bluuebunny/crossref_metadata_2025 huggingface dataset:
A comprehensive analysis of land use and climate change impacts on water quality in Italian river basins
Authors: Rufo Olinda Jack Mariano , Casagrande Samuele , Pham Vuong , Critto Andrea
Published: March 2024

The degradation of water quality, pivotal for sustainable development, is exacerbated by the interconnected impacts of climate change (CC) and land-use/land-cover change (LULCC). Rapid global development has amplified these effects, disrupting key processes that regulate river flows and runoff. LULCC, particularly in agriculture, plays a central role in nutrient cycle and runoff to the water bodies, thus affecting the water quality and ecosystem resilience. Concurrently, climate change intensifies algal blooms, reduces dissolved oxygen, and alters aquatic ecosystems. Shifts in precipitation and rising temperatures amplify pollutant transport and compromise water quality. Moreover, the complex interactions among LULCC and CC have significant impacts on nutrients, pollution concentrations, and sedimentation rates in freshwater ecosystems. This research focuses on the analysis of the dynamics and impacts of LULCC and climate-induced changes on the state of water quality at the river basin scale in Italy, supporting the achievement of good chemical and ecological status of the Water Framework Directive. First, this study aims to analyse LULCC pattern changes across various spatial scales with the use of geoinformation system (GIS) techniques to identify sensitivity and changes at the pixel level within different land use types. This analysis allows the identification of linkages and dependencies between LULCC indicators and their relationships with water quality parameters in each river basin of Italy. Second, to address the compound effects of climate change, this study examines historical patterns of climate change indicators and their correlation with water quality over time. It also investigates the temporal and spatial occurrence of extreme events, which are linked to changes in nutrient and pollutant levels. The final phase of the methodology involves the development of a machine-learning model aiming at understanding and predicting the complex interplay of multiple risk factors such as the combined effects of land-use change, climate variability, and other anthropogenic influences on water quality. By using machine learning techniques, the study will be able to identify intricate patterns and non-linear relationships between multiple risk factors and their collective influence on water quality dynamics. The results will provide a comprehensive understanding required for adaptive measures and decision-making support in Italy.
Dynamical downscaling of CMIP6 scenarios with ENEA-REG: an impact oriented application for the MED-CORDEX region
Authors: Calmanti Sandro , Anav Alessandro , Antonelli Marta , Carillo Adriana , Catalano Franco , Dell'Aquila Alessandro , Iacono Roberto , Marullo Salvatore , Napolitano Ernesto , Palma Massimiliano , Pisacane Giovanna , Sannino Gianmaria , Struglia Maria Vittoria
Published: March 2024

In the framework of the coordinated regional modeling initiative Med-CORDEX (Coordinated Regional Climate Downscaling Experiment), we present an updated version of the regional Earth System Model ENEA-REG designed to downscale, over the Mediterranean basin, the models used in the Coupled Model Intercomparison Project (CMIP6). The regional ESM includes coupled atmosphere (WRF), ocean (MITgcm), land (Noah-MP, embedded within WRF), and river (HD) components with spatial resolution of 12 km for the atmosphere, 1/12° for the ocean and 0.5° for the river rooting model.For the present climate, we performed a hindcast (i.e. reanalysis-driven) and a historical simulation (GCM-driven) over the 1980-2014 temporal period. The evaluation shows that the regional ESM reliably reproduces the mean state, spatial and temporal variability of the relevant atmospheric and ocean variables.In addition, we analyze the future evolution (2015-2100) of the Euro-Mediterranean climate under three different scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), focusing on several relevant essential climate variables and climate indicators for impacts. Among others, results highlight how, for the scenarios SSP2-4.5 and SSP5-8.5, the intensity, frequency and duration of marine heat waves continue to increase until the end of the century and anomalies of up to 2°C, which are considered extreme at the beginning of this century, will become the new normal condition of the Mediterranean Sea in less than a hundred years under the SSP5-8.5 scenario.Overall, our results demonstrate the improvement due to the high-resolution air-sea coupling for the representation of high impact events, such as marine heat waves, and sea-level height.
Interpretable Machine Learning to Uncover Key Compound Drivers of Hydrological Droughts
Authors: Blougouras Georgios , Reichstein Markus , Migliavacca Mirco , Brenning Alexander , Jiang Shijie
Published: March 2024

Hydrological drought (negative streamflow anomalies) can have significant societal and ecosystem impacts, and understanding its drivers is crucial for interpreting past and present droughts, as well as assessing future drought risk. However, despite recent research advancements, a comprehensive multivariate perspective on the drivers of hydrological drought remains elusive, particularly in the context of global warming, where distributional changes in drivers could result in an increased frequency of complex, compound events. In order to address this, quantifying the contribution of each driver is necessary. In our research, we devise an interpretable machine learning framework that can explain which hydrometeorological variables contribute to streamflow predictions. This is done by encoding a conceptual hydrological model into a neural network architecture, creating a physics-encoded hybrid model that allows us to maintain physical consistency and ensure a more causal understanding. We apply our framework to numerous North American basins across spatiotemporal scales and quantify the contribution of each potential driver to identified streamflow deficit events. We also investigate the mechanisms associated with compound drivers and assess if drought drivers are becoming increasingly complex due to climate change based on the defined compoundness index.  Overall, our framework has managed to capture the contribution of diverse drought drivers to events across different hydroclimatological regimes. The results demonstrate the effectiveness of our novel method in improving hydrological drought process understanding, especially the mechanisms and severity of droughts associated with compound drivers, thereby facilitating increased preparedness for future drought risks.
Long-term effects of biochar application on soil quality and yields under field conditions in Switzerland
Authors: Schlichenmaier Samuel , Steffens Markus
Published: March 2024

