bluuebunny/crossref_metadata_2025 huggingface dataset:
Benefits of the Brinkman Volume Penalisation Method for the Ice-Shelf Melt Rates Produced by Z-coordinate Ocean Models
Authors: Nasser Antoine-Alexis , Jourdain Nicolas C. , Mathiot Pierre , Madec Gurvan
Published: March 2024

Antarctic ice-shelf basal melting is a major source of uncertainty in sea level rise projections. A persistent challenge in simulating the ice-shelf-ocean interactions in z-coordinate ocean models is the introduction of artificial steps, leading to the generation of noise that impacts both melting and ocean currents. This study explores the potential of the Brinkman Volume Penalisation (BVP) method (Debreu et al. 2020, 2022) to address the recurrent issue of steps in ice-shelf-ocean models. While penalisation methods are typically applied to land topography, here, the method is generalised to ice-shelf interactions with oceans. This approach introduces porous cells that are half-ice, half-ocean, combined with a permeability parameter (friction within porous cells) to model the blocking effect of the ice draft. A unique aspect of this method is its ability to spread the penalisation region, thereby reducing model sensitivity to numerical level changes. We assess the potential benefits of the BVP approach within the idealised ice-shelf configuration ISOMIP+ as presented by Asay-Davis et al. (2016). First, a new calculation of the horizontal pressure gradient is formulated using the BVP approach, which eliminates residual biases in ocean currents down to zero machine precision. Second, the spreading of the penalised interface significantly reduces noise in the melt rates, enabling a smooth response of the ocean beneath the ice-shelf without the need for further mesh refinement. Other simulations are used to investigate the sensitivity of basal melting and freezing in the penalised configuration to changes in numerical parameters (e.g. spatial resolution). These results pave the way for a better numerical treatment of ice-shelves in earth system models.
Changes of clouds and sea ice in EC-Earth- and ERA5-driven retrospective ensemble hindcasts with the fully coupled ice-sheet–ocean–sea ice–atmosphere–land circum-Antarctic model PARASO
Authors: Sauerland Florian , Huot Pierre-Vincent , Marchi Sylvain , Goosse Hugues , van Lipzig Nicole
Published: March 2024

We created 4 retrospective hindcasts using PARASO, a five-component (ice sheet, ocean, sea ice, atmosphere, and land) fully coupled regional climate model over an Antarctic circumpolar domain: a control run forced with reanalysis data from ERA5 and ORAS5, and an ensemble of 3 members forced by 3 different EC-Earth global hindcasts. We compare the ocean and sea ice properties of the ERA5-driven simulation to the ensemble mean of the EC-Earth-driven ones, to separate the impact of the different source of boundary conditions from internal variability generated by the different ensemble members. Moreover, we analyse if and how the different ocean temperatures and sea ice extents influence the formation of clouds. We compare the moisture and heat fluxes at the ocean surface between the EC-Earth-driven ensemble and the ERA5-driven hindcast, as well as the moisture and cloud water contents in the atmosphere. This not only provides information on the contribution of external and internal variability inside the PARASO domain for those variables, but by comparing the variability in fluxes to the variability of clouds, we can also estimate the importance of ocean-cloud-interactions. Our results also show that the increasing trend observed in Antarctic sea ice extent observed prior to 2015 is well represented in the ERA5-driven run, but not in the EC-Earth-driven ensemble, indicating a stronger influence of mid-latitude forcings compared to local processes. 
Impact of microphysical perturbations on convective precipitation predictability
Authors: Czajka Beata , Barthlott Christian , Hoose Corinna
Published: March 2024

The predictability of deep moist convection is subject to large uncertainties, mainly due to inaccurate initial and boundary data, incomplete description of physical processes, or uncertainties in microphysical parameterizations. In this study we present results from a large 108-member ensemble focussing solely on the perturbation of microphysical uncertainties. We perturb the cloud condensation nuclei concentrations, the ice nucleating particle concentrations, the graupel sedimentation velocity as well as the width of the cloud droplet size distribution, all of which are not well constrained by observations. The model simulations are conducted with a convection-permitting configuration of the ICON model using a double-moment microphysics scheme. Results from four convective episodes during the Swabian MOSES field campaigns conducted in the summers of 2021 and 2023 show a large spread in convective precipitation in Germany. Based on convection-related parameters and microphysical process rates, the sensitivities of convection initiation, cloud and precipitation formation to the microphysical uncertainties are discussed. An important finding is e.g. the large sensitivity of hail formation on all analysed days. These results demonstrate the benefits of using an aerosol-aware double-moment microphysics scheme and that the use of microphysical uncertainties for ensemble modelling strategies can produce a sufficiently large ensemble spread for convective-scale predictability.
Impacts of climate change and LUCC on eco-hydrological processes in semi-arid and semi-humid regions of China  
Authors: Mo Xingguo , Hu Shi , Sang Jiawen , Huang Licheng , Liu Suxia
Published: March 2024

