bluuebunny/crossref_metadata_2025 huggingface dataset:
Multivariate forecasting of tropical cyclones using combined neural networks
Authors: Hudozhnik Yegor , Windisch Andreas
Published: March 2024

Tropical cyclones (TCs) are hazardous and destructive events that pose a threat to human life every year. Since the beginning of the meteorological observation era, predicting the behavior of cyclones has always been an issue. It has been proven that with climate change due to global warming, the proportion of stronger TCs increases, increasing the danger and potential harm of TCs.Numerous techniques have been developed over the years and are used in ensembles to detect, predict, and classify TCs. Nevertheless, the tasks in the field of TC prediction are considered challenging because the development of TC systems exhibits nonlinear behavior and depends on many environmental factors.Conventional TC forecasting methods are computationally intensive and require a relatively large amount of energy and time. Due to ongoing global warming, the behavior of TCs may constantly change and therefore requires the use of modern, environmentally friendly and more flexible learning methods for estimating and predicting the future behavior of TCs.In recent years, the study of the application of Deep Learning (DL) in this area proved to be highly effective. These methods are designed to facilitate the prediction process, as well as automatically detect possible trends that may occur over time. DL methods provide the most modern statistical analysis and can thus exert their influence on research.In our research, we have applied a novel approach of incorporating two-dimensional meteorological data to forecast the track and intensity of TCs together with scalar data of location, intensity, and temporal information. We have built and tested numerous sequence-to-sequence forecasting models based on ConvLSTM2D neural network layers and tested two-dimensional data compression using autoencoders as a data preparation technique. Our experiments have shown that the multivariate forecast yields perspective results. We have also succeeded in detecting the influence of recent trends in changes of TC behaviour in recent years and proved the ability of neural networks to fit themselves to those trends.
A 1500-year flood history in Romania using multi-archive reconstructions
Authors: Rădoane Maria , Perşoiu Ioana , Florescu Gabriela , Perșoiu Aurel
Published: March 2024

This study integrates documentary, instrumental, archaeological and sedimentological data to reconstruct periods of increased flooding in present-day Romania over the last 1500 years.We identified 22 flood-rich periods between AD 600-650, 830-930, 990 – 1020, 1060 – 1110, 1136 – 1165, 1195 - 1245, 1304 - 1317 and 1340 – 1373, 1400 – 1440, 1460 – 1470, 1490 – 1540, 1560 – 1580, 1592 – 1622, 1635 – 1657, 1667 - 1675, 1699 - 1731, 1771 - 1793, 1831 – 1864, 1890 - 1920, 1930s, 1970s - 1980s, 1990s – present. Our reconstructions show an increase in the incidence of floods during the Medieval Climate Anomaly and towards the end of the Little Ice Age.In order to understand the potential causes behind these flooding events, we have used reconstructions of seasonally-distinct air temperature, precipitation amount and atmospheric circulation patterns based on an array of proxy records (e.g., cave ice and speleothem stable isotopes, tree ring-based proxies).The most extensive floods were recorded between AD 1050-1250, mostly in the extra-Carpathian region, attributed to the advance of humid Eastern Mediterranean air masses. Currently, there is no conclusive information about their magnitude during the Migration Period, although the limited information of fluvial origin supports a reduced flood magnitude compared to the Medieval Climate Anomaly. Over the last 500 years, floods with maximum geomorphological effects occurred at the end of the 18th and 19th centuries (1770 – 1800 and 1880 – 1920) across the entire study area, against the background of an unstable climate, marked by the intensification of westerly Atlantic circulation and frequent northward incursions of Eastern Mediterranean cyclones. These were followed in magnitude by recent events (1990 - present), favored predominantly by warm and humid Eastern Mediterranean air masses, and the intensification of the westerly circulation of Atlantic origin at the onset of the Little Ice Age (1460 – 1470 and 1490 – 1530).Alongside the climate signal, floods in the last 500 years also exhibit a strong anthropogenic component, accentuated in the last 250 years.
Cross-Domain Interoperability and Deeptime Digital Earth Data
Authors: Hodson Simon
Published: March 2024

