bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-front wind forcing of a dense submesoscale filament
Authors: Umlauf Lars , Schmitt Mira , Peng Jen-Ping
Published: March 2024

In this study, the effects of cross-front winds on a submesoscale dense filament are investigated using high-resolution turbulence and velocity observations, and idealized numerical simulations. Our study area is the Baltic Sea, which is characterized by strong frontal gradients and pronounced submesoscale dynamics. Embedded in a large-scale frontal region, our observations reveal the existence of a 3-4 km wide, dense filament with an asymmetric structure resulting from the interactions between cross-front winds and the two submesoscale fronts laterally bounding the filament. These two fronts are driven by either downgradient winds, directed from the lighter surrounding waters toward the dense center of the filament, or upgradient winds, directed in the opposite direction. While the effect of a wind stress that is aligned with the frontal jet has been investigated in numerous previous studies, especially field data focusing on the role of cross-front winds are largely lacking at the moment. We find that for downgradient winds, when the surface Ekman transport and the frontal jet are aligned, both the frontal jet and the cross-front secondary circulation are enhanced. The latter supports a tendency for frontal re-stratification, suppression of turbulence, and mixed-layer shoaling. For the front with upgradient wind forcing, the Ekman transport and the frontal jet nearly cancel, and also the cross-front secondary circulation is strongly suppressed. Restratification by the secondary circulation is weak in this case, and the well-mixed turbulent surface layer is approximately twice as deep compared to the other side of the filament with downgradient forcing. We show that these mechanisms are consistent with results from idealized numerical simulations of frontal regions with downgradient and upgradient wind forcing.
Folded ice in the upper North East Greenland Ice Stream reveal timing of the onset of streaming
Authors: Jansen Daniela , Franke Steven , Bauer Catherine , Binder Tobias , Dahl-Jensen Dorthe , Eichler Jan , Eisen Olaf , Hu Yuanbang , Kerch Johanna , Llorens Maria Gema , Miller Heinrich , Neckel Niklas , Paden John , de Riese Tamara , Sachau Till , Stoll Nicolas , Weikusat Ilka , Wilhelms Frank , Zhang Yu , Bons Paul Dirk
Published: March 2024

Only a few localised ice streams drain most ice from the Greenland Ice Sheet. Thus, understanding ice stream behaviour and their temporal variability is crucially important to predict future sea-level change. The interior trunk of the 700 km-long North-East Greenland Ice Stream (NEGIS) is remarkable for the lack of any clear bedrock channel to explain its presence. Here we use isochronous radar reflections from an airborne radar survey as passive tracers of ice deformation. We present the first-ever 3-dimensional analysis of folding and advection of stratigraphic horizons within an ice stream, which shows that the localised flow and shear margins in the upstream part were fully developed only ca. 2000 years ago. This indicates that this type of streaming in the interior of an ice sheet can be triggered on short time scales.
Challenges and uncertainties in geodetic mass balance estimates for HMA glaciers using space-borne data
Authors: Bandyopadhyay Debmita , Shukla Aparna
Published: March 2024

Glacier mass balance (GMB) is an important variable for understanding the response of glaciers to climate change. The geodetic method for GMB estimation involves comparing changes in surface elevation over time using satellite or airborne remote sensing data. One of the major advantages of geodetic mass balance is that it accounts for 3-D variability (vertical and surface) in the mass balance, however, assuming that the elevations are accurate everywhere and reference a stable geographic datum. Nevertheless, errors in the geodetic GMB can result from seasonal adjustments, density adjustments and depend heavily on image quality. Further, the relative error of the digital elevation models (DEMs) plays a crucial role than the absolute error when calculating geodetic GMB, and can induce additional uncertainties in the estimates. In a rugged terrain like that of the HMA, with most of the glaciated region in the Himalayas having sudden steep slopes and thick supraglacial debris, results of glacier-level measurements over bedrock are less accurate than those over glacier ice. Further, based on the type of DEM utilized (optical or synthetic aperture (SAR) radar-based), the uncertainty in the GMB varies from 23.3% to 52.7%, with SAR-based GMB having lower uncertainty. In this work, comparisons between different studies highlight both the utility of geodetic mass balance estimates and a possible resolution to the prominent issues (highlighted here) that can assist in circumventing the challenges in GMB assessments over the HMA region.
State of permafrost in the Swiss Alps in 2023
Authors: Pellet Cécile , Noetzli Jeannette ,   PERMOS Scientific Committee
Published: March 2024

