bluuebunny/crossref_metadata_2025 huggingface dataset:
What makes a fire grow extremely large?
Authors: Scholten Rebecca , Banerjee Tirtha , Chen Yang , Desai Ajinkya , Liu Tianjia , Morton Douglas , Veraverbeke Sander , Randerson James
Published: March 2024

Wildfires are an important disturbance in global ecosystems and are a critical driver of trends in the land carbon budget. Fire is an extreme phenomenon, with the largest burned area often occurring during extreme fire seasons generating large fires. Days with fire conditions conducive to fire ignition and spread are increasing in a warming climate in many regions of the world, contributing to increases in fire occurrence and annual burned area. However, the climate, fuel, and weather conditions that lead to extremely large fires in different biomes are poorly understood.Here, we explore the temporal evolution of extremely large fires in temperate and boreal regions using new satellite-derived fire event tracking datasets optimized to match higher resolution time series of fire progression from aircraft and other sources. We aimed to understand the specific environmental conditions required for the development of a large fire. Our analysis revealed a disproportionate impact of multiple fire ignitions in creating large fires through merging. Our findings suggest that the largest fires in both biomes may be commonly created through multiple fires growing together. We hypothesize that a combination of physical and anthropogenic factors may accelerate merging, making these fires extremely difficult to contain and more robust to environmental controls regulating extinction. In our analysis, we use the Fire Events Database, the Arctic-boreal Fire Atlas, and GOFER, which enable attribution of ignition sources. Our analysis may contribute to an improved understanding of the influence of large-scale lightning storms in creating extremely large and destructive fire events.
Investigating heatwaves/droughts and convective precipitation extremes using compact descriptions of spatio-temporal fields
Authors: Szemkus Svenja , Friederichs Petra
Published: March 2024

The detection of local climate change signals, in particular those related to extreme events, is challenging due to the large internal variability of the climate system. The BMBF-funded project ClimXtreme Module B-CoDEx focuses on improving the signal-to-noise ratio of climate change signals in extreme weather events using innovative data compression methods.This study uses principal component analysis (PCA) for spatial extremes (Cooley and Thibaud, 2019) to analyse heatwaves and droughts over the northern hemisphere. An extremal pattern index (EPI) is introduced as an integrative measure of the intensity and spatial extent of an extreme heat anomaly. Its bivariate extension is used to account for simultaneous spatial extremes in two variables. EPI provides us with a compact description of heatwaves. We see, for example, that preceding precipitation deficits significantly influence the development of heatwaves, and that heat waves often coincide with instantaneous short-term droughts. To investigate extreme hourly precipitation, a scale-dependent decomposition using the dual-tree wavelet transform is proposed, as described e.g. in Buschow and Friederichs (2021). For this study, we rely on reanalysis data (COSMO-REA6, CERRA) over Germany. A comparison of the two datasets regarding their representation of large- and small-scale events shows significant differences, especially for the small-scale events. Furthermore, we apply established methods to perform a scale-dependent detection of extreme precipitation and to reveal trends that are hidden by variability on other scales. 
Microphysics of Europa’s surface with Galileo/NIMS data
Authors: Cruz Mermy Guillaume , Schmidt Frederic , Andrieu François , Cornet Thomas , Belgacem Ines
Published: March 2024

Europa’s surface is one of the youngest in the solar system. The Jovian moon is believed to hide a global liquid water ocean under its icy crust [1] and is exposed to intense space weathering due to the continuous bombardment by electrons and ions from Jupiter’s magnetosphere [2]. To understand the processes governing the evolution of the surface it is necessary to finely characterize the microphysics of the ice (composition via endmember volume abundance, grain size and surface roughness). However, the majority of the previous studies [3,4] do not allow to constrain precisely these parameters. Here we report the use of a radiative transfer model [5] in a Bayesian MCMC inference framework [6,7] to retrieve microphysical properties of Europa's surface using the Galileo Near-Infrared Mapping Spectrometer (NIMS) hyperspectral data [8]. We present the analysis of a calibrated spectrum of a dark lineament from the trailing Anti-jovian hemisphere. The estimated signal-to-noise ratio (SNR) is between 5 and 50, we mainly focus on the 1.0-2.5 µm region for which the SNR is higher with an uncertainty on the absolute calibration up to 10% [8]. A first work has allowed us to test all combinations of 3, 4 and 5 endmembers from a list of 15 relevant compounds [9]. We were able to test over 5,000 combinations and show that some compounds appear necessary to reproduce the observation, such as water ice and sulfuric acid octahydrate, in agreement with previous studies [3,4,10]. However, adding either hydrated sulfates or chlorine salts produces results substantially similar [9]. Here we present a follow-up study in which we focus on the few acceptable combinations identified by our Bayesian inversions and we analyze the results in terms of grain size and surface roughness. We show that the grain size of the mandatory endmembers is well constrained and similar from one combination to another [11]. The macroscopic roughness is however poorly constrained [11], as expected. Thanks to numerical optimizations we are able to invert independently every spectel of a NIMS hyperspectral cube with the bayesian MCMC algorithm. From this result, we present maps of microphysical properties on an entire hyperspectral image of a dark lineament. References: [1] Pappalardo, R. et al. (1999) JGR. [2] Carlson, R. W. et al. (2005) Icar. [3] Ligier, N. Et al. (2016) The Astr. Jour. [4] King, O. Et al. (2022) PSS. [5] Hapke, B. (2012). Cambridge Univ. Press. [6] Cubillos, P. et al. (2016), The Astr. Jour. [7] Braak, C. J. F. (2008), Stat & Comp. [8] Carlson, R. et al. (1992) ed. C. T. Russell. [9] Cruz-Mermy, G. (2022) Icarus. [10] Mishra, I. et al. (2021) Planet. Sci. [11] Cruz-Mermy, G. (2024) In prep.
Estimating the Climate Efficacy of Contrail Cirrus on Surface Temperature
Authors: Bickel Marius , Ponater Michael , Burkhardt Ulrike , Righi Mattia , Hendricks Johannes , Jöckel Patrick
Published: March 2024