This presentation, as part of a DDE-convened Union Symposium at EGU, will discuss avenues to pursue to enable greater Interoperability and Reusability of Deeptime Digital Earth Data, particularly in cross-domain research scenarios.CODATA is the Committee on Data of the International Science Council (ISC).  Consequently, an important part of its mission is to engage with International Scientific Unions and related initiatives, on data issues.  The ISC has entrusted CODATA to develop a programme of activity: ‘Making Data Work for Cross-Domain Grand Challenges’.  After some exploratory work, the flagship activity is the WorldFAIR project which focuses on the implementation of the FAIR principles both within and across 11 different domain and cross-domain case studies.  Other related work includes the recommendations on FAIR vocabularies, with the International Union for the Scientific Study of Populations (report https://doi.org/10.5281/zenodo.7818157), and in relation to the ISC-UNDRR Hazard Implementation Profiles.  Similarly, CODATA is working with a number of International Scientific Unions, notably IUPAC, around the Task Group on Digital Representation of Units of Measure.The common threads of this work are both to encourage the adoption and implementation of the FAIR principles, and to explore the requirements for better enabling cross-domain research.  Such work is of paramount importance: the major global scientific and human challenges of the 21st century (including climate mitigation and adaptation, disaster risk reduction, the interplay of society, the economy and energy policy) can only be addressed through cross-domain research that seeks to understand complex systems through machine-assisted analysis at scale.  Our capacity for such analysis is currently constrained by the limitations in our ability to access and combine heterogenous data within and across domains.CODATA has recently concluded a Memorandum of Understanding with the Deeptime Digital Earth initiative.  This agreement indicates a number of shared interests.  Particularly important is collaboration among DDE, IUGS CGI (Commission for Geosciences Information), and the wider CODATA and FAIR communities on the further development and representation of key terminologies.  Additionally, through a case study approach, DDE, IUGS CGI, CODATA and other partners plan to explore the applicability of the WorldFAIR methodology and the use of FAIR Implementation Profiles to understand FAIR requirements, progress and alignment.  Finally, the applicability of the emergent Cross-Domain Interoperability Framework (CDIF) will be explored, and further refinements and recommendations made. This presentation will describe the context for this collaboration and outline the specific activities.  It will be an important opportunity to socialise the community to this initiative, to get feedback and advice on the approach and to invite collaboration and expert input from the wider EGU community.
Spatio-temporal dynamics of four pine species recolonization in Southern Europe human-disturbed forestlines
Authors: Vitali Alessandro , Garbarino Matteo , Camarero J. Julio , Toromani Elvin , Spalevic Velibor , Čurović Milić , Urbinati Carlo
Published: March 2024

In this study we compared the encroachment patterns of four pine species across anthropogenic forestlines in Southern Europe. Using a synchronic approach, we studied structure and recent spatio-temporal patterns of pine recruitment at upper forestline ecotones in Albania, Italy, Montenegro and Spain. Within altitudinal transects we mapped and sampled 964 living individuals of Pinus heldreichii, Pinus peuce, Pinus sylvestris and Pinus uncinata growing above the current forest line. We measured their basal diameter, total height, and counted the number of seed cones. We differentiated seedlings (height < 0.5 m) from saplings (0.5m≤height < 2 m) and trees (height≥2 m). From individuals with basal stem diameter>4 cm we extracted one increment core for cambial age determination and tree-ring width measurements. On smaller specimens, we estimated the age by counting annual internodes (terminal bud scars) along the whole stem. We compared the ground cover around each pine, applied point pattern analyses, modelled the probability of seed cone production and estimated the average distance of seed dispersal. The four pine species exhibited heterogeneous density values and the overall averaged means ranged 2–7 cm for basal diameter, 54–106 cm for total height and 9–20 years for cambial age, suggesting a recent encroachment process. None of these structural variables decreased with increasing relative altitude and distribution patterns exhibited a few higher density spots but not cohort spatial structure. Ground cover differed between species and more significantly between size classes. Grass was the most frequent type at all sites except for P. sylvestris where shrubs prevailed. Basal area increments increased from 1990 and stabilized in recent years at all species except for P. peuce. Height and basal diameter predicted cones production better than cambial age. P. heldreichii and P. peuce dispersed seeds at longer distances than P. uncinata and P. sylvestris, suggesting different potential for further encroaching. Pine recruitment above the forestlines is quite synchronic at all sites (last 30 years), but in some cases it appeared as a high altitude tree densification process, whereas in others as a starting forestline advance.
Intraseasonal atmospheric variability under climate trends
Authors: Maraldi Bernardo , Dijkstra Henk , Ghil Michael
Published: March 2024

Low-order climate models have played an important role in understanding the low-frequency variability of the atmospheric circulation and how it can be affected by trends in anthropogenic forcing. A simple quasi-geostrophic model of the midlatitudes’ circulation (Lorenz, Tellus, 1984, 1990) is studied from the perspective of the theory of nonautonomous dynamical systems (NDS: e.g., Ghil et al., Physica D, 2008).We start with a study of the model’s behavior in the absence of time dependent forcing and determine in this case its steady states. A bifurcation analysis is carried out in order to identify distinct regime behavior types – stationary, periodic and chaotic – in the model’s parameter space. Next, we study the nonautonomous system with a meridional temperature gradient that varies seasonally, according to changes in insolation. The snapshot attractor (Tel et al., JSP, 2020) of the seasonally forced model is compared with the standard forward attractor of the autonomous model for two distinct epochs of the year, at peak summer and peak winter. In both cases, the effects of the change in forcing are reflected in a clear change of shape of the attractor. Predictability is lost in both cases: the summer attractor loses its periodicity when the forcing is seasonal. The winter one favors energy transport through one of the two wave components included in the model. For the same value of the forcing, the structure of the attractor in the autonomous case is quite different from that in the nonautonomous one.Finally, the meridional forcing is subjected to climate trends, both positive and negative, since the jet intensity changes in opposite directions at low and high altitudes (Lee et al., Nature, 2019). The analysis of the snapshot attractor of the system under climate trends suggests that the model does not follow the geostrophic assumption in certain ranges of the forcing, as the average zonal flow does not always show the expected dependence on the equator-to-pole temperature contrast. On the other hand, the energy transported by the eddies does follow the sign of the climatic trend. Overall, distinct effects are observed. Chaotic behavior can be completely suppressed in favor of a regularly periodic one and vice-versa. At the same time, circulation patterns can change, suddenly disappear, and be restored.In general, the snapshot attractor proved to be a robust tool in studying the internal variability of the midlatitude circulation, as well as the changes arising in it from anthropogenic forcing trends. The distinct regimes of behavior are being examined more closely by advanced spectral analysis methods (Ghil et al., Rev. Geophys., 2002) to better understand the effects of climate trends on low-frequency variability.
Chasing plastic storms: Assessing atmospheric microplastic deposition by a ‘pulse event’ of tropical storm Fiona in Eastern Canada
Authors: Ammendolia Justine , Allen Deonie , LeBlanc Amber D. , Jambeck Jenna Rachel , Merschrod Erika , Allen Steve , Walker Tony Robert
Published: March 2024

