bluuebunny/crossref_metadata_2025 huggingface dataset:
The role of (in)organic carbon removal as a pretreatment in the 13C isotope composition of various soils
Authors: Jakab Gergely , Filep Tibor , Chevallier Tiphaine , Szalai Zoltán , Zachary Dóra
Published: March 2024

Soil carbon content is a crucial property in fertility and soil health. Carbon occurs in the soil in organic and inorganic forms. Soil organic carbon enters the soil mainly as plant residues and root extracts from the biosphere, whereas the primary source of inorganic carbon is the parent material. Both organic and inorganic carbon forms are affected by the current environmental and artificial conditions and, consequently, change in space and time. In this dynamic system, biogen or pedogen effects can reform carbonates and change organic matter composition. Both carbon forms are the focus of research in the soil however, the interaction between them is less understood. Inorganic carbon forms play an essential role in soil organic matter stabilization and, therefore, in maintaining soil functions. The present study aimed to investigate the organic-inorganic carbon interaction processes in various soil horizons. As a proxy, the stable isotope δ13C values were measured separately in the organic and inorganic pools and the bulk soil. Altogether, 55 soil samples were taken from top and subsoils under various land uses and texture classes. Beyond the measurement of the bulk soils, one aliquot was heated to 550°C for six hours to eliminate the organic carbon content, whereas another one was treated with HCl to remove the carbonates. All samples were measured using a Thermo Scientific FLASH 2000 HT elemental analyzer mass spectrometer, identifying δ13C composition. The sum of organic and inorganic carbon was higher than the total carbon content (R2=0.94), suggesting that at least one carbon removal pretreatment was incomplete. Some low inorganic carbon content (
3D object detection and tracking in debris flows with cameras and LiDARs
Authors: Hirschberg Jacob , Bickel Valentin Tertius , Aaron Jordan
Published: March 2024

Debris flows are destructive mixtures of water and sediments. In mountain regions, debris flows are a relevant hazard as they threaten people and infrastructure. They move with rapid to extremely-rapid velocities, and often feature a coarse-grained front followed by a liquefied tail. Recently developed LiDAR sensors allow for long-term monitoring of debris-flow dynamics at high spatial (
On the relation of CMIP6 GCMs errors at RCM driving boundary condition zones and inner domain for Central Europe 
Authors: Machado Crespo Natália , Holtanová Eva , Belda Michal , Halenka Tomáš
Published: March 2024

Global climate models (GCMs) are important tools for studying the climate system and climate change projections. Due to their coarse spatial resolution, downscaling is necessary on a regional scale, hence, regional climate models (RCMs) represent a common solution for this issue. Nevertheless, outputs of RCMs are influenced by the boundary conditions provided by GCMs. This study evaluates CMIP6 GCMs regarding the variables relevant as RCM boundary conditions. Special focus is on the simulation of CNRM-ESM2-1, which is being used as a driving model for convection-permitting Aladin-Climate/CZ RCM, used as one source feeding new Czech climate change scenarios. The analysis is conducted over the boundaries and inside the RCM integration domain, where ERA5 is chosen as reference for the boundary and E-OBS for the inner domain. The CNRM-ESM2-1 performs well in terms of near-surface variables over the Czech Republic, but it exhibits larger errors along the boundaries, especially for air temperature and specific humidity. Weak statistical relationship between the GCM performance over the boundaries in the upper levels and over the inner domain suggests that the nested RCM simulation does not necessarily have to be influenced by the biases in the driving data.
Forecast Verification in Operational Hydrological Forecasting: A Detailed Benchmark Analysis for EFAS
Authors: Tanguy Maliko , Harrigan Shaun , Carton De Wiart Corentin , Wortmann Michel , Haiden Thomas , Prudhomme Christel
Published: March 2024

