bluuebunny/crossref_metadata_2025 huggingface dataset:
Deciphering local from global signals in Portimão Bank sedimentary dynamics 
Authors: Martins Mélinda , Ercilla Gemma , Drago Teresa , Veiga-Pires Cristina
Published: March 2024

Paleoenvironmental studies play a pivotal role in addressing contemporary environmental challenges, enhancing our understanding of Earth's history, and informing climate change preparedness strategies. The PC06 sediment core, retrieved at the base of the Portimão Bank (PB) at a depth of 3,520 meters, southwest of the Gulf of Cadiz, specifically provides a valuable contribution spanning 49,000 cal. years BP to the present. This is a multidisciplinary study including sedimentological (grain size, carbonates, organic matter, smear slides and sand fraction composition) and geochemical analyses (based on XRF data) to elucidate the paleoenvironmental changes and related depositional processes over that time. Based on the obtained results four main sedimentary units with distinct lithofacies characterize the stratigraphy of the core; from bottom to top, they are as follows: A- Pyritic mud, B- Pyritic organic-rich mud, C- Clay-rich mud, and D- Pelagic mud. These sedimentary units show a transition from terrigenous mud deposition (A to C) to biogenic sedimentation (unit D) during the Holocene. The units A to C are marked by significant silt peaks and high D50 values, which suggests the influence of bottom currents from the deep waters of the North Atlantic, particularly during the Heinrich events (HE) 5 and 1, while unit D is characterize by a high percentage of planktonic foraminifera and coccolithophorids. Furthermore, units A to C are slightly coarser than unit D. Those observations could be interpreted as variations in the environmental changes at two different temporal scales: i) from the glacial (A to C) to interglacial (D) periods; and ii) a short-scale local variations during the A to C unit sedimentation related to the presence of pyrite. This multidisciplinary analysis yields valuable insights into the interaction of local and global signals, refining our understanding of Portimão Bank sedimentary dynamics throughout the studied period. This work is a contribution of the MONTERA (CTM 2009-14157-C02 CSIC), EDUCOAST (PT-INNOVATION-067) and EMSO-PT (PINFRA/22157/2016) projects.
Evaluation of daily SPI and SPEI indices for near-real time drought monitoring over CONUS
Authors: Prat Olivier , Coates David , Wilkins Scott , Willett Denis , Leeper Ronald , Nelson Brian , Shaw Michael , Ansari Steve
Published: March 2024

Two drought indices; the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are computed over CONUS using daily precipitation and temperature estimates from the NOAA Daily U.S. Climate Gridded Dataset (NClimGrid-Daily). The NClimGrid-Daily dataset consists of four climate variables derived from the GHCN-D dataset: maximum, minimum, and average temperatures and precipitation from 1951 to the present with a 5-km grid resolution. While SPI only uses precipitation as an input to assess drought conditions, SPEI uses both precipitation and potential evapotranspiration (PET). The daily SPI and SPEI are computed over various time scales (30-, 90-, 180-, 270-, 365-, 730-day). The differences between the two indices are being evaluated focusing on the influence accumulation period, differing period of record, and various SPI (McKee et al 1993, Guttman 1999) and daily PET (Thornthwaite and Mather 1957, Camargo et al. 1999, Pereira and Pruitt 2004) formulations. The impact of the period of reference is analyzed to account for the impact of precipitation and temperature changes over time (i.e., 1952-present, 1960-1990, and 1990-2020 for instance). For the most recent period (2000-present), the NClimGrid-SPI and NClimGrid-SPEI are compared against existing droughts monitoring resources such as the weekly US Drought Monitor (USDM). The use of cloud-scale computing resources reduces considerably the computation time and allows for the near-real time computation of daily SPI and SPEI indices. The effort to transfer the SPI and SPEI from research to operation (R2O) and to provide near-real time drought monitoring capabilities is also presented.
Mesoscale and submesoscale biogeochemical signatures in a high-resolution ocean model (ICON-O/HAMOCC)
Authors: Casaroli Lucas , Ilyina Tatiana , Serra Nuno , Chegini Fatemeh
Published: March 2024

Within the oceanic mesoscale and submesoscale spectral ranges, energetic phenomena unfold which include eddies, fronts, filaments and internal waves. Those intricate features significantly impact the biogeochemical cycles. For instance, they contribute to the vertical transport of nutrients to the euphotic zone, modify the mixed layer depth through vertical displacement of isopycnals, and play a pivotal role in shaping the patchiness of phytoplankton. Many ocean biogeochemical models are constrained by computational resources, limiting their ability to resolve the complex details of high-resolution processes. In this study, we introduce a state-of-the-art ocean biogeochemical model (ICON-O/HAMOCC) with a uniform 10-km resolution. Our results show the impact of vortical structures on oxygen, phytoplankton, and carbon. The model solution highlights a robust signal of Tropical Instability Waves (TIW) in biogeochemical tracers in the Equatorial Pacific. We assess the seasonal and interannual variability of this signal, demonstrating the significant role of eddies in ocean oxygenation and in the carbon cycle.
Investigation of the Active Deformation in the Caucasus Region from Seismic and Geodetic Observations
Authors: Karabulut Hayrullah , Milyukov Vadim , Guvercin Sezim Ezgi , Ozarpaci Seda , Pavlovich Mironov Alexey , Ergintav Semih , Özbey Volkan , Zabci Cengiz , Konca Ali Ozgun , Diyagilev Ruslan , Mikhailovich Steblov Grigory
Published: March 2024