Atmospheric processes and extreme weather events are pathways for the global distribution and deposition of microplastics. Despite the global prevalence of meteorological events, our understanding of atmospheric microplastic pathways and fall-out to the terrestrial, aquatic and marine environment resulting from storms and severe events is limited. In this study, we geospatially consider a unique time series of the movement of atmospheric microplastics and anthropogenic microdebris during an extreme tropical storm in Atlantic Canada. The large tropical storm Fiona was recorded as the deepest cyclone that caused the worst financial damage on record for Eastern Canada during its’ landfall in Nova Scotia (September 22nd to 24th 2022). We collected a unique timeseries of passive deposition samples of atmospheric fall-out before, during, and after storm Fiona. Through micro-Raman spectroscopy and Nile Red fluorescence techniques, we chemically and morphologically characterized particles and quantifies the microdebris and microplastic fallout resulting from the storm. Using back trajectory modelling we aim to identify storm related sources and movement of these particles prior to deposition. As climate change drives increased storm frequency and intensity, it becomes more critical than ever to obtain meteorological baseline data of these pathways.
The effects of plant biostimulants application on soil microbial activity and nutrient uptake under field conditions in Denmark
Authors: Gebremikael Mesfin T. , Mendanha Thayna , Edelenbos Merete , Kristensen Hanne L.
Published: March 2024

Plant biostimulants can play significant roles in organic agriculture by stimulating natural processes that enhance nutrient availability and plant uptake, improve abiotic stress tolerance, and boost overall plant growth and development. Despite their roles, data on the efficacy of biostimulants in organic agriculture is limited, particularly in Scandinavian countries such as Denmark. We evaluated the efficacy of 10 different biostimulants on organic snack carrots and potatoes in Denmark for two years.A factorial experimental design was set up under field conditions for two years at two locations characterized by sandy clay (2021) and sandy (2022) soil textures at the experimental stations of Aarhus University in Denmark. The two factors were nitrogen levels (100% and 50% of recommended nitrogen) and biostimulants of different origins, namely, microbial origin (Proradix and Vesta), plant extracts (Crop-setand Combi-set), seaweed extract (Acadian), humic and fulvic acids (Humifirst). The biostimulants were applied at recommended rates, time, and application methods per the guidelines indicated on the product's label. Soil samples were collected to 0-25 cm depth a week before harvest and after removing the upper ground biomass. Two soil enzymes, dehydrogenase (DHA) and β-glucosidase (BGA), were selected as indicators of soil microbial activities. Macro (N, P, K, S, Ca, Mg) and micro (Fe, Mn, B, Cu and Zn) nutrients in the soil and the potato tubers were analyzed to evaluate the effects of biostimulants on nutrient use efficiency indices such as nutrient uptake.There was no significant interaction effect of the biostimulants and nitrogen levels on both enzymes and most of the plant nutrient uptakes at the two locations. The 100% nitrogen level resulted in a significantly (p
Phytoremediation of pesticide- and mineral oil-contaminated soils with perennial grasses in Ukraine
Authors: Tryboi Oleksandra , Romantschuk Ludmila , Matviichuk Nataliia
Published: March 2024

