bluuebunny/crossref_metadata_2025 huggingface dataset:
Decreased precipitation intensity in the South Pacific Convergence Zone during the Little Ice Age inferred from dinosterol hydrogen isotope ratios
Authors: Ladd Nemiah , Maloney Ashley , Nelson Daniel B , Richey Julie N , Witt Amanda , Sobeck Polly , Prebble Matthew , Peaple Mark , Sear David A , Langdon Peter G , Dubois Nathalie , Sachs Julian P
Published: March 2024

The South Pacific Convergence Zone (SPCZ) is the most prominent precipitation feature in the southern hemisphere, extending southeast from Papua New Guinea to French Polynesia. Changes in SPCZ precipitation dynamics can have major impacts on local communities and ecosystems, as well as the global hydrologic balance and ocean circulation. Variability in SPCZ precipitation can be characterized as changes in precipitation intensity throughout the entire rainfall band, or as changes in its mean annual position. Proxy reconstructions of precipitation rates from single sites within the SPCZ region cannot distinguish changes in SPCZ intensity from changes in SPCZ location, and the low density of proxy-based precipitation records from the pre-instrumental era makes it challenging to characterize past SPCZ dynamics.To address this gap, we present quantitative records of rainfall rates derived from sediment cores collected from five freshwater lakes in the western portion of the SPCZ (from Tetepare and Rendova Islands in Solomon Islands, and from Thion Island in northern Vanuatu), spanning the past 500 to 1000 years, depending on the site. Our records are based on the hydrogen isotope composition of the dinoflagellate biomarker dinosterol, which is quantitatively related to mean annual precipitation. Our dinosterol records are complemented by analyses of magnetic susceptibility, pollen, and leaf wax hydrogen isotopes. We pair our new dinosterol-based precipitation reconstructions with previously published, comparable records from lakes in Samoa, Wallis, and southern Vanuatu to demonstrate that precipitation rates were systematically lower throughout the western and central SPCZ during the Little Ice Age (1450 – 1850 CE), indicating a decrease in precipitation intensity. The earlier Medieval Climate Anomaly (950 – 1250 CE) is also characterized by a tendency to drier conditions than in the modern period, but with more spatial heterogeneity. This networked reconstruction of precipitation rates in the SPCZ region provides the opportunity to better assess how rainfall dynamics in the region have changed through time, and how modes of variability within the SPCZ are related to global climate change.
Impacts of climate change and weather extremes in Europe: building a knowledge base for decision support
Authors: Grieger Jens , Ulbrich Uwe , Buschow Sebastian , Lucio Eceiza Etor E. , Feldmann Hendrik , Friederichs Petra , Kaspar Frank , Kunz Torben , Niermann Deborah , Pinto Joaquim G.
Published: March 2024

The ClimXtreme program, funded by the German Ministry of Education and Research, focuses on the assessment of the frequency and intensity of historical extreme events and their impacts in Central Europe, their association with dynamical and thermodynamical processes and how these extreme events might change according to enhanced anthropogenic climate forcing.The program currently aims at the development of a basis for stakeholder decision making that consists of data, software, and information tailored to their needs. By means of dedicated hazard specific stakeholder interaction groups, relevant stakeholders and researchers will develop the knowledge base through a two-way process. Social scientists will explore and develop the communication process with stakeholders.Within the research program, a post-event assessment group will be formed aiming at rapid response of the project to extreme events occurring during project runtime. The group will make use of the developed knowledge base, apply pre-defined methods and workflows to assess current extreme events with diverse perspectives which are represented in ClimXtreme.Both the concept and selected recent results of the ClimXtreme program will be highlighted.
Fault Detection in Solar Thermal Systems using Probabilistic Reconstructions
Authors: Ebmeier Florian , Ludwig Nicole , Thümmel Jannik , Martius Georg , Franz Volker H.
Published: March 2024

As heating is the largest factor of Greenhouse gases in the household sector, it shouldbe the focus of our decarbonisation efforts. Solar Thermal Systems (STS), which provideheat based on solar energy, are a promising technology in this regard. However, STSare prone to faults due to improper installation, maintenance, or operation, often leadingto a substantial reduction in efficiency, damage to the system, or even an increase inenergy cost. As individual monitoring is economically prohibitive for small-scale systems,automated monitoring and fault detection should be used to address this issue.We propose a data-driven neural network approach for fault detection in small-scaleSTS, utilising probabilistic reconstructions from a long short-term memory (LSTM) basedVariational Autoencoder (VAE). Key factors in our approach are generalising from faultlessdata to previously unseen systems and an anomaly score derived from an ensemble ofreconstructions. We apply this to an operational dataset provided by our industry partner,which includes systems with different types of faults.Our results show that our model can detect faults in STS with comparable performanceto the state-of-the-art expert-based system used by our industry partner. Furthermore, ourmodel can detect previously undetected faults, specifically those resulting from unexpectedbehaviour in the control software or behaviours that were entirely unexpected and notconsidered in the expert-based system. Thus, a combination of our model and the expert-based system covers a broader range of faults than either system and is proposed forfurther use in the industry partner’s application. Additionally, other providers without afunctioning expert-based system could build upon our work to get a minimal viable productfor fault detection in STS, purely based on data from existing systems and without theneed to install additional sensors or domain-specific knowledge.
Trade-driven changes in global air pollutant emissions during 2004-2017
Authors: Ren Fangxuan , Lin Jintai , Wang Jingxu , Chen Lulu , Xu Junwei , Liu Yu
Published: March 2024