So far, the various components contributing to the global climate impact of aviation were mostly quantified and ranked on the basis of radiative forcings. However, regarding for example the Paris Agreement, the temperature change at Earth’s surface is the main target parameter, for which radiative forcing is only a proxy. A specific climate sensitivity parameter for contrail cirrus has, so far, not been established.Here we close this gap for contrail cirrus with specially designed global climate model simulations, equipped with a coupled mixed layer ocean to determine the corresponding surface temperature change. For the first time the climate sensitivity and efficacy parameters were calculated for contrail cirrus. The efficacy of contrail cirrus to warm the Earth’s surface is found to be 62% smaller compared to CO2 in the effective radiative forcing framework. That means that radiative forcings of same magnitude result in a much weaker surface warming for contrail cirrus than for CO2. The origin of the reduced efficacy can be explained in detail by analyzing the related Feedback processes. An opposing response of the natural clouds (even in sign), with decreasing resp. increasing low- and mid-level clouds in case of CO2 resp. contrail cirrus was found to be the main reason. In addition, a more negative Lapse-Rate Feedback was found for contrail cirrus, originating from a non-homogeneous vertical warming, with the largest temperature increase directly below contrail cirrus and decreasing in strength toward Earth’s surface.The reduced contrail cirrus efficacy substantially affects contrail cirrus mitigation concepts when using climate metrics based on surface temperature change (e.g. GTP or ATR). Therefore, re-routing aiming for contrail cirrus reduction, but leading to an increased fuel consumption and additional CO2 emissions might be much less effective than currently assumed.
Forest traits from PRISMA spaceborne imagery
Authors: Tagliabue Giulia , Panigada Cinzia , Savinelli Beatrice , Vignali Luigi , Gallia Luca , Gentili Rodolfo , Colombo Roberto , Rossini Micol
Published: March 2024

Forest ecosystems, spanning approximately one-third of the Earth's landmass, play a crucial role in providing essential ecosystem services. However, their extension and condition are under threat due to the impacts of climate change. While remote sensing holds the potential to assess the condition and functionality of global forests, challenges in methodology and technology hinder the accurate quantitative estimation of forest traits from spaceborne observations. The emergence of new-generation satellites and advanced retrieval techniques offers the prospect of overcoming these obstacles, yet the potential of both the data and models requires further evaluation. In this contribution, we focused on retrieving forest traits from PRISMA hyperspectral spaceborne imagery employing machine learning regression models as well as hybrid approaches. The area we selected for this study is the Ticino Park, a mid-latitude forest located in northern Italy along the Po river. We conducted an intensive field campaign in the park in the summer of 2022 in conjunction with four PRISMA overpasses to collect trait samples for the calibration and validation of the retrieval schemes. The results obtained highlighted the capability of PRISMA images and retrieval models to precisely quantify Leaf Area Index (LAI) (R2=0.91, nRMSE=8.3%), Leaf Water Content (LWC) (R2=0.97, nRMSE=4.7%) and Leaf Mass per Area (LMA) (R2=0.95, nRMSE=5.6%) in forest ecosystems. Less performing but still promising results were obtained for Leaf Chlorophyll Content (LCC) (R2=0.44, nRMSE=18.3%) and Leaf Nitrogen Content (LNC) (R2=0.63, nRMSE=14.2%). The comparison of the trait values in June and early September revealed a significant decline in both leaf biochemistry and LAI, which can be traced back to the stress induced in the Ticino Park by the severe drought that hit Europe in the summer of 2022. This underscores the valuable role of hyperspectral spaceborne imagery and new generation models for monitoring forest conditions.
Modelling the formation and  evolution of solar wind microstreams:from coronal plumes to propagating Alfvénic velocity spikes.
Authors: Gannouni Bahaeddine , Réville Victor , Rouillard Alexis
Published: March 2024

