bluuebunny/crossref_metadata_2025 huggingface dataset:
Fragmentation of atmospheric ice particles due to collision
Authors: Yadav Sudha , Grzegorczyk Pierre , Metten Lilly , Zanger Florian , Kumar Mitra Subir , Theis Alexander , Szakáll Miklós
Published: March 2024

Experiments were conducted in the cold room of the wind tunnel laboratory at Johannes Gutenberg University Mainz, encompassing collisions between bare graupel-graupel, bare graupel-ice sphere, bare graupel-graupel with dendrites and bare graupel-snowflake. This study addresses the underrepresented domain of secondary ice processes in clouds, focusing on fragmentation due to ice-ice collisions and their role in augmenting ice particle concentration. For this study, graupels were created using a setup that simulates the natural rotation and tumbling motion of freely falling graupels. The first set of experiments aimed to recreate previous collision experiments by producing more realistic nature-like graupels, while also improving the ice crystal fragment detection and counting process. 2mm and 4mm sized graupels were chosen based on previous observational studies.This research contributes vital preliminary data, including fragment number and size distribution, as well as their dependency on collision kinetic energy. For this purpose, new coefficients fitted on our experiments following the theoretical framework have also been proposed, which can be used to parameterize the number of fragments resulting from ice-ice collisions. Our study attempts to bridge the gap between laboratory observations and numerical simulations, advancing the accuracy of atmospheric models.
Electron transfer reactions and their role in soil carbon cycling
Authors: Aeppli Meret
Published: March 2024

Electron transfer reactions are central to the transformation of energy in the environment and play an important role in biogeochemical element cycling. In soils, one of the main drivers of carbon cycling is the activity of organisms that utilize the energy stored in soil organic matter by extracting electrons from organic carbon and transferring them to various electron acceptors. Yet, our understanding of this process is incomplete and the response of the soil carbon pool to climate change remains one of the primary sources of uncertainty in projections of atmospheric carbon dioxide concentrations.Here, I discuss how we can track electron transfer reactions in soil and relate them to bioenergetic descriptors to elucidate controls on soil heterotrophic respiration. I will use two examples from my research to illustrate this:  first, I show how to characterize the redox properties of solid phase electron acceptors on the basis of reaction thermodynamics. I focus on iron minerals which are abundant solid phase electron acceptors in many soils. Using mediated electrochemistry, I quantified differences in the reactivity and energetics of synthetic iron minerals and variations in mineral redox properties during microbial mineral reduction. Second, I demonstrate how we can assess effects of mineral redox reactivity on anaerobic microbial respiration in a redox-dynamic floodplain soil. To this end, I link the kinetics of electron transfer to electron acceptors to the rate of microbial carbon dioxide production in a series of soil incubations. These two examples provide inspiration on how to integrate the redox reactivities and energetics of electron acceptors into bioenergetic frameworks.
Modelling terrestrial vegetation dynamics and carbon-nitrogen cycles over the last glacial using LPX-Bern
Authors: Sun Qing , Joos Fortunat
Published: March 2024

The terrestrial vegetation plays a crucial role in co-regulating global energy, water, carbon, and nutrient cycles. Shifts in vegetation, including changes in forest and peatland areas as well as species distribution, contribute to the large uncertainties in terrestrial ecosystems and their services under increasing disturbances caused by anthropogenic climate change.To comprehensively assess vegetation responses and feedback to perturbations, particularly regarding carbon-nitrogen cycles and greenhouse gas exchanges, modelling efforts are indispensable. For instance, dynamical vegetation models can be exploited to investigate the terrestrial biogeochemical processes under past climate changes, such as glacial-interglacial transitions. However, such efforts often remain limited by the computational demands of complex Earth system models that struggle to capture multi-millennial timescales, which is further exacerbated by the challenges associated with model validation, leaving the long-term terrestrial vegetation dynamics largely under-constrained.Here we employ the LPX-Bern model, a cost-efficient Dynamic Global Vegetation Model of intermediate complexity with fully coupled water, carbon, and nitrogen cycles, and present the results for simulations since the last interglacial. We critically evaluate the current model configuration, validated for pre-industrial to present-day conditions, for the last glacial cycle. The challenges in applying the model to these past times, such as the knowledge gaps in process representation, limited data availability for validation, and the limitations in model parameterisations, are addressed. The implications from simulating such long timescales and potentials to enhance the terrestrial biogeochemical processes in DGVMs are discussed. This study thus aims to contribute to advancing model development in carbon-nitrogen cycles for improved future climate projections.
Exposing Seasonal and Spatial Variability in Storage and Release Upstream of the Outlet
Authors: Ceperley Natalie , Kurmann Sabina , Meier Anna , Helfer Martine , Schaefli Bettina
Published: March 2024

