bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantifying plastic contributions to different components of the river channel and floodplain
Authors: Schreyers Louise J. , van Emmerik Tim H.M. , Huthoff Fredrik , Collas Frank P.L. , Wegman Carolien , Vriend Paul , Boon Anouk , de Winter Winnie , Oswald Stephanie B. , Schoor Magriet M. , Wallerstein Nicholas , van der Ploeg Martine , Uijlenhoet Remko
Published: March 2024

Rivers are one of the main conduits that deliver plastic from land into the sea, and also act as reservoirs for plastic retention. Yet, our understanding of the extent of river exposure to plastic pollution remains limited. In particular, there has been no comprehensive quantification of the contributions from different river compartments, such as the surface, water column, riverbank and floodplain, to the overall river plastic transport and storage. Here, we provide an initial quantification of these contributions. First, we identified the main relevant transport processes for each river compartment considered. We then estimated the transport and storage terms, by harmonizing available observations on surface, suspended and floodplain plastic. This approach was applied to two river sections in the Netherlands, with a focus on macroplastics (≥ 2.5 cm). Our analysis revealed that for the studied river sections, suspended plastics account for over 96% of items transported within the river channel, while their relative contribution to mass transport was only 30-37% (depending on the river section considered). Surface plastics predominantly consisted of heavier items (mean mass: 7.1 g/#), whereas suspended plastics were dominated by lighter fragments (mean mass: 0.1 g/#). Additionally, the majority (98%) of plastic mass was stored within the floodplains, with the river channel accounting for only 2% of the total storage. Our study developed, and demonstrates, a harmonised approach for quantifying plastic transport and storage across different river compartments, providing a replicable methodology  which will be applicable to many different river environments. Our findings emphasize the importance of adopting a systematic monitoring approach, across the range of river compartments encountered, in order to achieve a coherent and  comprehensive understanding of riverine plastic pollution dynamics.
Analysis of trade-offs from the use of hydrogen blended with natural gas in the European Union
Authors: Brito Thiago , Höglund-Isaksson Lena , Rafaj Peter , Sander Robert , Klimont Zbigniew
Published: March 2024

Context: Increasing use of hydrogen (H2) across the economy is currently seen as an important strategy for decarbonization of fossil fuel-dependent sectors. Energy scenarios, especially those aiming at net-zero GHG emission targets, project that surplus electricity produced from renewable sources, such as solar and wind, will be converted and stored as H2 by electrolysis. The use of pure hydrogen would require the replacement or significant modification of some of the infrastructure (e.g. steel pipelines) and end-use appliances (e.g. combustion engines) by H2-dedicated equipment (e.g. PE/PVC pipelines, fuel cells); in fact, many sectors are already moving towards these solutions. However, hydrogen can also be blended into natural gas and used in the same applications. The combustion of such blends enables reduction of carbon intensity in several sectors without significant technological retrofits. However, hydrogen combustion under lean air conditions leads to higher thermal formation of nitrogen oxides (NOx), when compared to natural gas. The amount depends on the burner type, load and hydrogen blending ratio. While NOx emissions pose a direct risk to human health and act as a precursor to the O3 and particulate matter, deployment of H2 would also result in direct leakages to atmosphere and associated climate impacts.Objective: This study seeks to quantify and evaluate the potential NOx increases in the European Union (EU27) countries due to the combustion of hydrogen blended with natural gas.Methodology: We use GAINS model framework to conduct this analysis assuming that hydrogen combustion will mostly take place in the buildings, industry (boilers and furnaces) and power generation sectors. The exclusion of the transport sector is justified by the predominant use of hydrogen in fuel cell vehicles, which do not contribute to NOx formation. Since hydrogen blends will be used in the same devices as currently natural gas, existing abatement technologies as well as their adoption rates are kept across all sectors and regions.Expected Results: We expect the results of this study will allow us a better understanding of hydrogen impacts in terms of pollutant emissions. While the paper asserts that the findings are unlikely to influence the development or viability of future hydrogen economies in Europe, it acknowledges the importance of the analysis in revealing potential emissions trends and identifying local or country-specific trade-offs. The emphasis on existing regulations and emission control strategies in Europe provides context for the limited air quality impacts expected on the overall trajectory of hydrogen adoption. Moreover, these preliminary results could lead to relevant insights regarding expected H2 fugitive emissions which may impact climate mitigation targets and economical viability. 
A new low-cost GNSS instrument for monitoring of ground motions and critical infrastructures within the Greek “Supersite”
Authors: Ganas Athanassios , Mavropoulos George , Karamitros Ioannis , Nikolakopoulos Konstantinos , Charalampopoulou Vassiliki , Anastasiou Dimitrios , Athanassopoulos Theodoros , Kyriou Aggeliki , Tsironi Varvara
Published: March 2024

