bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of a new statistically rigorous comparison tool of observed and modelled flow directions of the last British-Irish ice sheet over time
Authors: Archer Rosie , Ely Jeremy , Heaton Timothy , Butcher Frances , Hughes Anna , Clark Chris
Published: March 2024

Past ice flow direction can be inferred through mapping of subglacial lineations (e.g. drumlins and mega-scale glacial lineations). A numerical ice sheet model can also be used to reconstruct possible ice flow directions according to ice physics. These two methods are rarely integrated to see if the model can explain the observational data. Previous model-data comparison workflows made a large step forward. However, they lack statistical rigour and certain capabilities, such as comparing an ensemble of model simulations. To overcome these challenges, we created the Likelihood of Accordant Lineations Analysis (LALA) tool.  LALA is a tool to compare numerical model ice sheet simulations to observational data of past flow direction. LALA was created to take a step forward in improving model-data comparisons; making comparisons statistically rigorous and adding the ability to directly grade multiple simulations against each other, a feature that was missing from previous tools. For this poster, we show an example of the tool in action and use LALA to compare model simulations of the British-Irish ice sheet and observations of flow direction from subglacial lineations taken from the BRITICE-CHRONO project. We present the best and the worst fitting simulations according to LALA. We also dissect the score produced to give an indication of the flow directions which are most (and least) regularly matched by the numerical modelling. These results highlight opportunities for model development and the potential to reevaluate observations.
Urban landslides triggered under similar rainfall conditions in cities globally
Authors: Luna Lisa , Arango Carmona Maria Isabel , Veh Georg , Lewis Elizabeth , Ozturk Ugur , Korup Oliver
Published: March 2024

As growing cities expand into steeper terrain, urbanization activities like clearing vegetation, cutting and filling slopes, and building infrastructure can increase rainfall-triggered landslide hazard compared to unmodified slopes. Landslide early warning systems can help to reduce rainfall-triggered landslide risk in susceptible areas, but few cities worldwide have established dedicated systems. Such systems often rely on rainfall thresholds that identify landslide triggering conditions, but determining these thresholds requires landslide inventory data that is not available everywhere. Furthermore, the variability of thresholds between cities, and the applicability of previously estimated global thresholds to urban areas has yet to be assessed, such that cities with limited landslide inventory data have few options to learn from areas with more information.Here, we compiled 1216 rainfall-triggered urban landslide records from 26 cities worldwide to address two open questions: 1. how variable are rainfall thresholds between cities? and 2. how do global rainfall thresholds for urban landslides compare to previously estimated thresholds from multiple land use types?  Using hourly, station-based precipitation data from the Global Sub-daily Rainfall Dataset (Lewis et al., 2019), we applied Bayesian multi-level quantile regression to estimate intensity-duration thresholds for each city and a global threshold for urban landslides. We found that landslides were triggered under surprisingly similar rainfall conditions in most cities despite widely varying climates, topographies, and income classes.  Median thresholds in cities with the highest and lowest mean annual precipitation were not credibly distinguishable, and in 77% of cities, the median threshold was indistinguishable from the global average. We show that urban landslides occurred at lower threshold intensities than previously reported for multiple land-use types, and that 31% of landslides occurred during moderate storms, not only during extreme rainfall.Our results suggest that urban hillslopes may be more adjusted to urbanization activities than to local environmental conditions, leading to similar thresholds between cities. Reports of urban landslides at relatively low intensity rainfall likely also reflects the role of anthropogenic hillslope modification and malfunctioning infrastructure in causing and triggering failures.  We offer a baseline for warning in cities with sparse landslide records and suggest that future updates to regional and global landslide early warning systems consider differing thresholds for urban and rural regions.
Source to Sea: The Climate Mitigation Significance of Shelf Sea Sedimentary Organic Carbon Stores
Authors: Austin William , Grant Rhiannon , Smeaton Craig , Garnett Mark
Published: March 2024

The burial of organic carbon (OC) in coastal and continental shelf sediments contributes to the regulation of atmospheric carbon dioxide on geological timescales and potentially mitigates present-day climate change. Major efforts are now underway to map and quantify the OC held in our continental shelf seas, including the first ever assessment of a national Exclusive Economic Zone (EEZ) sediment OC resource for the United Kingdom. When these OC-rich sediments are disturbed, either by natural or (increasingly) anthropogenic pressures, there is potential for significant quantities of carbon dioxide to be released to the water column and potentially the atmosphere.
The reactivity of sedimentary OC is generally defined as a susceptibility to decomposition, biotically or abiotically. Reactivity of OC in marine sediments determines the role the store plays in climate regulation and, equally, determines the vulnerability of the sedimentary OC store to disturbance both natural and anthropogenic. The recent development of the Carbon Reactivity Index (CRI) as a novel measure of OC reactivity based on thermogravimetric analysis has highlighted a wide continuum of OC reactivity in sediments across continental shelf seas. Here, we present new results that highlight the continuity of these processes across the land-ocean transition in the major estuaries (Clyde and Forth) of Scotland. Our results highlight new opportunities to integrate the protection of vulnerable sediment OC stores into objective marine management plans across coastal and shelf seas.
Responses of Tibetan antelope population to environment changes during the Holocene
Authors: Hou Juzhi
Published: March 2024