The most frequent contaminants of soil in Europe are heavy metals and mineral oil [1]. There are more than 5000 pesticide-contaminated in Ukraine that require cleanup [2]. In Ukraine before Russian invasion, according to the State Service of Ukraine for Geodesy, Cartography and Cadastre (StateGeoCadastre) there were around 125.44 thousand hectares of lands, contaminated by industrial and other waste as of January 1, 2019 [3]. Areas contaminated with explosives and mineral oil as a result of military activities after Russian invasion are under assessment, but can amount at least 5 million hectares of agricultural lands [4].Phytoremediation with perennial grasses can be a solution to large areas of contaminated lands in Ukraine, as it can be used to extract heavy metals and speed up degradation of organic contaminants [5].During 2021-2023, field trials performing phytoremediation approach were conducted at two contaminated sites in Ukraine within CERESiS (ContaminatEd land Remediation through Energy crops for Soil improvement to liquid biofuels Strategies) H2020 Project (GA 101006717). First site with fuel and mineral oil contamination and the second - with pesticides contamination, located in the north-western region of Ukraine. Pesticide contamination of the site occurred through minor leaks as a result of a long-term use of pesticides warehouse. Contamination with the fuel oil occurred through small leaks as a result of over 40 years of use and storage of fuel and lubricants by refuelling agricultural machinery. Both contaminated sites represent historical contamination as neither pesticides, nor fuel have been used or stored on the farm for more than 10 years. Baseline soil characterization showed that sites had significant chromium contamination, as well as high quantities of antimony, cadmium, hexachlorocyclohexane and petroleum products.For phytoremediation, trial sites were planted with Miscanthus x giganteous and Phalaris arundinacea. Both plants showed good performance, but Phalaris presented strong dependency on water availability. The second year harvest showed Miscanthus yield around 20 t of dry matter per hectare, and Phalaris more than 5 t of dry matter per hectare at both contaminated sites. Soil characterization after 2 years of growing showed promising phytoremediation potential of both crops with Miscanthus showing better results with decontamination from HCH, Chromium, Cadmium, Antimony and Stanum, and Phalaris performing more efficiently regarding decontamination from petroleum products and phenols.[1] Pérez & Eugenio (2018).[2] Moklyachuk et al. (2010).[3] Information of State Service of Ukraine for Geodesy, Cartography and Cadastre №6-28-0.21-4979.2-19 from 07.06.2019.[4] https://www.pravda.com.ua/eng/news/2023/03/3/7391820/[5] https://www.bbc.com/future/article/20230221-the-toxic-legacy-of-the-ukraine-war 
Machine Learning Insights into Aquifer Recharge: Site suitability analysis in season water availability scenarios
Authors: Fernandes Valdrich , de Louw Perry , Ritsema Coen , Bartholomeus Ruud
Published: March 2024

Groundwater models are valuable tools for optimising decisions that influence groundwater flow. Spatially distributed models represent groundwater levels across the entire area from where essential information can be extracted, directly aiding in the decision-making process. In our previous study, we explored different machine learning (ML) models as faster alternatives to predict the increase in stationary groundwater head due to artificial recharge in unconfined aquifers while considering a wider spatial extent (832 columns x 1472 rows, totalling 765 km2) than previous ML groundwater models. The trained ML model accurately estimates the increase in groundwater head within 0.24 seconds, achieving a Nash-Sutcliffe efficiency of 0.95. This allows quick analysis of site suitability at potential recharge rates. This study extends the approach to incorporate seasonal variation in water availability, illustrating the concept of storing excess water during winter to meet heightened demands during summer, when water availability is minimal. Additionally, we quantify the impacts of the local properties, geohydrological and surface water network properties, on the storage capacity by training ML models on estimating the summer decay rate of stored water in hypothetical aquifer recharge sites.  Among 720 hypothetical recharge sites, we vary its location, recharge rate and size to capture various combinations of local properties in the catchment. Artificial recharge is modeled using a MODFLOW-based groundwater model, representing the geo-hydrological properties and the surface water network in the Baakse Beek catchment in the Netherlands. The recharge is simulated from October 2011 till February 2012 with the remainder of the year simulated without any artificial recharge. Based on the modeled heads, the decay rate of stored water is calculated for the period until October. This calculated decay rate, in combination with the local properties are used to train and evaluate the ML model. The relative contributions of properties to the decay rate are quantified using the latest developments in explainable AI techniques. Techniques such as permutation importance and Ceteris paribus profiles not only help categorize the suitability of potential recharge sites but also quantify the relative contribution of each property. By leveraging these insights, water managers can make informed decisions regarding site improvement measures. 
Doing Hydrology forward for Science-Policy-Practice nexus at the intergovernmental level: the case of World Meteorological Organization (WMO) 
Authors: Dogulu Nilay , Franke Nicolas , Kim Hwirin , Mishra Sulagna , Uhlenbrook Stefan
Published: March 2024