Permafrost is classified as an essential climatic variable (ECV) by the Global Climate Observing System (GCOS) because of its sensitivity to changes in climatic conditions. The Swiss Permafrost Monitoring Network PERMOS documents the state and changes of permafrost conditions in the Swiss Alps since 2000 based on long-term field measurements. To account for the heterogeneous distribution and characteristics of mountain permafrost, PERMOS developed and implemented a comprehensive monitoring strategy, which relies on three complementary observation elements: (1) ground temperatures near the surface and at depth, (2) permafrost electrical resistivity to determine changes in ground ice content, and (3) rock glacier velocities, which can be used as a proxy to assess the permafrost thermal regime.In this contribution, we discuss permafrost conditions in the Swiss Alps during the hydrological year 2023 with respect to the observations of the past two decades. Combining results from the three observation elements, we analyse the short and long-term responses of permafrost to climate evolution. The hydrological years 2022 and 2023 were characterized by two consecutive winters with below average snow heights and two summers ranked second and fifth warmest on record since 1864. These weather and climate conditions lead to different permafrost evolutions at different depth levels and at different sites. While ground surface temperatures and active layer thicknesses at or close to record values were registered, a slight decrease of the permafrost temperatures was observed at 10 and 20 m depth, which is consistent with the decreasing rock glacier velocity and increasing permafrost resistivity observations. The permafrost conditions observed in 2023 constitute short term variations likely not affecting the long-term trend of warming and degrading permafrost consistently observed in the Swiss Alps for the past two decades.
Development of a site-specific standardised Cosmic Ray Neutron Sensor (CRNS) calibration protocol
Authors: Shishkin Konstantin , Fenton Owen , Finkele Klara , Hochstrasser Tamara , Richards Karl , Murphy Paul
Published: March 2024

Soil moisture is a key soil characteristic that must be taken into account when planning agricultural management activity e.g. trafficking of land or timing of nutrient application. Traditionally, soil moisture is measured using point-scale sensors or directly through field sampling followed by drying-weighing of the soil sample in the laboratory.  However, due to the spatial heterogeneity of soils, soil moisture varies significantly within a few meters within a single paddock, which limits the usefulness of the traditional point-scale methods for management decisions. In contrast, satellite measurements of soil moisture are too coarse in their resolution to give accurate descriptions of soil moisture at sub-field scale.   The Cosmic-Ray Neutron Sensor (CRNS) is a neutron sensing instrument that can be installed at field sites to monitor soil moisture conditions over intermediate scales. This approach uses the principle of elementary particle attenuation with depth to assess concentration of water molecules in soil within a footprint of 75-300 m radius, with a varying accuracy for the chosen footprint radius. Further exploration of both the CRNS footprint and accuracy is needed, necessitating the development of a standardized site-specific calibration process (the focus of the present work) to enable enhanced data integration across sites and improve the accuracy of neutron counts (NC) to volumetric soil moisture content (VMC) conversion within the defined footprint. For that purpose, the newly established Irish Soil Observation Network (ISMON) has installed ten CRS2000/B neutron sensors presenting an opportunity to create such a standardised protocol. This work presents the first results of the ISMON CRNS stations calibration and introduces a new vision towards development of standardised CRNS calibration protocol for grassland sites.
Enhanced coupled land-atmosphere data assimilation for reanalysis
Authors: Weston Peter , de Rosnay Patricia , Herbert Christoph , Pinnington Ewan
Published: March 2024

The CERISE (CopERnIcus climate change Service Evolution) project aims to develop land and coupled land-atmosphere data assimilation systems for the next generation of coupled reanalysis. This encompasses technical enhancements to the system architecture as well as scientific changes to improve the quality of the reanalyses.Recent work has focussed on developing ensemble perturbation methods for the land-surface. The existing ensemble spread in model variables at and near the land-surface is known to be insufficient which can cause problems when assimilating interface observations in a coupled system. This is because the existing ensemble perturbations are mainly applied to upper air atmospheric variables. One way to increase the spread at the surface is to directly perturb land-surface parameters such as vegetation cover and leaf area index. Results from this approach are encouraging in offline and coupled experiments.Another part of the project is to enhance the assimilation of passive microwave radiances over land. Currently the use of surface-sensitive passive microwave channels are largely limited to the ocean due to challenges in forward modelling of complex and heterogenous land surfaces. In CERISE, machine learning approaches are being explored to develop an observation operator to enable the use of these observations over land and snow surfaces.Finally, developing quasi-strongly coupled land-atmosphere assimilation is a key objective of the project. Developments so far have focussed on technical changes to build a framework to allow stronger coupling than the current weakly coupled assimilation strategy. A summary of recent progress in the CERISE project will be presented.
Tools and techniques for modular, portable (Machine Learning) parameterisations
Authors: Atkinson Jack , Orchard Dominic , Kasoar Elliott , Meltzer Thomas
Published: March 2024