There is a continuous need for integrating multi-parameter instrumental observations and measurements with Satellite Earth observation data towards continuous monitoring of the environment and infrastructures. This task attains more importance within the tectonic and seismically active area of the Greek "Supersite" (Corinth Gulf, Ionian Islands, etc.). The significant level of geohazards in this region have made necessary the implementation of new technological approaches that could offer reliable augmentation to permanent networks (both geodetic and seismological). In this contribution, we demonstrate the design, construction and installation of a new technological infrastructure that is based on the collaboration of a multidisciplinary research team and on low-cost equipment. Our low-cost instrumentation includes a multi-GNSS dual-frequency chip (Ublox ZED F9P module) mounted on a Raspberry-Pi 4 compute module IO board together with an industry-standard MEMS accelerometer. It provides signal tracking for most of GNSS systems (GPS, GLONASS, Galileo and BeiDou). The GNSS data are collected 24/7/365, quality-checked and processed by use of open-source software. The combined-synergistic use of these new sensors is compatible with ground motion data provided by GNSS reference stations and accelerometers used by seismic agencies. Current work includes the collection, homogenization, processing and archiving of daily data from three test sites using 4G telemetry. The GNSS data support the on-going, pre-operational monitoring of three test sites together with InSAR Copernicus data (Tsironi et al. 2022). Tsironi, V., Ganas, A., Karamitros, I., Efstathiou, E., Koukouvelas, I., Sokos, E. 2022. Kinematics of Active Landslides in Achaia (Peloponnese, Greece) through InSAR Time Series Analysis and Relation to Rainfall Patterns. Remote Sens., 14(4), 844. https://doi.org/10.3390/rs14040844
Conversations on multi-hazard risk: Qualitative and quantitative insights from MYRIAD-EU interviews on the dynamics of risk drivers and disaster risk reduction synergies in Europe
Authors: van Maanen Nicole , de Ruiter Marleen , Jäger Wiebke , Casartelli Veronica , Daloz Anne Sophie , Geurts David , Hochrainer-Stigler Stefan , Ma Lin , Monteleone Letizia , Padron Noemi , Reiter Karina , Šakić Trogrlić Robert , Torresan Silvia , Tatman Sharon , Ward Philip ,   MYRIAD-EU
Published: March 2024

Navigating the complexities of multi-hazard risks poses a significant challenge, requiring a holistic understanding that extends beyond theoretical frameworks. Although recent frameworks have contributed greatly to theoretical advancements, a critical gap remains in providing practical insights for on-the-ground stakeholders. These stakeholders, including policymakers, decision-makers, and practitioners are often responsible for preparing and dealing with the risks arising from multi-hazard events. Within the MYRIAD-EU project, the objective is to empower stakeholders on the ground with a systemic approach encompassing multi-risk and multi-sector assessment and management. To unravel the intricate web of systemic risk interdependencies across and within Europe and facilitate an improved assessment and management of multi-hazard risks, several comprehensive semi-structured interviews were conducted within the Pilot regions of the MYRIAD-EU project. These interviews spanned diverse geographic, hazard, and sectoral domains. The Pilot regions are the Canary Islands, the Veneto region, the Danube region, Scandinavia, and the North Sea. The insights obtained from these interviews, both qualitative and quantitative, including perspectives from both land and sea, offer a nuanced understanding of hazard combinations, vulnerability characteristics, changes in exposure and vulnerability over time, and the synergies and asynergies inherent in disaster risk reduction measures across Europe. Our findings aim to bridge the gap between theoretical frameworks and practical applications, providing valuable information for stakeholders to enhance their preparedness and response strategies in the face of multi-hazard risks. At the same time, the results will be used to develop a better understanding about the dynamic vulnerability and exposure of multi-(hazard-)risk.
Widespread gas hydrate on Earth’s continental margins
Authors: Cook Ann , Naim Fawz , Majumdar Urmi , Portnov Alexey , Jones Benjamin , Heber Ryan
Published: March 2024

Over the last decade, our research team at Ohio State University has analyzed geophysical well logs in over 1000 petroleum industry wells for natural gas hydrate. This is the largest well log assessment for gas hydrate and includes a number of basins: the northern Gulf of Mexico, offshore Western Australia, the Norwegian Sea, the Barents Sea and the UK Atlantic Margin.We find evidence for gas hydrate in nearly half of industry wells, indicating that hydrate is widespread in sediments on Earth’s continental margins. Hydrate typically occurs in discrete, cm to m-scale intervals with depth and is at relatively low concentration (~35% saturation or less in a hydrate bearing layer). In addition, we observe that most of these hydrate bearing layers are not near the base of hydrate stability.  At most locations in our assessment, hydrate is not susceptible to current anthropogenic warming. However, our assessment lacks information about a crucial location on continental margins because this interval is not typical measured by industry well logs: the updip edge of hydrate stability. The updip edge of hydrate stability (~300-500 m water depth) is a critical, largely uncharacterized zone where ocean warming can affect hydrate stability. Scientific ocean drilling is required to characterize the global gas hydrate occurrence and modern seafloor carbon flux along this sensitive boundary. 
New insights into seasonal to interannual salinity variability on the Northeast U.S. continental shelf and slope
Authors: Ryan Svenja , Ummenhofer Caroline C. , Gawarkiewicz Glen G.
Published: March 2024

