenue for real-time, accurate avalanche detection, potentially enhancing safety measures in high-risk areas. Furthermore, this concept, when fully operational, could detect the risk of collision between avalanches and vehicles and alert authorities in real-time, which would be crucial for time-sensitive rescue operations.
Into the Deep - Marine Image Analysis Hub for Citizen Scientists
Authors: Johansen Caroline
Published: March 2024

Into the Deep is a Citizen Science Project that brings remote marine ecosystems directly to your laptop and allows adult learners to take part in real time research by annotating images of marine ecosystems. For this pilot, there are 4 data sets from different marine environments, and an intuitive image annotation tool called BiiGLE PARTY. In this session we will present how Citizen Scientists (CS) are being strategically recruited in two ways: through social media and through pre-existing partner networks. All participants are introduced to four ecosystems and each CS must first elect to follow a short course that was developed in close collaboration with the scientists and adult education experts. This dynamic, online course explains the importance of each ecosystem, detailing human impact on a habitat and gives them the information to answer a specific scientific question. The course is Non-Formal Education, achieving specific learning goals, but not formally evaluated. We will present key data aligning educational input and CS projects, showing how learning helps both maintain and actively engage adult learners in climate-positive action. Following the notion that when people are more educated about the topic (in this case marine ecosystems), it fosters a more positive attitude towards the ocean, and promotes greater compliance with measures put in place to protect it. After completing the short course, participants automatically enter the BiiGLE PARTY CS tool and can annotate images from the relevant habitation dataset with gamified prompts and point systems to keep them engaged. Statistical parameters and check points are incorporated into the program to exclude annotation outliers and cross-check for accuracy. The results of these annotations feedback to the scientific owner of the dataset and into ongoing research. We present some of the ways results provide valuable help to scientists, including training machine learning for automatic image detection. The main goal of Into the Deep is to provide an easy-to-use tool for both researchers and adult learners, and to facilitate the dialogue and continued commitment between CS and the researchers they assist. To this end, we will present an E-book and framework outlining how scientists can easily incorporate this tool for their own research purposes and information about how to reach interested CS.
Influence of Drag Coefficient for Tropical Cyclone Intensification by Numerical Simulations. 
Authors: Yoshioka Hiroaki , Fudeyasu Hironori , Yoshida Ryuji , Ito Junshi , Horinouchi Takeshi , Ito Kosuke
Published: March 2024

A project ”Moonshot Goal 8” was established to study the possible weakening of typhoon intensity due to artificial interventions supported by Japan Science and Technology Agency. One of our measures is to increase the sea surface drag near typhoons by using obstacles such as large ships.The maximum potential intensity theory suggests that the equilibrium intensity decreases as the surface drag coefficient increases.Still, few numerical studies tested it for real tropical cyclones (TCs). Some studies used fine-resolution simulations (e.g., with a sub-kilometer grid) to agree with the theoretical indication, but the number of cases is limited by calculation resources. Also, no studies have been conducted to elucidate the effect of surface drag coefficient change in a limited oceanic region.Therefore, we aim to conduct a comprehensive study on how TC would react to surface drag change over limited regions that can be set in various ways. Now, we focused on the intensification of Typhoon Faxai in 2019 and conducted sensitivity experiments by changing the drag coefficient (CD) over the circle area around it. In this study, we ran the Scalable Computing for Advanced Library and Environment (SCALE) at a coarse horizontal resolution of 5 km. The resultant central pressure and maximum 10m wind speed were sensitive to CD, especially for the value. These were reduced almost linearly and weakened by about 60% of the control run (CTL) when CD was set to 3.0 times that in CTL. Additionally, the results of the sensitivity to a radius of changing CD area showed that maximum wind speed during the mature stage has remained unchanged when over 100 km radius area changed.We will conduct further studies until the meeting.
A new multiscale and multisensory strategy for the characterization of groundwater discharge in coastal areas – the SUBGEO project
Authors: Romano Gerardo , Capozzoli Luigi , Lapenna Vincenzo , Polemio Maurizio
Published: March 2024

