bluuebunny/crossref_metadata_2025 huggingface dataset:
Speleothem organic carbon isotopes as a novel tracer for terrestrial ecosystem change – new method developments
Authors: Lechleitner Franziska A , Rowan Sarah , Strähl Jan , Rauber Martin , Lang Susan Q , Szidat Sönke
Published: March 2022

The response of terrestrial ecosystems to anthropogenic climate change remains poorly understood and constitutes a major source of uncertainty in future climate projections. Stalagmites are a well-established terrestrial climate archive (Wong and Breecker, 2015), and may also serve as a sensitive recorder of surface ecosystem processes, as they are fed by dripping water that percolates through the soil zone. Coupled climate-ecosystem paleorecords from stalagmites could prove invaluable sources of information on the response of terrestrial ecosystems to past climatic shifts and their sensitivity to climate variability exceeding the instrumental range.

Here we present results from a method development study carried out at the Laboratory for the Analysis of Radiocarbon with AMS (LARA) at the University of Bern. Our results are based on a previous protocol by Lechleitner et al. (2019), which describes a rapid, low contamination method for carbon isotope analysis (δ13C and 14C) of the speleothem non-purgeable organic carbon (NPOC) fraction for small samples (<150 mg CaCO3). Decarbonation of acid digested carbonate samples is followed by wet chemical oxidation of the NPOC and analysis of the resulting headspace CO2 via mass spectrometry to determine its isotopic composition.

We have made significant progress in resolving the main issues that precluded the routine application of the method as presented in Lechleitner et al. (2019), namely incomplete removal of inorganic carbon from the sample solutions, and contamination from extraneous carbon at different method stages. Apart from an updated pre-cleaning protocol for stalagmite samples and extensive blank assessment, a new needle setup was installed, allowing reduction of the sample amount needed, and the CO2 flow is now being monitored during decarbonation to ensure complete removal of inorganic carbon prior to the oxidation step.

These results reiterate the great promise of this method to provide accurate, ecosystem-level information on past terrestrial environments at comparatively high temporal resolution.

 

References:

Lechleitner, F.A., Lang, S.Q., Haghipour, N., McIntyre, C., Baldini, J.U.L., Prufer, K.M., Eglinton, T.I., 2019. Towards organic carbon isotope records from stalagmites: coupled d13C and 14C analysis using wet chemical oxidation. Radiocarbon 61, 749–764. doi:10.1017/RDC.2019.35

Wong, C.I., Breecker, D.O., 2015. Advancements in the use of speleothems as climate archives. Quat. Sci. Rev. 127, 1–18. doi:10.1016/j.quascirev.2015.07.019
This Rift is on Fire: Volcano-Tectonic Evolution of the Christiana-Santorini-Kolumbo volcanic field, Aegean Sea
Authors: Preine Jonas , Hübscher Christian , Karstens Jens , Hooft Emilie , Nomikou Paraskevi
Published: March 2022

Many of the most hazardous volcanoes lie in rift systems, where tectonics often seems to exert control on magma emplacement. However, our current knowledge of the interplay between volcanism and tectonics is immature due to the lack of observations on geological time scales. Located in the southern Aegean Sea, the Christiana-Santorini-Kolumbo (CSK) volcanic field lies in a prominent continental rift zone caused by back-arc extension along the Hellenic Arc. Covered by numerous geophysical surveys, this area offers the unique possibility to reconstruct a volcanic rift in time and space. Previous studies have revealed that the CSK volcanic field developed during four distinct volcanic phases, which initiated in the Pliocene and only recently matured to form the vast Santorini edifice. Here, we combine P-wave velocity tomography models and high-resolution reflection seismic data to reveal the internal architecture and the spatio-temporal evolution of the rift basins as well as their relation to the evolution of the CSK volcanoes. Our joint analysis reveals a distinct NE-SW-directed horst-structure separating the volcanic rift into a volcanically active northwestern zone and a volcanically inactive southeastern zone. Using a refined seismo-stratigraphic framework of the internal architecture of the rift basins, we identify four distinct phases of the rift system that correspond to the volcanic phases of the CSK field. These phases reflect the gradual development of a Pliocene-Pleistocene NE-SW oriented fault system overprinting an older Miocene-Pliocene ESE-WNW oriented fault system. The latest volcanic phase, during which volcanism focussed on Santorini and became highly explosive, corresponds to a distinct shift in the tectonic behavior of the rift system after which enhanced subsidence at the Santorini-Anafi and Amorgos faults occurred that was rapidly filled up by thick volcano-sedimentary deposits. We conclude that the volcanism of the CSK field is fundamentally controlled by NE-SW-directed rifting, which lies parallel to the Pliny and Strabo trends of the southeastern Hellenic Arc. This volcanic system is bounded to the southeast by the Akrotiri-Anhydros horst, which seems to be a deep-rooted structural boundary for the volcanic plumbing system. The shift from ESE-WNW directed faulting to NE-SW directed faulting is an indication that the dominant direction of slab-rollback driving the extension of the CSK rift shifted from the southwestern to the southeastern Hellenic Arc with Santorini lying at the hinge of these trends.
Correcting biases in climate simulations using unsupervised image-to-image-translation networks
Authors: Fulton James , Clarke Ben
Published: March 2022

Global circulation models (GCMs) form the basis of a vast portion of earth system research and inform our climate policy. However, our climate system is complex and connected across scales. To simulate it, we must use parameterisations. These parameterisations, which are present in all models, can have a detectable influence on the GCM outputs.