Understanding the seasonal interplay of subsurface storage and release of water is critical to drought risk assessment in alpine environments because of the substantial carry-over effects of snow. Spatial variation across the catchment and its compartments governs the seasonal interplay and can shift dramatically according to annual fluctuations in snowfall. This analysis investigates the interaction between scale and yearly anomalies in assessing seasonal patterns of storage and release interpreted through the annual stable isotope signal (δ2H, δ18O, and δ17O) within the Vallon de Nant catchment in the Swiss Alps. We explore the limitation of simplifying catchment processes to a single outlet that integrates upstream water storage and release but overlooks nuanced variations within different compartments, including upstream springs, tributaries, near-surface groundwater, and vegetation (Larix decidua) and years with more and less snow.Furthermore, using a mixing model, we explore the effects of seasonal precipitation dynamics by examining the summer-to-winter precipitation ratio based on the variation of stable isotopes (δ2H, δ18O, and δ17O) within these distinct compartments and across multiple observation years. Notably, our findings highlight a pronounced anomaly in the fraction of summer-to-winter precipitation within springs, particularly following the snow-drought year of 2022. This observation raises critical questions regarding the long-term sustainability of groundwater resources in alpine regions. To ascertain the broader implications of this drought-induced anomaly, we extend our investigation to include 51 National Groundwater Monitoring (NAQUA) sites across Switzerland to assess the potential recurrence of this phenomenon on a broader scale.
River terrace formation in response to climate, regional uplift and local normal faulting: The Danube terrace staircase in Vienna
Authors: Salcher Bernhard , Neuhuber Stephanie , Otto Jan-Christoph , Payer Tom , Lüthgens Christopher , Fuchs Sebastian , Flores-Orozco Adrian , Ruszkiczay-Rüdiger Zsofia , Grupe Sabine , Fiebig Markus
Published: March 2024

The formation of impressive Quaternary terrace sequences along many mid to high latitudinal rivers is the consequence of surface uplift and a strong climate related impact on the fluvial system. Glacial and periglacial processes may amplify events of aggradation thereby providing clear stratigraphic markers in the fluvial terrace record. Terrace sequences are essential landforms in many continental basins even though local subsidence may counteract the regional uplift trend. We explore these opposing lithospheric forces, regional uplift vs. local normal faulting along the perialpine section of the Danube River that is supposedly strongly affected by a 100-kyr depositional cyclicity during the Quaternary. Within the city of Vienna, the Danube forms an impressive terrace staircase which is impacted by a continental scale normal fault at the transition Alps – Vienna Basin crossing the city right in its central parts. Hydrocarbon exploration indicate a vertical offset of up to c. 4 km that accumulated during the Miocene, but its recent activity remined so far ambiguous.Anthropogenic overprint led to the obliteration of terrace morphology and solifluction resulted in thick soil bearing colluvial deposits along slopes. To constrain fault activity, kinematics and stratigraphic information from terrace elevation, we used electrical resistivity tomography and analyzed data from numerous drill logs and outcrops. We applied terrestrial cosmogenic burial and luminescence dating to derive rates of vertical velocities and to support morphostratigraphic age modelling. We show how long-wavelength uplift and concomitant normal faulting controls terrace formation and landscape evolution under periods of aggradation and incision. Our study provides the largest set of cosmogenic derived depositional ages of perialpine fluvial sediments of the Eastern Alps and provides unambiguous evidence of active faulting within the city of Vienna.
Spatially remotely sensed evapotranspiration estimates in Sahel regions using an ensemble contextual model : structural uncertainty estimation and reduction 
Authors: Farhani Nesrine , Etchanchu Jordi , Dezetter Alain , Thiam Pape Biteye , Allies Aubin , Bodian Ansoumana , Boulet Gilles , Chahinian Nanee , Diop Lamine , Mainassara Ibrahim , Ndiaye Pape Malick , Ollivier Chloé , Olioso Albert , Roupsard Olivier , Demarty Jérôme
Published: March 2024

The Sahel region, identified as a "hot spot" for climate change, is characterized by a water scarcity and an inter-annual variability of water resources. Indeed, ongoing climate changes intensify the evaporative demand which could lead to more frequent period of droughts. Therefore, an important issue in these countries is to provide accurate estimation of evapotranspiration (ET) in a spatially distributed manner. The growing number of spatial ET products, including simple empirical equations (e.g., Penman-Monteith), land surface models (LSM), energy balance models, interpolated in-situ measurements, neural network approaches, or data fusion, form an interesting alternative in these areas scarcely gauged. However, until recently, there is no product combining simultaneously good spatiotemporal resolution (i.e.,
 Reconstructing the 2003-2022 Sea Level Anomalies field in ice-covered regions of the Southern Ocean
Authors: Mosneron Dupin Cosme , Sallée Jean-Baptiste , Veillard Pierre , de Lavergne Casimir , Prandi Pierre , Faugère Yannice
Published: March 2024