The Northeast U.S. continental shelf is a highly productive and economically important region that has experienced robust changes in upper-ocean properties in recent decades. Warming rates exceed the global and North Atlantic average and in particular several episodes of anomalously warm temperatures, so called marine heatwaves, have had devastating impacts on regional fisheries over the past decade. There are also indicators of a salinification of the region, which might be linked to large-scale changes in the North Atlantic circulation as well as changes in regional processes, such as the number of Warm Core Rings shedding of the Gulf Stream, driving an increased salinity flux into the continental slope and shelf region. With now more than a decade of remote-sensing sea surface salinity data, we revisit seasonal to interannual salinity variability and assess the role of salinity for modulating stratification on the continental shelf. We provide important regional context for the interpretation of data from the OOI Coastal Pioneer array, a local shelf-break observatory. We find that the local seasonal cycle is an interplay of seasonal freshwater input via local river discharge, driving decreasing salinities in spring and summer not just on the shelf but also in the Slope Sea. An observed salinification in the fall is likely linked to offshore forcing over the slope associated with the presence of Warm Core Rings. A coherent low-frequency salinity variability is found over the slope and shelf region in the Mid-Atlantic Bight (MAB) and Gulf of Maine, highlighting that shelf conditions in particular in the MAB are not solely dominated by upstream shelf conditions but are significantly impacted by local offshore variability. Furthermore, we synthesise hydrographic data from the NOAA ECOsystem MONitoring (ECOMON) program to construct mean cross-shelf sections along the MAB to investigate the relative contributions of thermal and haline components to the seasonal stratification. Overall, salinity serves as a valuable tracer, in addition to temperature, of these multi-variate processes and with now more than a decade of satellite surface salinity can shed new light on the spatio-temporal variability on the Northeast U.S. continental shelf. 
Possible contamination of Ukraine and neighboring countries by Cs-137 due to a hypothetical accident at the Zaporizhzhia NPP as a consequence of the Russian aggression
Authors: Balabukh Vira , Skrynyk Oleg , Bubin Sergiy , Laptev Gennadiy
Published: March 2024

The Zaporizhzhia nuclear power plant (ZNPP) has been occupied by Russian aggressors since March 4, 2022. Its proximity to the combat zone results in a real risk of an accident with radioactivity emissions. There have been a number of blackouts at ZNPP (the most recent one was reported on December 2, 2023, lasting for approximately 5 hours), which could potentially lead to an accident with a scenario similar to that of the 2011 Fukushima Daiichi NPP disaster. The objective of this research is to assess possible contamination of the territory of Ukraine and neighboring countries by Cs-137, emitted in a hypothetical accident at ZNPP, depending on weather patterns usually observed over the domain. The assessment is based on numerical simulations of atmospheric transport, dispersion and deposition processes.In order to obtain an input meteorology for the dispersion/deposition simulations, we chose 37 typical weather patterns out of 153 that were objectively identified in the domain during 2018-2020. Our selection aimed to keep seasonal and frequency distribution of the patterns in the sampled population. Generally, the selected patterns included 22 cyclonic, 12 anticyclonic, and 3 situations of western transport. Their mean duration was approximately 6 days. 3D meteorological data for the selected weather patterns were generated by means of the WRF v4.3 meteorological model based on ERA5 reanalysis data.The source term parameterization was based on freely available information published in scientific papers, reports etc. Several Cs-137 emission scenarios were considered by varying an emitted fraction of the total core inventory (50% and 3.43%) and a period of time when the source was active (24, 32, and 40 hours). The dispersion/deposition calculations were performed with the CALPUFF v6 and HYSPLIT v5.2.3 atmospheric dispersion models. Using these two models, which implement different computation algorithms, allowed us to perform the verification of the computed results.Our calculations showed that a hypothetical accident with the most conservative emission scenario (emitted 50% of the total core inventory) could lead to significant contamination of not only the territory of Ukraine but also neighboring countries. Generally, depending on the weather pattern, from 10 to 80% of the emitted Cs-137 could be deposited on the territory of Ukraine. The reduction of the total emission obviously leads to decreased absolute values of the contamination, however the fractions of deposited in Ukraine Cs-137 stay unchanged for each weather pattern. The work is supported by the grant program University for Ukraine (U4U) and The Yale School of the Environment. Oleg Skrynyk also acknowledges the support from the MSCA4Ukraine fellowship program, which is funded by the European Union.
Multiparametric exploration of active magma degassing at Mt. Etna in 2023
Authors: Biensan Clothilde , Taddeucci Jacopo , Ricci Tullio , Del Bello Elisabetta , Scarlato Piergiorgio , Palladino Danilo
Published: March 2024