The semi-arid and semi-humid region of China occupies an area of more than 200 million km2. Since years of ecological restoration implementation, land use cover changes (LUCC) significantly with the vegetation continually recovered in the recent decades. During this period, climate change is significant in the region with air warming and precipitation extremes intensification. How climate change and LUCC play different roles in the land surface – atmosphere exchanges and catchment hydrological processes is still not clear.  Based on VIP (Vegetation Interface Processes) distributed eco-hydrological model, the eco-hydrological changes are predicted integrated with remotely sensed vegetation information. Fourteen catchments in the study region are selected to explore the diversified responses and feedbacks of the vegetation recovery to climate change. It is found that evapotranspiration (ET) and vegetation gross primary productivities (GPP) are increasing steadily in the study period from 2000 to 2020, in which ET and GPP from the forest and cropland are more distinguished with each other. However, terrestrial water storage is decreasing in the southern catchment, especially those over the Loess Plateau. Although the water consumption from vegetation is increased, water availability  is still increasing in most of the study area due to enhanced precipitation, which implicated the intensification of the hydrological cycle with climate change and global greening. The complex interactions and feedback between re-vegetation and climate change in the water limited region posed challenges to the water resources management and ecosystem stability, in need of paying much more special attention.
Vivianite as a phosphorus sink in estuarine systems: The case study of the Brillantes mudflat, Loire, France
Authors: Barhdadi Mohammed , Mouret Aurélia , Barras Christine , Morin Guillaume , Maillet Grégoire , Durand Matthieu , Mojtahid Meryem , Bénéteau Eric , Dubosq Nicolas , Metzger Edouard
Published: March 2024

Phosphorus (P) is a key nutrient controlling primary production in aquatic systems. In coastal systems, the P cycle involves dynamic interactions between terrestrial, aquatic and sedimentary compartments. Over the last century, human activities such as deforestation, intensive agricultural practices and the disposal of municipal and industrial wastes have increased P inputs to coastal ecosystems. As a result, this increase in P inputs has led to an increase in the occurrence of algal blooms and higher oxygen demand in estuaries. In the Loire estuary, dissolved oxygen deficits have been a recurrent and worrying issue for several decades despite the improvement of water quality over the last 30 years due to reduced wastewater discharge and better effluent treatment. In this context, the burial of bioavailable P may influence the recovery of waters from eutrophication. The major P burial phases are apatite, organic P and iron-bound P. The results of sequential chemical extraction and pore water analysis carried out over a 5m-long sediment core from the intertidal Brillantes mudflat in the Loire estuary indicated a greater abundance of the iron-bound P compared to other phases. Iron-bound P occurs in two different forms: phosphorus bound to iron oxides and in the iron phosphate mineral known as vivianite. Vivianite is a ferrous iron phosphate mineral formed under reducing and low sulphate conditions in sediments where organic matter serve as electron donor for ferric iron reduction. Results of sequential chemical extraction of freeze-dried sediment samples combined with pore water data and scanning electron microscope–energy dispersive x-ray spectroscopy (SEM-EDXS) on resin-embedded sediment samples indicated that vivianite-type minerals may act as an important sink for P at the studied site. Authigenic vivianite crystals were found below the shallow sulphate/methane transition zone (SMTZ) at 94 cm depth and contain significant amounts of manganese, as observed in freshwater sediments. We therefore hypothesise that anthropogenic over-fertilization of coastal regions in the last century may have increased the importance of vivianite authigenesis in surface sediments. Consequently, vivianite is likely to be an important sink for P in estuarine systems worldwide.This study is part of a PhD financed by the European Project Life REVERS’EAU.
Influence of network geometry on the sensitivity of alluvial rivers to environmental and tectonic change
Authors: McNab Fergus , Schildgen Taylor , Turowski Jens , Wickert Andy
Published: March 2024

