bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the main heatwave patterns in the northeast of the Iberian Peninsula using ERA5 and CORDEX models
Authors: Ventura Sergi , Villalba Gara , Miro Josep Ramon , Peña Juan Carlos
Published: February 2023

Heatwaves are expected to increase not only in intensity but also in frequency and duration in the next decades. Most of the studies are focused on the temperature variable, but little is known about their synoptic structure, which is especially important in mid-latitude regions.In this study, we propose a Principal Sequence Pattern Analysis (PSPA) to classify the main synoptic patterns that define heatwaves in the northeast of the Iberian Peninsula. This is done by finding the most correlated input variables that represent the highest number of variance possible. The database used for this analysis comes from ERA5 reanalysis data covering the 1951-2020 period, in which we have selected three variables: mean sea level pressure (MSLP), geopotential height at 500 hPa (Z500) and maximum daily temperature at 2 meters (TMAX). Once the historical analysis is prepared, the same steps are repeated for CORDEX models (1951-2000) to discuss the performance of these models simulating heatwave periods.The multivariate analysis has resulted in four synoptic patterns that explain more than 50% of the total variance. The four patterns are divided into two groups, stationary and dynamical. The HWs with highest temperatures in the Metropolitan Area of Barcelona are the prefrontal patters, which are dynamical and undulated at Z500 and undetermined at MSLP, with mean maximum temperatures around 35°C. However, the warmest pattern in inland areas is stationary and stable, generated at Z500 by intense anticyclonic ridges covering the Iberian Peninsula and at MSLP by deep thermal lows. The CORDEX models simulate similar patterns but less defined due to the lack of resolution. Z500 results in an overestimation of the anticyclonic ridges and MSLP shows an underestimation of pressure gradients, simulating more undetermined patterns. However, there are discrepancies between the models, which will result in different future projections in the climate change scenarios.
An Automated Data Ingestion Workflow for the TOAR Database
Authors: Kreshpa Enxhi , Schröder Sabine , Selke Niklas , Schultz Martin
Published: February 2023

Over the last years, several repositories with curated environmental datasets have been created so that scientific communities have gained access to large collections of data from various domains. The level of data harmonisation and FAIRness, technical readiness and scalability of these repositories differs substantially. This restricts data exploration opportunities and limits scientific exploration with modern data science methods, such as machine learning. In­ the domain of air quality research, we have pioneered a data infrastructure for global observations of surface ozone and other air pollutant measurements that comes with rich possibilities for online data analysis. The data in the Tropospheric Ozone Assessment Report (TOAR) database is collected from about 40 different resource providers, from national and international environmental agencies to individual research groups around the world.One of these data providers is OpenAQ, the world's first open, real-time air quality platform. Due to the higher standards of curation, the need for data harmonization, and the enriched metadata in the TOAR database, we had to develop an automated workflow to transport archived and real-time data from this provider to the TOAR database. The primary step is to clean and format all the OpenAQ records, according to the TOAR database schema, and concurrently, refine the metadata. The workflow includes tests for data sanity and checks if time series and station metadata can be amended, or whether new time series or station records must be created. The automation manager triggers the workflow hourly, so the database provides clean and updated air quality data at any time. The presentation describes the automated workflow and its design principles and discusses how such a workflow might be re-used in other environmental domains. All TOAR-related codes are open source.
Modelling the seismic amplitude response to internal heterogeneity of mass-transport deposits
Authors: Ford Jonathan , Camerlenghi Angelo , Zolezzi Francesca , Calarco Marilena
Published: February 2023

Mass-transport deposits often show a low-amplitude, “acoustically transparent” seismic response compared to unfailed sediments. This amplitude signature is often interpreted as a lack of coherent internal reflectivity caused by a loss of internal structure during transport and emplacement, and is widely used to delineate mass-transport deposits in sub-bottom profiler data. An apparent contradiction is that cores penetrating such “acoustically transparent” deposits can sometimes retrieve well-stratified sediments that show little evidence of deformation.In this study we examine the variation in the single-channel seismic amplitude response with changing heterogeneity using synthetic seismic modelling. We model the internal structure of mass-transport deposits as a two-component binarised random medium, where the lateral correlation length is used to artificially control the degree of internal deformation/scale of internal structure, while maintaining the magnitude of the internal reflectivity constant. We construct two synthetic models: i) a simplified single-source marine example and ii) a multi-source example based on a real world “acoustically transparent” mass-transport deposit imaged by a dense network of AUV sub-bottom profiles in the Black Sea. We use 2-D elastic finite-difference modelling to model the seismic response (at sub-bottom profiler bandwidths) of an ensemble of both synthetic models with varying geostatistical parameters and random seeds for the mass-transport deposit zones. For the single-source synthetic model a reduction in observed amplitude with reduced lateral scale length is consistently observed across a range of vertical correlation lengths. For the real world Black Sea example, with realistic elastic and geostatistical parameters based on cone-penetration tests and physical property measurements from sediment cores, we find that when the lateral scale length of the random medium is around 1 m, recorded seismic amplitudes are, on average, reduced by ∼15% relative to unfailed sediments.We conclude that relatively small amounts of deformation at scales larger than the dominant seismic wavelength are, in general, able to a generate significant decrease in seismic amplitude, without requiring a reduction in the average reflectivity. Our synthetic modelling results should discourage interpretation of the internal structure of mass-transport deposits based on seismic amplitudes alone as “acoustically transparent” mass-transport deposits may still preserve coherent, metre-scale internal structure. In addition, the minimum scale of heterogeneity required to produce a reduction in seismic amplitudes is likely much larger than the diameter of sediment cores, meaning that such mass-transport deposits may still appear well-stratified and undeformed when cored.
Invertible neural networks for satellite retrievals of aerosol optical depth
Authors: Pelucchi Paolo , Vicent Jorge , Johnson J. Emmanuel , Stier Philip , Camps-Valls Gustau
Published: February 2023