Operational hydrological forecasting systems play a vital role for effective decision-making in disaster management and resource planning. This study addresses the critical need to conduct a fair and realistic assessment of the skill in one such system: the European Flood Awareness System (EFAS). As an integral component of the Copernicus Emergency Management Service (CEMS), EFAS undergoes monthly forecast verification, spanning lead times from 6 hours to 10 days. This verification process provides users with a valuable insight into the system’s performance in predicting streamflow for the preceding month.  Motivated by the importance of providing stakeholders with trustworthy information, our research focuses on a thorough examination of benchmark forecasts to evaluate EFAS performance. The choice of benchmark forecasts significantly influences the perceived accuracy of the system, and using benchmarks that are too easy to beat can lead to artificially inflated skill. Therefore, the primary objective of this work is to pinpoint the most suitable benchmark, serving as a robust reference for assessing the true capabilities of EFAS. This will then feed into the development of a ‘headline score’ which is a unique value of a key metric representative of a geographical domain that enables to track performance evolution.The study employs various benchmark forecasts, including persistence forecast, climatology, and the previous day’s forecast, using the Continuous Ranked Probability Skill Score (CRPSS) for skill assessment. Expanding on previous findings that identified persistence forecast as the most suitable for short lead times and climatology for longer lead times, this work refines and extends these results. We specifically examine the influence of catchment characteristics on the selection of the optimal benchmark at different lead times for operational forecasting evaluation. By uncovering the most robust benchmark, our study contributes to a more accurate understanding of EFAS capabilities, ultimately enhancing the overall performance assessment of EFAS. The nuanced insights gained from this focused examination serve as a step toward refining the methodology and criteria employed to develop new ‘headline scores’, instrumental in evaluating the evolution of the system’s forecasting skill.
The sandy beach subterranean estuary as a potential organic carbon sink
Authors: Amoako Kojo , Abarike Grace , Waska Hannelore , Niggemann Jutta , Dittmar Thorsten
Published: March 2024

Subterranean estuaries (STEs) beneath sandy beaches are biogeochemical reactors that can modify the chemical composition of fresh groundwater and recirculating seawater. Compared to surface estuaries, the mechanisms underlying the transformation of dissolved organic matter (DOM) in the STEs remain challenging to disentangle, particularly in high-energy beaches where DOM supplied from marine and terrestrial sources is exposed to alternating redox conditions, salinity gradients, and dynamic flows. Our study is aimed at elucidating the spatio-temporal patterns of DOM sources and sinks in high-energy beach STEs from a case study site on a barrier island in the German North Sea. We present a geochemical analysis of freshwater lens groundwater (FWL), seawater (SW), and beach STE groundwater samples (STEGW) collected over different seasons. STEGW samples were collected from multilevel wells with sampling depths of 6m, 12m, 18m, and 24m close to the dune base (ML1), near the high-water line (ML2), and the low-water line (ML3), and the FWLGW was collected from wells located at the northwestern part of the island. All samples were analyzed for their dissolved organic carbon (DOC) concentrations, and humic-like/terrestrial components of DOM (FDOM) were determined via fluorescence spectroscopy. DOM samples were desalted through solid-phase extraction and molecularly characterized via ultra-high-resolution electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. We found a decrease of FDOM along the salinity gradient in the land-sea continuum (FWL > STEGW > SW). DOC concentrations were highest in the FWL and SW but relatively lower in STEGW samples, suggesting a role of this STE as net organic carbon sink. The DOM composition of the groundwater samples from all sampling stations was highly diverse, with a total of up to 10,000 detected molecular formulas. The numbers of detected molecular formulas in FWL samples were twofold higher than those in SW samples, with intermediate values observed in the STEGW. There was a general decline in terrestrial DOM signature in the land/sea continuum, suggesting the loss of terrestrial DOM from land to the sea. Our results indicate that STEs under high-energy beaches are powerful sinks for organic carbon from both marine and terrestrial sources.
Back to the Otjosondu manganese deposit: an integrated structural, petrological and geochronological study
Authors: Plunder Alexis , Le Bayon Benjamin , Cagnard Florence , Poujol Marc , Cogné Nathan , Bailly Laurent
Published: March 2024