Alluvial rivers are an integral part of sedimentary systems, moving sediment from erosional source regions to sinks in which it is deposited and stored. Understanding their behaviour is crucial to interpreting landforms that develop along stream, such as cut-and-fill terrace sequences, and stratigraphic records preserved downstream. As such, a series of recent analogue and numerical modelling studies have explored how external forcings such as changes in sediment supply, precipitation rate, and base level—which, in turn, are associated with changing environmental or tectonic conditions—translate into aggradation and incision along alluvial rivers and variations in the amount of sediment they transport. In almost all cases, these studies have employed a simplified, linear geometry in which water and sediment are supplied only at the river inlet or increase continuously downstream. This simplification leads to difficulties when attempting to apply resulting concepts in field settings, where rivers form branching networks. For example, the system length is often emphasised as a key control on a river's response time, but a river network has no single length.Here, we explore the effects of network geometries on estimates of their sensitivity to external forcing. We use a physically based model describing the long profile evolution of and sediment transport by alluvial (transport limited) rivers. We analyse large sets of randomly generated network topologies to assess the range of possible behaviours. We show how the effects of an isolated event, such as a large landslide, propagate through an entire catchment. We also investigate responses to pervasive changes in sediment production or precipitation rate. We find that sensitivity to external forcing—as well as the extent to which the network response lags behind the imposed forcing—varies significantly throughout a river network, with important implications for interpreting distributions of fluvial terraces and their ages. Nevertheless, properties that integrate over the entire catchment, such as the total sediment export, do behave in similar ways to the simplified linear case. We show that variability in sediment export is closely related to the mean catchment length (i.e., the mean distance from channel heads to the catchment outlet), more so than the maximum trunk-stream length, as might otherwise be assumed. We conclude that accounting for network geometry is critical when interpreting landforms and patterns of sediment transport within specific catchments, while linear models remain useful for predicting river networks' general behaviour.
Optimizing Full Waveform Inverse Problems: A Combined Data and Model approach
Authors: Mercier Arnaud , Maurer Hansruedi
Published: March 2024

Full Waveform Inversion (FWI) has emerged as a groundbreaking tool in geophysics, offering unprecedented resolution in subsurface imaging. However, its broader application is often limited by substantial computational demands, especially in 3D elastic applications. This research addresses this critical barrier by introducing a novel approach that optimizes both data (source-receiver layout) and model (model parameterization) spaces, thereby reducing computational overhead and extending FWI's applicability. The interdependence between data and model spaces is a key factor to optimize FWI. We believe that both spaces must be simultaneously optimized to enhance the efficiency of FWI. This optimization is particularly crucial for intensive FWI problems but is also expected to make FWI accessible to a broader range of users, including those with limited computational resources.We combine principles from Optimal Experimental Design (OED) and Compact Full Waveform Inversion (CFWI). Selecting only the most relevant source-receiver pair ensures a minimal, yet informative data set. By using a wavelet representation of the model, it is possible to easily tune the compression of the model based on the local resolution. The outcome of our data-model approach is a source-receiver layout that maximize the resolution of a compressed representation of the model.Initial results with applications focused on synthetic 2D acoustic problems shows that the data-model approach allow for a significant reduction in both source-receiver pairs (≈ 50%) and model parameters (≈ 90%), whilst retaining 90% of the information content. Compare to classical OED criterion, our approach posses a lower time complexity by about 2 order of magnitude (O (m) vs O (mn2)). The significant speed up enables optimizing for sources and receivers independently, leading to further optimized layouts.The data and model compression enables the use of Gauss-Newton optimization algorithm, leveraging faster convergence and greater flexibility. Benefits of this algorithm includes the possibility to optimize source-receiver layouts not only prior to fieldwork, but also during the inversion. At each stage of the inversion process, the most relevant data points are effectively identified and retained. This selection significantly reduces both computational and memory requirements. An additional benefit of this approach is the straightforward implementation of targeted OED, enabling optimization of the source-receiver layout for specific subsurface targets.Key aspects to ensure a reliable and efficient data-model approach include evaluating the prior model's influence, examining the effects of compression ratio, resolving ambiguities in survey layout and model parametrization, and refining source and receiver positioning. We will present initial results and  highlight its potential benefits to significantly reduce the computational load of FWI.
Towards an Observation Operator for Satellite Retrievals of Sea Surface Temperature with Convolutional Neural Network
Authors: Broccoli Matteo , Cipollone Andrea , Masina Simona
Published: March 2024

Global ocean numerical models typically have their first vertical level about 0.5m below the sea surface. However, a key physical quantity like the sea surface temperature (SST) can be retrieved from satellites at a reference depth of a few microns or millimeters below the sea surface. Assimilating such temperatures can lead to bias in the ocean models and it is thus necessary to project the satellite retrievals to the first model level to safely use them in the assimilation process. This projection is non-trivial, since it depends on several factors (e.g., daily cycle, winds, latitude) and it is usually performed either with computationally expensive numerical models or with too simple statistical methods.  In this work we present an attempt to construct the projection operator with machine learning techniques. We consider three different networks: a convolutional neural network architecture called U-Net, which was first introduced in the field of computer vision and image segmentation, and it is thus optimal to process satellite retrievals; a pix2pix network, which is a U-Net trained in an adversarial way against a patch-classifier discriminator; a random forest model, which is a more traditional machine learning technique. We train the networks with L3 global subskin SST from AVHRR’s infrared channels on MetOp satellites produced by OSISAF and wind speed analysis at 10m by ECMWF to reproduce the ESA SST CCI and C3S global SST reprocessed product by CMEMS, that we take as ground truth during training and validation. The pix2pix network is the most effective in the projection and we thus choose it to shape an observation operator for the CMCC’s OceanVar assimilation system.Finally, we compare several one-year-long reanalysis-like experiments, based on the CMCC reanalysis system, that assimilate the SST in different ways, e.g. nudging, unbiased approach, as observation operator. We discuss the potential impact of such new scheme in providing the best surface ocean state estimate.
Neural network-based calibration of Swarm Langmuir Probe ion densities
Authors: Smirnov Artem , Shprits Yuri , Lühr Hermann , Pignalberi Alessio , Xiong Chao
Published: March 2024