The World Meteorological Organization (WMO) is an intergovernmental United Nations (UN) agency specialised in weather, climate and water-related infrastructure and services. It enables international cooperation at a global scale to promote scientific research based on the integrated Earth system approach, and facilitates the global exchange of Earth observation data and products.The global agenda on sustainable development is strongly intertwined with intensifying hydrological extremes and issues of water availability and quality impacting the environment, food and energy security. The UN 2023 Water Conference further reiterated the role of water at the heart of climate action which evolved as a powerful opportunity to create innovative ways of working with many and diverse stakeholders. Thus, handling of hydrology at institutions/organisations requires effective cross-coordination and interdisciplinary approaches within not only related disciplines but also across science, policy and practice sectors.The Hydrology, Water Resources and Cryosphere Branch at WMO’s Services Department contributes to strengthening the Science-Policy-Practice (SPP) interface through its various activities ranging from the State of Global Water Resources Report to the Hydrology Coordination Panel. The WMO Hydrology Action Plan and the WMO Hydrological Research Strategy (2022‑2030) have special emphasis on science-informed operational hydrology and effective water science-policy. In particular, the recently established unit “Global Processes and Water Policy” is aimed at highlighting the role of hydrology at the intergovernmental level, on platforms such as the Conference of the Parties (COP), the supreme decision-making body of the UN Framework Convention on Climate Change (UNFCCC).In this talk, we will introduce ongoing efforts of the Hydrology, Water Resources and Cryosphere Branch at WMO, and share our experiences working towards the SPP nexus.
Soil moisture shapes the responses of Quercus wutaishansea forest stand transpiration to potential evapotranspiration in the Liupan Mountains, Northwest China
Authors: Yu Pengtao , Liu Bingbing , Wan Yanfang , Wang Yanhui , Wu Yiheng
Published: March 2024

With climate change, accelerated increases in potential evapotranspiration (PET) and decreases in relative extractable water (REW) are increasingly affecting stand transpiration (T). However, the responses of T to PET under limited REW are still unclear, especially in forests of dryland region. In the present study, we partitioned the effects of REW and PET on T in oak (Quercus wutaishansea) forest stands in the Liupan Mountains, northwest China. The results showed that the reduction in REW due to drought resulted in a significant decrease in T. When REW was higher, i.e., above 0.5, there was a linear relationship of T with PET but an exponential relationship when REW was lower than 0.5. Moreover, REW in the soil layer of 20-60 cm rather than that in the soil layer of 0-20 cm plays a decisive role in T during drought. More REW, such that at the mid- and downslope sites, would be helpful to mitigate the decline in T under drought to some extent compared with less REW that at the upslope sites. These remind us that the soil moisture in dryland regions should be paid more attention in forest management and vegetation restoration in future.
Analysis and Development of Oceanographic Models:reaching the Swash Zone
Authors: Memmola Francesco , Coluccelli Alessandro , Russo Aniello , Brocchini Maurizio
Published: March 2024

The swash zone is the part of the beach where the final dissipation of the energy of the incident short waves usually occurs, while low-frequency wave energy is, generally, reflected back to sea. Swash zone flows are of fundamental importance not only because of their local effects but also because they  an affect the surf zone dynamics as a whole. Notwithstanding its importance, typical circulation models do not account for the swash zone dynamics and simplified boundary conditions are often used. This is achieved by calculating a mean shore line and provide along it shoreline boundary condition (SBCs) which take into account of the swash zone dynamics. We present a new SBCs which allowed us to reproduce a shoreline close to the one obtained by ROMSsl with a 0.1 m cross-shore resolution, but using a much coarser grid of 4 m.
Satellite-based energy models to estimate crop yield. An automatic approach at the regional scale
Authors: Gabrieli Davide , Corbari Chiara , Pirotti Francesco , Trestini Samuele , Teatini Pietro , Morari Francesco
Published: March 2024

The recent climate dynamics characterized by unpredictability and a series of extreme events pose challenges to society at various levels, particularly threatening agricultural production. The development of increasingly sophisticated models and computers combined with remote sensing techniques can serve as a means to safeguard the agricultural domain.The aim of this work is to develop a computational tool, named CROPORBIT, designed to operate at a regional scale for estimating crop yield. The capabilities of this tool have a significant positive impact on water management, crop health monitoring, and quantifying damage from extreme meteorological events, such as high temperatures.CROPORBIT combined the radiative model METRIC with a Photosynthetically Active Radiation-based model. Essential inputs for the tool include Landsat 8 and 9 satellite imagery and daily meteorological data retrieved from the regional network stations.The tool performs a multi-temporal analysis of crop growth, involving the interpolation of ET, stress coefficient, and dry biomass accumulation maps, which are then transformed into crop yield maps by applying a harvest index coefficient.CROPORBIT underwent validation in a series of soybean and corn fields situated in the low-lying plain of the Veneto Region, where crop yield maps were recorded by combine harvesters.The preliminary results have shown that CROPORBIT can predict the average crop yield with a good approximation while it was less performing in capturing the field yield variability. The main issues have proven to be the scarcity of clear-sky conditions imagery and the estimation of the harvest index variability.This research establishes the foundation for future investigations, emphasizing the need for improvements in spatial and time resolution. Enhancements in these aspects may lead to improved outcomes in terms of both accuracy and spatial variability.
Dissolved organic matter pathways and transformation across the urban environment
Authors: Schmidlin Diego , Platikanov Stefan , Teixidó Marc , Tauler Romà , Váquez-suñé Enric
Published: March 2024

