bluuebunny/crossref_metadata_2025 huggingface dataset:
Replacing Pulversized Fly Ash in cement with natural and anthropogenic geomaterials identifying the corresponding physico-chemical properties used for the encapsulation of Low-Level Waste
Authors: Kozlowski Andrea , Renshaw Joanna , Dobson Katherine
Published: March 2022

Clinker substitutes are frequently used in the cement and concrete industries to reduce CO2 emissions associated with production, improve physico-chemical properties and performance, and reduce costs. Pulversized Fly Ash (PFA), a fine waste residue produced in coal-fired power stations, is the commonly used partial clinker substitute in Ordinary Portland cement (OPC) for cements for the immobilisation of low-level nuclear waste (LLW). Because of the global trend to shut-down coal-fired power stations, the production of PFA is decreasing and will eventually cease. Alternative sustainable clinker substitutes can be used must meet strict performance standards for the safe enclosure of LLW for the final disposal. These include physical, chemical, and mechanical properties; performance and suitability for use.

This study investigates the suitability of different materials (natural and anthropologic) as a substitute of PFA in OPC in LLW immobilisation, and compares the behaviour of these substituted cements to those of the current standard. The focus of the study is on the cementing and physico-chemical properties of the cement, and the interaction between groundwater, the cement, and the stored waste.

Here we present the characterisation the standard PFA+OPC (samples provided by Low-Level Waste Repository Ltd.) using X-ray computed tomography (XCT), and the latest data from the ongoing analysis elemental composition of the alternative materials and the leaching tests. Over the leaching period the samples undergo repeated XCT analysis to link structural changes to the chemical evolution. Future work will include studying the long-term leaching effects and the interaction of the LLW (usage mock waste formulation) with concrete.

These studies will allow us to identify changes to the cement microstructure and physico-chemical properties arising from the PFA substitutes, and the chemical and physical interaction of the cements, especially with groundwater Such understanding is critical for the adoption of clinker alternatives in LLW encapsulation.
The role of multi-sector climate impacts in achieving water, energy, and land SDGs 
Authors: Vinca Adriano , Awais Muhammad , Byers Edward , Fricko Oliver , Frank Stefan , Satoh Yusuke , Krey Volker , Riahi Keywan
Published: March 2022

Several studies have explored the interaction across the water, energy, and land (WEL) systems under the scope of policy analysis, highlighting the importance and usefulness of integrated approaches in exploring pathways for achieving the Sustainable Development Goals (SDGs) in the WEL sectors. However, most of these studies neglect the possible impact of climate change on the natural system (e.g. water cycle and crop yields changes) or on technologies (e.g. power plant potentials, desalination, etc.) because of the high complexity, interconnection and uncertainty of these impacts.
Using the latest version of the MESSAGEix-GLOBIOM Integrated Assessment Model (IAM), we study the long-term resources, supply and demand of the energy, water and land sectors to determine the regional and sectoral investments required for achieving the SDGs. Here we show the implications of climate feedbacks for different regions and sectors under different climate mitigation scenarios. The largest component of climate impacts, and the highest source of uncertainty, are changes in water availability, which affect irrigation, provision of basic water and sanitation access, hydropower potential and the available technology options for cooling power plants.
Accounting for hydrological controls when clustering groundwater quality data
Authors: Kyriakidis Phaedon , Panagiotou Constantinos , Tziritis Evangelos
Published: March 2022

Groundwater salinization occurs when high concentrations of water-soluble salts are present in groundwater systems and is regarded as one of the most worldwide, severe, and complex phenomena affecting coastal aquifers. Salinization might occur, for example, from: (i) from marine sources via seawater intrusion, seawater ingression, (ii) underground or terrestrial sources (e.g., natural soils and rocks through the dissolution of soluble minerals), and (iii) salt and saline fluids from anthropogenic activities.

The analysis of salinization-related data by multivariate statistical methods is often undertaken in the context of efficient groundwater management. For example, clustering algorithms are used to delineate hydrogeohemically distinct water classes, whereas dimensionality-reduction algorithms are being used to decipher underlying natural and anthropogenic influences responsible for these distinct water classes. However, most of these algorithms do not explicitly account for spatial information and/or constraints, which can often have a significant impact on the classification of groundwater quality samples.  In the context of the MEDSAL Project (www.medsal.net), such spatial effects are incorporated in the clustering procedure via the inclusion of pertinent hydrological attributes, namely, hydraulic head and conductivity data, along with pair-wise distances between sample locations.