The Otjosondu area contains one of the most important Manganese deposit of Namibia. An exploration campaign in the late 2000’s acquired an extensive dataset (fieldwork, drillholes, geophysics and petrological data) to improve our knowledge of the deposit. The geological history is however, ill-studied and the deposit is classically attributed to banded iron formation of the Sturtian Chuos formation from the Damara sequence. Using samples from drillholes, we here provide Pressure-Temeprature-time constrain using thermodynamic modelling and LA-ICP-MS U-Pb ages on zircon, monazite and apatite to decipher the regional metamorphic evolution. Our petrological study concludes that the Otjosondu Mn deposit is affected by a HT-MP metamorphic event, estimated at ~670°C and 0.6. This HT-MP metamorphism is associated to a strong ductile deformation with development of shear zones, and multiple-scale intense folding. These metamorphic and structural features totally preclude the description of a typical sedimentary sequence, on which the previous authors had based their classical lithostratigraphic comparison. We date this HT metamorphic event at ca. 525Ma using U-Pb ages on monazite in paragneisses and in a granite, and U/Pb ages on zircon in the same granite.Detrital U-Pb ages on zircon reveal that the maximum deposition age is at ca. 540Ma. This excludes the attribution of the gneisses surrounding the Mn deposit to the Sturtian Chuos Formation challenging the prevailing interpretation of this ore deposit. Detrital U-Pb ages on zircon also record older magmatic events at ca. 620 and 585 Ma, which are well-known regionally, but were not previously documented in the Otjosundu area. Finally, U-Pb ages on apatite (490+/-3Ma) highlight a late thermal event (hydrothermal or static metamorphism). Results of this study illustrates the importance of characterizing the entire geological history of an ore deposit, to improve the future exploration.
Automated Solution for Discrete Gas Sample Analyses withPicarro G2508 and SAM Autosampler
Authors: Wozniak Jan
Published: March 2024

Automated Solution for Discrete Gas Sample Analyses withPicarro G2508 and SAM AutosamplerJan Woźniak1, Joyeeta Bhattacharya2, Magdalena E. G. Hofmann1, Frank Krijnen3, Guillermo HernandezRamirez41Picarro B.V., Eindhoven, The Netherlands, 2Picarro Inc., Santa Clara, USA; 3University of Saskatchewan; 4University of AlbertaAbstractGreenhouse gas research community has witnessed an ever-increasing need for automatedsolutions for measuring greenhouse gas concentrations in small discrete gas samples. However,traditional solutions like gas chromatographs often incur high initial and maintenance costs or arecomplicated to deploy and maintain, and almost impossible to work with in the field. There hasbeen a rising interest in the SAM autosampler (www.openautosampler.com) which so far hasbeen utilized mostly for isotopic measurements of greenhouse gases (e.g., isotopic CO2/CH4), inconjunction with low flow Picarro analyzers (200 mL/min). The results of our experiments show excellent precision and accuracy fordiscrete CH4, CO2 and N2O gas measurements. Also, we have been able to determine linearity indilution factors and characterized memory effects and its variability in different gas species (e.g.,comparing CO2 vs N2O). This report also provides recommendations on the methods and bestpractices for discrete gas sample measurements. In summary, the Picarro G2508 (or other GHGanalyzers) in conjunction with SAM Autosampler offers an attractive, cost-effective, and simpleralternative to gas chromatograph or similar available solutions
A global stochastic flood risk model for any climate scenario
Authors: Wing Oliver , Quinn Niall , Haylock Malcolm , Lamb Conor , Davies Rhianwen , Sampson Nick , Probyn Izzy , Daniell James , Elmer Florian , Brand Johannes , Bates Paul
Published: March 2024