GCMs are improving, but we need to use their current output to optimally estimate the risks of extreme weather. Therefore, we must debias GCM outputs with respect to observations. Current debiasing methods cannot correct both spatial correlations and cross-variable correlations. This limitation means current methods can produce physically implausible weather events - even when the single-location, single-variable distributions match the observations. This limitation is very important for extreme event research. Compound events like heat and drought, which drastically increase wildfire risk, and spatially co-occurring events like multiple bread-basket failures, are not well corrected by these current methods.

We propose using unsupervised image-to-image translations networks to perform bias correction of GCMs. These neural network architectures are used to translate (perform bias correction) between different image domains. For example, they have been used to translate computer-generated city scenes into real-world photos, which requires spatial and cross-variable correlations to be translated. Crucially, these networks learn to translate between image domains without requiring corresponding pairs of images. Such pairs cannot be generated between climate simulations and observations due to the inherent chaos of weather.

In this work, we use these networks to bias correct historical recreation simulations from the HadGEM3-A-N216 atmosphere-only GCM with respect to the ERA5 reanalysis dataset. This GCM has a known bias in simulating the South Asian monsoon, and so we focus on this region. We show the ability of neural networks to correct this bias, and show how combining the neural network with classical techniques produces a better bias correction than either method alone. 
Assessing risk managers' perceptions of risk mitigation strategies under a climate change and energy transition context. 
Authors: Mille Jonathan , Charlton Dr Danielle , Edwards Dr Stephen , Haklay Prof Muki
Published: March 2022

Climate change and the energy transition are long-term challenges that could occur in a chaotic and uncertain way. The potential and varied impacts of these phenomena on existing human systems is leading to a rethinking of the ability of organisations to adapt life-sustaining services and business supply chains. However, the different scenarios surrounding these two phenomena are not always well understood by the public, by those who manage critical infrastructure, businesses, key institutions and organisations and sometimes even by risk managers. In order to assess whether current risk management strategies are able to cope with these two phenomena, it is important to understand the knowledge and perceptions of risk managers of the impacts of climate change and energy transition. 

 

This research investigates the perception of climate change and energy transition by risk managers in order to (i) assess their understanding of the impact of the energy transition and climate change on current lifeline services and business supply chains, (ii) evaluate the needs of risk managers to integrate these phenomena into risk management strategies. Results of ongoing semi-structured interviews and questionnaires will be shared. Overall, the aim of this research is to improve cross-sectoral risk management strategies by integrating a systemic approach into risk management methodology and risk reduction strategies. 

 

The research has been conducted in Chile, which is a country critical  to the global energy transition. Chile  is the world's primary producer of copper (30%) and ranks second in global lithium production (20%), two minerals coveted by different economic sectors and necessary for the global energy transition. In addition the region is exposed to numerous natural hazards, including climate related phenomena and associated extreme weather and temperature events. The integration of risk management strategies that incorporate both climate change and a change in energy supply is crucial in order to avoid significant disruptions and cascading effects in the supply chains of these increasingly sought-after minerals. 
Ion-dependent adhesion between calcite surfaces
Authors: Dziadkowiec Joanna , Javadi Shaghayegh , Ban Matea , Jamtveit Bjørn , Røyne Anja
Published: March 2022

Disjoining pressure that operates between mineral surfaces in fluid-filled granular rocks is often strongly influenced by the ionic composition of pore solutions. Can various ionic species exhibit a remarkably different influence on the mineral adhesion and thus the cohesion within granular rocks? We explore this question in atomic force microscopy (AFM) experiments using two brittle calcite surfaces in a symmetrical surface configuration. Our AFM results show a robust difference between the adhesion in the presence of Na+ and Ca2+ ions. The adhesion is significantly higher for monovalent Na+ at a given ionic strength in comparison to more hydrated divalent Ca2+ cations. In addition, the adhesive forces are weakly modulated by the varying Ca2+ concentration. We thus infer that for weakly charged minerals such as calcite, Ca2+ can sustain relatively high positive disjoining pressures and thus thicker water films between the contacting mineral grains.
Annual crops yield, soil quality and gully filling practices at the Campiña in Southern Spain 
Authors: Castillo Carlos , Vallejo-Orti Miguel , Pérez Rafael , Taguas Encarnación V. , Wells Robert , Bingner Ronald , Gómez-MacPherson Helena
Published: March 2022

Gully filling practices are periodically carried out in commercial farms of annual crops in the Guadalquivir Campiña to reduce the extension of gully erosion after erosive events. Large quantities of fertile topsoil are scraped, transported and deposited by tractors and specialized machinery within eroded waterways. Thus, gullies are filled at the expense of soil quality in their vicinity leading to decreasing crop yields.