The application of the proposed spatially explicit clustering approach is illustrated using groundwater quality samples collected from the Rhodope coastal aquifer, located at north-eastern Greece. Sampling locations were grouped into four hydrogeochemically distinct water classes using k-means clustering with and without accounting explicitly for spatial information. Principal component analysis (PCA) was used to decipher underlying natural and anthropogenic influences responsible for these distinct water classes. The first four principal components (PCs) explained more than 83% of the total variance in water quality variables, from which the major component was found to be associated with salinization processes.
The Volkis’ adventure: the perfect combination of science and creative illustration
Authors: Schamuells Nia , Geyer Adelina , Aulinas Meritxell , Dorado Olaya , Hopfenblatt Joaquin , Martí Joan
Published: March 2022

Earth Science studies usually get less attention compared to other basic sciences, especially at teen ages. This is a pressing problem, which worsens considerably in those countries in which the primary and secondary educational systems regularly minimize or unbalance the presence of Earth Sciences in front of other branches of knowledge such as Biology or Physics. Child interests usually develop during young ages, and this will influence the interest of future generations on the understanding of our planet and the environment.  In this sense, the creation of engaging educational tools and resources that captivate the younger audience is one of the current challenges. More and more, comic books, graphic novels and illustrated children’s books are becoming a powerful tool to approach scientific concepts to kids and teenagers. Here we present the digital book: “Discover the volcanoes: Accompany the Volkis to their volcanic adventure”. A creative way to explain to a child and teen audience, how volcanoes work, as well as their impacts and benefits to our society. The leading characters are the Volkis, a secret club for volcano lovers that learn different aspects related to volcanology thanks to Rocky, the most experienced member of the group.  The book is composed of 13 sections covering the essential information needed to learn about volcanology. Where and why do we have volcanoes on Earth? How is the interior of a volcano? Why do volcanoes erupt? Which are the hazards derived from a volcanic eruption? are just some of the questions that are resolved in it. The Volkis, fantastic characters that represent different volcanic products, will guide young readers and instructors on their journey through the world of volcanoes. The book will be downloadable for free and  accompanied by a webpage (https://descubrelosvolcanes.es) where teachers, educators and readers can find additional material such as videos, coloring pages, experiments, etc.  The final aim of this book is to break the paradigms of how to teach science to children in an entertaining, striking, and didactic way, where not only children will learn, but also all adults who are accompanying them.

This project was funded by the Spanish National Research Council (CSIC) in its program “Cuenta la Ciencia – 4ª Edición” (Fundación General del CSIC) for promoting scientific culture. 
Synthesizing Daily Snow Cover Maps Using Satellite Images and Climate Information
Authors: Zakeri Fatemeh , Mariethoz Gregoire
Published: March 2022

Daily snow cover is an essential parameter in hydrology, climate, and environmental studies. Although remote sensing images provide valuable information on snow, they are restricted by clouds, clouds’ shadows, and temporal and spatial coverage. This study synthesizes daily snow cover maps based on climate and near clear sky Sentinel-2 and Landsat images. The motivation of this study is that snow patterns are repeatable between years with similar meteorological characteristics. Accordingly, a distance metric based on climate information is computed, including temperature and precipitation (1km resolution) as well as auxiliary data such as daily MODIS snow cover. This distance quantifies the mismatch between the days when clear sky Landsat or Sentinel-2 data is available, learning days, and days when there is no clear sky satellite data or test days. The proposed methodology is applied on a subset of the Alpine belt called the Western Swiss Alps and on the Jonschwil sub-basin, both located in Switzerland. We have synthesized daily snow cover maps for each of our regions of interest for 20 years since 2000.

To evaluate synthesized snow cover maps, we use leave-one-out cross-validation, comparison with a random selection process, and a degree-day snow model. The leave-one-out assessment shows a good agreement between the actual Landsat and the synthesized one. The synthesized snow cover maps also show that the proposed method output agrees with physical concepts as the physical features have been used along with satellite data in the proposed model. Considering physical features in synthesizing Landsat images is an innovation that allows us to use the methodology to synthesize images for the pre-satellite period. Moreover, random selection assessment shows that considering a metric based on climate and auxiliary data can synthesize snow cover as repeatable patterns depending on meteorological data.
Development of slow slip front during the nucleation of laboratory fluid-induced earthquakes
Authors: Passelegue Francois , Dublanchet Pierre
Published: March 2022

Fluid injections are known to induce earthquakes in the upper crust. Recent studies have highlighted that fluid injections can contribute to the nucleation of instabilities close to or far from the injection site due to stress transfer induced by poroelastic processes. In addition, recent studies have suggested the maximum magnitude earthquake is expected to be a function of the volume injected. However, the development of the slip front related to the fluid pressure front, as well as its implications on the induced seismic sequence in time and space, remain poorly constrained in the laboratory and in natural fault systems.

Here, we investigated the influence of the initial normal stress (i.e., the permeability of the fault plane) and of the injection rate on the development of both the fluid pressure front and associated slip front during the nucleation stage of laboratory fluid-induced earthquakes. Experiments were conducted on saw cut samples of andesite, presenting a negligible bulk permeability compared to the fault plane one. Strain gauges were glued all around the fault surface to track, (i) the strain transfer associated with slip front propagation during injection and the rupture velocity during dynamic rupture propagation. The dynamics of the fluid pressure front was inverted from pore pressure measurements located at both edges of the fault. The evolution of the slip distribution due to the change in fluid pressure around the injection site was inverted from strain gauge measurements, assuming a 3D modelling of the sample specimen using the Finite Element Method. Our preliminary results show that the initial stress acting on the fault controls the development of the slip front during the nucleation of the instability. In addition, the larger the injection rate, and the faster the propagation of the slip front compared to the fluid pressure front. Finally, the scaling between the volume of fluid injected and the associated nucleation moment differs from the one relating the volume injected to the seismic moment.