    The European Space Agency's Swarm constellation consists of three spacecraft (A, B, and C). Each of the satellites is equipped with a Langmuir probe (LP), which measures ion densities and temperatures. The LP processing assumes that the plasma consists exclusively of oxygen ions, which leads to the nighttime overestimation of plasma densities due to non-negligible influence of light ions that is not accounted for in the LP processing. Each of the Swarm satellites also provides electron density measurements by the Faceplate (FP), which is part of the Thermal Ion Imager (TII) suite. The FP densities do not depend on assumptions of the plasma composition. In this study, we use the FP densities as a reference, in order to calibrate the LP observations. We model the ratio of FP to LP data using neural networks. We create three models, for each of the satellites, and are able to produce, even from sparse observations, correction factors for Swarm LP densities. The proposed correction exhibits significant variations based on local time, season, altitude, and solar activity, consistent with the presence of light ions due to the downward ambipolar diffusion from plasmasphere. The developed model resolves the nighttime overestimation by Swarm-LP. The corrected LP data are in excellent agreement with COSMIC radio occultation observations, and can be used for numerous applications including empirical modeling of the topside ionosphere.
ISeeSnow - initiating an avalanche simulation tool intercomparison
Authors: Wirbel Anna , Oesterle Felix , Fischer Jan-Thomas , Chambon Guillaume , Faug Thierry , Gaume Johan , Glaus Julia , Hergarten Stefan , Issler Dieter , Jarosch Alexander , Jóhannesson Tómas , Martini Marco , Mergili Martin , Rauter Matthias , Robl Joerg , Rosatti Giorgio , Spannring Paula , Tollinger Christian , Vicari Hervé , Zugliani Daniel
Published: March 2024

The ISeeSnow pilot-study aims at bringing together and starting a conversation among the different groups in the field of gravitational mass flow simulations, with a focus on snow avalanches. These simulation tools are an integral part of engineering practice, scientific development and academic education.At its core, an objective comparison of simulation results is performed for three different test cases, based on a generic, idealized topography as well as a real-world simulation scenario. In this initial effort, we focus on thickness-integrated shallow water models using a simple Coulomb- or classical Voellmy rheology. In this manner, comparing simulation results for the test cases, prescribing the friction parameters, topography, release area and release thickness, allows us to analyze common features and differences stemming from the various implementations, i.e. formulation of model equations, choice of numerical methods and their implementation into computer code as well as geo-data handling (input/output). We also include simulation tools that rely on a different mathematical formulation and basic assumptions (e.g. 3D models or conceptual approaches) and perform a qualitative comparison for a specially designed test case. Furthermore, performing this pilot-study helps to identify common data needs, come up with standard result formats and discuss helpful visualization options. As a third outcome, we summarize ideas on what is needed to perform a more comprehensive model intercomparison study which also tackles model verification and validation tests, with respect to test designs, required input data as well as model configuration options. In this community-based contribution, we present the concept of the ISeeSnow pilot-study, show preliminary results of the simulation comparison and give an outlook on potential avenues for a future comprehensive model intercomparison project.
Designing a smart early warning hydrometeorological system for flashfloods and landslides in Zagori, Epirus, Greece (UNESCO World Heritage List)
Authors: Chasiotis Angelos , Nastos Panagiotis , Feloni Elissavet , Chasiotis Stefanos , Bousdeki Maria , Mathiou Panagiota , Manthos Theofanis
Published: March 2024

Increased intensity in rainfall leads to more intense flash floods, which seems to affect more possible landslides. Moreover, when these occurrences take place within regions designated as UNESCO World Heritage Sites, it holds significant importance to, at the very least, observe and subsequently establish warning systems for such events.The area of Zagori, located in North-West Greece, has just recently recognized in UNESCO’s World Heritage List for the universal value of the architecture as an example of a traditional, stone-built settlement that reflects a special culture, representative of the common heritage of Byzantine and Ottoman vernacular architecture of the wider Balkan region. The authenticity and integrity of the cultural property are also recognized concerning 20 villages distributed in Central Zagori, Tymfi and Papigo.
The region experiences a substantial impact from the climate crisis, particularly during the winter season when it witnesses numerous occurrences of flash floods, ultimately leading to the influence on local landslides.