Our research delves into solar wind's mesoscale features known as microstreams—periods of heightened speed and temperature lasting hours. Initially observed in Helios and Ulysses data, they're now prevalent in the 'young' solar wind by Parker Solar Probe and Solar Orbiter. Recent findings unveil microstreams' carriage of abundant Alfvénic perturbations—velocity spikes and magnetic switchbacks.Employing a high-resolution 2.5 MHD model, we scrutinize the genesis of microstreams from emerging bipoles interacting with the ambient corona. Our simulations reveal the tearing-mode instability, forming plasmoids released into the solar wind. Our domain spans the lower corona to 20 Rs, enabling observation of plasmoid formation and their evolution into Alfvénic spikes (Gannouni et al. 2023). The magnetic emergence rate modulates microstream characteristics.Additionally, 3D MHD simulations explore intermittent interchange reconnection in a 24x24x30Mm domain with a flux emergence rate of 1.38G/s. Reconnection spawns plasma jets and twisted magnetic field bundles, releasing hot plasma into the solar wind, inducing propagating waves and twists along magnetic field lines.
Long-term vegetation development in context of morphodynamic processes since mid-19th century
Authors: Ramskogler Katharina , Altmann Moritz , Mikolka-Flöry Sebastian , Tasser Erich
Published: March 2024

The availability of comprehensive aerial photography is limited to the mid-20th century, posing a challenge for quantitatively analyzing long-term surface changes in proglacial areas. This creates a gap of approximately 100 years, spanning the end of the Little Ice Age (LIA). Employing digital monoplotting and historical terrestrial images, our study reveals quantitative surface changes in a LIA lateral moraine section dating back to the second half of the 19th century, encompassing a total study period of 130 years (1890 to 2020). With the long-term analysis at the steep lateral moraines of Gepatschferner (Kauner Valley, Tyrol, Austria) we aimed to identify changes in vegetation development in context with morphodynamic processes and the changing climate.In 1953, there was an expansion in the area covered by vegetation, notably encompassing scree communities, alpine grassland, and dwarf shrubs. However, the destabilization of the system after 1980, triggered by rising temperatures and the resulting thawing of permafrost, led to a decline in vegetation cover by 2020. Notably, our observations indicated that, in addition to morphodynamic processes, the overarching trends in temperature and precipitation exerted a substantial influence on vegetation development. Furthermore, areas with robust vegetation cover, once stabilised, were reactivated and subjected to erosion, possibly attributed to rising temperatures post-1980.This study demonstrates the capability of historical terrestrial images to enhance the reconstruction of vegetation development in context with morphodynamics in high alpine environments within the context of climate change. However, it is important to note that long-term mapping of vegetation development through digital monoplotting has limitations, contingent on the accessibility and quality of historical terrestrial images, as well as the challenges posed by shadows in high alpine regions. Despite these limitations, this long-term approach offers fundamental data on vegetation development for future modelling efforts.
An analytical tool for estimating fault slip probability for CO2 storage resources under pressure constraints 
Authors: Kivi Iman R. , De Simone Silvia , Krevor Samuel
Published: March 2024

The majority of pathways toward net-zero CO2 emissions propose carbon capture and storage (CCS) at rates of several gigatonnes per year by mid-century. However, there are limits on the rates at which storage resources can be used. In addition to the total storage resource, constraints are imposed by reservoir injectivity and the possibility of triggering large earthquakes by injection-induced overpressure. Such dynamic constraints are rarely considered in the assessments of available resources and possible CCS deployment rates. In this work, we have extended an open-source tool, named CO2BLOCK, from calculating reservoir pressurization during CO2 injection to additionally estimating the probability of fault slip in the region. This provides a computationally efficient methodology for screening dynamic CO2 storage resources. The code features a deterministic hydrogeology module that employs analytical solutions of radial, multiphase flow for a single site with time-varying injection rates and the superposition principle to calculate the spatiotemporal evolution of pore pressure in multisite, basin-scale injection scenarios. The calculated overpressure is used to analyze the slip tendency of the faults imported or randomly distributed across the basin. A probabilistic geomechanical module runs Monte-Carlo simulations to generate cumulative distribution functions of slip probability as a function of pore pressure changes for each fault from statistical ensembles of uncertain parameters including the state of stress and fault attributes and frictional strength. A combination of the two modules yields the evolution of fault slip probability as a function of time through the project life. The proposed approach allows for optimizing large-scale CCS project designs for the number and spacing of injection sites to return maximum storage rates and capacities while maintaining the risk of induced seismicity at a low level. The application of CO2BLOCK could assist in developing more realistic representations of CCS scale-up potential and the subsurface resource use in different climate change mitigation pathways. 
Mapping Tree Mortality at Global Scale Using Sentinel-2
Authors: Mosig Clemens ,   co-authors
Published: March 2024