Tibetan antelope is the only genus of large mammal endemic to the Tibetan Plateau. In the past decades, the antelope population has been significantly affected by human activities, including massive illegal hunting, followed by strict protection policies and establishments of natural reserves. Various techniques and many efforts have been devoted to monitoring changes in antelope population as well as migration recently. However, it remains unclear how the antelope population changed in the past, and how it varied with climate and environment. Here, we present sedimentary records at Lake Zonag, one of the major calving grounds for the Tibetan antelope, to study past changes in antelope population and response to environment changes. The sedimentary fecal sterols, produced by antelopes, captured the sudden decrease in antelope due to illegal hunting in past decades, as well as the recent recovery. The antelope population varied significantly during the past 9000 years, generally following environment changes revealed by geochemical elements in the same sediment core. Large antelope population likely lived in environment with relatively warm, humid and dense vegetation cover, while small antelope population occurred in adverse environment with relatively cold, dry and sparge vegetation cover. Two periods with notably low antelope population were observed at 5100-4500 and 4100-3700 cal yr before present. The increase in antelope population in the past 400 years likely result from protection from early Tibetans. This study provides a perspective method to reconstruct past changes in antelope population, to study its response to environment changes, and to provide historical comparison for wildlife protection.
Ionospheric conductance due to electron and ion precipitations based on the comparison between EISCAT and DMSP estimates
Authors: Wang Xin , Cai Lei , Aikio Anita , Vanhamäki Heikki , Virtanen Ilkka , Zhang Yongliang , Luo Bingxian , Liu Siqing
Published: March 2024

Energetic particle precipitation is the major source of electron production that controls the ionospheric Pedersen and Hall conductances at high latitudes. Typically, the ionospheric conductances are estimated using either theoretical or empirical equations. The former method requires several ionospheric and thermospheric parameters as inputs. By contrast, empirical equations are simple, such as Robinson formulas and Galand formulas that have been widely used. In this study, we evaluate the empirical formulas of ionospheric conductances during four different types of auroral precipitation conditions based on 63 conjugate events observed by DMSP and EISCAT. The conductances calculated from the DMSP data with the empirical formulas are compared with those based on EISCAT measurements with the standard equations. The best correlation between these two is found when the empirical Robinson formulas are used in the presence of diffuse electron precipitation without ions. In the presence of ion precipitation, the correlation coefficients are smaller, but the correlation improves when the Galand formulas are used to estimate the contribution of ion precipitation to the conductances. For the condition of pure ion precipitation, the ionospheric conductances are increased up to 2-7 S for Pedersen and 2.5-10 S for Hall conductances. The increase is larger for a higher geomagnetic AE index. Overall, the empirical formulas applied to the DMSP particle spectra underestimate the ionospheric conductances.
ClimarisQ: A game on the complexity of the climate systems and the extreme events
Authors: Faranda Davide ,   ClimarisQ team
Published: March 2024

ClimarisQ is a smartphone/web game from a scientific mediation project that highlights the complexity of the climate system and the urgency of collective action to limit climate change. It is available in four languages: English, French, Spanish and Italian. It is an app-game where players must make decisions to limit the frequency and impacts of extreme climate events and their impacts on human societies using real climate models. ClimarisQ is a game conceived by the CNRS researcher Davide Faranda through the CNRS – AMCSTI – ISC-PIF scientific mediation incubator on complex systems. The development of ClimarisQ, powered by the videogame company Opal Games, has been financially supported by the University of Paris-Saclay : La Diagonale Paris-Saclay.The goal of the game is to explore the effects of mitigation and adaptation choices to extreme climate events at the local, regional and global levels. Can you achieve a greener trajectory than the IPCC RCP 4.5 emission scenario by playing ClimarisQ? Explore the feedback mechanisms (notably physical, but also economic and social) that produce extreme effects on the climate system.In the game, you make decisions on a continental scale and see the impact of these decisions on the economy, politics and the environment. You will have to deal with extreme events (heat waves, cold waves, heavy rainfall and drought) generated by a real climate model. Then, you will have to try to balance the “popularity”, “ecology” and “finance” gauges as long as possible. Fulfill all the missions to explore different climates. The game-over displays both the PPM (parts per million) of CO2 deviation from the intermediate scenario of greenhouse gas emissions established by the IPCC (RCP4.5), as well as the number of survival game turns. These elements stimulate thinking about climate change and motivate the player to do better next time. Thanks to the hazards introduced by the extreme events and cards, every game is different!
Digitized continuous magnetic recordings for the August/September 1859 storms from London, UK
Authors: Beggan Ciaran , Clarke Ellen , Lawrence Ewelina , Eaton Eliot , Williamson John , Matsumoto Keitaro , Hayakawa Hisashi
Published: March 2024

