bluuebunny/crossref_metadata_2025 huggingface dataset:
Linking sedimentary imprints of storms and tsunamis with numerical wave modeling: A case from a coastal lagoon in the Lesser Antilles (Saint Martin)
Authors: Fabbri Stefano C. , Sabatier Pierre , Paris Raphaël , Falvard Simon , Feuillet Nathalie , Lothoz Amélie , St-Onge Guillaume , Gailler Audrey , Cordrie Louise , Arnaud Fabien , Biguenet Maude , Coulombier Thibault , Mitra Saptarshee , Chaumillon Eric
Published: March 2024

We examined sedimentary records in a coastal lagoon on Saint Martin Island in the Lesser Antilles to identify and characterize extreme-wave events (EWEs), such as hurricanes and tsunamis. Employing a comprehensive approach involving sedimentological, geochemical, and radiocarbon dating analyses, complemented by X-ray computed microtomography (micro-CT) for examining sediment fabrics, we applied this multiproxy method to three oriented short sediment cores along a transect. This allowed us to identify sediment layers linked to both tsunami- and hurricane-induced EWEs. Five out of the seven EWEs were identified as paleo-tsunamis through their geochemical, sedimentary, and structural signatures. These five paleotsunamis were successfully dated over the last 3500 years, including the well-documented Pre-Columbian tsunami at approximately 1400 yrs CE and the transatlantic Lisbon tsunami at 1755 CE. This suggests a tentative local tsunami chronology of five well-documented events over the last 3500 years with a recurrence interval of 400 to 500 years.However, the most recent EWE corresponded to the powerful Category 5 Hurricane Irma in 2017. Over the last 150 years, another 14 less intense hurricanes impacted the island, leaving no sediment imprints in the lagoon. This finding is in line with most recent publications showing that tropical storm intensification rates have already changed as anthropogenic greenhouse gas emissions have warmed the globe (Garner, 2023).Furthermore, micro-CT-based sediment analysis provided a deeper understanding of the relationship between sediment fabric and tsunami wave dynamics. Therefore, we used the deposits of the Pre-Columbian tsunami and compared paleo-flow directions from micro-CT-derived fabric patterns to those from numerical tsunami models. The results that best explain the Pre-Columbian tsunami deposit emplacement are in line with a Mw 8.5–8.7 megathrust earthquake source located on the subduction interface at the Puerto Rico Trench, north of Anegada Island (Cordrie et al., 2022). Ultimately, integrating deposits of EWEs with numerical models is pivotal for devising effective hazard mitigation strategies tailored to vulnerable coastal communities.Cordrie, L., Feuillet, N., Gailler, A., Biguenet, M., Chaumillon, E., Sabatier, P., 2022. A Megathrust earthquake as source of a Pre-Colombian tsunami in Lesser Antilles: Insight from sediment deposits and tsunami modeling. Earth Sci Rev 228, 104018. https://doi.org/10.1016/j.earscirev.2022.104018Garner, A.J. Observed increases in North Atlantic tropical cyclone peak intensification rates. Sci Rep 13, 16299 (2023). https://doi.org/10.1038/s41598-023-42669-y
The High-Energy Tail of Energetic Electron Precipitation: Case studies
Authors: Nesse Hilde , Salice Josephine
Published: March 2024

Precipitating auroral, ring current, and radiation belt electrons will affect the ionization level and composition of the neutral atmosphere. Knowledge gaps remain regarding the frequency, intensity, and the energy spectrum of the Medium Energy Electron (MEE) precipitation (>30 keV). In particular, the understanding and predictive capabilities of the high-energy tail (>300 keV) are in general poor. This study estimates the loss cone electron fluxes from MEPED observations on board the POES/Metop satellites over a full solar cycle 2004-2014 to distinguish >30 keV events from >300 keV events. Data from the Northern and Southern Hemispheres (55-70oN/S) are combined in daily flux estimates. Flux peaks above the 90th percentile of the >30 kev flux are identified. The 33% highest and lowest associated responses in the >300 keV fluxes are labeled "E3 events" and "E1 events", respectively, resulting in 55 events of each type. Based on superposed epoch analysis, it is evident that high geomagnetic activity increases the probability of E3 events. More specifically, elevated solar wind speeds persisting in the recovery phase of a deep Dst trough appear characteristic of E3 events. Here, we test this assessment by examining solar wind parameters and geomagnetic indices for a selection of single events:E1 and E3 events with similar >30 keV flux strengths
The E1 event with highest >30 keV flux strength
The E3 event with the weakest >30 keV flux strength
The E1 event with the strongest Dst deflection
The E3 event with the weakest Dst deflection
Overview of Japan Coast Guard’s GNSS-A seafloor geodetic observation and data management
Authors: Nakamura Yuto , Ishikawa Tadashi , Watanabe Shun-ichi , Nagae Koya , Yokota Yusuke
Published: March 2024