The deformation and shortening in the Caucasus region are predominantly driven by the collision of Arabian and Eurasian plates with a possible contribution of the lithospheric deformation beneath the Caucasus.  The tectonic uplift/inversion, along with the formation of the Greater and Lesser Caucasus fold and thrust belts, is driven and maintained by the continental collision of the Arabian and Eurasian plates. However, the dominant factor for the regional variations of surface deformation and sub-crustal seismic activity, whether lithospheric delamination or slab detachment beneath the Caucasus region, is not well understood. Moreover, the variations in shortening along the Caucasus cannot be solely explained by plate boundary forces without constraints from lithospheric dynamics. The large uncertainties of the models lead to limited understanding of the formation and active deformation of this fold and thrust belt. The main reason for this shortcoming is the limited access to the seismic and geodetic data in the region. In this study, we merged seismic and geodetic data from Russia and surrounding countries.  We constructed a joint database for the period between 2007 and 2010 and updated 1D crustal velocity models for four sub-regions. We obtained the relocated seismicity within each region using the local velocity models. In addition, we updated the earthquake source mechanisms catalog in the Caucasus region.  A new Pn tomography model is computed using the new catalog. The crustal thickness variations are recomputed from receiver function analysis using the broad-band stations of Russia. We also update block boundaries and corresponding slip rates in the study region using both seismicity and geodetic data.
Prediction and predictability of drought events in the Spree region
Authors: Hauke Clara , Ulbrich Uwe , Rust Henning
Published: March 2024

The predictability of drought events in the Spree region is analyzed, aiming at developing hydrological extreme events forecast and warning systems and long-term solutions regarding sustainable, interdisciplinary and integrated water resources management in the project SpreeWasser:N.Predictors acting as potential indicators of imminent drought risk are inferred from statistical analyses, modeling and literature. Connections between certain states of the atmosphere (large-scale weather patterns) and local drought events are drawn, focussing mainly on agriculture as a user group. Special attention is paid to the succession of certain weather patterns and their impact on precipitation.A drought forecast based on k-nearest neighbor regression is being developed using an algorithm which automatically selects the meteorological variables and regions yielding the largest forecast skill as input predictor variables during a hindcast period. This machine learning approach supports the discovery of underlying physical links in atmospheric phenomena.The analysis and software development is based on ECMWF ERA5 reanalysis data and the objective weather type classification by the German Weather Service (DWD), spanning the years 1980 to 2021.
The use of trace metal-rich Greenlandic glacial rock flour for ocean enrichment experiments
Authors: R. Vives Clara , Bendtsen Jørgen , Vallentin Larsen Kristina , Daugbjerg Niels , Richardson Katherine , Thorleif Rosing Minik
Published: March 2024

In order to keep global warming below 2ºC, it is imperative not only to reduce future carbon dioxide (CO2) emissions but also to adopt negative emissions technologies (NETs) to remove approximately 600 Gt of CO2 from the atmosphere by the end of the twenty-first century. Among NETs, ocean alkalinity enhancement and ocean enrichment emerge as promising strategies for Carbon Dioxide Removal (CDR), leveraging the immense carbon-absorbing capacity of oceans.Glacial rock flour (GRF), an ultra fine-grained silicate mineral originating beneath the Greenland Ice Sheet, holds potential as a contributor to large-scale marine CO2 removal (mCDR). As it is transported into coastal waters, the dissolution of GRF in seawater naturally releases mineral components into the ocean. As a silicate-rich substance with micronutrients like iron and manganese, GRF has the dual capacity to enhance alkalinity and promote phytoplankton growth, presenting a viable avenue for mCDR. In a field study from the Kangerlussuaq fjord and glacier near the Greenland Ice Sheet (summer 2023) we observed that melt- and seawater contained an array of trace metals in high concentrations, including iron, manganese, zinc, copper, and cobalt, and the concentrations increased towards the fjord and away from the source. We explore the response to varying treatments with GRF, iron, manganese and zinc using laboratory incubation experiments with an Arctic phytoplankton diatom species (Coscinodiscus radiatus). We identify the relative mobilization rate of these trace metals in the GRF that can support phytoplankton growth and hypothesise that GRF can alleviate the co-limitation of iron and manganese on phytoplankton growth.
Sources and abundance of ice nucleating particles derived from long-term measurements at high time resolution
Authors: Möhler Ottmar , Bogert Pia , Böhmländer Alexander , Büttner Nicole , Höhler Kristina , Lacher Larissa , Ullrich Romy , Vogel Franziska
Published: March 2024

