bluuebunny/crossref_metadata_2025 huggingface dataset:
Decadal variation of predictive skill of seasonal climate over the Yangtze River and its possible causes
Authors: Shao Chunyu , Yuan Xing , Ma Feng
Published: February 2023

Seasonal climate predictions with global climate models which are developed based on the ocean-atmosphere interactions, contribute to the water resources management and hazard mitigation. Nowadays, multi-model ensemble seasonal climate prediction system, such as North American Multi-Model Ensemble (NMME), has become an effective way to provide useful forecast information a few months ahead especially over regions with strong ocean-atmosphere coupling. Previous studies have evaluated the skill of NMME hindcasts worldwide, however, it’s still unclear that whether the NMME real-time forecasts perform as well as the hindcasts and how the changes in ocean-atmospheric teleconnections affect the prediction skill. Here we show that although selecting an appropriate time frame for the calculation of climatology can reduce errors of real-time prediction, the real-time prediction skills are lower than hindcast skills in the Yangtze River basin, with anomaly correlation decreased by 14%-51% (38%-75%) and error increased by 30%-31% (51%-55%) for seasonal precipitation (temperature) predictions up to the sixth lead-seasons, and the skill decrease larger at longer leads. The failure in representing the decadal variations of ocean-atmospheric teleconnection (especially the association with Indian Ocean surface temperature) during the real-time forecast period can partly explain the decline in the prediction skills. Our findings suggest that improved simulations of the changes in the ocean-atmospheric teleconnections are necessary for skillful seasonal climate predictions in the real-time.
Global environmental constraints on magnetic reconnection at the magnetopause from in situ measurements
Authors: Michotte de Welle Bayane , Aunai Nicolas , Lavraud Benoit , Génot Vincent , Smets Roch
Published: February 2023

The location of magnetic reconnection at the Earth's magnetopause is a longstanding question in the field of magnetospheric physics. Various models  (Alexeev et al. 1998, Borovsky 2013, Trattner et al. 2007, etc) predicting the position of the X-line have been proposed. These models often rely on quantities whose global spatial distributions at the magnetopause are typically obtained through numerical simulations. In this study, we attempt to reconstruct these global distributions using only in-situ measurements. To do this, we have used statistical learning to automatically select in-situ data from four missions (Cluster, Doublestar, THEMIS, MMS). The 3D reconstruction of the magnetic field draping in the dayside magnetosheath (Michotte de Welle et al. 2022) reveals significant differences with the model of Kobel et Fluckiger 1994 for a certain range of IMF orientations. As this magnetostatic model is frequently used to predict magnetic shear at the magnetopause, we will examine the implications of these differences on the X-lines maximizing this quantity (Trattner et al. 2007). We will also extend this discussion to other relevant quantities such as current density and the Cassak-Shay reconnection rate, which can also be accessed using in-situ measurements.
Analyse of the largest ever-described coastal mega boulder in Cuba (Bucanero Resort site, Juragua, Oriente)
Authors: Dunán Avila Pedro Luis , Pedoja Kevin , Authemayou Christine , Nuñez Labañino Arelis , Peñalver Hernández Leandro Luis , Chauveau Denovan , de Gelder Gino , Benitez Frometa Pedro de Jesus , Jara Muñoz Julius , Izquierdo Martin Denyse , Traore Kalil , Arango Arias Enrique , Castellanos Enrique , Regard Vincent , Rodríguez Valdés Ángel Raúl
Published: February 2023

AbstractCoastal boulders or mega-clasts, named huracanolitos in Cuba, are found along many rocky shores. They result from storms/hurricanes or tsunamis, but despite being potentially important indicators for hazard assessment, their mode of emplacement is typically unknown. We studied a coastal boulder that is probably the largest one ever described on Cuba Island. Located on a low-lying coral reef terrace on the SE Cuban shore, the reefal limestone boulder is emplaced seaward of the ruins of the Bucanero resort. The latter was built in 1989, suffered from Hurricanes Ivan (2004) and Dennis (2005), and, in October 2012, was totally destroyed by Hurricane Sandy. Despite these extreme climatic events, satellite images obtained since 1962 show no movement of the block. In order to analyse the boulder and its morphological context, we have analysed its position, shape and its morphological environment. To determine its volume, we developed a low-cost, open-source Structure from Motion photogrammetry (SfM) procedure using a simple 3D spherical target (diameter 30 ± 0.2 x 10-3 m). Using various hydrodynamic equations, we calculated the breaking wave height and associated energy responsible for the dislocation of the coral reef terrace and transport of the boulder. To determine the exposure time of the block on the terrace, we performed 36Cl analysis and U/Th dating on post-depositional secondary calcite. From these data, the climatic or tsunamigenic (by earthquake or gravity event) origin is discussed. Notably, mapping and dating of a neighboring coastal landslide were made in order to correlate or not its effect on the setting up of the boulder.Keywords: coastal boulder; extreme-wave deposit; tsunami; hurricane; Cuba
Impacts on surface and sub soil physical properties under minimum tillage through long-term compost application
Authors: Loades Kenneth , Barclay Anna , Boldrin David , Caul Sandra , Giles Madeline , Hanlon Mark
Published: February 2023

