bluuebunny/crossref_metadata_2025 huggingface dataset:
Onset Periods: a novel approach to understand the onset of the monsoon season
Authors: Zilli Marcia , Hart Neil , Morris Francesca
Published: March 2024

In recent decades, several studies have proposed different methodologies to reliably identify the onset of the rainy season in monsoon climates, considering either a single variable, usually precipitation, or a combination of rainfall with other dynamic and thermodynamic variables (e.g. wind, specific humidity). These methodologies tend to define a single onset date, which can fail to diagnose critical characteristics of early season rainfall such as wet/dry spell phasing and intensity. Here, we propose a novel approach to identify the transition from dry to wet seasons as a period (6-8 weeks on average) with a positive gradient of the FFT-filtered precipitation, indicative of a steady increase in rainfall. This approach allows the characterisation of critical onset period rainfall characteristics, including information about wet and dry spell frequency and total precipitation, which is a valuable advance on typical single-date onset methods. Preliminary results considering observational and reanalysis datasets indicate a good agreement between the onset day identified using a traditional methodology and the onset periods over South America and Africa. A more in-depth analysis of the identified onset periods can provide further insights into the role of intraseasonal and interannual variability on the precipitation regimes. We also identified regions with distinct changes in the onset periods timing and related precipitation characteristics when considering present and future climate simulations, including simulations using convective-permitting models. For example, the method is able to distinguish that parts of eastern Brazil are projected to have a later onset period with more intense wet days, whereas in eastern Amazon the key signal is more dry days during the onset period, leading to a weaker intensity of onset. In addition to identifying the rainy season onset periods, this approach also identifies other onset periods, further classified as false onset (interval with positive filtered precipitation gradient followed by the onset period), second onset (interval with a secondary increase in the filtered precipitation gradient after the onset period), or wet spells (occurring during the dry season). These periods provide valuable information about spells of increased precipitation outside the rainy season onset, such as wet spells during the dry seasons or false onsets before the primary rainy season. When recurrent, they can indicate the influence of interannual or intraseasonal variability in off-season precipitation. As the core statistics that emerge from this approach are related to the intensity and phasing of rainfall rather than absolute amounts, future developments will focus on implementing the method in a seasonal forecast system, where only a few months of data are available, with the potential to obtain forecast skill which circumvents absolute rainfall biases.
Mapping the intensity of brittle deformation through ice covered regions: a study from Antarctica (North Victoria Land)
Authors: Cianfarra Paola , Bagnasco Alessio , Locatelli Michele , Federico Laura , Morelli Danilo , Salvini Francesco , Crispini Laura
Published: March 2024

North Victoria Land (NVL), Antarctica is one of the most remote and inaccessible outposts of our planet where few outcrops are available for direct geological investigation. The long-lasting tectonic evolution of this region results in a complex architecture characterized by the presence of regionally sized, crustal scale faults whose structural characteristics (e.g. geometry, thickness, location of transfer zones and off-shore prosecution) are still debated.In this work we present a map of the intensity of brittle deformation measured in 113 field outcrops along the Rennick-Aviator km-scale fault corridor, and quantified through the non-dimensional and scale invariant H/S parameter (H = fracture dimension and S = spacing among fractures belonging to the same azimuthal family; see Cianfarra et al. 2022). The sparse fracture measurements where then interpolated with Surfer® (Golden Software, LLC) v. 23.2.17 to analyse the spatial variability of deformation with the aim of clarifying the tectonic link between the Rennick and Aviator faults.The thematic map is prepared by a polymodal regression by full cubic surface that was applied to the field measurements (between 70.5°-71 °S and 160-165.5°E) collected during scientific expeditions funded and logistically supported by the Italian National Antarctic Program (e.g.; PNRA16-00056_G-IDEA and PNRA18-00338_LARK projects). Measurements were normalized by a weighting factor to take into account the brittle strength variability of the analysed lithotypes (e.g., basalts-dolerites, well cemented sandstone-conglomerates, granites-migmatites, gneiss)The comparison of our georeferenced thematic map with existing maps of satellite-derived potential fields, bed subglacial topography and off-shore bathymetry, and Antarctic geology which are available as free dataset in the web (e.g. ADMAP, BEDMAP, Quantarctica, GeoMAP dataset, among the others) allows to supply constraints for modelling ice covered tectonic structures, to better highlight the active role of the main tectonic lineaments of NVL, as well as to clarify the relationship, connection and link between onshore and offshore tectonic structures (this last topic is being investigated in the frame of the ongoing PNRA19-00051_BOOST project).Cianfarra et al. 2022, Tectonics 41, e2021TC007124, https://doi.org/10.1029/2021TC007124
Attribution of extreme weather events in Germany
Authors: Schröter Jonas , Tivig Miriam , Lorenz Philip , Kreienkamp Frank
Published: March 2024

