bluuebunny/crossref_metadata_2025 huggingface dataset:
Microfossils provide evidence of environmental changes during the Eocene-Oligocene transition in northwestern South America.
Authors: Trejos Tamayo Raúl , Garzón Darwin , Arias Viviana , Plata Angelo , Vallejo Felipe , Pardo Andrés , Flores Jose Abel
Published: March 2024

Marine and terrestrial microfossils respond to environmental and climatic changes during the upper Eocene to lower Oligocene in the onshore ANH-SJ-1 well in NW South America. The interval consists of mudstones and calcareous mudstones sedimented in lower to middle bathyal depths. During the upper Eocene, the warm calcareous nannofossil taxa dominated the assemblage. In contrast, over the early Oligocene, we recorded an increased abundance of cold-water taxa (e.g., Braarudosphaera spp., Clausicoccus subdistichus, and Isthmolithus recurvus). This shift is accompanied by pulses of eutrophic taxa (e.g., Braarudosphaera bigelowii, C. altus, Chiasmolithus spp., Ciclycargolithus floridanus, and Zygrhabilithus bijugatus), indicating fertilization in the surface waters.The marine palynomorphs record (dinoflagellates and foraminiferal organic linings) showed the highest abundance over the upper Eocene. Conversely, terrestrial palynomorphs (spores, angiosperms, and fungi) increased at the beginning of the early Oligocene. Reducing marine palynomorphs and incrementing in continental ones does not mean a shallowing since benthic foraminifera do not show bathymetric variations. Therefore, we suppose that the increase in continental palynomorphs input is due to the increase in fluvial discharges, which became influential in NW South America.An abrupt change in oxygenation rates, diversity, and wall type of benthic foraminifera was recorded at the Eocene-Oligocene boundary. Thus, we documented a dominance of agglutinated foraminifera and low diversity during the Eocene and increased calcareous foraminifera and high diversity during the Oligocene. A rise in the oxygenation index and the collapse of epifaunal microhabitats was also observed.These biotic variations in NW South America are interpreted as an ecosystem response to climatic changes during the Eocene-Oligocene transition (EOT). According to the turnover on benthic foraminifera, deep environments pass from corrosive bottom waters in the late Eocene to a deepening of the carbonate compensation depth (CCD) in the early Oligocene. This change coincided with the global CCD variations due to the EOT. The increased cold-water calcareous nannofossils in the lower Oligocene agree with the cold water's expansion to the tropical regions during the EOT. The increased abundance of nannofossils and terrestrial palynomorphs in surface waters, indicative of substantial inputs from phytoplankton and phytodetritus, suggested a general increase in export production. This could have triggered fluctuations in food availability for benthic foraminifera.The biotic response of microfossils to environmental changes coincides with climatic changes during the EOT, suggesting that tropical ecosystems in NW South America were affected by decreasing global temperatures and a new climatic regime.
Why are plume excess temperatures much less than the temperature drop across the core-mantle boundary?
Authors: Steinberger Bernhard , Roy Poulami
Published: March 2024

While the temperature drop across the thermal boundary layer (TBL) at the base of the mantle is likely > 1000 K, the temperature anomaly of plumes, which are believed to rise from that TBL is only up to a few hundred K. Reasons for that discrepancy are still poorly understood. It could be due to a combination of (1) the adiabat inside the plume being steeper than in the ambient mantle, (2) the plume cooling due to heat diffusing into the surrounding mantle as it rises, (3) the hottest plume temperature representing a mix of temperatures in the TBL, and not the temperature at the core-mantle boundary (CMB), (4) plumes not directly rising from the CMB due to chemically distinct material at the base of the mantle, (5) a plume-fed asthenosphere which is on average warmer than the mantle adiabat, reducing the temperature difference between plumes and asthenospheric average. Here we use the ASPECT software to model plumes from the lowermost mantle and study their excess temperatures. We use a mantle viscosity that depends on temperature and depth with a strong viscosity increase from below the lithosphere towards the lower mantle, reaching about 1023 Pas above the basal TBL, consistent with geoid modelling and slow motion of mantle plumes. With a mineral physics-derived pyrolite material model, the difference between a plume adiabat and an ambient mantle adiabat just below the lithosphere is about two thirds of that at the base of the mantle, e.g. 1280 K temperature difference at the CMB reduces to about 835 K at 200 km depth. In 2-D cartesian models, plume temperature drops more strongly and is rather time variable due to pulses rising along plume conduits. In contrast, 3-D models of isolated plumes are more steady and, after about 10-20 Myr after the plume head has reached the surface, their temperatures remain rather constant, with excess temperature drop compared to an adiabat for material directly from the CMB usually less than 100 K. This extra temperature drop is small because plume buoyancy flux is high. Hence the above points (2) and (3) do not contribute much to reduce temperature of isolated 3-D plumes. In our models, the asthenosphere is on average about 200-400 K hotter than the mantle beneath, due to plume material feeding into it. While this appears to reduce the plume temperature anomaly, a resulting cooler mantle adiabat also corresponds to an even stronger temperature drop in the basal TBL, offsetting that effect. In the Earth, plumes are likely triggered by slabs and probably rise preferrably above the margins of chemically distinct piles. This could lead to reduced excess temperatures, if plumes are more sheet-like, as the 2-D models, or temperature at their source depth is less than at the CMB.
Simple temporal domain adaptation techniques for mapping the inter-annual dynamics of smallholder-dominated croplands over large extents
Authors: Estes Lyndon , Khallaghi Sam , Abedi Rahebe , Asipunu Mary , Ha Nguyen , Luo Boka , Mai Cat , Wussah Amos , Xiong Sitian , Yao Yao-Ting
Published: March 2024