Ice Nucleating Particles (INPs), a minor and strongly temperature dependent fraction of atmospheric aerosol particles, are key players in the weather and climate systems be inducing the formation of ice in mixed-phase and cirrus clouds. There is increasing evidence that INPs not only induce the formation of precipitation in particular over continental areas, but also have an important impact on a number of radiatively important clouds types throughout the troposphere.New insight into the abundance, types, and sources of INPs, and by that also into their various roles in the atmosphere, can be obtained by longer-term measurements at high time resolution. Such measurements can be conducted with the PINE (Port-able Ice Nucleation Experiment) instrument, which was developed for both, flexible operation during dedicated laboratory experiments on ice nucleation processes and for automated operation during longer-term INP monitoring activities in the field.This contribution will give a short introduction into the topics of primary ice formation and ice-nucleating particles, and will present and discuss examples of recent longer-term records of INP measurements with the PINE instrument at different European field sites like the Sonnblick Observatory in Austria, the Helmos observatory in Greece, the Zeppelin observatory in Spitzbergen, or the National Atmospheric Observatory Kosetice in the Czech Republic. These locations will also become observatories as part of the pan-European infrastructure ACTRIS for longer-term monitoring of aerosols and INPs.
Reconstructing the global mean surface temperature of the last 130 thousand years
Authors: Baudouin Jean-Philippe , Weitzel Nils , Jonkers Lukas , Dolman Andrew M. , Rehfeld Kira
Published: March 2024

Global mean surface temperature (GMST) is a fundamental measure of climate evolution in both past and present and a key quantity to evaluate climate simulations. However, for paleoclimate periods, its reconstruction hinges on uncertain and indirect observations which are distributed sparsely and non-uniformly in both space and time. Large datasets of homogenised proxy records help to reduce the sparsity. Then, the records can be aggregated in an algorithm retrieving the GMST signal. Here, we build on the algorithm designed in Snyder 2016, and on a recent database of ocean temperature proxy records to reconstruct the GMST evolution over the last glacial cycle (the last 130 thousand years). First, we evaluate the algorithm and quantify the sources of uncertainty. This analysis draws on pseudo-proxy experiments using a range of simulations of the last glacial cycle. We find that the over-representation of some regions (e.g. coasts, the Atlantic), to the detriment of others (e.g. the central Pacific) significantly impacts the reconstructed temperature anomaly and its variations. Additionally, millennial and shorter timescale variability cannot be reconstructed by the algorithm, due to bioturbation and age uncertainty. However, these experiments also demonstrate the ability of our algorithm to reconstruct the amplitude and timing of GMST variations occurring at orbital timescale (>10.000 years). Second, we reconstruct the GMST evolution during the last glacial cycle. We compare our result to previous studies, and discuss the improvements coming from the use of the recent proxy database. The high number of proxy records allow us to additionally investigate smaller regions (e.g. hemisphere) and overall further our understanding of the driver of orbital-scale GMST variability.
The behavior of concave, convex, and straight coastlines on the generation of storm surges.
Authors: tiwari pawan , Rao Ambarukhana Devendra , Pandey Smita , Pant Vimlesh
Published: March 2024

Coastal regions are vulnerable to the devastating impacts of storm surges (SS), with a potential for widespread flooding and property damage. The study presents a comparative analysis of SS in three distinct coastal geometries: concave, convex, and straight coastlines. The coastline shape plays an important role in the generation mechanism of SS. Concave coastlines, characterized by inward-curving features such as bays and inlets, exhibit a propensity for SS amplification due to the funneling effect. As any storm approaches the concave coastline, surge waters are channeled into narrower spaces, leading to higher surge elevations. In contrast, convex coastlines, with outward-curving features, tend to disperse energy associated with SS waves, resulting in lower surge heights. The expansive nature of this coastline allows for greater dissipation of surge wave energy, reducing the risk to coastal communities. While, straight coastlines lacking the curvature of concave or convex shapes, are still susceptible to SS.
The study employs the Advanced Circulation (ADCIRC) model and hypothetical storm data to compute SS to understand its generation mechanism in response to different coastal geometries. The study is divided into two parts: the first is sensitivity experiments with different curvatures, and the second is considering the actual east coast of India having similar coastal configurations. Sensitivity analysis indicates that as the track moved from north to south, maximum water elevation (MWE) increased until the radius of maximum winds (Rmax) prevailed close to the center of the shape and then decreased for the concave and convex coastlines. It is seen that the MWE amplifies as the curvature of the coastline increases. Further, the MWE is higher for the 90° approach angle than 45° and 135° as measured from the north. Computations of water flux and energy density are made for these coastal configurations to understand the surge growth mechanism. The findings underscore the significance of accurate forecasting, coastal planning, and early warning systems to mitigate the impact of SS in concave, convex, and straight coastlines. Improved resilience strategies and disaster preparedness measures tailored to the specific characteristics of each coastal shape can enhance the safety and security of coastal communities facing the growing threat of extreme weather events.
Some alternative metods for causal discovery
Authors: Telcs András
Published: March 2024