Modelling flood hazards at large scales – both uniform frequency hazard maps and event simulations whose frequency varies in space – is a relatively new scientific endeavour. Data and computation constraints have historically necessitated either a more local focus to modelling efforts, or the building of proof-of-concept global-scale models whose fidelity inhibits most practical applications.Here, we present a global climate-conditioned flood catastrophe model; the culmination of decades of research into scaling inundation modelling, the incorporation of climate change, and synthetic event generation. 30 m resolution global maps representing fluvial, pluvial, and coastal flooding for given return periods were simulated using a hydrodynamic model with sub-grid channels whose inputs were defined using regional flood frequency analyses. Change factors from climate model cascades were flexibly used to perturb the local flood frequency a given flood map represents. Separately, a 10,000-year-long set of synthetic events were simulated using a conditional multivariate statistical model fitted to global fluvial-pluvial-coastal reanalysis data. The empirical return period of a given event is used to sample the corresponding flood map return period in order to build a long synthetic series of floods.With a global exposure model built using a top-down approach – downscaling capital stock models to high-resolution satellite-derived land-use and building height data – and a global vulnerability model derived from an extensive review of modelling and engineering literature, we demonstrate the calibration and validation of the global risk model. We also show the software challenges overcome to run this model, as well as to enable end-users to flexibly calculate the flood risk of their own exposures in the Oasis Loss Modelling Framework.
An effective machine learning approach for predicting near real-time ecosystem carbon cycle
Authors: Meunier Félicien , Sitch Stephen , Dietze Michael , Boeckx Pascal , Verbeeck Hans
Published: March 2024

Tropical forests store about half of the world’s above ground carbon and act as critical climate regulators as they absorbed one third of the global CO2 emissions over the past decades. These estimates of the present-day (and future) land carbon sinks are primarily obtained from land surface models (LSM) which are mechanistic tools that simulate the processes occurring at the interface between the atmosphere, the biosphere and the pedosphere. LSM are hence critical tools for understanding and predicting the dynamics of the land surface, its role in a changing Earth, and the impact of future climate and disturbances on its functioning. However, LSM have become increasingly complex and slow machinery that require heavy expert knowledge and computational tools to run. In this study, we tested whether data-driven (black box) models could efficiently reproduce process-based (mechanistic) models. To do so, we trained machine learning algorithms (gradient-boosted decision trees) with the model outputs of TrENDYv11 that were initially generated to estimate the global land carbon sink. Data-driven models performed extremely well in reproducing the long-term trends and the seasonality of the carbon sink over the Tropics, with an average accuracy of 91% and could further be used to make predictions, including near real-time forecasting of the carbon cycle of forests. We illustrate the latter by quantifying the impacts of last-year El-Niño on tropical ecosystem productivity, with a specific focus on the severe drought in the Amazon. While the simulations of the process-based models will only emerge in a year or so when the different teams will have run their own models, our tool could simulate in near real-time that the 2023 drought was for the largest reduction of Amazon GPP in recent history.
Exploring extreme flow events and associated patterns in Switzerland: a Dense feed-forward Neural Network approach
Authors: Zanoni Maria Grazia , Floriancic Marius , Seybold Hansjörg , Kirchner James W.
Published: March 2024

Switzerland relies significantly on sustainable water management to meet its diverse socio-economic and environmental needs. As climate change introduces heightened uncertainty in weather patterns, accurate forecasting of extreme flows from climatic data has become essential for efficient water resource management in the country. Furthermore, these events are likely shaped by nonlinear hydroclimatic and compound conditions distinct from typical average cases. A thorough understanding of these phenomena is therefore crucial for effective adaptation to changing climatic conditions. In this regard, data-driven techniques, such as Machine Learning algorithms, have proven capable of extracting knowledge from vast amounts of data, providing valuable insights into the underlying climate and societal dynamics driving extreme flow events.The aim of the present study is therefore twofold. First, we evaluate the ability of a Dense feed-forward Neural Network (DNN) model to predict drought and peak flow events in Switzerland based on anthropogenic, environmental and climatic data. On the other side, we investigate the role of each driver in the prediction and we study the temporal trends of the target and the features. The analysis was conducted on a large dataset consisting of daily discharge data from more than 400 sites across the country, from 1999 to 2019.  First, we evaluated the flow distribution at each individual site, considering only the extreme events and developing two distinct DNN models for droughts and for peaks. The DNN performed better in modeling droughts, achieving in the test set a mean Nash-Sutcliffe efficiency coefficient of 0.6 and a mean Kling-Gupta efficiency coefficient of 0.8, compared to 0.1 and 0.38, respectively, for the peaks.  A sensitivity analysis of the features, such as the cumulative precipitation and mean air temperature in the preceding weeks of the event, was performed. In addition, we delved into a detailed examination of the temporal trends of the climatic drivers and the extreme flow rates over the 20 years of the study. In the subsequent phase of the project, we explored a multi-site modeling approach to address the issue of the DNN model's poor performance in predicting peak flows.  We introduced geographic, land use and other anthropogenic factors specific to each watershed. By revealing the predictive potential of data-driven models, this study serves as a valuable foundation and resource for addressing extreme flow events and the hydroclimatic and anthropogenic patterns behind them.
Measurements of CO2 Profiles in the Lower Troposphere with the new Raman Lidar Channel of ARTHUS
Authors: Schumacher Moritz , Lange Diego , Behrendt Andreas , Wulfmeyer Volker
Published: March 2024