Despite its pivotal role in the climate system, subpolar circulation in the Southern Ocean remains poorly observed, primarily owing to the physical limitations of conventional satellite altimetry in ice-covered regions. However, recent progress in processing methods now enables precise SLA (Sea Level Anomalies) estimations within sea-ice fractures and leads.Thanks to these advances, previous studies were able to construct altimetry maps with a complete Southern Ocean coverage over the period 2011-2019. It allowed for the quantification of its full SLA seasonal cycle. Here, we introduce a novel SLA product that encompasses both open and ice-covered oceanic domains, and covers a larger temporal expanse amounting to two decades (2003-2022). Employing an optimal interpolation approach, multiple satellite missions, namely Envisat, Cryosat, SARAL/AltiKa, and Sentinel-3, are combined together, improving spatial resolution and increasing temporal range. A newly developed algorithm ensures the seamless continuity of observations, bridging the observational disconnect between open-ocean and leads data points.The robustness of the derived SLA product is corroborated against in-situ data from moorings and bottom pressure recorders. The observed seasonal cycle aligns consistently with the existing literature. Overall, the temporal extent of this dataset provides, for the first time, the opportunity to investigate the interannual variability of the whole Southern Ocean circulation through observational data.
Integrated Modelling of Landscape Functions: Testing the Impact of Land Use Change
Authors: Bogatinoska Borjana , Lansu Angelique , Hugé Jean , C. Dekker Stefan , Stoorvogel Jetse
Published: March 2024

Recognizing the limitations of disciplinary mathematical models for assessing diverse landscape functions, we present a conceptual framework for their integration. This study addresses the challenge of analysing multifunctional landscapes by proposing an integrated modelling approach. We demonstrate the feasibility and effectiveness of this approach in terms of model integration. A thorough analysis of endogenous and exogenous variables in each of the models is an important part of the framework. Through a case study in the Netherlands (catchment Aa of Weerijs) we evaluate the impact of land use change scenarios on drought resilience and on carbon sequestration.The results indicate that this framework of softly (loosely) coupling a hydrodynamic and a soil carbon model, is effective in understanding the relationship between water and carbon. The framework worked well through multiple model runs and iterations. When applied on a land use scenario of afforestation, the study area showed an average increase in soil moisture during a dry period (increase in drought resilience) and an increase in soil organic carbon (increase in sequestration).This softly coupled approach contributes valuable insights to environmental modelling, offering a pathway for researchers and practitioners to navigate complex model integration challenges. Such a softly coupled way of working with existing disciplinary models gives practitioners the opportunity to make informed decisions for sustainable landscape management. The thorough variables analysis as part of the framework enhances transparency in modelling, addressing situations where it may not always be obvious which variables and processes are represented and how.
Long-term trends of Gross Primary Productivity (GPP) and its drivers: A Comprehensive Analysis Based on Flux Measurements
Authors: Zhang Qian , He Mingzhu
Published: March 2024

This study aims to investigate the interplay of various biotic and abiotic factors on Gross Primary Productivity (GPP). Meteorological and flux observations from 71 global sites (1991-2014) obtained from FLUXNET, along with corresponding remotely sensed Fraction of Absorbed Photosynthetically Active Radiation (FPAR) data, were analyzed. The data encompassed 11 vegetation types based on the IGBP classification, including evergreen needleleaf forests, evergreen broadleaf forests, and deciduous broadleaf forests.Using the Mann-Kendall trend analysis method, trends in various parameters were extracted. Among the 71 sites, 66 sites showed significant trends in GPP, and 36 sites exhibited significant increases in GPP, accompanied by mostly increasing trends in Light Use Efficiency (LUE), except for one grassland site with a declining LUE. The trends in GPP and LUE were significantly related with a correlation coefficient of approximately 0.44. FPAR increased in some sites but decreased in 40% of the cases, while only one evergreen needleleaf forest site showed a decreasing trend in CO2 concentration. GPP and LUE were insignificantly correlated with meteorological factors (such as Air temperature (Ta), vapor pressure deficit (VPD), precipitation, and soil moisture (SM)), indicating that these environmental factors are not the main drivers. FPAR exhibited minimal changes, and the insignificant correlation between GPP and FPAR trends suggested that the increase in GPP is not solely driven by Leaf Area Index (LAI). The strong negative correlation between LUE and FPAR trends (R2 ≈ 0.31) implies that increasing LAI may decrease LUE. Additionally, a significant positive correlation between the trends of CO2 and LUE (R2 ≈ 0.19) suggests that the fertilization effect of CO2 promotes LUE, thereby promoting the increase in GPP. However, the trend in GPP shows a negative correlation with the trend in CO2 concentration, indicating that higher CO2 levels may limit the extent of GPP increase, possibly due to changes in the allocation of photosynthetic products.Further analysis is needed to understand the driving factors, especially for sites where GPP and LUE are decreasing without clear correlations with FPAR, CO2 concentration, and other meteorological factors.
A quantum computing concept for 1-D elastic wave simulation
Authors: Schade Malte , Bösch Cyrill , Hapla Vaclav , Fichtner Andreas
Published: March 2024