Tracking how agricultural systems are changing is critical to answering important questions related to socioeconomic (e.g. food security) and environmental sustainability (e.g. carbon emissions), particularly in rapidly changing regions such as Africa. Monitoring agricultural dynamics requires satellite-based approaches that can accurately map individual fields at frequent (e.g. annual) intervals over national to regional extents, yet mapping Africa's smallholder-dominated agricultural systems is difficult, as the small and indistinct nature of fields promotes mapping error, while frequent cloud cover leads to coverage gaps. Fortunately, the increasing availability of high spatio-temporal resolution imagery and the growing capabilities of deep learning models now make it possible to accurately map crop fields over large extents. However, the ability to make consistently reliable maps for more than one time point remains difficult, given the substantial domain shift between images collected in different seasons or years, which arises from variations in atmospheric and land surface conditions, and results in less accurate maps for times beyond those for which the model was trained. To cope with this domain shift, a model's parameters can be adjusted through fine-tuning on training data from the target time period, but collecting such data typically requires manual annotation of images, which is expensive and often impractical. Alternatively, the approach used to develop the model can be adjusted to improve its overall generalizability. Here we show how combining several fairly standard architectural and input techniques, including careful selection of the image normalization method, increasing the model's width, adding regularization techniques, using modern optimizers, and choosing an appropriate loss function, can significantly enhance the ability of a convolutional neural network to generalize across time, while eliminating the need to collect additional labels. A key component of this approach is the use of Monte Carlo dropout, a regularization technique applied during inference that provides a measure of model uncertainty while producing more robust predictions. We demonstrate this procedure by training an adapted U-Net, a widely used encoder-decoder architecture, with a relatively small number of labels (~5,000 224X224 image chips) collected from 3 countries on 3.7 m PlanetScope composite imagery collected primarily in 2018, and use the model, without fine-tuning, to make reliable maps of Ghana's  (240,000 km2) annual croplands for the years 2018-2023 on 4.8 m Planet basemap mosaics. We further show how this approach helps to track agricultural dynamics by providing a country-wide overview of cropping frequency, while highlighting hotspots of cropland expansion and intensification during the 6-year time period (2018-2023).
Climate Risk Projections with Pattern Scaling
Authors: Woodhouse Sally , Leach Nicholas J. , Davies Jonathan J. , Brennan James
Published: March 2024

The financial sector is becoming increasingly interested in understanding how it is exposed to the risks due to climate change. At Climate X our multi-disciplinary team of hazard and climate scientists work to generate useful projections of risk for a variety of users.To assess future changes in weather-related hazards we use publicly available climate model outputs from projects such as CMIP and CORDEX. However, these experiments are often not designed with decision-makers and risk assessment at the forefront. Most global climate models are still run at relatively low resolution, whereas decision makers are interested in very local changes (down to asset level). Projects that are run at high resolution, such as HighResMIP and CORDEX, often do not include all the scenarios that decision-makers are interested in and have limited ensemble members.This talk will explore how the use of pattern scaling can address these limitations. Pattern scaling extracts the signal from local changes in atmospheric variables to global mean temperatures (GMT). It can therefore be used to explore emissions scenarios for which there are limited (or no) GCM runs. This allows us to generate custom scenarios such as global warming levels or a client’s individual projections with only a trend in GMT. Additionally, by extracting temperature uncertainty in the climate sensitivity, local hazard responses and internal variability can be separated.
Evidence of Ice Flow Switching from Carlson Inlet to Rutford Ice Stream Based on Polarimetric Radar
Authors: Arenas-Pingarrón Álvaro , M. Brisbourne Alex , Martín Carlos , F.J. Corr Hugh , Robinson Carl , A. Jordan Tom
Published: March 2024