Dedicated scientific measurements of the strength and direction of the Earth's magnetic field began at Greenwich and Kew observatories in London, UK, in the middle of the 19th century. Using advanced techniques for the time, collimated light was focussed onto mirrors mounted on free-swinging magnetized needles which reflected onto photographic paper, allowing continuous analogue magnetograms to be recorded. By good fortune, both observatories were in full operation during the so-called Carrington storm in early September 1859 and its precursor storm in late August 1859. Based on digital images of the magnetograms and information from the observatory yearbooks and scientific papers, it is possible to scale the measurements to SI units and extract quasi-minute cadence spot values. However, due to the magnitude of the storms, the periods of the greatest magnetic field variation were lost as the traces moved off-page. We present the most complete digitized magnetic records to date of the ten-day period from 25th August to 5th September 1859 encompassing the Carrington storm and its lesser recognised precursor on the 28th August. We demonstrate the good correlation between observatories and estimate the instantaneous rate of change of the magnetic field.
Synthetic Data and AI - Teaching a Neural Network to Identify Clouds Despite the Lack of Annotated Observation Data
Authors: Scheirer Ronald , Pirinen Aleksis , Abid Nosheen , Agues Paszkowsky Nuria , Ohlson Timoudas Thomas , Ceccobello Chiara , Kovács György , Persson Anders
Published: March 2024

Clouds are characterized - among other things - by their intense variability in time, space and optical thickness. These variables impact the modulation of solar radiation (reflection, transmission and absorption) and may distort the signal from the surface beneath. This in turn makes it important to detect even optically thin clouds using remote sensing methods, even if the focus is on earth observation.This study has been initiated by the Swedish Forest Agency (SFA). In order to reduce the proliferation of bark beetles, SFA needs to identify stressed trees at an early stage. To this end, high-resolution scenes from the Multi-Spectral Imager (MSI) on board the Sentinel-2 platforms were analyzed. Unfortunately, the quality of ESA's scene classification layer (SCL) does not meet the requirements for reliably sorting out scenes contaminated with thin clouds.To overcome this problem, it was decided to make use of the fact that the integration of machine learning (ML) methods within the remote sensing domain has significantly improved performance on remote sensing tasks. But a common difficulty is that ML methods typically depend on large amounts of annotated data for training. Annotation or classification is usually done manually or by a superior instrument (i.e. active LIDAR). Since such a data basis is missing, a synthetic database (based on simulations instead of observations) was generated to train a Multi Layer Perceptron (MLP). The dataset consists of 200,000 data points, which have been simulated taking into consideration different cloud types, cloud optical thicknesses (COT), cloud geometrical thickness, cloud heights, as well as ground surface and atmospheric profiles. The MLP is trained to predict COT as a proxy for the cloud/clear decision.The performance of the proposed algorithm using both synthetic data (as used during training) and real satellite observations (never presented to the algorithm before) will be discussed in detail. It was found that the MLP approach trained on 1D synthetic data can seamlessly transition to real datasets without requiring additional training. Furthermore it outperforms the ESA-SCL.
Climate Change Effects on Flood Hazard and Risk in Harami̇dere Basin
Authors: Firat Egemen , Özer Buse , Yılmaz Koray K. , Türkkan Karaoğlu Gülçin , Fitoz Esra
Published: March 2024

In flood hazard and risk assessment studies, modeling is generally done by examining the hydrometeorological events that have developed by using past datasets. Recently, increasing rainfall per unit time due to climate change may cause flash floods. Hydrographs, which are input to 1D/2D hydrodynamic models, are also likely to change as a result of climate change. Hydrological calculations based on past data may underestimate the predicted values. Therefore, flood risks produced from the results of flood depth and hazard models may also remain at low values. In this study, firstly, a hydrological modeling study was carried out on the streams in Haramdere Basin by using hydrometeorological measurements between 2010-2022 and hydrographs were produced for Q2, Q5, Q10, Q25, Q50, Q100, Q500 and Q1000 returning periods. In mapping studies, river structures, stream geometry, digital surface and terrain model were determined using ground measurements and flight data. Then, flood depth and hazard maps were created with 1D and 2D hydrodynamic models. Economic risk calculation was made using these maps. Then, RCP8.5 scenarios known as having high precipitation anomalies for all climate models included in CMIP6 were re-run in the hydrological model. In this way, flow data were generated for each climate model RCP8.5 scenario. Then, 3 different climate change impacts (worst, medium and best) for Haramidere Basin in regards to flood hazard and risk will be revealed by analyzing the rainfall and runoff extremes produced from the hydrological model for all climate models. In the worst case scenario, the climate model with the highest rainfall and runoff extremes, in the medium case, the average of the values calculated from all climate models and in the best case scenario, the climate model with the lowest extremes will be selected. In this way, climate models specific to this basin will be determined for these 3 different Scenarios. Then, from these selected climate models, coefficients will be determined to be used in hydrological calculations for the effect of climate change on flooding events. Finally, flood risk calculations will be made for these 3 scenarios and the economic value of climate change in terms of flood risk will be quantified by comparing with the flood risk calculated with the measurements between 2010-2022.
Seasonal drought reduces microbial diversity and functional richness in the Amazon
Authors: Finck Jessica , Lange Dan Frederik , Quesada Beto , Portela Bruno Takeshi Tanaka , Ferreira Sávio José Filgueira , Andreote Fernando Dini , Kothe Erika , Gleixner Gerd
Published: March 2024