 
Triggering mechanisms of the induced seismicity at the Underground Gas Storage of Castor, Spain
Authors: Vilarrasa Victor , De Simone Silvia , Carrera Jesus , Villaseñor Antonio
Published: March 2022

Cushion gas injection at the Underground Gas Storage (UGS) project of Castor, Spain, induced hundreds of events, including thirteen with magnitude higher than 3.5 that were felt by the local population and led to project cancellation. The sequence of felt events comprises the three largest earthquakes (M4.08, M4.01 and M3.97) ever induced by any of the more than 640 UGS facilities around the world. The largest earthquakes occurred 20 days after shut-in, when pore pressure buildup had already dissipated. The induced earthquakes nucleated at depths ranging from 4 to 10 km, significantly deeper than the storage formation, which is located at 1.7 km depth. These features of the induced seismicity disregard pore pressure buildup as the triggering mechanism. Our analyses show that seismicity was induced by gas injection, which reactivated the critically stressed Amposta fault. The Amposta fault, which bounds the storage formation, is a mature fault with very low permeability as a result of clay accumulation into its core resulting from its 1,000-m offset. Pore pressure buildup, but specially buoyancy of the gas, which continued to act after shut-in, destabilized the Amposta fault aseismically. The accumulation of aseismic slip caused stress transfer, destabilizing a deep critically stressed fault. Subsequently, shear slip stress transfer combined with slip-driven pore pressure changes, induced the sequence of felt earthquakes. We conclude that the induced earthquakes at Castor could have been avoided because fault stability analysis reveals the high risk of inducing seismicity.

 

Reference

Vilarrasa, V., De Simone, S., Carrera, J. and Villaseñor, A., 2021. Unravelling the causes of the seismicity induced by underground gas storage at Castor, Spain. Geophysical Research Letters, 48, e2020GL092038
Asymptotic states of ice clouds
Authors: Spichtinger Peter
Published: March 2022

Ice clouds in the cold temperature regime (T<235K) are important features of the upper troposphere; however, these clouds are still not well understood. For instance, the measured ice crystal number concentrations show strong differences in comparison with theoretical investigations. In theory, we often consider the ice crystal number concentrations for nucleation events in clear air and use these as a benchmark. However, it is not clear how often such undisturbed nucleation events really happen, or if it is more probable to assume pre-existing ice for nucleation events.

A simple ice model is consistently derived from a more complex model. It consists of a 3D system of ordinary differential equations with variables number and mass concentration and saturation ratio. The model is analyzed in terms of dynamical systems properties. The system contains two Hopf bifurcations depending on the parameters vertical velocity and temperature, respectively. The stable states and limit cycles, respectively, show much smaller ice crystal number concentrations than the peak values in undisturbed nucleation events. These results agree with in situ measurements inside ice clouds.
A perspective on the current and future use of satellite radar observations for monitoring vegetation water dynamics
Authors: Steele-Dunne Susan
Published: March 2022

Many studies have demonstrated the value of microwave remote sensing for soil and vegetation applications in agricultural and natural systems. The sensitivity of microwave observables to internal water content makes them suitable for monitoring changes in above ground biomass associated with growth, seasonality and land cover change. In recent years, microwave observations have increasingly been used to monitor changes in vegetation water content associated with water status. Here, novel experimental data from field campaigns and analyses of satellite data records will be synthesized to provide a perspective on the current and future use of radar for monitoring vegetation water dynamics.

Ground-based radar and in-situ data will be used to illustrate the sensitivity of sub-daily radar data to detect the subtle response of the vegetation to variations in moisture supply and demand. These data will also be used to highlight the sensitivity of radar observables to surface canopy water (dew and/or interception). On the one hand, it will be shown that surface canopy water can have a confounding effect on vegetation parameter retrieval. On the other hand, microwaves can provide valuable information on this quantity of considerable interest in hydrology and land-atmosphere interactions.

 Analyses of existing satellite data records (ASCAT, Sentinel-1) will be used to show that the opportunities and challenges identifiable at field scale translate to the footprint scale. Furthermore, they will be used to outline a way forward. Future microwave missions offer unprecedented diversity in terms of sensors (in terms of frequency, polarization, viewing geometry, observation technique), as well as finer spatial and temporal resolution. To make optimal use of these new capabilities, we need to be willing to revisit our fundamental understanding of the factors affecting microwave interactions with vegetation. Finally, it will be argued that the use of machine learning can facilitate extracting the full information content of microwave observations by providing a means to reconcile microwave observables with land surface model states and parameters.
Short term predictions of coastal flooded areas using a machine-learning approach
Authors: Cavallaro Luca , Iuppa Cla , Sanfilippo Mariano , Musumeci Rosaria Ester , Foti Enrico
Published: March 2022

Coastal flooding is one of the most important natural hazards worldwide, increasingly growing in a changing climate. Various problems concerning the current and potential future risk of coastal areas, highlighting the needs for reliable forecast of storm conditions that can reach the coasts and of consequent estimated of the probability of flooding of urbanized areas.