Active magma degassing is the release of slightly over-pressurized gas pockets from volcanic vents. This activity can shed light on the geometry of the shallow plumbing system of volcanoes and its internal dynamics. During a summer 2023 field campaign, we conducted comprehensive recordings, including thermal infrared, high-speed, and high-resolution video, as well as broadband microphone signals, capturing ten consecutive days of active degassing events at the Bocca Nuova crater of Mt. Etna. Two distinct vents exhibited notable degassing activity. The first, henceforth referred to as 'Sboffer,' was a crater characterized by the emission of loud, low-frequency sounds accompanying each degassing event (hence the name). The second vent, smaller than the first one and designated as 'Ringer,' took the form of a circular pit on the Bocca Nuova crater floor, emitting volcanic vortex rings—reminiscent of smoke rings (hence the name)—during events. We focused our analysis on the thermal data, characterizing emissions from both vents by examining brightness temperature anomalies along horizontal measurement lines in the thermal video recordings. Both vents exhibited a bimodal distribution in the intensity and duration of events. Specifically, Sboffer produced larger events with a mean amplitude of 100-160°C and a recurrence time of approximately 500 seconds, along with smaller events with amplitudes of 20-24°C occurring every 200-400 seconds. Ringer, on the other hand, featured larger events with amplitudes of 70-100°C and smaller events with amplitudes of 20-23°C, occurring at much higher frequencies of every 4 and 1.5 seconds, respectively. The maximum temperature recorded during the larger events reached nearly 600°C for Ringer and 500°C for Sboffer. The exit velocities for large events were measured at 15 m/s for Sboffer and 10 m/s for Ringer. Remarkably, all parameters at both vents remained consistently stable throughout the ten-day observation period. Preliminary investigations were conducted to explore potential correlations between the acoustic signal and thermal data. The aim was to ascertain the depth of the explosive events and examine potential correlations with temperature variations and the intensity of the explosions.
New concepts on quantifying event data
Authors: Marwan Norbert , Braun Tobias
Published: March 2024

A wide range of geoprocesses manifest as observable events in a variety of contexts, including shifts in palaeoclimate regimes, evolutionary milestones, tectonic activities, and more. Many prominent research questions, such as synchronisation analysis or power spectrum estimation of discrete data, pose considerable challenges to linear tools. We present recent advances using a specific similarity measure for discrete data and the method of recurrence plots for different applications in the field of highly discrete event data. We illustrate their potential for palaeoclimate studies, particularly in detecting synchronisation between signals of discrete extreme events and continuous signals, estimating power spectra of spiky signals, and analysing data with irregular sampling.
Machine learning-based emulation of a km-scale UK climate model
Authors: Addison Henry , Kendon Elizabeth , Ravuri Suman , Aitchison Laurence , Watson Peter
Published: March 2024

High resolution projections are useful for planning climate change adaptation [1] but are expensive to produce using physical simulations. We make use of a state-of-the-art generative machine learning (ML) method, a diffusion model [2], to predict variables from a km-scale model over England and Wales. This is trained to emulate daily mean output from the Met Office 2.2km UK convection-permitting model (CPM) [3], averaged to 8.8km scale for initial testing, given coarse-scale (60km) weather states from the Met Office HadGEM3 general circulation model. This achieves downscaling at much lower computational cost than is required to run the CPM and when trained to predict precipitation the emulator produces samples with realistic spatial structure [4, 5]. We show the emulator learns to represent climate change over the 21st century. We present some diagnostics indicating that there is skill for extreme events with ~100 year return periods, as is necessary to inform decision-making. This is made possible by training the model on ~500 years of CPM data (48 years from each of 12 ensemble members). We also show the method can be useful in scenarios with limited high-resolution data. The method is stochastic and we find that it produces a well-calibrated spread of high resolution precipitation samples for given large-scale conditions, which is highly important for correctly representing extreme events.Furthermore, we are extending this method to generate coherent multivariate samples including other impact-relevant variables (e.g. 2m temperature, 2m humidity and 10m wind). We will show the model’s performance at producing samples with coherent structure across all the different variables and its ability to represent extremes in multivariate climate impact indices.References[1] Kendon, E. J. et al. (2021). Update to the UKCP Local (2.2km) projections. Science report, Met Office Hadley Centre, Exeter, UK. [Online]. Available: https://www.metoffice.gov.uk/pub/data/weather/uk/ukcp18/science-reports/ukcp18_local_update_report_2021.pdf[2] Song, Y. et al. (2021). Score-Based Generative Modeling through Stochastic Differential Equations. ICLR.[3] Kendon EJ, E Fischer, CJ Short (2023) Variability conceals emerging trend in 100yr projections of UK local hourly rainfall extremes, Nature Comms, doi: 10.1038/s41467-023-36499-9[4] Addison, Henry, Elizabeth Kendon, Suman Ravuri, Laurence Aitchison, and Peter AG Watson. (2022). Machine learning emulation of a local-scale UK climate model. arXiv preprint arXiv:2211.16116.[5] Addison, H., Kendon, E., Ravuri, S., Aitchison, L., and Watson, P. (2023). Downscaling with a machine learning-based emulator of a local-scale UK climate model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14253, https://doi.org/10.5194/egusphere-egu23-14253
Catastrophic (CAT) Bond as Sustainable Finance Instruments: Understanding from Cross-Country Perspectives
Authors: Suresh Nandini , Mishra Trupti , Parthasarathy Devanathan
Published: March 2024

