bluuebunny/crossref_metadata_2025 huggingface dataset:
Downstream versus upstream propagation of fluvial erosion in orogenic plateaus: Example of the eastern Tibetan Plateau
Authors: Yuan Xiaoping , Jiao Ruohong , Liu-Zeng Jing , Dupont-Nivet Guillaume , Wolf Sebastian , Shen Xiaoming
Published: March 2024

Fluvial erosion of small mountain belts is widely represented as a wave of upstream migration of knickpoints, starting from a stationary boundary of a high topography created by increased rock uplift rates. However, mountain belts such as the Tibetan Plateau and the central Andes are large, and fluvial erosion remains poorly constrained when orogens expand in width with their boundaries continuously advancing towards the foreland. Here we propose a simple analytical solution for a laterally expanding orogen dominated by fluvial erosion, and apply it to the propagation of Eastern Tibet where the plateau margin is characterized by widespread low-relief surfaces incised by steep river valleys. Our analytical solution is based on the assumption that the topography of Eastern Tibet was built by high uplift rates located in a belt along the plateau margins migrating outwards during plateau growth, as well as carved by erosion of large rivers originating from the interior of the plateau. We validate our analytical solution by comparing it to numerical models and various types of data from five large rivers in Eastern Tibet (Salween, Mekong, Yangtze, Yalong, and Dadu Rivers). The results show that the models with optimized parameters are generally consistent with the observed river-profile morphologies, exhumation magnitudes, and low-temperature thermochronometric ages. We also tested whether the observations on topography and exhumation could also be explained by a period of headward erosion and plateau retreat, the consequence of an early formation of the Tibetan Plateau. By testing various fluvial erodibilities and model durations, we could not reproduce the observed topographies, river profiles, and exhumation magnitudes. The tested model also predicts an increase in thermochronometric ages from the center to the margin of the plateau, opposite to the observed trend of ages. Our results thus show that the long-term fluvial erosion in Eastern Tibet features mainly a downstream migration of high erosion rates, which is fundamentally different from the headward erosion of most of small mountain rivers and a major plateau margin retreat. The characteristics described by our simple analytical solution may represent a common pattern of outward growing mountains and plateaus in tectonically active regions on Earth.
Unleashing the power of Dask with a high-throughput Trust Region Reflectance solver for raster datacubes
Authors: Raml Bernhard , Quast Raphael , Schobben Martin , Reimer Christoph , Wagner Wolfgang
Published: March 2024

In remote sensing applications, the ability to efficiently fit models to vast amounts of observational data is vital for deriving high-quality data products, as well as accelerating research and development. Addressing this challenge, we developed a high-performance non-linear Trust Region Reflectance solver specialised for datacubes, by integrating Python's interoperability with C++ and Dask's distributed computing capabilities. Our solution achieves high throughput both locally and potentially on any Dask-compatible backend, such as EODC's Dask Gateway. The Dask framework takes care of chunking the datacube, and streaming each chunk efficiently to available workers where our specialised solver is applied. Introducing Dask for distributed computing enables our algorithm to run on different compatible backends. This approach not only broadens operational flexibility, but also allows us to focus on enhancing the algorithm's efficiency, free from concerns about concurrency. This enabled us to implement a highly efficient solver in C++, which is optimised to run on a single core, but still utilise all available resources effectively. For the heavy lifting, such as performing singular value decompositions and matrix operations we rely on Eigen, a powerful open-source C++ library specialized on linear algebra. To describe the spatial reference and other auxiliary data associated with our datacube, we employ the Xarray framework. Importantly, Xarray integrates seamlessly with Dask. Finally, to ensure robustness and extensibility of our framework, we applied state-of-the-art software engineering practices, including Continuous Integration and Test-Driven Development. In our work we demonstrate the significant performance gains achievable by effectively utilising available open-source frameworks, and adhering to best engineering practices. This is exemplified by our practical workflow demonstration to fit a soil moisture estimation model. 
Remote detection of Thermal Anomalies at Campi Flegrei caldera via Independent Component Analysis (ICA).
Authors: Mercogliano Francesco , Barone Andrea , D'Auria Luca , Castaldo Raffaele , Silvestri Malvina , Bellucci Sessa Eliana , Caputo Teresa , Stroppiana Daniela , Caliro Stefano , Tizzani Pietro
Published: March 2024