Background: The application of composts to agricultural soil is a well-established practice with evidence showing multiple benefits within the field and beyond through changes in a number of soil functions. With soil health and function becoming increasingly important it is critical to understand the impact of soil management on function and changes in soil carbon, both within the root growth zone and, more importantly, within soil below the plough pan, an area of increasing interest.Methods: A long-term compost application trial was established in 2004 under continuous spring barley with 3 differing compost application rates and a unamended control treatment. Following establishment in 2004 all treatments, except the control, received 50 t ha-1 of municipal green compost, no amendments in 2005, low (35 t ha-1), medium (100 t ha-1), and high (200 t ha-1), applications in 2006 and 2007 before continuous 35 t ha-1 annual applications from 2008 to 2022. Plot structure is a randomised block design with soil being a sandy silt loam cultivated under minimum tillage practices. Intact soil cores were collected from both surface soils (~20mm) and subsoils (~300mm) for each plot in spring 2022 prior to compost application, cultivation, and sowing. Full water release data was collected including characterisation of the least limiting water range (LLWR), the available water beyond which mechanical impedance restricts root elongation (2.0 MPa). Additionally, soil resilience tests were performed to simulate trafficking with impacts on soil bulk density quantified and data on wet aggregate stability, visual evaluation of soil structure, and hydraulic conductivity were also collected.Results: Within surface soils, medium and high compost application rates increased hydraulic conductivity when compared to control plots, the low compost application rate decreased hydraulic conductivity when compared to unamended plots. Surprisingly, within subsoil, compost application was found to significantly impact hydraulic conductivity (P<0.04) with hydraulic conductivity shown to be higher within the medium rate compost application treatment. A significant difference in water stable aggregates (WSA) within surface soils was observed between treatments (P<0.01) and a significant difference in soil bulk density (BD) between treatments (P<0.01) with BD decreasing with increasing compost levels. No significant differences in sub soil bulk density were observed between treatments (P=0.131) however WSA was found to be significantly different in sub soils between treatments (P<0.01). Data on carbon, soil water release characteristics, and nutrient status will also be presented highlighting the long-term benefits of compost application.Conclusions: Results show that the surface application of compost under minimum tillage practice and the production of continuous spring barley can influence subsoil functions with wider ecosystem benefits.
Understanding rapid deglaciation at Mittelbergferner through a sediment-landform association lens
Authors: Mejías Osorio Paulina , Le Heron Daniel , Kettler Christoph , Davies Bethan , Grasemann Bernhard
Published: February 2023

Glaciers in the Ötztal Alps (Austria) have been undergoing retreat since the “Little Ice Age'' in 1850, leaving a complex geomorphic record of subglacial features, glacial and fluvial deposits, and slope-derived talus. By systematically describing and studying these features in modern alpine glacial environments, we can obtain clues as to what is driving these changes and how they are responding to the current climate conditions the Earth is facing. Mittelbergferner is one of the largest glaciers in the Ötztal Alps, and also a tourist destination in the Pitztal area, where there is an extensive suite of hitherto unstudied supra- and subglacial morphotypes that require documentation and interpretation. Here, a high resolution geological-geomorphological map is presented for the East and West lobes of Mittelbergferner based on photogrammetric data, which will be the main tool for studying sediment-landform assemblages in the area. Some of the observed features include the glacio-structural framework, drainage networks, flutes, small moraines and talus slopes. There are also signs of imminent detachments from the main glacier at the West lobe, as well as exposed bedrock within the ice and associated trails of diamicton, which are indicators of decrease in accumulation and consequent retreat. Other questions arise regarding supraglacial debris, sediment distribution and the precise role that dead ice plays on sedimentary architecture during the retreat process. The analysis of the landforms associated with ice recession at Mittelbergferner will contribute to understanding the sediment dynamics operating at rapidly retreating glaciers, offer additional perspectives on processes that are occurring in comparable glaciated areas of the Austrian Alps, and possibly give insight into future ice margin stability. 
A systematic investigation of ophiolite obduction resulting from the closure of small oceanic basins.
Authors: Ibragimov Iskander , Moulas Evangelos
Published: February 2023