Today, traditional water sources are starting to struggle to meet current urban demands. Alternative sources such as rainwater, urban stormwater runoff, or aquifers must be considered. Stormwater could represent a very interesting option to augment local water supplies. However, it is widely recognized that stormwater is a large contributor to diffuse pollution. In this context, DOM can be used as a biogeochemical cycle tracer and a proxy for stormwater quality, enabling an effective and sustainable urban water management. However, few studies have addressed the quality at small-scale catchment. To address this, we conducted six sampling campaigns in the city of Barcelona including different water matrices: rainwater, urban runoff (pedestrian and vehicular streets), and influents/effluents from Sustainable Urban Drainage Systems (SUDS). SUDs are urban green infrastructures primarily designed to prevent city flooding by enhancing permeability and facilitating aquifer recharge. Dissolved organic matter (DOM) quality was evaluated by spectroscopic techniques, i.e., measuring specific ultraviolet absorbance (SUVA254), along with fluorescence excitation-emission matrices (FEEM). Results highlighted that concentration of dissolved organic carbon (DOC) followed: rain < SUDS < Pedestrian Street < Conventional Street, providing an initial estimation of contamination levels. The SUVA254 index followed the sequence: rain < Pedestrian Street < Conventional Street < SUDs, indicating the enrichment in aromaticity of Dissolved Organic Matter (DOM) after percolating through the SUDS. Furthermore, calculated fluorescence indices (HIX, BIX, FI, α/β) aided in identifying the origin and maturity of organic matter in the different matrices. Our findings suggest that rainwater was comprised mostly of fresh, microbially derived DOM, while SUDS contained more matured DOM, primarily from terrestrial origin. In contrast, streets contained a different DOM composition, predominantly freshly and microbially derived. Additionally, FEEM together with the MCR-ALS chemometric method allowed us to identify up to six components (i.e., soluble microbial-like, fulvic-like, protein-like tryptophan, protein-like tyrosine, terrestrial humic-anthropic-like, marine and terrestrial-like). Our observations showed that the quantity of DOM decreased through its passage in the SUDS (street to SUD), indicating that these systems can change the quality and quantity of urban organic matter, potentially impacting the water quality of aquifers.
The Impact of Borehole Diameter on Loop Length and ThermalResistivity in Closed-Loop Ground Heat Exchanger System
Authors: Roy Sriparna , Chakraborty Tanusree , Shahu Jagdish Telangrao
Published: March 2024

Introduction: Geothermal heat pump systems GSHPs use the Earth’s subsurface as a heat source in winter and heat sink in summer. A GSHP system integrated with vertical HDPE U-loops for transferring the heat to and from the ground is called a closed-loop ground heat exchanger (CLGHE) system placed by drilling the boreholes. In this study, the relationship between borehole diameter, thermal resistance, and the optimum loop length of CLGHEsystems is investigated.Methods: Utilizing the standard thermal line source equation, analysis of borehole thermal resistivity bR variations across a spectrum of borehole diameter d sizes (ranging from 80-180 mm) has been performed. The soil thermal properties like conductivity λ are considered as 1.5 W/mK , initial ground temperature is considered to be 25⁰C. The analysis is extended to evaluate the influence of borehole diameter sizes on the optimal length of geothermal single U-loops using Ground Loop Design (GLD) software. This comprehensive assessment incorporated critical factors such as soil thermal properties, heat transfer fluid characteristics, and U-loop pipe attributes which has been replicated from the analytical study for a heat load of 10MWh.Results: The outcomes of our simulations revealed notable correlations: larger boreholes consistently demonstrated increased thermal resistance analytically. It has also been observed through the GLD simulations that the loop length increases as the borehole diameter increases for example: when the diameter increases from 80mm to 100mm the loop length increases from 57.6 to 56.5m for a geothermal grid of 2x2 rectangular configuration for the same soil properties and thermal loading conditions. The observed relationship holds implications for optimizing system design and performance, particularly in diverse soil conditions. In conclusion, our study contributes valuable insights into the thermal efficiency of GSHP systems, emphasizing the importance of borehole diameter in influencing overall energy transfer capabilities. These findings provide a foundation for further research and practical applications for the CLGHE systems.
Two million European single-family homes could abandon the grid by 205
Authors: Kleinebrahm Max , Weinand Jann Michael , Naber Elias , McKenna Russell , Ardone Armin , Fichter Wolf
Published: March 2024

Rising energy procurement costs and declining capital costs for renewable technologies are provoking interest in self-sufficiency for individual buildings. In this study, we evaluate the potential of self-sufficient energy supply for 41 million freestanding single-family buildings in the European building stock under current and future (2050) conditions. We employ spatial microsimulation to derive a synthetic building stock, identify 4000 representative buildings and calculate weather-robust cost-minimal energy systems using a high-performance computing cluster. Subsequently, we train surrogate models to transfer the optimization results to the entire European building stock. Our analyses show that buildings in regions with low seasonality, high solar radiation and high electricity procurement costs have high potential for self-sufficiency. Under current techno-economic conditions, 53% of the 41 million buildings are technically able to supply themselves independently from external infrastructures by only using local rooftop solar radiation, and this proportion could increase to 75% by 2050. By paying a premium of up to 50% compared to grid-dependent systems with electrified heat supplies, building owners could make over two million buildings fully energy self-sufficient by 2050.
Existential Threat: How Scientists Can Work With The Media To Communicate Complex Systemic Crises
Authors: Vince Gaia
Published: March 2024

