bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining ROV-based acoustic data and underwater photogrammetry to characterize Hakon Mosby Mud Volcano (Barents Sea) cold seep systems
Authors: Fallati Luca , Panieri Giuliana , Argentino Claudio , Varzi Andrea Giulia , Bünz Stefan , Savini Alessandra
Published: March 2024

Cold-seeps have a unique geo-ecological significance in the deep-sea environment. They impact the variability of present-day submarine sedimentary environments, affecting the evolution of the landscape over time and creating a variety of submarine landforms, one of which is Mud Volcanoes (MVs). MVs form due to mud, fluids, and gas extrusion, mainly methane, from deeper sedimentary layers. These natural gas seepage systems could significantly affect climate change and the global carbon cycle. We present a comprehensive method that combines ROV-based multibeam mapping and underwater photogrammetry to enhance the understanding of the physical relationships between geomorphic units characterizing the Hakon Mosby Mud Volcano (HMMV) and the distribution of associated habitats.
HMMV is indeed characterized by high thermal and geochemical gradients from its centre to the margins, resulting in a clear zonation of chemosynthetic communities. Our approach integrates multi-resolutions and multi-sources data acquired using a work-class ROV. The ROV-based microbathymetry data helped to identify the different types of fine-scale submarine landforms in the central part of HMMV. This revealed three distinct geomorphic units, with the central hummocky region being the most complex. ROV images were analyzed using a defined structure from motion workflow to study this area further, producing millimetric resolution 2D and 3D models. Object-Based Image Analysis (OBIA), applied on orthomosaics, allowed us to obtain a fine classification of main benthic communities covering a total area of 940m2, including the active seepage area of the hummocky rim. Four major substrate types were identified in these regions: uncovered mud, bacterial mats high-density, bacterial mats low- density, sediments and tubeworms. Their relationship with terrain morphology and seepage activity were investigated at different spatial scales, contributing to a deeper understanding the ecological functioning of cold seep ecosystems in MVs.
The proposed workflow and innovative processing techniques could serve as a model for future studies on cold-seep systems. These investigations aim to clarify the extent to which geomorphic, biogeochemical, and ecological processes occurring in extreme environments are inherently linked and marked by the spatial patterns found in associated habitats and sedimentary environments. 
Detrital zircon dataset and it’s tectonic implications from the Qilian-Qaidam-Kunlun collage, northern Tibet
Authors: He Weidong , Dong Yunpeng , Sun Jiaopeng
Published: March 2024

In the past decades, detrital zircon geochronology has been most widely used in sediment provenance research and basin analysis. In our research, we present a brief introduction to the procedure, methods, and results of the collection and summarization of an updated detrital zircon U-Pb geochronology database for the Qilian-Qaidam-Kunlun collage in northern Tibet. A total of 620 samples with 59830 lines of raw data were compiled, including 70 samples with in-situ detrital zircon Lu-Hf isotopes. Samples from 7 different geologic sub-units are briefly categorized and primarily discussed to highlight characteristic age spans, probability density distributions, major peaks, and εHf(t) values for sediments with different depositional ages. Its detailed raw data will be periodically accessible in the Deep-Time Digital Earth repository. Traditional data processing and visualization techniques might readily ignore internal variations in possible source regions with the accumulation of detrital zircon age data. This study further synthesizes these metadata collections using the Kolmogorov-Smirnov (K-S) test and multidimensional scaling (MDS) statistical analysis. Combined with the detrital zircon age facies for discriminating and comparing multiple samples, we hope to provide new constraints on the provenance analyses, crustal evolution, tectonic history, and supercontinent reconstructions of the Qilian-Qaidam-Kunlun collage, the northern part of the Qinghai-Tibet Plateau.
Exploring the potential of the north-eastern Adriatic basin to host freshened groundwater using onshore-offshore 3D hydrogeological modelling.
Authors: Corradin Cristina , Thomas Ariel T. , Camerlenghi Angelo , Zini Luca , Giustiniani Michela , Busetti Martina , Foglia Laura , Bertoni Claudia , Micallef Aaron
Published: March 2024