          The aim of this study is to evaluate the impact of recent filling practices in soil quality and crop production (wheat and sunflower) in four small gullied watersheds (< 5 ha) in a commercial farm near the town of Córdoba (Spain). Soil samples were taken at four transects defining 27 locations in each watershed (108 in total), including scraped, non-scraped and reference areas for analyzing  chemical and physical soil properties (cation exchange capacity CEC, texture, organic matter OM, carbonate content). In addition, at each sampling site, bulk density (BD, clod method), undrained shear strength (USS, vane test), soil colour (Munsell) and soil erodibility (jet test) were measured. At the same locations, yield surveys were conducted in 2 m2 plots at the end of May and July 2021 in watersheds on wheat and sunflower, respectively. Wheat grain and sunflower seeds were extracted, dried at 60ºC and weighted for the determination of crop yield.

          Significant differences were found between sampling sites in chemical and physical soil properties, with scraped areas showing light colours, lower CEC and OM and higher dry BD and USS. Soil colour was found to be a good proxy for soil quality. Topography along with soil quality explained ~ 60% of the crop yield variance, with showed large variations (between 3 and 6 t·ha-1 for wheat and 100 and 800 kg·ha-1 for sunflower). These results emphasize the need for quantitative analyses of gully erosion degradation to provide alternative and more efficient and sustainable management approaches for gully control.
Diverse models, diverse interglacial results? Sea ice physics versus model forcing
Authors: Sime Louise , Diamond Rachel , Schroeder David , Guarino Maria Vittoria , Sivankutty Rahul
Published: March 2022

Different IPCC-CMIP6 climate models give diverse results when run under common interglacial forcing. The mid-Holocene and the Last Interglacial are the two time periods from which we have the most results. The diversity is particularly true for the Arctic, where sea ice physics plays a key role. Whilst scientists have known for more than twenty years that summer temperatures in the Arctic during the Last Interglacial – the warm period around 127,000-128,000 years ago - were around 4°C above those of today (from lake, peat, and marine core data), the cause of this warmth puzzled scientists until 2020. Until 2020, it was thought this Last Interglacial warmth may have been driven by Arctic vegetation changes.  We present an analysis of a variety of CMIP6 model simulations run during the Last Interglacial.  Only one model simulates a fully sea ice-free Arctic during the summer –it includes an advanced representation of melt ponds in the sea ice model. Melt ponds are shallow pools of water which form on the surface of Arctic sea ice. We find that the inclusion of melt ponds within models is likely crucial for understanding Last Interglacial sea ice loss and Arctic warmth, and touch on the relationship between Arctic sea ice changes in warm climate and on high equilibrium sensitivity CMIP6 models. Alongside the impact of different physics in the models, we also consider forcing aspects including the impact of the meltwater from deglaciation and top-of-the-atmosphere radiation (orbital).
3D transversely isotropic shear-wave velocity structure of India and Tibet from joint modeling of Rayleigh and Love waves group velocity dispersion.
Authors: Dey Siddharth , Ghosh Monumoy , Banerjee Rupak , Sharma Shubham , Mitra Supriyo , Bhattacharya Shankar
Published: March 2022

We use regional Rayleigh and Love wave data, from 4750 earthquakes (M >= 4.0) recorded at 726 stations across India and Tibet, to compute fundamental mode group velocity dispersion between 10 s and 120 s, using the Multiple Filter Technique (MFA). These result in the dense coverage of 14,706 and 14,898 ray-paths for Rayleigh and Love waves, respectively. The dispersion data at discrete periods have been combined through a ray-theory based tomographic formulation to obtain 2D maps of lateral variation in group velocities, where the best resolution is upto 2.5° and 4° for Rayleigh and Love waves tomographic maps, respectively. The Peninsular Shield, the Himalayan foreland basin, the Himalayan collision-zone and the Tibetan Plateau, have been sampled at unprecedented detail. Rayleigh and Love wave dispersion curves, at each node point of the tomography, have been inverted for 1D isotropic shear-wave velocity structure of Vsv and Vsh, respectively, which are combined to obtain 3D Vsv and Vsh structures across India and Tibet. We jointly invert the two datasets at each node to obtain an isotropic 1D velocity structure. The isotropic inversion fits the two datasets reasonably well, however, the misfit in the dispersion dataset both at high and low periods is high. For this, we incorporate radial anisotropy in the velocity structure and parameterize the crust with three layers and upper mantle with two layers. Assuming this radially anisotropic earth structure, we use Genetic Algorithms (GA) to explore the model space extensively. The synthetic dispersion curves are computed using Thomson-Haskell method with reduced delta matrix. The free parameters used in the inversion are VPH and VSH, layer thickness (h) and Vs anisotropy represented by Xi (ξ=VSH/VSV)2. The non-linear inversion technique converges to a best-fitting model by iteratively minimising the misfit between the observed and the data. The 2D group velocity dispersion heterogeneities, the 3D structures of Vsv and Vsh (both isotropic and transversely isotropic) will be presented with a focus to characterize a) the structure of the Indian plate and it’s extent of underthrusting beneath Tibet, and b) to quantify the low-velocity zone at the base of the Himalayan wedge, across the basal decollement, which ruptures in megathrust earthquakes.
Linking contemporary parametric model uncertainties to projections of biogeochemical cycles
Authors: Löptien Ulrike , Dietze Heiner
Published: March 2022