The study presented here aims to develop a method to predict flooding in coastal areas through Artificial Neural Networks (ANNs). The method was applied to the village of Granelli, in the South-Eastern part of Sicily (Italy). The present work was organized into two-phase: the first was dedicated to create the database of the flooded areas, through a physically-based modelling of wave propagation from offshore to the coast; the second was dedicated to study how to use the relate through machine learning approach onshore flooding results to offshore wave characteristics.

As regards the first phase, the wave data used in the present study were obtained using two nested numerical models: SWAN and Xbeach. For an accurate simulation of wave propagation both in the nearshore zone and on the beach, a bathymetric survey of the submerged foreshore and a morphological survey of the emerged beach were carried out. The first one was surveyed through a Multibeam eco-sounder up to a depth of -12 m. The survey of the emerged beach was carried out using a Trimble TX8 Laser Scanner. As regards the boundary conditions, more than 1600 scenarios were simulated by changing both the offshore wave characteristics and the water elevation.

During the second phase, the offshore wave characteristics and the resulting flooded areas were used to train several configurations of an ANN. After a calibration process of the ANN configuration, the best one was identified through comparison with the results of Xbeach.

The proposed approach allows both to significantly reduce the time required for the estimation of flooding areas (8-9 hours required by Xbeach for each sea state against a few seconds required by ANN for the entire storm) and to obtain extremely reliable results with an accuracy of 0.05 m2 in terms of root mean square error.

Acknowledgments

This work has been partly funded by the project “NEWS - Nearshore hazard monitoring and EarlyWarning System" (code C1-3.2-60) in the framework of the programme INTERREG V-A Italia Malta 2014-2020, by the project “ISYPORT - Integrated System for navigation risk mitigation in PORT” financed under the program PNR 2015-2020 and by University of Catania funded project "Interazione Moto Ondoso - Strutture (IMOS)".
Magnetosheath jets and their dynamical properties derived from an analysis of Cluster data at solar minimum (2007,2008)
Authors: Echim Marius , Voiculescu Mirela , Munteanu Costel , Voitcu Gabriel , Teodorescu Eliza , Condurache-Bota Simona , Bujor Dănilă Emilian , Negrea Cătălin
Published: March 2022

We analize magnetosheath Cluster data from 2007 and 2008, included in FP7 STORM database (http://www.storm-fp7.eu). We identify magnetosheath jets based on a procedure that searches for significant departures of the local dynamic pressure from an average value.  The latter  is estimated from a running window spanning 20 minutes of data. The selection criterion is applied on Cluster 3 dataset and identifies 955 magnetosheath jets, with a notable difference between 2007 and 2008 (352 versus 603 events). The statistical analysis of the plasma bulk velocity, density, temperature, plasma beta, magnetic field and radial distance of the jets provides interesting elements for understanding their dynamics. There is evidence for deceleration of jets with decreasing distance from the Earth; interestingly, this trend manifests more clearly for jets detected in 2008. More jets are found in the dawn than in the dusk flank, for 2007 and 2008.  A comparison with the plasma parameters of the driver, the IMF Bz and the solar wind dynamic pressure from OMNI database, indicate there is no preference in terms of Bz polarity. The distribution of jet magnetic field, temperature (parallel, perpendicular), dynamic pressure, plasma beta and total speed is symetric when organized as a function of IMF Bz, with one exception, the jet perpendicular temperature and plasma beta. An increased solar wind dynamic pressure seems to correlate to higher values of the jet density but not velocity. We discuss these results in the context of previous similar magnetosheath jet analysis performed on MMS and THEMIS data.
Forecasting a proxy of humanitarian drought impact with machine learning using meteorological predictors; a case study for Zimbabwe
Authors: Panis Marijke , Phùng Phuoc , Ottow Bouke Pieter , Teklesadik Aklilu
Published: March 2022