The use of biochar in agricultural soils is currently being researched worldwide. Previous research results suggest that biochar has a positive effect on soil quality, in particular through improved soil structure, water holding capacity and nutrient sorption, as well as the potential for carbon sequestration. In order to evaluate the benefits and risks of the application, biochar needs to be tested under field conditions for long-term effects within different climate zones and soil types. Here we present first results from a long-term field experiment in Switzerland, in which we comprehensively and continuously evaluate the effects of biochar application on soil quality and crop yield.
The trial consists of five agricultural fields in Zürich, Switzerland, with a total area of 10.5 ha. Soil type is mostly clayey loam and fields are managed according to organic guidelines and with reduced tillage management. We applied biochar once in spring 2021 according to 8 t/ha on half of the area according to a split-plot design. All fields are monitored continuously until at least 2027 for soil carbon (total, carbonate and pyrogenic), total soil nitrogen, pH, cation exchange capacity, aggregate stability, water holding capacity and yields. In addition, water content and penetration resistance are measured during the vegetation period. First results indicate a positive effect of biochar application on soil organic and pyrogenic carbon, however no effects on the other measured parameters. Therefore, under the given soil and climatic conditions in temperate soils biochar application may be valid to increase long-term organic carbon contents and carbon sequestration. Other propagated effects of biochar application like improved water holding capacity, cation exchange capacity and yields require higher biochar application rates to be significantly affected.
Imaging Fracture Networks beneath the Los Angeles Metropolitan Area using High-Frequency Seismic Attenuation Tomography
Authors: Nardoni Chiara , Persaud Patricia
Published: March 2024

In the northern Los Angeles area, the interaction of complex tectonics and sedimentary structures has a significant influence on the attenuation characteristics of the crust. The region is also characterized by partially fluid-saturated crust and seismic sequences that promote intense fracturing. Modelling high-frequency seismic attenuation to image fine-scale crustal features and gain insight into the driving mechanisms of the seismicity is a powerful tool for seismic hazard assessment across this densely populated area.We develop the first high-resolution 3D seismic attenuation model across the Chino and San Bernardino basins using 5,300 three-component seismograms from local earthquakes (M
Considerable impacts of meteorological field choices on tropospheric ozone simulations by a global chemistry transport model
Authors: Qu Kun , Daskalakis Nikos , Kanakidou Maria , Vrekoussis Mihalis
Published: March 2024

The meteorological field serves as a vital input for chemical transport models (CTMs) to simulate tropospheric ozone pollution. For global CTMs, it is often directly provided by reanalysis meteorology datasets. Different choices of meteorological fields are likely to yield varied ozone levels and contributions of ozone-related processes, e.g., transport, chemical production/loss and dry deposition, to the variations of ozone pollution. However, relevant comparisons are seldom reported. Here we investigate the impact of meteorological field choices on the results of tropospheric ozone simulations performed by the TM4-ECPL global model. Two generations of meteorological reanalysis products from the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA-Interim and ERA5, are selected as input meteorological fields to drive the model for this comparative study. Results show that when driven by ERA5 meteorology, the model generates considerably higher mean mixing ratios of tropospheric ozone for the period of 2013-2017 compared to ERA-Interim-based results. This outcome is particularly pronounced in the high-latitude areas of both hemispheres and near the surface (by 5-10 ppbV). The model results by using both meteorological fields are validated against air quality monitoring data from over 10,000 sites and ozonesonde measurements globally. When using ERA5, the overestimation of near-ground Ox (ozone + NO2) levels by the model becomes more notable than using ERA-Interim (increases from 6% to 25%). However, the underestimation of ozone levels in the middle and high troposphere is reduced. Both simulations can well reproduce the annual trends of near-surface ozone pollution, indicating a more important role of ozone precursor emissions in driving ozone changes. Furthermore, through sensitivity simulations and budget analysis, we delve into the reasons behind the considerably higher ozone levels in the ERA5-driven simulation. 
Impact of hydrogen on atmospheric composition and climate
Authors: Chakraborty Tanusri , Thornhill Gill , Collins Bill
Published: March 2024

