bluuebunny/crossref_metadata_2025 huggingface dataset:
Litter mixing leads to the formation of a common decomposition pattern in a bog ecosystem
Authors: Müller Raphael , Zahorka Apoline , Holawe Franz , Glatzel Stephan
Published: February 2023

Peat accumulation is the result of a small imbalance between the formation and decomposition of plant litter. Changing environmental conditions alter the vegetation cover in peatlands and therefore litter quality inputs. Litter mixing effects, describing variable interactions between different litter types and decomposition rates, have been studied, but observations and directions of non-additive effects are not consistent. To better understand litter mixture effects of an ombrotrophic bog, where the encroachment of vascular plants has been observed, we incubated pure litter (Sphagnum (S), Betula (B), Calluna (C)) and three resultant mixtures (SB, SC, BC) over 70 days.We hypothesized that decomposition pattern of pure substrates differs from mixtures. Also, substrate specific decomposition patterns develop at the beginning of the experiment, which should harmonize with increasing time. Mixtures containing S litter have lower decomposition rates than their pure constituents, while mixtures without S (i.e. BC) show higher decomposition rates.For our incubation study, we collected three litter types (Calluna vulgaris (L.) Hull., Sphagnum capillifolium (Ehrh.) Hedw., Betula pubescens Ehrh.) from an ombrotrophic bog (Pürgschachen Moor, Austria). Oven-dried (60 °C) and sieved (< 2 mm) litter was used for litter bags containing 1 g of pure litter (S, B, C) or mixtures (SB, SC, BC). Bags were inoculated with bog water for 24 h and incubated in 50 mL conical tubes containing 4.5 mL of saturated K2SO4 (glass marbles were used to avoid contact) to ensure constant relative humidity. For every sampling day (0, 2, 14, 28, 70) four replicates of each substrate were prepared. Three bags per day were used for measurements of CO2 production rates, water extractable organic carbon (WEOC) and nitrogen (TN-L), mass loss and total carbon analysis. We measured the specific ultraviolet absorbance at 254 nm (SUVA254) to monitor aromaticity of organic compounds in WEOC. In addition, one litter bag was used for the analysis of C-, N-, P-degrading enzymes using a fluorometric microplate assay. Cube root transformed data was used for k-means clustering to detect litter specific decomposition pattern over time.As hypothesized, results show that S litter has a constant, low decomposition pattern over the whole experimental time. Other substates share a similar (low decomposition) pattern on day 0 and day 2 (high decomposition). After 14 days, pure substrates develop a specific pattern, while all mixtures share a common pattern. S containing mixtures (SB, SC) behave similar over time but remarkably different than related pure components only on day 28. Our results indicate that, especially in the beginning, patterns of decomposition are mainly time depend, possibly covering litter specific decomposition patterns. In conclusion, whole decomposition patterns showed no clear litter mixing effects, although some measured variabales indicate shifts with increasing time.
Breakup Magmatism and Paleogene Paleoenvironment: Initial Results from IODP Expedition 396 on the Mid-Norwegian Continental Margin
Authors: Planke Sverre , Berndt Christian , Zarikian Carlos A A , Huismans Ritske S , Bünz Stefan , Faleide Jan Inge , Lebedeva-Ivanova Nina , Zastrozhnov Dmitry , Scientists Expedition
Published: February 2023

Continental breakup in the NE Atlantic was associated with mafic magmatism recorded by basalt flows, volcanogenic sediments, magmatic underplates, and intrusive sheet complexes in the nearby sedimentary basins and continental crust. The voluminous magmatism is concomitant with the global hot-house climate in the Paleogene, and the injection of magma into organic-rich sedimentary basins is a proposed mechanism for triggering short-term global warming during the Paleocene-Eocene Thermal Maximum (PETM, ~56 Ma). IODP Expedition 396 drilled 21 holes along three transects on the mid-Norwegian continental margin to sample 1) Paleogene sediments along the Vøring Transform Margin and in hydrothermal vent complexes, and 2) basalt deposits from the Vøring Marginal High into the oceanic Lofoten Basin. A total of 2 km of core were recovered, including more than 350 m of basalt, 15 m of granite, and 900 m of late Paleocene to early Eocene sediments. Wireline logging data were recorded in eight holes. All the sites were located on industry-standard 2D and 3D seismic data. In addition, high-resolution seismic data were acquired in 2020 and 2022 over all the 21 Expedition 396 boreholes and 5 legacy ODP/DSDP sites using R/V Helmer Hansen. The seismic surveys included three P-Cable 3D cubes covering the 14 boreholes on the Modgunn (5), Mimir (5), and Skoll (4) transects. A comprehensive core-log-seismic integration program is ongoing for each site, based on an integration of high-resolution biostratigraphy, core and log based petrophysical data, and seismic modelling. The expedition recovered the first sub-basalt cores on the mid-Norwegian continental margin, recovering 15 m of granite. It furthermore collected the first samples from an Outer High at Site U1574, recovering both pillow basalts and hyaloclastites. These cores documented a shallow marine depositional environment of the emergent Eldhø volcano located near the foot of the Vøring Plateau. Finally, we drilled five holes through the upper part of a hydrothermal vent complex with a very expanded Paleocene-Eocene Thermal Maximum (PETM) interval dominated by biogenic ooze and volcanic ash deposits, documenting the temporal correlation of intrusive breakup magmatism in the Vøring Basin and a major hypothermal event. Collectively, the Expedition 396 sample archive offers unprecedented insight into tectonomagmatic processes in the NE Atlantic, including links to both rapid and long-term climate variation in the Paleogene.
Lateral magma flow in sill-complexes
Authors: Magee Craig , Jackson Christopher , Kopping Jonas
Published: February 2023