Causal inference is indeed a challenging endeavor, particularly when applied to observational studies of interacting systems. Perl's theory, along with the PC algorithm on directed acyclic graphs, and its extensions PCMCI and FCI, are powerful tools. However, their application to time series is time-consuming, and they still struggle to distinguish Markov-equivalent scenarios.In our talk, we will present some methods based on principles that are partly or fully different from those underlying the aforementioned tools. Due to time constraints, we will focus on the main principles that allow the discovery of causal relations between a pair of systems, including hidden common causes (referred to as common drivers or confounders in different schools of thought). We won't delve into the numerous technical challenges due to the time limit.
Uncertainty Quantification for Deep Learning
Authors: van Leeuwen Peter Jan , Chiu J. Christine , Yang C. Kevin
Published: March 2024

Many processes in the geosciences are highly complex and computationally challenging or  not well known. In those cases, Machine Learning, especially Deep Learning, is becoming increasingly popular to either replace expensive numerical models or parts of those models, or to describe relations between variables where the underlying equations are unknown. Despite many successful applications, the uptake of Deep Learning in science has been slow because proper uncertainty estimates are lacking, while these are crucial for comparison studies, forecasting, and risk management.Deep Learning can be considered as a method that provides a nonlinear map between an input vector “x” and an output vector “z”. The nonlinear map contains a large weight vector “w,” determined via optimization using training, validation, and testing dataset. To quantify the uncertainty in the output “z”, we need to take into account uncertainty in 1) the input “x”, 2) the weight vector “w”, and 3) the nonlinear map from input to output. Furthermore, the uncertainty in the weight vector depends on uncertainties in the training and testing dataset. Present-day Deep Learning methods such as Bagging, MC Drop-out, and Deep Ensembles ignore most of these uncertainty sources, or apply them incorrectly, resulting in an incorrect uncertainty estimate.In this presentation, we will, for the first time, take all uncertainty sources into account and provide an efficient methodology to generate output uncertainty estimates. Interestingly, by taking uncertainty in input training data into account, we show that the uncertainty quantification becomes more robust to outliers as it is a systematic and well-defined way to implicitly increase the training dataset. We then demonstrate an application for predicting cloud process rates from a deep neural net and provide a physical interpretation of the resulting uncertainty estimates.
Numerical and analogue modelling of boudinage under non-coaxial shear strain
Authors: Rosas Filipe , Gomes Afonso , Almeida Jaime , Duarte João , Riel Nicolas , Schellart Wouter
Published: March 2024

The recognition of different boudinage patterns is of key importance to the unravelling of the tectono-metamorphic evolution of different domains in different tectonic contexts and at different considered spatio-temporal scales.The main reason for this is twofold: (1) Boudins tend to preserve the relic metamorphic conditions that characterize deformation prior to the one recorded by matrix fabrics and associated mineral associations. (2) Specially under shear deformation regimes, quarter-structure geometric patterns comprising rotated boudins and folded matrix planar fabrics, can be used to determine the shear sense of the later (sin-boudinage) deformation.In the present work, we present preliminary numerical and analogue modelling results of boudinage, under non-coaxial (shear strain) deformation. We specifically investigate the potential influence of three main parameters on the genesis of different (boudins-folds) quarter structures patterns: i) the viscosity contrast between the boudin and the matrix; ii) the original position of the non-equidimensional boudin; and ii) the assumed (bulk) shear strain rate.We proceed by presenting a preliminary comparison of our results with archetypical natural examples of boudinage, in different tectonic-structural contexts and at different scales, further illustrating the potential value of these type of structures in the unravelling of the deformation history in different situations.AcknowledgementsThis work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020).
Monitoring wildfire smoke plumes and clouds with portable weather radar to nowcast hazards associated with extreme wildfires
Authors: Guyot Adrien , Turner Kathryn , Brook Jordan , Soderholm Joshua , McCarthy Nicholas , Protat Alain , McGowan Hamish
Published: March 2024

Extreme and megafires demonstrate a significant interplay between fire dynamics and the surrounding atmosphere, resulting in erratic fire behavior, rapid fire spread, long-range transport of burning embers, and pyro-convective activity that leads to the formation of pyrocumulus and/or pyrocumulonimbus clouds.These fire-induced clouds play a crucial role, generating strong updrafts and downdrafts, causing plume collapse, and carrying particles like firebrands downwind while also lifting smoke particles into the stratosphere. Monitoring these clouds poses challenges; satellites offer limited resolution and passive sensing, while ground-based weather radars provide the best means to track their entire lifecycle, especially portable systems deployed at proximity of the fire and offering better resolution and accuracy. These systems are capable of identifying specific features and phenomena, such as rotors and vorticity, pyrometeors and the formation of condensation.Our study presents observations from portable weather radars captured from various Australian wildfires. We introduce machine learning-based techniques to process radar data, aiming to provide actionable intelligence on wildfire-related hazards.
Significance of millennial-scale coastal upwelling and Rio Loa variability forAtacama paleoclimate during MIS 2
Authors: Fabritius Jessica , Jaeschke Andrea , Petersen Jassin , Wennrich Volker , Grunert Patrick
Published: March 2024