Today, our world of 8 billion people and countless other species faces planetary crises that are interconnected, complex, and existential in scale and comprehension, including climate change, biodiversity loss, pollution, nitrogen, and poverty. Scientists are at the heart of designing the studies to understand these threats, producing the data that calibrates them, and interpreting the those data. They are among the first members of society to recognise these threats and often the most committed to preventing their worst outcomes. For action on these crises, the general public, and policymakers representing them, need to understand the risks and also care about the outcomes: a job for the media, authors, artists and filmmakers. However, science and the media have very different communication styles and approaches, something that scientists often find uncomfortable. How can scientists best manage their public outreach, and work with the media to ensure their expertise and knowledge helps society navigate a better future?
Advancing Contrail Detection Methods over European Skies
Authors: Ortiz Irene , Soler Manuel , García-Heras Javier , Brenot Hugues , Clerbaux Nicolas , de Buyl Pierre
Published: March 2024

Under particular atmospheric conditions, aircraft water vapor emissions can evolve into enduring formations, known as contrails, wherein they entrap the long-wave infrared radiation emitted by the Earth's surface modifying, consequently, the temperature structure within the lower atmosphere. This phenomenon, linked to global warming, underscores the need for studying contrail environmental impacts. Achieving this requires accurate methods to identify formation patterns and monitor size, splitting, and evolutionary dynamics of these features. The present study introduces a novel approach for achieving contrail detection in Multispectral Satellite Imagery based on linear structure considerations and temporal dynamic analysis. The assessment of experimental results relies on images acquired over Europe at specific instances when contrails were visible, leveraging the high temporal resolution provided by the geostationary satellite Meteosat Third Generation.
Carbon dynamics of high-elevation tropical cushion peatlands in the Andes
Authors: Garcia Lino Mary Carolina , Pfanzelt Simon , Domic Alejandra , Hensen Isabell , Schittek Karsten , Meneses Rosa Isele , Bader Maaike
Published: March 2024

High-Andean tropical peatlands occur up to 5000 m a.s.l., where conditions vary from cool to freezing cold on a daily basis. In the tropical and subtropical Andes, these high-elevation peatlands are mainly composed of vascular cushion plants and occur in topographically wet locations in climates ranging from very humid paramos in the north to arid puna in the south. Like other peatlands, Andean cushion peatlands store large amounts of carbon, but with high amount of sediments and higher recent carbon accumulation rates. Often, these amounts have not been quantified, nor are the controls on carbon gains and losses sufficiently known to predict changes in carbon storage due to land-use and climate change. We reviewed the literature on carbon stocks and dynamics in (sub-)tropical Andean cushion peatlands, aiming to understand the topographic, hydrologic, climatic and biotic drivers and geographic patterns. We identified important roles for catchment size and sediment inputs, temperature in combination with water availability, and vegetation, but none of these roles can be quantified yet based on currently available data. However, it is clear that predicted regional differences in climatic changes (seasonality, permafrost behavior, temperature, precipitation regimes) imply that carbon-balance trends of cushion peatlands will differ regionally, with those in paramo most likely to continue as C sinks, while those in dry puna are more likely turning to C sources under increasing aridification.
Towards a better integration of the human and biophysical dimensions in global change modelling
Authors: Folberth Christian , Burek Peter , Kahil Taher , Kraxner Florian , Kuhn Michael , Palazzo Amanda , Wrzaczek Stefan , Yildiz Dilek
Published: March 2024

Global change encompasses on the environmental side components such as climate change, land degradation and pollution; and in the societal domain socioeconomic changes such as demography, economic development, and equality. This nexus is primarily driven by human activities and affects outcomes relevant for peoples’ well-being and viability through a network of interactions and feedbacks. Due to its strong influence on land surface and land-atmosphere processes and as a basis for food security and income, agriculture and rural livelihoods are at the heart of global change.Despite the close entanglement of rural populations, livelihoods, and agricultural production, their integrated assessment is so far hardly considered in large-scale and global foresight studies. Instead, most large-scale research on consequences of global change and potential solutions is still monothematic or combines few of the above elements.Integration across disciplines is taking place only to a limited extent, typically with static combinations of model outcomes. E.g., integrated land use models typically combine yield projections for changing climate with a priori projections of economic and population change. Other examples are the combination of independent projections of crop productivity and water availability to analyze adaptation potentials within the biophysical domain or across scientific domains the estimation of migration driven by changes in crop productivity and water availability. Importantly, both mono- and interdisciplinary studies are most often confined to business-as-usual scenarios or trajectories along shared socioeconomic pathways. Consequently, they do not capture feedbacks involving the human dimension and potentials for adaptation, and therefore lack outcomes that can inform on options for local and regional decision-making covering the water-food-population nexus.The state-of-the-art highlights a concerning lack of integrated approaches to model global change impacts and feedbacks across environmental and socioeconomic domains. Based on own research and literature that characterizes interactions in the water-food-population nexus under global change pressures and existing model types and approaches, we propose herein a platform for the quantitative integrated modelling and assessment of global change impacts and adaptation covering food and water security, land use, demography, migration, and adaptive capacity.Applications of such a modelling platform may address a wide range of pressing questions including shocks, their cascading effects and ultimate feedbacks (e.g. food security through output and input trade during and after Ukraine war; other historic shocks such as financial crisis; etc.); slow-onset global change impacts and adaptation; or transversal achievement of SDGs; and eventually serve as a first step towards the modelling of societal catastrophic change scenarios.
Resolving the aerobic methane emissions from Scots pine shoots
Authors: Pihlatie Mari , Tenhovirta Salla , Kohl Lukas , Koskinen Markuu
Published: March 2024

