bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative performance study of TSMP under homogeneous, heterogeneous and modular configurations
Authors: Caviedes-Voullième Daniel , Benke Jörg , Tashakor Ghazal , Zhukov Ilya , Poll Stefan
Published: February 2023

The compartmentalised (modular) design often found in multiphysics Earth system models allows for progressive offloading of compute-intensive kernels to accelerators. The nature of this process implies that some model components will run on accelerators, while other components will continue to run on CPUs, leading to the use of heterogeneous HPC architectures. Furthermore, different hardware architectures (e.g. CPUs, GPUs, quantum, neuromorphic)  within an HPC system can be grouped into modules, each tailored to the requirements of a particular class of algorithms and software, and interconnected with other modules via a shared network. Some of these modules may be focused on energy-efficient scalability, whereas others may be disruptive and experimental. Such a conglomerate of different hardware modules, where each module can work stand-alone or in combination with other modules, leads to the idea of modular supercomputer architecture (MSA). The first exascale system in Europe (JUPITER) is expected to be modular, following on from the experience of the JUWELS system. This new paradigm poses questions on how performance and scalability of models change from homogeneous, to heterogeneous to modular systems. The Terrestrial Systems Modelling Platform (TSMP) is a scale-consistent, highly modular, massively parallel, fully integrated soil-vegetation-atmosphere modelling system coupling an atmospheric model (COSMO), a land surface model (CLM), and a hydrological model (ParFlow), linked together by means of the OASIS3-MCT library. Each of these submodels can be considered as a module, with different domain sizes, computational loads and scalability. This implies that optimal configurations for solving a given problem require understanding many levels of non-trivial load balancing. It is currently possible to offload ParFlow to GPUs, while keeping COSMO and CLM on CPUs. This enables both heterogeneous and modular configuration, and thus prompts the need to re-evaluate load distribution and scalability to find new optimal configurations. In a previous study, preliminary results on heterogeneous configurations were presented (https://doi.org/10.5194/egusphere-egu22-10006).In this contribution, we extend our study and present a comparative study of performance and scaling for homogeneous, heterogeneous, and modular TSMP jobs. We study strong and weak scaling, for different problem sizes, and evaluate parallel efficiency on all three configurations in the JUWELS supercomputer. We further explore traces of selected cases, to identify changes in behaviour under the different configurations, such as emergent MPI communication bottlenecks and root causes of the load balancing issues.  
Seismic emissions from a passing train: turning ambient noise into a controlled source
Authors: Rebert Théo , Allemand Thibaut , Bardainne Thomas , Cai Caifang , Chauris Hervé
Published: February 2023

Train traffic is a powerful source of seismic vibrations. Recent studies have shown that trains illuminate geological structures both at the crustal and the geotechnical scale. Existing works have been able to reconstruct approximately the spectral characteristics of the wavefield emitted by a passing train. In this work, we show that we can recover information on the train itself with high accuracy by looking only at the seismic recordings.We record passing trains with seismic accelerometers less than 2 meters away from the track. We can isolate the signal emitted by each wheel, and thus reconstruct the trajectory of the train. This trajectory reconstruction is performed using a non-linear waveform inversion algorithm involving the varying train speed, the spacing between the wheels and an apparent wavelet emitted when the wheel hits close to the seismic sensor. After low-pass filtering the data below 15 Hz for passenger trains passing at around 100 km/h, we obtain harmonious waveforms suitable for our inversion technique. Especially, we are able to pick each wheel from the raw trace, which allows for a robust initial model avoiding local minima trapping during the non-linear inversion. The estimated parameters are minimally influenced by seismic wave propagation speeds, because the closest sleeper dominates the signal in this frequency band.These results suggest that train traffic is a repeatable seismic source that can be can be characterized with good accuracy.  By having a better information about the source process, it might be possible to extract more information from the noise recordings, and thus gain in resolution in the imaging of the near surface. Especially, we expect enhanced repeatability of Rayleigh velocities measurements which is important for subsurface monitoring. Further, this also allows for railway traffic monitoring as trains can be identified and their speed measured as they cross seismic arrays.
Designing of novel hydroxyapatite nanoparticles from fish by-products to be coupled with highly efficient phosphate solubilising bacteria
Authors: Quattrocelli Piera , Pellegrino Elisa , Piccirillo Clara , Pullar Robert C. , Ercoli Laura
Published: February 2023