Disasters have significant environmental, human, social, economic, and financial impacts. These effects are potentially long-lasting and have multi-generational consequences. Due to climate change, disasters have cascading and compound effects, heightening the financial risks. However, the number of countries issuing CAT Bonds as a financial instrument for tackling the financial burden of disasters is less than 5% as of 2023. This study explores the need to use CAT Bonds as a risk transfer mechanism that allows governments and insurers to spread their climate change risk across capital markets. It presents a comprehensive cross-country level analysis of the potential drivers that influence the CAT bond issuance at a sovereign level for 131 countries from 2016 to 2021 to understand their significance for issuers and non-issuers of CAT Bonds. These potential drivers were filtered after an exploratory factor analysis. Nonetheless, the imbalance between the number of issuers and non-issuers has resulted in poor classification accuracy results and bias. Hence, this study employs Logistic Regression with Synthetic Minority Over-sampling Technique (SMOTE) and without SMOTE. Further, a comparison study between the effective CAT Bond issuance in the Philippines against non-issuance in India was conducted to determine the obstacles in the Indian setting. The result from the study indicates that a country’s exposure to hazards, population growth, investment freedom, regulatory quality, gross budget balance, stock traded and rule of law have statistically significant impact on the issue of CAT Bond. Highlighting the Indian context, the major challenges the country faces in issuing CAT Bonds are its stringent rule of law, regulatory inferiority, economic uncertainty, and less stock traded.
Analyzing the Dynamics of Multiple ISW Emissions in the Strait of Gibraltar
Authors: Roustan Jean-Baptiste , Bordois Lucie , Dumas Franck , Auclair Francis , Carton Xavier
Published: March 2024

Internal solitary waves with large amplitude have long been observed in the Strait of Gibraltar (SoG). Beautiful satellite images depict the ISW observed at the entrance of the Alboran Sea, generated by the interaction between tides and the topography at Camarinal Sill, the most important topographic obstacle in the Strait. As the tidal current heads west, it becomes supercritical over the sill, leading to the development of an internal hydraulic jump. When the current weakens, the flow reverts to subcritical,  the internal hydraulic jump is released, leading to the eastward propagation of an internal bore. This bore progressively transforms into an ISW train due to non-hydrostatic dispersion and non-linear effects. While the main mechanism of generation is now well understood, there are still open questions about the intricate dynamics of these nonlinear internal waves and their evolution along the Strait. Previous studies show an important variability in the shape, intensity and arrival time of this internal solitary train.  Recent field experiments have revealed a complex network of local hydraulic jumps forming near Camarinal Sill. From the same dataset, the potential generation of not just one but two ISW trains has been addressed.  Then, we have investigated the implication on the evolution of these trains during their journey in the Strait of Gibraltar.  Our mooring data reveal the presence of two trains of ISWs with slightly different north-south fronts east of Camarinal Sill. We propose hypotheses to explain the tilting of the fronts based on differential mixing and meridional tidal variability . Moreover, these findings prompt us to reconsider our understanding of the physics responsible for the observation of non-rank ordered ISW trains in the eastern part of the strait. To deeply investigate the consequences of nonlinear wave-wave interaction in the disorganization of the train, we implemented a simplified 3D non-hydrostatic configuration. 
Quantitative characterization of orogenic evolution within the Wilcon cycle
Authors: Wang Tao , Zhang Jianjun , Huang He , Wang Chaoyang , Ding Yi
Published: March 2024

Orogens are mostly composite and experience multiple stages of the orogenic processes, such as the accretion of relatively small terranes (or soft collision) and continental collision, and these orogens are commonly called composite orogens, Thus, orogens vary in their nature and style, defining a broad spectrum of types that encompass the Wilson Cycle. From the point of view of the Wilson Cycle, orogens begin as accretionary and evolve into collisional, culminating in the termination phase during supercontinent amalgamation. Thus, each orogen may be viewed as having reached a certain stage of its evolution path in the Wilson Cycle. Moreover, active accretionary orogens will continue to evolve; for instance, the active accretionary orogenic systems around the margins of the Pacific Ocean, such as the North and South American Cordillera, may evolve or be reformed into collisional or even intracratonic orogens if the Pacific Ocean closes in the future. Based on this expected orogenic evolution, we use the decrease in the juvenile crustal areal proportions to semi-quantitatively trace the orogenic stages. Our research, part of the IGCP-662 project, "Orogenic Architecture and Crustal Growth from Accretion to Collision," investigates these orogen progresses, and characterization of orogens through comparative studies on the lithospheric architecture and crustal growth patterns of Phanerozoic orogens. A global igneous rock database, in collaboration with the Deep-time Digital Earth (DDE), provides the foundation for our analyses. The juvenile crustal areal proportions can be determined Quantitatively through isotopic mapping (Wang et al., 2023). This innovative approach enhances our understanding of orogenic processes, shedding light on the intricate relationships between orogenesis and continental growth within the framework of the Wilson Cycle.
Coupling water quality and quantity models to integrate climate risk to reservoir water quality into water planning
Authors: Onen Mustafa Onur , Rougé Charles , Douterelo Soler Isabel , Darch Geoff
Published: March 2024