International trade is associated with air quality, public health, and climate change through redistributing air pollutant emissions. Global trade patterns have undergone significant changes in the past decade causing large changes in anthropogenic emissions. Revealing the long-term pattern change of trade-embedded emissions and identifying the driving factors that change the emissions could be key to enhancing international and economic-environmental cooperation. Here we quantify international trade-induced air pollutant emissions (including black carbon (BC), organic carbon (OC), carbon monoxide (CO), ammonia (NH3), non-methane volatile organic compounds (NMVOCs), sulfur dioxide (SO2), nitrogen oxides (NOx)) and assess the contribution of five driving factors from 2004 to 2017. The results indicate a reversal of growth in global trade-related BC, CO, and NOx emissions since 2011, while there is a continuous increase in NH3, NMVOC, and CO emissions. The domestic consumption-based emissions and emissions embodied in exports (EEE) except for NH3 and NMVOC in East Asia show a consistent trend with global trade-related emissions, having a considerable contribution to global emission change. Sustained rising domestic consumption-based emissions and EEE in South Asia, Southeast Asia and Africa show that further cooperative and coordinated mitigation efforts are needed.
The impact of increased shellfish cultivation in the North Sea on the carbon cycle: a what-if scenario for the European Digital Twin Ocean. 
Authors: dols felix , lavaud Romain , Stechele Brecht , Troost Tineke , Cornacchia Loreta , van Duren Luca , Vilmin Lauriane , Meszaros Lorinc , El Serafy Ghada , Staneva Joanna , Drillet Yann
Published: March 2024

For the European Commission, the EDITO consortium is creating the European Digital Twin Ocean, a platform that integrates coastal and oceanic modelling tools with ocean observation databases and computing infrastructure. Building on EMODnet and CMEMS, EDITO Model Lab will contribute by making the next generation of ocean models more accessible.This work demonstrates one of the capabilities of the Digital Twin Ocean, focussing on human exploitation impacts on carbon fluxes. More specifically this what-if scenario is about the impact of upscaling the cultivation of shellfish in the North Sea on the carbon cycle. Upscaling the cultivation of shellfish is part of the envisioned “blue economy” and a promising option for multi-use of offshore wind parks. As shellfish are respiring organisms, they are a carbon source. At the same time shells are a carbon storage as they are built through biocalcification, a process that turns dissolved carbon and calcium into calcium carbonate.The research aims to quantify the effects of upscaling shellfish cultivation in the North Sea on the carbon cycle. This is done by implementing a biocalcification module (Stechele & Lavaud, manuscript submitted for publication in 2024), in the Dynamic Energy Budget (DEB) module integrated in Delft3D-FM’s water quality process library (Troost et al., 2010; Deltares, 2023). Our work includes assumptions about how harvesting accounts for calcium carbonate leaving the sea and is therefore sequestrated.
Development of a deep learning based system for heatwave detection using seasonal forecast data
Authors: Heidari Fatemeh , lin Qing , Díaz Esteban Yanet , Espitia Sarmiento1 Edgar , Xoplaki Elena
Published: March 2024

Heatwaves have been widely studied in recent years because of their major impact on human health, mortality, ecosystems, agriculture, and the economy. Globally, heatwaves are becoming more severe, longer, and recurrent with global temperature rise. Therefore, the study of heat waves and the development of an early warning system for prediction of regional heatwaves help climate preparedness and decision-making. In this research, we propose a heatwave prediction algorithm based on a deep learning model, a convolutional neural network (CNN). This CNN model is trained with reanalysis data ERA5 and real heatwave events from EMO observation data for years from 1993 to 2021. We illustrate the relationship between the patterns in geopotential height at 500 hpa (GPH), sea surface temperature (SST), and the real heatwaves that happened in the last 20 years. This study employs the hindcast data from SEAS5.1 with 25 ensemble members, available at C3S. GPH and SST from observation data are input to the model and the heatwave magnitude at every single grid point is the output. The heatwave is defined as a period of three or more consecutive hot days and nights when the daily maximum and minimum temperature (TX/TN) exceeds the long‐term (1993–2022) daily 90th percentile. For estimating the heat wave magnitude we accumulated TX exceedance the local 90th percentile for all heat wave days over a user-defined interval (monthly, seasonal, etc.) as in Zampieri et al. (2017), Toreti et al. (2019). The results show the CNN model using atmospheric circulation fields (SST and GPH) with adjusted parameters is able to forecast extreme events in Europe, and it can potentially enhance the AI-based early warning systems for extreme weather.Zampieri, M., Ceglar, A., Dentener, F., and Toreti, A. (2017). Wheat yield loss attributable to heat waves, drought and water excess at the global, national and subnational scales. Environmental Research Letters, 12 (6), 064008. doi:10.1088/1748-9326/aa723bToreti, A., Cronie, O., and Zampieri, M. (2019). Concurrent climate extremes in the key wheat producing regions of the world. Scientific Reports, 9(1), 5493. doi:10.1038/s41598-019-41932-5
Using Cascaded Diffusion Models and Multi-Channel Data Integration for High-Resolution Statistical Downscaling of ERA5 over Denmark
Authors: Quistgaard Thea , Langen Peter L. , Denager Tanja , Schneider Raphael , Stisen Simon
Published: March 2024