The Atacama Desert located in northern Chile is one of the driest places on earth. The factors determining recent hyperarid climate conditions and their interplay and variability on interannual and decadal time scales are generally understood. Evidence for wetter (yet arid) conditions in the Atacama’s past is mostly provided by ephemeral lacustrine and fluvial deposits. The main watercourse of the Atacama Desert is the Rio Loa sourced by rainfall in the Andean mountains. Information on changes in the terrestrial supply to the ocean is recorded in marine sediments off the Rio Loa mouth.Sediment core SO-104-52KL has been collected on the upper continental slope (∼340 m water depth, 21°S) off the Rio Loa during cruise 104, Leg 3 by RV Sonne in 1995. The preliminary chronology of the core based on 14C datings constrains the top and base of the core to 16 and 42 ka, respectively, with a mean sedimentation rate of 30-40 cm kyr-1. These very high average sedimentation rates allow reconstructions of the paleoceaonographic and paleoclimatic conditions during marine isotope stages (MIS) 3 and 2 on millennial to centennial time scales. The location of the core on the continental slope off the Rio Loa mouth allows for the parallel evaluation of the Humboldt Current System and Andean rainfall as moisture sources for the Atacama Desert.Proxy data for upwelling properties are established from microfossil assemblages and lipid biomarkers. Preliminary results show that foraminifera are abundant and well-preserved in the upper 4 m of the core. While planktonic foraminifera are rare, benthic assemblages are rich. In total, 24 genera and 49 species of benthic foraminifera were distinguished. The three taxa Bolivina, Bulimina, and Suggrunda, which indicate hypoxic to dysoxic conditions at the seafloor, make up most of the individuals. The dominance of hypoxia tolerating taxa indicates strong upwelling conditions via the presence of a pronounced Oxygen Mimimum Zone impinging on the upper continental slope. These data are put into context with relatively warm sea surface temperatures of average 21 °C as derived from alkenone data. Together with XRF data and grain-size analyses, both applied to characterize the terrestrial input by the Rio Loa, the expected proxy data will provide new insights into the dynamics of land-ocean coupling between the Atacama Desert and the eastern Pacific Ocean.This study is part of the CRC 1211 “Earth-Evolution at the dry limit” project, funded by the German Research Foundation (DFG).
Predicting near-surface seismic data and velocity models using synthetically-trained deep learning methods: applications in data-rich environments
Authors: Totten Eoghan , Bean Chris , O'Brien Gareth
Published: March 2024

Recent advances in machine learning offer a new way for Earth Scientists to make predictions about geological subsurface properties. In particular, methods based on Fourier Neural Operators (FNOs) are increasingly being used as a substitute for conventional approaches based on numerical forward modelling and inversion, at a fraction of the computational cost. Most importantly, FNOs have been shown to predict accurate 2D and 3D forward modelling simulations of seismic waves up to several hundred times faster than physics-based solvers after training.In synthetic volcanic settings to date, FNOs have been applied successfully to both the forward and inverse problem, capturing the fine-scale velocity structure of heterogeneous models. However, transferring the successful performance of simulation-trained FNOs to make accurate predictions from field-gathered seismic data is yet to be achieved. In order to accomplish this for volcanological data, training models would need to contain representative small-scale velocity heterogeneities and topography in order to produce highly scattered codas in the synthetic seismograms.This research presents work in progress on simulation-to-real applications of FNOs using field-gathered seismic data from offshore sedimentary basin settings as a testbed environment. Historical seismic survey datasets from Atlantic sedimentary basins are often supplemented with alternative geophysical surveys and site-specific geological constraints. Combining seismic borehole and stratigraphic logs with regional seismic datasets provides a link between field-gathered seismic waveforms, stratigraphy and depth-dependent, small-scale fluctuations in seismic velocity. This in turn enables the creation of synthetic velocity models and seismograms with field-derived properties, centring the collation of data for real-world machine learning applications in the numerical domain. We aim to bring insights gained from training FNOs on a better understood seismic environment to volcanic contexts in future work.
Spatial and Temporal Analysis for Identifying the Movement of Chronic Kidney Disease (CKDu) Hotspots; in Reference to River Basins in North Central Province, Sri Lanka
Authors: Arambegedara Charunika Sandamini , Lijun Yu , Cai Danlu , Zhu Jianfeng , Ranasinghe Asanga Venura , Silva Ambepitiyawaduge Pubudu De
Published: March 2024