Ophiolite obduction, the process by which part of the oceanic crust overlaps the continental margin, is challenging when it comes to the geodynamic reconstruction of lithospheric processes. The oceanic crust is, on average, denser than the upper continental lithosphere. This density difference makes the obduction of the oceanic crust difficult, if not impossible, when only buoyancy forces are considered. To overcome the difficulties posed by the negative buoyancy, the initial configuration of the oceanic basins must have specific thermal and geometric constraints. Here we present a systematic investigation of the geometrical/geodynamical parameters which control the ophiolite emplacement process. We used the LaMEM finite-difference code and acounted for petrologically consistent density structure of the oceanic and continental regions. Our study reveals which parameters are the most important during ophiolite emplacement and which are the most optimal geometries that favor ophiolite emplacement.Our current study focuses on “Tethyan” ophiolites which are characterized by relatively small inferred basin size and are commonly found in Mediterranean region. Based on a combination of various parameters, our study identified the most susceptible configurations for ophiolite obduction. Our models demonstrate, in agreement to geological data, that the obducted lithosphere must be young (<10Myr) and the length of the nature of Ocean-Continent-Transition (OCT) must be relatively sharp (length of initial OCT zone < 60 km) in order to achieve ophiolite obduction. In addition, our results show that the presence of a weak zone separating two parts of the oceanic lithosphere has a profound influence on the subduction initialization and final ophiolite obduction.
Anomalous diffuse CO2 emission from the summit crater of Teide volcano and changes of seismic activity in and around Tenerife, Canary Islands
Authors: Amonte Cecilia , Padrón Eleazar , Melián Gladys V. , Asensio-Ramos María , Rodríguez Fátima , Padilla German D. , Barrancos José , D'Auria Luca , Hernández Pedro A. , Pérez Nemesio M.
Published: February 2023

Tenerife is the largest (2,034 km2) and highest (3,718 m) island of the Canarian archipelago and is the only one hosting an active stratovolcano (Teide-Pico Viejo volcanic system). Its structure is controlled by a volcanotectonic rift-system with NW, NE and NS directions, with the Teide-Pico Viejo volcanic system located in the intersection. The last eruption Teide-Pico Viejo volcanic system occurred in 1798 through an adventive cone. Although Teide volcano shows a weak fumarolic system, volcanic gas emissions observed in the summit cone consist mostly of diffuse CO2 degassing (Hernández et al., 1998; Mori et al., 2001).More than 200 diffuse CO2 efflux surveys have been performed in the summit crater of Teide Volcano during the period 1999-2023. During each survey, diffuse CO2 emission was estimated in 38 sampling sites, homogeneously distributed inside the crater, by means of a portable non dispersive infrared (NDIR) CO2 fluxmeter using the accumulation chamber method. CO2 emission rates was estimated after spatial distribution maps constructed by sequential Gaussian simulation (sGs) algorithm. During 23 years of the studied period, CO2 emissions ranged from 2.0 to 346 t/d. The most remarkable feature of the temporal evolution of diffuse CO2 emission rate was an important increase that began few weeks after the occurrence of a seismic swarm of long period events was recorded on Tenerife in 2 October 2, 2016, a followed by a general increase of the seismic activity in and around the island (D’Auria et al., 2019). Several geochemical parameters showed significant changes during ∼June–August of 2016 and 1–2 months before the occurrence of the October 2, 2016, long-period seismic swarm (Padrón et al., 2021). Since then, anomalously high diffuse CO2 emission rates has remained in the crater of Teide. This change might be explained as an input of magmatic fluids triggered by an injection of fresh magma and convective mixing after the 2 October 2016 seismic swarm (D'Auria et al., 2019; Padrón et al., 2021). This work reflects how useful are the diffuse studies to understand the behaviour of the volcanic system and to forecast future volcanic activity. Monitoring the diffuse degassing rates has demonstrated to be an essential tool for the prediction of future seismic–volcanic unrest and has become an important monitoring tool to reduce volcanic risk in Tenerife.D'Auria, L., et al. (2019). J. Geophys. Res.124,8739-8752Hernández, P., et al. (1998). Geophys. Res. Lett. 25, (17) 3311-3314Mori, T., et al. (2001). Chem. Geol. 177, 85–99Padrón, E., et al. (2021). J. Geophys. Res.126,e2020JB020318
Seismic and aseismic slip driven by ascending fluids and overpressure pulses on faults
Authors: Jiang Danyang , Dal Zilio Luca , Rinaldi Antonio P.
Published: February 2023

It is well known that fault zones are conduits for fluids. In particular, elevated pore-fluid pressure can neutralize the strengthening effect of normal stress and bring the fault system closer to failure. Despite this, most earthquake cycle models prescribe a constant effective normal stress and neglect the evolution of fluid pressure and transport properties. In this study, we present a hydro-mechanical earthquake cycles (H-MECs) model on a 2-D antiplane strike-slip fault with rate-and-state friction, full inertia effects, and poro-visco-elasto-plastic rheology. As a proxy for metamorphic reactions, a source of fluids is imposed at bottom of the fault causing fluids to ascend along the seismogenic zone. We further adopt a permeability evolution law in which permeability increases with fault slip and decreases due to healing and sealing processes. Our results show that fluid overpressure at the base of the seismogenic builds during the late interseismic period, when the fault has low permeability, weakening the fault and triggering slow-slip transients and earthquakes. When the healing time is shorter than the average recurrence interval of earthquakes, overpressure pulses facilitate the propagation of fluid-driven aseismic slip and their ascent through the seismogenic zone, thus causing swarm seismicity. For healing times of the order of a few years, overpressure pulses trigger long-term slow slip events, whereas for even longer healing times, fluid-driven aseismic slip causes a transient unlocking of the fault, without causing any seismic event. As a result, our models show that charge and discharge processes of fluid pressure and relative changes in fault strength influence the timing, slip behavior, stress transfers, stress drop, and other rupture properties. Accounting for viscoelastic deformation and poroelasticity effects incorporating the two-way coupling of solid and fluid phases brings earthquake cycle simulations much closer to reality, allowing greater consistency with experimental and geologic constraints on fault zone structure and dynamics.
MAFIAT: Magnetic Field Analysis Tools
Authors: Price Daniel , Pomoell Jens , Kilpua Emilia
Published: February 2023