The impacts of drought are complex due to the multidimensionality (intensity, duration, and extent) and slow-onset nature of droughts. To be able to forecast the impact of droughts, one needs to prioritize and disentangle the diversity of impacts. In Zimbabwe, our country of interest, the Zimbabwe Red Cross Society prioritized crop loss, livestock loss, child malnutrition, and stunting. However, no high-quality data with national spatial coverage on these impacts is available. Therefore, it is necessary to use a proxy indicator for these impacts (or one of these impacts). As Zimbabwe is strongly dependent on rainfed- agriculture for its livelihood, our assumption is that a crop yield anomaly can be used as a proxy for crop loss impact. A negative crop yield anomaly derived from global historical yield series was used to determine the drought status (yes or no impact) in April and forms the target or predictand. The meteorological indicators to predict the crop yield are the observed 3-month-averaged El Niño–Southern Oscillation (ENSO) and the observed monthly rainfall from CHIRPS for each lead time. Also, a combination of monthly rainfall and ENSO was used as predictor. Our forecasting ML classification model, XGBoost, is run at lead times of one to seven months and at the livelihood zone/agro-climatic zone level. The entire dataset for 1983-2015 is divided into train (80%), test, and validation sets. Statistical performance is measured with the Probability of Detection and False Alarm Ratio of both the test and validation set. Our findings show the potential of ENSO-based data in forecasting our proxy for drought impact over various lead times. The addition of rainfall does not improve forecast skill. Future research will investigate if additional meteorological- and biophysical predictors such as soil moisture and Vegetation Condition Index improve the forecast skill. Our IBF Trigger Model for drought is currently a sequence of automated tasks that feed into an IBF-Portal with comprehensive visualizations for decision-makers. Both the development of the trigger model and the portal result from close collaborations and co-designs with the Zimbabwe Red Cross Society and its in-country partners.
On the improvement of surface currents from ocean/waves coupled simulations : Sensitivity to wave forcing
Authors: Aouf Lotfi , Law-Chune Stephane , Hauser Daniele , Chapron Bertrand
Published: March 2022

The climate is evolving rapidly and there is a strong need of better description on momentum and heat fluxes exchanges between the ocean and the atmosphere. Recently directional wave observations from CFOSAT shed ligth on the improvement of dominant wave direction and better scaling of wind-wave growth in critical ocean areas such as the Southern Ocean (Aouf et al. 2021). This work examines the validation of coupled simulations between the ocean model NEMO and the wave model MFWAM including assimilation of directional wave observations. The coupling experiments have been performed for austral summer and fall seasons during 2020 and 2021. The objective of this work is on the one hand to assess the impact of waves on key parameters describing the ocean circulation and on the other hand to evaluate the contributions of different processes of the wave forcing (stress, Stokes drift and wave breaking inducing turbulence) on the mixing in upper ocean layers. The outputs of the coupled simulations have been validated with in situ observations of ocean surface currents, temperature and salinity. The results clearly reveals an improvement in the estimation of the Antarctic Circumpolar Current (ACC) with an increase in the intensity of the current for example in the region between Tasmania and Antarctica. We also observed a significant improvement of the surface currents in the tropics, for instance the ascending brazilian current. In other respects, we have examined the contribution of improved surface stress on inertial oscillations of the current in the Southern Ocean.

Comparison of the surface currents from the coupled simulations with those provided by altimeters showed an increase in current intensity and a better description for small scales in regions of strong currents such as the Agulhas, ACC and Kuroshio regions. We also investigated the impact of wave forcing depending on the mixing layer length.

Further discussions and conclusions will be presented in the final paper.
Broadband Dynamic Rupture and Ground Motion Simulations (up to 5 Hz) of the 2016 Mw 6.2 Amatrice, Italy Earthquake
Authors: Taufiqurrahman Taufiq , Gabriel Alice-Agnes , Ulrich Thomas , Valentová Lubica , Gallovič Frantisek
Published: March 2022

Broadband earthquake ground motion simulations (>1 Hz) are of great interest to seismologists and the earthquake engineering community. The evolution of the earthquake ruptures related to the 2016 Mw 6.2 Amatrice earthquake and the uniquely dense seismological recordings provide an opportunity to understand better the processes controlling earthquake dynamics, strong ground motion, and the relation between earthquakes. We here propose a novel approach to design data-driven broadband (up to 5 Hz) dynamic rupture scenarios from 0.5-1 Hz Bayesian dynamic finite-fault inversion (Gallovič et al., 2019). We analyze the effects of enhancing the best-fitting smooth dynamic source inversion result by subsequent adding of complexity such as non-planar fault geometry (i.e., fault listricity and surface roughness), topography, inelastic off-fault rheology, and visco-elastic attenuation. We utilize the open-source software package SeisSol (www.seissol.org), suited explicitly for incorporating such geometrical complexities and high-resolution simulations performed on modern supercomputers. The obtained scenarios reproduce synthetics resembling the observations in terms of velocity and accelerations waveforms and Fourier-amplitude-spectra (FAS) up to 5 Hz. The simulated peak ground velocity (PGV) maps show de-amplification of ground motion amplitudes on the foot-wall and amplification on the hanging-wall as a consequence of the wave-focusing effect caused by the listric fault curvature. This effect is seen mainly for distances up to 10 km from the fault. Our study suggests that the complexity of the earthquake source should not be neglected for the seismic hazard assessment for regions adjacent to active faults.
Fire weather risk analysis over Portugal in the last decades and their impacts over the atmosphere  - The Monchique study case
Authors: Santos Filippe LM , Couto Flavio T , Salgueiro Vanda , Potes Miguel , Costa Maria João , Bortoli Daniele , Salgado Rui
Published: March 2022