The Japanese Archipelago lies along subduction zones, where megathrust earthquakes are known to occur repeatedly (e.g., Mw 9.0 2011 Tohoku-oki Earthquake). The source regions of such megathrust earthquakes mainly lie beneath the seafloor, making it necessary to monitor the crustal deformation not only on land but also on the seafloor. The Japan Coast Guard (JCG) has been conducting seafloor geodetic observation using the GNSS-Acoustic ranging combination technique (GNSS-A) since the early 2000s. By combining GNSS and underwater acoustic ranging, GNSS-A measures the absolute position of a seafloor benchmark in the precision of centimeters, which provides us fruitful information on the crustal deformation under ocean. JCG currently deploys 27 seafloor sites along the Japan Trench and the Nankai Trough named the Seafloor Geodetic Observation Array (SGO-A).JCG and the Univ. Tokyo group has been working on open data of GNSS-A. In the past, we have published the position time series data (Yokota et al. 2018), and the GARPOS software (Watanabe et al. 2020) which is used in our current routine analysis. Recently, we have been discussing on a standardized data format for GNSS-A in the task force of the Inter-Commission Committee on Marine Geodesy (ICCM) in the International Association of Geodesy. Currently, we are releasing the latest position time series data of each SGO-A site, and the GNSS-A observation dataset in the GARPOS data format (https://www1.kaiho.mlit.go.jp/chikaku/kaitei/sgs/datalist_e.html).
River long profile modelling since the Mid-Pleistocene for the Río Santa Cruz, Southern Patagonia.
Authors: Ruby Andreas , McNab Fergus , Schildgen Taylor , Wickert Andrew , Fernandes Victoria M.
Published: March 2024

Alluvial rivers connect sediment sources in mountain belts to depositional basins. They not only transport water and sediment, but also adjust to changing forcing conditions by aggrading or incising their beds, a process potentially recorded by fluvial terraces. The formation of stepped terrace sequences is commonly thought to be driven by cyclic changes in sediment and water supply, but may be modulated by rock uplift or sea-level changes.The Río Santa Cruz in Southern Patagonia, Argentina, flows ca. 250 km from its glacial headwaters in the Andes eastward to the Atlantic Ocean. There are no major tributaries or substantial anthropogenic impacts along its course. A set of at least six exceptional fluvial terraces stretches along ca. 230 km and rise up to 110 m above the river. Our preliminary 10Be cosmogenic nuclide exposure dates show that river incision began at ca. 1 Ma, and that terrace formation proceeded in roughly 100-ky intervals, suggesting control by orbital climate cycles, likely through their impacts on the sediment-to-water supply ratio. However, a step in the terrace age-elevation sequence between 700 and 300 ky points to a change in net incision rate at that time. Particularly at the upstream end of the river, terraces have been uplifted at a rate nearly twice as high compared to the rest of the river.While it is likely that multiple factors affected the evolution of the Río Santa Cruz over the last 1 Myr, the magnitude and spatial pattern of impacts from these different drivers is unclear. We apply a recent numerical model (GRLP), implemented here as a simple single-thread channel, to solve for the channel long profile evolution under different forcing scenarios. This approach allows us to test the impacts of individual, or combinations of, drivers on river-profile evolution.Our results suggest that Late Pleistocene 100 ky climate cycles have had the main impact on long profile evolution, especially along the upper 70 km of the river, with aggradation-incision cycles of up to an order of 10 m in magnitude. In contrast, sea-level change does not seem to influence significantly long profile evolution, as the exposed offshore slope does not change significantly compared to that onshore. To match the vertical distribution of terrace surfaces requires a long-term uplift rate of around 0.2 mm/yr, but with a hiatus between 700 and 300 ky. To accurately simulate the full terrace sequence, enhanced uplift is required upstream, decreasing exponentially towards the middle reaches.
Modeling the Cassini States of large icy satellites with an angular momentum approach
Authors: Coyette Alexis , Baland Rose-Marie , Van Hoolst Tim
Published: March 2024

It is generally assumed that the large icy satellites of Jupiter and of Saturn are, like our Moon, in an equilibrium rotation state called a Cassini State. In this state, the rotation of the satellite is synchronous with the orbital motion and the precession rate of the rotation axis is equal to that of the normal to the orbit. Moreover, the spin axis of the satellite, the normal to its orbit and the normal to the inertial plane remain coplanar and the obliquity (the angle between the normal to the orbit and the spin axis) is constant over time. For satellites with a slow orbital precession rate like the large icy satellites, up to four Cassini states are possible, characterized by a (theoretically) constant obliquity close to 0 (CSI), ± π/2 (CSII and IV) and π (CSIII). From these four states, only two are stable: CSI and CSIII.We here model these two stable Cassini States of triaxial satellites using an angular momentum approach. In our model, the motion of the spin motion in space is coupled with the polar motion of the satellite and, contrary to what is usually done in the classical Cassini States studies, we do not average the external gravitational torque over short period terms. We can therefore compute the mean obliquity value of the different satellites but also the nutations (small periodic variations) both in obliquity and in longitude, which are due to the periodic variations of the gravitational torque acting on the satellites. We identify and study two causes for the polar motion and their effects on the obliquity: the semi-diurnal polar motion due to the inclination and node precession and the long period polar motion due to the eccentricity and pericenter precession.
The environmental and health impact of salt dust aerosols from the dried Lake Urmia
Authors: Firouzeh Mahshad , Danesh-Yazdi Mohammad
Published: March 2024