Since 2019, the Deutsche Wetterdienst (DWD) has been actively developing a workflow for the operational attribution of extreme weather events. The primary objective is to automate as many steps of the process as possible with minimal human input, to communicate the impact of climate change on a particular event within days to weeks after it has happened.In parallel with some studies together with the World Weather Attribution group (WWA), like the study by Tradowsky et al. (2023) regarding the flash-floods in Western Europe in 2021, the decision was made to develop a national rapid attribution workflow. This leads to the opportunity to semi-operationally attribute more (and in addition weaker) extreme events. So far, in the first phase of the ClimXtreme project (https://climxtreme.net/), a prototype workflow for probability-based attribution was established based on the protocol used by the WWA (Philip et al., 2020). Now, in the second phase of the project, a synthesis tool will be added. The optimal approaches for a synthesis tool of different model results and observations are still a topic of active discussion. The synthesis itself is crucial for the end result of every probabilistic attribution study. Especially for rapid analysis, there has to be a fixed and accepted method that can be applied for different events. Various syntheses are therefore compared in order to determine the ones that are best suited for the region under consideration (mostly Germany and Mid-Europe) and for different event classes.This poster will focus on the recent developments and possible synthesis options for the probabilistic extreme weather event definition.
Temporal dynamics of water quality and microbial community composition in alpine springs
Authors: Boanca Filip Paul , Seelig Magdalena , Karwautz Clemens , Gerfried Winkler , Griebler Christian
Published: March 2024

Springs are vital water sources, and their vulnerability to environmental changes, particularly climate change, is of growing concern. The collaborative research project ECOSPRING, funded by the Austrian Academy of Sciences, focuses on the assessment of microbial communities and water quality patterns in selected springs all over Austria. Here, we will focus on understanding the response and vulnerability to hydrological events and climate change.The first aim of the project is to characterize the springs based on their temporal dynamics in terms of physical-chemical characteristics. A detailed analysis of the dynamics in discharge, temperature, pH, EC, stable isotopes, essential nutrients, and major ions will provide valuable insights into the geological imprint and prevailing hydrological conditions, as well as on catchment areas.Microbes are an integral component of aquatic ecosystems and can serve as sensitive indicators for environmental conditions. We will compare the microbial community composition in relation to the hydrogeological and physicochemical conditions.Our research activities target two spatial scales, from a local perspective, with 14 springs in the province of Styria studied monthly, to a regional approach by sampling around 100 springs distributed all over Austria twice, in winter/spring and summer/autumn marking the expected hydrological extremes.In the initial stages of our research, we gathered data from 15 selected springs of Styria. These springs exhibit a wide and dynamic spectrum in their physical-chemical properties. Together with records of discharge, springs could be categorized into stable, intermediate, and highly dynamic systems. Our preliminary results indicate a connection between these fluctuating physical-chemical conditions and the composition of the spring water microbiome. The underlying mechanisms driving these observed patterns are yet not fully understood and await further investigations.In summary, this research project seeks to enhance our understanding of the vulnerability of spring waters to anthropogenic pressures such as climate change. The findings will provide a knowledge base for future water resources management and contribute to the sustainable use of these vital resources.
The International Soil Moisture Network (ISMN): providing a permanent service for earth system sciences
Authors: Zink Matthias , Boehmer Fay , Korres Wolfgang , Kramer Kasjen , Dietrich Stephan , Olarinoye Tunde
Published: March 2024

Soil moisture is recognized as an Essential Climate Variable (ECV), because it is crucial to assess water availability for plants and hence food production. Having long time series of freely available and interoperable soil moisture data with global coverage enables scientists, practitioners (like farmers) and decision makers to detect trends, assess the impacts of climate change and develop adaptation strategies.The collection, harmonization and archiving of in situ soil moisture data was the motivation to establish the International Soil Moisture Network (ISMN) at the Vienna University of Technology in 2009 as a community effort. Based on several project funding periods by the European Space Agency (ESA), the ISMN became an essential means for validating and improving global land surface satellite products, climate and hydrological models. In December 2022, the ISMN was transferred to a new hosting facility the International Centre for Water Resources and Global Change (ICWRGC) and the German Federal Institute of Hydrology (BfG) in Koblenz (Germany). ISMN data are successfully provided from the new host since then and will be for decades to come as the German government committed to its long-term funding.This presentation is going to showcase the International Soil Moisture Network (ISMN). Beyond offering comprehensive in situ soil moisture data, ISMN freely disseminates additional environmental variables, including soil temperature, snow depth, snow water equivalent, precipitation, air temperature, surface temperature and soil water potential if they are available from our data providers. With a global reach, ISMN has already accumulated 3000 stations with observations at various depths, while about 1000 stations are updated on a daily basis. Ongoing efforts are concentrated on expanding the database by incorporating additional stations and networks from institutional or governmental sources. Substantial resources are directed towards fortifying the operational system and improve usability to better serve our users. Additional efforts are undertaken to include ISMN in the data-to-value chain by contributing to international initiatives like WMO, FAO and GCOS. One example is the contribution to WMO’s yearly Global State of the Water Resources report.
Guiding post-fire recovery: an assessment of Scots pine seed predation in the framework of active restoration interventions after a high-severity wildfire
Authors: Domanico Matteo , Mantero Giulia , Pastore Francesco , Meloni Fabio , Garbarino Matteo , Marzano Raffaella
Published: March 2024