In recent years, Sri Lanka has experienced a high prevalence of chronic kidney disease (CKDu) in certain regions, especially in the North Central Province (NCP). The etiology of this disease is not yet clearly understood, although several hypotheses involving environmental and occupational factors have been proposed. To better understand the patterns of CKDu incidence and its potential relationship to environmental factors, a spatial and temporal analysis was conducted using geographic information system (GIS) tools. In this study, we identified the geographical hotspots of CKDu incidence over a period of eleven years (from 2010 to 2020) in the NCP, of Sri Lanka. The analysis was done for the districts of Anuradhapura and Polonnaruwa in NCP. Furthermore, we analysed the temporal trends of CKDu incidence by comparing the disease burden between different years. Finally, we examined the association between river basins and CKDu incidence by overlaying the spatial layers of the disease incidence and river basins. Our results showed that there were significant spatial and temporal variations in CKDu incidence in the region over the study period. The disease is characterized by a fluctuating trend. Also, the number of hotspots has decreased over time, and the number of CKDu-affected patients has also decreased. Similarly found that CKDu hotspots were concentrated around the mainly 4 river basins in the region, indicating a possible link between water resources and the disease. By identifying CKDu hotspots and understanding the disease's movement over time, public health officials can target their efforts more effectively, reducing the disease's impact on affected communities. This study provides important insights into the spatial and temporal patterns of CKDu and suggests the need for further research to investigate the potential environmental risk factors contributing to this disease. Key Words: Chronic Kidney Disease of Unknown Etiology (CKDu), Hotspots Analysis, Spatial and Temporal Variation, Geographical Information System (GIS)
A Particle-in-Cell Simulation of Ion and Electron Dynamics from Tail Reconnection to the Inner Magnetosphere
Authors: Walker Raymond , El-Alaoui Mostafa , Rusaitis Liutauras , Lapenta Giovanni , Echterling Nicole , Schriver David
Published: March 2024

We have used a PIC simulation combined with a global MHD simulation to model the interaction between magnetotail plasma from reconnection and inner magnetosphere region. The PIC simulation extended from the solar wind outside of the bow shock to beyond the reconnection region in the tail. The initial simulation was carried out with nominal solar wind parameters and southward IMF. A partial ring current and diamagnetic current formed in the PIC simulation.  Initially, the partial ring current formed by drift of the particles loaded into the PIC simulation. However, the PIC run lasted ~2 m and by the end of the calculation particles from tail reconnection had reached the inner magnetosphere and contributed to the partial ring current.  The sources of the particles to the inner magnetosphere are bursty bulk flows (BBFs) that originate from a complex pattern of reconnection in the near-Earth magnetotail at about XGSM=-25- to -30 RE. After the particles jet away from the initial reconnection site, they can undergo further acceleration at secondary reconnection sites. Electrons jet away from the reconnection much faster than the ions setting up an ambipolar electric field allowing the ions to catch up after 4-14 di (ion inertial lengths). The initial energy flux in the BBFs is mainly in the form of kinetic energy flux from the jetting particles, but as they move earthward the energy flux changes to enthalpy flux. The energy flux in the simulated ring current is primarily in the form of enthalpy flux. The power delivered from the tail reconnection in the simulation to the inner magnetosphere (~6X1011 W) is consistent with observations. 
The bark carbon storage of Austrian commercial forests
Authors: Sinan Muhammed , Neumann Mathias , Hasenauer Hubert
Published: March 2024

In Austria, the Austrian Federal Office and Research Centre for Forests (BFW) provides basic forest data such as volume stock or the national carbon inventory. The Austrian carbon inventory currently records the carbon stored in the bark as part of the forest's total tree carbon stock. However, tree bark plays a vital role in the life span of a tree and is also important for the decomposition process following tree death. There is a veritable need to quantify the proportion of bark accurately because it has an important impact on economic calculations. In this study we assess the amount of carbon stored in the stem bark of Austrian commercial forests (in German “Wirtschaftswald”) as it can be derived from (i) the taper curve, (ii) the bark percentage, (iii) the bark density, and (iv) the bark fissure index. We applied this “bark carbon model" to the latest data from the Austrian National Forest Inventory (NFI). The model predicts for each tree the corresponding bark carbon content, which can be easily aggregated to plot or regional level for further use. Our results suggest, that about 7% of the total carbon in Austrian commercial forest is stored in the bark of the tree stems. The findings provide bark carbon information that can also be used for other purposes like potential harvesting of bark, or determining the fire adaptation of tree species. Moreover, this study helps to provide information for the bark carbon share of the Austrian National carbon inventory.
Investigating Storm Charge Distribution Trends with Intracloud Lightning Polarity Data
Authors: DiGangi Elizabeth , Lapierre Jeff , Zhu Yanan
Published: March 2024