Hydrogen(H2) is one of the most abundant greenhouse gases in the atmosphere that participates in stratospheric ozone depletion and influences air quality. Using hydrogen as an alternative energy source to meet net-zero carbon emissions by 2050 can increase the risk of Hydrogen Leakage. Excess H2 leaked from a hydrogen economy could travel from the Earth’s surface to the stratosphere, where its oxidation would increase water vapor (H2O) in the upper atmosphere. It also has the potential to modify stratospheric ozone destruction by altering catalytic reactions involving HOx (=OH+HO2) radicals as well as changing stratospheric temperatures. Additional H2 in the air would consume the hydroxyl radical (OH) and lengthen the atmospheric lifetime of methane (CH4), increasing its abundance, whilst the oxidation of both H2 and CH4 generates tropospheric O3. The changes in OH can cause a cascade of climate impacts that includes changes in aerosol clouds. Increases in H2 will increase the concentration of CH4, O3, and H20, resulting in increased radiative forcing. Here, we are using the UK Earth System Model (UKESM) chemistry-climate model to see the effect of indirect radiative forcing arising from increases in H2 in the atmosphere. We have conducted experiments at present and future H2 and CH4 concentrations and analyzed the feedback on O3, aerosol, and stratospheric H2O over the period of 40 years. The highlight of the study is to see the effects of radiative forcing on CH4, O3, and H2o separately . We have seen the effect on one component at a time by switching off the feedback of the other components and also see the effect of radiative forcing as a whole due to an increase in H2 concentration.
A web portal dedicated to climate change impact studies in the Global South: ClimatSuds.ird.fr
Authors: Tramblay Yves , Sultan Benjamin , Amoussou Ernest , Arias Paola A. , Bodian Ansoumana , Fita Borrell Lluís , Brouillet Audrey , Condom Thomas , Dezetter Alain , Diedhou Arona , Driouech Fatima , Hanich Lahoucine , Junquas Clémentine , Roux Emmanuel , Sané Youssouph , Scarcelli Nora , Ngo-Duc Thanh
Published: March 2024

The recent sixth IPCC report highlighted the lack of studies on the impacts of climate change in the Global South. While paradoxically these countries have the weakest resilience capacity to adapt to these forthcoming changes. In this context, a co-construction workshop was organized in 2022 to define the multi-sectoral needs of different academic or institutional actors working on the impacts of climate change. Bridging together meteorological and hydrological agencies, universities, research centers, and private companies from Africa, Europe, South Asia, and South America, this workshop allowed defining the types of data and their modalities of access, that are the most adapted to conduct impact studies of climate change in different domains. The main difficulties in accessing climate data identified for researchers working on climate change impacts were related to the lack of technical capability to retrieve and process the worldwide databases of climate models data and also the need for expertise to exploit this wealth of data efficiently. Following this workshop, a climate services platform was implemented in 2023 (https://climatsuds.ird.fr/) to access a large dataset of bias-corrected CMIP6 climate models simulations, as well as a set of climate indices relevant for impacts assessment (heavy rains, extreme heat..) and impact models outputs (ISIMIP2a) in different sectors (water, vegetation, agriculture, and health). The web platform enables data extraction by point, by country, or by free polygons, visualization in graphic formats, and export to NetCDF or CSV files. Besides data access functionalities, the web portal will gradually integrate different training resources for the users and new datasets according to their needs. 
Insights from the European Drought Risk Atlas
Authors: Rossi Lauro , Wens Marthe , De Moel Hans , Cotti Davide , Sabino Siemons Anne-Sophie , Hagenlocher Michael , Van Loon Anne , Maetens Willem , Masante Dario , Toreti Andrea , Naumann Gustavo , Rudari Roberto , Meroni Michele , Avanzi Francesco , Ghizzoni Tatiana , Barbosa Paulo
Published: March 2024

In the past decades, and notably the last few years, droughts have severely impacted various interconnected socio-economic sectors and ecosystems across the EU. These impacts encompass, among others, extensive losses in both rain-fed and irrigated agriculture, challenges and constraints in public water supply, disruptions in inland shipping, diminished production of hydropower and thermoelectric energy, impaired functioning of terrestrial and freshwater ecosystems, and implications for the tourism industry. In order to better prepare for future drought events in Europe, knowledge on the drivers, spatial patterns and dynamics of drought risks is urgently needed. The European Drought Risk Atlas responds to that need by mapping hotspots and risk drivers across diverse systems and regions within the EU. Combining conceptual risk models (impact chains) and a data-driven quantitative drought risk assessment based on machine learning, this Atlas represents a significant stride toward impact-driven drought risk analysis in present and projected global warming levels (+1.5°C, +2.0°C, +3.0°C). It provides a detailed and disaggregated perspective on the risks posed by droughts to societies and ecosystems, with a particular focus on agriculture, public water supply, energy, river transportation, freshwater, and terrestrial ecosystems.The data-driven analysis reveals that current levels of drought risk in the EU are already notable, with average annual losses presenting economic and environmental threats in nearly all regions. As expected, the Mediterranean region, particularly the Iberian Peninsula, faces high drought risk under both current and projected climate conditions, driven by the escalating dry conditions associated with global warming. However, while drought risk of certain sectors in Europe follows a north-south gradient of overall mean drying (south) and wetting (north) under climate change, the analysis underscores that each sector reacts distinctly to current and projected hazard conditions, exhibiting sector-specific sensitivity. Eastern and Western Europe may experience complex dynamics due to the interplay between drying and wetting patterns and precipitation variability, resulting in different risk conditions depending on the considered sector. While the analysis may still be refined as new data (observations and future climate simulations) become available, this Atlas represents a unique tool of unparalleled value that can shape future EU preparedness and adaptation policies.
Aerial Assessment of Methane Emissions from Canadian Landfills
Authors: Ghasemi Donya , Fougère Chelsea , Khaleghi Afshan , Stuart Jordan , Martino Rebecca , Bourlon Evelise , Risk David
Published: March 2024