We present a quantum computing concept for 1-D elastic wave propagation in heterogeneous media with two components: a theoretical formulation and an implementation on a real quantum computer. The method rests on a finite-difference approximation, followed by a transformation of the discrete elastic wave equation to the Schrödinger equation, which can be simulated directly on a gate-based quantum computer. An implementation on an error-free quantum simulator verifies our approach and forms the basis of numerical experiments with small problems on an actual quantum computer. As the presented approach promises exponential speedup compared to classical numerical wave propagation methods, it has the potential to significantly push the limits of global full-waveform inversion, particularly maximum feasible frequencies, on future quantum computers.
VLBI signal transmitter onboard Earth orbiting satellites
Authors: Karatekin Özgür , Sert Hakan , Vasseur Hugues , Dehant Veronique , Ritter Birgit , Hugentobler Urs , Kodet Jan , Jelić Željko , Paternoster Karel , Kronschnabl Gerhard , Ploetz Christian , Gunessee Akhil , Lopez Rosson Graciela , Krishnan Ananya
Published: March 2024

Creating an absolute space-tie where all the geodetic methods are onboard is the key for an improved and stable terrestrial reference frame as well as with various scientific applications. Such satellite concepts  have already been proposed to achieve an accurate and stable terrestrial reference frame. Next generation  Galileo satellites can provide a single well-calibrated platform for the colocation of the space-based geodetic techniques establishing precise and stable ties between the key geodetic techniques.  One of the most crucial and novel aspect of such concepts is the VLBI transmitter (VT) which will emit quasar-like signals from the space to be observed by the VLBI ground stations. VT can directly link the terrestrial and celestial reference frames and bring the unique features of VLBI technique to an Earth orbiting satellite. In the context of call for future Galileo payloads a novel VT has been under development.  VT shall be compatible both with the legacy and VGOS antennas.  Here, we present the progress on ongoing ESA study for VT for Galileo as well as for other future  missions. 
Applicability of groundwater recharge estimation from time series modeling of groundwater levels in a (semi-)urban area
Authors: Birk Steffen , Kokimova Ainur , Collenteur Raoul
Published: March 2024

Groundwater recharge estimates can be obtained from time series of hydrometeorological variables and groundwater levels using a data-driven approach that combines a root-zone model with a lumped-parameter groundwater model. This approach was successfully tested at an agricultural site where lysimeter data of seepage is available (Collenteur et al. 2021). At that site, groundwater levels are assumed to be solely driven by recharge from precipitation. Frequently, however, groundwater levels are affected by other hydrological stresses, for example, resulting from stream-aquifer interaction or direct human impacts such as water abstraction or construction activities. To assess the method under more complex conditions, we evaluate the recharge estimates obtained from the model application to a multitude of groundwater monitoring wells located in the urban area of Graz (Austria) and the semi-urban and agricultural area south of the city (Kokimova et al. 2022). Possible influences from the River Mur, including changes in hydraulic structures, were taken into account in the model, whereas other stresses were insufficiently known and thus ignored. The resulting recharge estimates show a wide range, with values in agricultural areas often plausible. However, at some locations, particularly in the urban area, extraordinarily high values that appear implausible were estimated. Besides the possible impact of unknown water abstraction and construction activities, the simplified representation of the urban recharge processes may explain these findings. Even where the model failed to provide reasonable recharge estimates, the results support the identification of possible local influences on groundwater levels, which should be further investigated to enable a better assessment of groundwater recharge, particularly in the urban area.Collenteur, R., Bakker, M., Klammler, G., Birk, S. (2021): Estimation of groundwater recharge from groundwater levels using non-linear transfer function noise models and comparison to lysimeter data. Hydrol. Earth Syst. Sci. 25: 2931-2949. doi: 10.5194/hess-25-2931-2021Kokimova, A., Collenteur, R., Birk, S. (2022): Data-driven time series modeling to support groundwater model development for the Grazer Feld Aquifer. EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7734, https://doi.org/10.5194/egusphere-egu22-7734
A synchronized solar dynamo model and its consistency with climate data
Authors: Stefani Frank , Horstmann Gerrit , Klevs Martins , Mamatsashvili George , Weier Tom
Published: March 2024

We examine a remarkable consistency of the power spectrum of paleoclimatic varved sediment data from Lake Lisan [1] with that of a novel solar dynamo model that is doubly synchronized by tidal effects and the revolution of the Sun around the barycenter of the solar system [2,3]. We support and specify the latter model by quantifying the tidal excitation of magneto-Rossby waves [4] at the solar tachocline and by estimating the effects of spin-orbit coupling. Typical time series resulting from this dynamo model are then utilized in a double regression of solar and anthropogenic influences on the global temperature of the past 170 years in order to quantify various climate sensitivities [5]. [1] S. Prasad et al., Geology 32 (2004), 581[2] F. Stefani et al., Solar Phys. 296 (2021), 88[3] F. Stefani et al., arXiv:2309.00666[4] G. Horstmann et al., Astrophys. J. 944 (2023), 48 [5] F. Stefani, Climate 9 (2021), 163
Synoptic perspective on the conversion and maintenance of local available potential energy in extratropical cyclones
Authors: Federer Marc , Papritz Lukas , Sprenger Michael , Grams Christian M. , Wenta Marta
Published: March 2024