Twist is an intrinsic property of magnetic flux ropes that aids in understanding their evolution and eruption. It can be difficult to compute, resulting in the common use of approximations that do not consider the geometry of the flux ropes. However, while these approximations are often relatively simple to compute, their results require careful evaluation to ensure they are correctly understood. Consequently, the magnetic field analysis tools (MAFIAT) Python package has been developed to compute the geometrically-based twist of coronal flux ropes. Here we describe MAFIAT’s initial features, its Jupyter notebook-based operation, its scientific relevance, and our plans for its future development.
Expert elicitation for parameterisation of a Bayesian Network model designed to simulate Faecal Indicator Organism (FIO) losses from septic tank systems in rural catchments
Authors: Mzyece Chisha , Glendell Miriam , Quilliam Richard S , Jones Ian , Pagaling Eulyn , Avery Lisa , Oliver David M
Published: February 2023

Bayesian Networks (BNs) are a modelling approach increasingly used in landscape management, e.g., to predict microbial water pollution risk and inform ecological risk assessment. BNs are widely acknowledged for their ability to integrate multiple data types in their structure, including expert knowledge derived through structured elicitation approaches and are therefore, advantageous when empirical evidence or large-scale datasets are scarce. Expert elicitation is a useful technique for quantifying and characterising expert knowledge regarding an uncertain quantity in situations where empirical data are missing, or additional information is required to augment available data. In this study, an expert elicitation approach utilising the Sheffield Elicitation Framework (SHELF) was employed to obtain expert judgements of an uncertain quantity included in a BN model designed to quantify faecal indicator organism (FIO) losses from septic tank systems by modifying an existing phosphorus risk BN model. The aim of the study was to quantify expert judgements on the proportions of FIOs likely to be delivered to a surface watercourse from septic tank systems based on soil hydrological properties, septic tank distance to watercourse and slope. The specific objectives were to:Solicit expert feedback on the structure of the BN conceptual model developed to identify key factors influencing FIO pollution from septic tank systems;
Use the SHELF elicitation protocol to obtain individual expert judgements on FIO delivery coefficients in form of percentiles for a series of soil type, slope and distance to watercourse scenarios;
Fit probability density curves to individual expert judgements and derive consensus from across the range of expert judgements using facilitated group discussion.
The structure of the BN model including identification and justification of model variables, approaches to expert elicitation and consensus expert judgements are presented. The study demonstrates effective use of expert opinion in BN model parameterisation and BN FIO modelling to inform on options for addressing microbial pollution originating from septic tank systems in the Tarland catchment in North Eastern Scotland.
Studying ionic composition in open field regions using a 16 moments multi-species fluid model
Authors: Lomazzi Paul , Réville Victor , Rouillard Alexis , Petit Pascal
Published: February 2023

Spectroscopic observations of the solar atmosphere reveal regions of the solar corona that are enriched in the abundance of heavy element with low-first ionisation potential (examples of low ‘FIP’ i.e. with <10 eV are Fe, Mg) relative to photospheric abundances. This enhancement in the abundance of low-FIP elements by a factor of three or four, called the ‘FIP effect’, is still not well understood. Moreover enriched abundances of low-FIP elements are also observed in the slow solar wind, which could give us more insights on its origins. An inverse-FIP effect corresponding to a decreased abundance of low-FIP elements has been measured in the atmosphere of M-type stars.Turbulent mixing of the chromosphere combined with the ponderomotive force caused by Alfvén waves propagating in these atmosphere could give a mechanism that might explain the FIP effect. Diffusive theories including the thermal force exerted on the ions due to a collision frequency gradient has also a role to play on minor ion extraction from the chromosphere.  Our goal is to study and compare these effects using  ISAM, a new 1D 16 moments multi-fluid model taking into account collisional effects of the different heavy ions. In this work we use profiles from 3 different solar wind types simulated using ISAM in which we propagate Alfvén waves with a Shell Model of Alfvén-wave turbulence. We then compare the FIP bias obtained from these 3 types of wind.This work has been funded by the ERC SLOWS SOURCE − DLV − 819189
Role of Geological Structures in Rock Slope Stability along a Road Corridor in Indian Himalaya
Authors: Singh Piyush Kumar , Pradhan Sarada Prasad
Published: February 2023