Due to their long-term storage capacity, coastal aquifers are an important source of freshwater for industry, agriculture, and human consumption. However, these onshore groundwater aquifers are under enormous stress mostly due to the increase in usage. Thus, in the last decades, there has been a growing interest in alternative freshwater sources, such as offshore freshened groundwater (OFG). This study focuses on the Venetian Friulian Plain (north-eastern Italy) and the neighbouring northern Adriatic Sea and aims to quantify the potential extent and the genesis of the complex aquifer system hosted in the Mid-Late Quaternary siliciclastic sediments. The main objective is to provide an updated hydrogeological overview of the study area, showing the offshore (OFG) extent of the onshore aquifer system. The objective of this paper is achieved through the development of four three-dimensional models of the study area: 1) a deterministic model based on lithostratigraphic data using Leapfrog GEO; 2) a discrete stochastic geostatistical model based on lithostratigraphic data using Petrel 2017; 3) an aquifer geometry trend model unlinked to lithological data; 4) a model of sedimentary sequences associated with Plio-Quaternary sea level fluctuations (Cyclothems). The input for the geological models is a large regional dataset that includes borehole stratigraphies, screens depth, well logs and seismic reflection profiles. Our results demonstrate that the Quaternary glacio-eustatic fluctuations in the northern Adriatic basin are primarily responsible for the formation of the groundwater aquifer system in the study area.  The sediments hosting these waters are mainly composed of sandy coastal deposits, which are a relict of the northward and southward migration of the coastline in relation to marine sea level changes. Previous studies show that similar sedimentary systems extend in the entire northern Adriatic Basin. Our hydrogeological models confirm the offshore continuum of the onshore groundwater aquifers, and suggest that vast OFG resources are potentially widespread in the entire northern Adriatic basin.
Exploring Extreme Climate Transitions in Kerala, India: A Multi-Decadal Investigation (1980-2020)
Authors: G Mohan Meera , Geetha Raveendran Nair Arathy Nair , Sankaran Adarsh
Published: March 2024

In response to the escalating challenges posed by climate change, this study addresses the critical need to understand the dynamics of extreme climatic events within Kerala, India. Focusing on the years spanning 1980 to 2020, specifically during 12 identified drought years within, we meticulously examine transitions between droughts and floods, recognizing the profound impact on the region's hydrological landscape. With a strategic selection of 17 stream gauge locations covering high, mid, and low lands, representing varied climatic zones, our investigation delves into the intricacies of climatic shifts. The study deals with the analysis of discernible trend of increasing frequency in extreme events over time, by employing a thorough approach incorporating statistical significance testing, frequency analysis of extreme events, and lag analysis and then to unravel the intricate relationships between streamflow and precipitation during distinct phases such as pre-drought, drought, and post-drought years. The research findings illustrate an erratic pattern in the occurrence of contradictory extremes, such as transitions between drought and flood. The timing and duration of these transitions are also found to be inconsistent, showing varying periods in-between and occasionally consecutive occurrences of the same extremes, which in turn highlights the complexity and irregularity of extreme event patterns present in Kerala. Notably, our analysis reveals a concerning trend where the frequency of extreme events is progressively increasing, indicating a higher occurrence of climatic extremes over the years. Specifically, from 2015 to 2020, the observed transitions are striking, in the case that, the total incidences of heavy rain (64.5-115.5 mm per day) were 360 across 10 months in 2015 whereas in the succeeding year (2016), followed by an unprecedented 100-year return period drought. The year 2017 again saw incidences of heavy rain climbing to a total of 360 events. Astonishingly, the anomaly continued with the recurrence of devastating floods in 2018, which persisted for a broadened period up to 2020. While extending the future dynamics for the coming decade, the study predicted the frequency and patterns of extreme events in Kerala by incorporating future General Circulation Model (GCM) precipitation data. The results indicate a substantial increase in the frequency of extreme events, coupled with the anticipated emergence of prolonged dry periods in Kerala's future hydroclimatic landscape. The integration of this data into the analysis enabled the estimation of variations in future streamflow, providing valuable insights into the evolving climatic scenario. This forward-looking approach allowed for the inference of potential patterns of extreme events over the past decade in Kerala, contributing to proactive strategies for climate resilience and adaptive water resource management in the region.
Multiple plant root strategies improve phosphorus acquisition under elevated CO2 in the Amazon rainforest
Authors: Martins Nathielly ,   AmazonFACE team
Published: March 2024

The impact of elevated atmospheric CO2 concentrations on forest productivity depends on the capacity of plants to balance the additional CO2 with the demand for additional nutrients. One hypothesis states that plants may allocate the extra carbon belowground in producing and maintaining fine roots to alleviate nutrient limitation. In the Amazon basin, where approximately 60% of the forest is on old and weathered soil, the litter layer is an important nutrient source. In some regions, root mats growing in the litter layer can be observed, where the roots intercept the newly mineralized nutrients before they reach the soil and may bind to the mineral matrix. To improve their nutrient uptake capacity, trees can either modify their root morphology to a ‘do-it-yourself” strategy, increasing root length and branching intensity or alternatively, they can outsource the same function by investing in symbioses with mycorrhizal fungi. Additionally, fine roots can stimulate microbial decomposition of recalcitrant substrates (e.g., wood debris) by exuding low molecular weight organic compounds (LMWO) and increasing P mobilization by phosphatase activity without changing decomposition. These strategies could also vary depending on the growing depth of roots due to the different physical conditions between the organic upper and mineral layers. However, little is known about the role of trait differences in roots under higher CO2 concentrations.To increase our understanding of belowground responses of understory plants to elevated CO2 concentrations, we set up an Open-Top Chamber experiment in a lowland forest in the Central Amazon. We observed that under eCO2, root productivity did not change in the litter layer but showed a decreased pattern in the soil layer. Moreover, plants intensified root foraging in the litter layer by increasing their specific root length more than threefold under elevated CO2. In contrast, roots in the soil mineral layer followed an “outsourcing” strategy by increasing arbuscular mycorrhizal colonization by 117%. In addition, our results showed a decrease in the organic P in litter without a change in C decomposition under higher CO2 concentrations, suggesting a direct P mobilization.Our results suggest that plants may plastically adjust resource acquisition strategies to increase nutrient uptake efficiency and be able to directly affect P mobilization from the litter layer. We conclude that this ability of plants to adapt their P acquisition strategies in response to eCO2 by tackling different sources within the litter-soil continuum and maximizing nutrient acquisition represents an important mechanism to support the CO2 fertilization effect and might affect the resilience of the Amazonian rainforest to climate change, and thus global carbon balance.
Spatial structure, chemotaxis and quorum sensing shape bacterial biomass accumulation in complex porous media 
Authors: de Anna Pietro , Scheidweiler David , Bordoloi Ankur , Jiao Wenqiao , Sentchilo Vladimir , Bollani Monica , Chhun Audam , Engel Philipp
Published: March 2024