The increase of wildfire severity and frequency in the Mediterranean area combined with the harsher environmental conditions damped by ongoing climate change, can hinder regeneration recruitment, particularly for obligate seeders in mountain ecosystems. Therefore, rethinking current post-fire management strategies in mountain ecosystem is crucial to mitigate the consequences of wildfire regime alterations on forest ecosystems and to re-establish ecosystem trajectories after large and severe wildfires. The high temperatures and scarce rainfall that characterized Autumn 2017 in Piedmont (North-Western Italy) led to an uncommon fire season, with ten large wildfires that burned about 9700 ha. The Susa fire was the largest event, burning with mixed severity almost 4000 ha, with Scots pine (Pinus sylvestris L.) stands being affected with the highest severity. Following the event, a reforestation project was started, aiming to restore the forest cover, particularly in large high severity patches far away from seed trees, likely to be affected by further degradation phenomena. Given the scarcity of Scots pine seedlings available in forest nurseries, direct seeding was considered a valid option, but it needed to be carefully planned, especially because of seed predation and run-off. Indeed, post-dispersal seed predation plays a key role in the natural dynamics of forest ecosystems as it can deeply affect the number of seeds available for recruitment. To assess the dynamics and rate of seed predation by different taxa and to identify the magnitude of seed losses, an experimental approach was then applied. Specific field experiments are being performed in both the fall and spring seasons, starting from October 2023, to evaluate the magnitude of post-dispersal seed predation within the high severity patches of the Susa fire, its spatial distribution considering three different microhabitats (open areas, close to deadwood, under shrubs) and the main predators involved among insects, birds, and rodents. Understanding the impact of post-dispersal seed predation is a crucial aspect to develop targeted post-fire management strategies, possibly reducing restoration costs and improving its success.
Inferring geographic and climatic variation in plant hydraulic traits from flux data
Authors: Joshi Jaideep , Arán Paredes Josefa , Stocker Benjamin
Published: March 2024

Plant water stress has major implications for vegetation productivity, mortality, and global carbon cycle variations. Yet, its representation in models constitutes a major source of uncertainty. This is related to uncertainties in the representation of water stress exposure due to unknown belowground rooting structure and water storage, and uncertainties in the representation of interactive responses to atmospheric dryness (vapour pressure deficit, VPD) and belowground moisture.Recent theoretical developments have given rise to several hydraulically explicit models for predicting plant physiological responses to VPD and belowground moisture at the leaf level. The P-hydro model that we have recently developed, accounts for the simultaneous acclimation of stomatal conductance and photosynthetic capacity using an eco-evolutionary optimality approach. Based on three “first principles” (balance of water demanded by transpiration and that supplied from the soil, coordination of the carboxylation-limited and light-limited photosynthesis rates, and maximization of net profit after accounting for the costs of maintaining photosynthetic and hydraulic capacities), it correctly predicts the responses of stomatal conductance, assimilation rates, leaf water potentials, and photosynthetic capacities to changing hydroclimatic environments. However, the hydraulic strategies of plants depend critically on their belowground rooting environments, such as soil properties and rooting depth.Here, we implement the P-hydro model for modelling ecosystem-level fluxes and couple it with a simple model of soil water balance within the rsofun modelling framework. The water-balance model accounts for variations in root-zone water storage capacity of plants, thus allowing us to characterize both above-ground and belowground hydraulic strategies. We investigate (1) the power of P-hydro in simulating gross primary production and evapotranspiration at globally distributed FLUXNET sites under conditions of simultaneous atmospheric and belowground dryness, benchmarked against a non-hydraulically explicit version of the model (P-model), (2) apply a Bayesian data assimilation approach to infer plant and soil hydraulic traits (plant conductivity and vulnerability, root zone water storage capacity, and cost parameters of the optimality model), (3) assess the environmental dependencies of the inferred traits and the generalisability of the model for global simulations.The P-hydro model, together with the inferred trait relationships, promises a simple yet robust approach to predicting the global environmental dependencies of ecosystem productivity.
Unlocking the potential of observations in shoreline modelling through data assimilation
Authors: Álvarez-Cuesta Moisés , Toimil Alexandra , Losada Iñigo
Published: March 2024