Numerical models across the geophysical sciences make extensive use of physical parameterisations to represent sub-grid processes such as eddies, convection, gravity waves, and microphysics. With the advent of machine learning (ML), big data, and artificial intelligence there are increasing efforts to develop data-driven parameterisation schemes or emulate existing, but computationally-intensive, parameterisations using ML techniques.Despite their name, the irony is that traditional design approaches often lead to parameterisations which are not themselves parameters, but rather tightly integrated, enmeshed pieces of code in a larger model. Such parameterisations and practices pose a threat to the reproducibility, accuracy, ease-of-(re)-use, and general FAIRness (Findable, Accessible, Interoperable, Reusable) [1] of the schemes being developed.In contrast, a modular approach to parameterisations (and their receivers, e.g., GCMs), would enable them to be more easily (1) interchangeable and Interoperable, to compare different schemes and assess uncertainty due to their inherent approximate behaviour, and (2) portable and Reusable, between models, to reduce engineering effort, and (3) understandable and Accessible, by being clear about dependencies and the physical meaning of program variables, and (4) testable, to aid verification and correctness testing. Achieving this goal in the context of numerical modelling brings a number of scientific, engineering, and computational challenges. In this talk we aim to set out some best-practice principles for achieving modular parameterisation design for geoscience modellers. We then focus on the particular challenges around modem ML parameterisations. To this end we have developed a library for easily interoperating ML-based parameterisations in PyTorch with Fortran-based numerical models, called FTorch [2]. By reducing the Fortran-PyTorch Interoperability burden on researchers this framework should reduce errors that arise and increase the speed of development when compared to other approaches such as re-coding models in Fortran. FTorch aims to make emerging ML parameterisation research more Accessible to those who may not have deep expertise of ML, Fortran, and/or computer science. It also means that models developed using PyTorch can leverage its feature-rich libraries and be shared in their native format, maximising Reusability. We discuss the design principles behind FTorch in the context of modular parameterisations and demonstrate our principles and approach by coupling ML parameterisations to atmospheric and climate models.In general, we present a number of considerations that could be used to make all parameterisation schemes more easily Interoperable and Re-useable by their developers. [1] Barker, M. et al, Introducing the FAIR Principles for research software, Sci Data 9, 622 (2022) https://doi.org/10.1038/s41597-022-01710-x[2] FTorch https://github.com/Cambridge-ICCS/FTorch
On the Importance of groundwater constraining in hydrological modeling of the Pamir region
Authors: Huang Jingheng , Pohl Eric , Richard-Cerda Juan Carlos
Published: March 2024

Central Asia is a climate change hot spot, facing an unprecedented juxtaposition of regional climate- and water-related issues. Meltwater from the Pamir Mountains plays a crucial role in Central Asia's hydrological cycle, and its response to climate change has been widely investigated using glacial-hydrological models. However, the hydrological simulation in Pamirs is highly uncertain, primarily driven by data scarcity and the complex interplay between climatic factors and glacier dynamics. Ongoing efforts concentrate on including more calibration data and constraining the uncertainty about the exact internal process representation of hydrological models. However, the quality of the groundwater simulation is often neglected. Groundwater reservoirs, buffering meltwaters and providing river flow when little to no surface runoff occurs, are extremely important in the Pamir region. Although physically based groundwater models provide a more detailed picture of the possible evolution of the system, empirical groundwater models are often used in hydrological modeling due to their minimal input data requirements and low computational cost compared to physically based models. However, the traditional empirical groundwater model with single linear storage is not suitable for the Pamir region. The region is characterized by a variety of sedimentary deposits in different landscape morphologies, resulting in varying delays in water recharge, release, and storage capacities. We improved the baseflow representation by coupling two linear groundwater reservoirs (one fast and one slow) into a widely-used hydrological model in the region. A representative catchment in the central Pamir, the Gunt River basin, is used as a case study to demonstrate the importance of groundwater in constraining the hydrological calibration process. Groundwater is the only contribution to winter river discharge in the Gunt basin and can thus be used as an indicator of groundwater parameter constraint. Here we show that the hydrological model can achieve good performance (in terms of daily discharge, seasonal snow cover fraction, and annual glacier mass balance) even when calibrated with only total daily discharge and winter baseflow. Especially the baseflow calibration helps constraining snowmelt onset in spring and improving adjustments of precipitation and temperature, which are the most uncertain sources in hydrological modeling in the region. Despite improvements, degree day factors still show a large variability. The resulting model equifinality problem still leads to predictive uncertainty, indicating that more glacier observations are needed for a sound process understanding. Based on the simulated results, the hydrological cycle in Gunt was analyzed and compared with previous studies.
Operational stream water temperature forecasting with a temporal fusion transformer model
Authors: Padrón Ryan S. , Zappa Massimiliano , Bogner Konrad
Published: March 2024