Slope stability analysis is essential for sustainable development since rock slope failure can destroy infrastructure and road networks, threaten public safety, cause economic setbacks, etc. Slope failures are mainly confined to hilly terrain across the world. Himalayan mountain belt, the youngest and tectonically active mountain chain, is highly vulnerable to landslides due to complex lithological and structural variability. It requires a detailed field and laboratory investigation to understand the causes, mechanism and behaviour of slope failure. The main objective of this study is the detailed stability analysis of a rock slope located near North Almora Thrust (NAT) in the Pithoragarh district of Kumaun Himalaya along National Highway-09, Uttarakhand, India. The current study uses a multi-parametric approach which includes the kinematic analysis of slope, analysis of rock microstructures and their relation to meso-structures, the effect of microstructures on rock strength and geochemical analysis to understand the influence of mineral properties on rock strength. The stability of the slope was evaluated based on the limit equilibrium method (LEM) and finite equilibrium method (FEM). To imitate the actual field conditions, the slope model was simulated under static and dynamic settings for saturated and unsaturated conditions. The slope consists of intercalations of dolomitic limestone and phyllite with uniaxial compressive strength (UCS) of 55 MPa and 20 MPa, respectively. The Rock Mass Rating (RMR) of the rocks of the slope depicts that the rock mass quality is ‘poor’, and Slope Mass Rating (SMR) analysis illustrates that the slope is partially stable. Rock microstructural study discloses the development of strong foliation in the phyllite, which serves as the seepage for groundwater percolation. Therefore, an increase in pore pressure along these foliations can decrease the overall strength of the rock, inducing slope failure. The effect of the microstructure orientation on the rock strength was also examined for the slope. It was observed that an increase in the intensity of rock microstructures brought on a drop in rock strength. Shear sense indicators observed in the thin sections confirm the existence of the thrust zone. The slope stability analysis based on LEM and FEM revealed that the slope is critically stable in dry condition, but may  become unstable when considering dynamic and saturated conditions.Keywords: Himalayas, Slope stability, RMR, SMR, Geological Structure, Kinematic Analysis, LEM, FEM 
(Ir)reversibility of future Antarctic mass loss on multi-millennial timescales
Authors: Klose Ann Kristin , Coulon Violaine , Pattyn Frank , Winkelmann Ricarda
Published: February 2023

Given the potentially high magnitudes and rates of future warming, the long-term evolution of the Antarctic Ice Sheet is highly uncertain. While recent projections under Representative Concentration Pathway 8.5 estimate the Antarctic sea-level contribution by the end of this century between -7.8 cm and 30.0 cm sea-level equivalent (Seroussi et al., 2020), sea-level might continue to rise for millennia to come due to ice sheet inertia, resulting in a substantially higher long-term committed sea-level change. In addition, potentially irreversible ice loss due to several self-amplifying feedback mechanisms may be triggered within the coming centuries, but evolves thereafter over longer timescales depending on the warming trajectory. It is therefore necessary to account for the timescale difference between forcing and ice sheet response in long-term sea-level projections by (i) determining the resulting gap between transient and committed sea-level contribution with respect to changing boundary conditions, (ii) testing the reversibility of large-scale ice sheet changes, as well as (iii) exploring the potential for safe overshoots of critical thresholds when reversing climate conditions from enhanced warming to present-day.Here, we assess the sea-level contribution from mass balance changes of the Antarctic Ice Sheet on multi-millennial timescales, as well as ice loss reversibility. The Antarctic sea-level commitment is quantified using the Parallel Ice Sheet Model (PISM) and the fast Elementary Thermomechanical Ice Sheet (f.ETISh) model by fixing forcing conditions of warming trajectories from state-of-the-art climate models available from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) at regular intervals in time. The ice sheet then evolves for several millennia under constant climate conditions. Finally, the climate forcing is reversed to present-day starting from different stages of ice sheet decline to test for the reversibility of ice loss.Our results suggest that the Antarctic Ice Sheet may be committed to a strong grounding-line retreat or even a collapse of the West Antarctic Ice Sheet when keeping climate conditions constant at warming levels reached during this century. Fixing climate conditions later in time may additionally trigger a substantial decline of the East Antarctic Ice Sheet. We show that the reversibility of Antarctic ice loss as well as the potential for safe overshoots strongly depend on the timing of the reversal of the forcing.
Assessment of Sentinel 2 derived phenometrics as predictor features for soil organic matter and pH mapping in a high-altitude Mediterranean forest
Authors: Canero Francisco M. , Rodriguez-Galiano Victor
Published: February 2023