Thermal InfraRed (TIR) Remote Sensing is a well-consolidated approach to detect ground thermal anomalies for geological, environmental and urban scenarios. Specifically, several methodologies have been developed for the TIR imagery analysis to retrieve the Land Surface Temperature (LST) and describe the thermal state of the Earth’s surface. In volcanic frameworks, the analysis of LST time series represents a valid tool for a fast characterization of the shallow thermal field, supporting the surveillance networks in monitoring their status, specifically for the areas inaccessible because of the high volcanic hazard.Here, we propose a workflow to detect the thermal patterns in volcanic areas by analyzing time series of satellite TIR images using the Independent Component Analysis (ICA) technique. In particular, the first step of the workflow relies on the retrieval of LST time series from Landsat-8 (L8) TIR nighttime acquisitions, which have spatial and temporal resolutions equal to 100 m and 16 days, respectively, acceptable for our purposes. We selected the nighttime images because they allow us to reduce the exogenous effects, as well as those related to the solar radiation. Therefore, we estimate the LST parameter by considering the Radiative Transfer Equation (RTE) based on the use of a single thermal band, as long as having the surface emissivity and the atmospheric information about the investigated area. The second step of the considered workflow deals with the application of the ICA method to the retrieved LST time series to identify the statistically independent components (ICs) of the LST multivariate dataset.We verify the robustness of the proposed workflow by analyzing the volcanic site of Campi Flegrei caldera (Southern Italy), which represents a well-suitable case study for the occurrence of several endogenous and exogenous phenomena. We first achieved the 2013 – 2022 LST time series and subsequently analyzed the four components identified by the ICA. We compare these main thermal patterns with other available independent datasets, for example, the seismicity, the ground deformation field and the depth of the water table in the area, proving: (i) the existence of a positive thermal anomaly at the Solfatara crater with endogenous nature; (ii) the occurrence of exogenous processes at the Agnano plain; (iii) the existence of peculiar climatic pattern at the Astroni crater.In conclusion, we remark that the proposed methodology allows the identification of the nature of thermal anomalies, even for complex volcanic scenarios where several processes of different nature occur interfering with each other.
Global Modeling of Major Flood Events
Authors: Ikan Tal , Dror Gideon , Gerzi Rosenthal Adi , Mayo Rotem
Published: March 2024

Floods are one of the most common natural disasters, and the rate of flood related disasters has more than doubled since the year 2000. Accurate and timely warnings are critical for mitigating flood risks, especially for major events that can potentially impact thousands. For that, we develop a global early warning system for major flood events, using discharge predictions from the Global Hydrological Model developed by Google.
We use agglomerative clustering to cluster discharge predictions at Hydro-ATLAS sub-basins that exceed certain return period thresholds. These extended space and time clusters indicate potential flood events.  A supervised model is then employed to extract clusters associated with a higher risk of major flood events.
We use the Dartmouth Flood Observatory (DFO) and GDACS datasets of historical flood events as ground truth for training the classification model. We use various data sources to extract cluster features, such as estimate of affected population, prior event density at the cluster’s location, total drainage area associated with the cluster etc.
Our initial experiments show promising results, demonstrating the potential of a machine learning-based early warning system to accurately predict major flood events on a global scale, using global hydrological discharge predictions. While the results are encouraging, we believe that further refinement and validation of the model, coupled with efforts to improve the quality of ground truth data and further cluster features, could increase the accuracy of the system.
Quantification of the pre-eruptive CO2 budget of Neo-Tethyan magmas and their forcing on Early Cenozoic global climate
Authors: Ostorero Lea , Sternai Pietro , Esposito Rosario , Bouilhol Pierre , Müller Veleda , Malaspina Nadia , Tumiati Simone , Ballato Paolo , Zhang Zhiyong , Ji Wei-Qiang , Dai Jingen , Frezzotti Maria Luce
Published: March 2024

Magmatic CO2 emissions can affect the atmosphere composition, thereby driving long term global climate changes. Early Cenozoic climate trends are generally associated with changes in global silicate weathering related to the India-Asia convergence and collision, whereas changes in degassing from Neo-Tethyan magmatic arcs and their likely climatic effects are largely dismissed. Here, we characterize the petrography and measure the volatile content (e.g. CO2, H2O, F, Cl and S) of glassy, bubble-bearing and reheated melt inclusions within quartz, feldspar and pyroxene crystals from Early Cenozoic basalts, andesites and rhyolites from Ladakh (India), Tibet and Iran. Integrating our unprecedented measurements with modeling of the Neo-Tethyan geodynamics, we quantitatively assess the history of magmatic emissions from the Neo-Tethyan arcs and their contribution to Early Cenozoic climate changes. Assessing the Neo-Tethyan magmatic forcing of Early Cenozoic climate has major implications for our understanding of global volatile cycling on geological timescales.
Using Landsat composites to document temporal change within Amazonian forest vegetation
Authors: Gupta Rajit , Ruokolainen Kalle , Tuomisto Hanna
Published: March 2024