Central to understanding climate change impacts and mitigation strategies is the generation of high-resolution, local-scale projections from global climate models. This study focuses on Danish hydrology, developing models finely tuned to generate essential climate fields such as temperature, precipitation, evaporation, and water vapor flux.Employing advancements in computer science and deep learning, we introduce a pioneering Cascaded Diffusion Model for high-resolution image generation. This model utilizes our understanding of climate dynamics in a hydrological context by integrating multiple climate variable fields across an expanded North Atlantic domain to produce a model for stable and realistic generation. In our approach, 30 years of low-resolution daily conditioning data (ERA5) are re-gridded to match the 2.5x2.5 km 'ground truth' data (30 years of DANRA), and preprocessed by shifting a 128x128 image within a larger 180x180 pixel area, ensuring varied geographic coverage. This data, along with land-sea masks and topography, is fed as channels into the model. A novel aspect of our model is its specialized loss function, weighted by a signed distance function to reduce the emphasis on errors over sea areas, aligning with our focus on land-based hydrological modeling.This research is part of a larger project aimed at bridging the gap between CMIP data models and ERA5 and DANRA analysis. It represents the first phase in a three-step process, with future stages focusing on downscaling from CMIP6 to CORDEX-EUROPE models, and ultimately integrating model and analysis work to form a complete pipeline from global projections to localized daily climate statistics.
SLIDE – Southern Latitudes Island Dispersal Evaluation 
Authors: Pearce David , Cockerton Luke , Malard Lucie , Schmale Julia , Convey Peter
Published: March 2024

The risks of invasions of remote ecosystems by new microorganisms is a major threat as they are likely to impact the diversity and function of resident communities and local ecosystems. In the Antarctic, aerial transport is the primary source of new biological inputs. Airborne communities are believed to be influenced by environmental and climatic conditions, which are already changing rapidly on a global scale, but especially in the Polar regions. Yet, the influence of climate change, weather patterns and environmental conditions on these airborne communities are still unclear. One of the key challenges in understanding these processes is the high heterogeneity and variability of airborne samples. Following the Antarctic Expedition (ACE), in which daily samples were taken around the Antarctic continent to provide spatial distribution of airborne microorganisms, a time series was conducted at one of the ACE field sites (South Georgia) over a period of two weeks, at both high and low altitude to establish the daily variability between aerobiological sample sets. Results showed that although there was indeed a high heterogeneity and variability within the sample sets and across sample types, reliable patterns in the overall diversity could still be determined, and hence single daily samples can still provide useful assessment of aerial diversity over spatial and temporal scales in the Antarctic. 
Embedded coherent structures from MHD to sub-ion scales in turbulent solar wind: PSP observations at 0.17 au
Authors: Alexandrova Olga , Vinogradov Alexander , Demoulin Pascal , Artemyev Anton , Maksimovic Milan , Mangeney Andre , Bale Stuart
Published: March 2024

We study intermittent coherent structures in solar wind magnetic turbulence from MHD to kinetic plasma scales using  Parker Solar Probe data during its first perihelion (at 0.17 au). These structures are energetic events localized in time and covering wide range of scales. We detect them using Morlet wavelets. For the first time, we apply a multi-scale analyses in physical space to study these structures. At large MHD scales, we find (i) current sheets including switchback boundaries and (ii) Alfvén vortices. Within these large scale events, there are  embedded structures at smaller scales: typically  Alfvén vortices at ion scales and a compressible vortices at sub-ion scales. To quantify the relative importance of different type of structures, we do a statistical comparison of the observed structures with the expectations of models of the current sheets and vortices. This comparison is based on amplitude anisotropy of magnetic fluctuations within the structures. The results show the dominance of Alfvén vortices at all scales in contrast to the widespread view of dominance of current sheets. The number of coherent structures grows from the MHD to the sub-ion scales. For one MHD scale structure there are ∼10 ion scale structures and ∼50  sub-ion scale structures. In general, there are multiple structures of ion and sub-ion scales embedded within one MHD structure. There are also examples of non-embedded structures at ion and sub-ion scales.
Regionally trained models for mapping aboveground biomass from Remote Sensing data fusion: a comparison of the capabilities of Machine Learning in 4 different biomes.
Authors: Perpinyà-Vallès Martí , Huertas Claudia , Escorihuela Maria José , Ameztegui Aitor , Romero Laia
Published: March 2024