Soil mapping has been performed using different predictor features including climatic grids, terrain, or remotely sensed data. However, studies that consider dense time-series of remotely sensed imagery are scarce. Sentinel 2, the operational multispectral mission of European Space Agency, provides remotely sensed data with a 5-day revisit time and 10-m spatial resolution for visible and near infrared bands. Land Surface Phenology (LSP) and derived phenometrics could be obtained from Sentinel 2 time series. In complex forested ecosystems, these phenometrics could be useful predictor features for the spatial prediction of soil properties such as soil organic matter (SOM) or pH. The aim of this work was two folded, i) mapping SOM and pH with thirteen phenometrics derived from Sentinel 2 and terrain features using two machine learning algorithms (Random Forest (RF) and Support Vector Regression (SVR)) and two Feature Selection methods (Sequential Forward and Backward Selection) and ii) evaluating the contribution of LSP phenometrics for SOM and pH mapping through Feature Selection performance.92 topsoil samples with SOM and pH data were collected in Sierra de las Nieves, southern Spain in 2019. The phenological features were extracted from a three-year time series of Enhanced Vegetation Index 2 (EVI2) computed from all available Sentinel 2 images of 30SUF tile for 2018-2020 period. The time series were smoothed using an asymmetrical gaussian method, and a 10% threshold-based method was used for phenometric extraction. Thirteen phenological features were extracted from the smoothed time series: amplitude, base value, end of season time, end of season value, large integral, left derivative, length of season, maximum value, middle of season, right derivative, small integral, start of season time and start of season value. Together with phenological data, elevation and twelve derived terrain features were used. The performance of two Machine Learning algorithms, Random Forest and Support Vector Regression, was evaluated within a framework with two Feature Selection methods, Sequential Forward Selection and Sequential Backward Selection.The assessment of phenometrics for SOM and pH mapping highlighted the importance of middle of season for SOM, and Large Integral and End of Season value for pH prediction. Together with phenometrics, LS Factor for SOM and elevation and Channel Network Distance for pH were also found relevant. The performance of RF and SVR was similar for both soil properties, outperforming SVR in terms of R2 for SOM modelling (SOM: R2 of 0.06-0.20 and RMSE of 5.42-5.53; pH: R2 of 0.20-0.37 and RMSE of 0.38-0.40). These results underpinned the suitability of Sentinel 2 time-series and LSP derived phenometrics for soil mapping in forested areas.   
Integrating sample management and semantic research-data management in glaciology
Authors: Spreckelsen Florian , tom Wörden Henrik , Hornung Daniel , Fitschen Timm , Schlemmer Alexander , Freitag Johannes
Published: February 2023

The flexible open-source research data management toolkit CaosDB is used in a diversity of fields such as turbulence physics, legal research, maritime research and glaciology. It is used to link research data and make it findable and retrievable and to keep it consistent, even if the data model changes.CaosDB is used in the glaciology department at the Alfred Wegener Institute in Bremerhaven for the management of ice core samples and related measurements and analyses. Researchers can use the system to query for ice samples linked to, e.g., specific measurements for which they then can request to borrow for further analyses. This facilitates inter-laboratory collaborative research on the same samples. The system helped to solve a number of needs for the researchers, such as: A revision system which intrinsically keeps track of changes to the data and in which state samples were, when certain analyses were performed. Automated gathering of information for the publication in a meta-data repository (Pangaea). Tools for storing, displaying and  querying geospatial information and graphical summaries of all the measurements and analyses performed on an ice core. Automatic data extraction and refinement into data records in CaosDB so that users do not need to enter the data manually. A state machine which guarantees certain workflows, simplifies development and can be extended to trigger additional actions upon transitions.We demonstrate how CaosDB enables researchers to create and work with semantic data objects. We further show how CaosDB's semantic data structure enables researchers to publish their data as FAIR Digital Objects.
Mafic microgranular enclaves trace the origin of post-collisional magmatism
Authors: Gómez Frutos Daniel , Castro Antonio
Published: February 2023

Mafic microgranular enclaves (MME) appear associated with most post-collisional batholiths around the world. Together with the mafic-intermediate (sanukitoid) and granitic suites, it constitutes one of the most common features of post-collisional magmatism. MME are considered to represent a mafic endmember with mantle affinity related to granite petrogenesis. Hence, they constitute an ideal tracer of the mantle involvement in crustal-scale processes. However, their exact relationship with the host granitic post-collisional suite and the role of such mantle remains unclear. In this regard, abundant MME in Los Pedroches batholith (Iberian Massif) can provide valuable constrains to this problem. Using new MME data, we provide a comparative study between MME and the mafic-intermediate (sanukitoid) suite of post-collisional batholiths, revealing an accurate overlap between the two groups. A common geochemical signature consisting of high MgO and K2O and low CaO is evidenced, pointing to a potential genetic link between MME and the sanukitoid suite in a modified mantle source. Further information provided by cotectic experimental liquids and petrographical evidence point to cotectic differentiation and orthopyroxene restite self-contamination as the main responsible mechanisms for the particular geochemistry of the series. Once the role of the mantle in MME formation and their magmatic evolution are characterized, their potential relationship with the host granites is established using isotopic criteria. Implications for post-collisional batholith petrogenesis is then discussed in a qualitative manner, suggesting a heterogeneous yet common origin for all post-collisional magmatism.
Future evolution of the snowpack in the Iberian peninsula
Authors: Revuelto Jesús , Deschamps-Berger César , López Moreno Juan Ignacio , Sourp Laura , Terzago Sylvia , Rojas Heredia Francisco , Réveillet Marion
Published: February 2023