Hydroxyapatite nanoparticles (nHAs) deriving from by-products have gained increasing interest as novel phosphorus (P)-based fertilisers, since they can provide a slow P release, minimising P losses and adverse environmental side-effects, and reducing the dependency of agriculture on mineral fertiliser inputs. Phosphate solubilising bacteria (PSB) have proven to release P available for crop uptake from different inorganic sources (e.g. tricalcium phosphate, TCP, hydroxyapatite, HA). In the present study, nHAs were prepared from salmon (S-nHAs) and tuna (T-nHAs) bones by a calcination process, followed by a high energy ball milling. The obtained fine powders were characterised by scanning electron microscopy (SEM) for size and shape and by X-ray diffraction (XRD) for crystal phase composition. The phosphate solubilisation activity of seven selected PSB strains belonging to Pseudomonas and Paraburkholderia genera was in vitro investigated under acidic (pH = 5.5) and alkaline (pH = 7.5) conditions by a quantitative assessment of the solubilised PO43- from TCP, S-nHAs and T-nHAs over time. Moreover, time trend of pH and organic acids in the liquid media were investigated. Characterization of S-nHAs by XRD and SEM revealed a biphasic composition of the material consisting of TCP and HA – about 50 wt% of each phase - and a heterogeneous rounded-shape (Ø < 50 nm) material. By contrast, XRD pattern of T-nHAs showed a single-phase composition mainly made of pure HA (> 95 wt%) and SEM micrographs exhibiting an elongated shape uniform in size (200 x 30 nm). At day seven, Pseudomonas graminis PG0319 solubilised the highest proportion of the total PO43- in the TCP substrate under acidic pH (83%), followed by Pseudomonas rhodesiae PR0393 and P. graminis PG1211 (79% and 72%, respectively). In S-nHAs under alkaline pH, Paraburkholderia terricola PT0405, PR0393, PG0319 and PG1211 solubilised from 53% to 57% of the total PO43-, whereas in T-nHAs under acidic pH the maximum solubilisation efficiency was 27% by PT0405 at day seven. The difference in the solubilisation of S-nHAs and T-nHAs is due to the lower solubility of HA in comparison with TCP. Values of pH in in the liquid media decreased over the time along with an increasing PO43- solubilisation activity, suggesting an extracellular secretion of organic acids by PSB. Accordingly, differential patterns of organic acids were detected among strains with TCP as well as S-nHAs and T-nHAs. Notably, gluconic, propionic, fumaric and acetic acids played key roles during P solubilisation with all the tested strains, substrates, and pH conditions. Our results indicate that the use of microbial inocula together with P-based nanofertilisers is a promising option for a sustainable agricultural transition.
Hydrogen isotope offsets between palmitic acid and phytol increase during cyanobacterial blooms
Authors: Ladd Nemiah , Klatt Antonia , de Jonge Cindy , Reyes Marta , Schubert Carsten , Nelson Daniel
Published: February 2023

Hydrogen isotope fractionation between source water and lipids is highly variable among different taxonomic groups, and also among different compound classes within individual organisms. This variability results in lipid δ2H values that often span as much as two orders of magnitude more variability than that of environmental waters within typical ecosystems, indicating that lipid δ2H values may provide valuable biochemical and ecological information. These applications of lipid δ2H values remain underexplored.Recent results from algal batch cultures indicate that hydrogen isotope fractionation by cyanobacteria differs significantly compared to eukaryotic algae. In particular, in single species cultures with constant water δ2H values, cyanobacteria tend to produce fatty acids that are slightly 2H-enriched compared to those from most eukaryotic algae, while phytol from cyanobacteria is very 2H-depleted compared to phytol from eukaryotes. This results in larger offsets between the δ2H values of phytol and fatty acids for cyanobacteria than those observed in eukaryotic algae. In order to determine if δ2H offsets between fatty acids and phytol change in freshwater lakes with variable abundance of cyanobacteria, we collected algal biomass from two depths in the water column of Rotsee, a small lake in central Switzerland, every second week from January 2019 to February 2020. During this time the percentage of algal biovolume from cyanobacteria ranged from 0 to 82 %, with two distinct cyanobacterial blooms occurring in July and October.Water isotopes in the lake were relatively stable throughout the year, with water δ2H values varying by < 10 ‰. Lipid δ2H values, on the other hand, displayed extreme variability throughout the year. Palmitic acid (C 16:0) δ2H values varied by nearly 100 ‰ (–282 to –192 ‰), while those of phytol varied by more than 200 ‰ (–417 to –168 ‰). Consistent with expectations based on the results of cultures of single algal species, cyanobacterial blooms were characterized by larger offsets between the δ2H values of palmitic acid and phytol, and these offsets were positively correlated with the percentage of total algal biovolume attributable to cyanobacteria (R2 = 0.29; p < 0.01). These results suggest that hydrogen isotope offsets between palmitic acid and phytol in sediments have the potential to be developed as proxies for past cyanobacterial blooms, and demonstrate that hydrogen isotopes of lipids in the geologic record that are produced by many different types of aquatic organisms are more likely to be driven by ecological changes rather than changes in water isotopes.
National climate services for the German coasts
Authors: Jochumsen Kerstin , Janssen Frank , Kruschke Tim , Brauch Jennifer , Ehlers Birte-Marie
Published: February 2023