In recent years, multiple remote sensing technologies have been used to quantify aboveground biomass (AGB) at different scales, from regionally trained models to global maps. The former are capable of providing higher resolution and accurate estimations albeit for smaller regions. Tailoring model weights and inputs to a specific biome or region have proved to be effective to obtain better results. Global maps, on the other hand, provide an attempt to standardizing AGB mapping at slightly to moderately lower resolutions and tend to have differences between them. A similar standardization with the benefits of regional mapping, applied across biomes, has yet to be available. For that, the first step would be comprehensively comparing state-of-the-art regional and local studies. However, existing inconsistencies in the different models and inputs used, which are often region-specific, make it impracticable.This study addresses the need for a comparison of a single methodology consistent across different biomes in order to understand the nuances that drive the estimation of AGB. We present a data fusion approach to mapping aboveground biomass at a 20m resolution using regionally trained, regression-enhanced Random Forests in 4 different biomes: semi-arid savannas in the Sahel region, dense tropical forests in Brazil, Mediterranean forests in coastal and pre-coastal areas of Catalonia, and temperate/boreal forests in Minnesota. GEDI L4A AGB data (25-m discrete footprints) is used to train a regression model in each study area. We derived predictors from Sentinel-1 SAR, Sentinel-2 multi-spectral and Digital Elevation Model (DEM) datasets, which are common for all locations. Additionally, auxiliary data such as proximity to coastlines, human-made structures or bio-climatic variables are used to enhance predictions in saturation-prone areas. Additional to the goodness of adjustment to the training data from GEDI, we carried out a thorough validation of the results using in-situ data from Forest Inventory plots gathered in all 4 study regions. This enables a comprehensive comparison of the capabilities of Machine Learning modelling to adapt to the particular characteristics of each ecosystem. An in-depth analysis is carried out to find the most important predictor variables in each biome, as well as to assess the accuracy that can be expected across a wide range of AGB values.
Consecutive Disasters: an approach to multi-hazard exposure, vulnerability, and recovery evaluation at global scale 
Authors: Borre Alessandro , Trasforini Eva , Ottonelli Daria , Ghizzoni Tatiana , Rudari Roberto
Published: March 2024

In an era marked by consecutive natural disasters, an advanced methodology for risk and impact assessment is critical. Recent disasters in Puerto Rico in 2017, Nepal between 2015 and 2017, and Indonesia in 2018 have highlighted the urgency of identifying regions at high risk of consecutive natural events, which are also characterised by vulnerabilities in organizational, social, and economic aspects that heavily influence the response and recovery stages following a disaster. The initial phase involved an analysis of the EM-DAT database to chart a global impact timeline within a multi-hazard scenario. Subsequent detailed assessments focused on riverine floods, individually and in conjunction with pluvial and wind events, across specific countries.The research goal is to identify countries where the complex interplay between consecutive disasters is crucial to risk evaluation, given the significant impact on the components of exposure and vulnerability. Initially adopting a single hazard approach, the research analyses the sequence and probability of flood events alongside local exposure levels to identify at-risk countries. Subsequently, the study expanded to incorporate a multi-hazard perspective, including floods, intense rainfall, and strong winds, within a specific country to evaluate the relevance of this innovative approach in risk assessment. Early findings underscore the necessity to adapt damage assessments to the specific needs and scales of the regions studied, accounting for both single and multiple hazard scenarios.Results demonstrate notable disparities in the annual exposure value percentage affected by consecutive disasters, providing key insights for stakeholders, academics, policymakers, and local administrators. This information provides them with a complex understanding of risk assessment and simplifies the formulation of more effective mitigation strategies. In conclusion, an integrated assessment of consecutive natural disasters alongside regional exposure levels provides a comprehensive framework for identifying areas in need of innovative risk management. Interdisciplinary cooperation is essential to comprehensively understand and improve the collective response and recovery from natural disasters, with particular emphasis on the socio-economic and infrastructural factors that distinctly affect the dynamics of consecutive events.
Classification of Phreatic Overgrowths on Speleothems (POS) from the Mallorca littoral caves
Authors: Entrena Ana , Auqué Luis F. , Gimeno María J. , Fornós Joan J.
Published: March 2024

Phreatic Overgrowth on Speleothems (POS) are a specific type of speleothem that growth at the surface of the brackish lakes in littoral caves. These lakes are direct or indirectly related to the height of the sea level, therefore, the POS precipitates at the height of the sea in the moment of their growth. This condition makes the POS a perfect marker of past sea level.These speleothems are very unusual and have only been found in few caves around the world. Up to the present, most of these deposits have been located on the island of Mallorca, where the largest collection of this type of speleothems have been studied.This study presents a complete classification of POS in hand-size scale and in thin section. The first one is based on the internal and external morphology of the POS and its acquired shape depending on the substrate on which these precipitates grow. The second one, related to the thin section study, allows to recognize a variety of crystalline fabrics: needle-like aragonite crystals (An), fibrous fascicular optic calcite (Ffo), columnar fascicular optic calcite (Cfo), columnar calcite (C), mosaic calcite (Mc), mosaic calcite with aragonite needles (MCan) and micrite (M) and microsparite calcite fabric (Ms). , Some of these fabrics were previously described in other speleothems (as stalactites or stalagmites) and others are new, not previously described in speleothems.All this information shows several important ideas: 1) most of the POS precipitate around previous stalactite-type vadose speleothem; 2) aragonite POS are mainly globular and fan shaped in their external and internal morphology, respectively, and aragonite mineralogy only appears in needle-like crystal fabric; 3) calcite POS are related to branched internal and external morphology and present more variability in their crystal fabric, being the mosaic type the most common. The data obtained have been used to identify some relationships between the precipitation conditions of POS and the features of these precipitates. This classification and the conclusions of the precipitation conditions demonstrate the importance of POS as a proxy. Moreover, this study helps to understand the precipitation process of POS and can be implemented and reviewed in POS deposits of other parts of the world.
Boreal forest fire monitoring by GNSS, referring to the 2011 BORTAS experiment
Authors: Mascitelli Alessandra , Aruffo Eleonora , Chiacchiaretta Piero , Realini Eugenio , Gatti Andrea , Fumagalli Alessandro , Di Carlo Piero
Published: March 2024