Deforestation of the Amazon rainforest biome has been of considerable international concern, as extensive forest loss has negative impacts on global carbon storage, hydrological cycles and biodiversity. Ongoing climatic change is predicted to make these effects worse, as climatic models suggest that increasing temperatures will often be accompanied by decreasing precipitation. Such change would put the continued existence of the rainforest biome at risk, as moisture-demanding species would be replaced by more drought-resistant ones. Field observations already indicate that even those Amazonian forests that are not directly affected by deforestation have started to change, and that they grow faster, store less carbon and contain more lianas than before. However, field measurements can only be carried out in a limited number of sites, and these only cover a minute part of the entire Amazon biome. To get a more complete understanding of the changes within the remaining Amazonian forests, we are carrying out broad-scale analyses using Landsat imagery. We first did pixel-based compositing using all image acquisitions within a 10-year time window in order to obtain a clean cloud-free reflectance surface. Two such composites were produced for different time periods (2000-2009 and 2013-2022) in order to identify potential changes across the forested landscape. The results are expected to identify areas where significant but non-obvious changes in the structure and/or function of the forest could be happening, and thereby to facilitate in assessing the degree of threat to the ecosystem
Seismic interferometry applied to microseismic monitoring networks in mountain areas
Authors: Barone Ilaria , Brovelli Alessandro , Cassiani Giorgio
Published: March 2024

Seismic interferometry using ambient seismic noise is a powerful technique to constrain shear-wave velocities at different scales. Microseismic monitoring is essential to ensure the safety of industrial operations, including hydrocarbon extraction, gas storage and geothermal production. Microseismic monitoring involves recording seismic vibrations continuously, in order to identify and locate local earthquakes. However, most of the recorded seismic signals is ambient noise, that could be used to infer the shear-wave velocities in the area, thus allowing a more accurate location of the seismic events.This study aims at applying seismic interferometry to ambient noise recorded by two small microsesimic monitoring networks in Switzerland, deployed around geothermal wells. The processing workflow for each station pair includes different steps as (1) cross-correlation of the raw seismic records, (2) analysis of the zero-crossings of the cross-spectra, (3) picking of the dispersion curve and (4) depth inversion. Due to the sparse nature of the seismic networks, surface wave tomography was not applied. Considerations on the topography effects, on the lateral variability of velocities and on the possible resonance effects due to the valley geometry will be done.
On the drought-flood conundrum: do droughts cause more or less flooding? Let’s discuss the science
Authors: Van Loon Anne ,   PerfectSTORM team
Published: March 2024

There seem to be two contrasting views on flooding after drought. Subsurface hydrologists pose that with dry antecedent conditions there is more storage available, which leads to lower flood peaks. Surface hydrologists pose that dry, hydrophobic soils support less infiltration and more surface runoff, which leads to higher flood peaks. But which theory is true? Or can both be true? And what happens if you put people and their actions in the mix? In this presentation is discuss the scientific and empirical evidence related to drought-flood events. I draw on scientific literature, global data analysis, a review of reports and news articles, qualitative case studies, and science communication examples. I will mostly focus on hydrological processes, but also highlight some meteorological and anthropogenic aspects.
Algal-bacteria raceway ponds for circular wastewater treatment
Authors: Biliani Styliani , Manariotis Ioannis
Published: March 2024

Raceway open systems are a highly promising, eco-friendly methodology for wastewater treatment. To assess how effectively nutrients and organic matter were removed from primary and secondary treated wastewater, two laboratory-scale open-raceway algal-bacteria ponds were used. The reactors were operated at organic loading rates (OLR) ranging from 29 to 95 and 9 to 38 g sCOD m3/d, for primary and secondary effluent, respectively. The hydraulic retention time (HRT) of both reactors dropped progressively from 5.5 to 2.2 d, and they thereafter ran at a HRT of 1.1 d. After 130 days, a high biomass concentration of around 2.2 g/ L was maintained with both substrates. Reactors were shown to be functional even at lower HRT levels by the quick removal of organic matter and nutrients. In less than 12 hours, the highly active biomass that was produced with both substrates resulted in the almost complete removal of organic matter and nutrients.With its exceptional settling capabilities, the algal-bacteria biomass may settle in less than ten minutes. The algal-bacteria content of biomass was 18.3 to 16.5% for lipids, 72.5 to 72.6% for proteins, and 2.6 to 3.2% for carbohydrates. The findings of the present work show that syntrophic algal-bacteria biomass is effective for the high-rate treatment of municipal wastewater. The low operational cost as well as the potential nutrient recovery and biomass valorization make the algal-bacteria process a circular-green model for wastewater management .
Effect of cloud feedbacks to CO2 level rise on the summer Arctic climate within the Eocene Deep-Time Model Intercomparison Project
Authors: Niezgodzki Igor , Knorr Gregor , Lunt Dan , Lohmann Gerrit
Published: March 2024