Stream water temperatures influence aquatic biodiversity, agriculture, tourism, electricity production, and water quality. Therefore, stakeholders would benefit from an operational forecasting service that would support timely action. Deep Learning methods are well-suited for this task as they can provide probabilistic forecasts at individual stations of a monitoring network. Here we train and evaluate several state-of-the-art models using 10 years of data from 55 stations across Switzerland. Static features (e.g. station coordinates, catchment mean elevation, area, and glacierized fraction), time indices, meteorological and/or hydrological observations from the past 64 days, and their ensemble forecasts for the following 32 days are included as predictors in the models to estimate daily maximum water temperature for the next 32 days. We find that the Temporal Fusion Transformer (TFT) model performs best for all lead times with a cumulative rank probability score (CRPS) of 0.73 ºC averaged over all stations, lead times and 90 forecasts distributed over 1 full year. The TFT is followed by the Recurrent Neural Network (CRPS = 0.77 ºC), Neural Hierarchical Interpolation for Time Series (CRPS = 0.80 ºC), and Multi-layer Perceptron (CRPS = 0.85 ºC). All models outperform the benchmark ARX model. When factoring out the uncertainty stemming from the meteorological ensemble forecasts by using observations instead, the TFT improves to a CRPS of 0.43 ºC, and it remains the best of all models. In addition, the TFT model identifies air temperature and time of the year as the most relevant predictors. Furthermore, its attention feature suggests a dominant response to more recent information in the summer, and to information from the previous month during spring and autumn. Currently, daily maximum water temperature probabilistic forecasts are produced twice per week and made available at https://drought.ch/de/allgemeine-lage/wassertemperatur/fliessgewaesser-1-1.html. 
Signature of Alfvénic and compressive waves in corotating Solar Wind high-speed streams on low-frequency geomagnetic activity at high latitudes
Authors: Carnevale Giuseppina , Regi Mauro , Francia Patrizia , Lepidi Stefania , Di Mauro Domenico
Published: March 2024

In the Solar Wind (SW), when a fast stream overtakes a slower one, it forms a corotating high-speed stream (HSS) with an upstream corotating interaction region (CIR) and a downstream rarefaction region (RR). The SW speed and the interplanetary magnetic field (IMF) exhibit wide fluctuations within CIRs and HSSs, that may have effects on the geomagnetic activity. Our study aims to investigate the effects of Alfvénic and compressive low-frequency fluctuations within SW corotating streams at 1 AU on geomagnetic activity in the low-frequency range (Pc5, 1-7 mHz), as observed at high-latitude geomagnetic observatories in both hemispheres. We analyzed several corotating streams, which were analyzed together with the corresponding geomagnetic field data recorded at ground observatories at high latitudes. For each observatory, we estimated a long-term geomagnetic power background in correspondence with quiet geomagnetic activity periods (low Kp index); then, we re-scaled the power to the background to better highlight the geomagnetic variations during the selected events. For SW data, we rotated the IMF and SW velocity components at 1AU into the Mean ElectroMagnetic Field Aligned (MEMFA) reference frame to identify fluctuation along two main directions: one aligned and one orthogonal to the ambient magnetic field. We compared the re-scaled geomagnetic field power with SW parameters, such as the power of IMF and SW velocity along the two directions, as well as with two quadratic invariants used to describe MHD turbulence: the normalized cross-helicity and the normalized residual energy. This combined method helps distinguish between compressive and Alfvénic fluctuations, providing insights into their impact on low-frequency geomagnetic variations.
Quantifying the role of ocean biogeochemistry on the deglacial atmospheric CO2 rise using transient simulations with MPI-ESM
Authors: Liu Bo , Ilyina Tatiana
Published: March 2024

The ocean plays an essential role in the rise of atmospheric CO2 by about 90 ppmv during the last deglaciation. The deglacial oceanic CO2 outgassing is jointly controlled by the physical, biological and geochemical processes, which affect the variations in ocean circulation, biological carbon pump and alkalinity inventory. Transient simulations of climate-carbon feedback, particularly using the comprehensive Earth System Models, are instrumental tools to quantify the contribution of different processes and their interactions. Nonetheless, knowledge gaps still exist in the deglacial variations of oceanic carbon and nutrient cycling because considerable model uncertainties arise from the choices of model processes and parameters, and the proxy data is too sparse to fully constrain the model outcome.We conduct transient simulations for the last deglaciation with the Max Planck Institute Earth System Model (MPI-ESM) and examine the impact of different model tuning of the global ocean biogeochemistry component and a sediment module on the deglacial CO2 outgassing. The atmospheric CO2 is prognostically computed for the carbon cycle, considering only the atmosphere and ocean compartments, and it is prescribed for radiation computation. We force the model with reconstructions of atmospheric greenhouse gas concentrations, orbital parameters, ice sheet and dust deposition. In line with the physical ocean component, we account for the automatic adjustment of marine biogeochemical tracers in response to changing bathymetry and coastlines related to deglacial meltwater discharge and isostatic adjustment.We find the deglacial CO2 outgassing is mainly driven by the sea surface warming in MPI-ESM, whereas variations in surface alkalinity and DIC have a relatively small contribution (~18%). Furthermore, the parameterisation of organic debris remineralisation considerably affects the deglacial increase in the global NPP due to different recycling rates of nutrients in the upper ocean. When a longer lifetime of dissolved organic matter is prescribed, the dissolved organic carbon pool in the glacial ocean increases, further facilitating the glacial ocean carbon sequestration. Including an interactive sediment module strongly impacts surface alkalinity due to input-sedimentation imbalance, affecting air-ocean CO2 flux. Thus, attention has to be given to tuning and adjustments regarding the input-sedimentation imbalance of alkalinity in ESMs to better represent proxy data and the deglacial oceanic CO2 outgassing.
Monazite Geochronology of Deformational Strain Fabric and its Tectonic Implications of the Lower-Middle Crustal Rocks: A Case Study of Ambaji Granulite, NW India
Authors: Tiwari Sudheer Kumar , Biswal Tapas Kumar
Published: March 2024