The mountains of the Iberian peninsula host seasonal snowpacks in various environments, from mediterranean climate in the Sierra Nevada to alpine climate in the Pyrenees. This range of conditions is expected to result in different, but largely unknown, sensitivity of the snowpacks to the ongoing and future climate change. We modeled the snowpack in five sites which were selected over the peninsula for their environmental importance as indicated by their national park status. We downscaled the EURO-CORDEX meteorological forcings on a 250 m grid and forced SnowModel to obtain an ensemble of spatialized snowpack simulations over the historical period (1970-2005) and a projection period (2005-2100) considering different RCP scenarios. The accuracy of the simulation was evaluated with satellite snow cover images and in-situ measurements. The general decrease in snowpack impacts the hydrological cycle temporality and the frequency of snow droughts in the basins but is modulated by the varying climatic conditions between the study sites.
A study on the establishment of computer vision for disaster identification based on existing closed-circuit television system
Authors: Chen Boris , Li Che-Yuan
Published: February 2023

Increasing climatic extremes resulted in frequency and severity of urban flood events during the last several decades. Significant economic losses were point out the urgency of flood response. In recent years, the government gradually increased the layout of CCTV water level monitoring facilities for the purpose of decision-making in flood event. However, it is difficult for decision makers to recognize multiple images in the same time. Therefore, the aim of this study attempts to establish an automatic water level recognition method for given closed-circuit television (CCTV) system.In the last years, many advances have been made in the area of automatic image recognition with methods of artificial intelligence. Little literature has been published on real-time water level recognition of closed-circuit television system for disaster management. The purpose of this study is to examine the possibilities in practice of artificial intelligence for real-time water level recognition with deep convolutional neural network. Proposed methodology will demonstrate with several case studies in Taichung. For the potential issue that AI models may lacks of learning target, the generative adversarial network (GAN) may be adopted for this study. The result of this study could be useful to decision makers responsible for organizing response assignments during flood event.
Physics-Aware Machine Learning for Carbon Fluxes at High Spatio-Temporal Resolution and Scales
Authors: Moreno-Martínez Álvaro , Martínez-Ferrer Laura , Muñoz-Marí Jordi , Izquierdo-Verdiguier Emma , Kimball John S. , Running Steven W. , Clinton Nicholas , Camps-Valls Gustau
Published: February 2023

Carbon captured via photosynthesis by vegetation is known as gross primary production (GPP). It is an important variable related to climate regulation and determines ecosystem carbon sources and sinks. GPP is routinely estimated globally by operational algorithms that combine remote sensing data at coarse spatial scales (e.g., MODIS, 500 m) and meteorological information. The need for global high-resolution operational products arises from the requirement of capturing GPP variability, which co-occurs at finer resolutions and over large areas. These specifications demand gap-free remote sensing data to obtain continuous maps, high spatial and temporal resolution, and realistic uncertainty quantification. Machine learning (ML) methods are widely used but sometimes do not fit real-world physics restrictions. Therefore, we propose a physics-aware machine learning methodology that combines 1) high spatial resolution spectra at 30m and gap-free observations derived from blending Landsat and MODIS with the HISTARFM algorithm, 2) meteorological information, and 3) in situ eddy covariance GPP estimates as reference data. The ML model further incorporates an extra regularizer that constrains the GPP estimates for improved consistency with ancillary data and covariates closely related to photosynthesis (e.g., SIF). Moreover, we rely on the HISTARFM methodology to provide well-calibrated data uncertainty estimates, which allows us to yield both epistemic and aleatoric uncertainty for the GPP estimates. The processing pipeline is fully implemented in Google Earth Engine (GEE), allowing us to estimate carbon fluxes over Europe at 30m. The methodology enables more precise and real-world carbon studies and opens the door to deriving other key fluxes at an unprecedented spatiotemporal resolution.   
Hydrological modeling using an improved algorithm for a better evaluation of the snow water equivalent (SWE) during spring floods in the Moroccan High Atlas Mountains.
Authors: Benkirane Myriam , Gascoin simon , Amazirh Abdelhakim , Sourp Laura , Laftouhi Nour-Eddine , Khabba Said
Published: February 2023

The present study aims to evaluate the performance of a hydrological model to simulate spring runoff processes, analyze the effect of snowmelt on seasonal flow, and identify the snowmelt contribution rate based on the snow water equivalent (SWE) in the Moroccan High Atlas watersheds.The main objective of this study is to evaluate the daily SWE in a poorly instrumented mountainous watershed using an improved hydrological model. The model algorithm improvement is considered an essential approach for better understanding the initial basin conditions that influence these hydrogeological behaviors. For this purpose, a seasonal analysis was performed to select flood events that reproduce this phenomenon.To this end, the calibration has been done by forcing the model with rainfall, runoff, temperature, and snow water equivalent (SWE), with an amelioration of the model algorithm. Interestingly enough, this improvement achieved 13% based on the Nash-Sutcliffe efficiency coefficients. Hence, the spring event flows were influenced by the snowmelt process, these results will have direct implications for flood event replication modeling and flood forecasting in these regions.The study demonstrates that this region is sensitive to the seasonal effect of snowmelt. Therefore, it is essential to take into account the contribution of snow in hydrological studies developed at the level of the Moroccan High Atlas mountainous watersheds. This approach is a great challenge that will improve the reproduction of seasonal flood events and allow a better forecast of flood events to reduce the uncertainties and risks of flooding in mountainous basin areas facing the same climate conditions.Keywords: Precipitation, SWE, Hydrological modeling, Calibration, Mediterranean climate, flood events, Zat basin.
Extraction of 3D structural data from Virtual Outcrop Models: problems and best practices.
Authors: Tavani Stefano , Corradetti Amerigo , Mercuri Marco
Published: February 2023