Canada is committed to reducing methane emissions by 50% below 2020 levels by 2030 in alignment with the Global Methane Pledge. The waste sector accounts for 23% of Canada’s methane emissions, and accurate estimations of current emissions from landfill sites are needed to guide mitigation efforts. In 2022, we conducted a cross-Canada aircraft-based methane measurement campaign in collaboration with Environment and Climate Change Canada (ECCC) and the UNEP’s International Methane Emission Observatory (IMEO). We used a Twin Otter equipped with high-speed gas analyzers and meteorological measurement sensors, which was flown in ascending loops, downwind transects, or both in combination, at 27 active and inactive municipal solid waste landfills in Ontario and Québec, Canada. Mass balance flux estimates were generated using the Top-Down Emission Rate Retrieval Algorithm. Additional mass balance measurements were made by Scientific Aviation using a similar approach based on Gauss’s theorem. A Gaussian dispersion model was used at other sites where conditions were unsuitable for mass balance. We were also able to compare some results to an independent truck-based measurement campaign of the same sites. Most mass balance measurements fell within a factor of ~3 with Greenhouse Gas Reporting Program data submitted by industry operators, showing reasonable correspondence within expected variability to atmospheric pressure changes and other weather variables.The research indicated that aircraft estimates were consistently higher than those derived from trucks. This implies a possible underestimation in truck measurements, particularly during sunny, low-wind conditions when the thermal lift of landfill CH4 plumes is notable. On the other hand, Gaussian dispersion model estimates were higher and more variable than mass balance-based methane emission rate estimates. We also compared our mass balance estimates to a First Order Decay landfill model used by the Environment and Climate Change Canada Waste Reduction for planning purposes, and we found that the model often overestimated emissions. These measurement-based estimates contribute to a refined understanding of methane emissions from Canadian landfills and provide valuable data for regulatory planning purposes.
Globally resolved marine carbon isotope data spanning the last 25ka: what do they tell us about the drivers of atmospheric radiocarbon and CO2 on millennial and deglacial timescales? 
Authors: Skinner Luke
Published: March 2024

Be10 in ice cores provides a uniquely well resolved indication of past radionuclide production rates, with a direct bearing on past radiocarbon production.  In the absence of past carbon cycle perturbations (e.g. involving ocean-atmosphere carbon exchange), Be10-based radiocarbon production rate anomalies should correlate directly with atmospheric radiocarbon anomalies, as confirmed by models.  Over the past ~30ka, Be10-inferred radiocarbon production rates and atmospheric radiocarbon (i.e. Intcal20) both exhibit recurrent millennial anomalies, typically of ~5ka duration.  A correlation between these anomalies breaks down during the deglaciation.  This is intriguing and suggests a mix of millennial carbon cycle and radionuclide production influences. Here, global compilations of marine carbon isotope data (radiocarbon and 𝛿13C) are used to assess the potential contribution of ocean circulation and air-sea gas exchange to the apparent millennial component of variability in Intcal20, and atmospheric CO2. We find that existing marine 𝛿13C data provide strong support for a marine influence on atmospheric radiocarbon. Support from marine radiocarbon data is more complex, due to the influence of ‘attenuation biases’ (arising from radiocarbon production changes), and due to a distinct regionalism in the ocean’s impact on atmospheric radiocarbon, versus atmospheric CO2, with air-sea gas-exchange playing a significant role. Major differences in the long-term evolution of radiocarbon and 𝛿13C across the last deglaciation further point to distinct and independent controls on these isotopes systems, providing clues as to the nature and timing of different carbon cycle processes during deglaciation.
The Imprint of Sea Ice Cover on the Biological Carbon Pump in the Southern Ocean
Authors: Holtappels Moritz , Baloza Marwa
Published: March 2024