More intense fire seasons have been favoured by climate changes worldwide, like Russia, Brazil, the USA, Canada and Portugal. Portugal experienced numerous severe fire seasons with catastrophic wildfires that caused enormous impacts in the last years. This study aimed to investigate the fire risk evolution in Portugal over the last 40 years and the extreme wildfire emission impacts derived from remote sensing data. First, the Fire Weather Index (FWI) from 1979 to 2020, at 0.25º spatial resolution, provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis version 4 based on meteorological variables, was used. Then, FWI monthly mean values and trends were analysed for four districts of Southern Portugal (Beja, Evora, Faro and Portalegre). The results indicate that the Faro district presented extreme fire risk values, which peaked on August 2, 2018, one day before the Monchique (a mountain in Faro) wildfire began and lasted between August 3 and 10. The Monchique wildfire was the most destructive in Portugal during 2018, with almost 27.000 ha burned. Second, based on the previous results, atmospheric products derived from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite, the first Copernicus mission dedicated to atmospheric composition monitoring, were collected. These datasets were obtained from Google Earth Engine (GEE), the online platform that combines multiple imageries and datasets with cloud processing to perform analyses. The Carbon monoxide (CO) and Nitrogen dioxide (NO2) concentrations, as well as Absorbing Aerosol Index (AAI) products were analysed during the fire event. The concentrations released by the wildfire reached values 3 and 5 times higher than usual for CO and NO2, respectively. Therefore, the work confirms that extreme wildfire events can release huge pollutant concentrations into the atmosphere. Also, the Sentinel-5 products are useful to evaluate the fire emission evolution in extreme wildfires events and may constitute additional valuable information to combine with ground-based information to map air quality related to wildfire occurrences.

This research was funded by the European Union through the European Regional Development Fund in the framework of the Interreg V A Spain - Portugal program (POCTEP) through the CILIFO project (Ref.: 0753-CILIFO-5-E), FIREPOCTEP project (0756-FIREPOCTEP-6-E), and also by national funds through FCT - Foundation for Science and Technology, I.P. under the PyroC.pt project (Refs. PCIF/MPG/0175/2019), ICT project (Refs. UIDB/04683/2020 and UIDP/04683/2020), and TOMAQAPA (PTDC/CTAMET/ 29678/2017).
Coupled atmosphere-ocean dynamics in the California Current System off the U.S. West Coast
Authors: Eirund Gesa , Münnich Matthias , Leclair Matthieu , Gruber Nicolas
Published: March 2022

Air-sea interactions substantially modulate oceanic and atmospheric mesoscale variability. Regions of particularly strong oceanic mesoscale activity and hence strong potential for these modulation effects are the highly productive eastern boundary upwelling systems (EBUS), such as the California Current System (CalCS). There, the interactions between atmospheric and oceanic processes can easily alter marine biogeochemical processes or force extreme events with highly anomalous conditions in ocean temperature, pH, and oxygen. Nevertheless, modeling this coupled variability remains challenging due to the small-scale nature of such interactions and the complexity of the system itself. In addition, the extent to which the interplay between atmospheric and oceanic processes impacts the spatial and temporal scales of mesoscale variability and affects the marine ecosystem and ocean biogeochemistry remains largely unknown.

Given these complex interactions between the atmosphere, the ocean, and marine biogeochemistry, we developed a coupled regional high-resolution Earth System Model (ROMSOC). For the atmosphere, ROMSOC uses the GPU-accelerated Consortium for Small-Scale Modeling (COSMO) model, and the Regional Oceanic Modeling System (ROMS) model for the ocean. ROMS in turn includes the Biogeochemical Elemental Cycling (BEC) model that describes the functioning of the lower trophic ecosystem in the ocean and the associated biogeochemical cycles. Our current model setup includes thermodynamical and mechanical coupling between the atmosphere and the ocean. Here, we present results from 10-year long coupled simulations for the CalCS at kilometer-scale resolution. We find that the inclusion of atmospheric feedbacks strongly affects oceanic dynamics such as upwelling strength, the advection of water masses and mixed layer depth. In a next step, we will test the hypothesis if this strong mesoscale coupling of the atmosphere and the ocean impacts the spatial and temporal scales of oceanic mesoscale variability such as marine heatwaves and can potentially act to shorten their duration.
Novel Underwater Mapping Services through European Open Science Cloud
Authors: Karantzalos Konstantinos , Nomikou Paraskevi , Wintersteller Paul , Quintana Josep , Baika Kalliopi , Ntouskos Valsamis , Lampridou Danai , Anbar Jafar , members NEANIAS team
Published: March 2022

Seafloor mapping is closely related to studying and understanding the ocean, which has increasingly raised interest in the past years. Coastal management, habitat loss, underwater cultural heritage, natural disasters, marine resources and offshore installations have underlined the need of charting the seabed. This upturn has been encouraged by many national and international initiatives and culminated in the declaration of the Decade of Ocean Science for Sustainable Development (2021-2030) by the United Nations, 2017. 