Biological tissues, sediments, or engineered systems are spatially structured media with a tortuous and porous structure that host the flow of fluids. Such complex environments can influence the spatial and temporal colonization patterns of bacteria by controlling the transport of individual bacterial cells, the availability of resources, and the distribution of chemical signals for communication. Yet, due to the multi-scale structure of these complex sys- tems, it is hard to assess how different biotic and abiotic properties work together to control the accumulation of bacterial biomass. Here, we explore how flow-mediated interactions allow the gut commensal Escherichia coli to colonize a porous structure that is composed of heterogenous dead-end pores (DEPs) and connecting percolating channels, i.e. transmitting pores (TPs), mimicking the structured surface of mammalian guts. We find that in presence of flow, gradients of the quorum sensing (QS) signaling molecule autoinducer- 2 (AI-2) promote E. coli chemotactic accumulation in the DEPs. In this crowded environment, the combination of growth and cell-to-cell collision favors the development of suspended bacterial aggregates. This results in hot-spots of resource consumption, which, upon resource limitation, triggers the mechanical evasion of biomass from nutrients and oxygen depleted DEPs. Our findings demonstrate that microscale medium structure and complex flow coupled with bacterial quorum sensing and chemotaxis control the het- erogenous accumulation of bacterial biomass in a spatially structured envir- onment, such as villi and crypts in the gut or in tortuous pores within soil and filters.
Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data 
Authors: Vanselow Steffen , Schneising Oliver , Buchwitz Michael , Bovensmann Heinrich , Boesch Hartmut , Burrows John P.
Published: March 2024

Methane (CH4) is an important anthropogenic greenhouse gas and its rising concentration in the atmosphere contributes significantly to global warming. A comparatively small number of highly emitting persistent methane sources is responsible for a large share of global methane emissions. Methane sources often show large uncertainties regarding their emissions or locations, especially at local scales, making their detection and quantification inevitable to support mitigating climate change.The TROPOspheric Monitoring Instrument (TROPOMI) onboard on the Sentinel-5 Precursor (S5P) satellite, launched in October 2017, provides measurements of the column-averaged dry-air mole fraction of atmospheric methane (XCH4) with a daily global coverage and a high spatial resolution of up to  km2, enabling the detection and quantification of localized methane sources.We developed a fully automated algorithm to detect regions with persistent methane enhancement and to quantify their emissions using a monthly XCH4 TROPOMI dataset from the years 2018-2021, generated with the WFM-DOAS retrieval algorithm, developed at the University of Bremen. The detection process comprises several steps, including an analysis of the monthly dataset, where we first characterize each region by several quantities, such as the number of months in which the region shows a methane enhancement, and then marking the regions that fulfill the defined persistence criteria. We detect more than 200 potential persistent source regions (PPSRs), which account for about 20 % of the total bottom-up emissions. By comparing the PPSRs in a spatial analysis with anthropogenic and natural emission databases we attribute one of the following source types to each detected region: coal, oil and gas, other anthropogenic sources (such as landfills or agriculture), wetlands, or unknown. Many of the detected regions are well-known methane source regions, like large oil and gas fields (e.g., Permian Basin in the USA, Galkynish and Dauletabad in Turkmenistan), coal mining areas (e.g., Bowen Basin in Australia, Upper Silesia Coal Basin in Poland), regions including large urban cities (Dhaka in Bangladesh, Mumbai in India, Rio de Janeiro in Brazil) or wetland areas (e.g., Pantanal in Brazil, Sudd in South Sudan).In this presentation, the algorithm and some results, including a global overview of the detected regions and a more detailed analysis for some of the regions, are presented.  
Low dissolved organic carbon flux in small mountainous catchments of Taiwan
Authors: Wang Pei-Ling , Cheng Ya-Fang , Tseng Jing-Yi , Lin Li-Hung
Published: March 2024