The rapid improvements of computer vision–based photogrammetric image processing pipelines (i.e., Structure from Motion–Multi View Stereophotogrammetry: SfM-MVS), coupled with the availability of various low-cost and portable acquisition tools, such as Digital Single-Lens Reflex (DSLR), mirrorless cameras, Unmanned Aerial Vehicle (UAV) and even smartphones, have revolutionized outcrop studies in structural geology and have brought traditional field geology into the digital age. This has had a transformative impact on Virtual Outcrop Models (VOMs), which have been promoted from mostly visualization media to fully interrogable quantitative objects. Among the several applications of VOMs in structural geology, extraction of near planar features (e.g., fracture and bedding surfaces) is one of the most important. Various procedures aimed at this purpose exist, spanning from fully automated segmentation and best fitting of point clouds to the manual picking of 3D polylines on both point clouds and textured meshes.Here we illustrate the pros and cons, best practices, and drawbacks of the main procedures for near planar geological data extraction from VOMs. While automated or supervised recognition and subsequent best-fitting of coplanar patches in point clouds has received remarkable attention, its application generally limits to rare case studies. Indeed, most commonly, geological outcrops do not expose patches of near planar surfaces which are large enough to carry out a robust best fitting, and the structural interpretation of the outcrop only permits manual picking procedures. In the latter case, the use of textured meshes must be preferred to point clouds, and during digitization the accuracy of the textured mesh must be considered, as well as the intrinsic roughness of any geological surfaces. The analysis of coplanarity and collinearity of the picked pointsets may help in identifying traces that diverge from idealized (low) collinear and (high) coplanar configurations. However, typically suggested threshold values often produces small datasets. Nonetheless, the goodness of the extraction of data based merely on the visual inspection of the best-fit plane, handling coplanarity and collinearity in real-time through live computation of best-fit planes from picked pointsets, is often acceptable.
Estimating Nitrogen Oxides emissions from inland waterway vessels using MAX-DOAS measurements – Results of pioneering measurements and plans to advance the method
Authors: Ripperger-Lukosiunaite Simona , Ziegler Steffen , Donner Sebastian , Kuhn Leon , Hoffmann Thorsten , Hoor Peter , Wagner Thomas
Published: February 2023

Nitrogen oxides (NOx, i.e. NO and NO2) are a major contributor to urban air pollution and have negative impacts on human health, relating to respiratory and cardiovascular problems. NO2 is also a precursor of secondary particulate matter and tropospheric ozone, which are also associated with adverse effects on human health. Inland waterway vessels are a significant source of NOx emissions due to their diesel engines operating at high temperatures. Emissions from inland ships are concentrated in the vicinity of waterways, and could be a significant local air pollution source, particularly in residential areas located along intensively used waterways, narrow and steep river valleys, and small villages without heavy road traffic or nearby power plants. Hence, quantifying the influence of inland ship emissions on air quality and humans is important.We demonstrate the use of ground-based MAX-DOAS (Multi AXis-Differential Optical Absorption Spectroscopy) measurements to estimate NOx emissions from inland ships on the Rhine River in western Germany. We show that this method can be used to derive ship emissions of NOx for individual plumes and as an average over several plumes. However, we also identify several challenges with this approach and propose ways to improve it.The combination of MAX-DOAS and in situ measurements, particularly knowledge of the NO/NO2 ratio could lead to more accurate estimates of ship emissions. In addition, we introduce planned systematic measurements at selected locations, such as narrow parts of the Rhine and Moselle valleys, where ship emissions may be a major pollution source. We plan to apply regional models to estimate the effect of the updated ship emissions on local NOx concentrations.
The role of vegetation in UK upland wildfires: Risk, Resilience, and Remote Sensing
Authors: Lees Kirsten , Lenton Tim
Published: February 2023

Wildfires are becoming a growing concern in the UK, as climate change increases the occurrence and persistence of periods of hot, dry weather. Vegetation type and management play an important but contested role in UK fire risk and resilience, and questions remain over the best ways to prevent large fires developing. Remote sensing can provide vital data on fire size, severity, and recovery times, but method effectiveness is dependent on understanding specific ecosystems. This research uses ground validation of four wildfires in the UK Peak District National Park to deliver insights which improve interpretation of satellite data in wildfire monitoring. These insights are then applied to a three-year remote sensing database of large wildfires in England and Wales, to give novel results on the links between vegetation type and management, and fire size and severity. Ecosystem resilience and recovery is further explored through analysing the vegetation growth post-fire at three of the four Peak District study sites. This project therefore develops and validates remote sensing methodology in wildfire research by combining field data with satellite imagery to yield new understandings of the relationships between vegetation and fire. 