Anthropogenic emissions of greenhouse gases, such as CO2 and N2O, warm the earth. This in turn modulates the atmospheric greenhouse gas concentrations. The underlying feedback mechanisms are complex and can be counterintuitive. Earth system models have recently matured to standard tools tailored to assess and understand these feedback mechanisms. Along comes the need to determine poorly-known model parameters. This is especially problematic for the ocean biogeochemical component where respective observational data, such as nutrient concentrations and phytoplankton growth, are rather sparse in time and space. In the present study, we illustrate common problems when attempting to estimate such parameters based on typical model evaluation metrics. We find very different parameter sets which are, on the one hand, equally consistent with (synthetic) historical observations while, on the other hand, they propose strikingly differing projections into a warming climate. By the example of simulated oxygen concentrations we propose a step forward by applying variance-based sensitivity analyses to map the respective parameter uncertainties onto their local manifestations - for both contemporary climate and climate projections. The mapping relates local uncertainties of projections to the uncertainty of specific model parameters. In a nutshell, we present a practical approach to the general question of where the present-day model fidelity may be indicative for reliable projections.

 
Analyzing the continent-ocean relationship in the centennial-scale Antarctic temperature variability over the past 2000 years
Authors: Lyu Zhiqiang , Goosse Hugues , Dalaiden Quentin , Crosta Xavier , Etourneau Johan
Published: March 2022

Reconstructions of Antarctic surface air temperature (SAT) covering the past two millennia include some large centennial variabilities that are still not well understood because of the model-data discrepancies. Paleoenvironmental and instrumental observations have highlighted strong interconnections in the Antarctic climate system as illustrated by close relationships between atmosphere and ocean (including sea ice) at all time scales. For instance, over past decades, the Amundsen Sea Low pressure (ASL) is associated with opposite regional sea ice changes in the Bellingshausen-Amundsen and Ross sea sector as well as with variations in snow accumulation over West Antarctica. This inspires us to explore the potentiality of better reconstructing and understanding the drivers of the centennial-scale variability of Antarctic SAT during the Common Era by taking advantage of those links between the Antarctic continental and the Southern Ocean data. To this end, we have compiled proxy-based sea surface temperature reconstructions for the Southern Ocean and qualitative sea-ice reconstructions around Antarctica, together with those having published ice-core based water isotopic and snow accumulation records. We first analyze the continent-ocean relationships by constraining the climate model with continental records through a data assimilation procedure. Results show that we are able to generally reproduce reconstructed variations in the Southern Ocean at centennial scale, particularly for sea surface temperature (SST) along the south Chilean coast and sea ice along the Antarctic Peninsula. In a second step, experiments with data assimilation combining both oceanic and continental records help us to determine how the inclusion of oceanic records improves the reconstruction of the SAT, atmospheric circulation, and sea ice (and SST) over the past two millennia in the high latitudes.

 

 
GPSFLOW: A Novel Simulator for Modelling Underground Hydrogen, CO2 and Gas Mixture Storage
Authors: Cai Zuansi , Zhang Keni , Guo Chaobin
Published: March 2022

Underground hydrogen storage can store grid-scale energy for balancing both short-term and long-term inter-seasonal supply and demand. However, there is no numerical simulator which is dedicated to the design and optimisation of such energy storage technology at grid scale. This study develops novel simulation capabilities for GPSFLOW (General Purpose Subsurface Flow Simulator) for modelling grid-scale hydrogen and gas mixture (e.g., H2-CO2-CH4-N2) storage in cavern, deep saline aquifers and depleted gas fields.