The German coastal areas of the North Sea and Baltic Sea: Wadden Sea World Heritage Site, 23000 km² of shipping lanes, around 600 km of dyke line and home of over 7 million people.Numerous actors such as coastal conservationists and port operators work on and with the coast. Climate change poses challenges for all of them. In order to meet these, knowledge about changes to the system due to climate change must be compiled. Possible impacts on the various fields of action must be evaluated and communicated.The Federal Maritime and Hydrographic Agency (BSH) is providing climate information based on observations and remote sensing data as well as water level forecasts, storm surge warnings and ice information for the German coast. In recent years, these fully established services were complemented by the DAS core service “Climate and Water” which is one of the measures translating the political framework “German Strategy for Adaption to Climate Change” (DAS) into action.We will provide information on the existing product portfolio of the national climate services, ranging from historical ice conditions to information on storms and sea level variations. Additionally, our service now includes information from high resolution climate simulations, and first results of the BSH model runs will be presented here. Special focus will be on the establishement of a feedback loop with important customers  and on the challenges in the user-provider-dialog.
First principles model of isotopic fractionation in formaldehyde photolysis: wavelength and pressure dependence
Authors: Pennacchio Luisa , E. Hillers-Bendtsen Andreas , V. Mikkelsen Kurt , S. Johnson Matthew
Published: February 2023

Experimental studies show large isotope-dependent effects in the photolysis rates of formaldehyde isotopologues, that are both wavelength and pressure dependent. These effects are on the order of 10-20% for 13C and 18O (L. Feilberg et. al, J. Phys. Chem. A, 109, 8314-8319, 2004), and 60% for CHDO (E. J. K Nilsson et. al, ACP, 14, 551–558, 2014). We have made a model of the elementary processes involved in the photodissociation including unimolecular dissociation, collisional quenching and crossing between excited state surfaces. Computational chemistry is used to characterize some of these processes. The model is validated by comparison to all existing experimental data and is then used to make predictions about the isotopic fractionation in additional isotopicules (and for conditions not yet addressed by experiment) including fractionation in clumped molecules. The following isotopologues of formaldehyde have been investigated; HCHO, DCHO, DCDO, D13CHO, H13CHO, HCH17O, HCH18O, H13CH17O and H13CH18O. Rice–Ramsperger–Kassel–Marcus (RRKM) theory was used to calculate the rates for decomposition of the S0, S1 and T1 states with CCSD(T)/aug-cc-pVTZ, ωB97X-D/aug-cc-pVTZ and CASPT2/aug-cc-pVTZ levels of theory. Furthermore, the rates and likelihood of intersystem crossing were investigated by including the spin-orbit coupling between the excited states. The model was able to replicate the experimental pressure trends accurately, however, the kinetic isotope effect was one order of magnitude too small for the non-deuterated isotopologues. We predict a large clumped isotope anomaly in 13C18O produced by formaldehyde photolysis.
Effects of cable geometry and specific noise sources on DAS monitoring potential
Authors: Bozzi Emanuele , Piana Agostinetti Nicola , F. Baird Alan , Becerril Carlos , Biondi Biondo , Fichtner Andreas , Klaasen Sara , Lindsey Nate , Nishimura Takeshi , Paitz Patrick , Shen Junzhu , Ugalde Arantza , Walter Fabian , Yuan Siyuan , Zhu Tieyuan , Saccorotti Gilberto
Published: February 2023

The Distributed Acoustic Sensing (DAS) method re-purposes fiber optic cables into a very-dense array of strain/strain-rate sensors, capable of detecting different types of seismic events. However, DAS data are characterized by lower SNRs compared with standard seismic sensors, mainly because of a) strong directivity effects, 2) ground coupling inhomogeneities, and 3) site effects. Hence, beyond the array geometry, specific noise sources may reduce the potential of DAS for seismic monitoring. Previous research has already shown successful case-studies for event detection/location. Nevertheless, a coherent test on the performances of various arrays of different sizes and geometries is still lacking.In this study, an extensive DAS database is organized for such a goal, including 15 DAS arrays that recorded at least one seismic event (located at a range of distances from the arrays). P wave arrival times are exploited to estimate the epicentral parameters with a Markov Chain Monte Carlo method. Then, to analyze the effects of cable geometry and potential sources of noise/ambiguity on the location uncertainties, a series of synthetic tests are performed, where synthetic traveltimes are modified as follows: a) adding noise with equal variance to all the DAS channels (SYNTH-01), b) adding noise characterized by an increasing variance with the distance from the event (SYNTH-02), c) simulating the mis-pick between P and S phases (SYNTH-03) and d) adding noise with a variance influenced by cable coupling inhomogeneities (SYNTH-04). Results show that the epicentral locations with automatic P wave arrival times have different degrees of uncertainty, given the geometrical relation between the event and the DAS arrays. This behavior is confirmed by the SYNTH-01 test, indicating that specific geometries provide a lower constraint on event location. Moreover, SYNTH-04 shows that simulating cable coupling inhomogeneities primarily reproduces the observed location uncertainties. Finally, some cases are not explained by any of the synthetic tests, stressing the possible presence of more complex noise sources contaminating the signals.
Potential to convert abandoned and orphaned oil and gas well sites for renewable energy production in Canada and the United States
Authors: Boutot Jade , Kang Mary
Published: February 2023