During 2010 and 2011, BORTAS (Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites) experiment has been carried out over northern America and Canada with the aim of studying the air masses which contain emission products from boreal wildfires [1]. In this study, the goal is to understand the potential of ground-based GNSS sensors in monitoring fire plumes. In relatively stable weather condition, strong correlation between GNSS-ZTD (Zenith Total Delay) and PM (Particulate Matter) can be found [2]; reflecting ZHD (Zenith Hydrostatic Delay) the delay caused by the standard dry atmosphere, the delay caused by PM is included in ZWD (Zenith Wet Delay) [3]. Referring to the 2011 BORTAS experiment, data from GNSS ground-based sensors located in the plume trajectories have been analysed. To evaluate the GNSS approach sensitivity, fresh plumes, aged plumes, and background plumes have been studied considering different flights. [1] Palmer, P. I., Parrington, M., Lee, J. D., Lewis, A. C., Rickard, A. R., Bernath, P. F., ... & Young, J. C. (2013). Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) experiment: design, execution and science overview. Atmospheric Chemistry and Physics, 13(13), 6239-6261.[2] Guo, M., Zhang, H., & Xia, P. (2020). A method for predicting short‐time changes in fine particulate matter (PM2. 5) mass concentration based on the global navigation satellite system zenith tropospheric delay. Meteorological Applications, 27(1), e1866.[3] Guo, J., Hou, R., Zhou, M., Jin, X., Li, C., Liu, X., & Gao, H. (2021). Monitoring 2019 forest fires in southeastern australia with GNSS technique. Remote sensing, 13(3), 386.
Effect of initial states on the uncertainty in sea-level rise projections until 2100 and beyond
Authors: Schöll Simon , Klose Ann Kristin , Reese Ronja , Jourdain Nicolas , Winkelmann Ricarda
Published: March 2024

Projections for Antarctica's contribution to global sea-level rise until 2100 range from a positive contribution due to increased ice loss, caused by an increase in surface melt and in dynamic loss of grounded ice, to a negative contribution due to increased snowfall. The high uncertainties in projections can be attributed to different sources, including emission trajectories, climate forcings from Global Circulation Models (GCMs) and Regional Climate Models (RCMs), as well as inter- and intra-ice-model differences.Here, we present an ensemble of future projections based on simulations with the Parallel Ice Sheet Model (PISM), driven by multiple climate forcings. These are based on several initial states and ice-sheet trajectories over the historical period, consistent with observations.We assess the influence of the initial states on the spread in projected sea-level change and compare these to the uncertainties arising from climatic forcings, to compare the sources of uncertainty in future sea-level projections until 2100 and beyond.
Are space-for-time substitution approaches appropriate in phenology research? Results from a macroecological approach
Authors: Silva-Cala Andrea L. , Rauschkolb Robert , Bucher Solveig Franziska , Kattge Jens , Zaehle Sönke , Römermann Christine
Published: March 2024

Knowing and understanding variation in plant phenology is important for three main reasons. 1. Plant phenology is sensitive to climate change, 2. Plant phenology influences the dynamics and interactions between species, and 3. It drives important ecosystem functions. Still, large-scale, macroecological analyses spanning several phenological databases from various continents and environmental conditions are scarce.Here we present the first results of a global analysis of the relationship between phenological events and functional traits in herbaceous plant species as a basis for predicting variations in ecosystem functions. More specifically, we analyzed phenological data from three different data sources: the PEP725 database from Europe, the NPN database from the US, and the PhenObs database from a global network of botanical gardens (www.idiv.de/en/phenobs). We evaluate spatio-temporal variations of three phenological stages: leaf emergence, open flowers, and onset of senescence. We linked phenological variations in space as well as phenological variations in time with variations in temperature (extracted from CRU TS database v4.07) of the observation periods and observation sites, respectively. Deduced associations between phenology and temperature across time and space were compared between Europe and North America, and between controlled environments in botanical gardens and natural environments.First results indicate that the direction of phenological responses to changes in temperature is consistent across time and space. However, the variability of this response is higher across time compared to space. This higher variation phenology is not explained by differences in variations of temperature, but we assume that other environmental and climatic factors could vary more strongly across the spatial compared to the temporal gradient. The phenological responses of plants growing in botanical gardens to increasing temperature, were less variable compared to plants growing in uncontrolled environments. We attribute these differences to botanic garden management, such as irrigation, which mitigates the effects of increased temperature and drought on herbaceous species phenology. On our poster, we will further determine the climatic factors and functional traits that explain inter- and intraspecific phenological variability.
Calibration uncertainty of optical isotope ratio spectroscopy measurements of methane and field comparison with mass spectrometry
Authors: Rennick Christopher , Yeo Cameron , Wilson Freya , Safi Emmal , Hopkinson Emily , Hillier Aimee , Pearce Ruth , France James , Lanoiselle Mathias , Lowry David , Arnold Tim
Published: March 2024