Ensuring public access to clean water faces unprecedented challenges. The rising frequency and intensity of hot-dry conditions, coupled with population growth, strain water stocks. Concurrently, the presence of excess phosphorus and nitrogen in freshwater lakes and reservoirs leads to harmful algal blooms (HAB) precisely when hot-dry conditions occur, impacting aquatic life and complicating water treatment for human consumption. Due to uncertainties in future climate, water demands, nutrient discharge, and ecological factors, determination of HAB risk is a complex task. This hard-to-quantify risk impacts water planning since it is unknown whether reservoir water will be usable in the hot, dry summers when it is most needed.Water planning increasingly involves fast water resource simulators. These tools evaluate the performance of adaptive infrastructure investments within complex water resource systems under changes in supply-demand conditions. Relying on water balance calculations, these fast models prioritise water quantity targets and typically neglect water quality. This overlooks water quality impacts on resource availability. Conversely, advancements in aquatic ecosystem modelling have produced complex water quality simulators, incorporating numerous space and time variant equations for hydrodynamics, biogeochemical and ecological processes, and particularly addressing HABs. These processes are much more complex than water balance dynamics, leading to models with much slower run-times than water resource simulators. In addition, to account for water quality in the design of operating strategies, we need two-way coupling of these models to communicate the simulated water quality and quantity states with each other frequently throughout simulations.To achieve this two-way coupling, we integrated a high-performing lake model, the General Lake Model (GLM), into a recently developed water resource simulator called Pywr. Thanks to its 1D resolution of physical processes, GLM operates at speeds comparable to Pywr, and this work is, to our knowledge, the first to apply it to water planning. Enhanced communication between the models is facilitated by Pywr's extended parameters, allowing the execution of customised tasks at each timestep. Furthermore, Pywr's advanced scenario handling capability renders the coupled framework ideal for risk assessment. Coupled models are pivotal for designing operating strategies aimed at minimising HAB risk under diverse future conditions (climate, water demands and nutrient transport). Successful implementation will shed light on the feasibility of constructing new reservoirs, evaluating their susceptibility to algal blooms, and informing billion-pound investment decisions.
Projected amplification of rainfall extremes due to warming-induced reduction of snow fraction: an assessment based on convection-permitting simulations
Authors: Vohnicky Petr , Dallan Eleonora , Marra Francesco , Fosser Giorgia , Pesce Matteo , Borga Marco
Published: March 2024

In mountainous regions, temperature determines the state of precipitation (liquid or solid) and in turn significantly affects runoff formation and flood generation. Projected temperature increase due to global warming may therefore affect the rainfall/precipitation ratio during heavy storms, hence intensifying the flood regime. This study aims to assess the projected variations in liquid/solid fraction of precipitation during heavy precipitation events in the upper Adige River, Italy (Eastern Italian Alps). The study utilizes simulations from an ensemble of convection-permitting climate models (CPM), which are suitable to the task given their ability to explicitly represent deep convection and to resolve the mountainous topography. The CPM data provided by the CORDEX-FPS Convection project at 1-hour temporal and remapped to 3 km spatial resolution, cover historical and far-future (2090-2099) time periods under the extreme climate change scenario (RCP8.5). Observational data from the densely instrumented river system are utilized for bias evaluation. Lastly, the Simplified Metastatistical Extreme Value (SMEV) approach, known for the reduced uncertainty compared to conventional approaches, is incorporated for frequency analysis. This method proves particularly useful for analyzing extremes from short time periods, such as those in CPM simulations. The projected changes in both sub-daily mean areal precipitation and liquid rainfall return levels are examined at various spatial scales based on the sub-basins total area. Our preliminary results underscore the significance of leveraging advanced statistical techniques and high-resolution climate models to address emerging challenges in hydrology and climate science. The climate-induced shifts in return period of liquid precipitation identified in this study are expected to have implications for both water resources management and adaptation measures.
Satellite gravity validation by new airborne gravimetry in coastal regions of Antarctica and Norway
Authors: Dale Bjørnar , Bjerregaard Simonsen Sebastian , Christian Dahl Omang Ove , Enzlberger Jensen Tim , Forsberg René
Published: March 2024

Airborne gravimetry provides gravity observations of higher spatial resolution than what can be obtained from satellite gravity field measurements, and together with terrestrial measurements they augment the satellite observations to determine high-resolution geoid models. Satellite altimetry in coastal and ice-covered regions is known to have significant errors. We use modern strapdown gravimetry for the surveys and compare the indirect method, using Kalman filtering, and the direct filtering method for the processing. We present the result of strapdown gravimetry for two airborne campaigns conducted in Antarctica 2022 and Norway 2023. During both campaigns the sensors used were an iMAR navigation-grade inertial measurement unit together with a geodetic GNSS receiver.The 2022 campaign covered part of the sea-ice covered Weddell Sea and was surveyed as a piggyback activity as part of the ESA CRYO2ICE and NERC DEFIANT 2022 Antractica campaign. The 2023 airborne campaign was carried out in the coastal region of Norway near Trondheim. In both areas the data were compared to satellite altimetry and other gravity data from ship or airborne surveys. Both campaigns show improvements in spatial resolution and accuracy of the new mGal-level airborne gravimetry data when compared to satellite altimetry and older marine gravity observations.
Enhancing mountainous permafrost mapping by leveraging rock glacier inventory
Authors: Feng Min , Yan Dezhao , Hu Zhongyi , Xu Jinhao
Published: March 2024