Excess tree mortality in the wake of climate extremes has been observed globally. However, we still lack precise data on mortality at global scale to understand respective drivers and spatiotemporal dynamics. The Sentinel-2 satellite fleet, equipped with the MultiSpectral Instrument (MSI), covers the entire earth on average every five days at spatial resolutions ranging from 10 m to 60 m. Mapping tree mortality from Sentinel-2 globally in diverse ecosystems requires equally diverse reference data. Using globally distributed high-resolution aerial orthoimagery reference data and artificial intelligence methods, we can translate spectral signatures of remote sensing into deadwood. Specifically, in this study we show how to predict the share of standing deadwood for a 10 m pixel in a specific year. The method takes into account temporal patterns, spatial context, as well as all Sentinel-2 spectral bands. This will enable us to map tree mortality globally at a new level of precision.
Introducing biofouling effects in a lagrangian-tracking particle 3d model
Authors: Buñuel Arnau
Published: March 2024

One of the most challenging problems in the study of oceanographic pollution is the fate of macroplastics. A good understanding of the litter pathway since the moment they enter the sea is essential to reduce environmental hazard, also to withdraw them before they become microplastics. For this purpouse we use a Lagrangian tracking model to evaluate the dispersion and accumulation in coastal zones of marine macroplastics.\\Our 3-dimensional model, named MOHID-Lagrangian tool, is prepared to estimate particle trajectories given a hydrodinamic field. Also it includes windage effects, coastal beaching or waves effect through Stokes drift. To take into account the effects of algae and mollusc attaching to our lagrangian particles we added a biofouling term. This term modify the sinking velocity of particles by increasing its density. We relate the variation of this density to the attached biofilm growth, interpreting this as a function of ambient algal concentration, encounter rate and other algae properties.
Impact of grain size distribution and wind velocity on the armoring layer of aeolian megaripples
Authors: saban lior , Katra Itzhak , Kroy Klaus , Yizhaq Hezi
Published: March 2024

Aeolian megaripples are a landscape formation widespread on Earth and Mars that develop in sand surfaces with a bimodal grain size distribution of coarse and fine grains. Megaripples are relatively high with a greater wavelength compared with normal sand ripples. Previous works provided quantitative information on the morphological characteristics, development, flattening mechanisms, longevity, and transverse instability of megaripples. It has been hypothesized that the sorting process of the initial bimodal size distribution is a key factor in megaripple formation. In this study, we experimentally explored the impact of the grain size distribution on the crest characteristics under different wind velocities in a boundary-layer wind tunnel. The controlled experiments allowed measurements of sand fluxes, particle size distributions, and ripple morphology by a laser module. The results reveal links between the rate of growth of the incipient megaripples, ripple height, and the armoring layer thickness and composition to wind velocity. The ripples grow higher as the wind velocity increases, and the armoring layer is thicker up to a certain wind velocity when erosion of the crest starts. In addition, the correlation between the armoring layer's nonlinear thickening rate and the ripples growth rate seems to indicate a fundamental connection between ripples height and the formation of the armoring layer, which is crucial for megaripples formation.
The effects of extreme rainfall trends on compound flood risk: A case study over Greater Boston
Authors: Emmanouil Stergios , Langousis Andreas , Perry Elizabeth , Madaus Luke , Hacker Joshua , Anagnostou Emmanouil N.
Published: March 2024

Climate adaptation strategies and vulnerability assessments over coastal areas require proper modeling of the interplay and nonstationary nature of the physical processes involved in compound flooding. As a result of the reported upward trajectories of rainfall intensity over the Contiguous United States, flood risk estimates are also expected to vary. However, given the systematic and random inconsistencies of traditional extreme rainfall estimation approaches and the increased uncertainty surrounding climate model projections, the effects of climate change on the estimation of flood risk from compound hazards remains an open question. In this effort we aim to: (a) combine the observed rainfall intensity trends from the past 40 years (i.e., from 1979 to 2020; see also Emmanouil et al., 2022) across various scales of temporal averaging, with storm surge and antecedent streamflow conditions, to estimate how flood inundation levels evolve, and (b) assess the effects of those trends on flood risk estimation within areas affected by compound hydrological events. In doing so, we use hydrodynamic simulations of reported flood occurrences over the Greater Boston area (MA, United States) for a period of 20 years (i.e., from 2000 to 2019), along with the parametric modeling scheme proposed by Emmanouil et al. (2023). The latter has been shown to properly weight and link the exceedance probabilities of the main flood-driving mechanisms to the return periods of the maximum inundation levels, thus providing a sufficient depiction of the conditions over the studied domain and allowing for estimation beyond the range covered by the available simulations. Assuming that the dependence structure of the driving mechanisms remains time-invariant, our findings aim to enhance the understanding of how flood risk from compound hazards has been affected by extreme rainfall trends induced by the changing climatic conditions and, therefore, support decision-making on the design and protection of critical infrastructure.ReferencesEmmanouil, S., Langousis, A., Nikolopoulos, E. I., & Anagnostou, E. N. (2022). The Spatiotemporal Evolution of Rainfall Extremes in a Changing Climate: A CONUS‐Wide Assessment Based on Multifractal Scaling Arguments. Earth’s Future, 10(3). https://doi.org/10.1029/2021ef002539Emmanouil, S., Langousis, A., Perry, E., Madaus, L., Hacker, J., and Emmanouil, E.N. (2023) Decomposing the effects of compound mechanisms on flood risk estimation for urban environments: A case study over Greater Boston, UrbanRain23, 12th International Workshop on Precipitation in Urban Areas, Pontresina, Switzerland, 29 November – 2 December 2023.
Identification of self-sealing processes in claystone-bentonite mixtures by digital image correlation
Authors: Stoppe-Struck Nina , Langhorst Gerrit , Laurich Ben
Published: March 2024