The retrieval of atmospheric aerosol properties from satellite remote sensing is a complex and under-determined inverse problem. Traditional retrieval algorithms, based on radiative transfer models, must make approximations and assumptions to reach a unique solution or repeatedly use the expensive forward models to be able to quantify uncertainty. The recently introduced Invertible Neural Networks (INNs), a machine learning method based on Normalizing Flows, appear particularly suited for tackling inverse problems. They simultaneously model both the forward and the inverse branches of the problem, and their generative aspect allows them to efficiently provide non-parametric posterior distributions for the retrieved parameters, which can be used to quantify the retrieval uncertainty. So far INNs have successfully been applied to low-dimensional idealised inverse problems and even to some simpler scientific retrieval problems. Still, satellite aerosol retrievals present particular challenges, such as the high variability of the surface reflectance signal and the often comparatively small aerosol signal in the top-of-the-atmosphere (TOA) measurements.In this study, we investigate the use of INNs for retrieving aerosol optical depth (AOD) and its uncertainty estimates at the pixel level from MODIS TOA reflectance measurements. The models are trained with custom synthetic datasets of TOA reflectance-AOD pairs made by combining the MODIS Dark Target algorithm’s atmospheric look-up tables and a MODIS surface reflectance product. The INNs are found to perform emulation and inversion of the look-up tables successfully. We initially train models adapted to different surface types by focusing our application on limited regional and seasonal contexts. The models are applied to real measurements from the MODIS sensor, and the generated AOD retrievals and posterior distributions are compared to the corresponding Dark Target and AERONET retrievals for evaluation and discussion.
Combined natural and numerical-modeling constraints on subduction interface strength at deep metamorphic conditions
Authors: Abila Ana Lorena , Behr Whitney , Ruh Jonas
Published: February 2023

The integrated stress magnitude or bulk effective viscosity of subduction interface shear zones is a key component of both long- and short-term subduction dynamics. Current constraints on average subduction interface viscosity come from laboratory flow laws for subduction-related rock types and range from 1018 Pa.s (quartz-rich lithologies) to 1023 Pa.s (metabasaltic lithologies) for typical subduction strain rates and viscous subduction interface conditions (e.g. T between 400-900 °C). However, this viscosity range is based on end-member flow laws, which means it likely overestimates the true range in viscosity that is possible along the subduction interface. In nature, subduction shear zones are commonly a mixture of multiple rock types in various distributions (e.g. clast-matrix melanges); and furthermore, natural shear zones show a range in width from place to place, suggesting varying strain rates. Our goal in this study is to place more precise bounds on the global range of shear zone viscosity (or integrated shear stress) for natural subduction shear zones at deep subduction conditions. To do so, we curated a set of 9 geologic maps of eclogite facies shear zones from existing literature, focusing on those that a) show minimal retrogressive overprint, b) have defined shear zone widths, and c) have well-constrained PT conditions. These maps were digitized and implemented in a simple shear visco-elasto-plastic numerical model with constant strain rate (10-12 s-1) boundary conditions and experimentally constrained flow laws assigned to each rock type, including eclogite (eclogite mafic blocks), wet quartz (quartz-rich blocks, schists, gneisses), blueschist (blueschist mafic blocks), wet olivine (peridotites), antigorite (serpentinites), and aragonite (calcareous blocks). Numerical experiments  ran for a restricted amount of time steps to assure  steady-state stress/viscosity (<10 ky). Resulting integrated shear stresses and viscosities were then compared for the different example shear zones. Initial results indicate that natural shear zones should exhibit effective viscosities that vary by at least 1-2 orders of magnitude at a specific temperature, depending on the distribution of weak vs. strong blocks and the matrix rheology. Additional results and statistical analysis of all of the shear zones will be presented at the meeting. 
Measurements of microphyscs in cold air Outbreks
Authors: Choularton Tom , Lloyd Gary ,   M-phase ACAO
Published: February 2023