Tropical rainforests such as the Amazon are of high importance as a global carbon sink. Due to its well-known nutrient limitation, the Amazon rainforest relies heavily on rapid microbial decomposition of biomass to release freshly available nutrients for plant growth. Despite the fundamental importance of decomposers for this ecosystem, little is known about the biodiversity of such microbiomes, their functional activity, and spatial and seasonal variability. We used 16S rDNA and ITS rDNA sequencing to analyze the microbial communities of the Amazon’s terra firme and the much drier white-sand ecosystems during the dry and wet seasons in 2022. Bacterial microbiomes differed significantly between seasons, displaying lower bacterial species richness and diversity in response to seasonal drought. In contrast, fungal richness and diversity differed strongly between sites, but were less affected by seasonal variation, suggesting their hyphae network and associations with plants as potential protectors against drought effects. Fungal and bacterial communities alike showed lower abundance of taxa involved in organic matter decomposition following seasonal drought. These changes were also reflected at the functional level, with samples collected during the dry season and at white-sand sites featuring lower abundances of decomposition and denitrification pathways. Soil hydro-chemical data also emphasizes how prolonged drought may limit soil nutrient supply via local microbiomes. Our results suggest that the reduced nutrient availability and soil connectivity during drought and within the white-sand ecosystem lower microbial activity and functional redundancy, henceforth demonstrating a strong impact of ecosystem type and drought on tropical microbiomes and their functional capacities. Our results further highlight that the observed increase in droughts in the Amazon rainforest may additionally limit nutrient supply through the microbial community, limiting carbon sequestration in the ecosystem with negative consequences for the global climate system.
Are spatial patterns of soil moisture or percolation affected by throughfall heterogeneity? Empirical evidence from a beech-dominated forest.
Authors: Hildebrandt Anke , Christine Fischer-Bedtke , Johanna Clara Metzger , Gökben Demir , Thomas Wutzler
Published: March 2024

Heterogeneity in throughfall, caused by the redistribution of precipitation in the vegetation canopy, has repeatedly been hypothesized to influence the variation in soil water content and runoff behavior, especially in forests. However, observational studies directly relating the spatial variation in the soil water content or dynamics to net precipitation are rare. Here, we investigate how throughfall patterns affect the spatial heterogeneity in the soil water response in the main rooting zone. We assessed rainfall, throughfall, and soil water content (at two depths, 7.5 and 27.5 cm) in a 1 ha temperate mixed beech forest plot in Germany during the 2015 and 2016 growing seasons using independent, high-resolution, stratified, random designs. Because the throughfall and soil water content cannot be measured at the same location, we used kriging to derive the throughfall values at the locations where the soil water content was measured.Spatial patterns of throughfall were related to canopy density. Although spatial autocorrelation decreased with increasing event size, temporally stable throughfall patterns emerged, resulting in the reoccurrence of higher- and lower throughfall locations across precipitation events. Linear mixed-effects model analysis showed that while soil water content patterns were poorly related to spatial patterns of throughfall, the increase in soil water content after rainfall was strongly related. More water was stored in the soil in areas where throughfall was elevated. At the same time, however, the local soil water response was modified by the soil wetness itself in a way that suggests processes of rapid drainage and runoff. Locations with a lower than average topsoil water content tended to store less of the input water, indicating locally enhanced preferential flow. In contrast, in the subsoil, locations with above average water content stored less water than their drier counterparts. In addition, macroporosity also modified how much water was retained in soil storage.Overall, throughfall patterns influenced soil water content much less than soil water dynamics shortly after rainfall events. Furthermore, drainage reduced the soil moisture variation within hours to days, when returning from the wetted to the dry state. Therefore, we conclude that percolation rather than the soil water content is affected by small-scale spatial heterogeneity in canopy input patterns.ReferenceFischer-Bedtke, C., Metzger, J. C., Demir, G., Wutzler, T., and Hildebrandt, A.: Throughfall spatial patterns translate into spatial patterns of soil moisture dynamics – empirical evidence, Hydrol. Earth Syst. Sci., 27, 2899–2918, https://doi.org/10.5194/hess-27-2899-2023, 2023.
Effect of polyvinyl chloride and polypropylene microplastics on nutrient status in two vineyard soils of contrasting pH
Authors: Contin Marco , Sternad Lemut Melita , Pellegrini Elisa , Jez Erika
Published: March 2024