Stream dissolved organic carbon (DOC) is an important component of the global carbon cycle. The export ofDOC from land to the ocean is well quantified by examining large rivers, but this often excludes small mountainous rivers (SMRs), where DOC is primarily allochthonous and acts as a microbial energy source, shaping stream biogeochemical cycling. Revealing the temporal and spatial variation of DOC in SMRs is crucial for filling the missing piece of DOC export and understanding the role of DOC in stream ecology.Taiwan frequently experiences extreme weather events and earthquakes, thereby featuring deep river incisions, rapid uplift and erosion, and limited soil development. It represents an ideal model system for studying SMRs with high area-normalized material fluxes. Two catchments, the Gaoping and Beinan River systems, with high particulate organic carbon (POC) flux in Taiwan, were examined. The variation of DOCconcentrations was wider in the Gaoping River system (ranging from 0.07 to 8.85 mg/L with a mean of 0.66 mg/L) compared to the Beinan River system (ranging from 0.26 to 0.67 mg/L with a mean of 0.37 mg/L). However, the mean values in both systems are significantly lower than the global average. Despite a greater human impact in the lower reach of the Gaoping River as a result of the dense population, temporal variations were substantial at all sites, but the disparities between wet and dry seasons were notable at specific sites. Temperature appeared to be the primary factor controlling DOC concentrations during the non-typhoon period. During the typhoon event, the DOC concentrations were positively correlated with total suspended solids (TSS). By analyzing the temporal sequence, the variation in DOC concentration and TSS exhibited a clockwise hysteresis with the DOC max proceeding TSS max. This event contributed approximately 10% of the annual DOC flux in the catchment. Compared with the POC flux, the DOC flux derived from these two catchments is much lower, indicating a decoupling of transportation for particulate and dissolved materials and limited river metabolisms in SMR catchments.
Mare Tranquilitatis Hole - a habitable place for a first lunar settlement
Authors: Grandl Werner
Published: March 2024

Space stations on the lunar surface are exposed to cosmic rays, solar flares, micrometeorites and huge temperature variations. Therefore human outposts on the lunar surface have to be covered by huge layers of regolith. In 2009 the Japanese lunar orbiter SELENE (Selenological and Engineering Explorer) has detected three giant lunar holes: Mare Tranquilitatis Hole (MTH), Marius Hills Hole and Mare Ingenii Hole. The holes differ from normal impact craters and may be the entrances to underground lave tubes. The deepest one is MTH with 107 m and 98 x 84 m in diameter. According to Haruyama et al. the soil of lunar holes could contain water resources (protons from solar-wind hydrogen flux or even water molecules). Lunar holes reduce the effects of cosmic rays because of their limited field of view from the bottom. They provide also milder temperatures than the lunar surface. In the shadowed areas the temperature  ranges from -20°C to +30°C during the lunar day. These benefits make lunar holes become favourite locations to establish initial lunar stations. In a first step we propose to build an initial base on the lunar surface at the edge of MTH. It can be used for storage and as a "site hut" for astronauts to supervise the following work. In a second step the initial base is enlarged by a modular structure down to the bottom of MTH. Robotic and semi-robotic machinery is used to erect the modular structures. Lunar regolith is used for protection against cosmic rays and meteorites (ISRU In Situ Resource Utilization). Finally MTH could be  closed by a transparent dome and filled with air to create a "green" habitat for human settlers. 
Changes in soft bed subglacial hydrology associated with Climate Change
Authors: Hart Jane , Baurley Nathaniel , Martinez Kirk
Published: March 2024

Recent research on the subglacial hydrology beneath the soft bedded West Antarctic Ice streams has shown the presence of a braided subglacial hydrology. We have been able to investigate the seasonal changes associated with a soft-bedded braided system from a series of instrumented temperate glaciers, and show there is a continuum between a subglacial channelized and braided system.In particular, a braided subglacial river system can store summer meltwater, which is released during winter during positive degree days during winter (winter events) resulting in speed-ups. Here we show how recent increases in air temperature (and associated feedbacks such as proglacial lake growth), from a series of temperate soft-bedded glaciers, lead to potential changes in the subglacial hydrology and resultant glacier dynamics.
Towards imaging 3D crust and mantle structure by means of ocean tidal loading tomography
Authors: Dmitrovskii Andrei , Munch Federico , Boehm Christian , Martens Hilary , Khan Amir
Published: March 2024

Ocean tide loading (OTL) brings about recurring deformation of the Earth’s surface. Some of the OTL harmonics, e.g. M2, O1, Mf, cause sufficiently large surface displacement to be registered by the Global Navigation Satellite Systems (GNSS). These displacements are sensitive to the interior structure of the planet in a broad range of temporal and spatial scales making them a potentially unique source of information about the planet’s response at low frequencies. Comparison between observations and predictions for 1D elastic Earth models result in discrepancies of up to 3 mm (Bos et al., 2015, Martens et al., 2016). Spatial coherency of these discrepancies hints to 3D interior structure as one of the main sources of such residuals.In this context, we present a framework to invert OTL observations for 3D crustal and mantle structure based on a trust-region Newton-type iterative algorithm. Furthermore, we resort to the adjoint approach as an efficient means of computing the gradient for the high-dimensional model space. Focusing on the design of the inverse algorithm, we constrain ourselves to deformations of an isotropic elastic planet, which are governed by a self-adjoint forward operator. In order to assess the robustness of the method, we perform a suite of 3D synthetic inversions that mimic the distribution of the GNSS stations in South America. Preliminary results indicate enhanced sensitivities to the crustal and upper mantle density and elastic properties in the vicinity of the coastlines.
Dansgaard-Oeschger events - time series analysis and modelling across the hierarchy
Authors: Boers Niklas
Published: March 2024