The flow of polar ice is controlled by its viscosity that is spatially variable and depends, among other factors, on the orientations of the anisotropic crystals of ice, often referred as crystal orientation fabric. Ice crystalizes in planes represented by the c-axis, a direction perpendicular to the main plane of the crystals, and it is highly anisotropic: the viscosity along the c-axis is two orders of magnitude greater than across, and hence it can be a key factor for ice flow modelling. Interestingly, the ice crystals rotate to accommodate ice flow, similarly to how dominoes tend to align under strain, and ice c-axis orientation evolves to be perpendicular to the direction of the maximum strain rate. Thus, ice flow and crystal orientation fabric are related. However, critically for our work, c-axis evolution is not instantaneous and, particularly in currently slow deforming ice, crystal orientation fabric contains traces or past ice flow conditions. Here, we use data from the British Antarctic Survey (BAS) airborne radar PASIN2 for deep ice sounding in Rutford Ice Stream, collected during the 2019-2020 season, to derive crystal orientation fabric. Because electromagnetic waves propagate at different speeds depending on the wave polarisation being parallel or perpendicular to the c-axis, an optical phenomenon called birefringence, we compare signals from different antenna orientations in our array to derive englacial crystal orientation fabric. We then compare our radar-derived crystal orientation fabric with strain rate derived from satellite ice flow observations. To aid the interpretation, we use a numerical model that bounds the prediction of ice fabric from ice flow under different assumptions. We find that Carlson Inlet, now stagnant, show traces of past fast flow on its crystal orientation fabric. This agrees with previous studies that suggest flow-switching and water-piracy between neighbouring Carlson Inlet and Rutford Ice Stream (Vaughan et al., 2008). Our method provides a framework to investigate the timing and the causes of the flow-switching event. More in general, we demonstrate the use of existing and future airborne polarimetric data to investigate recent changes in the cryosphere.
Warming reduces global agricultural production by decreasing cropping frequency and yields
Authors: Zhu Peng
Published: March 2024

Annual food caloric production is the product of caloric yield, cropping frequency (CF, number of production seasons per year) and cropland area. Existing studies have largely focused on crop yield, whereas how CF responds to climate change remains poorly understood. Here, we evaluate the global climate sensitivity of caloric yields and CF at national scale. We find a robust negative association between warming and both caloric yield and CF. By the 2050s, projected CF increases in cold regions are offset by larger decreases in warm regions, resulting in a net global CF reduction (−4.2 ± 2.5% in high emission scenario), suggesting that climate-driven decline in CF will exacerbate crop production loss and not provide climate adaptation alone. Although irrigation is effective in offsetting the projected production loss, irrigation areas have to be expanded by >5% in warm regions to fully offset climate-induced production losses by the 2050s.
Flood risk to cultural heritage: a voyage through scales
Authors: De Lucia Claudia , Castelli Fabio , Arrighi Chiara
Published: March 2024

Floods are among the most frequent and damaging events worldwide, affecting population and residence buildings, economic activities, agriculture but also cultural heritage (hereinafter CH). Flood impacts to CH are very challenging to evaluate, due to their intangible values (e.g., spiritual, social, aesthetic) and difficulty in replacing unique objects. These aspects make the evaluation of CH exposure and vulnerability complex, also depending on the scale of analysis adopted.This work aims at illustrating the differences in risk evaluations, as the scale of analysis varies. It highlights the information usually available for flood risk analysis of CH when moving from a large scale, e.g. regional/national level, to building scale, with different stakeholders’ perspectives, and demonstrates a very detailed approach for hazard modelling inside the CH building. The regional/national scale considers CH often as a point feature and usually aims at identifying geographic damage hotspots, i.e., river basin authority perspective. Few information is available at this scale, mostly hazard classification (low to high probability of occurrence) and often a tailored taxonomy for exposed assets has to be developed.The site/city scale usually considers cultural heritage as a polygon feature with a better description of flood depths and of building characteristics such as the building type (e.g., religious or rural), the presence of underground floors or the presence of artworks. It identifies risk priorities and potential damage, i.e. it adopts a mayors’ perspective.The building scale analysis, i.e., heritage manager perspective, requires moving towards a 3D geometric description of the cultural building by incorporating elevations of features with respect to the terrain to better understand actual inundation depths and their effects. On-site inspections are required to measure specific characteristics of the structure such as the location and the height of the openings, which let floodwater enter inside the building. Such information allows for a downscaling of a city inundation model, that provides the hydrograph to assign as boundary condition to the building.The method is applied to the Florence area (central Italy) and to a museum inside the city center. The 2D inundation model at building scale shows the inundation inside the basement of the museum, formerly a crypt, where a part of the permanent art collection is exhibited. The museum model reveals the flow and the quantity of water within different part of the building. A comparison with the historical records of the 1966 flood in the Museum, confirms the findings of the simulation.Acknowledgments. This work received co-funding by (i) Regione Toscana, Fondo per lo Sviluppo e la Coesione 2014-2020, Project “GiovaniSì” and by (ii) the RETURN Extended Partnership, European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005)
The European Drought Impact Database (EDID) - from Research to Operation
Authors: Stahl Kerstin , Szillat Kathrin , Blahova Monika , Blauhut Veit , Rossi Lauro , Masante Dario , Maetens Willem , Toreti Andrea
Published: March 2024