Warmer-than-today and ice-free early Eocene Arctic region serves as a testbed for possible future climate changes in the northern polar region dominated by increasing CO2 forcing and associated shrinking sea ice. It is essential for our understanding of recent climate changes to investigate short wave (SW) cloud effects on the SAT rise in the Arctic region in the high CO2 worlds as well as to separate the temperature changes in cloud-free from all-sky conditions in the same region. Here we present the first results of the boreal summer SW cloud feedbacks to atmospheric CO2 level rise from 1x to 3x pre-industrial level of 280 ppm across the ensemble of models participating in the Eocene Deep Time Model Intercomparison Project (DeepMIP). We use a relatively novel approximate partial radiative perturbation (APRP) method to decompose the cloud feedback into the contribution from changes in cloud fraction, absorption and scattering (including cloud albedo feedback) as well as to separate the radiative effects of cloud changes from surface albedo changes. Our first results show discrepancies between the models regarding the effects of clouds on surface air temperature changes. Most of the models show that the net effect of clouds has a relatively modest positive effect (warming) on surface temperature changes however one of the models shows a cooling effect. These differences are due to different effects of cloud fraction and scattering across the ensemble. Furthermore, all models show warming due to surface albedo changes and moderate warming due to atmospheric non-cloud effects. However, surface albedo changes show big discrepancies in magnitudes between the models that result from particularly big differences in the overcast conditions.
Barchan swarm dynamics simulated with a Two-Flank Agent-Based Model
Authors: Robson Dominic , Baas Andreas
Published: March 2024

Barchans are often found in swarms spanning hundreds of square kilometres and many tens of thousands of dunes.  The scale of such systems prohibits the use of computationally intensive models of the motion of sediment under fluid flow.  Instead, several agent-based models have been developed to study these vast systems.  Such models consider only idealised symmetric barchans subject to a perfectly unidirectional wind.  In contrast, barchans in nature are often subject to some seasonal variation in the wind direction and rare but strong storms events.  The wind variability as well as interactions between the bedforms means that a typical barchan in a swarm will not be perfectly symmetrical.  To resolve the discrepancy between the modelled and real-world dunes, we have developed a new agent-based model: the Two-Flank Agent-Based Model (TFABM) which can account for both barchan asymmetry and variation in the wind.  The model uses a simple algorithm for determining the outcome of collisions between dunes but which nevertheless is able to reproduce the majority of collisional phase-spaces observed in other studies.  The collision rule is controlled by a single model parameter which also controls the growth of asymmetry and the rate of calving of the simulated barchans. Using this model, we have simulated swarms spanning tens of square kilometres and containing thousands of dunes under both unimodal and bimodal winds in both cases generating swarms which have spatially homogeneous size-distributions, something which is observed for real-world swarms but had not been successfully reproduced in earlier agent-based models.  We also find that varying the wind direction changes the dune asymmetry distribution of swarms in a way that cannot be predicted from the asymmetry growth of isolated dunes subject to the same wind regime.  The range of values for the parameter which controls asymmetry and collisions under which we observe spatially homogeneous swarms also coincides with the range of values for which the width of the asymmetry distribution is similar to real-world swarms.  Furthermore, this range of values also matches with the range for which collisional phase-spaces have been successfully reproduced.  The coincidence that several phenomena are reproduced with the same small range of this parameter suggests that the process which it controls may be fundamental to the behaviour of barchans in nature.   
How can overshoot risks be included in long-term adaptation planning?
Authors: Theokritoff Emily , Yesil Burcu , Menke Inga , Saleh Khan Mariam , Gomes Marques Inês , Capela Lourenço Tiago , Pires Costa Hugo , Schleussner Carl-Friedrich
Published: March 2024

As climate change intensifies, it is essential to take a wide range of climate scenarios and their consequential impacts into account for adaptation planning. Overshoot scenarios, during which global warming will temporarily exceed the 1.5°C Paris Agreement target before it is brought down again in the following decades, are increasingly likely under current emissions trajectories. They would result in complex risks such as limits to adaptation and irreversible impacts and stress the need to prepare long-term adaptation plans under deep uncertainty.Here, we introduce the latest version of the Overshooting Proofing Methodology, a self-assessment tool designed to guide adaptation planners and policy-makers to integrate overshoot risks into planning processes, and present novel insights from its application with key stakeholders at city and regional levels. We also reflect on how adaptation pathways can allow to adequately plan a sequence of adaptation measures over time based on information collected through this tool. Its initial implementation in selected cities/regions reflects its applicability in varied climatic settings together with a range of climate related challenges. This work provides insights on key data gaps, capacity building needs and avenues for future adaptation planning, policy-making and research.
High fidelity modelling of iceberg capsize
Authors: De Pinho Dias Nicolas , Leroyer Alban , Mangeney Anne , Castelnau Olivier , Thiebot Jean-Baptiste
Published: March 2024