The structure of magma plumbing systems controls the distribution of volcanism and influences tectonic processes. Yet determining the structure of such plumbing systems is difficult because: (1) active intrusion networks cannot be directly accessed; (2) field outcrops are commonly limited; and (3) geophysical data imaging the subsurface are restricted in areal extent and resolution. Our current view is thus that plumbing systems are dominated by the vertical transfer of magma via dykes and/or some form transcrustal networks of conduits and reservoirs, extending from a melt source to overlying reservoirs and eruption sites. Whilst there is a wealth of evidence to support the occurrence of vertically dominated systems, field- and seismic reflection–based observations highlight that extensive lateral magma transport (over 10’s to 1000’s kilometres) may occur within mafic sill-complexes. Most mafic sill-complexes occur within sedimentary basins, but some intrude crystalline continental crust and volcanoes, and consist of interconnected sills and inclined sheets. Yet the extent to which active volcanic systems and rifted margins are underlain by sill-complexes remains poorly constrained, despite important implications to elucidating magmatic processes, melt volumes, and melt sources. Furthermore, questions remain as to how magma can travel through sill-complexes, across vast areas, without erupting or freezing. Here, we demonstrate how we can use geophysical data (particularly seismic reflection), tempered with geological structural, petrological, and chemical data, to map sill-complexes and understand their construction.
Novel indices for analysis of protection against snow avalanches in wind-disturbed forest
Authors: Baggio Tommaso , Piazza Natalie , Bast Alexander , Bebi Peter , D'Agostino Vincenzo
Published: February 2023

Windthrows are natural disturbances affecting the structure of forests. Such events are predicted to increase in magnitude and frequency due to climate change. The altered forest structure influences forests’ protection capacity against the release of snow avalanches. Previous studies investigated windthrown forest characteristics and their recovery time in study areas smaller than 10 ha, not accounting for larger spatial scales. In this study, we developed a new method for the spatial assessment and monitoring of forests affected by large-scale windstorms to evaluate the protection against the release of snow avalanches. We propose the use of two indices: (1) stored volume height, assessing the uniformity of the biomass on the ground, and (2) adapted tree parameters, evaluating the characteristics of the standing trees. We implemented the algorithm in the R environment and published the scripts on https://github.com/TommBagg/Wind-disturbed_forest_analysis.The developed indices were applied in two unmanaged windthrow areas periodically surveyed with photogrammetric techniques (deriving dense point clouds) to investigate the long-term changes in protective effects (Disentis, Switzerland) and the short-term influence of snow cover (Franza, Italy). The first area was affected by the storm Vivian in 1990 and four surveys have been performed (1991, 2001, 2009 and 2019), while the storm Vaia hit the Franza area in 2018 and three surveyed were performed (October 2019, October 2020 and December 2020). Analyzing the Disentis area, over 29 years, the minimum level of protective capacity was observed ten years after the storm event. As forest recovery proceeded, forest protective capacity increased again and natural regeneration has progressively provided an anchoring effect against the release of snow avalanches, 29 years after the windthrow event. However, a careful evaluation of the gaps between growing trees (outcome of the adopted tree parameters index) should be performed, as deadwood in these gaps decays, facilitating the potential avalanche formation. The stored volume height was further used to evaluate the forest protection in relation to the snow cover height in the Franza (IT) area, evaluating the necessary snow amount to smooth the rough surface created by the biomass on the ground. This study provided new insights into the long-term protective efficiency of windthrow forests, introducing two new indices to spatially assess and monitor their development over time.
Water scarcity and climate change impacts in the Eastern Italian Alps: A case study of the Adige river basin
Authors: Shrestha Susen , Zaramella Mattia , Bertoldi Giacomo , Borga Marco , Terzi Stefano , Massimiliano Pittore
Published: February 2023