The monitoring of groundwater resources and the identification of energy resources play a crucial role in the sustainable development and management of coastal areas. This is a fundamental aspect considering the climate changes occurring in areas particularly exposed to physical hazards resulting from extreme weather events and higher are the risks of coastal erosion, groundwater salinization, flooding and other hazards in low-elevation coastal zones (Oppenheimer et al., 2019).  Currently, 2.15 billion people live in the near-coastal zone and 898 million in the low-elevation coastal zone globally (Reiman and al, 2023). Moreover, coastal freshwater reservoirs can represent a fundamental resource to address water shortages. The hydro-geological potential and economic factors linked to the submarine groundwater are the starting point of the two-year Italian Research Project of National Relevance (PRIN-2022) SUBGEO where the University of Bari (UNIBA) and the two Institutes (IMAA and IRPI) of the National Research Council are involved. The project is focused on the submarine groundwater discharge analysis with an innovative and integrated geophysical approach based on the use of electric and electromagnetic methods for the twofold targets of coastal underground freshwater reservoir non-invasive characterization and to gain useful tools for the optimal and sustainable management of the coastal areas and resources.Subgeo will develop an innovative geophysical approach to provide spatially continuous and high-resolution information on the subsoil structure from the offshore areas, where the outward fluxes mix with the seawater, to the onshore ones including the urban areas.The proposed strategy will be tuned by small-scale laboratory experiments and by numerical simulations to define the best acquisition procedures and check the sensitivity of the strategy for different subsurface conditions. The final goal of the project consists of reproducing a high-resolution and detailed hydrogeophysical model for managing the water resources in coastal areas. ReferencesOppenheimer M., Hinkel J. et al.: Sea Level Rise and Implications for Low Lying Islands, Coasts and Communities Supplementary Material, http://hdl.handle.net/11554/9280, 2019.Reimann L, Vafeidis AT, Honsel LE. Population development as a driver of coastal risk: Current trends and future pathways. Cambridge Prisms: Coastal Futures. doi:10.1017/cft.2023.3, 2023;1:e14.
Hybrid plasma simulation around Mercury: ion counting statistics
Authors: Teubenbacher Daniel , Exner Willi , Narita Yasuhito , Varsani Ali , Laky Gunter
Published: March 2024

Understanding Mercury's magnetosphere is a primary goal of the BepiColombo mission. In addition to spacecraft observations, numerical modeling efforts have shown to add invaluable insight to the Hermean magnetic field topology, current systems and plasma distributions. However, existing comparisons between observed and modeled data are predominantly qualitative, lacking quantitative agreement due to diverse mathematical approaches. Notably, quantitative inconsistencies of observed and modeled ion densities and energies are particularly affected. Hence, this study addresses systematic and stochastic deviations, focusing on establishing confidence intervals for "ion counting" within the hybrid AIKEF (Adaptive Ion Kinetic Electron Fluid) model. The kinetic treatment of the ions enables to directly compare model results with observations of the Planetary Ion Camera (PICAM), which is a part of the SERENA suite onboard the BepiColombo mission. Multiple ion counting methods are introduced and evaluated, including a simple sphere method, an omnidirectional method, and a field-of-view method. Our findings demonstrate that applying the field-of-view method to the modeled data, within the derived confidence interval, yields ion velocity distributions consistent with PICAM observations of Mercury’s magnetosheath. The AIKEF model and the developed analysis tools serve as a powerful and convenient method of reproducing the ion and electro-magnetic field profile around Mercury for the BepiColombo mission, both in flyby and in-orbit measurements.
Soil organic carbon dynamics after land-use change – combining process-based modelling with machine learning
Authors: Seitz Daria , Dechow Rene , Emde David , Schneider Florian , Don Axel
Published: March 2024