The Seasonal Ice Zone (SIZ) around Antarctica covers an area of 16 Mio km2 and is considered the largest biogeochemical province in the Southern Ocean. Despite a well-documented control of sea ice on primary production, its large-scale effect on the biological carbon pump, i.e. the sinking of organic carbon into deep waters and ultimately to the sediments, remains poorly constrained. Here we demonstrate that the degree of sea ice cover during the growth season is a strong predictor for carbon remineralization rates in underlying sediments. We compiled the available benthic rate measurements for the SIZ and found that more than 80% of the variability can be explained by only two environmental factors: long-term occurrence of moderate sea ice cover in the summer season, and water depth. The empirical model was used to map the benthic carbon remineralization for the entire SIZ, showing elevated rates especially at the Antarctic Peninsula and the Amundsen Sea in West Antarctica, and the D’Urville Sea, Davis Sea and Prydz Bay in East Antarctica. Altogether, benthic remineralization in the entire SIZ summed up to 46 Tg C per year, of which 71% can be assigned to shelf sediments. Applying an empirical function for the burial rate, the total organic carbon supply to the sediments was estimated to be 52 Tg C per year and the carbon export from the euphotic zone (
The need for realistic experimental setups in controlled environments: insights from a two-year ecotron experiment on earthworms’ impact on ecosystem H2O, CO2 and N2O dynamics
Authors: Sauze Joana , Forey Oswaldo , Piel Clément , Gritti Emmanuel S. , Devidal Sébastien , Faez Abdelaziz , Ravel Olivier , Capowiez Yvan , Landais Damien , Roy Jacques , Milcu Alexandru
Published: March 2024

Recent studies have highlighted the potential role of earthworms in modulating soil greenhouse gas (GHG) emissions, yet the complexity of natural ecosystems and the lack of high-resolution temporal data have limited our understanding. To bridge this gap, a two-year experiment was undertaken in a controlled ecotron setting, utilizing large-scale lysimeters (5 square meters in area and 1.5 meters in soil depth) in the Macrocosms experimental platform of the Montpellier European Ecotron (CNRS). This study aimed to provide an understanding of the impact of earthworms (specifically endogeic and anecic ecotypes) on water and greenhouse gas emissions in a realistically simulated agricultural ecosystem undergoing a three-crop rotation.We employed continuous, high-frequency monitoring to measure ecosystem-level exchanges of CO2, N2O, and H2O. While temporary increases in CO2 fluxes were noted in earthworm-inhabited replicates, the cumulative data over the entire study period did not demonstrate a significant increase in CO2 emissions. Interestingly, the presence of endogeic earthworms was correlated with a notable reduction in N2O emissions during wheat cultivation (by 44.6%), although this effect did not persist throughout the entire experimental timeline. Additionally, while earthworms had an impact on water infiltration along the soil profile, no consistent patterns were observed in terms of ecosystem evapotranspiration or water use efficiency (WUE) changes attributable to earthworm activity.Our findings provide critical insights into the role of earthworms in terrestrial GHG dynamics, particularly in agricultural settings. Contrary to prevailing assumptions, this study suggests that earthworm activity does not lead to a significant increase in greenhouse gas emissions over a period of two years under conditions that closely emulate agricultural environments. These results underscore the importance of conducting long-term, high-resolution studies in realistically simulated ecosystems to better comprehend the intricate relationships between soil biota and greenhouse gas emissions.
Detecting Floating Macroplastic Litter with Semi-Supervised Deep Learning
Authors: Jia Tianlong , de Vries Rinze , Kapelan Zoran , Taormina Riccardo
Published: March 2024

Researchers are increasingly utilizing Deep Learning methods for computer vision to identify and quantify floating macroplastic litter. While these methods can provide precise assessments of plastic pollution by automatically processing images and videos, they often rely on the availability of large amount of annotated data for supervised learning (SL). Moreover, the manual labeling work is expensive and time-consuming. This hinders obtaining high model generalization capability, which is essential for the development of robust computer vision systems for structural monitoring.To overcome this challenge, we propose a two-stage semi-supervised learning (SSL) method for detecting floating macroplastic litter based on the SwAV (Swapping Assignments between multiple Views of the same image) approach. SwAV is a self-supervised learning method that extracts the feature representations of data (such as images with macroplastic litter) without manual annotations. In the first stage of the SSL method, we use SwAV to pre-train a ResNet50 (Residual Neural Network with 50 layers) backbone architecture on more than 100K unlabeled images. In the second stage, we add additional layers to ResNet50 to create a Faster R-CNN (Faster Region-based Convolutional Neural Network) architecture, and fine-tune it for object detection using a limited amount of labeled data (
Active Growth Pattern of Adjacent Thrust-sheets in the Indo-Myanmar Fold-Thrust Belt, Northeast India
Authors: Kshetrimayum Alexander Singh , Chang Chung-Pai , Goswami Pradeep K , Chang Wu-Lung
Published: March 2024