Measurements were made in 2 sets of cold air outbreaks using the UK FAAM BAE 146  research aircraft. The first set were performed in March 2022 over the Eastern Atlantic the second set were perform in October to early November 2022 in the Western Atlantic over the Labrador Sea based in Goose Bay, Eastern Canada. In each set of experiments the focus was to study the evolution of the cloud microphysics as influenced by Cloud condensation nuclei, ice nuclei and secondary ice processes  in the stratocumulus clouds being advected southwards over progressively warmer sea until cloud break-up occurred into convective clouds. The aims were to improve the treatment of these cloud types in Global climate models and weather forecast models. These projects formed part of m-Phase funded by NERC as part of its Cloud Sense programme and ACAO a Met office program to study these clouds.A range of aerosol and cloud microphysical equipment was used in the 2 projects which will be discussed in the presentation.Analysis of the data set including a new novel Holographic instrument is still underway at the time of writing; however, some preliminary results indicate that:

Generally the ice crystal number concentration exceeded the ice nucleus concentrations measured at the same temperature
Some regions consisted entirely of super cooled water
A range of secondary ice particle production mechanisms were observed including ice splinter production during riming and droplet shattering on freezing after capture by ice crystals
Generally if the convective region was reached by the aircraft then secondary ice production was greater than in the stratocumulus region
Precipitation was mostly in the ice phase
Mapping the Geogenic Radon Potential as a first step to define the Radon Priority Areas
Authors: Benà Eleonora , Ciotoli Giancarlo , Ruggiero Livio , Petermann Eric , Bossew Peter , Mazzoli Claudio , Verdi Luca , Sassi Raffaele
Published: February 2023

Radon (222Rn) is a radioactive gas considered the major source of ionizing radiation exposure for the population and several epidemiological studies provided evidence of its detrimental effects on human health. As a consequence, the World Health Organization classified this gas as the second cause of lung cancer after cigarettes smoking. A significant fraction of lung cancer can be attributed to the indoor Rn exposure, i.e. houses and workplace. In particular, Indoor Radon Concentration (IRC) is the product of the Geogenic Radon Potential (GRP), conceptualised as the contribution of Rn released by the Earth. Therefore, in the characterisation of the potential risk over an area is fundamental considering the geological constraints under the dwellings, the building styles and living habits. In Europe, the Basic Safety Standards Directive 2013/59/EURATOM aims to reduce the human exposure to Rn in houses and workplace, on the one hand fixing some reference values, on the other hand requiring to the European states to delineate the Radon Priority Areas (RPA), i.e. that areas where IRC exceed the European Directive reference value. In particular, mapping the GRP as an indicator of the Rn related hazard is fundamental for: (i) delineate the RPAs through the quantification of geogenic Rn, that can potentially influx within buildings; (ii) understand how GRP can affect the vulnerability over an area thus contributing to the Rn risk. In this study, we focused on mapping the GRP of a specific study area located in the Pusteria Valley (Bolzano province, eastern Italy). This area is well-known from a geological and structural point of view and it is characterised by a wide non-seismically active fault zone showing a very high gas permeability.  In particular, we have applied a machine learning technique (i.e. Forest Regression), to construct a high resolution (50 m*50 m) GRP map of the study area considering several proxy variables related to the Rn sources (e.g., radionuclide content in rocks), to the Tectonically Enhanced Radon (TER) quantity and to the exhalation process towards the atmosphere. Furthermore, we have assessed the vulnerability of the area by introducing the location of inhabited areas to provide a preliminary map of RPAs. Results show that dwellings characterised by high vulnerability are located in the area with the highest GRP. This work represents the first attempt in Italy to define the RPAs.
Supermodelling: synchronising models to further improve predictions
Authors: Schevenhoven Francine , Shen Mao-Lin , Keenlyside Noel , Weiss Jeffrey B. , Duane Gregory S.
Published: February 2023

Instead of combining data from an ensemble of different models after the simulations are already performed, as in a standard multi-model ensemble, we let the models interact with each other during their simulation. This ensemble of interacting models is called a supermodel. By exchanging information, models can compensate for each other's errors before the errors grow and spread to other regions or variables. Effectively, we create a new dynamical system. The exchange between the models is frequent enough such that the models synchronize, in order to prevent loss of variance when the models are combined. In previous work, we experimented successfully with combining atmospheric models of intermediate complexity in the context of parametric error. Here we will show results of combining two different AGCMs, NorESM1-ATM and CESM1-ATM. The models have different horizontal and vertical resolutions. To combine states from the different grids, we convert the individual model states to a ‘common state space’ with interpolation techniques. The weighted superposition of different model states is called a ‘pseudo-observation’. The pseudo-observations are assimilated back into the individual models, after which the models continue their run. We apply recently developed methods to train the weights determining the superposition of the model states, in order to obtain a supermodel that will outperform the individual models and any weighted average of their outputs.
Study of the 2 m temperature bias of the numerical weather forecasting model Arome over the French Alps
Authors: Préaux Danaé , Dombrowski-Etchevers Ingrid , Gouttevin Isabelle , Seity Yann
Published: February 2023