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In the frame of this work, SMILE ZAGORI project’s objectives (which is funded by Greek Government) are presented, as well as the general scheme of an under-development tool that is equipped with a monitoring system for flashfloods and landslides. This system is set to advance into an expanded Early Warning System (EWS) by incorporating data from newly deployed hydro-meteorological sensors. Additionally, it will incorporate data gathered from various sources, including unmanned aircraft (UAS), terrestrial relief scanners (TLS), and handheld laser scanners (HLS) to enhance its capabilities. Keywords: Hydrometeorological hazard; Flooding; Early Warning System; Civil protection; LandslidesAcknowledgement: This work is financed by Greek Government – Program “Antonis Tritsis”. Authors would like to thank the Municipality of Zagori for the provision of available data.
An unbiased view of the contributions to turbulence cascade in Earth's magnetosheath.
Authors: Montagud-Camps Victor , Toledo-Redondo Sergio , Hellinger Petr , Verdini Andrea , Papini Emanuele , Stawarz Julia , Sorriso-Valvo Luca , F. Albert Inmaculada , Castilla Aida
Published: March 2024

Earth's magnetosheath is a medium where plasma parameters can take a wide range of values and where plasma fluid properties can vary greatly, depending on the distance to the bow shock and the upstream solar wind conditions. Plasma turbulence that develops in the magnetosheath is also affected by these changes, thus giving rise to a similar variety of turbulence regimes.With the data collected during the MMS unbiased magnetosheath campaign, it is now possible to explore the plasma parameter space of the magnetosheath and study turbulence properties with a set of high-cadence in-situ measurements. This dataset was gathered from February 1st 2023 to April 1st 2023 and consists of 15 inbound magnetosheath crossings from which 300 burst-data intervals were collected. During each crossing, the burst-mode measurements were taken for 3 minutes every 6 minutes, without imposing any selection criteria to collect the data. The length of the time intervals and their time resolution make them suitable to study the turbulent dynamics around the ion spectral break.In this work we will study the different contributions to the energy cascade rate (measured by means of scaling laws derived from the Hall-MHD equations) and their dependence on plasma conditions, like the plasma beta, and turbulence properties, such as the spectral index and turbulence anisotropy.
A laboratory study of plumes associated with pyroclastic density currents
Authors: Carazzo Guillaume , Robert Geoffrey
Published: March 2024

Volcanic plumes associated with propagating pyroclastic density currents can rise tens of kilometers into the atmosphere, dispersing fine ash particles over large areas with a potential hazard for aviation safety. Such plumes originate from the buoyancy reversal of the pyroclastic density currents caused by the entrainment and heating of ambient air combined with the sedimentation of coarse particles. Several experimental and numerical studies investigated the formation, dynamics and impacts of these plumes but the mechanisms controlling the mass partitioning between the buoyant rising plume and the dense propagating current have received less attention despite its crucial importance for hazard assessment. Here, we present a new laboratory study aimed at investigating the controls on the mass partitioning during the plume lift-off. The experimental set-up is designed to simulate a gravity current of ethanol and ethylene glycol (EEG) flowing under a sloping roof in a tank of fresh water. The EEG mixture is less dense than fresh water but may become denser when mixed with water allowing us to generate a plume associated with the gravity current. Depending on the source conditions, the turbulent gravity current may either fully lift-off to form a buoyant plume, separate in a dense propagating flow and a buoyant plume, or propagate along the slope with no plume formation. We show that the transition between the three regimes is strongly controlled by the Richardson number defined at the source and by the slope. The results are consistent with the theoretical predictions of a simple 1D model and provide constraints on the mass partitioning during the formation of the plume.
Microgravity surveys for geothermal exploration in Tenerife and La Palma islands (Canary Islands)
Authors: Ortega-Ramos Víctor , Lai Julian Benjamin , Sulvarán Aguilar Isabella Michelle , Quezada-Ugalde Adriana , Álvarez Hernández Aarón , García Hernández Rubén , Jiménez-Mejías María , Martínez van Dorth David , Padilla Germán D. , D’Auria Luca , Pérez Nemesio M.
Published: March 2024