Over the past decade, the Adige river basin in the Eastern Italian Alps has experienced water scarcity during early spring and late summer, due to a combination of decreased snowmelt, less precipitation, and increasing water demand. This condition has caused tension and disputes between upstream and downstream water users, particularly between hydropower companies in the upstream region (Trentino/South Tyrol) and agricultural users in the downstream areas (Veneto region). The potential for water scarcity impacts to intensify and expand in the future remains a major concern with climate change leading to more frequent warm and snow droughts in the region. Informing the region's administration, institutions, communities, and businesses to manage water scarcity conditions, is essential to prepare and mitigate the potential future impacts. This work aims to explore decision-making options in drought conditions in the Adige river basin, along with the potential impacts of climate change, by exploiting hydrological models for the river basins and for the major reclamation consortium in the area. The study will focus on years with severe drought, such as the 2022 drought period, using simplified decision options and examining how the decisions to meet the water needs of hydropower agencies in the upstream part of the Adige river basin could impact agricultural water use in the downstream part. The analysis will then be repeated in similar conditions, but with the added element of climate change forcing and reduced glacier volumes in the Alps. This study will identify those needs that might not be fulfilled in certain drought scenarios providing valuable insights for decision-makers and supporting the development of effective strategies to prepare and better manage future water scarcity conditions in the region.
Denoising Cryoseismological Distributed Acoustic Sensing Data Using a Deep Neural Network
Authors: Zitt Johanna , Paitz Patrick , Walter Fabian , Umlauft Josefine
Published: February 2023

One major challenge in Environmental Seismology is that signals of interest are often buried within the high noise level emitted by a multitude of environmental processes. Those signals potentially stay unnoticed and thus, might not be analyzed further.Distributed acoustic sensing (DAS) is an emerging technology for measuring strain rate data by using common fiber-optic cables in combination with an interrogation unit. This technology enables researchers to acquire seismic monitoring data on poorly accessible terrain with great spatial and temporal resolution. We utilized a DAS unit in a cryospheric environment on a temperate glacier. The data collection took place in July 2020 on Rhonegletscher, Switzerland, where a 9 km long fiber-optic cable was installed, covering the entire glacier from its accumulation to its ablation zone. During one month 17 TB of data were acquired. Due to the highly active and dynamic cryospheric environment, our collected DAS data are characterized by a low signal to noise ratio compared to classical point sensors. Therefore, new techniques are required to denoise the data efficiently and to unmask the signals of interest. Here we propose an autoencoder, which is a deep neural network, as a denoising tool for the analysis of our cryospheric seismic data. An autoencoder can potentially separate the incoherent noise (such as wind or water flow) from the temporally and spatially coherent signals of interest (e.g., stick-slip event or crevasse formation). We test this approach on the continuous microseismic Rhonegletscher DAS records. To investigate the autoencoder’s general suitability and performance, three different types of training data are tested: purely synthetic data, original data from on-site seismometers, and original data from the DAS recordings themselves. Finally, suitability, performance as well as advantages and disadvantages of the different types of training data are discussed.
River and Groundwater Interaction in the mid-stream area of Tama River, Tokyo, Japan
Authors: Suzuki Taiga , Tsujimura Maki , Sato Keisuke , Asakura Hiroko , Nagano Kosuke
Published: February 2023

This study aims to evaluate a role of Tama river in groundwater recharge by using multi-tracer approach and statistical analysis in a mid-stream area of Tama River, western Tokyo. We performed an intensive sampling of river water, groundwater and spring water in the mid-stream area of Tama River watershed including tributaries, Akikawa River and Asakawa River from May through September 2022, and totally 21 of river water, 35 of groundwater and 17 of spring water were sampled, and stable isotopic compositions (δ2H, δ18O), inorganic constituent concentrations were determined on all water samples. The d18O of Tama River water increases with flow especially after joining of the tributaries. The chemistry of Tama River, shallow groundwater and the spring water is characterized dominantly by Ca-HCO3 type, whereas the deep groundwater shows a Na-HCO3 or Na-Ca-Mg-HCO3 type dominantly. We applied End Member Mixing Analysis to estimate the contribution ratio of Tama River water to the shallow groundwater in the mid-stream area using d18O and SiO2 as tracers, and we selected the volume weighted mean of precipitation, mean of Tama river water and the groundwater taken in the border between mountain and plain area. The contribution ratio of river water to the total groundwater recharge ranges from 21% to 83%. Also, we performed a principal component analysis using all analyzed components to evaluate the category of the water chemistry considering the river water and the groundwater interaction. Further, we conducted hierarchical clustering analysis using PCA results. Consequently, the all of water samples are classified in 6 groups, and the shallow groundwater is categorized in the same group as the river water. The results show clearly that the Tama River water contributes dominantly to the shallow groundwater in the mid-stream area, and the river water partly recharges the deep groundwater. It seems to be due to the decline of the major aquifers from south-west to north east directions, which is from river to mid-stream plain area.
Analyzing the ability of BEL1D for inverting TEM data.
Authors: Ahmed Arsalan , Aigner Lukas , Michel Hadrien , Deleersnyder Wouter , Dudal David , Flores Orozco Adrian , Hermans Thomas
Published: February 2023