There are, at present, two accepted primary paradigms for thunderstorm charge distribution using a simple tripole model: “normal” polarity storms, which are characterized by a central negative charge region, an upper positive charge region, and sometimes a lower positive charge region; and “inverted” polarity storms, which are characterized by a central positive charge region, an upper negative charge region, and sometimes a lower negative charge region. The real distribution of thunderstorm charge is known to be more complex than the tripole model can represent, but the normal/inverted paradigm is still widely used in the field. Characterizing storms as having a normal or inverted polarity has been a subject of interest in lightning research since discovering that inverted storms produce a larger-than-average fraction of positive amplitude cloud-to-ground (CG) lightning compared with normal storms. +CG lightning is understood to have generally higher peak currents and a much greater probability of producing continuing current than -CGs, which is relevant for research into subjects like lightning-initiated wildfires and transient luminous events. Thunderstorm charge distribution is also directly related to storm microphysics and thermodynamics, which, in turn, links it to the meteorological characteristics of storms and storm environments.Most published research on storm polarity has either investigated large-scale trends in +CG versus -CG frequency from long-range lightning detection systems (LDSs), or has used LDSs which map lightning in 3D to infer storm polarity directly from intracloud (IC) lightning leader propagation patterns. Data on IC lightning from long-range LDSs is a resource which, to our knowledge, has not yet been used to study bulk storm charge structures. It stands to reason that if inverted storms favor the production of more +CGs than normal storms, then they would also favor the production of more -ICs. The goal of this study is therefore to interrogate several years of lightning data from the Earth Networks Total Lightning Network (ENTLN) to determine whether or not IC peak current information can be used to study storm charge structure and the geographic distributions of inverted and normal polarity storms.
Reactive transport modeling to study the impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary
Authors: Seibert Stephan L. , Massmann Gudrun , Meyer Rena , Post Vincent E.A. , Greskowiak Janek
Published: March 2024

Dissolved species of terrestrial and marine origins are transformed in Subterranean Estuaries (STEs) before they flow into the coastal oceans. The occurring biogeochemical reactions are highly complex, demanding the application of numerical reactive transport modeling (RTM) approaches to achieve a deeper process understanding. The objective of this study was to quantify the impact of organic matter degradation and secondary mineral reactions on the fate of dissolved species in a generic sandy STE. A comprehensive RTM approach was developed for this purpose, investigating the effects of ion activities, pH, pe, redox reactions, mineral equilibria (goethite, siderite, iron sulfide, hydroxyapatite and vivianite) as well as surface complexation. We found that the STE biogeochemistry was very sensitive to the assumed reaction network. For example, dissolved inorganic carbon and pH were mainly controlled by calcite and siderite dynamics. Dissolved Fe2+ and HS- were precipitated as goethite, siderite and/or iron sulfides, respectively. PO43- concentrations were strongly controlled by the formation of P-bearing minerals, e.g., vivianite and hydroxyapatite, as well as surface complexation. Our work helps to establish the relative importance of some of the major biogeochemical processes in the STE. In a next step, field data from a high-energy STE site on Spiekeroog (‘DynaDeep observatory’) will be used to explore which processes take place in real-world STEs.
Scattering properties generated from real shaped ice crystals and snowflakes for ICON’s Radar Forward Operator EMVORADO
Authors: Dutta Soumi , Ori Davide , Mendrok Jana , Blahak Ulrich
Published: March 2024

Radar Forward Operators (RFO) act as an important link between the physical properties of cloud and precipitation and the observed radar quantities. A major source of uncertainty in radar forward operators is identified in the scattering properties of frozen and mixed-phase hydrometeors. Appropriate modeling of the internal structures of complex-shaped hydrometeors plays a pivotal role in the simulation of their polarimetric scattering properties. When RFOs are applied to weather model output, it is also desirable to ensure the consistency between the properties of hydrometeors assumed in the weather model and those implemented in the scattering simulations. Failing to do so, would impede a correct interpretation of model-observation comparison studies. The present study aims to model the microphysical and scattering properties of realistic ice crystals and snowflakes using the snow particle aggregation and DDA scattering models. The aggregation model includes realistic monomer generators for various ice crystal shapes. The simulated scattering properties are implemented into the EMVORADO RFO of the ICON model. Simulated properties are primarily kept consistent with the ICON microphysical assumptions. The shapes of snowflakes and ice crystals (dendrites and plates) are generated from the aggregation model, and used as input to the DDA scattering model to compute multi-frequency polarimetric radar scattering properties. The derived scattering properties are expected to explain better the observed polarimetric radar signatures of ice crystals and snow aggregates. Nonetheless, when simulating the snowflake shapes, one must make some decisions regarding its monomer composition. This study also explores the use of the innovative Lagrangian-particle cloud model McSnow in combination with the snowflake aggregation simulator. McSnow is able to simulate the snowflake evolution based on the physical and thermodynamic profiles of clouds and thus informs the aggregation model about the snowflake composition in terms of monomer shapes, size, and number. The synergy of these models is expected to elucidate the link between ice cloud processes and the polarimetric properties of cold clouds.
Relief stability of western Europe middle mountains from morphometry and 10Be denudation rates: the Strengbach catchment case in the central Vosges massif
Authors: van der Woerd Jérôme , Moreno Martin Daniel S. , di Chiara Roupert Raphaël , Mathieux Bastien , Perrone Thierry , Rixhon Gilles , Merchel Silke , Mériaux Anne-Sophie , Chabaux François
Published: March 2024