The global atmospheric circulation is maintained by the conversion of available potential energy (APE) into kinetic energy. At midlatitudes, this conversion occurs to a large extent in extratropical cyclones through baroclinic instability. Although kinetic energy is easily defined locally, APE is typically defined as a global integral. Therefore, local APE conversion is not well understood.Here, we investigate local APE conversion within the North Atlantic storm track using ERA5 reanalysis data. We utilize a recently introduced formulation of APE, which is exact and defined locally for individual air parcels. First, we explore APE conversion during a period of rapid cyclogenesis, which we then extend to a climatology of extratropical cyclones.Our results indicate that the synoptic upper-level flow determines the distribution of high APE values, which are primarily located in the high-latitude upper troposphere. We show that APE is converted locally into kinetic energy by descending air parcels within the ageostrophic circulation, for example, induced by a jet streak upstream of an extratropical cyclone. The local APE originates not only from advection from the polar, upper-tropospheric APE reservoir, but also from local generation by vertical motion. In fact, the net baroclinic conversion of APE to kinetic energy is the result of much larger positive and negative local contributions. Thus, the global Lorenz energy cycle is more complex on synoptic scales. In addition, we show that surface heat fluxes resulting from air-sea interactions and latent heat release act as diabatic sinks for APE. However, the effect of surface heat fluxes is small compared to the conversion of APE to kinetic energy, as little APE is located in the mid-latitude lower troposphere.In summary, the study shows that the local APE perspective allows the energetics of North Atlantic extratropical cyclones to be better understood in terms of local APE advection as well as adiabatic (ascent and descent) and diabatic effects.
Enhancement of Land Use and Land Cover Mapping using Satellite Imagery through Machine Learning Techniques 
Authors: Shakya Achala
Published: March 2024

With the advent of a large number of available satellite imagery for classification, several classification techniques have been developed to classify these images over the years. Each classification method has its own set of challenges that restrict its use. Hence, a novel research method is proposed using hybrid techniques (Machine Learning and Deep Learning) and geospatial techniques for enhancing land use and land cover mapping using satellite images. Furthermore, this study will provide insights into integrated agricultural management to achieve the UN’s Sustainable Development goals. This study uses freely available satellite images, i.e., Sentinel 1 and Sentinel 2, for classifying land use/ land cover over an agricultural area in Hissar, India. The major crops grown in this area include paddy, maize, cotton, and pulses during Kharif (summer) and wheat, sugarcane, mustard, gram, and peas during Rabi (winter) seasons. The datasets for the study area were pre-processed using SNAP and ArcGIS software. After pre-processing, a comprehensive feature set is identified consisting of Polarimetric features such as elements of covariance matrix, Entropy/scattering angle (alpha), and traditional geometric features such as shape, size, and area. After this phase, dimensionality reduction techniques (such as PCA) were applied to reduce the no. of features to the most important ones. Utilizing the feature set, a hybrid machine learning model is constructed using ground truth images by fine-tuning the model. For the best split, the test and train ratio is divided into 70:30. Optical (Sentinel 1) and Microwave (Sentinel 2) datasets are fused and the quality of the fused image was evaluated using several fusion metrics, including Erreur Relative Globale Adimensionnelle de Synthese (ERGAS), Spectral Angle Mapper (SAM), Relative Average Spectral Error (RASE), Universal Image Quality Index (UIQI), Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR), and Correlation Coefficient (CC). After obtaining the resultant fused image hybrid technique is used for the final classification. The classification accuracy is represented using overall classification accuracy and kappa value. A comparison of classification results indicates a better performance by the hybrid technique with an overall accuracy of 92%.
Individual Flood Risk Adaptation in Germany: Exploring the Role of Different Types of Flooding
Authors: Dillenardt Lisa , Thieken Annegret
Published: March 2024

Keywords: risk communication, protection-motivation, flood type, household, surveyWhether and how flood-affected people prepare for flooding is commonly assumed to depend on their perception of risk, options to cope and responsibilities. However, the influence of different flood types, i.e., fluvial, flash and urban pluvial floods, is unclear, but might be relevant for effective risk communications. We use survey data from more than 3000 households affected by different types of flooding in Germany to investigate their influence on adaptive behaviour and influencing factors. We use descriptive statistics, Kruskal-Wallis Tests and single factor ANOVA to identify differences and similarities between respondents. We use linear regressions to identify factors that influence adaptive behaviour of households in the context of fluvial, pluvial and flash flooding.We found that most respondents were motivated to protect themselves, but that there were flood type specific differences in the factors influencing an adaptive response. For example, those affected by fluvial events have had implemented most often measures before the last flooding, showed signs of emotional coping frequently and were less likely to implement (more) measures, while those affected by flash flooding showed less confidence in the effectiveness of measures, but were less likely to rate their costs as too high and were most likely to implement measures after the event. We argue that inter alia the severity and experience of flooding, as well as the management of flooding, shapes adaptive behaviour. We further found that regardless of the type of flooding, the perception of the effectiveness of adaptive measures and a positive perception of personal responsibility are critical to promote the protection motivation of those affected. We found, that these two key elements can be strengthened by offering financial support for adaptive measures. We also found that communication on a municipality level enhances the sense of self-responsibility. We conclude that communication and management strategies need to involve municipalities and should be tailored to the type of flooding. Up to now, risk communication mainly addresses fluvial flooding situations.
Unraveling Venus's Atmospheric Composition: Insights into CO, H2O, and OCS Abundances through Observations and Modeling
Authors: Liao Ting-Juan , Young Eliot , Bullock Mark , crisp dave , Yung Yuk
Published: March 2024