The Dansgaard-Oeschger (DO) events are characteriszed by pronounced abrupt changes in climatic conditions in high northern latitudes. While they have first been discovered in Greenland ice core records, their imprints are global and can be deteced in proxy archives across the globe. They can be considered as the archetype of abrupt climate changes for which empirical evidence exists, but have not yet been fully explained. In this talk I will present some recent results from analyzing ice-core derived time series with a focus on dating uncertainties, from concentual models proposing unerling physical mechanisms, and from comparing spatial patterns of the impacts of the DO events on global atmospheric circulation patterns. 
The climate impact of a future hydrogen economy
Authors: Hauglustaine Didier
Published: March 2024

Inflammable air, known today as hydrogen, was first identified and produced in 1766 by the British chemist and physicist Henry Cavendish. Today, hydrogen can be produced by splitting the liquid water molecules. The water electrolysis producing hydrogen can be powered by renewable energy in the case of "green" hydrogen. Hydrogen is also produced from fossil fuels by steam reforming of methane in natural gas in conjunction with carbon sequestration in the case of "blue" hydrogen, or without carbon sequestration in the case of "grey" hydrogen. The use of hydrogen enables energy conversion and storage, and can provide a way to decarbonize sectors of the economy where decarbonization has no alternative or is hard to reach, such as long-distance transport by truck, train or airplane, heavy industries, or for domestic use in mixture with natural gas. Hydrogen has no direct greenhouse effect but is an indirect climate gas which induces perturbations of atmospheric methane, ozone and water vapour, three powerful greenhouse gases. The budget of atmospheric molecular hydrogen will be presented and the main sources and sinks will be briefly discussed. Based on the results of state-of-the-art global numerical climate and chemistry models, we derive various indicators intended to quantify the climate impact of hydrogen and in particular derive its Global Warming Potential (GWP).All the scenarios considered in this study for a future transition towards a hydrogen economy in Europe or in the world clearly suggest that a "green" hydrogen economy is beneficial in terms of CO2 emissions mitigation for the relevant time horizons and leakage rates considered. In contrast, the results suggest that carbon dioxide (CO2) and methane (CH4) emissions associated with the production and transport of "blue" (and "grey") hydrogen reduce the climate benefit of such a transition and even introduce a climate penalty in the event of a very high leakage rate or strong penetration of "blue" hydrogen on the market. Various assumptions will be illustrated for future “blue” hydrogen production carbon intensity. Reducing the leakage rate of H2 (and CH4 in the case of "blue" hydrogen production) and increasing the "green" hydrogen production sector appear to be the key levers towards maximum mitigation of CO2 emissions from a large-scale structural transition to a hydrogen economy.In addition, in the specific case of aviation, the use of liquid hydrogen powered aircraft induces additional climate forcings from water vapour emissions in the upper atmosphere and from impact on contrail formation. In the case of an hydrogen powered fleet, the forcings from NOx and from contrails are still subject to large uncertainties. These effects will be illustrated based on various assumptions for future aircraft using hydrogen fuel. 
Quantum Machine Learning for Deformation Detection: Application for InSAR Point Clouds
Authors: Le Nhung , Männel Benjamin , Motagh Mahdi , Brack Andreas , Schuh Harald
Published: March 2024

Abstract:Machine Learning (ML) is emerging as a powerful tool for data analysis. Anomaly detection based on classical approaches is sometimes limited in processing speed on big data, especially for massive datasets. Meanwhile, quantum algorithms have been shown to have the potential for optimization, scenario simulation, and artificial intelligence. Thus, this study combines quantum algorithms and ML to improve the binary classification performance of ML models for better sensitivity of surface deformation detection. We experimented with GNSS-InSAR combination data to identify significant deformation regions in Northern Germany. We classify the movement characteristics based on four main features: vertical movement velocities, root mean square errors, standard deviations, and outliers in the GNSS-InSAR time series. Our primary results reveal that the classification accuracy based on Quantum Machine Learning (QML) is outstanding compared to the pure ML technique. Specifically, on the same sample dataset, the classification performance of the neural network based on pure ML is only around 50 to 70%, while that of the QML technique can reach ~90%. The significant deformation regions are concentrated in the river basins of Elbe, Weser, Ems, and Rhine, where the average surface subsidence speed varies around -4.5 mm/yr. Also, we suggest dividing the surface movement features in Northern Germany into five classes to reduce the effect of the data quality variety and algorithm uncertainty. Our findings will advocate the development of quantum computing applications as well as promote the potential of the QML for deformation analyses. Keywords: Quantum Machine Learning, Binary Classification, GNSS-InSAR Data, Deformation Detection.
Monitoring induced seismicity in urban environment: assessing the performance of low-cost stations within Dense Semi-permanent Seismic Networks
Authors: Minetto Riccardo , Lengliné Olivier , Grunberg Marc , Turlure Mathieu , Schlupp Antoine , Vergne Jérôme , Jund Hélène , Schmittbuhl Jean
Published: March 2024