Compared with the widespread knowledge about the supply of soil with nutrients for optimal vine growth, the possible effect of microplastics in vineyard soils has not yet been addressed. Little is known about how microplastics may affect the bioavailability and fractionation of nutrients in vineyard soils of contrasting pH. In this study, a 120-day soil incubation experiment was performed to investigate the effect of new and aged polypropylene (PP) microplastics and polyvinyl chloride (PVC) microplastics on the soil pH, nitrogen availability (NH4+ and NO3-) and binding behaviour of macro- (phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg)) and micro-nutrients (iron (Fe), copper (Cu), manganese (Mn) and zinc (Zn)). The results showed that the presence of microplastics in soils increased the pH and decreased the bioavailability of macro- and micronutrients in the soil, with the acid soil being more affected. Furthermore, the presence of PVC microplastics had a stronger impact on nutrient availability than PP microplastics. The most important finding of this study was that micro-PVC particles in soil utterly reduce the bioavailability of nitrate (NO3-) in both calcareous and acid soil samples. This pronounced negative effect was only measured for the micro-PVC particles from the PVC tube ties used in the vineyards and not from the standard PVC material (Sigma Aldrich). Wine producers should be aware that PVC microplastics reduce the bioavailability of nitrate in soils. However, further studies are in progress to clarify the mechanisms involved in the reduction of soil nitrate bioavailability by PVC microplastics from degraded vineyard strings, in particular from the microbial side.
To what extent do iron organic carbon interactions attenuate C release from permafrost thaw?
Authors: Opfergelt Sophie , Roux Philippe , du Bois d'Aische Eléonore , Villani Maëlle , Thomas Maxime , Osy Cécile
Published: March 2024

Enhanced thawing of the permafrost in a warming Arctic exposes previously frozen soil organic carbon (OC) to microbial decomposition, leading to the release of soil C as greenhouse gases. Depending on temperature and moisture environmental variables, a centennial to millennial-year-old C pool can be reached, thus accelerating the feedback to climate change. Iron-OC interactions in soils and sediments contribute to stabilize OC (by adsorption onto Fe oxides or forming Fe-OC complexes), thus mitigating permafrost C emissions. However, their formation and stability are dependent on soil pH and redox conditions. The heterogeneous soil moisture conditions and drastic changes in soil water pathways upon permafrost thaw make the significance of Fe-OC interactions in attenuating permafrost C emissions uncertain. Using radiogenic Sr isotopes, we show that, in saturated layers, Fe-OC interactions can remain undissociated and preserved since their formation. In contrast, we highlight that at the redox interface, processes of dissolution and precipitation of the Fe-OC interactions occur, changing the OC stabilization potential. Given the implications for overall long-term ecosystem C storage, we will discuss an approach to estimate at the landscape scale in the Arctic: (i) the proportion of permafrost soils Fe with potential for interactions with OC (reactive Fe), and (ii) the locations which are the most sensitive to changes in Fe-OC interactions.
Mapping out lightning processes in both the VHF and VLF using LOFAR and the Met Office’s lightning detection system, LEELA
Authors: Marlton Graeme , Hare Brian , Scholten Olaf , Protts Mike , Stone Ed , Twelves Sue , Devoto Francesco
Published: March 2024

Lightning is one of the most destructive meteorological phenomena being a hazard to people and objects on the ground as well as aircraft. In addition to the strong currents and optical emission from a lightning stroke broadband radio emissions are also produced from the VLF to VHF. The LOw Frequency ARray (LOFAR) telescope centred in the Netherlands consists of a large array of VHF (30-300 MHz) receivers which can be configured to image a lightning strike in the 30-80 MHz bandwidth. The Met Office Lightning Electromagnetic Emission Location using Arrival time differencing LEELA system operates in the VLF (3-30 kHz). It also archives the raw incoming VLF data allowing the individual VLF waveforms to be analysed. From a lightning flash recorded in June 2021 over the Netherlands, 8 distinct events were detected by both systems. Here we present an analysis of these 8 events which include dart leaders, negative leaders, an intensely radiating negative leader and a cloud to ground strike. Initial results show that while both systems co-locate the events they are sensitive to different processes within the lightning strike process. VHF emission from a lightning strike is observed for periods of 30-40 ms and captures the development of the lightning channel. However, VLF emission is observed for much shorter periods of a few ms likely corresponding to the rapid vertical movement of charge during the strikes.
Impact of vegetation on urban open-channel flow: Practical experiment with 2D IBER hydraulic simulations in Monterrey, Mexico.
Authors: Nieto Butrón Jacob Jesús , Ramírez Serrato Nelly Lucero , Barco Coyote Selene , Yépez Rincon Fabiola Doracely , Jácome Paz Mariana Patricia
Published: March 2024