The investigation into Venus's atmosphere has highlighted deficiencies in photochemical models when it comes to explaining the distribution of trace gas species, particularly crucial elements like CO and OCS, which play a vital role in Venus's sulfur cycle and cloud formation.To gain a comprehensive understanding of the abundance and variability of these trace gases ahead of the DaVinci probe's descent, we initiated an observational study using NASA's IRTF telescope equipped with the high-resolution ISHELL spectrometer. Conducted from June 11 to June 30, 2023, our study involved capturing K, H, and J-band spectra of Venus's night side. We employed the SMART software to calculate synthetic spectra, considering various gas abundances and emission angles.With our high-resolution spectral data (R=λ/Δλ~25,000), we successfully mapped the abundances of CO, H2O, and OCS in the equatorial region, revealing both daily and latitudinal variations. Our focus was on examining the delicate balance between chemistry and transport, evident in the observed anti-correlation between OCS and CO abundance with cloud opacity.Through near-infrared observations, this study aims to unravel the intricate interplay between atmospheric dynamics and chemical reactions in Venus's cloud formation. By providing insights into observed cloud patterns and elucidating the relationship between atmospheric chemistry, dynamics, and cloud creation on Venus, we contribute crucial parameters to refine existing photochemical models.
A workflow for building an automatic earthquake catalog from near-real time DAS data recorded on offshore telecommunications cable in central Chile.
Authors: Baillet Marie , Trabattoni Alister , van den Ende Martijn , Vernet Clara , Rivet Diane
Published: March 2024

Distributed Acoustic Sensing (DAS) is of critical value for the offshore expansion of seismological networks. The work presented here is part of the 5-years ERC ABYSS project, which aims at building a permanent seafloor seismic observatory leveraging offshore telecommunication cables along the central coast of Chile. In preparation for this project, a first experiment named POST was conducted from October to December 2021 on a submarine fiber-optic cable connecting the city of Concón to La Serena. DAS data were recorded continuously for 38 days over a distance of 150 km, constituting more than 37,500 virtual sensors sampled at 125 Hz. We develop a workflow to detect more than 3500 local, regional and teleseismic events with local magnitudes down to ML = 0.5, automatically processing over 72 TB of data. We show that applying those methods to DAS data combined with data from the national onland seismic network greatly increases the accuracy of the earthquake hypocenter localizations. As a first step, we perform automatic seismic phase arrival picking using PhaseNet pretrained on conventional seismological stations, followed by phase association with GaMMA. We then apply a correction of the phase picks to account for shallow sedimentary layers and invert for the event hypocenter with VELEST. Finally, we estimate a local magnitude based on peak ground displacements.  The ABYSS project near-real time data collection started the 30th of September 2023 using three DAS units to sense two offshore telecommunications cables connecting the cities of Concón to La Serena and La Serena to Caldera. The DAS data covers over 500 km of cable, comprising 30,000 virtual sensors sampled at 62.5 Hz. These data are synchronized once a day with a storage server located in France, the volume of which is anticipated to reach an estimated 608 TB by the end of the project. By applying our workflow, tested and validated on the POST experiment, to our daily data, we are able to process data in near-real time to build a catalog that will span 5 years, and that will be used as a reference for subsequent studies within the framework of the ABYSS project. Furthermore, the size of our catalog, enriched with numerous offshore events is a significant improvement over the existing regional catalogs, which may aid future studies of the Chilean margin subduction zone seismicity. 
Fault offset rate and historic earthquake catalogue-based seismic coupling estimate for the central Apennines (Italy)
Authors: Di Lorenzo Cinzia , Carafa Michele , Di Naccio Deborah , Kastelic Vanja
Published: March 2024

The large amount of long-term fault slip rate measurements allows for determining the long-term tectonic moment rate for the central Apennines (Italy). Converting the long-term moment rate in seismicity rates requires a correct estimation of the long-term seismic coupling due to aseismic creep, possibly responsible for some of the observed dislocations. Ignoring this issue could induce a gross overestimation of the regional seismic hazard. Consequently, we must quantify the fraction of tectonic deformation released as earthquakes to correctly use the fault-based approach for forecasting long-term seismicity and assessing the seismic hazard of a region. To this aim, we introduce the seismic coupling in the calculation and treat it as a statistical variable. The probabilistic approach also considers the uncertainties in each parameter of active faults (depth of seismicity cutoff, length, and slip rate). The parameters of a regional Tapered Gutenberg-Richter distribution are determined to reproduce the observed earthquake size distribution. We found that about three-quarters of the long-term tectonic moment rate goes into earthquake activity, suggesting a non-marginal role of aseismic deformation for active faults in the central Apennines.
Tracking changes in the emission strengths of source-specific aerosols by coupling a receptor model with machine learning
Authors: Dai Qili , Dai Tianjiao , Bi Xiaohui , Wu Jianhui , Zhang Yufen , Feng Yinchang
Published: March 2024