Lake Urmia (LU), a hypersaline lake in Iran and formerly recognized as the second-largest hypersaline lake worldwide, was desiccated to an area of less than 350 km2 in August 2023, facing almost a complete drying condition. This environmental catastrophe has resulted in the generation of extensive playas, potentially acting as sources of salt dust that, in turn, pose health and environmental risks to the nearby areas. In this study, we first identified the major environmental controls influencing salt dust generation in LU and developed a learning-based model to predict aerosol optical depth (AOD) using satellite data from 2017 to 2023. We then quantified the impact of salt dust aerosols diffused within a radius of 20 km around LU on the neighboring residential regions. The results demonstrated a significant correlation between AOD around LU and soil moisture (-0.66), soil temperature (0.70), wind speed (0.29), and precipitation (-0.53). We also found a significant correlation of 0.91 between the monthly averaged AOD in the East Azerbaijan and West Azerbaijan provinces and that observed in LU. Finally, the calibrated learning model could predict AOD with high accuracy, evidenced by R2 = 0.77 and RMSE = 0.147. The developed model can further be used to assess the impact of future climate-driven changes in the meteorological variables on the salt dust generation from LU.
Nowcasting of extreme precipitation events: performance assessment of Generative Deep Learning methods
Authors: Franch Gabriele , Tomasi Elena , Wanjari Rishabh Umesh , Cristoforetti Marco
Published: March 2024

Radar-based precipitation nowcasting is one of the most prominent applications of deep learning (DL) in weather forecasting. The accurate forecast of extreme precipitation events remains a significant challenge for deep learning models, primarily due to their complex dynamics and the scarcity of data on such events. In this work we present the application of the latest state-of-the-art generative architectures for radar-based nowcasting, focusing on extreme event forecasting performance. We analyze a declination for the nowcasting task of all the three main current architectural approaches for generative modeling, namely: Generative Adversarial Networks (DGMRs), Latent Diffusion (LDCast), and our novel proposed Transformer architecture (GPTCast). These models are trained on a comprehensive 1-km scale, 5-minute timestep radar precipitation dataset that integrates multiple radar data sources from the US, Germany, the UK, and France. To ensure a robust evaluation and to test the generalization ability of the models, we concentrate on a collection of out-of-domain extreme precipitation events over the Italian peninsula extracted from the last 5 years. This focus allows us to assess the improvements these techniques offer compared to extrapolation methods, evaluating continuous (MSE, MAE) and categorical scores (CSI, POD, FAR), ensemble reliability, uncertainty quantification, and warning lead time. Finally, we analyze the computational requirements of these new techniques and highlight the caveats that must be considered when operational usage of these methods is envisaged. 
Ordinary and Bundle-Unmixing Approaches Under the Influence of the BRDF Effect
Authors: Kizel Fadi
Published: March 2024

Remotely sensed spectral data play a vital role in interpreting and understanding land cover properties. However, due to its typically low spatial resolution, the ability to extract information from the data using traditional applications is limited to the pixel size, which, in many cases, is bigger than the phenomena of interest. On the other hand, spectral unmixing allows for extracting information from such data at the subpixel level by estimating the fractional abundance of the different land cover types within the pixel, so-called endmembers (EMs). Many approaches have been developed for this purpose. Nonetheless, the ordinary methods use only a single spectral signature for each EM, disregarding the highly probable spectral variability within each EM spectra. Therefore, bundle-unmixing methods were developed to overcome this limitation by using a set of spectra for each EM.Previous research results show the advantage of bundle-unmixing methods in enhancing the fraction estimation for various cases with an EM variability due to multiple effects. Still, despite the encouraging results, only very few works considered the spectral variability caused by the impact of the Bidirectional Reflectance Distribution function (BRDF). Thus, this work focused on studying the performance of ordinary and bundle-unmixing methods under the influence of the BRDF effect. We comparatively examined five methods, each with particular characteristics: two bundle methods and three ordinary ones; among them, one method relies on the Spectral Angle Mapper (SAM) as an objective function. We used three data sets for experimenting: 1) a laboratory set involving three land covers measured from various viewing zenith angles, 2) a synthetic data set created by simulating spectral data influenced by the BRDF effect using semi-empirical models, and 3) an areal data set including hyperspectral images over the Icelandic volcanic area. We examined the methods' performance under various signal-to-noise (SNR) ratio levels.The results clearly show the superiority of the bundle methods in reducing the effect of the BRDF on the estimated fractions. Besides, the most exciting outcome shows that despite relying on only one spectral signature per EM, the SAM-based method outperforms the other ordinary methods and provides accurate results comparable to the bundle ones. Our study aimed to understand better the complex relationship between BRDF, spectral variability, and unmixing accuracy. This investigation may enhance remote sensing data analysis and refine the unmixing approach in the presence of BRDF-induced spectral variability to improve land cover mapping and environmental monitoring using spectral data.
Exploring the Interplay of Climatic Trends, Reservoir Fluctuations, and Vegetation Dynamics in Paphos, Cyprus: A Decade-Long Study Towards Sustainable Resource Management
Authors: Loulli Eleni , Varvaris Ioannis , Eliades Marinos , Papoutsa Christiana , Tzouvaras Marios
Published: March 2024