The accuracy of GPSFLOW is verified by comparisons against the National Institute of Standard and Technology (NIST) online thermophysical database and reported lab experiments, over a range of temperatures from 20-200 oC and pressure up to 1000 bar. The simulator is benchmarked against an existing model for modelling pure H2 storage in a synthetic aquifer. Several underground hydrogen storage scenarios including H2 storage in a synthetic salt cavern, H2 injection into a CH4-saturated aquifer experiment, and hydrogen storage in a depleted gas field using CO2 as a cushion gas are used to test the GPSFLOW’s modelling capability. The results show that GPSFLOW offers a robust numerical tool to model underground hydrogen storage and gas mixture at grid scale on multiple parallel computing platforms.
A multi-model ensemble Kalman filter for forecasting and data assimilation
Authors: Bach Eviatar , Ghil Michael
Published: March 2022

Data assimilation (DA) aims to optimally combine model forecasts and noisy observations. Multi-model DA generalizes the variational or Bayesian formulation of the Kalman filter, and we prove here that it is also the minimum variance linear unbiased estimator. However, previous implementations of this approach have not estimated the model error, and have therewith not been able to correctly weight the separate models and the observations. Here, we show how multiple models can be combined for both forecasting and DA by using an ensemble Kalman filter with adaptive model error estimation. This methodology is applied to the Lorenz-96 model and it results in significant error reductions compared to the best model and to an unweighted multi-model ensemble.
Drone-based GPR system for 4D glacier data acquisition
Authors: Ruols Bastien , Baron Ludovic , Irving James
Published: March 2022

Thanks to the excellent propagation characteristics of radar waves in ice, ground-penetrating radar (GPR) has been one of the key geophysical methods used in the field of glaciology over the last 50 years. Alpine glacier GPR surveys are typically performed either directly on the glacier surface (e.g., on foot, skis, or with snowmobiles), or by helicopter several tens of meters above the surface. Helicopter-based surveys allow the coverage of large areas safely and efficiently, but this comes at the expense of reduced resolution of glacier internal structures, particularly in the context of 3D surveys. On the other hand, ice-based acquisitions offer high-resolution opportunities, but are very time-consuming, often risky, and can be physically exhausting to perform. Recent advances in the development of drone technologies open new data acquisition possibilities for glacier GPR data, combining the advantages of both ice and air-based methods.

We have developed a drone-based GPR system that allows for safe and efficient high-resolution 3D and 4D data acquisition on alpine glaciers. Our custom-built GPR instrument uses real-time sampling to record traces of length 2800 ns, which corresponds to a depth of over 200 m in glacier ice. Each trace is stacked over 5000 times and acquired using a sampling frequency of 320 MHz, the latter of which is just enough to avoid aliasing with our single lightweight 70-MHz-center-frequency antenna. Traces are recorded at a rate of 14 Hz, meaning that a drone speed of at least 4 m/s can be considered while maintaining a sufficiently high trace density for high-resolution studies. This is at least four times faster than a conventional survey on foot. The total weight of our GPR system plus single transmit/receive antenna is around 2 kg. The drone used in our work has a maximum payload capacity of about 6 kg and is equipped with a radar-based ground sensor which enables us to follow the glacier surface topography during the flights. An independent differential GPS allows us to locate each recorded GPR trace with decimeter precision.

We performed initial testing of the above-described system in August 2021 on the Otemma glacier and successfully acquired around 70-line kilometers of 3D GPR data, over an 8-day period, covering a large portion of the glacier. In September 2021, we undertook additional fieldwork on the Tsanfleuron and Sex-Rouge glaciers and recorded 30-line kilometers of 3D GPR data in less than 3 days. We could then determine and model with high-precision the ice-thickness distribution over the Tsanfleuron pass. These first field results show the concrete benefit of drone-based GPR glacier surveys and motivate further development towards 3D and 4D studies.
Joint effects of climate, tree size, and year on annual tree growth derived from tree-ring records of ten globally distributed forests
Authors: Anderson-Teixeira Kristina ,   ForestGEO dendrochronology team
Published: March 2022

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree's growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥3-month seasonal windows) and negative to temperature (usually maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.
Rock slope dynamics in flysch formation under cold climate (part 3) : rockfall forecasting
Authors: Laliberté Jacob , Gauthier Francis , Tom Birien
Published: March 2022

Rockfalls are major natural hazards for road users and infrastructures in northern Gaspésie (Eastern Canada) where nearly 15 kilometers of road runs along 10 to 100 m high flysch rockwall. The Ministère des Transports du Québec (MTQ) has recorded more than 17 500 rockfalls that have reached the roadway since 1987, which represents a nearly permanent danger for users. In the late 90s, protective berms were erected to reduce the number of rocks reaching the roadway. Despite the efficiency of these infrastructures, more than a hundred events are still recorded each year. Based on previous studies showing that rock instabilities in this type of geology is strongly correlated with meteorological events, we used different machine learning methods (logistic regression, classification tree, random forest, neural network) to design the best operational rockfall prediction model. Three event variables based on different rock fall frequency and magnitude thresholds were created. Nearly one hundred weather variables were used to explain and predict events. Preliminary results show that thawing degree-days is one of the most effective variables explaining the occurrence of winter and spring rockfall events. In summer, rainfall intensity is the most potential explanatory variable. Finally, fall events appear to be more responsive to rain events and freeze-thaw cycles. In order to optimize the percentage of predicted events and reduce the false alarm ratio, it remains important to evaluate the impact of each parameter on the performance of the models. These models can be used operationally as decision support tools to predict days with high event probability.
Investigation of stochastic similarities between wind and waves and their impact on offshore structures
Authors: Vrettou Sofia Efraimia , Trompouki Alexandra , Iliopoulou Theano , Sargentis G.-Fivos , Dimitriadis Panayiotis , Koutsoyiannis Demetris
Published: March 2022