Understanding the subsurface is of prime importance for many geological and hydrogeological applications. Geophysical methods offer an economical alternative for investigating the subsurface compared to costly boreholes investigation methods, but results are often obtained through an inversion problem whose solution is non-unique. There are two types of inversion approaches: deterministic and stochastic. Deterministic inversion provides a unique solution with no way to efficiently and accurately assess uncertainty  but is relatively fast to compute. Stochastic inversions investigate the full range of solutions which make them computationally very expensive. In this research, we assess the robustness of the recently introduced BEL1D method for the stochastic inversion of the time domain electromagnetic data (TDEM). We analyze the effect of the accuracy of the forward model (through the open-source SimPEG code) on the estimation of the posterior space using a synthetic case and discuss the importance of prior selection. We also apply the algorithm on field data collected in Vietnam to assess saltwater intrusions. We observed that the proper selection of timesteps and space discretization is essential to limit the computation cost while maintaining the accuracy of the posterior estimation. Secondly, the selection of the prior distribution has a direct impact on fitting the observed data and is crucial to a realistic uncertainty quantification. Furthermore, in contrast to previous studies, we suggest rejecting models not fitting the data at an early stage for reducing computational costs. Lastly, the application of BEL1D together with SimPEG for stochastic TDEM inversion is a very efficient approach as it allows us to estimate the uncertainty at a limited cost.Keyword: Saltwater intrusion, uncertainty, TDEM, BEL1D, SimPEG
Freva is dead, long live Freva! New features of a software framework for the Earth System community
Authors: Kadow Christopher , Lucio-Eceiza Etor E. , Bergemann Martin , fast Andrej , Thiemann Hannes , Ludwig Thomas
Published: February 2023

Freva (the Free Evaluation System Framework [1; 2]) is a platform developed by the earth science community for the earth science community. Designed to work over HPC environments, it efficiently handles the data search and analysis of large projects, institutes or universities. Written on python, the framework has undergone a major update of the core. Freva offers:A centralized access. Freva comes in three different flavours with similar functionalities: a command line interface, a web user interface, and a python module that allows the usage of Freva in python environments, like jupyter notebooks.
A standardized data search. Freva allows for a quick and intuitive search of several datasets stored centrally. The datasets are internally indexed in a SOLR server with an implemented metadata system that satisfies the international standards provided by the Earth System Grid Federation.
Flexible analysis. Freva provides a common interface for user defined data analysis tools to plug them in to the system irrespective of the used language. Each plugin can be encapsulated in a personalized conda environment, facilitating the reproducibility and portability to any other Freva instance. These plugins are able to search from and integrate own results back to the database, enabling an ecosystem of different tools. This environment fosters the interchange of results and ideas between researchers, and the collaboration between users and plugin developers alike.
Transparent and reproducible results. The analysis history and parameter configuration (including tool and system Git versioning) of every plugin run is stored in a MariaDB database. Any analysis configuration and result can be consulted and shared among the scientists, offering traceability in line with FAIR data principles, and optimizing the usage of computational and storage resources.
 Freva has also experienced an upgrade on the sysadmin side:Painless deployment via Ansible, with a highly customizable configuration of the services via Docker.
Secure system configuration via Vault integration.
Straightforward migration from old Freva database servers or between Freva instances.
Improvements in the dataset incorporation.
Automatic backup of database and SOLR services.
[1] https://www.freva.dkrz.de/[2] https://github.com/FREVA-CLINT/freva-deployment
Modeling the relationship between mechanical yield stress and material geometry using convolutional neural networks
Authors: Najafi Fahimeh , Andersen Sveinsson Henrik , Dreierstad Christer , Malthe-Sørenssen Anders
Published: February 2023

Neural networks have proved to be able to capture the relevant and informative features of a wide variety of data types and predict the desired output for different regression or classification problems. Finding a mapping between materials’ structure and a given physical property of those systems is an example of a problem that could be approached with machine learning methods like neural networks. Especially when we are dealing with systems with a very large design space where using classical computational methods like molecular dynamics can be very time and resource-consuming for the study of a very large number of systems, a well-trained neural network can be greatly faster and more efficient for computing the relevant properties. In this work, we study α-quartz crystals with one porous layer with simplex noise as the shape of porosity. Simplex noise is a gradient based procedural algorithm that can produce irregular geometries with surface morphology resembling what is observed in nature. The property that we want the neural network to learn is the yield stress of these systems under both shear and tensile deformation. Molecular dynamics simulations are used for a randomly selected sample of possible structures in order to generate the ground truth to be used as the training data. We employ deep convolutional neural networks (CNN) which are commonly used when dealing with image or image-like data since the input data for the problem in hand is a binary 2-D structure of the porous layer of the systems. The trained model is compared with a basic polynomial fit of stress versus porosity. The trained CNN is successful in predicting the yield stress of a system based on the geometry of that given system, with lower variability and higher precision compared to the base polynomial regression method. The saliency maps created with the trained model show the model to be successful in capturing the physics of the problem when compared with the stress fields calculated using molecular dynamics simulations. This method of modeling materials can be further developed for the inverse design of structures with desired properties without the need for a huge number of simulations on a wide domain of possible systems.
Implementing a toroidal flux rope model in EUHFORIA and assessing its performance in predicting CME magnetic-field at 1 AU
Authors: Sarkar Ranadeep , Pomoell Jens , Kilpua Emilia , Asvestari Eleanna
Published: February 2023