Millions of oil and gas wells are abandoned and orphaned in Canada and the United States. These well sites can be repurposed for wind and solar energy, while the wells access itself can be redeveloped for geothermal energy production. To identify opportunities for repurposing abandoned and orphaned wells and well sites for renewable energy development, we analyze public oil and gas well data from state, provincial, and territorial agencies to estimate the number and geospatial distribution of abandoned and orphaned wells in Canada and the United States. As of March 2022, we identify 4,724 orphaned wells and 420,113 abandoned wells in Canada and identify 123,318 orphaned wells (as of March 2022) and 3,151,700 abandoned wells (as of August 2022) in the United States. Using this dataset, we analyze geographic locations of abandoned and orphaned wells with national maps of renewable energy potential (geothermal, wind, and solar) and land cover/land use in Canada and the United States. We then evaluate how the potential to repurpose wells/well sites vary across Canada and the United States. Due to funding shortfalls, many abandoned and orphaned wells remain unplugged and are negatively impacting the environment and contributing to greenhouse gas emissions. Repurposing wells and well sites can provide an additional funding stream to manage the millions of abandoned and orphaned wells around the world.
What impact does the pathway through the solar corona make on CMEs?
Authors: Wyper Peter
Published: February 2023

Decades of observations have revealed that Coronal Mass Ejections (CMEs) come in a variety of forms. Some have a classic 3-part structure, whilst others can be fan shaped or jet-like. Some of these differences can be put down to projection effects, but differences in magnetic structure also play a key role. Observational and simulation studies are now highlighting that the path by which a CME flux rope traverses the solar corona, and in particular the magnetic structures it interacts with on the way, shape the ultimate characteristics of the CME further out in the heliosphere. Therefore, understanding the nature of CME flux rope interaction with the ambient corona is a key part of predicting their evolution through the heliosphere and ultimately their geoeffectiveness at Earth. In this talk I’ll discuss from a modelling perspective some recent efforts to understand this interaction process and what it tells us about CMEs on a range of scales.
Wave generation due to the collapse of partially and fully submerged granular columns in large-scale laboratory experiments
Authors: Treflik-Body Erica , Steel Elisabeth , Take Andy , Mulligan Ryan
Published: February 2023

Under changing climate, coastal regions are increasingly vulnerable to a variety of hazards, including rapid subaerial and submarine landslides. These hazards can generate tsunamis and dense turbidity currents, which threaten both onshore and offshore infrastructure. Due to the complex geomechanics of failure, limited physical modelling has been conducted that encompasses both the triggering of granular landslides and subsequent waves associated with partially and fully submerged mass failures. Further, experimental modelling of submerged failures has primarily focused on the waves generated in the direction of failure (seaward) and not on the waves formed above and behind the failure (shoreward). To this effect, a series of large-scale granular collapse experiments were conducted by releasing 0.75 m and 0.5 m tall columns of 9.25 mm nominal diameter river stone into reservoir depths ranging from 0.20 m to 1.10 m to explore the wave generation and runup processes in both seaward and shoreward directions. The columns were released by a pneumatically-actuated vertically rising gate designed for the 2.10 m wide and 1.20 m high glass-walled flume. The gate lifts rapidly in 0.7 s, which enables the instantaneous loss of support of the source volumes and results in granular collapse. The wave amplitude is measured using wave capacitance gauges and the failure mechanics are captured with high speed cameras. Overall, the wave amplitudes measured in these highly instrumented large-scale physical models are in good agreement with empirical relationships developed in a previous study using smaller-scale models. The large-scale experimental results provide insight and opportunity to develop relationships between the initial column submergence depth and the magnitude of the shoreward propagating waves, which has previously not been explored. Connecting the amplitude of the waves with the tsunamigenic potential for partially to fully submerged granular materials will assist in understanding risk to offshore infrastructure and communities in coastal regions.
 
 
Trench retreat rates in narrow subduction zones controlled by overriding plate thickness
Authors: Gea Pedro J. , Mancilla Flor de Lis , Negredo Ana M. , van Hunen Jeroen
Published: February 2023