Drought impact data play a crucial role in assessing drought risk, aiding in the determination and validation of warning levels, and predicting potential impacts. Although there is a growing consensus on the operational use of monitored physical drought hazard indices, there is currently no universally accepted convention for drought impact data. This contribution delves into the methodology, development, and content filling of the European Drought Impact Database (EDID), illustrating the challenges involved in transitioning from initial research databases to a database tailored for operational purposes, specifically within the framework of the Copernicus European Drought Observatory. Drawing on previous experience with text-based drought impact reports and regional sector-specific operational impact monitoring, EDID addresses the need for common, yet impact-specific, and information-specific solutions. The conceptual data model for coding text into usable data attributes, such as the impacted system, time, and location of the impact, needed to balance between parsimony and flexibility. The model developed allows for future expansion of sources and links; linked attribute tables enable the storage of source and sector-specific data. The implementation of a new severity score applicable across all nine impacted systems highlights this challenge of finding a balance between commonality and specificity. To test the method's applicability, diverse existing databases, including the European Drought Impact Report Inventory (EDII) and regional or national inventories, such as the Czech Intersucho data, were integrated into the new EDID. Additional content was gathered through a semi-automated webcrawl+translation+classification procedure to fill gaps using media reports. The development and content-building of EDID mark significant progress towards a Europe-wide and more consistent collection and archiving of drought impact data. However, challenges persist for the real-time operational use of EDID as an indicator of the situation and for certain future analyses. Drought impact reports often lack sufficiently accurate geographical or time references and other key attributes. The spatial differences in the current EDID database's impact data records content highlight the need for more effective sharing of regional experience and knowledge, serving as examples across larger regions, as well as a  systematic approach to impact data collection. Despite these challenges, the EDID represents a substantial step forward in enhancing our understanding of drought impacts on a broader scale.This work was part of the project EDORA - European Drought Observatory for Resilience and Adaptation (The European Commisssion DG Environment and Joint Research Centre; https://edo.jrc.ec.europa.eu/edora/)
Trajectories of River-Floodplain Adjustments Following Compounding Wildfire-Flood Disturbances
Authors: Morrison Ryan R. , Hahn Aleah , White Daniel , Wohl Ellen
Published: March 2024

Wide, low-gradient segments within river networks (e.g., “beads”) play a critical role in absorbing and morphologically adapting to disturbances, such as wildfires and debris flow. However, the magnitude and rate of active channel morphological adjustment compared to pre-disturbance conditions and the post-fire response of in-stream restoration features and geomorphic units is not clearly understood. To better understand the impact of major disturbances on river beads, we analyzed trajectories of river morphology adjustments following the 2020 Cameron Peak wildfire and 2022 flood and debris flow at Little Beaver Creek, Colorado, USA. We used historical National Agriculture Imagery Program imagery (2009-2019) and post-fire drone-imagery surveys (2021-2023) to assess morphological change in a 500-m, low gradient bead of Little Beaver Creek. We analyzed remotely sensed imagery for pre- and post-geomorphic metrics in rates of floodplain destruction and formation, and changes in channel width and channel migration. Rates of floodplain destruction and formation, along with centerline migration greatly increased after the first post-fire runoff season and recovered to the historical range of metrics three years after the fire. The large flood in 2022 increased the rate of channel width reduction with immediate infilling of side channels, followed by the infilling of pools, and growth in bars and islands. The ability of the active channel of Little Beaver Creek to quickly adjust to fire and flood disturbances demonstrates the importance of river beads for enhancing river-floodplain resilience to large disturbance events, especially compounding hazards such as fires and floods. Our research also can inform river management and restoration about the importance of heterogeneous and dynamic river-floodplain systems to support resilient watersheds.
Effect of city and climate change on weather conditions, building thermal comfort and energy consumption: application to Strasbourg region
Authors: Breton Florentin , Micolier Alice , Abdellatif Makram , Mendez Maxence , Blond Nadège
Published: March 2024

Weather conditions play a large role in thermal comfort and energy consumption, such as during a cold spell (body hypothermia and building heating) or a heatwave (body overheating and building air conditioning). These weather conditions can be modified by urban factors and climate change, such as higher temperatures in city-center and in future periods. However, weather conditions used for building design and renovation are often taken for convenience from past data near airports. The present study aims to determine weather conditions with urban factors and climate change, as well as thermal comfort and energy needs for several building types in different environments. Measurements and simulations are combined to provide weather conditions and building estimations for different locations (rural, periurban, urban), seasonal cases (winter, summer, heatwave) and periods (recent past, mid-century, end-century). A first application of the approach is presented over the city of Strasbourg (France).We find that the urban case has higher temperature, reduced windspeed and relative humidity, less energy for winter heating and less summer thermal comfort than the periurban than the rural case. Climate change leads to higher temperature and lower relative humidity, and to less summer thermal comfort especially during a heatwave and for older buildings. The combined effect of city, heatwave and climate change on outdoor air temperature reaches 8 to 11 degrees, and similarly for the indoor air temperature of very old buildings but 5 to 7 degrees for recent (well-insulated) buildings. This approach may support building renovation strategies and analyses of population vulnerability. The perspectives include the application to other regions, a comparison of urban climate models, and an investigation of urban scenarios.
Dynamical systems analysis of the "El Niño Southern Oscillation" phenomenon 
Authors: Mindlin Julia , Mindlin Gabriel B , di Nezio Pedro
Published: March 2024