Processed claystone-bentonite mixtures are considered as potential backfill material for drifts and shafts in deep geological high-level radioactive waste repositories, foremost due to their strong self-sealing and radionuclide retardation properties. Self-sealing is mainly facilitated by the materials’ swelling capacity when getting in contact with water from the surrounding host rock. A timely sealing of fractures and voids is of high significance in the isolation of radioactive nuclides. However, a specific duration for a fracture to close upon wetting, the exact processes involved (next to interlayer water uptake in smectite) and the necessary width of a swelling zone are unclear.
In order to investigate the self-sealing, past research focused almost exclusively on the (free) swelling capacity of bentonites or claystone and hence neglected other processes for permeability reduction upon saturation. More recently, µCT techniques have been used to overcome the lack of direct evidence of fracture closure in clay rocks and to provide a mechanistic understanding of self-sealing processes.
To obtain a deeper understanding of the self-sealing behavior of crushed claystone-bentonite mixtures, we map the swelling induced strain in a simple 2D approach using digital image correlation (DIC). For this purpose, an artificial fracture in specimen with different claystone/bentonite ratios but defined initial bulk density and initial water content is saturated and a camera taking pictures of the sample surface every two minutes documents the wetting front as well as the developing strain. For DIC the free software GOM is used that allows tracking strains beneath the order of pixel resolution, which in our setup is about 10 µm.
In previous experiments with Opalinus clay localized tiny fissures appeared when the wetting front spread into the specimen and contributed to the closure of an a-priori induced fracture. Further, a straining zone, advancing ahead of the wetting front, lead to a more evenly volume expansion that finally closed not only the artificial fracture but also the newly formed tiny fissures.
In general, we assume a somehow similar self-sealing behavior in the claystone/bentonite mixtures, but we expect different responses depending on the claystone/bentonite ratio. Additional tests (e.g. wettability, BIB-SEM, zeta potential) could be used to understand the observed behavior.
Dissolved Helium Estimation in the Casaglia Geothermal Reservoir: a Geological Active Area
Authors: Balzan Silvia , Caracausi Antonio , Buttitta Dario , Coltorti Massimo
Published: March 2024

Deep fluids and their isotopic signatures, especially He due to its inert nature, are powerful tools for investigating the processes occurring within the crust, as fluids- rocks interaction, storage and transfer mechanism. Numerous studies have emphasized the connection between local seismicity leading to widespread microfracturing processes and an increase in the release of 4He that was previously trapped within minerals. Thus, the episodic degassing of 4He through the crust can sustain the excess of He in natural reservoirs respect to the steady-state diffusion processes.The aim of this study is to determine whether the quantity of He stored in the geothermal reservoir of Casaglia, an exploited mining concession located at the top of the Dorsale Ferrarese, which is a seismically active area in the Emilia-Romagna Region, can be attributable to long lasting diffusion process and to highlight the contribution that these geochemical approach can provide to enhance the understanding of underground phenomena, revealing changes in the stress field and related earthquakes.We collect fluids from the reservoir and we analyse their chemical and isotopic composition. In particular, the helium abundance is very high, up to 3956 ppm. It is also characterised by a 3He/4He ratio of 0.02Ra, clearly indicating that the dominant component is attributable to radiogenic 4He produced by U and Th decay in the crust.The measured total amount of He stored in Casaglia reservoir vary from 107 to 105 mol/km3 rocks, depending on the porosity. This data has been compared with the expected amount of helium accumulated over time under steady-state crustal degassing, which has been computed taking into account the local stratigraphy, the age of formation of the anticline hosting the reservoir (Upper Pliocene - Pleistocene) and the abundances of U and Th in the rocks. The preliminary result shows that there is at least an order of magnitude difference between the experimental evidence and the calculated data in terms of the amount of helium accumulated in the reservoir, even under the most conservative conditions, assuming that there are no losses of 4He due to advection or diffusion processes.Our study demonstrates that the in-situ production of 4He in the crust and a long-lasting diffusion through the crust are not the main processes that rule the He degassing in the Casaglia reservoir but alternative and episodic processes controlling the transport mechanism act simultaneously.Finally, exploiting the established association between rock deformation and helium degassing, monitoring helium flux in active tectonic settings may yield valuable insights into variations in the stress field and the occurrence of seismogenic processes. This aspect highlights the applicability of our findings in contributing to the understanding of underground phenomena, emphasizing the potential of geochemical approaches to reveal changes in the stress field and seismic activities.
Geospatial Foundation Models for Efficient Retrieval of Remote Sensing Images
Authors: Brunschwiler Thomas , Blumenstiel Benedikt , Moor Viktoria , Kienzler Romeo
Published: March 2024