Subducting slabs are the main drivers of plate motion and flow in Earth’s mantle. Thus, much effort has been put into understanding the main factors controlling slab dynamics and subduction-induced mantle flow. Slab width (W) has been shown to have a major role in controlling the subduction dynamics and more specifically, the trench motion (e.g., Stegman et al., 2006; Schellart et al., 2007). Both numerical modelling experiments and retreat velocities observed in wide subduction zones show that the trench retreat velocity (VT) decreases as the slab is wider. However, observations on natural narrow subduction zones (W ≤ 1000 km, e.g. Calabria, Gibraltar, Scotia) do not show a direct relation between W and VT, thus indicating that other factors, still poorly understood, may play a more relevant role on trench retreat velocities. The aim of this work is to identify which are these factors that exert a dominant control. To accomplish this, we use self-consistent 3D numerical subduction models to systematically evaluate the effect of slab width, strength of coupling with the lateral plate and overriding plate thickness on trench motion. In contrast to what happens in moderate to wide subduction zones, our simulations show that slab width has little influence on trench retreat velocity for narrow subduction zones, which is a robust result for different viscous couplings at the lateral slab edge.  On the contrary, our results indicate that the major influence is exerted by the thickness of the overriding plate, with the trench retreat velocities decreasing noticeably as the plate thickness increases. These results are in agreement with retreat velocities observed in narrow subduction zones showing no direct relation with slab width, but an inverse dependence on overriding plate thickness. ReferencesSchellart, W. P., Freeman, J., Stegman, D. R., Moresi, L., and May, D. (2007). Evolution and diversity of subduction zones controlled by slab width, Nature, 446(7133), 308–311. doi:10.1038/nature05615Stegman, D. R.; Freeman, J.; Schellart, W. P.; Moresi, L.; May, D. (2006). Influence of trench width on subduction hinge retreat rates in 3-D models of slab rollback, Geochemistry Geophysics Geosystems, 7(3), Q03012–. doi:10.1029/2005gc00105
A number density/temperature description of the Earth’s outer radiation belt
Authors: Rasinskaite Dovile
Published: February 2023

Substorms can inject electrons of energies ranging from 10s to 100s keV (often called source and seed populations) into the magnetosphere which can be accelerated to relativistic energies and be harmful to space-based infrastructure. Here we present a number density/temperature description of the Earths outer radiation belt obtained by using omni-directional flux and energy measurements from the HOPE and MagEIS instruments from the Van Allen Probe mission. This dataset provides a comprehensive statistical study of the whole Van Allen probe era. Values of number density and temperature are extracted by fitting energy and phase space density in log space to find the distribution function. Zeroth and second moments are taken respectively of the distribution function to find the number density and temperature. A number density/ temperature description is advantageous over an energy/flux description as it allows to differentiate between the transport and heating of electrons. The shape and variation of plasma distributions is also discussed, and general statistical properties presented. The relative importance of transport and heating is also discussed. We will explore the classification of substorm injections (i.e., is the injection a heating or transport of electrons, or a combination of both) and this technique can be extended across more energy ranges. 
Analysis of erosion drivers in the Hydrological Open Air Laboratory Petzenkirchen
Authors: Rab Gerhard , Krammer Carmen , Brunner Thomas , Schmaltz Elmar , Széles Borbála , Blöschl Günter , Strauss Peter
Published: February 2023

Soil erosion and sediment loading are mainly caused by extreme events with rare occurrence. Thus, long term observation is necessary for identification of causes and factors that trigger the erosion process and lead to the generation of river sediment.To investigate the main drivers of erosion in the catchment of the Hydrological Open Air Laboratory (HOAL) Petzenkirchen, we performed time series analyses for the period of 2002-2022, including agricultural land use, precipitation, discharge and sediment load with high temporal and spatial resolution. The HOAL Petzenkirchen, located in the alpine forelands of Lower Austria, extends to 66 ha and is mainly used for intensive agriculture.To highlight the effect of heavy precipitation events, a 100-year flood event that occurred in 2021 is analysed in detail to demonstrate the immense impact of such events on the sediment loading.
Risk communication during seismo-volcanic crises: the example of Mayotte, France
Authors: Lacassin Robin , Devès Maud , Pécout Hugues , Robert Geoffrey
Published: February 2023

Population information is a fundamental issue for effective disaster risk reduction. As demonstrated by numerous past and present crises, implementing an effective communication strategy is, however, not a trivial matter. Here, and in Devès et al. 2022, we draw lessons from the seismo-volcanic “crisis” that began in the French overseas department of Mayotte in May 2018, and which is related to a submarine eruption off the eastern coast of the island. The seismo-volcanic activity is still ongoing today and large uncertainties remain about its possible future evolution. Mayotte’s case study is interesting for several reasons: (1) although the seismo-volcanic phenomenon itself is associated with moderate impacts, it triggered a social crisis that risk managers themselves qualified as “a communication crisis”, (2) risks are perceived mostly indirectly by the population, which poses specific challenges, in particular to scientists who are placed at the heart of the risk communication process, and (3) no emergency planning or monitoring had ever been done in the department of Mayotte with respect to volcanic issues before May 2018, which means that the framing of monitoring and risk management, as well as the strategies adopted to share information with the public, has evolved significantly over time. Our first contribution is to document the gradual organization of the official response. Then we attempt to understand what may have led to the reported “communication crisis”. To that end, we collect and analyze the written information delivered by the main actors of monitoring and risk management to the public from May 2018 to April 2021. Finally, we compare its volume, timing, and content with what is known of at-risk populations’ information needs. Our results outline the importance of ensuring that communication is not overly technical, that it aims to inform rather than reassure, that it focuses on risk and not only on hazard, and that it provides clues to possible risk scenarios. We issue recommendations for improvement of public information about risks in Mayotte, but also elsewhere in contexts where comparable geo-crises may happen. Devès, M., Lacassin, R., Pécout, H., & Robert, G. (2022). Risk communication during seismo-volcanic crises: the example of Mayotte, France. Nat. Hazards Earth Syst. Sci., 22, 2001–2029, https://doi.org/10.5194/nhess-22-2001-202
End-to-end modelling of flood risk and impact for climate change resilience
Authors: Jones Anne , Taylor Andrew , Butt Junaid , Edwards Blair , Diaz Jorge Luis Guevara , Avegliano Priscilla Barreria
Published: February 2023