Since the 1980s, when the World Meteorological Organization launched the TOGA (Tropical Ocean-Global Atmosphere Program) program, great advances have been made in understanding ENSO by studying a hierarchy of models (Dijkstra, 2005). At the most complex end of this hierarchy are the Global Climate Models (GCMs), with which simulations of the entire climate system are performed, while at the most elementary end are the simple dynamical models that involve the minimum number of modes necessary to generate the phenomenon and therefore represent the dominant physical processes. Conceptually, two different ways of understanding the irregular oscillations of ENSO are still valid: it could be either a self-sustained oscillator of a chaotic nature or a stable mode excited by atmospheric noise. In this work, we use methods from complex systems to revisit the ideas regarding two plausible dynamics of ENSO. We ask if the dynamics can be better represented as a self-sustained oscillator of a chaotic nature or a stable mode excited by noise. For this, we analyzed the sea surface temperatures (SSTs), one of the output variables of the simulations generated with GCMs, the most complex simulations available from the extended system. This temperature field averaged in a particular region of the eastern equatorial Pacific (Niño 3.4) gives rise to a temporal signal widely used for ENSO monitoring and as a proxy for the study of the oscillation. In order to analyze the dynamics of the system, we reconstruct the phase space from an embedding of the temporal signal. We find that three modes are enough to recover the ENSO dynamics of the extended system, in principle of infinite dimension. Our conceptual model is based on the existence of a self-sustaining oscillation with a critical slowing down in phase space; that is, the system traverses a region of phase oscillation with a critical slowing down in phase space; that is, the system traverses a region of phase space more slowly, and includes a periodic forcing that gives rise to chaotic behavior for certain values of the parameters. We validate the model with a topological and statistical analysis of the periodic orbits in the system and, in addition, we show that the complexity of the signal is better represented as a self-sustained oscillator of a chaotic nature than as a stable mode excited by noise (Wang, 2018).Dijkstra, HA, Nonlinear Physical Oceanography, volume 28. Springer, 2nd revised edition, 2005.Wang C., A review of ENSO theories, National Science Review, Volume 5, Issue 6, November 2018, Pages 813–825
Correlation of Social Media-Driven Risk Perception and Flood Insurance Uptake for Floods in the US
Authors: Veigel Nadja , Kreibich Heidi , de Bruijn Jens , Aerts Jeroen C.J.H. , Cominola Andrea
Published: March 2024

Social media platforms play a key role in enhancing human response to natural hazards. They serve as tools for individuals to share first-hand observations, insights, and experiences, thus contributing to improved resilience. Increased attention of social and communication media content toward natural hazards has the potential to foster take up of private precaution and resilience measures such as purchasing a flood insurance. This study investigates the driving factors behind flood insurance purchase decisions in the US, with a focus on the roles of risk perception and social media as potential drivers for such decisions. We investigate the relationship between household flood insurance uptake and social media attention for flood events that occurred in the continental US from 2014 to 2021. We argue that the surge in insurance uptake in counties affected by flood events is primarily attributed to heightened risk perception resulting from direct exposure to flooding and from citizens’ awareness due to exposure to flood related information. We compare the time series of insurance take-up rate in a county with the number of flood-related social media posts in the adjacent counties using Dynamic Time Warping, which measures the similarity between two time series by optimally aligning their temporal structures. Additionally, we control for time passed since the last flood as well as the number of communities participating in the Community Rating System since these factors have shown to be important drivers of insurance uptake and may otherwise distort the temporal patterns associated to social media exposure. With our data-driven analysis we first evaluate the correlation between exposure to flood-related content on platforms like X (formerly Twitter) and an increased likelihood of purchasing flood insurance. Consecutively, we quantify variations in risk perception and resilience due to exposure to flood-related content on social media. This analysis provides a comprehensive view of risk communication through social media and its implications for resilience-building efforts.
Advancing water resource management: Insights and implications from global machine learning models in groundwater prediction
Authors: Wetzel Maria , Kunz Stefan , Nölscher Maximilian , Schulz Alexander , Biessmann Felix , Broda Stefan
Published: March 2024