Analyzing the coastal response is a complex problem that usually requires the use of numerical modelling in combination with observations (Alvarez-Cuesta et al., 2023). To this end, data assimilation is a useful tool to blend observational data and models to produce more accurate forecasts.Here, the performance of different data assimilation algorithms in predicting multiscale shoreline dynamics is studied. Two statistical algorithms based on the Kalman filter (Alvarez-Cuesta et al., 2021) and one variational algorithm named 4DVar (LeDimet, F-X. & Talagrand, O., 1986) are employed together with an equilibrium cross-shore model and a one-line longshore model. A twin experiments procedure is performed to obtain the observation requirements for the different assimilation algorithms in terms of accuracy, length of the data collection campaign and sampling frequency. Similarly, the initial system knowledge needs and the ability of the different assimilation methods to track the system non-stationarity are evaluated under synthetic scenarios. With noisy observations, the Kalman filter variants outperform the 4DVar. However, the 4DVar is less restrictive in terms of initial system knowledge and tracks nonstationary parametrizations more accurately for cross-shore processes. Results are demonstrated at two real beaches governed by different processes with different data sources used for calibration and stress the need for assimilating shoreline observations to produce robust forecasts.REFERENCESAlvarez-Cuesta, M., Losada, I. J. & Toimil, A. (2023). A nearshore evolution model for sandy coasts: IH-LANSloc. Environmental Modelling and Software, 169, 105827Alvarez-Cuesta, M., Toimil, A., & Losada, I. J. (2021). Modelling long-term shoreline evolution in highly anthropized coastal areas. Part 1: Model description and validation. Coastal Engineering, 169(July), 103960.LeDimet, F-X. & Talagrand, O. (1986). Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus a 38.2: 97-110.
Applicability Of Multi-National Digital Elevation Model (DEM) For Cross-Boundary Flash Flood Modeling
Authors: Mohammed Mohammedawel Jeneto
Published: March 2024

In July 2021, the northwestern European continent experienced a devastating flood caused by unusually high rainfall, resulting in significant socio-economic destruction. One of the areas that was highly affected by this flooding was Southern Limburg (Geul River) in the Netherlands. The Geul River, located between Belgium, Germany, and the Netherlands, posed a challenging situation for modeling the catchment due to its cross-boundary nature. The need to harmonize input datasets from different countries with varying characteristics arose despite the abundance of available data in the study area. This study assesses the feasibility of combining multi-national Digital Elevation Models (DEM) for cross-boundary flash flood modeling purposes.The quality of the DEM significantly impacts the accuracy of flood dynamics. However, it should be noted that elevation data from various sources creates elevation mismatches, particularly in the overlapping areas between different DEMs. A comprehensive quality assessment is indispensable to ensure the compatibility and reliability of these datasets for hydrology and flood modeling. Thus, To evaluate the accuracy of the DEMs, various statistical measures such as Root Mean Square Error (RMSE), Mean and Standard Deviation (STD) have been calculated. Initially, a pixel-by-pixel-based elevation difference map was generated. Upon analysis, it was observed that the overall elevation differences ranged from -7.0 to 7.0 meters. Despite certain pixels exhibiting pronounced differences in elevation, the overall statistical analysis indicated minimal variation. The calculated RMSE and STD values were both ≤ 0.3 meters for the overlapping parts of the DEM. These errors were considered negligible in relation to the actual slope values and had no significant impact on the flow direction within the catchment. This merged dataset provides a comprehensive representation of the terrain, enabling more accurate and reliable flood modeling simulations compared with calibrated result.
Improved root development leads to higher root derived carbon stocks in formerly deep-plough soils - A biomarker-based approach
Authors: Gocke Martina , Burger Dymphie , Schneider Florian , Kappenberg Arne , Bauke Sara
Published: March 2024

Roots can add significant amounts of carbon (C) to the subsoil, which enhances soil fertility and can mitigate climate change. About 5% of agricultural soils in Germany have been deep-ploughed (ploughing depth 30-120 cm) at least once. This technique can provide better root access to the subsoil and may help to increase yields. Studies on deep-ploughed soils focused on C stability, whereas not much is known about root-derived C in the subsoil (>0.3 m). We hypothesized that five decades after deep-ploughing, root-derived C stocks were higher compared to conventionally ploughed treatments due to better root development. This was measured by analysing suberin and cutin monomers as tracers for root- and shoot-derived C at three former deep-ploughed sites in N Germany with different soil textures and different deep-ploughing depths. Concentrations of suberin monomers in the soil were positively correlated with root biomass, this was especially strong at one sandy site. Suberin contributed more to the bulk soil organic carbon (SOC) stocks than cutin throughout the soil profile, independently of the ploughing depth. The three sites responded differently to deep-ploughing. The contribution of suberin monomers to the bulk SOC stock at silty site Banteln and the sandy site Essemühle was 38% higher in the deep-ploughed plots than at the reference plot, respectively, these differences were most visible in the subsoil of Essemühle. We conclude that when deep-ploughing enhances C stocks and root development, suberin SOC stocks increase as well, especially in the subsoil of sandy sites with low pH.
Multifractal analysis for evaluating the representation of clouds in global km-scale models
Authors: Freischem Lilli , Weiss Philipp , Christensen Hannah , Stier Philip
Published: March 2024