Flooding is a constant danger in many cities. To prevent and mitigate their impacts, mathematical modeling is carried out to simulate the behavior of the flow within the environment and define the possible flood zones. Incorporating vegetation in hydraulic models is pivotal for understanding its impact on flow characteristics, sediment transport, and channel morphology.The Santa Catarina River in Monterrey, Nuevo León, Mexico, grapples with irregular water flows. During dry seasons, minimal water levels promote unchecked vegetation growth along its banks and bed, potentially obstructing normal flow. Conversely, extreme weather events like hurricanes lead to rapid surges, sweeping away vegetation and debris. Balancing this fluctuation—from sparse to intense flows—presents challenges in managing the river's vegetation, necessitating strategies that reconcile environmental preservation with urban infrastructure resilience.For this purpose, This study utilized two hydraulic models through IBER to assess vegetation's impact on flood simulations. One model employed a Digital Elevation Model (DEM), portraying terrain topography. The second model used a Digital Surface Model (DSM) integrating manually digitized vegetation from (2020) Google Earth imagery. Assigned heights of 3m for shrubs and 15m for trees emulated their impact on water flow. Both the DEM and DSM, with a 5-meter resolution, were obtained via LiDAR techniques from the INEGI government web platform. the models also utilized a land use classification obtained from a Sentinel-2 satellite image (from 2023). Hydrological data for both models were derived from the cumulative rainfall during Hurricane Alex in 2010.The findings highlight significant changes in flood patterns attributed to vegetation. Its presence alters the flow, shifting the flood zone towards a southwest residential-commercial area. In this integrated model, the maximum depth reaches 16.78 meters, compared to 10.70 meters in the DEM-based hydraulic model. Additionally, the consistently affected area deepens from 2 meters to 4.37 meters when considering the vegetation-inclusive DSM-based approach.These findings underscore the crucial role of vegetation in shaping flood pathways within urban environments, emphasizing the need to consider both natural and human-introduced elements in flood risk management strategies. Future research directions could explore the evolving impact on populations across varied flood zones and conduct comprehensive cost evaluations regarding risk mitigation, recovery efforts, and infrastructure fortification. These avenues present promising trajectories for further studies, offering insights into the socio-economic and financial implications of diverse flooding patterns in urban settings.
Exploring CO2 Cycling in Karst Critical Zones: Lessons from Milandre Cave
Authors: Rowan Sarah , Leutscher Marc , Szidat Sönke , Lechleitner Franziska
Published: March 2024

We know that the concentrations of CO2 and DIC in the subsurface are often magnitudes higher than in the soil zone, and therefore we need to understand this reservoir and its vulnerability to change. Understanding the critical zone in the context of CO2 input, cycling dynamics, and export is essential as this carbon is particularly vulnerable to changes in water table rise which may result in rapid release of CO2 into the atmosphere. Cave environments provide an accessible natural window into the critical zone as they connect meteoric water, soils, the unsaturated vadose zone, and saturated zone. We conducted a two year monitoring campaign at Milandre cave in northern Switzerland, analyzing pCO2, d13CO2, and 14CO2 at various environmental interfaces, including the soil zone, within the epikarst, and in the cave itself. Forest soils maintained stable, modern 14C signatures and low d13C indicating year-round contribution of CO2 from C3 tree and plant root respiration. Conversely, meadow soils exhibited notable seasonality in F14C, suggesting a dominance of respiration from older soil pools in the winter months. Distinct variations in CO2 concentrations were observed within the cave, influenced by temperature driven ventilation dynamics. Keeling plot analysis revealed a consistent contributing endmember of C3 vegetation. However, similarities between the F14C of the meadow soils and cave CO2 suggests a significant contribution of meadow soil CO2 into the cave. These findings offer vital insights into the nuanced dynamics of CO2 sources and cycling processes within the critical zone of Milandre Cave, shedding light on the influences of seasonal variation and ecological influences of critical zone carbon and the export of carbon from terrestrial ecosystems.
A combined dataset of path-averaged and in-situ measurements of greenhouse gases to inform on the sensitivities to localized source patterns and transport effects in the urban atmosphere.
Authors: Schmitt Tobias D. , Pilz Lukas , Maiwald Robert , May Maximilian , Löw Benedikt A. , Kleinschek Ralph , Wietzel Julia B. , Kuhn Jonas , Schmitt Stefan , Schmidt Martina , Vardag Sanam N. , Hase Frank , Griffith David W. T. , Butz André
Published: March 2024