Novel Underwater cloud services offered through the EC H2020 NEANIAS project support this joint quest by implementing Open Science procedures through the European Open Science Cloud (EOSC). The services produce user-friendly, cloud-based solutions addressing bathymetry processing, seafloor mosaicking and classification. Hence, NEANIAS Underwater services target various end-users, representing different scientific and professional communities by offering three applications.

The Bathymetry Mapping from Acoustic Data (UW-BAT) service provides a user-friendly and cloud-based edition of the well known open-source MB-System, via Jupyter notebooks. This service produces bathymetric grids and maps after processing the data throughοut a flexible and fit-for-purpose workflow by implementing sound speed corrections, applying tides, filters and choosing the required spatial resolution.

The Seafloor Mosaicking from Optical Data (UW-MOS) service provides a solution for representing a large area of the seafloor, in the order of tens of thousands of images, and tackling visibility limitations from the water column. The service performs several steps like camera calibration, image undistortion, enhancement, and quality control. The final product could be a 2D image Mosaic or a 3D model.

The Seabed Classification from Multispectral, Multibeam Data (UW-MM) service focuses on seabed classification by implementing cutting-edge machine learning techniques and at the same time providing a user-friendly framework. The service unfolds within four steps: uploading the data, selecting the desired seabed classes, producing the classification map, and downloading the results.

Therefore, NEANIAS Underwater services exploit cutting-edge technologies providing highly accurate results, regardless of the level of expertise of the end-user, and reducing the time and cost of the processing. Moreover, the accessibility to sophisticated services can simplify and promote the correlation of interdisciplinary data towards the comprehension of the ocean, and the contribution of these innovative services is expected to be of high value to the marine community.
Spurious Behaviour in Networks from Spatio-temporal Data
Authors: Haas Moritz , Goswami Bedartha , von Luxburg Ulrike
Published: March 2022

Network-based analyses of dynamical systems have become increasingly popular in climate science. Instead of focussing on the chaotic systems aspect, we come from a statistical perspective and highlight the often ignored fact that the calculated correlation values are only empirical estimates. We find that already the uncertainty stemming from the estimation procedure has major impact on network characteristics. Using isotropic random fields on the sphere, we observe spurious behaviour in commonly constructed networks from finite samples. When the data has locally coherent correlation structure, even spurious link-bundle teleconnections have to be expected. We reevaluate the outcome and robustness of existing studies based on their design choices and null hypotheses.
Graphical Model Assessment of Probabilistic Forecasts
Authors: Lang Moritz N. , Stauffer Reto , Zeileis Achim
Published: March 2022

As a consequence of the growing importance of probabilistic predictions in various application fields due to a necessary functional risk management and strategy, there is an increasing demand for appropriate probabilistic model evaluation. Besides proper scoring rules, which can evaluate not only the expectation but the entire predictive distribution, graphical assessment methods are particularly advantageous to diagnose possible model misspecifications.

Probabilistic forecasts are often based on distributional regression models, whereby the computation of predictive distributions, probabilities, and quantiles is generally dependent on the software (package) being used. Therefore, routines to graphically evaluate probabilistic models are not always available and if so then only for specific types of models and distributions provided by the corresponding package. An easy to use unified infrastructure to graphical assess and compare different probabilistic model types does not yet exist. Trying to fill that gap, we present a common conceptual framework accompanied by a flexible and object-oriented software implementation in the R package topmodels (https://topmodels.R-Forge.R-project.org/).  

The package includes visualizations for PIT (probability integral transform) histograms, Q-Q (quantile-quantile) plots of (randomized) quantile residuals, rootograms, reliability diagrams, and worm plots. All displays can be rendered in base R as well as in ggplot2 and provide different options for, e.g., computing confidence intervals, scaling or setting graphical parameters. Using examples of post-processing precipitation ensemble forecasts, we further discuss how all theses types of graphics can be compared to each other and which types of displays are particularly useful for bringing out which types of model deficiencies.
Tropical forest CH4 budget: the importance of local hotspots
Authors: van Asperen Hella , Warneke Thorsten , De Araújo Alessandro , Forsberg Bruce , Ferreira Sávio , Alves-Oliveira João , Ramos de Oliveira Leonardo , de Lima Xavier Thiago , Sá Marta , Teixeira Paulo , Pires Elaine , Moura Veber , Komiya Shujiro , Botia Santiago , Jones Sam , Lavrič Jost , Trumbore Susan , Notholt Justus
Published: March 2022

Methane (CH4) is one of the most important anthropogenic greenhouse gases. Despite its importance, natural sources of methane, such as tropical wetlands and termites, are still not well understood and a large source of uncertainty in the tropical CH4 budget. The Amazon rainforest is a key region for the (global) CH4 budget but, due to its remote location, local CH4 concentration and flux measurements are still rare.