Clouds are one of the largest sources of uncertainty in climate predictions. Emerging next-generation km-scale climate models need to simulate clouds and precipitation accurately to reliably predict future climates. To isolate issues in their representation of clouds, and thereby facilitate their improvement, km-scale models need to be thoroughly evaluated via comparisons with observations.Traditionally, climate models are evaluated using spatio-temporally averaged observations. However, aggregated evaluation loses crucial information about underlying physical processes, such as convective updrafts, and the resulting cloud macrophysical structures. We postulate that a novel spatio-temporal evaluation strategy using satellite observations provides direct constraints on physical processes.Here, we introduce multifractal analysis as a method for evaluating km-scale simulations. We apply it to top-of-atmosphere outgoing longwave radiation (OLR) fields to investigate structural differences between observed and simulated clouds in the tropics. For this purpose, we compute structure functions from OLR fields to which we fit scaling exponents. We then parameterise the scaling exponents to compute scaling parameters. The parameters compactly characterise OLR variability and can be compared across simulations and observations. We use this method to evaluate the ICON-Sapphire and IFS-FESOM simulations run for cycle 3 of the nextGEMS project via comparison with data from the geostationary satellite GOES-16.We find that clouds in both models exhibit multifractal scaling from 50 to 1000km. However, the scaling parameters are significantly different between ICON and IFS, and neither match observations. In the ICON model, multifractal scaling exponents are lower than in observations whereas in IFS, they are larger. The observed differences indicate how the modelling approaches in ICON and IFS impact the organisation of clouds. More specifically, the deep convection scheme in ICON is switched off completely whereas it is still active in IFS, which could explain the difference in scaling behaviour we observed.Our results show that spatio-temporal analysis is a promising new way to constrain global km-scale models. It can provide key insights into model performance and shed light on issues in the representation of clouds.
Quality assessment of Persistent Scatterer Interferometry time series using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling
Authors: Omidalizarandi Mohammad , Shahryarinia Kourosh , Mohammadivojdan Bahareh , Neumann Ingo
Published: March 2024

Large-scale, cost-effective, and reliable deformation monitoring of natural objects or man-made infrastructures is still challenging. Numerous past studies have employed the Persistent Scatterer Interferometry (PSI) technique, utilising open-source synthetic aperture radar (SAR) data from C-band of satellite Sentinel-1, for this purpose. However, a limited number of investigations have been performed to evaluate the quality of the Persistent Scatterer (PS) data points.
In this research, a comprehensive and sophisticated multi-step procedure is developed and implemented to perform quality assessment of the PS data points using vector-autoregressive-based spatio-temporal (VAR-ST-PS) modelling. Firstly, the PS points are classified into buildings and ground types using LoD2 building models. Multivariate PSI time series analysis is then carried out to understand the temporal behaviours of groups of PS points in local geometric patches. This involves modelling and analysing PSI time series to estimate deterministic and stochastic parameters such as offset, velocity, standard deviation, and corresponding distributional parameters. A spatio-temporal modelling is employed within the local geometric patches of PS points using a mathematical surface approximation model. A 95% confidence interval is estimated for the approximated surfaces using a bootstrapping approach. Subsequently, an appropriate quality model for the PS points is derived from the above-mentioned temporal and spatial modelling.
The quality assessment and subsequent deformation analysis are carried out for areas of interest in the state of Lower Saxony, Germany. The PS data points for this study are extracted from the freely available online platform of the BodenBewegungsdienst Deutschland (Ground Motion Service Germany) provided by the Federal Institute for Geosciences and Natural Resources (BGR), Germany. For validation purposes, a time series of leveling and Global Navigation Satellite System (GNSS) measurements in the Hengstlage area, Germany, are considered, which provided by Landesamt für Geoinformation und Landesvermessung Niedersachsen (LGLN). In addition, cross-validation is performed for different local geometric patches. In the end, the results of the deformation analysis are compared with those obtained from the BGR. The outcomes of this study can be used to track earth surface displacements over time. This information could be valuable in understanding natural hazard processes such as landslides, earthquakes, and floods, and in improving the safety and resilience of communities and infrastructure.
Paleomagnetism of the Late Cretaceous Padana Fm in Xigaze forearc basin and its paleogeographic constraints on the southern margin of Asia prior to the India-Asia Collision
Authors: Xu Shihua , Li Yong-Xiang , Liu Xinyu , Li Bincheng , Li Xianghui
Published: March 2024