Drought is a complex phenomenon that cannot be easily detected in its early stages and advances slowly, but cumulatively. Its consequences can be short-term, such as water deficiency in rivers and dams, and long-term like saltwater intrusion and ecosystem degradation. These impacts make agricultural productivity vulnerable, exacerbate waterborne diseases and increase the risk or wildfires, posing a threat to food security, safety and sovereignty. Cyprus, characterized by a semi-arid climate, experienced in recent years prolonged and frequent droughts that had multiple impacts on agricultural production and consequently the ecosystem and the economy. In the face of a changing climate and increased frequency of droughts, monitoring and understanding such phenomena is crucial in mitigating their impacts. Our overall goal is to investigate the relationships between climatic trends, reservoir fluctuations and vegetation dynamics over the study period. Therefore, we provide a comprehensive analysis of the previously mentioned relationships for the hydrological region of Paphos, (Cyprus) for the period between 2013 and 2023. Vegetated areas are extracted using the European Space Agency WorldCover tree cover, shrubland, grassland, and cropland land cover classes. The study integrates measurements at meteorological stations and satellite-derived time series to assess the relationship between climatic variables and vegetation processes. In particular, we compare the Standardized Precipitation Index (SPI) calculated using CHIRPS data (Climate Hazards Group InfraRed Precipitation with Station Data), with hydrological drought indices provided by the Water Development Department. The latter are estimated on the basis of a drought indicator system that utilizes monthly dam Inflows and mean daily flows of hydrometric stations. Additionally, we analyze spatial climatic variables (such as the MODIS Land Surface Temperature and Evapotranspiration) and vegetation indices (such as MODIS and Sentinel-2 Normalized Difference Vegetation Index, Enhanced Vegetation Index, and Green Chlorophyll Index). Preliminary results show that vegetation dynamics and drought patterns vary based on seasons and the studied land cover classes. The findings of our study are anticipated to contribute to sustainable land and water resources management in the Paphos region.AcknowledgementsThe authors acknowledge the ‘GreenCarbonCY’: Transitioning to Green agriculture by assessing and mitigating Carbon emissions from agricultural soils in Cyprus. The ‘GreenCarbonCy project has received funding from the European Union - Next Generation, the Recovery and Resilience Plan “Cyprus_tomorrow”, and the Research & Innovation Foundation of Cyprus under the Restart 2016-2020 Program with contract number CODEVELOP-GT/0322/0023.
Understanding the future Monsoon activity across the Ganga-Brahmaputra-Meghna basin using CMIP6 HighResMIP models  
Authors: Ali Haider , Fowler Hayley
Published: March 2024

The pattern of Monsoon rainfall across the Ganga-Brahmaputra-Meghna (GBM) basin is crucial for supporting various farming and ecological systems and play a significant role in affecting the basin’s food-water security, well-being, and prosperity. However, the understanding of Monsoon activity is limited due to the poor representation of large-scale processes in the climate models and their coarser resolution. This study utilises sub-daily precipitation from finer resolution CMIP6 HighResMIP models to study the changes in properties of monsoon rainfall based on the timing (onset/offset/duration) of the Monsoon and the trend in rainfall (total and extreme rainfall). All models show a delay in the monsoon but there is disagreement in trends in retreat and duration of the monsoon. Also, CMCC models project a decline in magnitude of rainfall whereas NERC models project an increasing trend. The models output is also evaluated against the reference datasets like MSWEP and ERA5 reanalyses. Our study highlights the uncertainty in climate models to capture the monsoon rainfall and disagreements in results across different horizontal resolutions and nature of models. Importantly, the delay in future Monsoon supported by all models have a strong implication on agriculture and economy of the delta.
Impact of different emission inventory on the modelled concentrations chemistry transport models over Europe
Authors: Karlický Jan , Villaba-Pradas Anahí , Huszár Peter , Machado Crespo Natália , Verma Shruti , Halenka Tomáš
Published: March 2024

While the impacts of CO2 and other well mixed greenhouse gases on continental to global scales are well understood, there are still gaps and uncertainties connected to the non-CO2 forcers. One of the main goals of FOCI project is to improve our understanding of non-CO2 forcers on climate, weather, air quality and health, such as short-lived gases and aerosols. To assess the long-term impact of these gases, we need first to find and understand uncertainties in simulations given by different emission sources.
In this study, we performed a set of simulations on 27 km domain over Europe with RegCM-Chem and WRF-Chem models with emission inputs based on different emission inventories, namely CAMS, EDGAR and EMEP. We analyzed differences in resulting tropospheric ozone, NO2 and aerosol concentrations in selected time periods of 2015. We found significant differences in results that emerge from using different emission inputs.
Short-term variability and uncertainties of trace gases in the boreal summer UTLS from AirCore measurements during the OSTRICH campaign
Authors: Degen Johannes , Baier Bianca , Blazaki Kyriaki , Chen Huilin , Engel Andreas , Heikkinen Pauli , Karhu Juha , Kivi Rigel , Leuenberger Markus , Meixner Katharina , Nyfeler Peter , Sweeney Colm , van Heuven Steven , Zanchetta Alessandro , Laube Johannes
Published: March 2024