The stable isotopic signatures of atmospheric methane (CH4) – carbon δ 13C(CH4) and hydrogen δ 2H(CH4) – are tracers that can help distinguish the relative contributions from different emissions sources. Optical isotope ratio spectrometers (OIRS) deployed at atmospheric monitoring stations have the capability for continuous measurements, providing time series data that can complement sampling campaigns using isotope ratio mass spectrometry (IRMS). OIRS instruments, however, require larger volumes of calibration gases than IRMS and the measurement is of the isotopologues directly (12CH4, 13CH4 and 12CH3D) rather than conversion to CO2 and H2. Here, we demonstrate the calibration method for Boreas, a preconcentrator-OIRS system deployed at an atmospheric monitoring station in the South of England and show that these measurements are compatible with those made by IRMS. Measurements with Boreas are referenced to a whole air working standard that is sampled in sequence with air, following the principle of identical treatment. We show the results of a field comparison to IRMS measurements of bag samples taken from the same air inlet simultaneously with the preconcentrator.The calibration method uses mixtures prepared gravimetrically at a range of amount fractions from a single high-purity CH4 parent that has been characterised for δ 13C and δ 2H by IRMS. This method is capable of calibration over a wide range of amount fraction and isotopic composition. A rigorously derived uncertainty budget shows that the major contributions are from the uncertainty in the assignment of δ 13C and δ 2H of the methane parent and the spectrometer, with minimal contribution from uncertainty in the amount fraction of the standards.
Experimental and numerical thermos-kinetic modelling of hydrothermal alteration of volcanic rocks - Example of La Soufrière de Guadeloupe (Eastern Caribbean , France)
Authors: Décossin François , Martel Caroline , Arbaret Laurent , Champallier Rémi , Penhoud Philippe , Azaroual Mohamed , Muller Fabrice , Komorowski Jean-Christophe , Heap Michael
Published: March 2024

Volcano unrest associated to ascent of magmatic fluids (magma, brines, gases) at shallow depths in the presence of a very active hydrothermal system, can promote or enhance extensive hydrothermal rock alteration and form fragile discontinuities within the edifice. A process that can favour flank instability and culminate in partial flank collapse, engendering significant risks to the surrounding population. In the MYGALE ANR project, we focus on hydrothermal alteration timescales of andesitic rocks to better assess the hazard of volcano flank instability at La Soufrière de Guadeloupe (Eastern Caribbean, France). The conditions and kinetics of hydrothermal alteration reactions of the volcanic rocks of La Soufrière lava dome are determined by three approaches: mineralogical, experimental, and by modelling. Firstly, we characterized the natural alteration sequence of 20 samples from the lava dome and lava flows showing different degrees of alteration and porosity. SEM and XRD analyses of the samples show that the plagioclases are replaced by secondary minerals such as kaolinite, natroalunite, and amorphous silica. Secondly, we performed time-series fluid flow-through experiments, in which fluids are circulated through a pristine and porous andesite core (representative of the unaltered state of the present-day lava dome at La Soufrière). We varied temperature (200-250 °C), pressure (100-150 bar), duration (from days to months), and fluid composition (H2O-HCl mixtures). Rock permeability is measured in-situ and the mineralogical changes are characterized by post-experiment using various methods (SEM, EDS, EMPA, X-ray microtomography, and XRD). A sharp decrease in permeability of four orders of magnitude (from 10-14 to 10-18 m2) during the first 3-6 days was observed when using pure water as the percolating pore fluid. The cause of this large and fast decrease in permeability is currently being investigated. Experiments using H2O-HCl fluids are in progress attempting to reproduce the alteration sequence of the natural samples. Thirdly, we performed thermodynamic and kinetic numerical modelling using Perple_X, Phreeqc, and GEM-Selektor codes, in order to better constrain the conditions (especially the fluid phase composition) for hydrothermal alteration and to explore the alteration kinetics for timescales longer than those attained experimentally.
G3P v1.12: Advancements of a Global Groundwater Storage Anomaly Dataset from Satellite Gravimetry
Authors: Haas Julian , Sharifi Ehsan , Dorigo Wouter , Jäggi Adrian , Ruz Vargas Claudia , Boergens Eva , Dahle Christoph , Dobslaw Henryk , Dussaillant Inés , Flechtner Frank , Lictevout Elisabeth , Kosmale Miriam , Luojus Kari , Mayer-Gürr Torsten , Meyer Ulrich , Paul Frank , Preimersberger Wolfgang , Reißland Sven , Zemp Michael , Güntner Andreas
Published: March 2024