The Arome numerical weather prediction system is routinely used for weather forecasting over the mountains of the French Alps, Pyrénées and Corsica. However, its skills at temperature forecasting are altered by several 2 m temperature biases: (1) a cold bias at high altitude, (2) a low-altitude warm bias occurring in stably stratified layers and (3) a warm bias during snowfall situations.Targeted numerical simulations (successive activation of some dynamic, physical and assimilation modifications) were carried out on the day of January 12, 2021, a problematic snowy situation in the Arve valley (Haute-Savoie, French Alps).Over this period, the operational version of Arome has a mean absolute error (MAE) of 2.3°C in the valley. The increase of vertical resolution does not improve the performance of the model in the valley. The MAE is nevertheless decreased from 1.4 to 1.1°C in the mid-altitude range and from 1.5 to 1.2°C above 2000 m. Conversly, the use of a new surface scheme (ISBA-DIF) associated with a more complex snowpack model (ISBA-ES) allows to better represent the arrival of the warm front in the valley and reduces the error (to 1.8°C) whatever the altitude. The current surface scheme therefore seems too simplistic to correctly model soil-atmosphere interactions in the mountains. Forcing Arome with full-day data assimilation also reduces the bias in the valley (to 2.0°C). However, this experiment deteriorates the scores in the mid-altitude and high-altitude mountains. Furthermore, the situation has a poor initial state as biases are present even before the snow event starts. This may point towards deficiencies in the assimilation of in-situ data in mountain regions, that should be overcome in future work.These results show that the warm bias during this snowy event has multiple origins. A carefull analysis of other situations will be needed to confirm and correct theses biases. 
Tidal effects on groundwater levels in Maputo, Mozambique
Authors: Meng Xue , Zhou Yangxiao , Wang Jinguo , Stigter Tibor , Mussa Fatima , Juizo Dinis , Yang Yun
Published: February 2023

Groundwater is an important source for water supply in Maputo City, Mozambique. A groundwater monitoring network has been established for systematically monitoring of groundwater level and salinity changes. Automatic data loggers were installed to register groundwater levels and EC values every hour. Three observation wells were installed in the coast to detect seawater intrusion. The measured groundwater levels show clearly tidal effects. In this study, time series analysis methods were used to identify dominant periodic changes in groundwater levels (GWLs), effects of tide, and estimation of aquifer diffusivity using tidal effect parameters. Autocorrelation and cross-correlation analysis were used to estimate the periodic components and lag time between the tide and GWLs, respectively. Spectral analysis was used to ascertain the dominant periodic components in the tide and GWLs by means of estimating amplitude spectrum and power spectrum density. Cross-spectral analysis was used to determine the lag time between the tide and GWLs by means of estimating cross-power spectrum density. Furthermore, wavelet analysis was used to investigate changes of periodic components over the measured period. The estimated amplitudes and lag times were used to estimate aquifer diffusivity. The results identified dominant periodic component with a 12hour period both in the tide and GWLs. However, groundwater level is lag behind the tide with 2-4 hours depending on the distance of the observation wells to the costal line. The wavelet analysis results show no changes of dominant periodic components over the time. Therefore, the estimated amplitude and lag time were used to estimate aquifer diffusivity. The estimated parameter values are 2.72595E-05 h/m2, 6.97843E-05 h/m2, and 6.14906E-05 h/m2 from observation wells. These correspond values of transmissivity as 440 m2/d, 172 m2/d, and 195 m2/d, respectively. The estimated transmissivity values are useful for constructing saltwater intrusion models.
Reimagining automated mineralogy for the 21st century
Authors: Taylor Rich
Published: February 2023