One of the major challenges in space weather forecasting is to reliably predict the magnetic structure of interplanetary coronal mass ejections (ICMEs) in the near-Earth space. In the framework of global MHD modelling, several efforts have been made to model the CME magnetic field from Sun to Earth. However, it remains challenging to deduce a flux-rope solution that can reliably model the magnetic structure of a CME. Spheromaks are one of the models that are widely used to characterize the internal magnetic structure of a CME. However, recent studies show that spheromaks are prone to experience a large rotation when injected in the heliospheric domain which may affect the prediction efficacy of CME magnetic field at 1 AU. Moreover, the fully inserted spheromaks do not have any legs attached to the Sun. In addition, due to the inherent topology of the spheromak, the in-situ signature may exhibit a double flux-rope-like profile not reproduced by standard locally cylindrical flux rope models. Aiming to study the dynamics of CMEs exhibiting different magnetic topologies, we implement a new flux-rope model in “European heliospheric forecasting information asset” (EUHFORIA). Our flux-rope model includes an initially force free toroidal flux-rope that is embedded in the low-coronal magnetic field. The dynamics of the flux rope in the low and middle corona is solved by a non-uniform advection constrained by the observed kinematics of the event. This results in a global non-toroidal loop-like magnetic structure that locally manifests as a cylindrical structure. At heliospheric distances, the evolution is modeled as a MHD process using EUHFORIA. We track the evolution of the flux-rope up to 1 AU and assess the model results with the observed in situ profile of the associated CME.  This work is an important step forward in developing a realistic CME model that can be used for reliable space weather forecasting.
Drivers of the Annual Cycle of Rainfall over Central Africa: The Role of Water Vapor and the Mid-Tropospheric Meridional Circulation
Authors: Longandjo Georges-Noel T. , Monyela Bellinda Mashoene , Rouault Mathieu
Published: February 2023

The Intertropical Convergence Zone (ITCZ), with its twice-annual passage over central Africa, is considered as the main driver of the rainfall seasonality. But recently, this paradigm was challenged. To find out what are the main drivers of the annual cycle of rainfall over central Africa, we present a simple comprehensive paradigm with both local forcings and regional-scale processes playing crucial role. Due to the local evaporative cooling effect, the foot of the ascending branch of Hadley cells occurs where the temperature is the warmest, indicating a thermal low. This distorts the southern Hadley cell by developing its bottom-heavy structure. As result, both shallow and deep Hadley cells coexist over central Africa year–round. The deep mode is associated with poleward branches at upper levels that transport the atmospheric energy. The shallow mode is characterized by a meridional return flow in the mid-troposphere that transports the water vapour instead of lower branches as widely reported. This favours the building-up of the mid-tropospheric moisture flux convergence with a limited contribution of the midlevel easterly jet, conducive to deep convection. Embedded in this strong rising branch of Hadley cells at midlevels, the intense convective rainfall, and with it the rainfall maximum position, is seasonally controlled by the dynamics of the midlevel shallow meridional return flow. This highlights the interhemispheric rainfall contrast over central Africa and outlines its unimodal seasonality. On the other hand, forced by the Congo basin cell, the precipitable water regulates the deep convection from the vegetated surface of Congo basin, acting as a continental sea. This nonlinear mechanism separates the rainfall into three distinct regimes – (i) the moisture-convergence-controlled regime, with convective rainfall exclusively occurring in the rainy season and (ii) the local evaporation-controlled regime with drizzle and (iii) the precipitable-water-controlled regime, with exponential increase of rainfall that both occur during the dry season.
Seismic anisotropy analysis based on synthetic and measured data for crystalline rock characterization
Authors: Behnen Kathrin , Hertrich Marian , Maurer Hansruedi , Shakas Alexis ,   Bedretto-Team
Published: February 2023