The Global Gravity-based Groundwater Product (G3P) has evolved with a new version (V1.12), bringing substantial enhancements to our satellite-based groundwater storage anomaly dataset—a prototype for a future product within the EU Copernicus Climate Change Service. Groundwater as the world's largest distributed freshwater storage, is a vital resource for human, industrial, and agricultural needs. Despite its significance, Copernicus lacks a service delivering operational, observation-based, and globally comprehensive data on changing groundwater resources. G3P could serve as a pivotal extension to the Copernicus portfolio. Leveraging the unique capabilities of GRACE and GRACE-FO satellite gravimetry, G3P monitors subsurface mass variations employing a mass balance approach. This involves subtracting the satellite-based and partly model-based water storage compartments (WSCs) snow water equivalent, root-zone soil moisture, glacier mass and surface water storage from GRACE/GRACE-FO monthly terrestrial water storage anomalies (TWSA). Ensuring a consistent subtraction of individual WSCs from GRACE-TWSA involves filtering them similarly to GRACE-TWSA, using filters whose type and parametrization had to be derived by spatial correlation analyses. The G3P dataset spans more than two decades (from 2002 to 2023) with a monthly resolution and global coverage at 0.5-degree spatial resolution. Notable updates in V1.12 compared to previous versions include an extended data time period until September 2023, modifications of the methodology of several WSCs, and the incorporation of new evaluation results.This study has received funding from the European Union’s Horizon 2020 research and innovation programme for G3P (Global Gravity-based Groundwater Product) under grant agreement nº 870353.
Spatial patterns of DO events in Greenland ice core chemistry
Authors: Kjær Helle Astrid , Vinther Bo , Svensson Anders , Rasmussen Sune , Blunier Thomas , Erhardt Tobias , Harlan margareth , vallelonga Paul , Maffezoli Niccolo , Gkinis Vasileios , Sowers Todd , Menking Andy , deCampo Aylin , Morris Valerie , Vaughn Bruce , Buizert Christo , Steffensen Jørgen Peder
Published: March 2024

Deep ice core drilling efforts have been ongoing since the 1960’ and several records of Greenland impurities exist thanks to huge multiple nation efforts and the work of many dedicated people over the years and include Camp Century, Dye3, GRIP, GISP2, Renland, NGRIP, NEEM, RECAP and the new EGRIP ice core. The 25 Dansgaard-Oeschger (DO) events, first named in the Greenland ice core δ 18O signal from GRIP, are found in all deep Greenland ice cores with a significant corresponding signal also reflected in chemistry and impurities contained in the ice.  Continuous flow analysis (CFA) is the preferred method  to investigate the long Greenland ice cores for their impurity content and often includes NH4+ , Ca2+ , and Na+ ions, while Ion Chromtography (IC) was previously utilized. The chemical impurities besides being influenced by transport and accumulation patterns, provide information about forest fires, wind-blown dust, and sea ice, respectively.  We show here CFA measurements performed in Copenhagen in 2019 on the Dye3 old core at depths of 1753–1820m and 1865–1918m representing both Holocene, Younger Dryas and Glacial sections (GS 5 to 12) and the high accumulation RECAP ice core CFA profile. The ReCAP ice core extends 584.11m and while the glacial section is strongly thinned and covers just 20 meters of the ReCAP core, it nonetheless due to the high resolution of the CFA measurements done in 2015 and 2016, cover all 25 expected DO event. Here we present these two datasets of Dye 3 and RECAP by CFA done at University of Copenhagen and compare for DO'swith other central Greenland ice cores with the aim to constrain spatial patterns of DO events in Greenland ice core chemistry records. 
CAMELS-DE: Benchmark dataset for hydrology – significance, current status and outlook
Authors: Dolich Alexander , Ebeling Pia , Stölzle Michael , Kiesel Jens , Götte Jonas , Guse Björn , Haßler Sibylle , Mälicke Mirko , Tarasova Larisa , Heidbüchel Ingo , Hauffe Corina , Müller-Thomy Hannes , Loritz Ralf
Published: March 2024