Permafrost is a key component of the cryosphere, which plays significant roles in surface energy, hydrological, and biogeochemical processes. Moreover, permafrost, a sensitive indicator of climate change, has experienced widespread degradation in recent decades. The Tibetan Plateau, hosting the largest mid-low latitude permafrost area, is particularly susceptible to these changes, warranting a deeper understanding of permafrost distribution and environmental interactions. However, permafrost mapping traditionally relies on empirical and physical models, each with its set of advantages and drawbacks. Empirical models, while user-friendly, introduce uncertainties due to data quality and scale issues. On the other hand, physical models, offering precision, demand high-quality data and face challenges in extensive simulations over large areas. With the advancement of artificial intelligence technologies, machine learning has rapidly formed many implementation algorithms and been applied in different fields. Permafrost mapping has been investigated with a variety of machine learning algorithms (i.e., neural networks, support vector machines, random forest, and gradient boosting), and demonstrated superior accuracy over traditional methods when applied to large areas, especially when there are abundant training data available.Despite these advancements, challenges persist, notably in mountainous areas characterized by scarce in situ data and complex topography. This study proposes a novel approach involving rock glaciers as valuable indicators for permafrost mapping. Intact and relict rock glaciers, representing the presence or absence of permafrost, offer crucial insights, particularly in mountainous regions where traditional methods fall short. The study focuses on the Qilian Mountains, a representative mountainous area on the Tibetan Plateau. Leveraging machine learning and rock glaciers, the research aims to simulate the Permafrost Zonation Index (PZI). Rigorous accuracy evaluations and comparisons with existing permafrost maps are conducted, promising a nuanced understanding of permafrost dynamics in this challenging terrain. The integration of technological advancements and innovative approaches holds the potential not only to advance permafrost research but also to inform conservation strategies and climate change assessments on a broader scale.
Analysing airborne CO2 flux measurements in relation to spatiotemporal characteristics of drained fen meadows in the Netherlands with machine learning
Authors: van der Poel Laura , Franssen Wietse , Bataille Laurent , Hutjes Ronald , Kruijt Bart
Published: March 2024

Worldwide, peatlands have been transformed from carbon sinks to carbon sources due to years of intensive agriculture and livestock farming, requiring low water tables. In the Netherlands, emissions from drained organic soils mount up to around 3% of all national greenhouse gas emissions, and account for 4.6 to 7 Mt CO2 annually. As part of the 2019 national climate agreement, the Dutch government set a specific mitigation target for these emissions of 1 Mt per year by 2030. In light of this target, the Netherlands Research Progamme on Greenhouse gas dynamics in Peatlands and organic soils (Dutch: NOBV) investigates the efficiency of proposed mitigation measures, and aims to contribute valuable scientific findings to the politically and socially sensitive debate around this issue. The focus of our study aligns with the NOBV's objective to enhance the understanding and quantification of drivers of regional emissions.To research regional fluxes, NOBV incorporates a new approach: Eddy Covariance (EC) measurements are taken from a low-flying ultra-light aircraft. Fluxes of CO­2, momentum, sensible and latent heat are measured, as well as meteorological variables. Weather permitting, the airborne surveys are done twice a week since 2020, over the three main fen meadow areas in the Netherlands. The crosswind, parallel flight tracks ensure that the footprints overlap, thus cover the full area. Additionally to the airborne data collection, a large EC tower network has been established with both stationary and mobile systems, encompassing 25 measurement sites.In this study, we combine airborne and tower flux data, to make use of their different strengths: spatial heterogeneity and temporal continuity, respectively. We use footprint analysis to extract the corresponding spatial information from maps, remote sensing, and a daily soil-water information product. Using this data, we train a boosted regression tree (BRT) machine learning algorithm. Feature selection and hyperparameter tuning are applied as model optimization techniques, and subsequently Shapley values and various simulations are used to interpret the model’s outputs.Related to the public debate and other studies on emissions from organic soils, we specifically investigate the influence of water table dynamics. A first analysis shows that during nighttime and at high incoming photosynthetically active radiation, every 10 centimeters lowering of efficient water table depth leads to 3.7 tonnes CO2 ha-1 yr-1, which corresponds to current estimates. We will present these, and further results, showing what and how determines the CO2 fluxes from drained fen meadows in the Netherlands.
Quantifying Uncertainty in Lagrangian Transport for Assessing Environmental Problems
Authors: Mancho Ana M.
Published: March 2024