This work explores the potential of content-based image retrieval to enable efficient search through vast amounts of satellite data. Images can be identified across multiple semantic concepts without needing specific annotations. We propose to use Geospatial Foundation Models (GeoFM), for remote sensing image retrieval and evaluated the models on two datasets. The GeoFM named Prithvi uses six bands and outperforms other RGB-based models by achieving a mean Average Precision of 61% on ForestNet-4 and 98% on BigEarthNet-19. The results demonstrate that the model efficiently encodes multi-spectral data and generalizes without requiring further fine-tuning. Additionally, this work evaluates three compression methods: i) binary embeddings, ii) trivial hashing, and iii) locality-sensitive hashing. Compression with binarized embeddings isthe best option for balancing retrieval speed and accuracy. It matches the latency of much shorter hash codes while maintaining the same accuracy as floating-point embeddings.
Recession discharge from compartmentalized bedrock hillslopes: hydrogeological processes and solutions for model calibration 
Authors: Roques Clement , Abhervé Ronan , Marti Etienne , Cornette Nicolas , de Dreuzy Jean-Raynald , Rupp David , Boisson Alexandre , Leray Sarah , Brunner Philip , Selker John
Published: March 2024

Due to the difficulties of gathering relevant data of groundwater systems and the lack of fundamental physically-based understanding on the processes involved, the representation of groundwater flow heterogeneity in catchment- to regional-scale hydrological models is often overlooked. We often limit the representation of groundwater with simplified homogeneous and shallow aquifers where effective hydraulic properties are derived from global-scale database. This raises questions regarding the validity of such models to quantify the potential impacts of climate change, where subsurface heterogeneity is expected to play a major role in their short- to long- term regulation.We will present the results of a numerical modelling experiment designed to explore the role of the vertical compartmentalization of hillslopes on groundwater flow and recession discharge. We found that, when hydraulic properties are vertically compartmentalized, streamflow recession behaviour may strongly deviate from what is predicted by groundwater theory that considers the drainage of shallow reservoirs with homogeneous properties. We further identified the hillslope configurations for which the homogeneous theory derived from the Boussinesq solution approximately holds and, conversely, for those for which it does not. By comparing the modelled streamflow recession discharge and the groundwater table dynamics, we identify the critical hydrogeological conditions responsible for the emergence of strong deviations. We further present new solutions to better represent subsurface heterogeneity in catchment-scale models and calibrate hydraulic parameters that properly capture the groundwater and streamflow dynamics.
Machine learning based rapid earthquake characterization using PEGS in Alaska
Authors: Bletery Quentin , Juhel Kévin , Licciardi Andrea , Vallée Martin
Published: March 2024

A signal, coined PEGS for Prompt Elasto-Gravity Signal, was recently identified on seismograms preceding the seismic waves generated by very large earthquakes, opening promising applications for earthquake and tsunami early warning. Nevertheless, this signal is about 1,000,000 times smaller than seismic waves, making its use in operational warning systems very challenging. A Deep Learning algorithm, called PEGSNet, was later designed to estimate, as fast as possible, the magnitude of an ongoing large earthquake from PEGS recorded in real time. PEGSNet was applied to Japan and Chile and proved capable of tracking the magnitude of the Mw 9.1 Tohoku-oki and Mw 8.8 Maule earthquakes within a few minutes from the events origin times. Here, we apply this algorithm to a very well instrumented region: Alaska. We find that, applied to such a dense seismic network, the performance of PEGSNet is drastically improved, with robust performances obtained for earthquakes with magnitudes down to 7.8. The gain in resolution also allows us to estimate the focal mechanism of the events in real time, providing all the information required for tsunami warning within less than 3 minutes.
Multiple factors drive the infection rate in the progress of the COVID-19 pandemic
Authors: Sun Yelin , Shi Peijun
Published: March 2024

Although the World Health Organization has declared that the COVID-19 pandemic no longer qualifies as a global public health emergency, it still needs to review the response of society to the COVID-19 pandemic. Previous studies indicated that socio-economic status (SES) was linearly associated with the COVID-19 pandemic. However, this relationship may be more complex due to regional differences. Meanwhile, it needs to analyze the nonlinear impact of multiple factors on the infection rate. In the study, we analyzed the differences in infections among low, lower-middle, upper-middle and high SES group (LSG, LMSG, UMSG, and HSG, respectively), and considered the social and meteorological factors, revealing the effect and mechanisms of SES on infections. The results showed that the relationship between SES and infection rate was inverted U-shaped, especially in the first three phases. The contribution of meteorological factors to the infection rate first increased and then decreased. In the first phase, mask usage was the most important factor affecting the change in infection rate, with the contribution of 23.17%. In the second phase, temperature was the most important factor affecting the change in infection rate. In the third and fourth phases, vaccination was the most important factor. Furthermore, the nonlinear impact of multiple factors related to SES on the infections explains the complex relationship between SES and infections. The study argues for greater attention to countries with medium SES and the need for future targeted measures to cope with infectious diseases.
On the integration of ontological models of risk in artificial intelligence and machine learning applications to advance multi-hazard risk assessment
Authors: Pittore Massimiliano , Griffo Cristine , Mosca Alessandro , Ferrario Davide , Campalani Piero
Published: March 2024