Trace gas patterns in the upper troposphere and lower stratosphere (UTLS) can provide valuable insights into the mechanisms and the interplay of processes controlling the distribution of these species. We use vertical greenhouse gas profiles derived from measurements with the balloon-based AirCore technique to obtain detailed information on the distribution of carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4) in and around the polar UTLS region during the boreal summer. The analysis is based on new data from the ATMO-ACCESS campaign called OSTRICH (Observations of Stratospheric TRace gases Influencing Climate using High-altitude platforms), which took place in the summer of 2023 in Sodankylä, Finland. More than 30 vertical profile measurements over a ten-day period allow for study of short-term changes in composition, with the balloons covering an altitude range from the ground to >30 km. In addition, the results of the comparison between the six participating international AirCore groups (Universities of Groningen (The Netherlands), Bern (Switzerland), Frankfurt (Germany), Finnish Meteorological Institute, Forschungszentrum Jülich (Germany) and the National Oceanic and Atmospheric Administration (NOAA, US)) enable an evaluation of the measurements themselves. Due to the simultaneous sampling with different AirCores during each flight these results contribute to the assessment of AirCore data quality in general and the determination of uncertainties. Moreover, future technical improvements and adaptations in processing algorithms can be derived from this intercomparison. The measurements mostly agree quite well, confirming the quality of vertical trace gas distributions derived from the AirCore technique. It is however an essential task to pinpoint the reasons behind the deviations that were observed in some cases. Next to these differences within one flight we discuss the variability in the profiles between individual flights. Only at altitudes above the 80 hPa level do expected and remaining similar behaviours of CO2 and CH4 mole fractions appear. The measurements in lower parts of the atmosphere show large deviations from day-to-day during the campaign phase. These clear (short term) variations in trace gas composition show that a single vertical profile in many different layers of the atmosphere, such as the UTLS, is not necessarily representative. Balloon-borne sensors with higher spatial and temporal resolution can therefore help to better constrain trace gas variability across various altitude ranges.
PRETTY – First experience from a 3U CubeSat In-Orbit Demonstrator for GNSS-Reflectometry under grazing angle geometry
Authors: Dielacher Andreas , Moser-Moritsch Michael , Hoermanseder Walter , Semmling Maximilian , Li Weiqiang , Zus Florian , Moreno Mario , Wickert Jens , Cardellach Estel , Nahavandchi Hossein , Pirat Camille
Published: March 2024

The PRETTY CubeSat In-Orbit Demonstrator (IOD) Mission has been finally launched on 9th October 2023 into a Sun-Synchrounous Orbit (SSO) in 560km height. The Launch and Early Orbit Phase (LEOP) was successful, meaning that communication with the CubeSat was possible, solar panels and VHF antennas are deployed. The commissioning phase is started. The 3U CubeSat hosts two scientific payloads, a radiation dosimeter and a novel GNSS-Reflectometry payload. The GNSS-reflectometer will be measuring earth surface under grazing elevation angles at the L5 frequency, in order to obtain altimetric altitude under various surface conditions (e.g., ocean waters or sea ice). The measurements will be done by correlating the direct and reflected signal (the so called interferometric approach), exploiting the full bandwidth of the GNSS signal.An Algorithm Theoretical Baseline Document (ATBD) has been created within the scientific consortium and first simulation results have been conducted (and the results are analyzed within the consortium). For this presentation we will focus on the status of the satellite and present the first results obtained from space.
Retrieval of Cloud Properties for the Copernicus Atmospheric Missions Sentinel-4 (S4) and TROPOMI / Sentinel-5 Precursor (S5P) using deep neural networks
Authors: Romahn Fabian , Loyola Diego , Doicu Adrian , Molina García Víctor , Lutz Ronny , Argyrouli Athina
Published: March 2024