Monazites crystallize along with silicate minerals, displaying microstructure characteristic of different recrystallization processes. They crystallize as the result of dislocation creep, dissolution creep or dissolution- precipitation creep, depending on pressure-temperature conditions and fluid composition. In dissolution- precipitation creep, newly formed grains replace pre-existing ones and appear as a distinct compositional domain under X-Ray and BSE images. Rock strain-fabric can be correlated with monazite-microstructure and dated using monazite-chemistry. Because it contains a significant amount of Th and U and lacks common Pb and continues to be used for Th-U-total Pb geochronology by chemical analysis in Electron Probe Microanalyser. As the closure temperature of monazite for Th-U-total Pb is ca. 800 °C; each domain retains its age of formation and can be used as geochronometer. Thus, monazite geochronology is used as an effective tool to constrain the timing of fabric development. Fourteen samples of Ambaji granulites of South Delhi Terrane, Aravalli Delhi Mobile Belt, NW India were used for the monazite geochronology and 306 analyses were performed. The microfabric of these samples has been studied to ascertain the category of strain fabric present in them.The Ambaji granulite comprises pelitic, calcareous, and mafic granulites with several phases of granite intrusions, G0-3. The granulites were deformed by three phases of folding, F1–3, during South Delhi orogeny and marked by a subhorizontal pervasive fabric, S1, axial planar to isoclinal-recumbent F1 folds that developed during granulite facies metamorphism. S1 is overprinted by discrete sets of subvertical shear zones associated with a mylonitic fabric, S2, that were developed axial planar to NE-SW striking upright F2 folds and facilitated exhumation of granulite facies rocks to the upper crust. The shear zones show early history of high-temperature thrust sense shear and late stage low-temperature sinistral shear. The NW-SE striking F3 folds also affected the granulite facies rocks. Brittle strike slip, and normal fault (Sf fabric) that developed post F3, led the final exhumation of the granulite facies rocks to the surface. The S1 monazites are Y-depleted and recrystallized through dislocation creep, and the S2-Sf monazites are Y-enriched and recrystallized through dissolution-precipitation creep. Different monazite population yielded distinct ages of circa 875-857, 834-778, and 764-650 Ma for S1, S2, and Sf strain, respectively, indicating that the South Delhi orogeny spanned 875-650 Ma overlapping with the early phase of the Pan-African orogeny or representing a transition between Grenvillian and Pan-African orogeny.
Shear-strain rates across the East Anatolian Fault (EAF) response to the 2020 Mw6.8 Elazig, and 2023 Mw7.8/Mw7.6 Kahramanmaras earthquake sequence
Authors: Liu Ziming , Wang Teng
Published: March 2024

Shallow creep, as a widespread phenomenon in the earthquake cycle, plays an important role in understanding the behavior of faults and seismic hazards. However, it is still under debate whether creeping is an inherent behavior of fault or is a form of afterslip following large earthquakes. The East Anatolian Fault was recently ruptured by the 2020 Mw6.8 Elazig, and 2023 Mw7.8/Mw7.6 Kahramanmaras earthquake sequence, providing a unique opportunity to investigate the relation between shallow creep and earthquakes along strike-slip fault. Here, we show the spatial distribution and temporal evolution of creeping segments along the EAF using the InSAR phase-gradient stacking method. We derive the shear-strain rates in three periods – before the 2020 earthquake, between the 2020 and 2023 earthquakes, and after the 2023 earthquake sequence. By comparing the spatial distribution of the interseismic strain rates, the coseismic slip, and the post-seismic strain rates, we document a tight connection between creeping and coseismic slip on the two recent earthquakes. We also investigate the temporal behavior of faults following the two earthquakes using time-series shear strain analysis. The results reveal behaviors of shallow creep on different segments of the EAF with different statuses before the earthquakes. Our results shed new light on understanding the mechanism of creeping and its relation with large earthquakes during the earthquake cycle.
Application of Life Cycle Assessment in Vegetarian Lunch Box: Environmental Impact Hotspot Analysis of Whole Grain and Vegetable Production
Authors: Chen Chih-Kang , Tung Ching-Pin
Published: March 2024