The variability of CO2 in the atmosphere is still not well understood. Key to improve this understanding are continuous measurements of the CO2 concentration over long periods of time as well as in different altitudes. At the “Land-Atmosphere Feedback Observatory” (LAFO) [1] of the University of Hohenheim, Stuttgart, Germany, we are operating the ground based Raman lidar system ARTHUS. ARTHUS stands for "Atmospheric Raman Temperature and HUmidity Sounder" [2]. This automatic system provides high resolution measurements up to the turbulent scale of temperature, water vapor mixing ratio as well as extinction and backscatter data continuously. But measuring CO2concentrations with Raman lidar is quite challenging because of its comparatively low concentrationresulting in an overall weak backscatter signal and thus a low signal-to-noise ratio. To investigate the capabilities of our system for capturing CO2 profiles, we developed and incorporated a new channel. For the measurements we utilize the 2ν2 CO2 Raman line, which is well separated from relevant Raman lines of other constituents of the atmosphere (e.g. O2). At the conference we will present and discuss the first results of the first measurements at the LAFO site between August and October 2023. Comparison of the measured with expected profiles show good agreement. The latter where obtained by appropriately scaling profiles of the water vapor mixing ratio channel of the same system. In the near future, we will add a scanning unit to the system. This will enable us to calibrate and compare the CO2 lidar data with in-situ instruments located at the ground. Furthermore, the identification and quantification of carbon sources and sinks along the surface will then be possible. References:[1] Späth, F., S. Morandage, A. Behrendt, T. Streck, and V. Wulfmeyer, 2021: The Land-Atmosphere Feedback Observatory (LAFO). EGU21-7693 (2021). DOI:10.5194/egusphere-egu21-7693[2] Lange, D. et al.: Compact Operational Tropospheric Water Vapor and Temperature Raman Lidar with Turbulence Resolution. Geophys. Res. Lett. (2019). DOI:10.1029/2019GL085774
Increased atmospheric CO2 and the transit time of carbon in terrestrial ecosystems
Authors: Muñoz Estefanía , Chanca Ingrid , Sierra Carlos
Published: March 2024

The response of terrestrial ecosystems to increased atmospheric CO2 concentrations is controversial and not fully understood, with previous large-scale forest manipulation experiments exhibiting contrasting responses. Although there is consensus that increased CO2 has a relevant effect on instantaneous processes such as photosynthesis and transpiration, there are large uncertainties regarding the fate of extra assimilated carbon in ecosystems. Filling this research gap is challenging because tracing the movement of new carbon across ecosystem compartments involves studying multiple processes occurring over a wide range of timescales, from hours to millennia. We posit that a comprehensive quantification of the effect of increased CO2 must answer two interconnected questions: How much and for how long is newly assimilated carbon stored in ecosystems? Therefore, we propose that the transit time distribution of carbon is the key concept needed to address these questions effectively. Here, we show how the transit time distribution of carbon can be used to assess the fate of newly assimilated carbon and the timescales at which it is cycled in ecosystems. We use as an example a transit time distribution obtained from a tropical forest and show that most of the 60% of fixed carbon is respired in less than 1 year; therefore, we infer that under increased CO2, most of the new carbon would follow a similar fate unless increased CO2 would cause changes in the rates at which carbon is cycled and transferred among ecosystem compartments. We call for a more frequent adoption of the transit time concept in studies seeking to quantify the ecosystem response to increased CO2.
A Graphical Representation of Climate Change Impacts with Associated Uncertainties
Authors: George Jose , Pavizham Athira
Published: March 2024