Due to their fast computational performance and accuracy, neural networks are nowadays commonly used in the context of remote sensing. The issue of performance is especially important in the context of big data and near-real-time (NRT) operational processing. Classical retrieval algorithms typically use a radiative transfer model (RTM) as a forward model to solve the inverse problem of inferring the quantities of interest from the measured spectra. However, these RTMs are often computationally very expensive and therefore replacing them by a NN is desirable to increase performance. But the application of NNs is not straightforward and there are at least two main approaches:
For the inverse problem in atmospheric remote sensing, there are two main approaches to apply NNs:
1. NNs used as forward model, where a NN accurately approximates the radiative transfer model and can thus replace it in the inversion algorithm 2. NNs for solving the inverse problem, where a NN is trained to infer the atmospheric parameters from the measurement directly
The first approach is more straightforward to apply. However, the inversion algorithm still faces many challenges, as the spectral fitting problem is generally ill-posed. Therefore, local minima are possible and the results often depend on the selection of the a-priori values for the retrieval parameters.
For the second case, some of these issues can be avoided: no a-priori values are necessary, and as the training of the NN is performed globally, i.e. for many training samples at once, this approach is potentially less affected by local minima. However, due to the black-box nature of a NN, no indication about the quality of the results is available. In order to address this issue, novel methods like Bayesian neural networks (BNNs) or invertible neural networks (INNs) have been presented in recent years. This allows the characterization of the retrieved values by an estimate of uncertainty describing a range of values that are probable to produce the observed measurement.
We apply and evaluate both approaches for the retrieval of cloud properties and consider their potential as operational algorithms for current (Sentinel-5P) and future (Sentinel-4) Copernicus atmospheric composition missions.
Ten years of ground and surface water monitoring in the abandoned Hg-mine of Abbadia San Salvatore (central Italy): geochemical investigations before reclamation
Authors: Meloni Federica , Nisi Barbara , Cabasso Jacopo , Montegrossi Giordano , Bianchi Francesco , Rappuoli Daniele , Vaselli Orlando
Published: March 2024

Since February 2013, 21 periodical samples (mostly carried out seasonally) of ground and surface waters within and outside the former Hg-mine of Abbadia San Salvatore (Tuscany, central Italy) have been analyzed for the main composition, Hg, As, Sb, and, in most cases,  selected trace elements. The groundwater samples refer to a phreatic aquifer at depths between 5 and 10 m, characterized by low transmissivity and whose waters are interacting with terrains containing tailings derived from the production of liquid mercury by roasting cinnabar. The temperatures are thus strongly affected by seasonal variation, while the pH values are mostly circumneutral. The results evidenced the presence of relatively high concentrations of Hg and, to a minor extent, As and Sb, forcing the local authorities to intervene to test specific strategies to remove mercury. Strikingly high seasonal variations of the geochemical facies were observed and were apparently not related to meteoric precipitations. The variability of the main composition, i.e. Ca(Mg)-SO4, Ca(Mg)-HCO3 and, subordinately, Na-HCO3, is intimately associated with the large differences recorded in terms of Hg, and, to a lesser extent, As and Sb. This is likely related to the water-rock interaction processes governed by the dissolution of carbonates and gypsum/anhydride (typical minerals recognized in the waste materials used to fill a paleo-valley in the SW margin of the mining area). The highest recorded Hg concentration was 407 µg/L during the wet period, decreasing down to 81.4 µg/L in the dry period, when the groundwater level decreases in most boreholes by up to 2 m. This also results in an increasing electrical conductivity. The low transmissibility of this shallow aquifer is clearly evidenced when the piezometers are purged before sampling, as they tend to be rapidly emptied. The groundwaters upstream and downstream of the mine are found to have a concentration of Hg < 1 ppb. This suggests that there is no interference between the mining area aquifer and the volcanic one. Apparently, no significant correlations were found between Hg and other metals, probably suggesting that the presence of liquid Hg often recovered in the piezometer cores is perhaps the main source of mercury. The speciation of Hg, As, and Sb of selected ground and superficial waters was computed by PHREEQC modelling. In addition, to simulate how Hg is vehiculated through the aquifer, a chemical transport model was developed. Presently, the installation of a hydraulic barrier is the most suitable solution to minimize the water-rock interaction processes, responsible for the recorded Hg variability, possibly coupled with additional operations, e.g. extractant agents or filters, to remove mercury before discharging the pumped waters into a surface stream.
Exploring fluvial morphodynamics through scales 
Authors: Gailleton Boris , Steer Philippe , Davy Philippe , Schwanghart Wolfgang
Published: March 2024

Surface processes control mass transfer efficiency on Earth, responding to tectonic and climatic forcings. These forcings impact landscape dynamics across a wide range of temporal scales, from individual events (e.g., storms) to geological time spans (e.g., Cenozoic climate cooling). Bridging these temporal scales poses a significant challenge for Landscape Evolution Models (LEMs). While LEMs are conventionally employed to study the effects of climate or tectonics on landscape dynamics over geological time, numerical methods simulating short-term processes such as landslides, floods, erosion, and sediment transport struggle to be projected beyond a few hundred years. 

In this contribution, we address this challenge by leveraging a recent model development—graphflood—that enables the computation of hydro-stationary water surfaces and discharge using a simplified shallow water approximation. This new model shows an order-of-magnitude improvement in speed over its predecessors, achieved through the efficiency of algorithms applied to directed acyclic graphs. Through testing induced subgraph dynamic traversals for initial calculations of a stationary state and employing GPU techniques to maintain the state to slower erosion and deposition processes, we demonstrate the potential for an additional order-of-magnitude reduction in computation time for fluvial dynamics. We also investigate how the computation of landslide runout using a shallow water approximation with a friction coefficient modified to account for velocity-weakening can be introduced within the same numerical framework. 