Obtaining high-resolution seismic catalogs from seismic data requires long-term monitoring and a sufficient number of sensors. Permanent seismic networks are usually limited to a small number of sensors, while very dense seismic networks (thousands of sensors) are typically installed for a limited period of time (days to a few weeks) and represent a large investment.In the framework of the PrESENCE project, we test the performance of a Dense Semi-permanent Seismic Network (DSSN) deployed in an urban environment (Strasbourg Eurométropole). This network, made up of Raspberry Shake seismographs, allows to record data over long periods (years) and from dozens of sites, thanks to the use of low-cost seismic stations operated by non-seismologists.The study aims to determine the advantages and limitations of these stations in urban environment, especially for the monitoring of induced seismicity. This is done by quantifying their impact on magnitude of completeness and location accuracy, as well as their contribution in detecting events with techniques such as template matching. The analysis was carried out on data recorded from January 2018 to September 2023 in the Strasbourg (France) area, which includes a seismic crisis that culminated in a M3.6 earthquake that led to the closure of the Geoven deep geothermal energy site operated by Fonroche-Geothermie. We conclude that these low-cost stations have provided a significant and valuable impact on the induced seismicity monitoring.
Impact of Climate Change and Climate Action on Indian manufacturing MSMEs and need for just transition in the sector: Evidence from Faridabad Industrial Cluster in India
Authors: Goel Mansi , Mishra Trupti , Banerjee Rangan
Published: March 2024

Climate change is a global problem, and it impacts all entities. These impacts are different for each entity and are experienced disproportionately. To ensure a just transition, the impacts ensuing from climate change need to be studied. These impacts, including the ones resulting from transitioning away from climate change, are not well studied for some entities such as the micro, small, and medium scale enterprises (MSMEs). Due to their inherent lack of capacity, MSMEs are already very vulnerable. They are the ones responsible for about 50% of exports in India and are the second highest employer in the country. The social importance of this sector thus makes it imperative to ensure a smooth transition in this sector.
In this study, we present a theoretical framework on how climate change (including climate action) might impact manufacturing industries. We then go on to explain how these impacts affect MSMEs differently as compared to large industries. The theoretical framework can be tailored to study impacts at individual, cluster, and sectoral levels. To operationalize the theoretical framework, we present a case study where we quantify the possible economic impacts of climate change on the Faridabad industrial cluster, which is one of the largest industrial clusters located in Northern India. Understanding the impacts will help minimize them, giving way to a just transition. Policymakers and individual factory owners can use the framework to identify avenues where there might be greatest impact to them, and develop a tailored strategy to overcome them.
Modelling the thermal regime of a recently destabilised talus: the Eyjafirdi landslide (October 6th 2020, Iceland)
Authors: Philippe Meven , Magnin Florence , Morino Costanza , Deline Philip , J. Conway Susan
Published: March 2024

In mountainous periglacial environments, permafrost degradation can be comprised among the triggering factors of landslides. Such hazards represent a threat for human lives and infrastructures (Geertsema et al., 2009). The extent of permafrost, and hence location of areas at risk of landslides, is estimated at the global scale using models based on air temperatures (e.g. Gruber, 2012). However, at the local scale, specific geological settings can allow the persistence of permafrost beyond its climate boundaries. In talus slopes specifically, peculiar air circulation named “chimney effect” can exist and favour permafrost formation and persistence at their foot, at location where it is not always predicted by models (Wicky and Hauck, 2017).In Iceland, talus slopes can be destabilised and generate landslides (Morino et al., 2019). However, due to the complexity of their geological setting, the thermal regime of talus slopes is difficult to model. Hence, only few numerical studies were conducted (e.g. Wicky and Hauck, 2017; Tanaka et al., 2006). This makes challenging to understand the destabilisation mechanisms of talus slopes, when determining the triggering mechanisms associated with permafrost degradation remains a crucial challenge. In that scope, we installed 16 temperature sensors within the talus (and close rockwall) where the Eyjafirdi landslide originated from (October 6th 2020, Iceland). They recorded temperature hourly from August 2021 to July 2022. The primary analysis of the dataset reveals that a chimney effect indeed occurs within the talus; therefore, we suspect that an ice lens could have persisted at the bottom of the talus – outside of the predicted extent of permafrost. This hypothesis is supported by the observation of molards within the landslide deposits – i.e. cones of loose debris formed by the degradation of ice-cemented blocks of sediment, transported by the landslide (Morino et al., 2019).In order to better characterise the thermal regime of the Eyjafirdi talus slope, we first reconstruct the temperature back to 1881 at the level of our sensors. We base that reconstruction on the correlation between our measured temperatures and air temperature datasets from meteorological stations – that go back to 1881. The reconstructed temperatures will then be used as forcing data, to constrain a thermal numerical model of the Eyjafirdi talus slope.Model runs will be performed using the commercial software FEFLOW. It uses the finite element method (i.e. a discretisation of the studied object as a mesh) to solve equations of heat transfer, taking into account freezing and thawing processes. These numerical models will allow us to determine whether the chimney effect indeed maintained an ice lens within the Eyjafirdi talus slope. Moreover, thanks to our unique temperature dataset, our study will represent the most accurate effort to model talus slopes so far.
Towards CO2 emission monitoring from space using FOCAL XCO2 retrievals of OCO-3 satellite measurements
Authors: Weimer Michael , Hilker Michael , Fuentes Andrade Blanca , Noël Stefan , Reuter Maximilian , Buchwitz Michael , Bovensmann Heinrich , Burrows John P. , Bösch Hartmut
Published: March 2024