Gravimetry is a passive geophysical technique that measures variations in the Earth's gravitational field over its surface. This method studies the gravimetric anomalies caused by the presence of heterogeneities in the subsurface, and its values vary depending on the density of the different geological bodies in the subsoil. This technique has become fundamental in geothermal exploration, providing information on the subsurface density distribution, which allows for constraining underground geological structures. Specifically, it could enable identifying and characterizing gravitational anomalies generated by geothermal resources.This work is focused on the islands of Tenerife and La Palma, belonging to the Canary Islands. These two islands have been the object of different microgravity studies in recent decades. However, we aim to reach unprecedented detail on some target areas to get a detailed image of the subsurface density distribution. We measured gravity on 109 points in a few target areas of Tenerife and 67 points on the Cumbre Vieja Volcano Complex on the island of La Palma. The precise positioning of the measurement points was realized with a differential GPS (Leica Viva CS10) reaching less than 0.003m of accuracy in the vertical component. Gravity measurements have been realized with a CG-6 Autograv™ gravity meter with a reading resolution of 1 μgal. Every gravity value has been obtained with an average of at least ten measurement cycles of thirty seconds each. This allowed reaching a precision of less than five μgal. Firstly, we got Bouguer anomaly maps of the different target areas of Tenerife and La Palma. Then, we perform inverse modelling to retrieve 3D density models of such regions. Although preliminary, the results reveal a complex geological setting, in accordance with previous geophysical studiesThe gravimetric method plays a crucial role in identifying geothermal resources in the Canary Islands. This technique offers perspectives to further develop renewable energies in the Archipelago, fostering a transition towards more sustainable and environmentally friendly energy sources.
A model-based methodology for the delineation of complex alpine spring catchments
Authors: Seelig Magdalena , Seelig Simon , Vremec Matevž , Wagner Thomas , Winkler Gerfried
Published: March 2024

Spring catchments in Austria are frequently located in alpine regions that are strongly exposed to the effects of global warming. To predict their impact on spring flow, the delineation of hydrological catchments establishes the link between atmospheric input, catchment characteristics, and aquifer properties. This study proposes a delineation methodology that combines a lumped-parameter model with the analysis of stable isotope data. The model includes a semi-distributed snow module (CemaNeige) and a rainfall-runoff model (GR4J), which were applied iteratively to a set of potential catchments of varying extent and location to simulate spring flow. Constraining the models by spring flow data and remote sensing of snow cover distribution allowed us to differentiate plausible catchments from implausible ones. The mean catchment elevation was estimated based on stable hydrogen and oxygen data collected monthly at the springs. The proposed methodology was tested at two karst springs draining geologically complex catchments in different mountain ranges of the Northern Calcareous Alps, where the hydrological catchments deviate strongly from the orographic ones. The catchments lie mainly in mountainous plateau regions that are characterized by high altitudes and long-lasting snow cover. The model results and isotope analysis are in line with additional, independent information based on tracer experiments, structural geology, and speleology. The proposed methodology provides a quantitative, model-based approach to delineate plausible spring catchments in high alpine and complex hydrogeological settings. It thus forms the knowledge base for sustainable management of alpine freshwater resources under a changing climate.
Sources of biases in blocking representation in climate models
Authors: Barpanda Pragallva , Li Camille
Published: March 2024

Despite decades of research, climate models have failed to produce a consistent picture about regional variations in atmosphere blocking. The lack of sufficient model outputs has impeded the progress in unraveling the sources of biases in the model simulations. To address this issue, we perform a systematic analysis of blocking events, from two state-of-the-art climate models  with high temporal and spatial resolution — Community Earth System Model, Large Ensemble Community Project 2 (CESM LENS2) and the Norwegian Earth System Model medium resolution (NorESM2-MM) —alongside an idealised simulation featuring regionally varying CO2 forcings. A benchmark dataset of blocking events is created using the finite-amplitude local wave activity metric since it captures the growth and decay of high-amplitude Rossby waves while conserving wave activity density up to higher accuracy.  We also perform a detailed analysis of the wave activity budget to quantify the dominant physical processes that lead to biases in historical runs and processes that shift blocking patterns in warming scenario model runs.
Why do sun-blocking drops high up in the air cool down the world less than we would expect?
Authors: Günther Moritz , Schmidt Hauke , Timmreck Claudia , Toohey Matthew
Published: March 2024

Some large rocks can burst out and put fire and smoke into the air, and I will call them fire rocks. Sometimes, the fire rocks also give off little drops in the higher part of the air, which stay there for a few years. Sun light has a hard time passing through these drops, and this makes the world a bit darker. When the fire rocks give off sun blocking drops, we would expect the world to get quite a lot colder, because the world now gets a lot less power from the sun. However, it actually gets only a bit colder: the change is less than we would expect. In order to find out why, I use a computer to study how the world would respond to the sun-blocking drops.
The small cooling can be explained by the fact that some places of the world cool faster than others. One key place is that part of the world where the water is the warmest. On a paper that shows all the world's land and water, this place is in the left part of the largest water body. I will call it the warm water place. The drops that come from the fire rocks cool down the warm water place very much. When the warm water place cools down a lot, the rest of the world can remain more or less how it was before, because the warm water place has a strong control over the rest of the world. Over the warm water place there is a lot of up-going air, which means that it is well tied to the air that is closer to space. For this reason, the warm water place can even out the cooling very well, much better than any other place in the world.
Making the world darker with these drops is a way to make the world colder, but we are most used to the case where the world gets warmer because humans put warming smoke into the air. We can put a number on the forces that are caused by the warming smoke and the cooling drops. In the end, warming and cooling are the same thing, just with a different sign, so we can look at them side by side. The forcing that comes from the warming smoke does not leave such a strong mark on the warm water place, and for this reason it is very good at making the world hotter. On the other hand, the warm water place responds in a strong way to the cooling drops that block the sun light, and this makes the cooling drops very bad at cooling the world.
Taking your breath away with Early Cretaceous Boreal seawater oxygenation
Authors: Blok Carlette N. , Andreasen Rasmus , Sheldon Emma , Jelby Mads E. , Ineson Jon , Anderskouv Kresten , Bodin Stéphane
Published: March 2024