Offshore wind farms are increasingly gaining acceptance in the field of energy production. From an engineering point of view, such offshore structures are affected by various sources of uncertainty. The most severe one, is the impact that wave (height and period) and wind processes have, either at the fatigue, and in some cases failure of such structures, or at the efficiency of their energy production. In this work, we are focusing on the stochastic properties of the above processes and on their impacts on offshore structures. By extracting data from gauging stations at the Aegean Sea, we specifically examine the stochastic similarities among the marginal moments and the correlation function with focus on the extremes of the wind velocity and the wave height and period, and we discuss their impacts on open sea structures.
Distributed Modeling: from REA to hillslope-resolving 
Authors: Peters-Lidard Christa
Published: March 2022

Eric Wood's contributions to distributed modeling were partially motivated by a desire to test the REA hypothesis as well as by a desire to demonstrate the impact of remotely sensed data on hydrologic prediction.  In this brief talk, I will review the advances in distributed modeling, such as high-resolution terrain, distributed hydrometeorological forcings and soil-vegetation parameters, high performance computing and communications, data assimilation, coupled land-atmosphere modeling, that laid the foundation for macroscale and ultimately "hyperresolution" modeling.  These foundational advances exemplify the 3rd paradigm in hydrology and are moving us towards embracing a 4th paradigm in hydrology, where we enable a rigorous confrontation of our hypotheses embodied within our models with a range of data types across many locations and spatial-temporal scales.  
Classifying weather types in Europe by Self-Organizing-Maps (SOM) with regard to GCM-based future projections
Authors: Wehrmann Sibille , Mölg Thomas
Published: March 2022

The interdisciplinary research project "BayTreeNet" investigates the reactions of forest ecosystems to current climate dynamics. In the mid-latitudes, local climatic phenomena often show a strong dependence on the large-scale climate dynamics, the weather types (WT), which significantly determine the climate of a region through frequency and intensity. In the topographically diverse region of Bavaria, different WT show various weather conditions at different locations.

The meaning of every WT is explained for the different forest regions in Bavaria and the results of the climate dynamics sub-project provide the physical basis for the "BayTreeNet" project. Subsequently, climate-growth relationships are established in the dendroecology sub-project to investigate the response of forests to individual WT at different forest sites. Complementary steps allow interpretation of results for the past (20th century) and projection into the future (21st century). One hypothesis to be investigated is that forest sites in Bavaria are affected by a significant influence of climate change in the 21st century and the associated change in WT.

The automated classification of large-scale weather patterns is presented by Self-Organizing-Maps (SOM) developed by Kohonen, which enables visualization and reduction of high-dimensional data. The poster presents the evaluation and selection of an appropriate SOM-setting and its first results. Besides, it is planned to show first analyses of the environmental conditions of the different WT and how these are represented in global climate models (GCMs) in the past and future.
Leaf Area Index at a forested ICOS site: a detailed method comparison
Authors: Lange Holger , Tsai Yun-Yun , Cerny Jakub
Published: March 2022

The three-dimensional structure of forest canopies is essential for light use efficiency, photosynthesis and thus carbon sequestration. Therefore, high-quality characterization of canopy structure is critical to improving our carbon cycle estimates by Earth system models and better understanding disturbance impacts on carbon sequestration in forested ecosystems.

In this context, a widely used observable is the Leaf Area Density (LAD) and its integral over the vertical dimension, the Leaf Area Index (LAI). A multitude of methods exists to determine LAD and LAI in a forest stand. In this contribution, we use a mature Norway spruce forest surrounding an ICOS flux tower at Hurdal site (NO-Hur) to investigate LAD and LAI with six different methods: field campaigns using (1) the Plant Canopy Analyzer LAI-2000; (2) the LaiPen LP 110; (3) Digital Hemispheric Photography at a set of plots within the area; (4) a Lidar drone flight covering the footprint area of the tower; (5) an airborne Lidar campaign, and (6) a satellite LAI product (MODIS).