The phrase “automated mineralogy” has been synonymous with electron microscopy in the geosciences for decades. The use of energy dispersive spectroscopy (EDS) to rapidly map samples and identify phases of interest has gradually seen a shift out of its original industry applications and into the academic research environment. A major issue for academics wishing to take advantage of this powerful tool is the original platforms are rigid in terms of their industry designed outputs, and there has been a lack of development in both the software and hardware capable of providing automated outputs.However, rather than just looking backwards at what automated mineralogy was originally designed for, there is a more forward looking and important conversation as geoscience projects increase in scope. To think about geoscience in the context of topics such as big data, statistical relevance, and the use of increasingly prevalent machine learning techniques, we need to think about how we collect and store data. This naturally requires a greater integration of the problems geoscientists are trying to address with the solutions that microscopy and microanalysis equipment suppliers provide. Greater access to the data acquired on scientific equipment not only provides greater research flexibility but opens much smarter routes towards a future of correlated datasets with minimal user input.Using quantitative chemistry as the basis for automated mineralogy provides unique capabilities for large area analysis such as thin sections. Quantitative textural information can be extracted from the sample such as grain sizes, shapes, and mineral associations, alongside quantitative geochemical data providing mineral classification, including mineral and whole rock/sample compositions. This provides a wealth of information for the petrologist to understand their sample and a one-stop-shop for many geoscience workflows. This is a ready made mechanism to generate large datasets across multiple samples in a consistent fashion – the key to big data.Here we show one example of greater integration of data acquisition with user generated computational software showing the power of large area quantitative EDS mapping with geoscience-oriented functions of XMapTools. By importing calibrated, quantitative EDS maps XMapTools can be used to rapidly perform a variety of petrological calculations without the need for a separate, long-winded calibration step using microprobe data. Here we use quantitative EDS from high grade metamorphic rocks to obtain mineral and bulk compositions alongside textural information such as modal abundances. These mapped data are imported directly into XMapTools and can be used to generate oxide values, cation per formula unit (cpfu), end member proportions, and perform thermodynamic calculations.
Latest quaternary active faulting and paleoearthquakes on the Kangding segment of the Xianshuihe Fault Zone, Eastern Tibetan Plateau
Authors: Ma Jun , Zhou Bengang , Wang Mingming
Published: February 2023

The Xianshuihe Fault Zone (XSHF) is one of the most active strike-slip faults on the eastern Tibetan Plateau. Along the NW-striking, left-lateral XSHF, as many as 8 M >7 and 29 M >6.5 earthquakes have occurred since 1700 CE. The Kangding segment is a special part of the XSHF that has four active faults and can exhibit large earthquakes. From north to south, they are the Yalahe Fault, Selaha Fault, Mugecuo South Fault, and Zheduotang Fault. However, the activity and paleoearthquake sequence of branch faults in Kangding segment remain controversial. Our detailed research is focus on the Yalahe Fault and Zheduotang Fault in Kangding segment. We mapped accurate fault traces and deformed landforms based on detailed interpretations of high-resolution imagery and aerial photographs combined with field observations. Geological and geomorphological evidence was obtained for the Holocene activities. Paleoearthquake sequence was built based on the trench work. We discussed the recurrence characteristics and slip behavior.The Yalahe Fault follows a quasiperiodic recurrence model and Zheduotang Fault displays uniform slip behavior. From the result of paleoearthquake, the Yalahe Fault, Selaha Fault, and Zheduotang Fault experienced cascading ruptures. Therefore, the branch faults in Kangding segment have ability to generate large earthquakes in the future.
Joint multifratcal analysis of available wind power and rain intensity from an operational wind farm
Authors: Jose Jerry , Gires Auguste , Schnorenberger Ernani , Tchiguirinskaia Ioulia , Schertzer Daniel
Published: February 2023

Wind power production plays an important role in achieving UN’s (United nations) Sustainable development goal (SDG) 7 - affordable and clean energy for all; and in the increasing global transition towards renewable and carbon neutral energy, understanding the uncertainties associated with wind and turbulence is extremely important. Characterization of wind is not straightforward due to its intrinsic intermittency: activity of the field becomes increasingly concentrated at smaller and smaller supports as the scale decreases. When it comes to power production by wind turbines, another complexity arises from the influence of rainfall, which only a limited number of studies have addressed so far suggesting short term as well as long term effects. To understand this, the project RW-Turb (https://hmco.enpc.fr/portfolio-archive/rw-turb/; supported by the French National Research Agency, ANR-19-CE05-0022) employs multiple 3D sonic anemometers (manufactured by Thies), mini meteorological stations (manufactured by Thies), and disdrometers (Parsivel2, manufactured by OTT) on a meteorological mast in the wind farm of Pays d’Othe (110 km south-east of Paris, France; operated by Boralex). With this simultaneously measured data, it is possible to study wind power and associated atmospheric fields under various rain conditions.Variations of wind velocity, power available at the wind farm, power produced by wind turbines and air density are examined here during rain and dry conditions using the framework of Universal Multifractals (UM). UM is a widely used, physically based, scale invariant framework for characterizing and simulating geophysical fields over wide range of scales which accounts for the intermittency in the field. While statistically analysing the power produced by turbine, rated power acts like an upper threshold resulting in biased estimators. This is identified and quantified here using the theoretical framework of UM along with the actual sampling resolution of instruments under study. Further, from event based analysis, differences in UM parameters were observed between rain and dry conditions for the fields illustrating the influence of rain. This is further explored using joint multifractal analysis and an increase in correlation exponent was observed between various fields with increase in rain rate.
SIGALE: An online early warning system for gravitational hazard (Savoie, France)
Authors: Cadet Héloïse , Rouquet David , Lescurier Anne
Published: February 2023