The prior characterization of a reservoir volume as well as the monitoring of potential changes during heat extraction is highly important to ensure an economic and safe engineering and operation of a geothermal reservoir. While the use of active seismic measurements from the surface and in boreholes is commonly used to describe the seismic velocity field in the subsurface, its potential to analyze the seismic anisotropy is often neglected. We used active seismic crosshole measurements to analyze seismic anisotropy at the field scale to provide important information about the elastic properties and take advantage of this information for the analysis of the in-situ rock-physical conditions.For the analysis of seismic anisotropy, a reliable data set is essential. We studied the sensitivity of the resulting anisotropy model to inaccuracies in the survey geometry by computing synthetic data and showed that inaccuracies of only a few degrees in dip and azimuth of the borehole orientation can significantly change the resulting anisotropy model of the volume. Especially the orientation of the symmetry axis used to describe a transverse isotropic model (TI) is highly sensible to source and receiver positions.Beyond the analysis of the synthetic data, the focus of our study was on the exploitation of real measurement data. These data were recorded in a campaign in the Bedretto Underground Laboratory for Geosciences and Geoenergies (BULGG) in Ticino, Switzerland. The laboratory provides the opportunity to record crosshole data with high quality in a controlled environment. The geometry of the boreholes that we used allows a high coverage of ray path orientations which is crucial for the analysis of anisotropic wave propagation. The recorded data were used to create an anisotropy model of the subsurface based on a grid search and optimization algorithm, searching for both the optimized Thomsen parameters and the ideal orientation of the symmetry axis of the tilted TI model. The results give evidence of an ambient elastic anisotropy, while the host rock (Rotondo Granite) has proven negligible intrinsic anisotropy in previous laboratory measurements at sample scale. Further investigation will analyze the effect of the fracture inventory and ambient state of stress as potential controlling factors of the observed anisotropy. This relation can potentially help to monitor changes in the stress field during geothermal operations for a better hazard assessment.
Groundwater-surface water interactions manifested on stream network geometry across United States
Authors: Freund Elham , Seybold Hansjörg , Jasechko Scott , Kirchner James
Published: February 2023

The branching angles of stream network are the fingerprint of the processes that shape our landscape. However, the mechanisms that give rise to stream network patterns on Earth are not fully understood. Recent studies have shown controls of climate, tectonics, and lithology on channel incision and the planform geometry of stream networks. Our analysis of one million river junctions and over 4.2 million groundwater well observations across the contiguous United States shows for the first time that stream network branching angle vary systematically with the degree to which streams and groundwater interact.  Streams that are losing their water to groundwater exhibit narrow branching angles while streams that are gaining water from groundwater exhibit wide branching angles on average. We show that the correlation between branching angle and fraction of losing streams is stronger than branching angle and other controls of stream network planform geometry. The systematic relationship between branching angle and losing fraction persist across a range of topographic gradient and across several stream orders. Our findings brings forward a mechanistic linkage between previously shown correlation between branching angles and climate.
Variability in North Sea wind energy and the potential for prolonged winter wind drought
Authors: Kay Gillian , Dunstone Nick , Maidens Anna , Scaife Adam , Smith Doug , Thornton Hazel , Dawkins Laura , Belcher Stephen
Published: February 2023

The UK is committed to substantially increasing offshore wind capacity in its drive to decarbonise electricity production and achieve net zero. If low wind episodes – or “wind drought” events – occur during high energy demand periods, energy security may be threatened without alternative supply. To ensure resilience of the power system now and in the coming years as offshore wind generation grows, better understanding of the severity, frequency and duration of low wind episodes would be useful. Variability in winds is likely to dominate over trends in the next few decades, and hence having improved information on present day characteristics of wind drought is valuable.Here we focus our attention on the North Sea as a centre of current and planned offshore wind resource for the UK and a number of other European countries, and on the winter season, given the occurrence of weather patterns that risk security of supply. We use a large ensemble of initialised climate model simulations to provide a synthetic but realistic event set that greatly increases the sample size of extreme events compared with that available from reanalysis data, and gives more robust information about their likelihood and properties. Using the basic unit of a week of low winds as the timescale of analysis, we report on the frequency and duration of wind drought events. In addition, we examine the wider conditions associated with wind drought events to investigate what remote factors may contribute to prolonged wind drought.
Potential of novel organic NP(K)-char fertilizers as part of a circular economy-based phosphorus supply chain – results from a pot experiment
Authors: Görres Carolyn-Monika , Kammann Claudia , Appel Thomas
Published: February 2023