One of the major questions in climate science is to improve the accuracy of sea-level rise prediction, for which mass loss of the polar ice caps has a significant contribution. In this work, the focus is on buoyancy-dominated capsize of large icebergs. The capsizes generate specific seismic signals, which in turn can be analysed and used as a unique tool to study the long term evolution of such large icebergs capsize and the glacier response.To better quantify ice mass loss due to iceberg calving at marine terminating glaciers, coupling iceberg calving simulation and inversion of the seismic waves generated by these events and recorded at teleseismic distances is necessary. To achieve our task, a complex fluid/structure model of the iceberg capsize is required to obtain accurate forces history acting on the glacier terminus. The simulated forces can then be compared to the force inverted from the seismic signal. Therefore, based on our recent work, we implement a Computation Fluid Dynamics (CFD) approach to reach a high fidelity modelling of the iceberg capsize. First work using the experimental data of an iceberg capsize showed the need and ability of CFD computations to precisely reproduce the iceberg kinematics for different cases. We will present more advanced CFD configurations, including the contact between the capsizing iceberg and a rigid glacier front. Computation results are compared and validated against lab scale experiments, where we outline that some 3D effects cannot be neglected. We will also present full scale capsize simulations, in which the mixing of ocean layers occurs. In particular, we will quantify the transport of particles within the ocean to illustrate the potential change of nutriments distribution or of pressure experienced by local fauna due to iceberg calving.
Benefits and challenges of daily GRACE(-FO) satellite Data Assimilation (DA) for predicting fast-evolving hydrological processes.
Authors: Retegui-Schiettekatte Leire , Schumacher Maike , Forootan Ehsan
Published: March 2024

Terrestrial Water Storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE, 2002-2017) and its Follow-On mission (GRACE-FO, 2018-now) reflects a vertical summation of large-scale mass changes, globally. Better-than-monthly temporally resolved gravity solutions, such as daily GRACE(-FO) data, have the potential to reflect fast evolving hydrometeorological events. In the DansK-LSM project, supported by the Independent Research Fund Denmark (DFF), we will assess for the first time the benefits and challenges of daily GRACE(-FO) TWS Data Assimilation (DA) into a water-balance model (the modified 10 km resolution World-Wide Water Resources Assessment model, W3RA) for fast-evolving flood monitoring. Therefore, our particular interest is to assess to what extent a remotely sensed TWS data, which has a low spatial resolution, can help improving hydrological modelling during flood events. This experiment is performed within the region of the Ganges-Brahmaputra Delta for major floods occurred in 2004, 2007 and 2008. The daily DA is implemented in-house through a daily Ensemble Kalman Filter (EnKF) along with localization. When compared to the monthly solution, the daily TWS DA succeeds at transferring the High-Frequency (HF) GRACE TWS signal into the model (correlation coefficients of 0.97 between GRACE and daily DA TWS). However, the filter encounters some difficulties at accurately disaggregating the TWS into the different vertical water storage compartments (namely affecting the soil water) as well as horizontal grid cells. The observed irregularities are attributed to the very intensive use of ensemble statistics when the DA step is performed on the daily basis. To address this issue, a few possibilities for more stable filters and regularizations are explored and assessed. In this presentation, we will explore the spatial and temporal impacts of these choices.
Evolution of the plumbing system at Campi Flegrei caldera (Italy) during the 2007-2023 unrest
Authors: Trasatti Elisa , Astort Ana , Polcari Marco , Caricchi Luca , Di Vito Mauro A.
Published: March 2024

Campi Flegrei Caldera (Italy) is affected by a still ongoing unrest characterized by increasing seismicity rates, gas emissions and ground deformations. Multi-technique geodetic data (satellite, inland and seafloor GNSS measurements) are collected to understand the evolution of the unrest from its beginning in 2007 to the end of 2023, to get insights on the plumbing system. The data show increasing rates of deformation in the last 16 years, focusing in the caldera center. 3D finite element models are employed in a Bayesian inversion framework, including the elastic heterogeneous structure of the underlying medium based on the newest seismic tomography of the area. The analysis divides the whole period into seven distinct time intervals, based on the changes in ground displacement time series. The modeling approach implements a double-source plumbing system: a shallower source with its depth and geometry determined by the inversion framework, and a second deeper tabular source at 8 km depth, consistent with the petrological and geochemical evidence of melt and massive degassing from the deeper portion of the magmatic system. The results reveal that the shallower source beneath Pozzuoli exhibits a gradual decrease in depth, from 5.9 km during 2007-2010 to 3.9 km during 2015-2023. The shallower seismicity, above 3 km depth, is influenced by the long-term straining of the local crust due to the continuous inflation of the shallower source. Concurrently, the deeper tabular source at 8 km depth experiences a limited but constant deflation over time. The depicted plumbing system evidences a sequential growth of horizontal opening and volumetric expansion of the shallower source, likely fed by the deeper source for 16 years at least, for a total volume variation of about 60 million cubic meters. To determine whether the shallower source is fed by fluids and/or magma, we performed calculations of volatiles and/or magma transfer from 8 km upwards, considering different settings. The most plausible scenario accounts for magma ascent associated with degassing and outgassing. Indeed, the volumetric variation calculated from geodetic data for the shallower source reflects the injection of an equivalent volume of magma and a deep source that is continuously refilled by a flux of magma comparable to the ascending one.
Lessons learned from modelling flux ropes with EUHFORIA
Authors: Asvestari Eleanna
Published: March 2024