The SIGALE (System of Information Geographic for grAvitational hazard vigiLancE assessment) project aims at developing an experimental early-warning system of gravitational hazard (landslides and rockfalls) over the road infrastructure network of Savoie (France). This network is about 3 300 km long.We propose a new approach based on machine learning to predict a vigilance  degree. The vigilance degree is a combination of susceptibility model and trigger model.The landslide susceptibility model is based on topographical data, landcover and lithology. The rockfall susceptibility model is based on statistical results of propagation using Flow-R.The trigger models have been trained on an event database of 863 landslides and 481 rockfalls events from 2008 to 2020. The database covers 13 years, so about 4 745 days, over about 6 000 sectors. The thousand events are spread over 28 millions of spatio-temporal sectors. The dataset is thus highly unbalanced and specific machine learning has been deployed. The trigger models features are based on rainfalls and temperatures.Our results show that, in spite of the high class imbalance issues of such database, the trigger models provide recall values of about 75%, with about 60% of precision.Our prototype is a web-service showing vigilance degree model for both landslide and rockfall with different zooming information for decision support.
Increasing methane emissions from the North Slope of Alaska since 2000 and late Autumn-Winter emissions from multiple Arctic regions
Authors: Ward Rebecca H. , Ganesan Anita L. , Sweeney Colm , Miller John , Goeckede Mathias , Laurila Tuomas , Hatakka Juha , Ivakhov Viktor , Makshtas Alexander
Published: February 2023

Large stores of carbon frozen in the Arctic as permafrost are under threat of thawing as temperatures in the Arctic increase at a rate four times that of the global mean. This study uses recent atmospheric data from the North Slope of Alaska and Northeast Siberia to provide the most up-to-date assessment of emissions and trends from these two major high-latitude regions.We use two methods to quantify emissions and assess trends across different seasons: 1) Using 35 years of data from Barrow, Alaska, a wind sector method that quantifies trends in emissions by calculating concentration enhancements over background using wind direction to identify the land sector (first used in Sweeney et al., 2016), and 2) using Barrow data and recent data from three Siberian stations, an inversion method with the high-resolution atmospheric transport model NAME that quantifies both emissions and trends from these regions. We use results from these two approaches to quantify the temperature sensitivity (Q10) of soils based on correlations between surface air and ground temperatures with methane emissions.With the inclusion of atmospheric concentration data after 2015, we now show that land emissions from the North Slope of Alaska have been increasing since 2000, reflecting a change from previous analyses, which showed no significant increase in summertime methane emissions between 1986-2014 (Sweeney et al., 2016). We find significant emissions from the late shoulder season (Autumn-Winter), which has historically been undermeasured and underrepresented in models and emissions inventories, in this region of Alaska as well as two North-eastern Siberian locations, the Taymyr Peninsula and the East Siberian Lowlands. We show that emissions during this late-season have been growing over the past two decades at a rate similar to summer-time emissions.Our results based on long-term atmospheric data can be used to show that important change is happening in the Arctic, with an increasing emissions trend and the presence of late shoulder season emissions.
Multi-point Investigation of CME Alfvénicity and Coherence near 1 au
Authors: Scolini Camilla , Lugaz Noé , Winslow Réka , Farrugia Charles
Published: February 2023

Our knowledge of the physical processes carrying information across Coronal Mass Ejections (CMEs), thereby controlling the way CME structures respond to external disturbances  in interplanetary space, is still incomplete. One prominent question is whether CMEs are “coherent” structures, i.e. potentially capable of responding in a uniform manner to external forces, and across what (macroscopic) spatial scales does such coherence exist. A necessary condition for different regions within a given CME to exhibit a coherent behavior is that they must be causally connected to the perturbation source. Past studies suggested interplanetary CMEs may behave as coherent structures only locally, and indicated that the spatial scale of coherence may be hampered by interactions with large-scale structures in the solar wind. Additionally, observational studies often assumed the correlation in the magnetic field profiles at different spacecraft locations as a proxy for coherence, but the physical link between correlation and coherence is still to be established. Characterizing the physical mechanisms mediating CME structural changes in different solar wind conditions at a fundamental level is therefore imperative to better understand their evolution and impact on space-borne and ground-based anthropic activities. In this study, we investigate the role of Alfvénic fluctuations (AFs) as mediators of coherence within interplanetary CMEs, and the physical relationship between correlation and coherence using multi-point observations near 1 au. In order to determine if and to what extent AFs alter CMEs at different spatial scales, we compare CME signatures at multiple spacecraft in terms of presence/absence of AFs, AF properties (if present), and correlation of magnetic signatures.  We contextualize the results in terms of the CME interaction history and the causal connection of different spacecraft observations. This study reveals how AFs affect the correlation of CME magnetic signatures across different spatial scales, and helps reconcile correlation scales within CMEs with their coherent behavior. 
Disentangling first-order controls of rock-water-plant interactions: a case study with the WITCH2O critical zone model
Authors: Kuppel Sylvain , Goddéris Yves , Riotte Jean , Schott Jacques
Published: February 2023