Fieldsite ZF2 (60 km NW of Manaus, Brazil) is located in pristine tropical rain forest. At this fieldsite, a Spectronus FTIR-analyzer (measuring CO2, CO, CH4, N2O & δ13CO2) was installed at the foot of the K34 tower, set up to measure different heights above and below the canopy continuously. In addition, by use of a Los Gatos portable analyzer (measuring CO2 & CH4), additional semi-continuous concentration measurements were performed at the valley tower (studying the nighttime build up of valley CH4), above the igarapé  (capturing the CH4 ebullition bubbles leaving the water surface), and on the plateau (studying the spatial horizontal heterogeneity of CH4 concentrations within the canopy). Furthermore, the portable analyzer was used for soil, water, termite mound, and termites flux measurements.

By combining tower and flux chamber measurements, the role and magnitude of different ecosystem sources could be assessed. We observed that, while soils in the valley are a small source of CH4 (0.1 to 0.2 nmol CH4 m-2 s-1), overall the soils of this ecosystem are expected to be a net CH4 sink (-0.3 to -0.5 nmol m-2 s-1 ). Estimated total ecosystem CH4 flux, based on nighttime concentration analyses of the tower data, indicate that the ecosystem is a net CH4 source (~1 to 2 nmol CH4 m-2 s-1). We propose that the net CH4 emission of the ecosystem is driven by local emitting hotspots, such as the valley stream and standing water, termites and termite mounds (~1 nmol CH4 m-2 s-1), anoxic soil spots and decaying dead wood.

 
Synthetic high-resolution daily snow cover maps for long-term hydrological modeling
Authors: Wiersma Pau , Zakeri Fatemeh , Mariéthoz Grégoire
Published: March 2022

To study long-term changes in the hydrology of snow-fed catchments, there is a need for long-term time series of snow cover data. Satellite imagery and climate reanalysis can both be used to quantify past snow cover, but they lack in baseline period length and spatial resolution respectively. In this study we apply statistical methods to generate synthetic high-resolution daily snow cover maps, and consequently use these maps as forcing in long-term hydrological modeling. The results are benchmarked against a case without synthetic snow cover forcing. Multiple hydrological models are used to reduce the uncertainty related to the model choice. The study is performed on the Thur catchment in Eastern Switzerland, a meso-scale catchment covering a wide elevation range and experiencing multiple periods of intermittent snow cover annually. We expect the synthetic snow cover maps to provide added value through the high-resolution spatial information on snow appearance and disappearance, leading to better estimates of snow melt runoff. However, we also expect them to show some physical inconsistencies, particularly after periods of high snow accumulation. Should it prove promising, this approach can be used to study both past and future hydrological changes in any snow-fed catchment using ERA5 and CMIP6 climate data, potentially spanning the entire period 1950-2100. Additionally, this framework of synthetic satellite data generation could be expanded to other hydrological variables or to environmental image time series in other fields than hydrology.

 
Low Frequency Marsquakes and Where to Find Them: Automated Event Back Azimuth Determination Using a Multi-Body Wave Polarisation Analysis Approach
Authors: Zenhäusern Géraldine , Stähler Simon , Clinton John , Giardini Domenico , Ceylan Savas , Garcia Raphaël
Published: March 2022

NASA's InSight mission continues to record seismic data over 3 years after landing using its very broadband seismometer. The situation of working with a single station requires efficient back-azimuth determination based on data of available body wave phases in the seismic record.

This study presents an effective way to estimate back azimuths using a comprehensive polarisation analysis. It uses a continuous wavelet transform to transform the seismic signal into time-frequency domain, and then performs an eigenanalysis of the spectral matrix to obtain information on the polarisation of the signal. Non-polarised signals are masked to enhance the seismic signal. We use the polarisation around both the P- and S-wave arrivals in selected frequency bands to estimate the back azimuth. For stronger signals, the P-wave polarisation provides the main information. For weaker signals, the result can be improved significantly based on the orthogonality of the P- and S-wave polarisation vector, which constrains the result for poorly polarised/contaminated P signals. This method is applied to synthetic marsquakes and to well-located earthquakes recorded in Tennant Creek, Australia. We find that the polarisation method reliably estimates the back azimuth for both sets of events.

The Marsquake Service has provided distance estimates for around 35 marsquakes, but only 10 had been assigned back azimuths. Back azimuth estimation – based on the polarisation at narrow-band of initial P-wave energy - is particularly challenging due to the highly scattered signals and noise in the seismic data. Our method, when applied to martian data, obtains results for 30 events in total, significantly improving our understanding of the spatial distribution of seismic activity on Mars. Most of the located events lie in the general Cerberus Fossae region, a large graben structure towards the east of InSight, though we also find quakes in other directions (e.g. north, towards Elysium Mons) that had previously not been expected to be tectonically active. This extended set of located marsquakes will allow for interpretation of martian tectonics, in particular the Cerberus Fossae region. The method could potentially be applied to sparse terrestrial networks, such as ocean bottom seismometers.