This study presents a comprehensive geomorphic investigation to delineate the growth patterns of the Nungba and Barak-Makru thrust sheets within the Indo-Myanmar fold-thrust belt in Northeast India. Employing well-established geomorphic indices, like Normalized Steepness Index (Ksn), Hypsometric Integral (HI), and Transverse Topographic Symmetry Factor (T), the study provides a nuanced understanding of recent tectonic activities as well as intricate growth dynamics of these thrust sheets. The Ksn and HI reveal distinct patterns of growth in the northern segments of both the Nungba thrust sheet (NTS) and Barak-Makru thrust sheet (BMTS), exhibiting more intense deformation compared to their southern parts; nevertheless, the NTS is experiencing more intense activity. Field observations, including patterns of stream incision and geomorphic anomalies such as fault scarps, drainage deflections, and disposition of strath terraces, corroborate these findings and provide a tangible context to the geomorphic data. Variations in stream incision patterns from north to south across the thrust sheets offer a lens into the spatial variation in growth patterns, suggesting a north-to-south decrease in tectonic uplift of the terrane.
Furthermore, the spatial distributions of T values elucidate differing mechanisms of down-tilting patterns in the thrust sheets, with NTS tilting northward and BMTS southward. This bidirectional tilting pattern is attributed to the variable uplift rates at the basal structural discontinuities of the thrust sheets, resulting from the differential strain accommodation, influenced by the ongoing collisional dynamics within the fold-thrust belt. This study underscores the importance of geomorphic investigations in understanding the complex and variable nature of tectonic processes within a growing orogen, highlighting that the adjacent thrust sheets exhibit distinct growth patterns even under similar principal stress regimes. The research not only provides vital insights into the active tectonic processes shaping the Indo-Myanmar fold-thrust belt but also illuminates the importance of integrating geomorphic and field investigations in understanding the ongoing orogenic dynamics.
Understanding Volcanic Margin Evolution through the Lens of Norway's Youngest Granite discovered by IODP Expedition 39
Authors: Gernigon Laurent , Knies Jochen , Schönenberger Jasmin , Piraquive Alejandro , van der Lelij Roelant , Huyskens Magdalena H. , Planke Sverre , Berndt Christian , Jones Morgan , Millett John M. , Mohn Geoffroy , Alvarez Zarikian Carlos A.
Published: March 2024

Three boreholes drilled during the International Ocean Discovery Program (IODP) Expedition 396 have yielded unexpected findings of altered granitic rocks covered by basalt flows, interbedded sediments, and glacial mud on the Kolga High situated near the continent-ocean transition on the mid-Norwegian margin.  To assess basin and basement structures near Kolga High in relation to the broader regional setting, a potential field forward modelling study was conducted. One specific goal was to evaluate the density distribution beneath the Kolga granite. The necessity of low-density crustal material beneath the Kolga High challenges the hypothesis of an old, thick, dense, and inherited basement high directly beneath the basalt, given the low gravity signal observed. In our potential field model, the rock density underneath the basalt remains relatively low (2.4 g.cm-3 in average). Based on onshore measurements, Caledonian or Precambrian ‘fresh’ granitoids and other inherited basement rocks typically exhibit bulk densities usually exceeding 2.65-2.75 g.cm-3. The gravity signal observed on Kolga High, along with the low-density necessary to fit it, suggests that the inherited basement should be situated at a considerably greater depth (~up to 10 km), which is approximately 5-7 km deeper than the drilled Kolga granite/basalt interface. To unravel the weathering chronology for this enigmatic granite, the K-Ar method was selected to date fine-grained clay minerals. X-ray diffraction was performed on different grain size fractions to identify both protolithic and authigenically formed K-bearing minerals derived from the IODP rock samples (Holes U1565A and U1566A). K-Ar geochronology was then performed on five grain size fractions (
Using a regionalized distributed hydrological modelling approach for prediction low flow on ungauged French territory based on the training of artificial neural network 
Authors: de Fournas Thomas , Folton Nathalie , Colleoni François , Pujol--Nicolas Killian
Published: March 2024

This study delves into the exploration of low-flow rivers, a crucial subject within the global river network. These rivers, characterized by reduced flows over significant periods, play an essential role in various ecosystems. They constitute a substantial portion of the global river network, spanning diverse regions, including arid, semi-arid, temperate, humid tropical, boreal, and alpine areas. The flow variations observed in these watercourses are influenced by multiple factors, including climate change and increased water withdrawals associated with human activities. Ungauged basins, where reliable flow data is not readily available, present a significant hurdle in hydrological modelling. The absence of direct measurements makes it difficult to understand and predict the flow dynamics of rivers and streams, particularly in regions with low flow watercourses. To overcome this challenge, the study leverages the SMASH platform (Spatially-distributed Modelling and ASsimilation for Hydrology), a versatile multi-model framework capable of handling the complexities associated with ungauged territories.The model implemented within the SMASH platform draws inspiration from the GR model family, a collection of global and semi-distributed models developed over the past years at INRAE. SMASH is a flexible, spatially distributed hydrological modelling platform capable of operating at high spatial and temporal resolution in both gauged and ungauged catchments. It is designed to simulate flow hydrographs across all grid cells in the computational domain.Additionally, it incorporates functionalities for parameter sensitivity analysis and methods for both uniform and spatially distributed parameter calibration with different objective functions.The principal aim of this study is to test the performance of various hydrological model structures, inspired by the GR model on the SMASH platform in low flow context. The evaluation centers on calibration and validation processes, employing uniform calibration techniques and regionalization approaches over a comprehensive dataset spanning 40 years at a daily time step. This extensive evaluation aims to elucidate the efficacy of these models in reproducing the low flows, seasonnality and bilan of watercourses over a set of basins (100) covering France with differents hydrometeorologic catchments. Furthermore, the study introduces a novel dimension by leveraging an artificial neural network (ANN) to process catchment descriptors specific to France. The ANN facilitates the exploration of regionalization by establishing a meaningful correspondence between select catchment descriptors and model parameters.The study will then conclude with a comprehensive comparison of all simulations, highlighting the best hydrological model structure and regionalisation.
Minimal Impact of Late-Season Melt Events on Greenland Ice Sheet Annual Motion
Authors: Ing Ryan , Nienow Peter , Sole Andrew , Tedstone Andrew , Mankoff Kenneth
Published: March 2024