Life Cycle Assessment (LCA) is a systematic approach used to evaluate the environmental impacts of products, services, or activities throughout their life cycle, from raw material acquisition and production to use and final disposal or recycling stages. The goal of LCA is to comprehensively assess environmental impacts across the entire life cycle, including energy consumption, greenhouse gas emissions, water and land use, and more. The execution of LCA primarily involves four stages: "goal and scope definition," "life cycle inventory," "life cycle impact assessment," and "life cycle interpretation." This method helps identify and improve environmental hotspots in products or activities, aiming to reduce adverse impacts on the environment.This study references the "Packaging Lunch Box Product Category Rules" published by the Environmental Protection Administration of the Executive Yuan in Taiwan. Using a vegetarian lunch box manufacturer in Taiwan as a data source, a "Vegetarian Lunch Box Carbon Footprint Calculation Tool" was developed using SimaPro. Users can input first-tier data for each stage of the product life cycle (such as raw material input, energy, transportation distance, and output products), enabling the calculation of the carbon footprint of the vegetarian lunch box.However, during the "life cycle interpretation" stage, this study found that the "raw material acquisition stage" contributes 80% of the carbon footprint throughout the entire life cycle of the vegetarian lunch box. This indicates significant negative environmental impacts during the "agricultural production" process. As a result, the study traces the environmental impacts of upstream agricultural production processes for grains and vegetables and proposes an improvement strategy: regenerative agriculture.Regenerative agriculture practices include protective tillage to reduce physical soil disturbance, increasing biodiversity in fields, cover cropping to enhance soil carbon and prevent erosion, crop rotation for balanced soil nutrient use, and refraining from using chemical fertilizers and pesticides. The goal of regenerative agriculture is to sequester carbon in the soil and above-ground biomass, reducing greenhouse gas emissions, increasing crop yields, enhancing resilience to unstable climates, and improving the health and vitality of rural communities.This study will also employ the life cycle assessment method to collect inputs and outputs for both conventional farming practices and regenerative agriculture, comparing their environmental impacts.
Demystifying model uncertainty and internal variability in climate change projections over the 21st century
Authors: Gomez-Garcia Martin , Pui Alexander
Published: March 2024

Overall uncertainty in climate model projections is composed of scenario, model, and internal variability components. While scenario uncertainty is expressed by considering different climate scenarios, model uncertainty and internal variability components are largely ignored by climate information service providers. Instead, model projections are often expressed through the ensemble mean, which may lead to both overly optimistic assessments of risk, or on the other hand misinformed maladaptation strategies.Here, we propose a new uncertainty quantification approach that better informs end users of climate projections, showing that the multi-model internal variability, owing to its chaotic nature, is in fact virtually irreducible, and that model uncertainty grows moderately throughout the 21st century. For three future scenarios, we quantified the global internal variability of two metrics: annual precipitation (PRCP) and boreal summer average maximum daily temperature (TXJJA), by employing a single realization of each CMIP6 climate model. Our results showed that observed internal variability of the 1981-2010 period for the TXJJA metric has a negligible variation throughout the 21st century for all three scenarios. For the PRCP metric, small changes of internal variability were detected towards the end of the 21st century in the most adverse scenario (SSP3-7.0). Importantly, we observed that characterizing uncertainty in such manner produced a nuanced, and non-misleading results compared to that of the ensemble mean approach. Furthermore, the proposed uncertainty quantification approach can be expanded to similarly evaluate the uncertainty in indices of extreme weather.
Exploiting induced carbonate precipitation to improve reservoir storage integrity and geothermal system efficiency
Authors: Salter Philip , Dobson Katherine , Minto James , Warnett Jay
Published: March 2024

Biomineralization, through microbially, thermally, or enzyme induced carbonate precipitation (MICP/TICP/EICP), is a cost-effective cementation process for changing porosity and permeability in the subsurface. This study aims to optimize compositional and injection parameters for biomineralization fluids, and to develop understanding of the interactions between geochemical reactions and fluid transport properties at the pore (micron) scale. Utilizing real-time in situ X-ray computed tomography (XCT), we compare traditional Microbially Induced Calcium Carbonate Precipitation (MICP) with novel thermally delayed (TICP) and Enzyme Induced Calcium Carbonate Precipitation (EICP) in a range of lithologies. This allows us to investigate the impact of mineralogy, grain size distribution, and temperature as well as the injection composition and strategy. We present quantitative analysis of crystal locations, the volume of carbonate and of individual crystals, and the effect of crystals on permeability and flow localisation over time. Coupled to measured changes in microstructural and macroscopic properties over repeated precipitation and dissolution cycles we present refined models of reactive transport for different injection strategies, and identify the optimal treatment strategy for different subsurface applications. This includes validation of the durability of precipitated calcite seals during dissolution phase, simulating the behaviour of CO2-enriched brines.This work provides the underpinning understanding principles of crystal formation, growth and hydrodynamic feedback mechanisms necessary for accurate modelling of reservoir scale dynamic processes.  However, we also show how TICP and EICP strategies can improve performance of real-world Carbon Capture and Storage systems, driving more homogeneous, widely distributed and larger volumes of precipitated CaCO3 by maintaining permeability during treatment at higher degrees of cementation when compared to MICP. We also show how variable injection strategies allow improvement of other physical properties (e.g. mechanical strength) and enables the addition of highly conductive additives or phase change materials without reducing precipitation and flow. Using CaCO3 precipitation we observed a 470% increase in the thermal conductivity of unsaturated quartz sand after 9 cycles of MICP, and an 800% increase following addition of 5 wt% expanded natural graphite (ENG). Our findings also demonstrate the compatibility of integrating paraffin as a phase-change material within the porous matrix of ENG prior to MICP/EICP treatment significantly increasing specific heat capacity. These new geomaterials have widespread implications for thermal energy storage, specialized geothermal grouts/backfill, shallower wells and reduced geothermal energy costs.The project's outcomes impact the commercialization of engineered biomineralization and its role in the subsurface energy transition.
Monitoring of microfiber pollutants in karst environments
Authors: Balestra Valentina , Fiorucci Adriano , Marini Paola , Bellopede Rossana
Published: March 2024