Mesozoic Oceanic Anoxic Events (OAEs) were linked to the accumulation of organic-rich sediments in response to global climatic and environmental changes, resulting in transient episodes of oceanic deoxygenation. To better understand the evolution of seawater oxygenation in the Boreal Realm during the Early Cretaceous (late Hauterivian – early Aptian), this study presents high-resolution datasets of Rare Earth Element plus Yttrium (REE + Y; REY) patterns and redox-sensitive trace elemental (RSTE) concentrations in the Danish Central Graben (DCG). Oxygenation in the seawater column can be derived from the Cerium (Ce) anomaly (Ce/Ce*), which is based on the premise that Ce acts differently in well-oxygenated environments compared to the other REYs. At the seafloor, anoxia is indicated by the enrichment of RSTEs Vanadium (V) and Uranium (U). A decline in Ce anomaly values and low RSTE concentrations from the late Hauterivian to late Barremian indicates a shift from an oxygen-depleted to a more oxygenated seawater column and seafloor conditions in the Boreal Realm. A similar trend is observed in the Tethyan Realm, suggesting the existence of a global long-term driver of seawater oxygenation level. In the DCG, this long-term trend is interrupted by a brief drop in relative sea level, leading to partial isolation of the basin, reduced ventilation, stratification of the water column and consequently short-term anoxic conditions at the sediment–water interface. This resulted in the deposition and preservation of an organic-rich layer (Munk Marl Bed) during the early Barremian. During the early Aptian, an organic-rich layer (Fischschiefer Member) of regional extent, linked to the global OAE-1a, was deposited. Significantly elevated Ce anomaly values along with increased concentrations of U and V signify anoxic conditions within this Boreal basin, whereas the seawater column in the Tethyan Realm exhibited dysoxic conditions. Variations in anoxia and the fact that some OAEs are only observed locally, leads to the conclusion that short-term regional or local factors can overprint global changes.
Flood Forecasting with Deep Learning LSTM-Networks: Relevance of Catchment Attributes in Regional Network Training
Authors: Morgenstern Tanja , Grundmann Jens , Schütze Niels
Published: March 2024

Floods present one of the most frequent natural hazards in Germany. In order to efficiently and successfully deal with instances of floods we need timely and reliable forecasts of the expected runoff. During the last decades, several deep learning methods proved to be valuable for rainfall-runoff modelling in many larger catchments, especially Long Short-Term Memory (LSTM) networks. One of the core challenges of data-driven models is the provision of an extensive and informative training database, implicitly describing the cause-effect relationships for different catchment conditions. However, the data basis of individual catchments regarding flood events may be limited due to short observation time series as well as a general lack in flood events during the observation period, which may cause flawed data-driven models for flood forecasting. These problems become even more pronounced in hourly flood forecasts for small-scale, fast responding catchments.In this study with the purpose of hourly forecasting runoff events in small-scale Saxon catchments, we solved aforementioned dilemma through an extension of the training database from single-catchment datasets (“local network training”) to one dataset containing multiple catchments from one bigger region (“regional network training”). In consequence, we trained our LSTM networks on hourly rainfall and runoff time series of preselected rainfall-runoff-events from 52 Saxon catchments. Alongside these time series, we included a selection of attributes regarding the catchment’s characteristics and its climate, which allows the model to differentiate between catchments and to condition the runoff generation according to the catchment characteristics. In this contribution, we show that our regional network training facilitates rainfall-runoff simulations even at gauging sites with short observation periods – too short to enable local network training – and in in extreme cases even at ungauged catchments during flood events. We further discuss the following questions:Which catchment attributes have the highest influence on the quality of hourly flood forecasting in regional network training? The selection of attributes contains topography (e.g. area, catchment shape, elevation, slope & river length), land use (e.g. sealing of the ground & vegetation) as well as climatic conditions (e.g. aridity, yearly potential evapotranspiration and rainfall).
In which case may the catchment attributes be omitted in regional network training?
When do local and regional network trainings result in flood forecasts of similar quality?
Assessing the Effect of Temperature on the Biodegradation Dynamics of Biodegradable Mulch Films in Laboratory Soil Incubations
Authors: Wille Flora , Sander Michael
Published: March 2024