Anthropogenic emissions of carbon dioxide (CO2) are the main driver of the change in climate since the industrial revolution. Policy mitigation strategies include reduction of these emissions. The Paris Agreement from 2015 requires the states to report their greenhouse gas emissions on a regular basis. Space-borne remote-sensing measurements of CO2 are considered potentially of great value  to monitor CO2 emissions, due to their better coverage in comparison to in-situ instruments. Measuring CO2  from space of an adequate quality is a challenge because of the stringent requirements related to the accuracy and precision of the data products and thus the instruments. In this study, we use the Fast atmospheric traCe gAs retrievaL (FOCAL) algorithm to retrieve maps of the column-averaged dry-air CO2 mole fraction (XCO2) with the goal of quantifying CO2 emissions for specific emission targets using Orbiting Carbon Observatory 3 (OCO-3) snapshot area maps. This data product is planned to  be used in the German national Integrated Greenhouse Gas Monitoring System (ITMS), for which an operational data assimilation system for greenhouse gases is being set up for Germany.
EOmaps: An open-source python package for geographic data visualization and analysis.
Authors: Quast Raphael , Wagner Wolfgang
Published: March 2024

EOmaps is a free and open-source python package specifically tailored for geographic data visualization and analysis.The main goals of the package are twofold:Speed up and simplify the daily struggle of geographic data visualization
Directly use the figures as fully customisable interactive data-analysis widgets
EOmaps is built on top of matplotlib and cartopy and integrates well with the scientific python infrastructure (numpy, pandas, xarray, geopandas, datashader, etc.). It provides a flexible and well-documented API to create publication-ready figures and it can be used to visualize (potentially large) structured (e.g. raster) or unstructured (e.g. unordered lists) datasets provided in arbitrary projections. In addition, EOmaps comes with many useful features to help with scientific geo-data analysis:Maps can have multiple layers to interactively compare and (transparently) overlay datasets, web-maps etc.
Once a dataset is plotted, you can assign arbitrary callback functions to interactively run your analysis-workflow on selected datapoints (e.g. load data from a database, plot underlying timeseries, histograms etc.)
Figures created with EOmaps can be exported as images (png, jpeg, ...), vector-graphics (svg) or embedded in Jupyter Notebooks, web-pages (html) or in GUI frameworks such as Qt or tkinter.In this presentation we will highlight the capabilities of EOmaps and show how it can be used in a variety of different situations to aid your scientific data analysis workflow.EOmaps source-code: https://github.com/raphaelquast/EOmaps  EOmaps documentation: https://eomaps.readthedocs.io/
Extreme weather breaks phenological and landscape controls on temperate peatland fuel moisture; implications for carbon stock release through changing wildfire regimes
Authors: Ivison Katy , Little Kerryn , Graham Laura , Kettridge Nick
Published: March 2024

Temperate peatlands and heathlands are at increasing risk of severe wildfires under future climates which may combust legacy carbon stocks. The moisture content of the different fuel layers determines the threat posed. The controls on fuel moisture and their response to extreme weather have previously been unknown. Here, we show that controls differ between fuel layers. Fine dead fuel moisture is dominated by weather, live fuel by temporal controls including season and phenology, and soil organics by elevation and soil type. This separation of controls in time and space produces a landscape resistance to severe wildfire. However, extreme weather events break the phenological control on live fuel moisture and the landscape control of organics, resulting in low moisture content across all fuel types. This leads to the most severe conditions for fire ignition, spread and impact in traditionally non-fire prone regions, producing a landscape susceptible to severe environmental impacts and carbon emissions within a new summer wildfire regime.
Actively engaging people on rainfall (or any geoscience topic) through short interactive food related activitie
Authors: Gires Auguste , Dallan Eleonora
Published: March 2024