Due to their socioeconomic impact, the forecasting of coronal mass ejections (CMEs) is of paramount importance. This has led to decades of model development based on the knowledge we have gained from observations and our understanding of the physical processes that take place and could explain these observations. Currently we have empirical and magnetohydrodynamic (MHD) models that show promising results in CME forecasting. However, these are observationally driven and strongly dependent on the quality and quantity of observations we have at our disposal. The vast majority of our CME observations are made on the ecliptic plane. And in situ observations are collected by a few spacecraft scattered in the same plane. In the case of MHD models, we are also limited by numerical implementation issues and our understanding of the CME plasma and magnetic structure, as well as the physical processes CMEs undergo during their journey in the heliosphere.EUHFORIA (EUropean Heliospheric FORecasting Information Asset), is a state-of-the-art 3-dimensional MHD model that can simulate CMEs in the inner heliosphere, either as hydrodynamic pulses (cone model) or magnetised flux ropes (spheromak, FRiED-3D, torus). Throughout this presentation we will explore the observable parameters the CME implementations in EUHHFORIA depend on and how they are impacted by observational limitations. We will also discuss the performance of the spheromak CME and how we can track it with a novel tool. Last but not least, we will discuss the physical processes manifested in spheromak CME simulations and how they can shed light on the evolution of 3D flux ropes in the interplanetary space depending on the ambient medium (solar wind and interplanetary magnetic field) they are embedded in.
Radioactive contamination of a peripheral glacier in Southeast Greenland
Authors: Wojciechowski Kamil , Yde Jacob Clement , de Villiers Simon , Samolej Krzysztof , Bonczyk Michał , Łokas Edyta
Published: March 2024

Glaciers host complex and dynamic microbial ecosystems that are influenced by anthropogenic contaminants and can be regarded, not only as a considerable pollutant repositories, but also as secondary sources of pollutants. Contaminants such as heavy metals and fallout radionuclides are being brought to glaciers by long-range atmospheric transport and then deposited with wet and dry precipitation. Special attention has been given to cryoconite, debris found on glacier surfaces forming granule-shaped aggregates of minerals and organic matter. Cryoconite is known for its potential for exceptionally high accumulation of radioactive isotopes. Accumulated anthropogenic radionuclides, originating from atmospheric nuclear weapon tests and incidents, can be released back into the environment with sediment and meltwater fluxes and as a melt-out during glacier recession, posing a risk to downstream and proglacial ecosystem health. Many factors contribute to the secondary pollutant release, with climate change and glacier recession playing an increasingly important role in recent decades. Mittivakkat Gletsjer, a peripheral glacier located on Ammassalik Island in Southeast Greenland, shows significant volume and area losses, and although being one of Greenland’s most extensively explored glaciers, little is known about the radioactive pollution presence and its possible sources. This is true not only for Mittivakkat Gletsjer but for glaciers in Greenland in general. Cryoconite samples were collected from the glacier surface of Mittivakkat Gletsjer in August 2022 and activity concentrations of 238Pu, 239+240Pu, 241Am, 137Cs and 210Pb were measured (up to 1.44Bq/kg, 28.5Bq/kg, 14.4Bq/kg, 1100Bq/kg, 2900Bq/kg, respectively). Obtained values are higher than other environmental matrices (soils, mosses, lichens) indicating high radionuclide accumulation in cryoconite. Radioactive contamination sources were identified by determining the isotope ratios 238Pu/239+240Pu, 239+240Pu/137Cs and 241Am/239+240Pu (0.0514±0.0071, 0.0251±0.0044, 0.54±0.12). The results suggest that global fallout, an aftermath of atmospheric nuclear weapon tests, is likely the main source of radioactive pollution at Mittivakkat Gletsjer. A two-sources model (global fallout and Chernobyl incident) shows that global fallout is responsible for 92% of plutonium and 62% of cesium in the measured samples. High correlations (r2>0.75) between sample altitude and 238Pu, 239+240Pu, 241Am, 137Cs activity concentrations have been found. Samples collected from higher elevation accumulated more radionuclides, a relationship also observed at other glaciers. The same is not true for 210Pb for which a very weak correlation (r20.7) and weaker for 137Cs and 210Pb (r2
The Performance of the Man-Kendall Test in the Analysis of Coastal Changes along Cliff Sections on the Baltic Sea
Authors: Fuchs Michael , Tiepolt Lars , Schütze Karsten , Torizin Jewgenij
Published: March 2024