Urban areas are a major and growing contributor to anthropogenic greenhouse gas (GHG) emissions and are thus an important target for emission reduction efforts. However, measurement-based information for planning, implementing, and monitoring such reduction efforts on city scales is rarely available to policymakers and stakeholders. Such monitoring systems typically rely on three key components: measurements of GHG concentrations (or turbulent fluxes), modeling of the atmospheric transport and prior information on the spatial and/or temporal structure of the emissions. The high spatial and temporal heterogeneity of urban areas and their emissions is especially challenging for atmospheric transport models and gridded inventories, which are currently pushed to resolutions of kilometers and below in an effort to accurately represent these effects. However, GHG concentration measurements are often performed by in-situ systems and are thus not necessarily representative for the kilometer scales on which measurements, transport modeling and prior information are typically compiled. This becomes increasingly important with the ever-improving quality of measurements, models, and inventories themselves.We present a dataset of urban path averaged concentration measurements of CO2 and CH4 and their comparison to co-located in-situ measurements. The path averaged measurements are taken along a 1.55 km long path over the city of Heidelberg, Germany. The observatory utilizes FTIR spectroscopy and is now in continuous operation since February 2023. Analysis of the path averaged and co-located in-situ measurements reveals differences of up to 20 ppm in CO2 for specific wind directions, which are most likely a result of a local atmospheric transport phenomenon. Further, the two measurements show differences in CH4, which are likely a result of different sensitivities to local emissions. Overall, the data indicate a clear but different sensitivity of either measurement approach to localized source patterns. Thus, the dataset enables the assessment of the representativeness of the different measurement approaches and of the performance of atmospheric transport models and emission inventories in the urban environments.
Destination Earth Data Lake unlocking Big Earth Data processing
Authors: Puechmaille Danaele , Schick Michael , Saulyak Borys , Dillmann Martin , Wolf Lothar
Published: March 2024

The European Commission’s Destination Earth (DestinE) initiative will deploy several highly accurate thematic digital replicas of the Earth (Digital Twins) for monitoring and simulating natural and human activities, as well as their interactions. This will enable end-users and policy makers to execute “what-if” scenarios for assessing both the impact of environmental challenges (weather extremes, climate change etc.) and the efficiency of proposed solutions. DestinE is implemented in a strategic partnership between the European Space Agency (ESA), the European Centre for Medium-Range Weather Forecasts (ECMWF) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT).Data Lake is one of the three components of DestinE system. The DestinE Data Lake must tackle several technical challenges. Firstly, the unprecedented volumes of data generated on a frequent basis within the scope of DestinE call for novel and efficient data access and near-data processing services, beyond the traditional “data-to-the-user” paradigm (in which users must download a multitude of files locally, extracting the required parts e.g. variables, area-of-interest etc. and afterwards using them as inputs in their algorithms).Secondly, the DestinE Data Lake must handle a wide variety of data. In order to offer users a uniform interface to all the data they need for their applications, the DestinE Data Lake must provide access not only to the challenging volumes of Digital Twin outputs but also to federated data from various existing and upcoming data spaces, beyond traditional Earth Observation. This is managed via a user-driven data portfolio and fulfilled by a harmonised data access layer that abstracts away the heterogeneity and complexity of the underlying data sources.Thirdly, the intense processing requirements of DestinE Digital Twins are fulfilled by hosting them on European High-Performance Computing (EuroHPC) sites. Data produced by the Digital Twins (DTs) must be processed where produced, at the edge of the DestinE Data Lake. This is achieved having defined a reference architecture, geographically distributed, with cloud stacks deployed in close proximity with the HPCs, for efficient data exchange.Last but not least, DestinE follows a user-centric approach, evolving in response to on-boarded use cases. This requires a flexible architecture and user-driven data portfolio/ services, which can easily evolve to emerging user needs, incorporate new services, workflows and data sources, including future Digital Twins.
Enhancing Nitrogen Removal in European River Basins: The Crucial Role of Wetland Conservation and Restoration as Nature-Based Solutions
Authors: Bertassello Leonardo , Basu Nandita , Feyen Luc
Published: March 2024