The Xigaze forearc basin was formed along the southern margin of Asia as the Neo-Tethys Ocean subducted beneath Asia. Among the strata within the Xigaze forearc basin, the Padana Formation (Fm) comprises purple-red and gray shale interbedded with sandstone, and likely holds crucial evolution information of the southern Asian margin during the Late Cretaceous prior to the India-Asia collision. However, the chronology of the Padana Fm has not been well constrained. To refine the chronology of the Padana Fm and better constrain the paleopositions of the southern margin of Asia, we conducted a paleomagnetic study of the strata in the Xigaze forearc basin, with a particular focus on the Padana Fm. A total of 263 paleomagnetic samples were collected and subjected to stepwise thermal demagnetization, revealing two-component magnetizations. The low temperature component (LTC) was removed by ~300℃, representing overprints of the present geomagnetic field. The high-temperature component (HTC) was typically unblocked at 580∼680 °C, indicating magnetite and hematite as major remanence carriers. A total of 110 reliable HTCs were isolated from the sandstones in the Padana Fm and passed reversal tests, representing primary remanence. Changes in polarities of the HTCs with stratigraphic heights define four polarity zones, which, together with results of previous detrital zircon U-Pb ages and biostratigraphic zones, allow to constrain the chronology of the Padana Fm to 83.6 Ma-69.2 Ma. With the significantly refined chronology, the paleomagnetic data of the Padana Fm can be used to constrain the tectonic evolution of the Xigaze forearc basin in the Late Cretaceous. Tentative interpretations of the coeval paleogeography of the southern Asian margin prior to the India-Asia collision will be discussed.
Chlorine cycle in subduction zone settings: insights from chlorine isotopes in olivine-hosted melt inclusions and bulk rocks
Authors: Bouvier Anne-Sophie , Rose-Koga Estelle , Portnyagin Maxim , Nichols Alexander , Flemetakis Stamastis , John Timm
Published: March 2024

Chlorine (Cl) is a highly hydrophile and incompatible element which may provide insights into the transfer of elements from the slab to the surface in subduction zone settings. Bulk rocks data have shown that Cl stable isotopes (δ37Cl) are effective tracers of subducted fluids influence in volcanic rocks, with δ37Cl variation up to 3‰ along an arc (Barnes et al., 2009). Nevertheless, a more profound comprehension is needed to identify the specific contributions from the different slab lithologies. Recent advancements in secondary ion mass spectrometry (SIMS) enable precise determination of δ37Cl values at high spatial resolution. In situ measurements of olivine-hosted melt inclusions provide a first order constraint on the δ37Cl of primary magmas since these melt droplets are unaffected by near surface processes.Chlorine isotopes measurements in melt inclusions from arc samples have revealed large variation within a single rock sample (more than 2‰), and even larger considering melt inclusions from different rock samples along a single arc (up to 5‰). The combination of these data with O and B stable isotopes or with trace elements, measured within the same melt inclusions, suggest that the intra-sample and along-arc variations are related to variable influences of different Cl sources (Bouvier et al., 2019; Bouvier et al., 2022a,b). Indeed, the lowest δ37Cl values (down to -3.4‰) usually reflect the imprint of subducted sediments, whereas the highest δ37Cl values (up to -3.1‰) might reflect the presence of amphibole in the mantle source. Intriguingly, when we compare δ37Cl values from bulk rocks with those obtained in situ in melt inclusions from the same volcano, discrepancies occasionally emerge. These deviations cannot be ascribed solely to instrumental biases. Instead, the difference between bulk rocks and melt inclusions suggests that the latter preserve undegassed signatures which might be lost in bulk rocks. In situ measurement of δ37Cl in melt inclusions can thus be very useful to: (i) better constrain the behavior of Cl and δ37Cl in subduction zone settings, in particular during fluid-rock interaction within the mantle wedge and during degassing, and (ii) track the influence of crystallization/dissolution of Cl-rich minerals in the context of arc magma genesis and differentiation. References:Barnes et al. (2009), G3, doi:10.1029/2009GC002587; Bouvier et al. (2019), EPSL 507, doi:10.1016/j.epsl.2018.11.036; Bouvier et al (2022a), EPSL 581, doi:10.1016/j.epsl.2022.117414; Bouvier et al. (2022b), Front. Earth Sci., doi:10.3389/feart.2021.793259
Soil CO2 emission and stable isotopes (δ13C, δ18O) of CO2 and calcites reveal the fluid origin and thermal energy in the supercritical geothermal system of Krafla, Iceland
Authors: Bini Giulio , Chiodini Giovanni , Ricci Tullio , Sciarra Alessandra , Caliro Stefano , Mortensen Anette K. , Martini Marco , Mitchell Andrew , Santi Alessandro , Costa Antonio
Published: March 2024