Airborne Light Detecting and Ranging (LiDAR) surveys became essential in tracking the evolving coastal landscapes of Mecklenburg-Vorpommern on the Baltic Sea for more than one decade, producing a data series of Digital Terrain Models (DTMs) crucial for estimating coastal erosion along the exposed cliffs. Although change detection based on differences between these DTMs is supposed to represent erosion and deposition accurately, a detailed analysis indicates that the initial and final DTMs in the data series sometimes fail to capture the full extent of changes due to various factors. So, natural phenomena, such as the movement of cliff materials (rolling, sliding, creeping), human activities aimed at coastal protection, and errors in DTM processing may disturb clear trends, introducing uncertainties and, in particular, making the data series appear alternating.To address these issues, we proposed to apply the robust Mann-Kendall test, a non-parametric statistical method used to identify trends in a data series without assuming any particular data distribution. It focuses on determining the direction and consistency of trends (ascending or descending), rather than the change’s magnitude. By implementing this approach, we can pinpoint areas that exhibit clear trends, thereby significantly improving the accuracy of coastal retreat estimations. In regions where trends are not readily apparent, it becomes crucial to investigate potential contributing factors thoroughly by exploring natural environmental dynamics, assessing the impact of human activities, and scrutinizing any errors in data processing. Such a comprehensive analysis ensures a more holistic understanding of the factors influencing these zones.We employed the proposed approach across four distinguished shore areas characterized by the distinct geological composition of the cliffs, delving into the trends of coastal retreat over the past ten years. As expected for areas with clear trends, the estimation of the dimensions of the recent coastal retreat was in good agreement with historically recorded data. Additionally, in areas exhibiting no discernible trends, we were able to identify the underlying reasons, shedding light on the intricacies of coastal dynamics.
Modeling local precipitation in Southern South America using Deep Learning: A sensitivity analysis on the choice of input features and loss function in the climate change signal
Authors: Bettolli Maria Laura , Baño-Medina Jorge , Olmo Matias , Balmaceda-Huarte Rocio
Published: March 2024

Southern South America (SSA) covers the extratropical part of South America (20–60°S) and presents a wide variety of climates. To the west of the Andes mountain range, annual precipitation increases southward from very dry conditions along the Atacama Desert in northern Chile to more than 3000 mm in the south. Conversely, east of the Andes, it increases from the Argentinian Patagonia in the south towards southeastern South America (southern Brazil, northeastern Argentina and Uruguay) where severe thunderstorm environments are typical. Global climate models project that the observed negative (positive) trends in precipitation over the subtropical central Andes (Southeastern South America) are expected to be more intense causing concern about water availability, ecosystems and socio-economic activities. However, the regional-to-local information that can be obtained by downscaling over GCMs outputs and needed for adaptation and mitigation policies, is still scarce over SSA. Unlike other parts of the world, limited studies analyzing the statistical downscaling (ESD) potential to simulate daily precipitation are available over the region and deep learning-based models have not been tested for downscaling daily precipitation over the region up to now.In this context, this work presents a comprehensive assessment of Convolutional Neural Networks (CNNs) to downscale daily precipitation at a continental-scale, building on the validation framework of the European project VALUE. To this end, we conduct a sensitivity analysis to the domain size as well as to the selection of the loss function on the modeling of precipitation in both present and future climates. Overall, the CNNs show skilful performance in modeling daily precipitation characteristics, including the extremes, over the different climatic regions of SSA. Nevertheless, we find the selection of the loss function to be a source of uncertainty over the arid regions of northern Chile and northwestern Argentina for both present and future climates by projecting different climate change signals. Regarding the domain size, the CNNs show to be effective in selecting informative predictors and their area of influence demonstrating their self-learning skill and their efficiency to be applied on a continental scale. These results encourage the construction of ensembles of deep learning models based on different loss functions in SSA to account for this type of uncertainty in the modeling of precipitation, especially in future climates.
Multiscale characterisation of varied risks for transportation infrastructures under climate change
Authors: Qiu Yangzi , Versini Pierre-Antoine , Mifsud-Couchaux Nathanaël , Tchiguirinskaia Ioulia
Published: March 2024

The infrastructures of Régie Autonome des Transports Parisiens (RATP) system are significant for the transportation of the Île-de-France region, providing essential social and economic services. In order to assess and mitigate the negative impact of climate change, this study aims to characterise the flood and heat wave risks of RATP infrastructures under climate change on multiple scales. Extreme flood events and heat wave events may result in the functional disruptions to the RATP infrastructures by interrupting circulation for more or less long periods. Therefore, a better understanding of the multi-scales risk (combining hazard, exposure and vulnerability indicators) of RATP infrastructures could enhance their resilience to climate change. With this respect, a multi-scale analysis of flood and heat wave risks of RATP infrastructures is presented by integrating the Universal Multifractal (UM) framework and analytic hierarchy process (AHP). The UM framework is a stochastic method that allows analysis of the natural hazards (extreme precipitation and temperature) and risks under three future climate scenarios (RCP2.6, RCP4.5, RCP8.5) across a range of scales. The AHP method is applied for quantifying the various risks by weighting hazard, exposure and vulnerability indicators based on experts’ knowledge. The results show that a certain number of RATP stations and lines are prone to flood and heat waves under climate change, especially in the RCP8.5 scenario. By undertaking the multiple scales of flood and heat wave risks of RATP infrastructures, this study seeks to contribute valuable insights that will inform strategic planning and resilience-building initiatives for RATP infrastructures under climate change (adaptation measures). It provides a theoretical basis for multiple risk assessments in other metropolitan areas worldwide.
From surface to subsurface: Investigating drought cascades and recovery patterns with (daily) satellite observations of soil moisture and terrestrial water storage
Authors: Blank Daniel , Eicker Annette , Güntner Andreas
Published: March 2024