Many areas of the world are prone to several natural hazards, with their occurrences possibly compounded, cascaded, or otherwise connected, either causally or across space and time, and effective risk reduction is only possible if all ensuing relevant threats are considered and analyzed. The examination of multiple hazards for the assessment of risk poses a range of additional challenges partly due to the differing characteristics of underlying processes, partly due to the broader range of consequences and the related risk-driving factors (e.g, exposure and vulnerability).Considering the increasing availability of data about some components of risk, in the past decade several frameworks and approaches including artifical intelligence and in particular machine learning algorithms have been proposed to support multi-hazard/multi-risk assessment studies.However, several challenges can be acknowledged that hinder the application of machine learning: the complex interplay among the risk components in multi-hazard contexts, for instance, along with the paucity of available quantitative information on impact (i.e., damage, loss) might impair the development of training datasets of adequate size and quality. Furthermore, information on multi-hazard risk is relying on heteogeneous data, often qualitative. Lastly, but not least, additional uncertainty is associated to the complexity and current lack of consensus in the conceptual definition of high-impact multi-hazard events by the different involved scientific as well as praxis-oriented communities.In this context, the use of ontologies and semantic data representations may prove useful to tackle the above-mentioned challenges. An ontology is a structured representation of shared knowledge about a specific domain, encoded in the form of axioms, natural language labels, synonyms, definitions and other types of annotation properties. Risk-oriented ontologies can be used for instance to provide a common operational basis to the basic underlying conceptual definition, to be agreed upon and shared across communities with different scientific background. Furthermore, ontologies can be used to access and exploit background knowledge in order to build better predictive models, expand or enrich feature engineering in machine learning or to constrain the search for a solution to an optimization problem (e.g., setting hard constraints based on logical inferences). Formal ontological representations can also provide a consistent support to the development of so-called explainable models, therefore controlling the unnecessary spread of "black box" models in sensitive operational environment such as, e.g., impact forecasting and early warning.
The role of tectonic, volcanic, and fluvial processes as controls of Neogene intermontane basin evolution in the western Colombian Andes
Authors: León Santiago , Faccenna Claudio , Conrad Ethan , Valencia Víctor A.
Published: March 2024

The sediment dispersal patterns at active orogens are highly sensitive to changes in the landscape configuration triggered by the combined effects of deformation, volcanism, and geomorphological processes. Hence, reconstructing source-to-sink systems provides valuable insights into the interplay between deep-seated and surface processes as controls of the coupled development of mountain ranges and intermontane sedimentary basins.The Oligocene-Miocene evolution of the Colombian Andes has been shaped by subduction tectonics and the collision of an oceanic terrane, which are linked to changes in the kinematics of crustal deformation and the tectono-magmatic history of continental arcs. Nevertheless, the combined effect of such processes on the growth of the Western and Central Cordilleras and the associated intermontane basins remains elusive.Here, we use a large dataset of detrital zircon U-Pb ages from Oligocene-Pliocene strata of intermontane basins of western Colombia, and available (bio)stratigraphic and structural constraints to reconstruct: i) the regional-scale configuration of source areas and accumulation settings, ii) the sediment routing systems, and iii) the history of basin connectivity. We interpret the sediment dispersal patterns as controlled by the pulsed uplift of the Central and Western Cordilleras linked to a syn- to post-collisional transpressional tectonic regime, and to changes in the drainage network driven by intra-basinal arc-related magmatic activity
An experimental study of high-alumina basalt differentiation and the effect of H2O and pressure on plagioclase – melt equilibria 
Authors: Melekhova Elena
Published: March 2024