Reducing aerosol mass loading requires targeted control of emissions from anthropogenic sources. Accurately tracking the changes in emission strengths of specific aerosol sources is vital for assessing the effectiveness of regulatory policies. However, this task is challenging due to meteorological influences and the presence of multiple co-existing emissions. Using multi-year data on ambient black carbon (BC) and PM2.5 from Tianjin, China, as a case study, we employed a data-driven approach that integrates a dispersion-normalized factor analysis receptor model with a machine learning technique for meteorological normalization. This approach enabled us to differentiate between the emission sources of BC and PM2.5 and their meteorological impacts. The source-specific aerosol exhibited abrupt changes in response to human-made interventions, such as those during COVID-19 and holiday periods, after accounting for weather-related variables. Notably, significant reductions were observed in emissions from coal combustion, vehicles, dust, and biomass burning over years, affirming the effectiveness of policies such as clean winter heating initiatives and the support for the Clean Air Actions. This coupled approach holds significant promise for advancing air quality accountability studies.
Leveraging Multi-Sector Needs Assessments to Assess Dynamic Social Vulnerability: A Methodological Exploration
Authors: Bove Jean-Baptiste , De Angeli Silvia , Massucchielli Lorenzo , Miozzo Davide
Published: March 2024

In the context of escalating climate change impacts, conflicts, urbanization, and the complex interplay between ecological, physical, human, and technological systems, this research explores an innovative methodology for the assessment of dynamic social vulnerability for disaster risk assessment and management by exploiting Multi-Sector Needs Assessments (MSNA) data. Current frameworks for assessing social vulnerability frequently exhibit a hazard-specific focus and are not often generalizable because of differences in methodologies or limits in data availability. Moreover, they often fail to incorporate the dynamic nature of vulnerability, and neglect the inclusion of critical context-specific elements. The proposed research addresses these limitations by exploring the innovative application of MSNAs conducted by humanitarian organizations for assessing dynamic social vulnerability. MSNAs, by providing data across various sectors and geospatial scales, offer an underutilized resource for understanding the multi-dimensional and dynamic aspects of vulnerability in crisis-affected contexts. The use of MSNA data, which includes repeated assessments over time and disaggregation by different population groups and geographic levels, presents new opportunities to understand how and why social vulnerability can change over time. This research aims to address the methodological challenges of data accessibility,  standardization, comparability, and representation of socio-economic factors by proposing an innovative way of constructing a social vulnerability index based on MSNA data and indicators that can capture and reflect changes in social vulnerability over time. This approach will be demonstrated through a case study, providing a practical illustration of how dynamic social vulnerability can be effectively measured and analyzed using MSNA data. The research will also highlight how the methodology can be replicated to any other country for which MSNA data is available. By bridging the gap between crisis-driven needs assessments and long-term social vulnerability analysis, this study contributes to more informed, context-specific, and timely strategies in disaster risk management, humanitarian response and policy-making. The findings are expected to enhance the understanding of social vulnerability in varied contexts, highlighting the dynamic nature of vulnerability from a multi-risk and multi-hazard perspective.
Improving sea ice projections with the modern-era satellite altimetry record of freeboard and thickness
Authors: Petty Alek , Cardinale Christopher , Smith Madison
Published: March 2024

Future projections of Arctic sea ice remain poorly constrained, due in large part to the significant inter-model spread across the CMIP6 archive. Various recent studies have explored novel calibration methods to better constrain future sea ice conditions, especially the timing of an ice-free Arctic, but can come to different conclusions based on the calibration approach taken. Some approaches exclude outlier models, while others seek to exploit sensitivities of sea ice area/extent to global warming (e.g., Northern Hemisphere temperatures) to better constrain the multi-model ensemble. As long-term and reliable observations of sea ice thickness are lacking, calibration efforts have primarily relied on sea ice concentration/area data from the passive microwave satellite record. We are leading a new NASA-funded effort to utilize the multi-year record of observed sea ice freeboard and derived sea ice thickness from ICESat-2, together with similar data from the original ICESat and ESA’s CryoSat-2 missions, to reduce inter-model uncertainty in future sea ice projections. Although the sea ice altimetry data record is more limited in space and time than the longer-term passive microwave concentration record, it can offer significant advantages; for example, freeboard is measured very accurately by modern laser altimetry satellites, providing more information within the consolidated ice pack, and is now output by some of the CMIP6 models, enabling direct comparisons between the model and the satellite measurements. Only a small fraction of CMIP6 models provide the direct output of derived freeboard so assumptions (mainly related to the bulk ice and snow density) need to be made when estimating freeboard with the core model output. Initial results suggest this can have an important impact on the comparisons. Converting the observations of freeboard to sea ice thickness introduces significantly more uncertainty to the observed data but can radically simplify the model comparison effort. In this presentation we will showcase our initial efforts to better utilize the satellite altimetry record for calibrating CMIP6 simulations of future sea ice conditions across both poles, but with a primary focus on projections of the timing of an ice-free Arctic. We discuss some of the nuances of using freeboard as a more direct observational constraint compared to thickness, providing motivation for more modeling groups to provide the direct ice density and freeboard outputs in the lead-up to CMIP7. Finally, our analysis has all been carried out within the NASA-supported CryoCloud compute environment using the cloud-based (AWS) CMIP6 data archive, so we include additional insight into the benefits of this analysis approach and the small but important impact from differences in model output availability (compared to the recent IPCC analysis). 
A comprehensive model for COS isotope discrimination during leaf COS uptake
Authors: Ubierna Nerea , Baartman Sophie L. , Popa María Elena , Ogée Jérôme , Krol Maarten C. , Wingate Lisa
Published: March 2024