Accurate and reliable predictions of groundwater levels are essential for sustainable water resource management. Faced with the impacts of climate change and the increasing stress on groundwater resources, there is a growing necessity to balance domestic, agricultural, and industrial utilization. To address these challenges, innovative and progressive approaches in predicting groundwater levels are necessary, such as the application of machine learning (ML) methods. The advancement of these ML-based prediction models is a crucial component of the BMBF project KIMoDIs. Within this research initiative, an AI-based monitoring, data management, and information system for coupled prediction and early warning of low groundwater levels and groundwater salinisation is being developed.Currently, the state-of-the-art in hydrogeology involves individual models for each groundwater monitoring well (local models). While local models can achieve high predictive accuracy, their application to a multitude of measurement points is impractical. Conversely, global models allow training and prediction for multiple measurement wells simultaneously. This model class has the potential to learn and capture dynamics beyond a single well and their dependency on dynamic input variables (e.g., meteorological parameters) as well as static variables (e.g., specific hydro(geo)logical or morphometric site properties). Particularly with extensive training datasets, global model approaches can provide predictions at measurement points sharing similar site properties to those used in training (generalization). Additionally, they offer advantages in terms of computational requirements as well as model management, as only one model needs to be trained and applied over a large area.The objective of this study is to demonstrate the predictive capabilities of modern ML methods in the context of groundwater level prediction. Further, it provides insights and recommendations regarding the extent to which global models, with a wealth of spatial and temporal information, can contribute to improve prediction accuracy. Global ML models are used for short-term prediction of groundwater levels on a regional scale: Two model architectures (Temporal Fusion Transformer and Neural Hierarchical Interpolation for Time Series Forecasting) are applied to over 5000 groundwater monitoring points in Germany in order to predict groundwater levels for up to 12 weeks. Meteorological data and historical groundwater level data dating back to 1990 (dynamic features) as well as hydrogeological, soil and morphometric properties (static features) are used as input data. Additionally, feature importance is assessed, and eliminating various inputs enabled to identify suitable features for groundwater level prediction.
Results from reprocessing the vintage 1978 ENI-ENEL seismic reflection profiles acquired on the onshore of Campi Flegrei
Authors: Bruno Pier Paolo G. , Cardillo Cosimo
Published: March 2024

In 1978, seven seismic reflection profiles were acquired through a joint venture between Agip and Enel to explore geothermal resources in the Campi Flegrei caldera. These vintage profiles reflect the technological limitations of that era: sparse shot points, limited channels, low bandwidth and dynamic range, resulting in a low signal-to-noise ratio, especially near volcanic structures. Despite these limitations, they can offer invaluable insights in Campi Flegrei, where obtaining new seismic data is impractical due to urbanization, environmental concerns, and intensified volcanic hazards.This presentation shares the outcomes of a reprocessing aimed at enhancing profile signal-to-noise ratio. Given acquisition geometry and data quality, contemporary seismic processing methods like pre-stack depth imaging, reflection tomography, and full-waveform inversion are impractical. The reprocessing adapted to data quality limitations, utilizing time-domain algorithms. It involved assigning a crooked line geometry, conventional common-midpoint (CMP) processing, and less conventional common reflection surface (CRS) processing. CRS stacking, not reliant on stacking velocity estimation, improves seismic imaging quality. P-wave velocity models were reconstructed along the profiles through tomography algorithms applied to picked first arrivals. Post-stack time migration and depth conversions with vertical stretching were applied to CDP/CRS stacks.Despite limitations, these depth images, tied to exploration wells and geophysical logs, can significantly contribute to understanding the near-surface structure of this dynamic region and its structural and stratigraphic relations with the sedimentary Volturno Plain to the North.
Etna's paroxysmal activity in 2021: A deflation episode revealed by joint DInSAR and GNSS ground deformation analysis
Authors: Vásquez Castillo Alejandra , Guglielmino Francesco , Cannavò Flavio , Bonforte Alessandro , Puglisi Giuseppe
Published: March 2024

In the final months of 2020, the summit craters of Mount Etna displayed intense Strombolian-type activity as well as an increase in seismicity. In December 2020, a period of paroxysms with powerful, brief bursts of lava fountaining began, which intensified in February 2021 and lasted until April.We used both ascending and descending Sentinel-1 SAR images along with daily GNSS solutions at 21 stations to evaluate the surface deformation at Mount Etna in order to understand the dynamics of the shallow plumbing system, which is probably related with the feeding of the observed paroxysmal activity. According to the InSAR and GNSS time series, the volcano edifice entered a period of intense and continuous deflation for almost three months, matching the prolonged paroxysmal activity characterized by the occurrence of 17 lava fountain episodes. To integrate the two data sets, we have applied the 3D SISTEM algorithm, which allows to estimate 3D ground displacements by combining GNSS measurements of deformation and differential Interferometric Synthetic Aperture Radar (DInSAR) maps of surface displacement. We have used analytical models to constrain the sources of the paroxysmal activity and to evaluate the deflating source parameters by inverting the displacement obtained with the 3D SISTEM algorithm. Preliminary results reveal a centripetal deformation pattern that might be linked to a shallow source below the summit craters area. However, a detailed analysis of the deformation pattern indicates the presence of contributions that are not related to the magmatic source, but are probably attributable to tectonic or geomorphologic processes.The aim of this work is therefore twofold. First, to infer the shape and dynamics of the magmatic feeding system of Mount Etna and its magma discharging regime. Second, given the complexity of the deformation signals at Mount Etna, to analyze how to deal with their different contributions including volcanic‐, tectonic-, geomorphological processes, and atmospheric noise.
Feature tracking of sub-metre resolution Capella SAR imagery to measure mountain glacier ice flow
Authors: Izzard Jamie , Quincey Duncan J. , Elliott John R. , Wendleder Anna
Published: March 2024