Water-rich high-alumina basalts are widely implicated in models of subduction zone magma genesis and porphyry copper mineralisation, yet their phase relationships at high pressures have been very little studied since the pioneering work of Yoder and Tilley (1963). To fill this gap an experimental study has been carried out on water-saturated phase relationships of a high-alumina basalt (HAB) from St. Kitts, Lesser Antilles volcanic arc (Eastern Caribbean), in the pressure range 1.5 to 20 kbar. Experimentally produced glasses, mineral compositions and mineral assemblages match whole rock data of Lesser Antilles high-alumina basalts and high-alumina basaltic andesites, phenocryst assemblages and mineral chemistry. I show that the liquidus silicate mineral phase changes from olivine and plagioclase at low pressures, through clinopyroxene and amphibole at intermediate pressures, to garnet above 14 kbar. Experimentally produced mineral assemblages correspond well to plutonic xenolith found in Lesser Antilles and change from dunnite, and olivine and hornblende gabbro dominated lithology at pressure ≤ 10 kbar to hornblende pyroxenite, hornblendite and eclogite at pressures ≥ 10kbar.Melt compositions describe liquid lines of descent that resemble those of many magmatic arc sequences; only alumina shows any strong correlation with pressure. Water saturation (as determined by the difference method) is lower than predicted by most solubility models. The evolved melts generated at low crustal conditions from these experimental series do not resemble silicic melts associated with porphyry copper deposits.I also address the long-debated origin of high-An plagioclase (An > 90), which occurs in many volcanic and plutonic rocks associated with arc magmatism. Additional experiments on HAB at water-undersaturated and fluid-saturated experiments with 2M CaCl2 solution and CaCO3 have been carried out at 7 kbar to evaluate fluid composition and aH2O on An content of plagioclase. These experiments, combined with existing experiments on broadly basaltic compositions, demonstrate that high-An plagioclase (An ≥ 90) crystallises readily from fluid-saturated high-alumina basaltic melts at pressures of 1 to 10 kbars and temperatures 850 – 1100 ºC. However, the limit of An content produced by experiments is An96. Addition of CaCl2 to the fluid and CaCO3 to the system does not have a significant effect on An content. To produce plagioclase with An content more than 96 mol% a secondary process such as re-melting/re-crystallisation must be involved (Melekhova et al 2022).Melekhova E., et al. (2022) Journal of Petrology 63.5 (2022): egac033.
Intra-annual velocity variability extracted from multi-sensor and multi-temporal datasets produced by different processing chains
Authors: Charrier Laurane , Dehecq Amaury , Brun Fanny , Millan Romain , Beraud Luc , Ducasse Etienne , Rabatel Antoine , Copland Luc , Dow Christine
Published: March 2024

Ice velocity products with a sub-annual resolution are needed to better understand subglacial hydrology, glacier instabilities and glacier response to short-term events, such as calving or increased melt. Different processing chains are now releasing scene-pair velocities worldwide (ITS_LIVE, GOLIVE, RETREAT, PROMICE, MEaSUREs, Millan et al., 2019). Their temporal resolution is up to 2 days and their spatial sampling up to 50 m. However, analysing the sub-annual variability of glacier dynamics on a global scale remains challenging. Indeed, the amplitude of the velocity at high temporal resolution is frequently smaller than the uncertainty in many areas. In addition, the available datasets are complex to use because the velocities span different temporal baselines, are derived from images from different sensors, and are computed using different correlation and post-processing parameters. The methods developed to post-process ice velocities usually select only a subset of the datasets, require strong a priori knowledge of glacier velocities, remain sensitive to systematic errors and/or have not been validated for different glacier dynamics. Therefore, there is a need to develop and validate an operational method able to fully exploit the available ice velocity datasets in order to provide homogeneous and robust sub-annual velocity time series.Here, we propose a method based on the temporal closure of the displacement measurement network. To be robust to both systematic and random errors (e.g., temporal decorrelation and random noise), we invert the system using an iterative reweighted least square with a robust downweighting function. We propose a regularisation strategy that can account for different glacier dynamics (e.g., normal vs. surge flow). The performance of the method is evaluated using GNSS stations in the Yukon (Canada) and the European Alps. The resulting velocity time series have a homogeneous temporal sampling and reduced uncertainty (up to 60%). Annual velocity peaks are retrieved with a Mean Absolute Error in the order of 10 to 30 days, and 1 to 40 m/y. The results reveal the spatio-temporal propagation of annual velocity peaks and glacier surges along glacier centerlines. This method can be applied to any available dataset. The code will be published in a github repository.
 Permeability evolution of a fractured, porous and permeable sandstone at simulated georeservoir conditions
Authors: Fazio Marco , Sauter Martin
Published: March 2024

Bentheim sandstone is regarded as a conventional georeservoir rock even at great depth, due to its mineral composition, homogeneity, micro- and macrostructure. Therefore it has been extensively tested for a variety of applications to understand its physical and mechanical properties under changing environmental conditions. A recent study has shown how the simultaneous change of pressure, temperature and pore pressure, therefore recreating environmental conditions at selected depths, affects the evolution of permeability at depths, both when the rock is buried and when the rock is exhumed. The interaction between those variables has a complex effect on the permeability of Bentheim Sandstone, which could not have been identified by assessing individually the role of a variable. These results show that the permeability of such rock could be overestimated with classical studies and highlight the importance of investigating rock mechanical and hydraulic properties at georeservoir conditions. These experiments have been performed on intact samples.However, rocks at depth contain fractures and faults, which may alter the interconnectivity of the pore space, hence the permeability of the rock itself. The deformation and failure of Bentheim Sandstone at high strain resulted in permeability loss due to the formation of comminuted material and grain crushing which lowered the pore space interconnectivity. No fractured sample has been tested under simultaneously changing environmental conditions. To fill this gap, we replicate the experimental procedure used to test intact samples of Bentheim sandstone, both under simultaneously changing conditions and under a sequential variation of different variables, after the sample has been brought to failure. Our goal is to understand the importance of fractures on the permeability evolution at different simulated depths.