Nutrient density in manure and fermentation residues is too low to economically justify transporting them to regions with phosphorus (P) and nitrogen (N) demands. However, they present a valuable feedstock for the production of commercial P fertilizers via pyrolysis. Phosphorus availability in the resulting chars for plant uptake can be further improved by adding potassium (K) salts to the feedstock prior to pyrolysis, while vinasse can be added for N enrichment. Such recycling-derived N-P(-K doped) fertilizers are expected to release nutrients slowly to the plants and to have positive environmental effects like nitrate retention, reduction of nitrous oxide (N2O) emissions and carbon (C) sequestration. We conducted a greenhouse pot experiment with celery and spinach cultures to investigate the P fertilization performance and environmental effects of newly developed recycling-derived N-P(-K) char fertilizers. Four novel pyrolysis products were tested: three different N-enriched (vinasse) dry flowable products (pyrolyzed material: dried pelletized chicken manure, digestate, and the dried solid fraction of pig slurry, respectively), and a char from dried pig manure, which had been enriched with potassium acetate prior to pyrolysis. The pot experiment demonstrated that P-char fertilizers, combined with a liquid organic N fertilizer commonly used in organic farming (vinasse), can provide the same P-fertilization as triple super phosphate (TSP), with yields similar to or higher than those obtained with mineral N fertilizers. Furthermore, the char fertilizers, and in particular the K-doped char, reduced nitrate leaching significantly compared to treatments with TSP + calcium ammonium nitrate (CAN) or TSP + vinasse. Liquid vinasse application drastically enhanced N2O emissions compared to pots where less or no liquid vinasse was applied without char. P-char fertilizers may thus provide a promising building block for a circular economy-based P supply chain while simultaneously reducing environmental costs in the form of less nitrate leaching and lower N2O emissions and contributing to soil C sequestration in the plough layer.The project was funded by the Federal Ministry of Food and Agriculture (BMEL) on the basis of a resolution of the German Bundestag. The project was carried out by the Federal Agency for Agriculture and Food (BLE) within the framework of the Innovation Promotion Program. Title of the research project: "Carbon-based fertilizers from phosphorus-rich slurry, manure and fermentation residues by carbonization with nitrogen recovery", grant numbers 2818105215, 2818105015 and 2818107115.
Assessment of Long-Term and Spatio-temporal Changes between Rice Productivity and Irrigation Water Demand in South and North Korea based on Shared Socioeconomic Pathways (SSP) Scenario
Authors: Lee Sujong , Karthe Daniel , Lee Woo-Kyun , Lee Halim
Published: February 2023

Climate change exacerbates food and water security, and it has been extended to hunger and malnutrition globally. In 2019, The Food and Agriculture Organization (FAO) announced North Korea was a food shortage country, and it has continued today. In South Korea, an agricultural drought has occurred irregularly since the 2010s by climate change and it impacts both crop quality and quantity negatively. Since these agricultural droughts and food shortages have increased gradually, in terms of climate change, agricultural risk must be addressed at the national level and long-term perspective. To address the agricultural risk quantitively in South and North Korea, rice productivity and Irrigation water demand are set as proxy variables of food and water variation in the agricultural domain. The overall methodology is divided into three-stage. 1) Classification of rice paddy area on the Korean Peninsula using remote sensing data based on machine learning algorithms, 2) Crop simulation using EPIC model on representative years and calibration/validation of the model, 3) multi-temporal crop simulation based on SSP scenario until the 2100s. The rice productivity and irrigation water demand matrix based on the scenario will be calculated and it will be used as a proxy variable in the water-food nexus. Consequently, the results will be extended to agricultural risk assessment on the national level-based Water-Food Nexus approach to address the Sustain Development Goals (SDGs) in Korean Peninsula
Mediterranean sea-surface and deep responses to large-scale atmospheric forcing in evaluation Med-Cordex simulations
Authors: Cusinato Eleonora , Rubino Angelo , Gualdi Silvio , Zanchettin Davide
Published: February 2023

The Mediterranean Sea is one of the few regions in the world where ocean deep convection events occur, contributing to trigger the local thermohaline circulation. The variability of this circulation is typically affected by large-scale atmospheric modes of variability of Atlantic and Eurasian origin, like, e.g., the North Atlantic Oscillation (NAO), the Eastern Atlantic pattern (EA), the Eastern Atlantic Western Russian pattern (EAWR) and the Scandinavian pattern (SCA). Whereas previous studies assessed the impacts of these modes on air-sea heat and freshwater fluxes over the Mediterranean Sea, few studies explored the propagation of these signals from the surface towards the interior of the Mediterranean Sea and mostly they relied on the use of single model simulations.In this contribution we investigate the Mediterranean thermohaline response to winter forcing from NAO, EA, EAWR and SCA using a multi-model analysis of evaluation simulations belonging to the Med-Cordex initiative. We present results from a composite analysis around strong positive and negative phases of these modes to track the propagation of the associated signals from the sea surface towards the Mediterranean interior in key regions such as the South Adriatic, the Aegean and Levantine Seas and the Gulf of Lion. Different simulations show only a partial agreement as far as the identification of the modes mostly contributing to deep water formation is concerned.
Data challenges and opportunities from nascent kilometre-scale simulations
Authors: Anantharaj Valentine , Hatfield Samuel , Polichtchouk Inna , Wedi Nils
Published: February 2023