Anthropogenically emitted CO2 is warming the earth’s climate to temperatures that already exceed pre-industrial levels by more than 1.2 oC. Terrestrial vegetation has slowed the rate of climate change by removing part of this anthropogenic emission. Accurate estimations of the present and future terrestrial carbon sink are still needed for forecasting climate and for informing policies for climate stabilization. This requires precise knowledge of the photosynthetic C uptake over land (gross primary production, GPP), independently of the C released through plant and soil respiration. The gas carbonyl sulfide (COS) has emerged as a promising tracer for GPP. This is because both CO2 and COS are a substrate for carbonic anhydrase (CA), the first enzyme involved in photosynthesis, so that the uptake by foliage of COS and CO2 often covaries. Estimating GPP from COS measurements and atmospheric budgets also requires quantifying ocean and industrial COS sources, which is challenging. Isotopic constrained COS tropospheric mass balances can help quantify the relative contribution of these sources if the isotope discrimination during COS uptake by terrestrial vegetation (the main COS sink) is known. However, little is known about plant-atmosphere COS isotope exchange; measurements are challenging and theory to interpret these measurements is limited. Herein, we present a new comprehensive model for discrimination during COS uptake by plants (∆34S) and use it to revisit existing COS isotope datasets and atmospheric budgets. Our ∆34S model expands Davidson et al. (2022) pioneer framework by accounting for leaf COS production. By analogy with the well-established model for photosynthetic discrimination against 13CO2, Davidson et al. ∆34S model stated that COS discrimination occurs as COS diffuses into the leaf and binds to CA. Leaf COS emission was not considered, although it has been reported in species ranging from bryophytes to wheat and trees. Because it is uncertain where these emissions occur, we tested different leaf-level COS emission scenarios - including zero emissions - in various leaf compartments (cuticle, intercellular space, cytosol), alone or in combination. We used this comprehensive model to generate predictions for ∆34S in C3 and C4 species and discussed implications for determining a global plant uptake fractionation factor. Our mechanistic model provides a framework to interpret vegetation-atmosphere COS isotope exchange that can prove useful to improve COS uptake-based GPP estimates and our understanding of plant function, especially when combined with other isotopes (C, O, H).
Effect of cover cropping and soil tillage on soil CO2 emissions
Authors: Gelybó Györgyi , De Luca Giulia , Balogh János , Fodor Nándor , Fóti Szilvia , Sugár Eszter , Sándor Renáta
Published: March 2024

It has long been in the focus of research interest how cover cropping affect water regime of the soil. However, its simultaneous effect on CO2 emission, i.e. soil respiration is not so widely reported. We examined an agricultural experiment set up as a maize-oat rotation under conventional and reduced tillage tillage and four different cover-cropping treatments (fallow, oilseed radish, mixture, phacelia) in Martonvásár (Hungary). Soil respiration measurements were carried out using infrared gas analyzer in 5 replicates per treatment plot (tillage-main-crop-cover crop combinations). Measurements covered two years in the different main crops and also in cover crops. A total of 10 measurement campaigns were organized in 2021 and 2022, which covered both main crops and cover crops. Meteorological parameters were measured in a nearby automatic meteorological station.Besides soil respiration measurements ancillary measurements have been carried out to better characterize soil status. Using a penetrologger soil penetration resistance, using handheld sensors, soil water content measurements and soil temperature was recorded. Also, point scale continuous soil water content profile measurements were carried out. At each plot, vegetation was characterized using the VI green index derived from RGB imagery and periodically chlorophyll content (SPAD) and leaf area index was recorded. Here we analyze soil respiration, VI green soil temperature and soil water content measurements. The results showed differences between tillage treatments and between main crops. For further results please see abstract “Impact of cover crops and conventional and reduced tillage on plant productivity in a bicultural maize-oat cropping system”.