Extreme melt and rainfall events can induce temporary acceleration of Greenland Ice Sheet motion, leading to increased advection of ice to lower elevations where melt rates are higher. In a warmer climate, these events are likely to become more frequent. In September 2022, unprecedented air temperatures caused multiple melt events over the Greenland Ice Sheet, generating the highest melt rates of the year. In this study we investigate the impact of these large late-season melt events on the ice dynamics of five land- and two marine-terminating outlet glaciers of the west Greenland Ice Sheet. The scale and timing of the largest event overwhelmed the subglacial drainage system, enhancing basal sliding and increasing ice velocities by up to ~240% relative to pre-event velocities. However, ice velocity returned rapidly to pre-event levels, and the speed-ups caused a regional increase in annual ice discharge of only ~2% compared to when the effects of the speed-ups on ice discharge were excluded. In contrast, the total annual runoff from the studied glaciers increased by 24%. Therefore, although late-season melt events are forecast to become more frequent and drive large amounts of runoff, their impact on net mass loss via ice discharge is minimal.
Vertical Mixing of Suspended Sediment in Big Rivers using ADCP data and Machine Learning
Authors: Tomsett Chris , Leyland Julian , Darby Steve , Gernon Tom , Parsons Dan , Hincks Thea , Wolstenholme Josh
Published: March 2024

Sediment is an intrinsic component of the fluvial network, supplying material for floodplains and coastal landforms which provide resilience during flooding and storms. As a result, an understanding of the fluvial processes that control how much sediment moves through our river systems, and how this varies across the globe, is of fundamental importance.For the purpose of estimating sediment delivery through the fluvial network, it is often assumed that rivers are well mixed through their vertical extent. However, empirical data reveals that there is frequently large variability in the concentration of sediment through the water column. Better understanding this variability is of interest to the geomorphological community to help explain variations in sediment transport and improve estimates of sediment flux.In this research, we utilise a collection of Acoustic Doppler Current Profiler (ADCP) data from large rivers across the globe to investigate variations in the vertical distribution of suspended sediment. Calibrations of ADCP backscatter to Suspended Sediment Concentration (SSC) from the wider literature are used, alongside median grainsize and acoustic frequency, to create a Machine Learning (ML) model from which SSC from uncalibrated ADCPs can be estimated. This new ML model is subsequently implemented to explore the variations in the vertical mixing of suspended sediment both temporally and spatially. This variability is explored to identify the importance of catchment characteristics in determining variations in suspended sediment concentration within the water column. Comparison of multiple river systems and their catchment characteristics, both between sites and through time, enables the identification of key attributes which exert a greater control on this variation through the water column. Subsequently, this leads to an improved understanding of sediment flux through the river system, whereby knowing the variation in sediment concentration within the water column can help to better calibrate current methods of estimating flux.
Radio Sounding of the Venusian Atmosphere and Ionosphere with EnVision
Authors: Tellmann Silvia , Oschlisniok Janusz , Pätzold Martin , Dumoulin Caroline , Rosenblatt Pascal
Published: March 2024

EnVision has been selected in the M5 call of ESA’s Cosmic Vision program as the next European led mission to Venus. It is dedicated to unravel some of the numerous open questions about Venus' past, current state and future and will help to understand why Venus and Earth evolved so differently.The Radio Science Experiment (RSE) on EnVision will perform extensive studies of the gravitational field but also Radio Occultations to sense the Venus atmosphere and ionosphere at a high vertical resolution of only a few hundred metres. These radio occultations provide electron density profiles in the ionosphere and atmospheric density, temperature and pressure profiles in the upper troposphere and mesosphere (~40 – 90 km). Additionally, they allow to study the H2SO4 absorption in the Venus cloud layer.The first radio occultation experiment at Venus was conducted during the Mariner 5 flyby in 1967, followed by Mariner 10, several Venera missions, Magellan, and the Pioneer Venus Orbiter, and Akatsuki. The most extensive radio occultation study of the Venus atmosphere so far was carried out by the VeRa experiment on Venus Express.EnVision will use two coherent frequencies (X- and Ka-band) to separate dispersive and nondispersive effects. This allows to distinguish between ionospheric wave structures and other noise induced effects in the ionosphere.The use of Ka-band, which has never been used to sense the Venus atmosphere before, allows to study the H2SO4 absorption in the Venus cloud layer due to its high sensitivity to sulfuric acid absorption. Ka-band is also sensitive to liquid H2SO4 which provides the opportunity (in combination with X-band) to distinguish between gaseous and liquid H2SO4 absorption features on Venus for the very first time.The short orbital period of EnVision in combination with its very small orbital inclination allows to cover all latitudes, longitudes, local times and solar zenith angles on Venus. Especially short-term variations caused by atmospheric waves can be identified to study traveling or stationary small scale atmospheric structures.
Urban 3D Change Detection with Deep Learning: Custom Data Augmentation Techniques
Authors: Contu Riccardo , Marsocci Valerio , Coletta Virginia , Ravanelli Roberta , Scardapane Simone
Published: March 2024