The Krafla geothermal system is located within a volcanic center that periodically erupts basaltic lavas, and has recently attracted an economic interest due to supercritical fluids forming near a shallow magma intrusion (~ 2 km depth). Here, we discuss new soil CO2 flux and stable isotope data of the CO2 efflux (δ13C) and hydrothermal calcites (δ13C, δ18O) of drill cuttings to estimate both the current magmatic outgassing from soils and the thermal flows in the geothermal system. Soil CO2 emission is controlled by tectonics, following the NNE-SSW fissure swarm direction and a WSW-ENE trend, and accounts for ~ 62.5 t d–1. While the δ18O of the H2O in equilibrium with deep calcites is predominantly meteoric, both the δ13C of the soil CO2 efflux and of the fluids from which calcite precipitated have a clear magmatic origin, overlapping the δ13C estimated for the Icelandic mantle (–2.5 ± 1.1 ‰). Estimates based on the soil CO2 emission from the southern part of the system show that these fluxes might be sustained by the ascent and depressurization of supercritical fluids with a thermal energy of ~800 MW. Such significant amount of energy might reach 1.5 GW if supercritical conditions extended below the whole investigated area. Finally, we report an increase in the soil CO2 emission of about 3 times with respect to 14 years ago, likely due to recent changes in the fluid extracted for power production or magmatic activity. Pairing the soil CO2 emission with stable isotopes of the efflux and calcite samples has important implications for both volcano monitoring and geothermal exploration, as it can help us to track magmatic fluid upflows and the associated thermal energy.
Three-dimensional simulations of future GLOF events in High Mountain Asia under different SSP scenarios
Authors: Furian Wilhelm , Sauter Tobias , Schneider Christoph
Published: March 2024

In High Mountain Asia (HMA), rising temperatures and retreating glaciers are leading to the formation of new glacial lakes and the expansion of existing ones. The sudden release of water from such lakes can lead to devastating glacial lake outburst floods (GLOF) threatening people and infrastructure for many kilometers downstream. Therefore, it is important to obtain information on future glacial lakes, e.g., their location, area, and volume as well as the timing of their development. This data can in turn be used to estimate the range and destructive potential of future GLOF events, which is crucial for the sustainable development of settlements and infrastructures.Dam failures at glacial lakes and the subsequent flooding events are often investigated using two-dimensional models (e.g. HEC-RAS). These 2D models are based on the solution of the shallow water equations, which assume that the vertical velocity of the water is always much lower than the horizontal velocity. In case of a moraine failure, however, high vertical accelerations are observed in the behavior of the dam break wave in mountainous terrain, which violates the shallow water equations. To overcome these shortcomings of 2D models, fully three-dimensional Computational Fluid Dynamic (CFD) models can be used, which are based on the solution of the Navier-Stokes equations along with the volume of fluid method to locate the interface between water and air.In our research project, we use the 3D open-source CFD model OpenFOAM to determine the possible range of GLOF events at future glacial lakes in HMA. To capture the different climate pathways and the corresponding differences in lake volume, we use previously published data on the evolution of future glacial lakes over the course of the 21st century under different SSP scenarios. To account for the uncertainties of future moraine height or composition, we simulate different moraine failure scenarios resulting in different magnitudes of GLOFs. These simulations allow us to determine the velocity of the initial break wave and identify potential inundation areas. By intersecting the resulting flood map with land-use and land-cover maps (while taking into consideration the potential changes in this data during the coming decades), we can estimate affected agricultural land and potentially damaged infrastructures. Our findings can contribute to helping local communities adapt to emerging challenges, implement risk minimization measures, and enhance sustainable development in HMA.
Combining ERT and an orthophoto time series to investigate thaw-related landslides in the Canadian Arctic
Authors: Eppinger Saskia , Heidler Konrad , Lantuit Hugues , Krautblatter Michael
Published: March 2024

Retrogressive thaw slumps (RTS) are a common permafrost related landslide type in the Arctic and provide a large amount of material to coastal nearshore zone, lakes and rivers. RTS are characterized by highly dynamic changes and rapid internal processes. Along the Canadian coastline there is an increasing number of RTS documented over the last century, acting sensitive to a warming climate.The occurrence and behaviour of these landslides is strongly dependent on the presence of ground ice, including their likelihood for polycyclicity and reactivation. To detect and evaluate the ground ice content in different activity- and stabilization stages we used electrical resistivity tomography (ERT) on several RTS on Herschel Island in the Canadian Beaufort Sea. We combined ERT profiles remeasured 10 years apart, with orthophotos since 1952 to gain a detailed insight in their long-term behaviour, the availability of ground ice and the factors controlling polycyclicity.This study demonstrates the capacity of ERT for detecting massive ice bodies and internal changes. Combining this with a time component and orthophoto analysis, provides a unique insight into the behaviour of retrogressive thaw slumps, but also shows the need to use complimentary techniques to correctly interpret geophysical measurements.
Understanding the atmospheric kinetic energy spectrum
Authors: Kouhen Salah , Storer Benjamin , Aluie Hussein , Marshall David , Christensen Hannah
Published: March 2024