Land-use changes affect soil organic carbon (SOC) stocks over decades. However, IPCC default for greenhouse gas emissions reporting suggests a simple linear SOC stock change over 20 years only. Using process-based modelling approaches such as RothC to describe SOC dynamics after land-use change requires model validation. However, there are only few long-term field experiments where SOC stocks have been observed long enough to get sufficient data for such a model validation. This lack of data makes validating models for large-scale use challenging.Based on empirical data from over 3000 sites from the German Agricultural Soil Inventory we selected 204 sites with land-use change history within the last 60 years and created an artificial data-set using a reciprocal modeling approach. This approach utilizes machine learning models trained on sites under permanent land use to predict SOC stocks for similar sites where the land use had been changed. In addition, we extracted further empirical data from over 30 sites with land-use change in the temperate zone from a comprehensive meta-analysis.These two datasets were used to test the ability of the well-known SOC model RothC to simulate land-use change effects on SOC stocks. In these tests, we use the observed or predicted SOC stocks assumed at equilibrium to model the carbon input under permanent land use and corresponding SOC dynamics after land-use change. These modelled SOC dynamics are then compared with observed SOC stocks after land-use change.We will discuss opportunities and challenges of using process-based models to describe SOC dynamics after land-use change on regional to national scale. 
How to select the right parametric model for daily precipitation ? Impact of distribution tails on goodness-of-fit test
Authors: Ear Philippe , Di Bernardino Elena , Laloë Thomas , Troin Magali , Lambert Adrien
Published: March 2024

Modeling the distribution of precipitation data is required in many applications regarding water resource management and planning, such as flood and drought events. A critical step in statistical modeling is to find probability distributions that correctly describe the occurrences and intensities of precipitation. The statistical modeling of daily precipitation via parametric distribution is often done using the Gamma, Pearson Type 3, and Weibull distributions. However, these statistical models used for precipitation have many drawbacks. As these models are either light or heavy-tailed, they are not suited for applications in large areas with varying tail characteristics. Over the last few years, multiple models of probability distributions of precipitation in compliance with extreme value theory on both ends of the spectrum have been developed, such as the Extended Generalized Pareto Distributions (EGPD). In particular, the EGPD family allows for an adaptable distribution that can model both low and extreme precipitations while dealing with the flexibility of modeling light and heavy tails. When it comes to testing the goodness-of-fit of parametric distributions, the Kolmogorov-Smirnov test is often referred to. However, this test fails to detect divergence in the tails of distributions, making it unfit for discriminating between distributions that must be well fitted to extreme precipitation events. A fast and efficient test called the exact Berk-Jones statistical test (also referred to as the Calibrated Kolmogorov-Smirnov test) is investigated. This test allows for theoretically better power for diverging extreme tails. In this study, the exact Berk-Jones statistical test is compared to the classical Kolmogorov-Smirnov test on multiple parametric distributions, including the EGPD, on a 38-year high-resolution grid dataset of daily precipitation over France.
Reduced ENSO Variability During the Onset of 4.2ka Event
Authors: Dang Shaohua , Yu Kefu , Liu Zhongfang
Published: March 2024

It is widely believed that anomalies in the state of tropical Sea Surface Temperature (SST), manifested as intensified ENSO variability, triggered the collapse of the Northern Hemisphere monsoon that occurred from 4500 to 3900a BP, known as the 4.2ka event. However, explicit records of ENSO variability, including events and variance, during the onset of 4.2ka event were still lacking to show how it changed and related to this climatic event. Here, we present a century-length (104-year) monthly coral record from the South China Sea (SCS) combined with modeling data to show that reduced ENSO variability was associated with an intensified Pacific Walker circulation ranging from 4400 to 4300 years BP, precisely corresponding to the onset of 4.2ka event. We hypothesize that such a mean state of tropical Pacific climate might not have triggered the development of the 4.2ka event, but rather responded to it.