The horizontal spatial structure of LAI values is investigated using marked point process statistics. Intercomparison of the methods focusses not only on biases and root mean squared errors, but also on the spatial patterns observed, quantifying to which extent a simple bias correction between the methods is sufficient to make the different approaches match to each other.
Language model for Earth science for semantic search
Authors: Ramachandran Rahul , Muthukumaran Ramasubramanian Muthukumaran , Koirala Prasanna , Gurung Iksha , Maskey Manil
Published: March 2022

Recent advances in technology have transformed the Natural Language Technology (NLT) landscape, specifically, the use of transformers to build language models such as BERT and GPT3. Furthermore, it has been shown that the quality and the domain-specificity of input corpus to language models can improve downstream application results. However, Earth science research has minimal efforts focused on building and using a domain-specific language model. 

We utilize a transfer learning solution that uses an existing language model trained for general science (SciBERT) and fine-tune it using abstracts and full text extracted from various Earth science journals to create BERT-E (BERT for Earth Science). The training process utilized the input of 270k+ Earth science articles with almost 6 million paragraphs. We used Masked Language Modeling (MLM) to train the transformer model. MLM works by masking random words in the paragraph and optimizing the model for predicting the right masked word. BERT-E was evaluated by performing a downstream keyword classification task, and the performance was compared against classification results using the original SciBERT Language Model. The SciBERT-based model attained an accuracy of 89.99, whereas the BERT-E-based model attained an accuracy of 92.18, showing an improvement in overall performance.

We investigate employing language models to provide new semantic search capabilities for unstructured text such as papers. This search capability requires utilizing a knowledge graph generated from Earth science corpora with a language model and convolutions to surface latent and related sentences for a natural language query. The sentences in the papers are modeled in the graph as nodes, and these nodes are connected through entities. The language model is used to give sentences a numeric representation. Graph convolutions are then applied to sentence embeddings to obtain a vector representation of the sentence along with combined representation of the  surrounding graph structure. This approach utilizes both the power of adjacency inherently encoded in graph structures and latent knowledge captured in the language model. Our initial proof of concept prototype used SIMCSE training algorithm (and the tinyBERT architecture) as the embedding model. This framework has demonstrated an improved ability to surface relevant, latent information based on the input query. We plan to show new results using the domain-specific BERT-E model.
Orange snow and citizen science
Authors: Dumont Marie , Gascoin Simon , Reveillet Marion , Voisin Didier ,   Collectif neige orange
Published: March 2022

In the beginning of February 2021, a large dust plume travelled from the Sahara across the Mediterranean Sea and deposited a colorful layer of particles on the snow-covered slopes of the Pyrenees and the Alps. The event was widely reported in the media due to the surprising color of the sky and of the snow cover. 

To characterize the amount of dust deposited on the ground during this remarkable event, we organized a citizen science campaign. We collected 150 snow samples from which the deposited dust mass was measured over the Pyrenees, the French and the Swiss Alps. The analysis of all samples shows a robust deposition gradient from the Pyrenees to the Alps and enhanced deposition rates on south facing slopes in agreement with satellite data. The samples were used in combination with detailed snow modeling to evaluate the dramatic impact of the dust deposition on the melt and duration of the snow cover. 
Crater Rim Collapses Affect the Lava Fountaining Frequency during the Fagradalsfjall Eruption, Iceland 2021
Authors: Eibl Eva P. S. , Thórðarson Thorvaldur , Höskuldsson Ármann , Gudnason Egill Á. , Dietrich Thoralf , Hersir Gylfi Páll , Ágústsdóttir Thorbjörg
Published: March 2022

The Fagradalsfjall eruption on the Reykjanes peninsula, Iceland, lasted from 19 March to 18 September 2021. While it continuously effused lava at the beginning, it opened up 7 further vents in April and focused the activity from late April on Vent 5. Surprisingly the continuous effusion changed to pulses of lava effusion (as lava fountains or vigorous overflow) between 2 May and 14 June that was seismically recorded as tremor pulses. We examined the frequency of 6939 lava fountaining pulses based on seismological data recorded at NUPH at the SE corner of Núpshlíðarháls 5.5 km southeast of the active vent.

We subdivide the time period into 6 episodes based on sudden changes in the pattern. In this presentation we present the different fountaining patterns and systematic changes and discuss their origin. Our comparison with vent height, vent stability and lava effusion style, led us to conclude that the changes in the pulsing behaviour might be caused by collapses from the crater walls. The system is clearly unstable and evolving with time.
Radon hazard vs. radon risk – consequences for radon abatement policy
Authors: Bossew Peter , Petermann Eric
Published: March 2022

Exposure to indoor radon (Rn) is recognized as a health hazard which may cause several 100,000 lung cancer fatalities per year world-wide. Physical causes are Rn generation as part of the decay chains that originate in ubiquitous uranium and thorium and its transport through the natural to the built environment, where it can infiltrate indoor air. Generation and transport of Rn constitute geogenic Rn hazard. Its geographical distribution reflects the ones of the properties of the media in which the processes occur, namely their geochemistry and physical properties such as porosity, permeability and humidity. By linking to measured indoor Rn concentration, geogenic hazard can be transformed into the expected indoor Rn concentration in a hypothetical house at a location or the probability that in the house a Rn threshold is exceeded.