Water is the first order controlling factor of the weathering reactions. In the recent years, efforts have been made towards the building of model cascades able to simulate the water fluxes and the residence time of the water in the various compartments of the critical zone. Those hydrological constrains are then injected into numerical models simulating the water-rock interactions from the surface down to the impervious bedrock. In this contribution, we describe such a model cascade, where the water-rock interaction model WITCH is fed by the process-based ecohydrological model EcH2O-iso. This model cascade, WITCH2O, is designed for the modeling of water fluxes & stores, as well as the weathering reactions and transport of weathering products (including atmospheric CO2 consumption), from the vertical profile to the catchment scale, and from the submonthly to decadal time scales. We deployed WITCH2O in a small tropical headwater catchment in peninsular India where long-term observations of water and geochemical fluxes are available, allowing for model calibration and evaluation across the different processes simulated. Using various temporal averages of simulated water fluxes and stores, we notably analyse the influence of hydrological variability upon the dynamics of weathering rates and nutrient concentrations. Our results also highlight the control of root zone uptake and lateral water redistribution upon spatial variability of geochemical patterns. 
What can we see by illuminating the ambient deep sea?
Authors: Wu Tian , Ren Yu , Liu Sibiao , Li Chuanzhi , Yao Pengfei , Hu Xin
Published: February 2023

Geoscientists usually use visuals like graphs and tables to explain their research to their peers or to non-specialists. However, it has been challenging to visualize how our Earth system works hidden behind complex geoscientific data effectively and intuitively to the general public. Art, as a universal language, has seen tremendous growth in the application of scientific data visualization in the last decade. Science-art collaborations become increasingly vital in creating new ways of popularizing geoscience. Here we present our recent immersive science-art interactive work titled 19 HZ, which explores the tectonic evolution and shaping of the deep sea through the visualization of submarine seismic data. The deep oceans were assumed to be quite silent. However, as more and more submarine monitoring experiments have been carried out, a hidden soundtrack under the sea was revealed, composed by marine animals like fish and mammals, and a number of natural phenomenons like submarine earthquakes and volcano activities, as well as human activities like ship-tracks. Our team (Deep Sea Light, DSL) has been working on the auralization and visualization of submarine seismic data, which offers a great opportunity to explore the dynamic world of deep oceans. Using seismic stations, we have successfully detected the activities of earthquakes, volcano eruption, and even fin whale songs. We further use the Audio Spectrum and the Touch Designer to visualize enormous soundtracks under the sea in 3D perspective and present different scenarios physically to the audience through artistic interactive devices. Under the lens of the ocean soundscape, our project will make the ambient deep-sea world more accessible to the public and convey to them how humans should listen to and understand the submarine world reverently. 
Rapid gas measurements in volcanic plumes with UAVs: online and offline measurements of various trace gases with light UAVs
Authors: Karbach Niklas , Geil Bastien , Blumenroth Jonas , Bozem Heiko , von Glahn Christian , Hoor Peter , Bobrowski Nicole , Hoffmann Thorsten
Published: February 2023

To protect people and infrastructures in the immediate vicinity of active volcanoes, monitoring the gas composition of the emitted plume is crucial. In order to react quickly to sudden changes in this composition, frequent measurements are key, as different ratios like the halogen/sulfur or the CO2/SO2 ratio can give hints on changing volcanic activity due to their different solubility in magma.   However, monitoring the chemical composition of the volcanic plume is not an easy task, especially since stationary ground-based gas monitoring stations do not always measure the concentration in the plume, only under certain meteorological conditions, and remote sensing methods are not available for all gases of interest. In this case, human interaction is required to move the measurement equipment to the location of interest, which is close to the active vent. Not only does this pose a serious health risk, it is also burdensome, as the researcher must climb the volcano, take the measurements, climb back down, and analyze the results. This lengthy procedure can be sped up and facilitated by using lightweight drones to take the measurements. Sensors and various other instruments, such as miniaturized alkaline traps or impregnated syringe filters that employ an electrophilic addition to a double bond to selectively absorb halogen species in the oxidation states -1, ±0 and +1, can be mounted on the drone and controlled via a radio link to a ground station. The online results can then be used during the flight to locate the plume to ensure efficient sampling with the absorbers. The landing site of the drone is usually located far away from active vents, which significantly reduces health hazards and speeds up the process.This poster presents such a drone with its advanced sensor system and absorbers for the determination and quantification of CO2, SO2, acidic gases and halogen species and its deployment during a measurement campaign on Etna in July 2022.
Viscosity of crystal-free silicate melts from the active submarine volcanic chain of Mayotte
Authors: Chevrel Oryaëlle , Verdurme Pauline , Le Losq Charles , Pannefieu Salomé , Médard Etienne , Berthod Carole , Komorowski Jean-Christophe , Bachèlery Patrick , Neuville Daniel R. , Gurioli Lucia
Published: February 2023