First, we explore various sets of fluvial erosion and deposition laws (e.g., stream power, Meyer Peter Muller) to determine the minimal representation needed for fluvial morphodynamics and projecting them across scales at the lowest computational cost. We then perturb the system with landslides processes and observe the controls on its resilience to external forcings. Lateral dynamics (e.g., lateral erosion, deposition, interaction with valley walls) and the model's ability to capture different river states (e.g., high flow vs low flow, flood) emerge as crucial elements in understanding the complexity of river responses to climato-tectonic perturbations. 
Metryc and DeepCyc: Pioneering Tools from Reask in Disaster Risk Financing and Humanitarian Impact Mitigation
Authors: Schmid David , Loridan Thomas , Shaylor Marie
Published: March 2024

The escalation of climate-related disasters presents an urgent need for innovative risk financing mechanisms. Metryc, a groundbreaking product by Reask, emerges as a pivotal tool in this domain, especially in the context of tropical cyclones. It represents a significant advance in parametric insurance, facilitating swift, post-disaster financial recovery. Metryc’s intensity-based approach, distinct from traditional distance-based models, minimizes basis risk and offers cost-effective risk transfer solutions. This method’s superior accuracy in modeling wind speeds post-cyclone landfall enables rapid insurance payouts, crucial for immediate disaster response and recovery.
Complementing Metryc, DeepCyc, another Reask product, stands as a probabilistic hazard model integrating current climate data and future climate scenarios. This climate-connected model transcends the limitations of conventional models reliant on historical data, thus offering a more robust and future-oriented risk assessment. DeepCyc’s high-resolution (1x1 km²) probabilistic hazard modeling is instrumental in precise insurance structuring and premium determination, reflecting modern-day climatic realities.
The humanitarian impact of these tools is profound. By ensuring expedited financial relief, Metryc significantly enhances the capacity of affected communities to recover from catastrophic events. This rapid response mitigates the long-term socio-economic impacts of disasters, facilitating quicker restoration of livelihoods and infrastructure. Moreover, DeepCyc’s forward-looking approach in risk modeling acknowledges the evolving nature of climate risks, ensuring that risk assessments remain relevant and effective in a changing world.
In summary, Metryc and DeepCyc represent a synergistic approach in disaster risk financing. Metryc’s immediate post-disaster financial support and DeepCyc’s comprehensive, climate-informed risk assessment model together provide a robust framework for mitigating the humanitarian and economic impacts of climatic disasters. This dual approach underscores the potential of advanced technology in transforming disaster risk management and resilience-building in the face of climate variability and change.
Microplastics pollution in groundwater: Case study - Slovenia
Authors: Colmenarejo Calero Elvira , Kovač Viršek Manca , Bizjak Tine , Mali Nina
Published: March 2024

Microplastics (MPs), are considered an emerging global pollutant and a significant contributor to environmental pollution. They are defined as plastic particles measuring less than 5 mm which can vary in chemical composition, color, shape, density, size, and other characteristics. MPs generated through urban, industrial, and agricultural activities have the potential to reach the environment, including groundwater. However, despite the significance of groundwater as a vital resource, there is a notable dearth of information regarding the occurrence, transport, and risk of MPs in this environment.In Slovenia, groundwater resources are the primary source of drinking water for 98% of the population. A considerable number of these resources are affected by different anthropogenic activities that result in contamination by different pollutants, among which MPs are probably included. The present study aimed to investigate the presence of MPs in karst and alluvial aquifers of three different regions of Slovenia. Particular emphasis has been given to the improvement of sampling and detection of MPs in groundwater along with the evaluation of the impact of hydrogeological environment, land use and anthropogenic activities in the recharge zone of each sampling site on the occurrence of MPs in groundwater.Groundwater samples were collected from a total of 19 locations, 8 were situated in alluvial aquifers and 11 in karst formations. In each location a total of 3 cubic meters of water was sampled using an in-situ filtration system with a filter pore size of 10 - 100 µm. The samples were then analyzed in the laboratory using a digital microscope with a magnification range of 100 - 5000x and stereomicroscope with magnification 12,5 – 100x. The chemical composition of particles was determined using FTIR microscope and ATR-FTIR. The results showed that MPs were present in all sampled sites, with fibers and fragments being the most common observed shapes. The study proves the presence of MPs in both, alluvial and karst aquifers of Slovenia and demonstrates the suitability of an in-situ filtration system for sampling MPs in groundwater.
Multiscale Numerical Modeling of Ultrasound-Induced Granular Avalanches
Authors: Martin Hugo A. , Mangeney Anne , Jia Xiaoping , Maury Bertrand , Lefebvre-Lepot Aline , Maday Yvon , Dérand Paul
Published: March 2024