Computational experiments using earth system models, approaching kilometre-scale (k-scale) horizontal resolutions, are becoming increasingly common across modeling centers. Recent advances in high performance computing systems, along with efficient parallel algorithms that are capable of leveraging accelerator hardware, have made k-scale models affordable for specific purposes. Surrogate models developed using machine learning methods also promise to further reduce the computational cost while enhancing model fidelity. The “avalanche of data from k-scale models” (Slingo et al., 2022) has also posed new challenges in processing, managing, and provisioning data to the broader user community. During recent years, a joint effort between the European Center for Medium-Range Weather Forecasts (ECMWF) and the Oak Ridge National Laboratory (ORNL) has succeeded in simulating “a baseline for weather and climate simulations at 1-km resolution,” (Wedi et al., 2020) using the Summit supercomputer at the Oak Ridge Leadership Facility (OLCF). The ECMWF hydrostatic Integrated Forecasting System (IFS), with explicit deep convection on an average grid spacing of 1.4 km, was used to perform a set of experimental nature runs (XNR) spanning two seasons corresponding to a northern hemispheric winter (NDJF), and August - October (ASO) months corresponding the tropical cyclone season in the North Atlantic. We developed a bespoke workflow to process and archive over 2 PB of data from the 1-km XNR simulations (XNR1K). Further, we have also facilitated access to the XNR1K data via an open science data hackathon. The hackathon projects also have access to a data analytics cluster to further process and analyze the data. The OLCF data center supports high speed data sharing via globus data transfer mechanism. External users are using the XNR1K data for a number of ongoing research projects, including observing system simulation experiments, designing satellite instruments for severe storms, developing surrogate models, understanding atmospheric processes, and generating high-fidelity visualizations.During our presentation we will share our challenges, experiences and lessons learned related to the processing, provisioning and management of the large volume of data, and the stakeholder engagement and logistics of the open science data hackathon.Slingo, J., Bates, P., Bauer, P. et al. (2022) Ambitious partnership needed for reliable climate prediction. Nat. Clim. Chang.  https://doi.org/10.1038/s41558-022-01384-8Wedi, N., Polichtchouk, I., et al. (2020) A Baseline for Global Weather and Climate Simulations at 1 km Resolution, JAMES. https://doi.org/10.1029/2020MS002192
Geophysical mass flow over complex micro-topography: from grain-scale mechanics to continuum modeling
Authors: Jing Lu , Yang Shuocheng , Kwok Fiona C. Y.
Published: February 2023

Geophysical mass flows involve granular earth materials surging down natural slopes, one of the major threats to mountainous regions worldwide. Accurate modeling of geophysical mass flows requires closure relations both within the flow (rheology) and at the flow-substrate interface (boundary conditions). However, although recent years have seen significant advances in the modeling of granular flow rheology, our understanding of how flowing granular materials interact with the substrate remains largely elusive. Here, we focus on micro-topography, i.e., geometric base roughness that is about the same size as the grain size, and investigate its effects on the granular flow dynamics as well as the associated closure relations. To systematically vary the base roughness from smooth to rough, we generate the base using immobile particles with varying particle size and spatial arrangement in laboratory experiments (with particle image velocimetry for flow kinematics extraction) and discrete element method simulations. Two granular flow scenarios are considered, including steady-state flow down inclines and granular column collapse. In the first scenario, it is found that basal slip occurs when the base roughness is below a range of intermediate values and a general slip law connecting the slip velocity, the mean flow velocity, and the base roughness is developed. In the second, transient flow scenario, basal slip inevitably occurs even for very rough bases due to inertial effects and a transient basal slip law is proposed to correlate the slip velocity with local flow properties based on kinetic theory arguments. The basal slip laws developed in this work can be readily incorporated as a dynamic boundary condition in continuum modeling of granular flows. In future work, grain-scale mechanisms relevant to more realistic geophysical flows will be investigated, including the feedback effects of pore fluid pressure on the flow mobility during basal sliding and the role of irregular particle shapes in hydro-mechanical modeling of geophysical mass flows.
Tropical cyclone storm surge emulation around New Orleans
Authors: Thomas Simon , Jones Dan(i) , Mayo Talea , Gopinathan Devaraj
Published: February 2023

Storm surges can have devastating effects on coastal communities. These events, often caused by tropical cyclones, are difficult to simulate due to the challenging nature of process-based modelling and the relative paucity of data covering extreme tropical cyclone conditions. In order to make optimal use of existing physical models, we build an emulator to actively learn the relationship between tropical cyclone characteristics and maximum storm surge height. We used the ADCIRC physical storm surge model, a reliable but costly tool, to simulate a series of representative tropical cyclones that typically affect the coast near New Orleans. These initial storms were sampled using Latin hypercube design, varying tropical cyclone characteristics such as the landfall speed, central pressure, and others. By running the ADCIRC model for each of these events, we were able to determine the maximum sea surface height caused by each simulated storm. Next, we trained a Gaussian process to fit the maximum sea levels at each point along the coast given the tropical cyclones' characteristics as input. Through active learning, we iteratively selected additional tropical cyclones to further improve the emulator’s accuracy. Finally, we evaluated the model's performance using a held-out test set of idealised tropical cyclones. Our emulator approach allowed us to efficiently create a high-quality, low-cost statistical model that can potentially be used to predict the probability of future storm surge heights. Additionally, it allowed us to separate uncertainties in the input distribution of tropical cyclone characteristics from uncertainties in the model itself. By better understanding these sources of uncertainties, we can work towards more accurately assessing the potential impacts of future storms on coastal communities.