Recent studies highlighted a preoccupant pollutant which impact natural environments: the microfibres. The term “anthropogenic microfibres” (MFs) includes fibres
Vital role of hydraulic capacity uncovered by mechanistic modelling of extreme drought impacts on European forests
Authors: Papastefanou Phillip , Arend Matthias , De Kauwe Martin , Grams Thorsten , Kahmen Ansgar , Rammig Anja , Sabot Manon , Zaehle Sönke
Published: March 2024

Climate extremes like drought are threatening forests worldwide. Record breaking forest mortality has been observed in central Europe in the past five years. Meanwhile, more and more experiments are being set up that enable measurements of  the hydraulic states of dying trees under extreme drought stress. These experimental data can be exploited by mechanistic vegetation models, offering  the possibility to disentangle environmental drought stressors, e.g. atmospheric and soil moisture dryness, and their effects on a plant’s hydraulic system, such as stomatal closure and loss of hydraulic conductivity. Here, we show how a next generation plant hydraulic modelling is able to accurately reproduce the water potential dynamics of dying trees. We apply this plant hydraulic model to European drought experimental sites, including the canopy crane experiment II in Basel, Switzerland, and the KROOF experiment in Freising, Germany. We find that soil heterogeneity, rooting depth and stem hydraulic capacity are critical in determining whether a tree survives or succumbs to drought. Furthermore, good knowledge of four parameters is crucial to accurately capture the magnitude and temporal development of observed leaf and stem water potential: (1) stem hydraulic capacitance, (2) P50 (the water potential at which 50% of a plant’s hydraulic conductivity is lost), (3) saturated xylem hydraulic conductivity, and (4) the reference leaf water potential associated with full stomatal closure. Finally, when implemented into the terrestrial biosphere model QUINCY, our hydraulic scheme produces a clear mortality signal associated with recent drought events, giving confidence in our capacity to project the impact of future droughts on European forests
WRF-Chem CO2 simulation over a medium sized city: An evaluation across grey-zone resolutions
Authors: Abdallah Charbel , Lauvaux Thomas , Joly Lilian , Crevoisier Cyril , Grouiez Bruno , Combaz Delphine , Dumelié Nicolas , Té Yao , Fu Hao , Lopez Morgan , Hase Frank , Humpage Neil , Bès Caroline , Guedj Axel , Pernin Jérôme , Bourdon Aurélien
Published: March 2024

Metropolitan areas are known to be anthropogenic “hot spots” of Greenhouse Gas (GHG) fluxes. To track the effectiveness of climate mitigation policies and emission reduction objectives, large metropolitan areas like Munich and Paris regions are currently being instrumented with dense atmospheric GHG networks, further assimilated in inversion systems with high-resolution inventories, also complementing the data collected by remote sensing instruments on the ground and in space. To study medium-sized cities, where a large fraction of the global population lives, spaceborne measurements often fail to quantify fossil fuel emissions since the atmospheric signatures are below the detection threshold of current instruments. For the past two years (2022 and 2023), two large-scale campaigns of the MAGIC initiative led by CNRS and CNES (https://magic.aeris-data.fr) have been taking place in Reims, France, a city with a population of 300,000 inhabitants (207 hab./km2) located to the East of Paris (approx. 100 km away). During these two intensive measurement campaigns, a wide range of ground-based instruments have been deployed around the city to measure CO2 concentrations, in addition to instrumented balloons and aircraft. The goal of these campaigns was to evaluate CO2 emissions from the area and to assess the detection capabilities of current satellite instruments.In our study, we simulated the atmospheric CO2 mixing ratios using the Weather Research Forecast model coupled to a chemistry transport model (WRF-Chem) at 4 horizontal resolutions (9 km, 3 km, 1 km, and 333 m). Typically, mesoscale models are used for resolutions coarser than 1 km while microscale Large-Eddy Simulation models (LES) are used for resolutions finer than 100m. In between, i.e. the grey-zone, turbulent motions are not resolved explicitly but high resolutions might offer a better representation of fine plume structures. Here, we present the results of a multi-scale multi-instrument comparison between the model and the observations to characterize the model performances and the ability of the model to reproduce the observed variations in concentrations. We found that the detectability of the various CO2 plumes remains challenging. First, the strength of the anthropogenic signals from the city remains low compared to gradients from nearby sources, whether industrial or metropolitan, hence making the city plume hard to study. We also showed that improvements in the modelling of CO2 plumes were not significant between the 1 and 0.3 km horizontal resolution scales, thus suggesting that LES models might be better suited for such studies.
Sketch-based geological modelling with flow diagnostics: the digital back-of-the-envelope for 3D geology and subsurface flow
Authors: Jacquemyn Carl , Jackson Matthew D , Hampson Gary J , Petrovskyy Dmytro , Geiger Sebastian
Published: March 2024