Understanding the mechanisms of seismic-wave-induced triggering of landslides and earthquakes at micro-strain amplitudes is crucial for quantifying seismic hazards. Granular materials, as an out-of-equilibrium and metastable model system, offer insights into landslides and fault dynamics within the unjamming transition framework from solid to liquid states. Recent experiments suggest that ultrasound-induced granular avalanches result from reduced interparticle friction via shear acoustic lubrication. However, investigating crack growth or slip at the grain contact scale in optically opaque granular media remains challenging.We present a new multiscale numerical modeling of 2D dense granular flows triggered by basal acoustic vibrations of an inclined plane. We introduce a time-scale separation method, addressing the characteristic scales of grain motion on one hand and the propagation of acoustic vibrations on the other. Our approach results from the coupling between the Convex Optimization Contact Dynamics model (COCD) and the computation of vibration modes.Numerical simulations of ultrasonic vibrations in the millisecond range and flow onset in the second range reveal a correlation between local rearrangements at the grain scale and continuous flows at the macroscopic scale. Ultrasounds primarily propagate through strong-force chains, while a decrease in interparticle friction occurs in weak contact forces perpendicular to these chains. This friction reduction initiates local rearrangements leading to continuous flows through a percolation process with a delay dependent on proximity to failure. Ultrasound-induced flow, compared to gravity-driven flow, appears more spatially uniform, suggesting the role of effective temperature induced by ultrasonic vibration. The simulations align well with experimental observations of granular flows triggered by ultrasound below avalanche angles, supporting the validity of our numerical method.
Community-led AA for flash floods: Lessons learned from the last-mile community during 2022 Extreme Event in North-Eastern Bangladesh 
Authors: Rayhan Md , Rahman Md. Hasanur , Dewyan Rashel , Shampa Shampa , Murshed Sonia Binte , Haque Shammi
Published: March 2024

Forecast-Based Early Action (FbA) is a promising disaster risk reduction technique that allows communities to take proactive steps with the help of accurate forecasting before a disaster strikes. The current global evidence indicates that timely FbA can save more lives and minimize the impact on communities in the emergency and recovery stages. However, the FbA funded by humanitarians or governments needs some specific forecast window (e.g., 7 to 9 days for riverine floods in Bangladesh) from impact identification to intervention deployment. But in the case of rapid on-set disasters (such as flash floods (FF)), such forecast windows might be difficult to identify as these disasters might happen within 5 to 6 hours. In such cases, our research focuses on how the last mile community takes anticipatory action (AA). As a case study site, we selected the north-eastern (NE) region of Bangladesh, which experienced extreme FF during June 2022.The first goal of this study was to look into how flash floods change the impact dynamics of last-mile communities over time. The second goal was to investigate how forecasting can be improved in terms of effectiveness and inclusiveness. The third goal was to investigate community-led AA during normal and extreme FF events. To understand local experiences and observations related to climate and environmental cues, 12 Key Informant Interviews (KIIs) and 14 Focus Group Discussions (FGDs) were conducted during Nov-Dec 2023. The Key Informant Interviews (KII) were conducted with representatives from NGOs, CBOs, trade organizations, and government officials. FGDs were held with a variety of groups, including women, the elderly, the disabled, ethnicity, religion, and occupation.Our research found that rather than official forecasting, communities rely on indigenous knowledge such as cloud patterns, wind flow, atmospheric changes in hilly areas, sudden water temperature drops, color changes, and so on. These indicators serve as early warning signs of impending flash floods, allowing residents to plan ahead of time. Based on these predictive indicators, they take proactive measures such as elevating house plinths and safeguarding essential assets related to their livelihoods around 2.5 months before the FF period. Because the global lead time for FF is short, any AA must rely on community action. Because the NE region of Bangladesh has a long history of FF, their solution would be beneficial for other parts of the world to learn about, especially as the world experiences more FF because of climate change.
Enhancements of geomechanical models for potential siting areas in Switzerland
Authors: Reiter Karsten , Ziegler Moritz , Heidbach Oliver , Desroches Jean , Fjær Erling , Giger Silvio
Published: March 2024

After the upper earth's crust was mainly explored in the last century for the extraction of water, minerals and energy resources, the focus of exploration is increasingly shifting to the temporary storage of energy, the extraction of thermal energy and the disposal of CO2 or radioactive waste. The geomechanical stability of the host rock is particularly relevant for the barrier integrity of a geological repository. The stresses acting on the lithologies and the waste-induced pore pressure evolution determine whether a potential failure can occur. Various methods are used to estimate individual components of the stress tensor on a meter scale. Since the local stress state may be strongly influenced by tectonic structures and spatially variable rock properties, it is necessary to apply 3-D geomechanical models, to predict the spatial distribution of the stress state beyond the in-situ data.Geomechanical-numerical models require detailed information about the structural composition such as stratigraphic boundaries or faults, and the material properties of the subsurface lithologies. Technically the task is to estimate the equilibrium of forces between gravity and the elastic response due to lateral displacement boundary conditions that result in a best-fit with respect to pointwise stress magnitude data. With the increase in available data, the calibration process becomes more complex, but also provides a framework for testing the validity of the data and the models.Motivated by the Sectoral Plan Deep Geological Repositories, a comprehensive exploration program was done in three sites in Northern Switzerland between 2016 and 2021, involving 3-D seismic surveys and drilling of nine boreholes. This enabled to refine 3-D geomechanical-numerical models for the potential repository sites. These models differ significantly not only due to the improved geometrical data, but the large number of stress magnitude data and the increased numerical resolution. The presentation is intended to provide an overview of the modelling process, the calibration procedure, the new features of the models and the key results.