In recent years, the number and capability of Synthetic Aperture Radar (SAR) sensors in low earth orbit has grown considerably, with multiple satellites now capable of capturing sub-metre resolution imagery. We present the first application of such very fine resolution SAR imagery to measure ice velocity of a high mountain glacier. To achieve this, we apply feature tracking to a pair of Capella images in spotlight mode (0.35 m resolution) acquired in July 2021 over Baltoro Glacier in the Karakoram, Pakistan, and compare the results to ice velocities derived from feature tracking using more commonly employed TerraSAR-X Stripmap (3 m) and Sentinel-1 Interferometric Wide (IW) (5 x 20 m) imagery. We show that Capella-derived velocities reveal subtle features that are not evident in velocities derived using coarser resolution imagery. In particular, slower moving ice at the glacier margin, variations in velocity between different flow units, and lateral fluctuations reflecting the local topography are all more clearly resolved. However, the small footprint of the imagery and lack of stable ground within the frame poses a challenge for co-registration which could affect the feasibility of broad-scale applications. Despite this, we show that sub-metre resolution SAR imagery enables us to observe and analyse glacier dynamics at temporal and spatial resolutions that were previously impossible using satellite-based methods. We suggest that such imagery may be used alongside in-situ methods to improve our understanding of fine-scale glaciological processes which may have a significant impact on broader scale glaciological systems. 
Morphological analysis and river inversion as a proxy to constraint upper crustal magmatic pluton emplacements: evidence from the Larderello-Travale Geothermal System, northern Apennines. 
Authors: Montanari Domenico , Lanari Riccardo , Marco Marco , Papeschi Samuele , Del Ventisette Chiara , Lupi Matteo
Published: March 2024

Geomorphological techniques are used worldwide to explore how the topography responds to surface, crustal and mantle processes. This is the case for the recent developed river dynamic model inversion, that promises to return time vs uplift rate histories required to achieve the modern fluvial configurations. In the framework of the ‘Migrate Project’, a multidisciplinary project combining geology, seismology and machine learning financially supported by the SNSF, we test a novel method of rivers inversion to constrain the surface vertical movements caused by the emplacement of middle-shallow crustal magmatic pluton. We selected, as case study, the Larderello-Travale Geothermal System (LTGS), in the northern Italian Apennines, where multiple magmatic bodies intruded since the late Pliocene causing a large-wavelength surface uplift of at least 600 meters. However, since none of the LTGS plutons reach the surface, their spatial distribution is only constrained by exploration wells or geophysical investigations. Our work aims to: (1) quantify the surface response to pluton emplacement and (2) identify intrusions not yet documented in the area.We modelled 31 river basins draining the LTGS and surrounding regions. For all catchments, the available ages of plutons constrained by wells, spatially correlate with the local peaks of increasing uplift rates (> 0.2 mm/y). We document a diffuse regional uplift during middle/late Pliocene, likely a consequence of the first magmatic pluton emplacement, followed by a continuous uplift throughout Quaternary times. However, during this time interval, the uplift style changed to confined pulses, which we interpret as locally emplaced magmatic batches. In addition, uplift rates decreased systematically from 0.6 Ma to present, which suggests a potential reduction on the topographic response to magma emplacement, even if the thermal anomaly is still quite evident. This work confirms that plutons provide a topographic swell, and we suggest that our approach could be used to locate undocumented plutons, leading to new potential strategies for geothermal exploration.
Using seismic and timelapse camera observations to study flood-induced morphological changes on an alpine gravel-bed reach
Authors: Johannot Adele , Gimbert Florent , Recking Alain , Piantini Marco
Published: March 2024