Climate change is driving increased urgency for better quantification of climate hazards and their impacts for stakeholders across multiple economic sectors. Flooding has been highlighted as one of the most significant climates risk to UK economic infrastructure, with costs expected to increase with climate-driven changes to rainfall, such as increased intensity of summer storms. To accelerate climate change adaptation and enable economic resilience to climate change impacts, close collaboration is needed between climate scientists, impact modellers, and stakeholders, and technology advances can support this by enabling and streamlining the process of developing and deploying climate impact modelling workflows to translate complex datasets and scientific models into actionable information.In this presentation, we describe the application of such a technology for the case of pluvial flooding, undertaken as part of the IBM Research and Science and Technology Facilities Research Council partnership, the Hartree National Centre for Digital Innovation (HNCDI), a 5-year programme established to develop and apply new technology to key economic challenges in the UK. Here, we model pluvial flood hazard for a case study region in northeastern England, using a 2-d physical simulation model of flood inundation, driven by open-access geospatial and climate datasets. Flood hazard maps are translated to impact using open asset location data and damage functions.We consider the sensitivity and scalability (in terms of computational cost) of the hazard and impact predictions to multiple factors, including (1) DEM/DSM representation of land surface (2) soil and land use parameterisation, and (3) model spatial resolution. We also contrast the use of drivers in the form of extreme rainfall scenarios created using a traditional design storm approach, and ensembles of synthetic storms from a stochastic weather generator, both derived from hourly 1km gridded rainfall observations. Finally, we reflect on key gaps to be addressed in the models, data and technology to meaningfully inform climate adaptation across industry sectors.
Deep learning for mapping water bodies in the Sahel
Authors: de FLEURY Mathilde , Kergoat Laurent , Brandt Martin , Fensholt Rasmus , Kariryaa Ankit , Kovács Gyula Mate , Horion Stéphanie , Grippa Manuela
Published: February 2023

Inland surface water, especially lakes and small water bodies, are essential resources and have impacts on biodiversity, greenhouse gases and health. This is particularly true in the semi-arid Sahelian region, where these resources remain largely unassessed, and little is known about their number, size and quality. Remote sensing monitoring methods remain a promising tool to address these issues at the large scale, especially in areas where field data are scarce. Thanks to technological advances, current remote sensing systems provide data for regular monitoring over time and offer a high spatial resolution, up to 10 metres.  

Several water detection methods have been developed, many of them using spectral information to differentiate water surfaces from soil, through thresholding on water indices (MNDWI for example), or classifications by clustering. These methods are sensitive to optical reflectance variability and are not straight forwardly applicable to regions, such as the Sahel, where the lakes and their environment are very diverse. Particularly, the presence of aquatic vegetation is an important challenge and source of error for many of the existing algorithms and available databases.  

Deep learning, a subset of machine learning methods for training deep neural networks, has emerged as the state-of-the-art approach for a large number of remote sensing tasks. In this study, we apply a deep learning model based on the U-Net architecture to detect water bodies in the Sahel using Sentinel-2 MSI data, and 86 manually defined lake polygons as training data. This framework was originally developed for tree mapping (Brandt et al., 2020, https://doi.org/10.1038/s41586-020-2824-5).   

Our preliminary analysis indicate that our models achieve a good accuracy (98 %). The problems of aquatic vegetation do not appear anymore, and each lake is thus well delimited irrespective of water type and characteristics. Using the water delineations obtained, we then classify different optical water types and thereby highlight different type of waterbodies, that appear to be mostly turbid and eutrophic waters, allowing to better understand the eco-hydrological processes in this region.  

This method demonstrates the effectiveness of deep learning in detecting water surfaces in the study region. Deriving water masks that account for all kind of waterbodies offer a great opportunity to further characterize different water types. This method is easily reproducible due to the availability of the satellite data/algorithm and can be further applied to detect dams and other human-made features in relation to lake environments. 
Attribution of flood changes with time series in the presence of autocorrelation: Modifications for Spearman‘s Rho and Kendall‘s Tau
Authors: Lun David , Fischer Svenja , Viglione Alberto , Blöschl Günter
Published: February 2023