In an area of widespread misinformation, it is crucial for scientists to reach out to the general public and explain their research topic to increase knowledge and, more importantly, to enhance curiosity and to stimulate people to pay more attention to their geophysical environment. The general aim of this research is testing an innovative approach to actively engage people on geosciences topics, in a funny and informal way, through short interactive food-related activities. As rainfall scientists, we carefully designed these activities to unveil part of the underlying complexity of this geophysical field. In particular, we focus on the  extreme variability of rainfall over wide ranges of scales in both space and time, of which people are usually unaware despite commonly experiencing rainfall.  Each activity is designed with similar underlying concepts: 1) A single simple take home message on rainfall. 2) The studied feature is visible at first sight to strike people’s minds. 3) Real rainfall data is somehow mimicked with food. 4) The activity itself lasts a few minutes. 5) It is designed as a game to foster people's engagement.  Various activities were designed with these specifications. An illustration is the rainfall drop size distribution variability which is highlighted through sweet or salty cookies (ex: macaron / “baci di dama”) representing drops variability in shape and in the actual size in their fall. Another illustration is the representation of rainfall monthly distribution and its variability, through the use of glasses with liquid (champagne, soda, water…) height corresponding to rainfall depth during a month. In each case, there is an incentive to engage in the game through the hope of getting the bigger cookie or most filled glass. Activities are implemented in informal settings (family, friends, lab meetings) during either snacks or dinner. In the former case, a single one is carried out while in the latter several ones -typically one per course- are.  In order to evaluate if active engagement is indeed achieved, the following methodology is implemented. During the activity, a previously briefed outside observer fills a pre-defined grid to assess the level of engagement of people. After the activity, people are invited to let us know  about new ideas, observations, questions, and send us pictures on the topic of the activity. The latter step is much more qualitative. As a side product, how the “take home messages” are remembered by people is also partially assessed keeping the informal approach of the activity.  Implementation and interpretation of the activities in various contexts will be discussed in this presentation.
Thunderstorm and Hail Frequencies in South America and Australia Based on Overshooting Tops
Authors: Fischer Jannick , Kunz Michael , Bedka Kristopher
Published: March 2024

Convective storms over South America and Australia are among the most intense worldwide (e.g., Zipser 2006). However, they are less researched compared to US and Europe. This study analyses the thunderstorm climatology over South America and Australia based on over 20 years of overshooting cloud top (OT) satellite detections (Khlopenkov et al. 2021). These OTs serve as robust, horizontally homogeneous indicators of strong updrafts and hence intense thunderstorms. Furthermore, we focus on the frequency of severe storms and hail by using ERA5 Reanalysis data to exclude OTs in unfavorable environments (e.g., Punge et al. 2023).The resulting climatologies of intense thunderstorms and hail are largely consistent with existing literature, showing strong thunderstorm activity in tropical regions but more severe (e.g., hail-producing) storms in south-central South America and southeast Australia. Some notable details will also be discussed, such as the discrepancy with observational hotspots near the coast in South America and a surprisingly strong signal over northwest Australia. Furthermore, regarding a climate change signal, preliminary analysis indicates no significant trend for South America. However, the multi-year variations are strongly linked to the El Ninjo-Southern Oscillation (ENSO).
Seismic Thermography
Authors: Lebedev Sergei , Fullea Javier , Xu Yihe , Bonadio Raffaele
Published: March 2024

What is next in seismic tomography? In this presentation, we make a case that a key future direction is the inversion of seismic data directly for temperature within the Earth. We term this emerging branch of seismic imaging Seismic Thermography. Variations in temperature are of great interest because they indicate the thickness and, consequently, mechanical strength of the lithosphere and density variations and convection patterns in the sub-lithospheric mantle. Seismic tomography maps seismic-velocity variations in the mantle, which depend on temperature. Temperatures and the lithospheric structure and thickness are, thus, often inferred from tomography. Tomographic models, however, are non-unique solutions of inverse problems, regularized to ensure model smoothness or small model norm, not plausible temperature distributions. For example, lithospheric geotherms computed from seismic-velocity models typically display unrealistic oscillations, with improbable temperature decreases with depth within shallow mantle lithosphere.It is more accurate to invert seismic data directly for temperature and avoid the errors due to the intermediate-model non-uniqueness. Because seismic-velocity sensitivity to composition is weaker than to temperature, we can use computational petrology and thermodynamic databases to invert seismic data primarily for temperature, with reasonable assumptions on composition and other relevant properties and with additional inversion parameters such as anisotropy.Here, we apply thus defined Seismic Thermography to the thermal imaging of the lithosphere, asthenosphere and the lithospheric thickness using surface waves. Conductive geotherms and standard compositions fit the data from Precambrian continents and from Britain and Ireland, which we use as examples. Exotic compositions and temperature profiles can also be mapped, when required by the data, using specially defined components of the parameterisation. The accuracy of the models depends critically on the accuracy of the extraction of structural information from the seismic data. Random errors have little effect but correlated errors of even a small portion of 1% can affect the models strongly.Seismic Thermography builds on the techniques of seismic tomography and relies on computational petrology but it is emerging as a field with its own scope of goals, technical challenges and methods. It is producing increasingly accurate models of the Earth and important inferences on its dynamics and evolution.