Morphological changes in alluvial rivers are very active and remain very complex to predict because of the high spatio-temporal variability of bedload. This strongly limits the ability of river managers to assess risk or conduct ecological restoration. With the recent development of non-intrusive methods to monitor bedload, such as seismic or acoustic tools, acquisition of data has been highly facilitated compared to direct measurement methods involving in-situ sampling. The challenging task remains in the interpretation of the signals during phases of intense bedload transport which are responsible for major morphological changes. The analysis of such signals requires a good understanding of the underlying physics as well as in-situ field observations to confort interpretation. In this work, we combine seismic with timelapse camera observations with the objective to have a better understanding of bedload behavior and its consequences on the morphology during floods on an alluvial reach of the Severaisse river in the French Alps. Data consists in 3 seismic sensors continuously recording at 200Hz from upstream to downstream along the reach, as well as data from 2 cameras taking timelapse photos of the reach at a 10 min interval during flood. We We find that high frequency seismic power, attributed to bedload, exhibits a characteristic scaling relationship against discharge, materialized by two different phases: a scaling of about 5 from above the threshold of motion (around 12m3/s water discharge) up to a critical discharge of 25 m3/s, and a scaling of about 1.4 above 25 m3/s. We interpret the first scaling to be due to bedload occurring in a diluted regime as described in previous models, and the second scaling to be due to bedload in an intense transport phase. This shift only occur during floods where we observe channel shifting or important re-working of the bed and we suppose that it represents a phase of intense transport responsible for morphological changes. Interestingly, for the most extreme flood with a return period of 50-years, the seismic power versus discharge relationship shows a distinct behavior form the other floods, materialized by a particularly larger and singular hysteresis. Next steps include understanding why this distinct signature occurs, quantify the morphological changes by calculating indexes from image analysis and investigate how bedload and hence the morphological changes depends on the season, characterized by a snow-melting spring and summer and rainy autumn and winter through a multi-year scale.
The turning point in vegetation decline in the Northern Hemisphere driven by hydroclimatic extremes
Authors: Du Ruohua , Wu Jianjun
Published: March 2024

Extreme climate events such as droughts and heatwaves significantly impact the stability of ecosystem function and are expected to intensify in the future. The mid-high latitude regions of the Northern Hemisphere (23.5° to 90°N) exhibit pronounced seasonality and are highly sensitive to climate variations. However, further research is needed to understand the vegetation decline and its changing trends driven by extreme hydroclimatic and their compound events in this region. This study, based on multi-source data including NDVI, LAI, and GPP from 1982 to 2015 as vegetation growth indicators, amid to identify vegetation decline during the growing season and explore its temporal trends, and to further reveal the seasonal response. The research supported the importance of drought and high temperature compared to extreme wet and cold conditions. Due to the high frequency, wide impact and long duration of impact, independent low SM dominated the cumulative vegetation decline, followed by low SM and high VPD compound events. High VPD caused stronger negative impacts on vegetation growth than high T and that it was more strongly coupled to SM. We further found a turning point in vegetation decline. Because of the significant increase in VPD and its enhanced coupling with low SM, low SM and its compound events, especially SM- & VPD+ & T+ compound events, led to a significant enhancement of the vegetation decline after about the 21st century. Furthermore, the sensitivity of vegetation growth to extreme hydroclimatic has also significantly increased, with stronger intensity of vegetation decline. Seasonally, early growing season vegetation was more vulnerable (with the strongest continuous decline) due to experiencing the longest duration of negative impacts, while summer vegetation was more sensitive to extreme hydroclimatic, with the strongest intensity. Notably, compound events of high VPD and low SM primarily affected summer vegetation growth. Additionally, there was a significant lag time in vegetation response to extreme hydroclimatic, especially to high VPD and high T. In over half of the regions, the vegetation response to high T and high VPD had a lag time exceeding two months, which may be associated with seasonal legacy. In the context of global warming, further investigation is needed to explore the inter-seasonal connections. This research significantly contributes to a deeper understanding of ecosystem responses to extremes hydroclimatic and its future changes.
Optimal blending of ensemble forecasts for probabilistic precipitation nowcasting
Authors: Weissmann Martin , Köhldorfer Simon , Necker Tobias , Kann Alexander
Published: March 2024

Precipitation nowcasting is essential for mitigating the negative effects of severe weather, necessitating accurate and timely forecasts. Our study introduces a novel Local Ensemble Transform Kalman Filter (LETKF)-based blending approach that effectively combines ensemble forecasts to provide cheap probabilistic nowcasts. Our method optimally weights ensemble probabilities by considering precipitation/radar observations as the ground truth. It shifts computed weights in time and refines neighborhood probabilities (NPs). The upscaling step for computing NPs introduces two free parameters, neighborhood size and precipitation rate, which can be selected based on the forecasters needs. Demonstrated within GeoSphere Austria's regional forecasting system using AROME ensemble forecasts over Austria, our technique was especially beneficial for short lead times of up to 2 hours. Longer lead times require to incorporate signal propagation, which is possible by shifting weights in space and time. Our study underscores the effectiveness of data assimilation techniques in enhancing ensemble blending. The proposed approach affordably improves the robustness and accuracy of short-term probabilistic forecasts and holds the potential for extending it to multi-model ensemble blending.