In this presentation, I will describe a maritime oil spill case that affected the Eastern Mediterranean and several Middle Eastern countries' shorelines in early 2021 [1]. The sequence of events was successfully reconstructed, supported by remote sensing images and Lagrangian Coherent Structures. The comparison of the performance of various datasets found connections between Lagrangian Coherent Structures and Uncertainty Quantification [2].AcknowledgmentsSupport from PIE project Ref. 202250E001 funded by CSIC, from grant PID2021-123348OB-I00 funded by MCIN/ AEI /10.13039/501100011033/ and by FEDER A way for making Europe.References[1] G. García-Sánchez, A. M. Mancho, A. G. Ramos, J. Coca, S. Wiggins. Structured pathways in the turbulence organizing recent oil spill events in the Eastern Mediterranean.   Scientific Reports 12, 3662 (2022).[2] G. Garcia-Sanchez, A.M. Mancho, M. Agaoglou, S. Wiggins. New links between invariant dynamical structures and uncertainty quantification. Physica D 453, 133826 (2023).
Desert Sensing – Characterizing recent surface dynamics in arid regions through high-performance data analytics of multi-sensor Earth Observation archives and in situ records
Authors: Arisoy Baturalp , Ullmann Tobias , Stauch Georg
Published: March 2024

Climate change continues to impact diverse ecosystems. Drylands stand out as particularly vulnerable environments, as they are highly responsive to key indicators of change. The sensitivity and response time of these regions remain largely unknown, underscoring the need for a deeper understanding of their systems.Arid regions are considered optimal for Earth Observation based research, primarily due to factors such as minimal anthropogenic disturbance, sparse vegetation cover, and low cloud coverage. These attributes make drylands advantageous for studying and monitoring the impact of climate change, providing valuable insights into these vulnerable ecosystems.Southern Mongolia stands out as an especially well-suited study area to test novel approaches and to detect land surface changes over both space and time. The basin of Orog Nuur was selected in this study to observe long-term environmental changes, building on significant prior studies conducted around the drainage basin.Our approach emphasizes the utilization of state-of-the-art earth observation technology to unveil the dynamics of desert ecosystems. This involves cloud-based processing, such as Google Earth Engine and the German High Performance Data Analytics (HPDA) platform “terrabyte”. Throughout the project, we will apply various multispectral and active SAR techniques spanning 50 years to monitor geomorphological processes, ecosystem changes and ongoing surface dynamics linked to climate change indicators. Some of important pillars of the long-term time series analysis can be listed as greening and precipitation events, lake level dynamics, dune movement rates, mapping of sedimentological, geomorphological provinces and aeolian coverage, in order to understand frequency-magnitude relationships.The findings will be supported by a series of fieldworks covered by UAS campaigns and auxiliary ground-truth sensors, ensuring the accuracy of our estimations by in-situ measurements. Based on the derived surface characteristics, various ecosystems will be defined, and a high-level ecosystem integrity model will be developed. Ultimately, our model aims to represent the intactness, functioning and structure of the different ecosystems within arid regions. Additionally, due to our high temporal study concept, the model will serve as the base for quantifiable measurements of the responsiveness and adaptiveness of the ecosystems.Having a model for ecosystem intactness not only help to preserve fragile ecosystems but also strengthens the resilience and adaptive capacity of communities. Furthermore, the transferability of our framework to other drylands may also lead to a comprehensive understanding of the arid characteristics.Keywords: Earth Observation, arid regions, dryland, remote sensing, climate change, impact, geomorphological process, ecological modelling, land surface dynamics
Using commercial microwave links and SEVIRI observations for rainfall estimation in Zambia
Authors: Blettner Nico , Wiegels Rebecca , Kunstmann Harald , Chwala Christian
Published: March 2024

In Zambia, like in many African countries, the dedicated rainfall observation network is sparse, whereas accurate information about rainfall is crucially needed. In such a data-poor country, opportunistic sensors like commercial microwave links (CMLs) can be very beneficial. However, the irregular spatial distribution and the fact that many CMLs are very long and operate at low frequencies are common characteristics for rural areas in Africa which make rainfall retrieval with CMLs challenging. In addition, the lack of reference data complicates the adoption and adjustment of existing CML processing methods. In particular, the detection of rain events in noisy CML data, which can have a significant effect on the resulting estimated rainfall amounts, requires special attention as the long low-frequency CMLs provide comparatively noisy data. One option to support CML data processing is the usage of satellite data.We use level 1.5 data from Meteosat Second Generation (MSG) SEVIRI to generate a precipitation probability (PC) product, similar to the PC products from NWC SAF. Our PC product is generated by a convolutional neural network (CNN) which was trained with SEVIRI and high-resolution radar data in Germany and which was validated with station data in Burkina Faso. We use this PC product to improve the rain event detection during the data processing of almost 1000 CMLs with 15-minute min-max data over several months of the rainy season 2021/2022. In addition, we use two other rain event detection methods, the Python implementation of the nearby-link approach from RAINLINK and the simple rolling standard-deviation method. From the processed CML rainfall estimates, we produce interpolated rainfall maps which we then validate with rain gauge data.Preliminary results show that the nearby-link and rolling standard-deviation method produce satisfactory results in urban regions where CML density is high and CML frequencies are larger than 10 GHz. The application of the SEVIRI-based PC product for improved CML data processing, in particular for the long low-frequency CMLs, is currently being investigated and we will present first results to analyze its potential and limitations.