Over the past century, the nitrogen pollution problem has grown concomitantly with population growth, intensified agricultural practices, and a warming climate. In Europe, the presence of excess nitrogen in the environment has already exceeded safe planetary boundaries, posing a threat to Earth’s water supply and biodiversity.While considerable efforts are now focused toward mitigating this problem through increased regulatory measures on wastewater treatment plants and implementation of better agricultural management practices, there is a growing interest in the use of wetlands as nature-based solutions (NBS) to improve water quality and, in particular, to reduce nitrogen loading to downstream water.Despite these benefits, wetlands are among the most degraded ecosystem in Europe, having experienced significant shrinkage over the past centuries, now constituting only one-third of their 1700 extent. This decline is largely attributed to agricultural expansion on drained productive wetland soils, while also contributing to increased nitrogen pollution from excess use of fertilizers.To address these issues, starting from nitrogen surplus data and current wetland extent at European scale we estimate with a physically-based model that current removal potential of wetlands is about 1113 ± 101 kt of N per year (~6.5% of total N surplus in European soil). The significance of wetlands in water quality remediation is underscored by the fact that this nitrogen would otherwise enter the river network and, subsequently, the sea. Given that the current riverine loads in EU watersheds amount to about 2730 kt N per year, the loss of current wetlands would increase this figure by over 40%, with detrimental consequences for the status of surface waters and the eutrophication of coastal areas.We propose a set of restoration scenarios, along with the associated costs, for the restoration of wetlands that have been drained for agricultural purposes. Our analysis aligns with the objective of the Nature Restoration Law, requiring EU member states to implement effective restoration measures to cover at least 20% of the EU’s land and sea areas by 2030. We show that by restoring 2.6% of EU land (equivalent to 20% of historical wetlands), we could nearly double the current nitrogen uptake (2108 ± 187 kt of N per year), and significantly improve riverine water quality by reducing more than 30% of their loads to the sea. In addition, wetland restoration will offer a wide array of ecosystem co-benefits from flood prevention and carbon sequestration to provision of critical habitat for specialized flora and fauna.
How does 3°C global warming affect hail over Europe?
Authors: Thurnherr Iris , Cui Ruoyi , Velasquez Patricio , Brennan Killian , Wilhelm Lena , Wernli Heini , Steger Christian R. , Schär Christoph
Published: March 2024

Thunderstorm-related severe weather, in particular hail, causes extensive damage to life and infrastructure in the Alpine region. However, changes in hail impact due to a warmer climate are still not fully understood. In the scClim project, convection-permitting regional climate simulations over Europe using the model COSMO with a ~2.2 km horizontal resolution have been conducted for present-day climate conditions (2011-2021) and a climate scenario with a 3°C global warming using a pseudo-global-warming approach. ERA5 reanalyses were used as boundary conditions and a CMIP6 simulation (MPI-ESM1-2-HR) to infer the large-scale climate-change signal. The integrated online diagnostic HAILCAST is used to calculate maximum hail size. The simulations provide total precipitation and maximum hail size estimates every 5 minutes, which allows for hail cell tracking in the climate simulations and the analysis of hail events in a warmer climate. Validation of the present-day simulation against observations of temperature, precipitation and hail shows an overall good model performance. For hail in particular, radar-based, station-based and crowd-sourced observations have been used to assess the model performance in simulating hail on spatial, diurnal and seasonal scales. The validation outcome encourages further study of the climate signal of hail as simulated with the pseudo-global-warming approach. We will show projected changes in the spatial distribution and seasonal cycle of hail over Europe as well as changes in lifetime, storm area and location of hail cells due to a 3°C global warming.
Comparing methods to quantify grain-scale sediment structure in gravel-bed rivers
Authors: Hodge Rebecca , Voepel Hal , Yager Elowyn , Leyland Julian , Johnson Joel , Sear David , Ahmed Sharif
Published: March 2024

Understanding when gravel moves in river beds is essential for a range of different applications, but is still surprisingly hard to predict. The critical shear stress at which a grain will move depends on its relative size and structure within the bed, and spatial and temporal changes in grain-scale structure are likely to be a major driver of changes in critical shear stress. Consequently grain-structure metrics such as protrusion, pivot angle and contact with any surrounding fine grained matrix are used as parameters in models to predict critical shear stress, and so there is an increasing demand for measurements of these parameters in order to improve our predictive ability. However, we do not have established methods for measuring these parameters, nor do we know whether different methods provide consistent results. Here we present and compare new datasets of sediment structure metrics collected from eight locations in a small gravel-bed stream using three different methods: direct field-based measurements, terrestrial laser scanning (TLS), and computed tomography (CT) scanning. Using each method, we measure metrics including grain size distribution, grain protrusion and fine matrix content. We find that distributions of grain size are consistent between field-based and TLS data, but smaller in CT data. All three methods produce similar distributions of protrusion relative to grain size. There is also some consistency between field and CT measures of fine-grained matrix. However, the identification of similarity also depends on the type of analysis, and an alternative analysis shows less similarity in protrusion and fine-grained matrix between the different methods. Of the three methods, TLS-based approaches have potential to be most easily applied, and our analysis suggests that for grain-size and protrusion they perform as well as the alternative methods. However, they cannot currently be used for measuring fine-grained matrix content.