Changes in soil water storage can be studied on a global scale using a variety of satellite observations. With active or passive microwave remote sensing, we can study the upper few centimeters of the soil, while satellite gravimetry allows us to detect changes in the entire column of terrestrial water storage (TWS). The combination of both types of data can provide valuable insight into hydrological dynamics in different soil depths towards a better understanding of changes in subsurface water storage.We use daily Gravity Recovery and Climate Experiment (GRACE) data and satellite soil moisture data to identify extreme hydroclimatic events, focusing on prolonged droughts. To enhance our comprehension of the subsurface, we utilize not just surface soil moisture data but also integrate information on root zone soil moisture. Original level-3 surface soil moisture data sets of SMAP and SMOS are compared to post-processed level-4 data products (both surface and root zone soil moisture) and a multi-satellite product provided by the ESA CCI.We analyse the correspondence between high and low percentiles in TWS and soil moisture time series, which allows us to identify extreme events in different integration depths and storage compartments. Furthermore, we compute the rate of change of anomalies to assess how quickly the system accumulates storage deficits during drought conditions and recovers from them for different soil depths. Our investigation focuses on the temporal dynamics of near-surface soil moisture and TWS, highlighting the cascading effects that propagate from the surface into the subsurface. The results we obtained indicate characteristic patterns of the temporal dynamics of drought recovery in varying soil depths. Specifically, our analysis shows that surface soil moisture recovers faster than TWS, and that this recovery process slows down as soil integration depth increases.
Revisiting the relation between ocean heat storage and thermal expansion from a water mass perspective
Authors: Waldman Robin , Meyssignac Benoît , Fourest Sébastien , Guillaume-Castel Robin , von Schuckmann Karina , Sallée Jean-Baptiste
Published: March 2024

The excess anthropogenic ocean heat is causing thermal expansion, which has driven approximately 40% of the industrial-era global mean sea level rise. This relation between ocean heat uptake H and thermosteric sea level rise hθ is mediated by the so-called expansion efficiency of heat (EEH=hθ/H, in m/YJ) which characterises the expansion of a water-mass under a unit increase of its enthalpy. The EEH of a water-mass depends on its temperature, salinity and pressure. At global scale the EEH has been characterized in both historical observations and climate simulations, but the the role of regional EEH and of individual water-mass layers in the formation of this global expansion efficiency remains undocumented. Here we propose a new approach where the EEH is decomposed in temperature coordinate into a temperature plus a pressure contribution to seawater thermal expansion. We show that the temperature contribution largely dominates the global signal. We also show that the global EEH can be interpreted as a weighted global average thermal expansion coefficient.We make use of the global EEH decomposition in temperature coordinate to estimate the contribution of individual water-mass layers to global thermal expansion in both historical reference observational datasets and Climate Model Intercomparison Project (CMIP5-6) historical and scenario simulations. Results show a contrasting picture of water mass contributions to global thermal expansion and sea level rise. Whereas ocean warming is distributed between mode, intermediate and deep waters, a disproportionate share of global ocean expansion occurs within tropical waters and subtropical mode waters. Regionally, tropical Pacific waters and subtropical north Atlantic mode waters appear as key contributors to global thermal expansion. These results show that the regional distribution of ocean heat uptake is a key driver of thermal expansion and sea level rise not only at regional scale but also at global scale. We also show that projections of future sea level rise at global scale critically depend on the ability of climate models to simulate both the regional water mass properties and their heat uptake.
Simultaneous trace gas flux monitoring of 10 greenhouse gases and air pollutants with a single instrument
Authors: Hundt Morten , Brunner Marco , Bruckhuisen Jonas , Aseev Oleg
Published: March 2024

Monitoring of trace and greenhouse gas fluxes is key to understand the interaction between atmosphere, plants, and soil and therefore to improving our understanding of the climate system in general.Complex flux systems, in environments where both biogenic and anthropogenic sources and sinks play a role, require measurement of many different inert and reactive trace gases and greenhouse gases simultaneously to obtain a complete budget.Until recently, however, the monitoring was usually limited to only a few gases per measurement device making the technique complex and expensive but providing only a limited picture. MIRO Analytical has developed a novel multicompound gas analyzer that can monitor up to 10 air pollutants (CO, NO, NO2, O3, SO2 and NH3), greenhouse gases (CO2, N2O, H2O and CH4) and other atmospheric trace gases such as (OCS, HONO, CH2O) simultaneously at ppb level.The eddy covariance (eddy flux) technique is often used to measure fluxes of trace gases but requires a high time resolution. Our compact instrument, combing several mid-infrared lasers (QCLs), offers 10 Hz sampling rate, outstanding precision, selectivity and accuracy and an automatic water vapor correction, which makes it ideal for eddy covariance flux measurements.In our contribution, we will introduce the measurement technique and will demonstrate application examples of this all-in-one atmospheric flux monitor. The system will be compared to alternative devices in parallel measurements and results of long-term observations and shorter campaigns will be presented.