Release of CH4 from shoots remains the least understood and most enigmatic process of tree-mediated CH4 fluxes. While stem emissions of trees derive from transported or local, biotic pathways, CH4 emissions from shoots likely originate dominantly from abiotic, aerobic production within the canopies. The estimates of the global source strength of aerobic CH4 emissions suffer from large uncertainties, due to insufficient understanding of the source processes.In this contribution, we show the environmental drivers, temporal patterns, and physiological determinants of the aerobic CH4 emissions from the shoots of Scots pines and discuss the contribution of aerobic canopy emissions to the boreal forest CH4 cycles. We present shoot-level CH4 fluxes from saplings and mature Scots pine trees, measured in various settings, outdoors and in the greenhouse. We used chamber enclosure methods with online greenhouse gas analysers in both manual and automated measurement settings. For the automated measurements we built a custom measurement system that allowed continuous measurements of greenhouse gas fluxes.The results from CH4 flux measurements under different light sources indicate that aerobic CH4 emissions are to the most part determined by the intensity and spectral composition of light, and that the emissions are most prominent under direct solar radiation. Hence, the diurnal variations exhibited by these emissions are associated with the diurnal cycle of sunlight, but also vary depending on the cloud conditions. By exposing Scots pine saplings to drought, we further distinguished that the light-driven CH4 emissions from shoots are not a byproduct of photosynthesis-related biochemical reactions. Rather, these emissions result from abiotic thermal and photodegradation of plant compounds.In ambient conditions, we show median aerobic CH4 emissions of 5.41 ng CH4 g-1 DW h-1under direct sunlight and 2.52 ng CH4 g-1 DW h-1 during variable cloudiness. These emissions are 1-2 % of the emission factor used in most of the global upscale estimates of aerobic CH4 emissions from vegetation. Therefore, Scots pine canopies in boreal climates are likely a CH4 source of only minor importance on a global scale. These emissions may, however, decrease the sink strength of the boreal upland forest soils: our conservative estimate is that the canopy emissions of CH4 may decrease this soil sink strength by 2.1 – 4.6 %. This estimate may yet underestimate the significance of canopy fluxes on the ecosystem scale due to the high spatiotemporal variation of both the canopy CH4 emissions and the CH4 uptake rates of boreal upland soils. To further refine the estimates of the source strength of aerobic CH4 emissions of tree canopies it is, therefore, important to gain more data of shoot-level CH4 fluxes from field measurements.
Pushing the Limits of Subseasonal-to-Seasonal Sea Ice Forecasting with Deep Generative Modelling 
Authors: McDonald Andrew , Smith Jonathan , Yatsyshin Peter , Andersson Tom , Bowler Ellen , van Zeeland Louisa , Ubald Bryn , Byrne James , Pérez-Ortiz María , Turner Richard E. , Hosking J. Scott
Published: March 2024

Conventional studies of subseasonal-to-seasonal sea ice variability across scales have relied upon computationally expensive physics-based models solving systems of differential equations. IceNet, a deep learning-based sea ice forecasting model under development since 2021, has proven competitive to such state-of-the-art physics-based models, capable of generating daily 25 km resolution forecasts of sea ice concentration across the Arctic and Antarctic at a fraction of the computational cost once trained. Yet, these IceNet forecasts leave room for improvement through three main weaknesses. First, the forecasts exhibit physically unrealistic spatial and temporal blurring characteristic of deep learning methods trained under mean loss objectives. Second, the use of 25 km scale OSISAF data renders local forecasts along coastal regions and in regions surrounding maritime vessels inconclusive. Third, the sole provision of sea ice concentration in forecasts leaves questions about other critical ice properties such as thickness unanswered. We present preliminary results addressing these three challenges, turning to deep generative models to capture forecast uncertainty and improve spatial sharpness; leveraging 3 and 6 km scale AMSR-2 sea ice products to improve spatial resolution; and incorporating auxiliary datasets, chiefly thickness, into the training and inference pipeline to produce multivariate forecasts of sea ice properties beyond simple sea ice concentration. We seek feedback for improvement and hope continued development of IceNet can help answer key scientific questions surrounding the state of sea ice in our changing polar climates.