Statistical dependency measures such as Kendall’s Tau or Spearman’s Rho are frequently used to analyse the coherence between time series in environmental data analyses. Autocorrelation of the data can however result in spurious cross correlations if not accounted for. Here, we present the asymptotic distribution of the estimators of Spearman’s Rho and Kendall’s Tau, which can be used for statistical hypothesis testing of cross-correlations between autocorrelated observations. The results are derived using U-statistics under the assumption of absolutely regular (or β-mixing) processes. These comprise many short-range dependent processes, such as ARMA-, GARCH- and some copula-based models relevant in the environmental sciences. We show that while the assumption of absolute regularity is required, the specific type of model does not have to be specified for the hypothesis test. Simulations show the improved performance of the modified hypothesis test for some common stochastic models and small to moderate sample sizes under autocorrelation. The methodology is applied to observed time series of flood discharges and temperatures in Europe and yields results that are consistent with the literature on flood regime changes in Europe. While the standard test results in spurious correlations between floods and temperatures, this is not the case for the proposed test, which is more consistent with the literature on flood regime changes in Europe.
Using pseudo-global-warming storylines and process-based ecosystem models for impact assessment of extreme events on agricultural production.
Authors: Martin Lioba , Haas Edwin , Kraus David , Grote Rüdiger , Scheer Clemens
Published: February 2023

With an increasing probability of extreme events, their significance for agricultural production has also grown. Ecosystem models enable us to integrate current knowledge about plant-climate interactions with climate change scenarios. Since impacts of weather extremes differ depending on crop, intensity, length, and timing, a process-based approach is necessary to quantify to what extent extreme events impact agricultural production. We used the ecosystem model LandscapeDNDC to evaluate the effect of extreme conditions, like drought or intense heat waves, on agricultural production. We modified LandscapeDNDC to better account for heat stress by integrating a yield reduction function dependent on the timing and intensity of a heat wave and crop fatality due to stress overload. We validated the model performance using historical yield records at the regional scale.In the second step, we applied pseudo-global-warming storylines to assess how the extreme heat wave of 2018 – 2022 would have affected yields of maize and wheat in a + 2 K warmer world. This exercise identifies which regions are most vulnerable regarding climate extremes and quantifies to what extent extreme climate events can affect crop yields compared to baseline conditions. Using process-based ecosystem models in combination with storyline-based climate projections is a promising approach to assess the impact of low-probability extreme weather events with a potentially high-impact outcome on agricultural production.
Numerical modelling of flanking structures in layered viscous media
Authors: Dabrowski Marcin
Published: February 2023

Flow perturbation can deflect the layering of the host rock around slip surfaces in shear zones resulting in the development of flanking structures. The details of flanking structure geometry can provide important clues about shear sense, flow kinematics, and finite strain, although not without ambiguities. The developing structures share similarities to fault-related folds that play an important role in sedimentary basins.Mechanical anisotropy has been shown to have a major influence on both the slip rate and flow perturbation. Willis (1964) derived an analytical solution for an elliptical inclusion embedded in a homogeneous anisotropic elastic matrix subject to a uniform load in the far field. The solution can be reduced to the case of an incompressible viscous medium and an arbitrarily oriented inviscid slit (slip line). The reduced solution, which is exact for the initial state of homogeneous planar anisotropy, provides useful insights into the initial stages of deformation and it can be used to approximately study finite strain deformation of a power-law host. However, anisotropic fluids such as ductilely deforming foliated rocks keep a ‘memory’ of deformation due to their evolving microstructure, which affects the flow field. In this study, I will use different numerical modeling techniques to examine the impact of host layering on the perturbing flow and structure development around a slip surface in shear zone.
Probing Into the Crust Through eastern Scotland: seismological contraints on the Highland Boundary Fault
Authors: Gilligan Amy , Hawthorn David , Clark Robert , Baker Sophia , Blackwell Alice , Cornwell David , Gani Inuwa Lukman , Kennedy Heather , Löer Katrin , Madani Ahmed , Watt Emma
Published: February 2023

The Highland Boundary Fault (HBF) delineates a fundamental division in the topography and surface geology in Scotland, separating 1000-500Ma metamorphic rocks to the north from predominantly ~440-360Ma sedimentary rocks of the Midland Valley to the south. Despite detailed geological mapping of the HBF and surrounding areas, the role(s) of the HBF in the tectonic history of Scotland is contested. On one hand, the HBF may represent a major plate boundary that was active initially as a strike-slip, then reactivated as a high angle thrust fault. On the other hand, some argue that lateral movement on the HBF was limited, and the topographic break seen at the HBF is primarily due to differences in erosion rates. Seismicity on the HBF has been reported in both the instrumental and historical records, including a M4.8 earthquake in Comrie in 1839 and an earthquake swarm in Aberfoyle in 2003. Notably, no seismicity has been observed in northeast Scotland. It may be that there is no seismicity in this region, or that the distribution of seismic instrumentation has been insufficient to detect very small magnitude earthquakes (<M2). To address these questions, in March-May 2022 we deployed a new network of 10 seismometers in north eastern Scotland as part of the PICTS (Probing Into the Crust Through eastern Scotland) project, which, together with a BGS Seismology permanent station, DRUM, form three transects across the HBF. These instruments form the first dense seismometer deployment in this region and data from them will allow us to place high-resolution constraints on the structure of the crust and uppermost mantle across the HBF, determine crustal thickness in this region, and to investigate if any seismicity is occurring on the eastern portion of the HBF. Here we present preliminary results from the data recorded on seismometers from the PICTS project, including images of crustal structure from receiver function analysis that show differing crustal structure to the north and south of the HBF. 
Consequences of Fault Reactivation on Subsurface Flow in Crystalline Rock
Authors: Kern Dominik , Silbermann Christian B. , Magri Fabien , Steffen Rebekka , Steffen Holger , Nagel Thomas
Published: February 2023