The Kinetic Energy spectrum of the atmosphere in the mesoscales (10-500 km) is poorly understood. Aircraft measurements in the eighties first revealed that there was a kink in the spectrum, a transition from a slope of -3 to a slope of -5/3, that occurred at scales below around 400 km (Nastrom et al. [1984]). Since that time many possible mechanisms have been posited for the transition but there has been no consensus. We will present a new way of analysing the local scaling laws of geophysical data using coarse-graining, extending the work of Sadek and Aluie [2018]. Our technique allows for the creation of spatial maps of spectral slope, as well as conditioned spectra that can be used to analyse the relationship between different meteorological variables and the atmospheric kinetic energy power spectrum. This enables us to explore causes for the observed shallower slope. We observe shallower spectral slopes in regions of greater convective activity, as well as shallowing in regions of high orographic variability and interesting latitudinal effects. The important implications of our work for the celebrated Nastrom and Gage spectrum (Nastrom et al. [1984]) will be discussed. References: GD Nastrom, KS Gage, and WH Jasperson. Kinetic energy spectrum of large-and mesoscale atmospheric processes. Nature, 310(5972):36–38, 1984. Mahmoud Sadek and Hussein Aluie. Extracting the spectrum of a flow by spatial filtering. Physical Review Fluids, 3(12):124610, 2018.
Tropospheric NO2 in China during the COVID-19 lock-down is largely decreased due to the controlled human mobility
Authors: Zhang Yuxiang
Published: March 2024

Tropospheric NO2, one of the major atmospheric pollutants, is harmful to human health and plays an important role in atmospheric chemistry. Tropospheric NO2 concentration is controlled by anthropogenic emission and meteorological conditions, such as solar radiation and humidity. In early 2020, unprecedented lockdowns and travel bans were implemented in China to fight COVID-19, leading to a large decrease of NO2 compared with preceding years. To isolate the effects of anthropogenic emission and weather, we applied a linear regression model between satellite observed NO2 column density and meteorological variables. Compared with 2017, it is found that atmospheric NO2 in 2020 changed -37.8 ± 16.3 %, with the contribution of weather +8.1 ± 14.2 % and anthropogenic emission -49.3 ± 23.5 %. Similar results were also found in 2018 and 2019, revealing that the effect of reduced emission on atmospheric NO2 is counteracted by the weather, and is actually larger than the observation. The simulations by GEOS-Chem model also supported the results in typical regions. The reduction of NO2 induced by anthropogenic emission can be well explained by human mobility, showing significantly negative correlations to migration indices provided by Baidu Location-Based-Service, particularly that inside the city. The intra-city migration index can explain 40.4 ± 17.7 % variance of the emission-induced reduction of NO2 in 29 megacities, each of which has a population of over 8 million in China.
Comparison of C-band radar and infrared thermal data for monitoring corn field in semi-arid area.
Authors: Elallaoui Abdelhafid , Frison Pierre-Louis , Khabba Saïd , Jarlan Lionel
Published: March 2024

In semi-arid Mediterranean regions, the scarcity and limitations of water resources pose major challenges. These invaluable resources are threatened by various factors such as climate change, population growth, urban expansion, and agricultural intensification. Specifically, agriculture, which consumes approximately 85% of the water in the semi-arid zone of the South Mediterranean region, directly contributes to the depletion of groundwater. To promote rational irrigation management, it becomes imperative to monitor the water status of crops. Remote sensing is a valuable technique allowing for monitoring crop fields in different parts of the electromagnetic spectrum giving complementary information about crop parameters. The main objective of this study is to assess the potential of radar and Infrared Thermal data for monitoring the water status of crops in semi-arid regions. In this context, a radar system was installed in Morocco, in the Chichaoua region, consisting of 6 C-band antennas mounted on a 20-meter tower. These antennas are directed towards a maize field. This system allowed for radar data acquisition in three different polarizations (VV, VH, HH) with a 15-minute time-step over the time period extending from September to December 2021. Additionally, the system is complemented by continuous acquisitions from a Thermal Infrared Radiometer (IRT) at 30-minute intervals. These data are further supplemented by in-situ measurements characterizing crop parameters (state of the cover, soil moisture, evapotranspiration and meteorological variables). The study initially focused on analyzing the diurnal cycle of radar temporal coherence. The results indicated that coherence was highly sensitive to wind-induced movements of scatterers, with minimal coherence when wind speed was highest in the late afternoon. Moreover, coherence was also responsive to vegetation activity, particularly its water content, as the morning coherence drop coincided with the onset of plant activity. Subsequently, the study examined the potential of the relative difference between surface vegetation temperature and air temperature to monitor the water status of crops. The results showed that during a period of imposed water stress, the amplitude of this difference increased. These results open perspectives for monitoring the water status of crops using radar and thermal observations with a high revisit frequency.