CAMELS datasets are recognized in the hydrological community as consistent and comprehensive benchmark datasets for hydrological and meteorological analyses. CAMELS stands for "Catchment Attributes and MEteorology for Large-sample Studies”. CAMELS datasets link landscape and catchment attributes (e.g. land use, geology, soil properties), hydrological time series (e.g. water level, discharge) and meteorological time series (e.g. precipitation, air temperature) in a large number of catchment areas. They clearly indicate the uncertainties and processing of individual variables and thus enable the comparison of models and data in different landscapes, but also contribute to the general understanding of hydrological processes across landscapes. This is crucial for assessing the consequences of the climate crisis and improves the basis for water resource management decisions. Although CAMELS datasets are intensively used in other countries, such a dataset is still lacking for Germany.This contribution highlights the crucial importance of consistent and easily accessible benchmark datasets for hydrological research and education. We discuss both the challenges faced so far in compiling the dataset and the future ambitions of the project. In addition, an overview is given of the scope of the first version of the CAMELS-DE data set, which will include around 2,000 measuring stations with daily time series of discharge and water level with an average length of nearly 50 years in mainly small and medium-sized catchments. Also included are the landscape and catchment attributes as well as meteorological time series. A key focus is on the easy availability and straightforward import of data into programming environments. We discuss how such benchmark datasets not only increase efficiency in the use of environmental data, but also play a key role in ensuring the reproducibility of research results. Especially in the age of machine learning learning, they form an indispensable basis for modern, data-driven hydrology. By integrating CAMELS-DE into the research landscape, we want to emphasize that data publications and benchmark datasets are much more than a by-product of a doctoral thesis, but rather the basis and key to modern environmental science.
Numerical analysis of polar orbits for future Enceladus missions
Authors: Parihar Taruna , Hussmann Hauke , Wickhusen Kai , Caritá Gabriel , Stark Alexander , Oberst Jürgen , Benedikter Andreas , Rodrigues Silva Filho Eduardo , Matar Jalal , Galas Roman
Published: March 2024

Saturn's moon Enceladus gained limelight with the discovery by the Cassini spacecraft of plumes of ejected gas and ice particles from pronounced linear structures in its South Pole region called “Tiger Stripes". The small (500 km) satellite is believed to have a porous rocky core and an ice shell, separated by a global subsurface saltwater ocean. The tidal heating potentially aids in driving chemical reactions in the moon’s interior which makes it a very promising candidate where the right conditions for life formation may exist. This makes Enceladus a prime target for a future spacecraft remote sensing mission. Due to the strong gravitational perturbations caused by Saturn, the higher gravitational moments of Enceladus and additional perturbations by the other moons of Saturn, the dynamic environment for artificial satellites around Enceladus is extremely complex. As a consequence, the search for natural stable orbits is far from trivial. We carried out comprehensive numerical integrations of spacecraft orbits, with the aim to find suitable candidate orbits for a remote sensing mission. A polar orbit is desirable to further investigate the tiger stripes region, and for mapping of the global subsurface ocean. Also, the orbit should provide repeated coverage for various instruments on board the satellite. All the relevant perturbations caused by the Sun, Jupiter, Saturn and its other moons, the higher degrees and order of Enceladus’ gravity field and solar radiation pressure are taken into account. We searched for suitable orbits in inertial space by varying orbital parameters such as semi-major axis (350 to 450 km), inclination (40° to 120°) and longitude of ascending node. Moderately inclined orbits (inclination between 45° and 60°) covering the equatorial and mid-latitude regions of Enceladus were found to be stable from several months up to years. In contrast, the more useful polar mapping orbits were found to be extremely unstable due to the so-called “Kozai mechanism”, due to which a spacecraft would impact the moon’s surface within a few days. However, an example of a highly inclined orbit was found with inclination of approximately 79°, which had an orbital life time of 13 days. A longer mission in this orbit would require correction maneuvers every approximately 10 days. This would provide coverage of the tiger stripes region and allow for a global characterization of the ocean. We also determined the delta-v that would be necessary to maintain such an orbit over a mission of several months. Also, special attention was paid to satellite formation flying in this orbit to maintain a stable baseline for a distributed radar sounder system (across-track formation of multiple satellites).
A detailed view of the magmatic plumbing system beneath Askja Volcano, Iceland, from ambient noise tomography 
Authors: Fone Joseph , Winder Tom , Rawlinson Nicholas , White Robert , Brandsdóttir Bryndís
Published: March 2024

The volcano Askja in the Northern Volcanic Zone (NVZ) of Iceland last erupted in 1961 and has been steadily deflating from the 1970s until August 2021 when GPS and InSAR measurements confirmed that it had begun re-inflating. The NVZ has hosted a network of seismic stations operated by the University of Cambridge Volcano Seismology group since 2006. In the summer of 2023, this network has been augmented by 12 three component nodes that will record for ~2 months in addition to 10 broadband instruments that will be left for a year in or around the caldera of Askja with an average station spacing of ~1-2 km. The combination of the long-term recordings from the backbone network during deflation and the more recent short-term dense recordings will provide a unique dataset to examine how this switch from deflation to inflation may effect the seismic velocity structure beneath the volcano, thereby providing new insight into the underlying magmatic system. In this study, we present preliminary results from the application of ambient noise tomography to this dataset to try and image any changes in the magmatic system, which will involve stacking different periods of ambient noise cross-correlations to obtain two sets of dispersion curves that are sensitive to the subsurface velocity structure beneath Askja prior to and following the switch to reinflation in August 2021. This allows us to produce 3D models of shear wave velocity that can be compared to help elucidate changes in the plumbing system that occurred due to this switch. The dense deployments in the caldera have the advantage of allowing us to measure dispersion curves to high frequencies due to the short interstation distances, which is expected to yield more information on shallow subsurface structure where GPS and InSAR measurements appear to indicate that the source of the inflation is concentrated.