Important aspects for subsurface installations, such as Deep Geological Repositories (DGRs), in crystalline rock are the presence and evolution of fractures and faults, since they control the subsurface flow regime. According to climate extrapolation, it is expected that cold and warm period will alternate, accompanied by ice sheet progression and regression. The large moving mass of an ice sheet causes a dynamic response of the earth's crust, referred to as glacial isostatic adjustment (GIA) [1]. GIA changes the displacement and stress field not only under and near the ice sheet but also in its far-field. In view of the long-term assessments, we apply boundary conditions derived from an established GIA model [2] in order to analyze induced far-field stress and pore pressure changes and their impacts on existing faults in a hydromechanical simulation. As indicator for permeability changes we apply the Coulomb failure stress criteria. To quantify the consequences on the subsurface flow we run a component transport simulation before and another after the fault reactivation, revealing how the faults canalize the radionuclid propagation. For both kinds of simulations, hydromechanical and component transport, we apply Finite-Element methods (FEM) [3].The INFRA project is funded by the DFG under grants NA1528/2-1 and MA4450/5-1. [1] Holger Steffen, Patrick Wu. "Glacial isostatic adjustment in Fennoscandia - a review of data and modeling". Journal of geodynamics 52.3-4, p. 169-204, 2011. https://doi.org/10.1016/j.jog.2011.03.002[2] Georg Kaufmann. "Program package ICEAGE". Manuscript, Institut für Geophysik der Universität Göttingen, vol. 40. p. 840, 2004.[3] OpenGeoSys 6.4.3. Lars Bilke, Thomas Fischer, Dmitri Naumov, Christoph Lehmann, Wenqing Wang, Renchao Lu, Boyan Meng, Karsten Rink, Norbert Grunwald, Jörg Buchwald, Christian Silbermann, Robert Habel, Linda Günther, Mostafa Mollaali, Tobias Meisel, Jakob Randow, Sophia Einspänner, Haibing Shao, Kata Kurgyis, Olaf Kolditz, Jaime Garibay. 2022. https://doi.org/10.5281/zenodo.709267
Comparison of Methods for Learning Differential Equations from Data
Authors: Schötz Christof
Published: February 2023

Some results from the DEEB (Differential Equation Estimation Benchmark) are presented. In DEEB, we compare different machine learning approaches and statistical methods for estimating nonlinear dynamics from data. Such methods constitute an important building block for purely data-driven earth system models as well as hybrid models which combine physical knowledge with past observations.Specifically, we examine approaches for solving the following problem: Given time-state-observations of a deterministic ordinary differential equation (ODE) with measurement noise in the state, predict the future evolution of the system. Of particular interest are systems with chaotic behavior - like Lorenz 63 - and nonparametric settings, in which the functional form of the ODE is completely unknown (in particular, not restricted to a polynomial of low order). To create a fair comparison of methods, a benchmark database was created which includes datasets of simulated observations from different dynamical systems with different complexity and varying noise levels. The list of methods we compare includes: echo state networks, Gaussian processes, Neural ODEs, SINDy, thin plate splines, and more.Although some methods consistently perform better than others throughout different datasets, there seems to be no silver bullet.
Improving estimations of design storms from weather radar observations using a simplified metastatistical extreme value approach
Authors: Lengfeld Katharina , Marra Francesco
Published: February 2023

Extreme precipitation is among the most devastating atmospheric phenomena, causing severe damage worldwide, and is likely to intensify in strength and occurrence in a warming climate. Quantifying the frequency of occurrence of short-duration extreme rainfall exceeding certain amounts is important for hydrologists and urban planners. In Germany, the official design storms are determined from long time series of stations measurements (KOSTRA DWD2010R). Stations, however, only represent a limited region and cannot provide information for ungauged areas. Weather radar networks represent an alternative to overcome these issues, but their time series currently span periods of up to a few decades. Therefore, estimating design precipitation from radar observations with traditional methods is prone to large uncertainties because only few extreme events are included in the statistical analyses. Recently, non-asymptotic approaches, such as the simplified metastatistical extreme value, proved promising in estimating design precipitation from short records of sub-daily data, such as the ones from weather radar archives. We will present the results obtained applying the simplified metastatistical extreme value approach to the 21-year time series of the German weather radar network, and compare them to traditional estimates from the KOSTRA DWD2010R and to estimates from station observations. Using the simplified metastatistical approach, we find a clear reduction in uncertainty of hourly to daily design precipitation with return periods of 5, 20 and 100 years. Last, we show that the simplified metastatistical approach is less sensitive to particularly extreme events (such as the July 2021 event in Western Germany) than traditional methods.