Hazard turns into risk if somebody is exposed to the hazardous agent. Given a certain amount of hazard, the risk results from conditions which enable exposure (defining vulnerability and susceptibility to the hazard) and the presence of people who are actually exposed. While hazard yields a probability that somebody exposed suffers a detriment, risk quantifies the size of the detriment, e.g. the expected number of Rn induced lung cancer fatalities per unit area. Elevated risk can occur also if the individual probability of detriment is low, if the number of exposed persons is high.

Rn abatement policy which through regulation aims to reduce the detriment, should respond differently to hazard and risk. In the former case, it should reduce the probability of individual high exposure occurring, by remediation, or avoiding it to occur, by preventive action. Responding to the latter means reducing collective exposure.

So far, policy has mainly focused on the first, i.e. hazard reduction, while comparatively less attention has been given to the second, although the overall detriment to society depends on it. Although Rn regulation has already been developed extensively in Europe, discussion of the aspect of collective risk reduction seems to be in the beginning only.

In this presentation, we outline the problem by showing the difference between hazard and risk and addressing existing Rn abatement strategies.
Improving hydrological process understanding and model prediction using soil moisture data
Authors: Branger Flora , Araki Ryoko , Wiekenkamp Inge , McMillan Hilary
Published: March 2022

Soil moisture is a critical control of process-based hydrologic models. This variable has so far been little used, mainly due to the difficulty to extract information from in-situ soil moisture observations that can be directly compared to simulated model variables. The concept of hydrological signature is now being increasingly used for the evaluation of hydrological models. However, hydrological signatures based on soil moisture are still rarely used.

We propose nine soil moisture signatures, encompassing three levels of hydrological time response (storm event response : rising time, normalized amplitude, response type, rising limb density, seasonal response : dates and durations of seasonal transitions, average characteristic values : distribution type, field capacity and wilting point). These signatures were applied to datasets from six in-situ observatories around the world with contrasted climates and land uses. The obtained values were analysed to assess whether the signatures could discriminate between land uses and could be interpreted in terms of hydrological processes.

Results showed that differences could be found between land uses for most signatures, and that these differences could be attributed to flow pathways or soil wetness, hence indicating that the signatures are good indicators of key hydrological processes and potentially useful for model evaluation.
Lithospheric and Atmospheric Changes Associated with Rapid, Pulsed Assembly of Mafic Upper Crust: Assembly of the Karoo LIP Intrusive Complex
Authors: Gaynor Sean P. , Augland Lars , Svensen Henrik H. , Schaltegger Urs
Published: March 2022

Large Igneous Provinces (LIPs) are commonly correlated with global climate change, and environmental, as well as biological, crises. These are short-lived igneous events, typically much less than 5 Ma, can erupt more than 1 Mkm3 of volcanic rocks, while potentially emplacing over 500,000 km3 of upper crustal intrusions. As a result, LIPs represent some of the most rapid periods of lithospheric growth, generating enormous volumes of mafic upper crust. Detailing the duration and pace of these high flux magmatic events has, however, is hampered by a lack of high-precision geochronology. We focus on the Karoo LIP in southern Africa as a natural laboratory for testing models on the formation of mafic upper crust through large-volume mafic LIP intrusions. The Karoo LIP is comprised of a suite of basaltic lava flows, sills, dike swarms, and was emplaced during the early Toarcian. Approximately 340,000 km3 of sills are interlaid within Karoo Basin sedimentary rocks. Differential uplift, erosion and availability of drill core material allows for sampling of the entire intrusive succession in the basin.

We report new high-precision U-Pb zircon and baddeleyite ages, Hf isotope compositions and apatite volatile compositions from sills emplaced from base to top of the Karoo Basin. Using these data, we are able to address several fundamental questions of LIP emplacement: (1) what is the total of intrusive LIP magmatism within the Karoo Basin; (2) is there variable magma flux during assembly of the intrusive complex; (3) is there is a relationship between age and structural position of sills within the basin; (4) is it justified to correlate the intrusion of the LIP with global climate change at this level of precision; (5) does the composition and extent of thermogenic degassing vary throughout the basin?

Our new data indicate that the 340,000 km3 of intrusive magmas were emplaced in approximately 500 kyr, solidifying new mafic upper crust through a downward stacking assembly, and that the entirety of intrusive magmas were emplaced within the uncertainty of the early Toarcian oceanic anoxic event. This pulsed assembly is in agreement with atmospheric models that require pulsed degassing of the basin to cause the observed early Toarcian isotope excursions. In addition, these data also indicate that dolerite sills throughout the basin assimilated sedimentary wall rock during crystallization, which helped facilitate zircon crystallization within pegmatitic pods interfingered within the sills. Finally, volatile compositions preserved in apatite indicate that thermogenic wallrock-sill interactions significantly affected the final volatile compositions of the sills, and trace the release of LIP-driven gases from the basin.