Mulch films are widely used in modern agriculture due to their many benefits, including extension of the growing season, control on weeds, and saving irrigation water. Biodegradable mulch films (BDMs) — films containing one or more polymer(s) that can be fully metabolically utilized by soil microorganisms to form CO2 and microbial biomass — are considered a viable substitute to conventionally used, environmentally persistent polyethylene films that accumulate in soils over time if not completely removed after harvest. The European Norm for BDMs (EN 17033:2018) stipulates laboratory incubations at 20-28°C to test biodegradation of BDMs for certification. However, to comprehend and predict the fate of BDMs in situ in field soils, it is crucial to understand how temperatures (and variations thereof in the field) affect biodegradation dynamics. Research on this subject is currently limited. In the work presented here, we systematically assess the effect of temperature on the biodegradation dynamics of three commercially available BDMs which are mainly composed of the biodegradable polyesters poly(butylene adipate-co-terephthalate) (PBAT) and polylactic acid (PLA). Laboratory soil incubations were conducted at four environmentally relevant temperatures (i.e., 5, 15, 25, and 35°C) across three different agricultural soils over a two-year period. The biodegradation extents were monitored by quantifying residual PBAT and PLA in the soils at five specific timepoints by Soxhlet extraction of the polymers from the soils combined with polymer quantification using proton nuclear magnetic resonance spectroscopy analysis (1H-NMR). The results show that the biodegradation of both PBAT and PLA is substantially affected by temperature, with a general trend of higher temperatures leading to increased biodegradation rates and extents. In the case of PLA, increasing temperature consistently increased biodegradation across all tested soils and BDMs. PBAT exhibited similar trends, except for one soil, in which the highest temperature (35°C) did not result in the highest PBAT biodegradation extents. The differences between PLA and PBAT likely reflect their distinct primary hydrolysis pathways — enzymatic hydrolysis for PBAT and abiotic hydrolysis for PLA — as well as differences in the presence and activity of polymer-specific microbial degraders between the soils. The results of modeling efforts will be presented that aim to further clarify the temperature effects on biodegradation rates and assess the extent to which these dynamics can be captured by temperature-reactivity relationships, such as the Arrhenius rate law. The results of this work will provide a basis towards predicting the effects of temperature on in situ field biodegradation rates, using laboratory incubations at temperatures of 20-28°C (as specified by the European Norm for BDMs (EN 17033:2018)) as a basis.
Quantifying Adaptation Measures for Thermal Stress in German Cities using the Microscale Urban Climate Model PALM-4U: Insights from the UrbanGreenEye Project
Authors: Salim Mohamed , Schubert Sebastian , Lehmler Sebastian , Stöckigt Benjamin , Frick Annett , Churkina Galina
Published: March 2024

The UrbanGreenEye project is a collaborative research initiative focusing on monitoring urban areas for climate change adaptation using remotely sensed indicators. The project addresses the critical need for comprehensive and accessible data to support sustainable urban development. In the context of climate change adaptation, the project recognizes the challenges faced by local civil services in obtaining timely and cost-effective information about urban structures. This study presents the crucial role of the microscale building-resolving urban climate mode PALM-4U in quantifying the effectiveness of vital indicators derived from Earth Observation, such as land surface temperature (LST), urban green volume, vegetation vitality, and imperviousness. For instance, the implementation of PALM-4U enables a detailed deficit analysis of urban green volume, allowing for the identification of areas experiencing thermal and hydrological stress. The model PALM-4U is used in validating greening scenarios, providing valuable insights for urban planners and decision-makers in formulating effective adaptation measures. Recognizing the inherent uncertainties in satellite-based calculations of indicators, the model PALM-4U investigates the impact of these uncertainties on the accuracy of PALM-4U simulations. By employing artificial intelligence algorithms, including Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models, the UrbanGreenEye project aims to enhance the reliability of satellite-derived data for improved urban climate modeling. Through collaboration with nine partner municipalities, this research contributes to bridging the gap between remote sensing capabilities and local authorities' needs. The outcomes of this study will facilitate the creation of a robust model for urban green volume deficiency, identifying hotspots for adaptation measures and supporting evidence-based urban planning strategies. Additionally, urban areas, influenced by the urban heat island effect, experience elevated surface and air temperatures due to factors such as increased solar absorption, lack of vegetation, and human activities. The model PALM-4U is used to explor the relationship between surface and air temperatures. Understanding this correlation is crucial for informing decisions by city planners and policymakers to mitigate the urban heat island effect. The insights gained also aid meteorologists in accurate temperature predictions for urban areas and contribute to scientific understanding of temperature dynamics, providing valuable perspectives on the potential impacts of climate change on future cities. Ultimately, the assessment of remotely sensed indicators using the model PALM-4U within the UrbanGreenEye project is considered a considerable step towards enhancing the resilience of urban areas to climate change.