Assessing the Quaternary topographic stability of western Europe middle mountains characterized by low tectonic activity remains challenging. We suggest to tackle this question in the Vosges – Upper Rhine Graben system where elevation reach up to 1400 m asl. This study is focused on the Strengbach catchment, that flows from the Vosges massif towards the Rhine graben, upstream of Ribeauvillé in the central Vosges. The catchment reaches 29 sq.km between 500 to 1200 m elevation. Morphometric analysis of the main trunk and tributaries is performed to constrain the areas of topographic disequilibrium along the valleys (knickpoints). 10Be cosmogenic isotope analysis in river sediments from various sites in the catchment is used to constrain the migration rates of these topographic instabilities at the millennial scale.The morphometric analysis performed in the Strengbach catchment (catchment topography - χ-elevation profiles) provide evidence of relic topographic surfaces upstream of a 2 km-long convex knick-zone located at about 700 m. Below this zone, the catchment is deeply incised and ramified with knick-points in the tributaries at about 500 m. Above the knick-zone, fluvial incision is reduced with a high-standing knickpoint at about 950 m marking the upper section of the Strengbach stream. 10Be denudation rates points to relatively small variations along the main trunk upstream (36 ± 2 - 44 ± 3 mm/ka), while denudation rates derived from the tributaries range from 38 ± 2 mm/ka to 75 ± 5 mm/ka. We show that these variations are primarily controlled by topographic and lithologic factors, namely the presence of sandstones in the sub-catchments, characterized by higher erodibility than crystalline rocks. The 10Be cosmogenic isotope concentrations in sediments from both upstream and downstream of the knickpoints, and in the tributaries, constrain at first order the migration rate of the knickpoints along the river profile and the retreat rate of sandstone cliffs upstream some tributaries. Migration rates on the order of 100-200 m/Ma suggest that at the millennial scale, the topography is relatively stable. These data will be used to discuss the source of topographic disequilibrium present in the catchments.
Potential for atmospheric carbon dioxide removal in mafic quarries via enhanced rock weathering of basalt fines
Authors: Stubbs Amanda , Khudur Faisal , MacDonald John , McDade Linzi , Friel Mark
Published: March 2024

Enhanced rock weathering (ERW) is a recognized carbon dioxide removal (CDR) strategy that uses crushed silicate rock (e.g., basalt) to capture atmospheric CO2, offering co-benefits such as improved soil health and increased crop production [1]. One of the main disadvantages of ERW includes the production of energy needed to crush and transport rocks to their application site [2]. Basalt quarries might be capable of removing CO2 on-site by optimizing the management of their quarry fines. This approach would reduce transport-related emissions while repurposing valuable and previously underutilized material. To test this possibility, basalt and dolerite fines from Breedon’s Orrock Quarry and Tarmac’s Cairneyhill Quarry in Scotland are used as potential feedstocks for on-site CDR, respectively. These samples show initial evidence of on-site weathering as secondary minerals are present in some areas of the fines at both the quarries. Thermogravimetric analysis (TGA) on these samples corroborates field observations as 0.75% and 1.76% CO2 were detected at Orrock and Cairneyhill, respectively. It is estimated that 10 kg CO2/ t Orrock fines and 23 kg CO2/ t Cairneyhill fines have been sequestered passively. Based on the CaO and MgO content, the carbonation potential is 190 kg CO2/ t Orrock fines and 160 kg CO2/ t Cairneyhill fines. Due to the challenge of accessing this potential under ambient conditions, it's essential to evaluate various on-site basalt management practices. To test this, ex-situ, column-based experiments were performed in the following manner. Fines from both sites were placed into columns with varying thicknesses (1 cm and 5 cm) and grain sizes (bulk and
Correlation between Ozone and Particulate Matter in the Near-surface Layer of Guangzhou Urban Area, China
Authors: Zhang Jinpu , Wang Xinming
Published: March 2024

A profound understanding of the correlation between ozone and particulate matter is crucial for the collaborative prevention and control of these pollutants. However, existing research predominantly focuses on near-surface analysis, with limited exploration into the vertical variations of the ozone-particulate matter correlation. Leveraging two years of observation data from the Canton Tower Atmospheric Pollution Vertical Gradient Observation Platform, this study investigates the correlation between ozone and particulate matter at different heights in the near-surface layer of Guangzhou urban area. The results indicate that: ①The correlation between ozone and particulate matter is more pronounced in summer and autumn at different heights but diminishes in winter; ②At lower levels, the correlation between ozone and particulate matter is weaker, ascending with altitude, and peaks at higher levels; ③Regardless of the height, the correlation between ozone and particulate matter is positively influenced by smaller particle sizes. In summary, within the near-surface layer below 500 meters in the urban area of Guangzhou, especially under meteorological conditions conducive to ozone generation, a significant positive correlation between ozone and particulate matter is evident. As altitude increases and particle size decreases, the correlation coefficient significantly rises, particularly in high-level ultrafine-sized particles, suggesting shared chemical mechanisms in the formation processes of ozone and particulate matter. This study contributes novel observational evidence supporting the cooperative control principle of ozone and particulate matter.