Following an unprecedented seismic activity that started in May 2018, a new volcanic edifice, Fani Maoré, was constructed on the ocean floor 50 km east of the island of Mayotte (Indian Ocean). This volcano is the latest addition to a submarine volcanic chain characterized by an alkaline basanite-to-phonolite magmatic differentiation trend. Here, we performed viscosity measurements on five silicate melts representative of the East-Mayotte Volcanic Chain compositional trend: two basanites from Fani Maoré, one tephri-phonolite and two phonolites from different parts of the volcanic chain. A concentric cylinder viscometer was employed at super-liquidus conditions between 1500 K and 1855 K, and a creep apparatus was used for measuring the viscosity of the undercooled melts close to the glass transition temperature in the air. At super-liquidus temperatures, basanites have the lowest viscosity (0.11 to 0.99 log10 Pa⸱s), phonolites the highest (1.75 to 3.10 log10 Pa⸱s), while the viscosity of the tephri-phonolite falls in between (0.89 - 1.97 log10 Pa⸱s). Viscosity measurements at undercooled temperatures have only been performed for one phonolite melt because Raman spectroscopy showed nanolites within the basanite and tephri-phonolite glass samples. The phonolite has a viscosity of 10.19 to 12.30 log10 Pa⸱s at 1058 to 986 K. Comparison with existing empirical models revealed discrepancies up to 2.0 log units with our experimental measurements. This emphasizes (i) the lack of data falling along the alkaline basanite-to-phonolite magmatic differentiation trend to calibrate empirical models, and (ii) the complexity of modeling the variations in viscosity as a function of temperature and chemical composition for alkaline magmas. The presented new measurements indicate that, at eruptive temperatures between 1050 °C and 1150 °C, the anhydrous, crystal- and bubble-free basanite melt is very fluid with a viscosity around 2.6 log10 Pa⸱s whereas the anhydrous phonolite crystal- and bubble-free melt at eruptive temperatures ranging from 800 to 1000 °C has a viscosity around 6 - 10 log10 Pa⸱s. These new viscosity measurements are essential to define eruptive models and to better understand the storage, transport and ascent dynamics of Comoros Archipelago magmas, and of alkaline magmas in general, from the source to the surface.
Rock slope failure evolution towards a sensitive close-to-failure system
Authors: Leinauer Johannes , Dietze Michael , Knapp Sibylle , Jokel Maximilian , Barbosa Natalie , Scandroglio Riccardo , Krautblatter Michael
Published: February 2023

Rock slope instabilities cause significant risk in populated alpine areas. To anticipate the final failure, a detailed understanding of the preparatory process dynamics including all potential promoting and triggering factors is needed. While standard external and internal drivers are known, measured evidence and a quantification of their relevance at a specific site is often lacking.Here, we present the evolution of the imminent Hochvogel summit failure (200,000–600,000 m³) over multiple decades towards the current highly sensitive system. We identified the three most relevant potential drivers at the Hochvogel instability: (i) earthquakes, (ii) seasonal and short-term meteorological effects and (iii) increasing internal stress. To quantify these, we use diverse sources of information. Earthquake catalogues and the records of the regional seismic broadband stations help to constrain known historical rock fall events at the Hochvogel. The effect of precipitation events, snowmelt and temperature is quantified by the analysis of high-resolution crack opening and rain data of the last four years. Finally, we exploit the record of our local seismic network to reveal internal rock bridge failures, rock fall activity in the flanks and the seismic stressing of the instable mass due to local earthquakes.The current process dynamics prove a close-to-failure status of the instability. The combination of historic records and high-resolution real-time data not only makes the Hochvogel a benchmark site for alpine hazard early warning but also enables the comprehensive definition and quantification of its relevant drivers. This will improve the global understanding of rock failure dynamics and so the anticipation ability for instable rock slopes.
Variability of North Atlantic Water Mass Properties along Western Boundary and Interior Pathways
Authors: Fortin Anne-Sophie , Lozier Susan
Published: February 2023

The Atlantic Meridional Overturning Circulation (AMOC) exports cold, fresh, dense waters formed in the subpolar North Atlantic to equatorward latitudes along the western boundary and interior pathways. The properties of the water formed in the North Atlantic vary from year to year, however the strength and time scale for the downstream communication of this variability is still unclear. While several past studies have focused on tracking specific property anomalies, particularly from the Labrador Sea, we approach our study by investigating property variance downstream of the water mass source region. In effect, we aim to understand the downstream memory of water mass property variability in the North Atlantic along western boundary and interior pathways. To do so, we analyze hydrographic properties on neutral density isopycnal surfaces in the subpolar North Atlantic and along the western boundary and interior pathways with two reanalysis products from the Met Office, the hydrographic dataset (EN4) and ensemble prediction system (GloSea5), over their overlapping time period (1993-2019). Our results show different patterns of downstream variance for the interior compared to the western boundary, which we interpret in terms of known circulation features in the deep North Atlantic and what we have learned from past Lagrangian studies.