The ability to detect changes occurring on the Earth's surface is essential for comprehensively monitoring and understanding evolving landscapes and environments.To achieve a comprehensive understanding, it is imperative to employ methodologies capable of efficiently capturing and analyzing both two-dimensional (2D) and three-dimensional (3D) changes across various periods.Artificial Intelligence (AI)  stands out as a primary resource for investigating these alterations, and when combined with Remote sensing (RS) data, it has demonstrated superior performance compared to conventional Change Detection (CD) algorithms.The recent introduction of the MultiTask Bitemporal Images Transformer [1] (MTBIT) network has made it possible to simultaneously solve 2D and 3D CD tasks leveraging bi-temporal optical images.However, this network presents certain limitations that necessitate being considered. These constraints encompass a tendency to overfit the training distribution and challenges in inferring extreme values [1]. To address these shortcomings, this work introduces a series of custom augmentations, including strategies like Random Crop, Crop or Resize, Mix up, Gaussian Noise on the 3D CD maps, and Radiometric Transformation. Applied individually or in specific combinations, these augmentations aim to bolster MTBIT's ability to discern intricate geometries and subtle structures that are otherwise difficult to detect.Furthermore, the evaluation metrics used to assess MTBIT, such as Root Mean Squared Error (RMSE) and the change RMSE (cRMSE), have their limitations. As a response, the introduction of the true positive RMSE (tpRMSE) offers a more comprehensive evaluation, specifically focusing on MTBIT's efficacy in the 3D CD task by considering only the pixels affected by actual elevation changes.The implementation of custom augmentations particularly when applied in synergy, like Crop or Resize with Gaussian Noise on the 3D map, yielded substantial improvements. These interventions led – through the best augmentation configuration – to the reduction of the cRMSE to 5.88 meters and the tpRMSE to 5.34 meters, compared to the baseline (standard MTBIT) values of 6.33 meters and 5.60 meters, respectively.The proposed augmentations significantly bolster the practical usability and reliability of MTBIT in real-world applications, effectively addressing critical challenges within the realm of Remote Sensing CD. REFERENCES: [1] Marsocci, V., Coletta, V., Ravanelli, R., Scardapane, S., Crespi, M., 2023. Inferring 3D change detection from bitemporal optical images. ISPRS Journal of Photogrammetry and Remote Sensing, 196, 325-339
Using cloud chamber experiments and numerical simulations to investigate the complexities of cirrus cloud thinning effectiveness
Authors: Steinke Isabelle , Schorr Tobias , Leisner Thomas
Published: March 2024

In this study, we present a series of systematic AIDA cloud chamber experiments investigating the cloud microphysics governing cirrus cloud thinning effectiveness (i.e., the competition between heterogeneous and homogeneous ice nucleation) at temperatures below 230 K. Parcel model simulations based on our experimental studies show that the total ice crystal concentrations are very sensitive to the complex interplay between background aerosol, seeding and updraft velocities. We find regimes of successful cirrus thinning, as well as regimes resulting in thicker cirrus (overseeding). In addition, we also find that updraft fluctuations potentially play a critical role in influencing cirrus cloud thinning effectiveness.
Ground-based observation of a bright ELVE and the associated thunderstorm in high latitude inland region
Authors: Yang Jing , Qie Xiushu , Zhang Hongbo , Jiang Rubin , Sun Zhuling , Chen Zhixiong , Liu Mingyuan , Yuan Shanfeng , Liu Dongxia , Xu Chen
Published: March 2024

The upper atmosphere is dynamically perturbed by the underlying thunderstorms and lightning, and the optical phenomena known as transient luminous events (TLEs) are one of the manifestations.  Up to now, TLEs includes sprites, elves, blue jets, blue starters, gigantic jets and halos, etc.  Due to the very short duration, dim brightness and very large horizontal scale (hundreds of kilometers), elves are very hard to be captured by ground-based cameras.  An elve event is recorded for the first time over inland region in Asia Continent on the night of 20 September 2016.  The elve is unusual bright with its parent lightning located about 505 km away from the camera.  The elve occurred in the parent thunderstorm dissipating stage with low cloud tops and the thunderstorm is located completely in inland region with relatively dry, stable and low shear environment, not documented so far.  The elve parent stroke is vertically aligned located in small thunderstorm cell with weak reflectivity.  Sferic waveforms suggest that the magnetic field of the elve parent stroke is the maximum among all the strokes during the storm life cycle.  The impulse and total charge moment change of the parent stroke is 617 and 3577 C km, respectively.  In addition, the elves parent stroke sferics exhibit unique wave train feature not available both in the sprite parent stroke and other strokes that did not produce TLEs in the same thunderstorm.