Sketch-based geological modelling with flow diagnostics provides an interactive and intuitive prototyping approach to quickly build geomodels and generate quantitative results to evaluate volumetrics and flow behaviour. This approach allows users to rapidly test the sensitivity of model outputs to different geological concepts and uncertain parameters, and informs selection of geological concepts, scales and resolutions to be investigated in more detailed models. Here we apply the sketching and prototyping approach to different aspects of geo-energy modelling and use in geoscience and engineering training.Rapid Reservoir Modelling (RRM) is a free open-source sketch-based geological modelling tool with an intuitive interface that allows users to rapidly sketch geological models in 3D (bitbucket.org/rapidreservoirmodelling/rrm). Geological models that capture the essence of heterogeneity of interest and related uncertainty can be created within minutes. Geological operators ensure correct truncation relationships between these 3D surfaces by the modelling engine. Flow diagnostics then computes key indicators of predicted flow and storage behaviour within seconds. Example use cases and how models can be shared, will be discussed, including:(1) Scenario screening to identify heterogeneities with the most impact on CO2 storage. Capturing uncertainty in geological concepts cannot be achieved by changing a numerical variable but can be varied easily by sketching the different concepts, such as lateral connectivity, continuity and geometry of geological heterogeneities that act as flow barriers and pathways. Capturing multiple different concepts in conventional modelling approaches is time-consuming and in practice not often carried out.(2) Use of mini-models and hierarchical models to derive effective properties. Models with varying complexity of heterogeneity are sketched at smallest relevant scale, and effective properties are calculated. Calculated effective properties can then be used to populated models sketched at larger scale. Sketching is free of existing restrictive templates, realistic subsurface models can be generated easily.(3) Training of geoscientists and engineers to investigate the impact of geological interpretations on storage volumes and connectivity. Geomodels addressing all three aspects are constructed and analysed quickly, using simple, geologically intuitive workflows that do not require prior geomodelling expertise. However, using conventional modelling packages, the learning curve to create or adapt a geological model is steep and long and can distract from training objectives. Using intuitive sketch-based approach the entry point to creating a geological model is much more accessible while still maintaining the key learning, i.e. impact of geology on subsurface applications.
Introducing uncertainty in hazard analysis in a simple way: example of rockfalls
Authors: Jaboyedoff Michel
Published: March 2024

One of the main problems of risk assessment is to evaluate the uncertainty of the results. One relevant solution is to provide exceedance curves based on simulations of the risk calculation (Macciotta et al., 2016; Jaboyedoff et al. 2021), as can be done with CAT models. Instead of performing a single calculation, up to 106 are performed with imputed viability based on different approaches such as observed distributions, standard probabilistic laws such as Poisson or uniform distribution, expert knowledge based on triangular distributions, etc. This can be done on the basis of a "deterministic calculation" of the risk, which allows a better assessment of the uncertainty of the risk.Drawing upon a precedent risk calculation study within a road corridor, a novel risk calculation methodology is suggested, employing stochastic simulations to introduce variability across the parameters in the risk equation. The outcome manifests as an exceedance curve akin to those generated by catastrophe models. This approach systematically introduces uncertainty into the risk calculation, providing a simplistic means to address inadequately documented cases with limited data. This approach tends to minimise risk or call risk calculations into question. References:Jaboyedoff, M., Choanji, T., Derron, M.-H., Fei, L., Gutierrez, A., Loiotine, L., Noel, F., Sun, C., Wyser, E. & Wolff, C. 2021. Introducing Uncertainty in Risk Calculation along Roads Using a Simple Stochastic Approach. Geosciences, 11, doi: 10.3390/geosciences11030143.Macciotta, R., Martin, C.D., Morgenstern, N.R. & Cruden, D.M. 2016. Quantitative risk assessment of slope hazards along a section of railway in the Canadian Cordillera—a methodology considering the uncertainty in the results. Landslides, 13, 115-127, doi: 10.1007/s10346-014-0551-4.
Vortices in the magnetic tail of Uranus
Authors: Pantellini Filippo , Griton Léa
Published: March 2024

Over the last twenty years, a still very limited number of extended numerical simulations of the Uranus magnetosphere, showed that large scale magnetic vortices form tailwards of the planet. Their structure is strongly time-dependent on daily and seasonal time scales, both,   because of both, the unusually large 59 deg angle between the magnetic axis and the rotation axis of the planet and the small angle (unique in the solar system) between the rotation axis and the orbital plane. Based on results from 3D magnetohydrodynamic simulations, we comment on the nature and the structure of the vortices at both solstice and equinox. 