Recent decades have seen increased occurrence of extreme climatic events, which have had devastating consequences, both in terms of loss of life and property. Proper understanding of the possible variations in climatic extremes is important in developing mitigation and adaptation plans. Climate change impact prediction employs a series of numerical models, each with their own limitations that contribute towards the overall uncertainty. Climate change impact prediction results are often not intuitive to a decision maker and the added complexities from uncertainties can complicate the policy making exercise. A clear and concise representation of the possible risks of climate change and the associated uncertainties needs to be developed to bridge the gap between the climate scientist and the policy maker. Here, a framework for graphical representation of regional climate risks in terms of hazards and vulnerabilities is developed. The uncertainties are quantified in terms of level of confidence as the result of an ensemble exercise. To help regional stakeholders relate to the prediction results, analysis of extremes is performed with respect to historical hazards in the region. Risk factors for climate extremes that happened in the past in the region are studied and the future risk for an event of same return period is compared to the historical risk. The methodology is validated in the Bharathapuzha catchment in Kerala, India, a catchment which is identified to be climate change hotspot. In terms of flood events, the risk of low intensity flood events is seen to be increasing in the catchment with high confidence, while high intensity flood events are seen to be predicted at low levels of confidence. The catchment is seen to be drying up with high intensity drought events being predicted at high confidence.  
Energy Conversion and Transport in Dayside Electron Diffusion Regions.
Authors: Fargette Naïs , Eastwood Jonathan , Waters Cara , Newman David , Goldman Martin , Lapenta Giovanni
Published: March 2024

The electron diffusion region (EDR) is believed to be a key region for the conversion of energy associated with magnetic reconnection from magnetic to kinetic and thermal, but the nature of energy transport and conversion in EDRs is still not well understood. In this work, we capitalise on recent studies that have increased the number of referenced EDRs observed by MMS and perform a statistical study of 80 near X-line events previously identified in the literature. Upon detailed analysis, MMS was found to be located within the inner EDR for 45 of these events, while others correspond to outer EDR or IDR crossings.We investigate energy partition in their vicinity and find that the electron enthalpy flux dominates within the EDRs compared to the bulk kinetic and heat fluxes. We then evaluate the stationary terms of the energy conservation equation and find that large fluctuations of the electron enthalpy flux divergence tend to occur in the EDRs, suggestive of a complex energy transfer process dominated by the internal energy flux contribution. We also examine the possible role of magnetic shear/guide field, but this is somewhat limited by the fact that many events occur at relatively high shear and low guide field conditions. We conclude with considering how in future work, comparing these results to magnetotail- (symmetric) and magnetosheath- (low shear) EDR may bring further insight into how the regime in which magnetic reconnection occurs can impact the energy conversion and transport.
Simulating ice sheets during Pleistocene glacial cycles: A dance of CO2, ice and orbital cycles
Authors: Scherrenberg Meike D.W. , van de Wal Roderik S.W. , Berends Constantijn J.
Published: March 2024

During the Mid Pleistocene Transition (MPT; 1.2-0.7 Ma) glacial cycle periodicity shifted from 40 thousand years (ka) to an average 100 ka. While orbital cycles have a large influence on glacial cycle periodicity, the MPT took place without any clear change in the power spectrum of the orbital forcing. This suggests that the MPT must have resulted from Earth system processes rather than a change in external forcing.In this study, we use an ice-sheet model to simulate the evolution throughout the past 1.5 million years of the Laurentide, Eurasian, Greenland and Antarctic ice sheets. We force the model with last glacial maximum and pre-industrial climate time-slices from the PMIP4, which are interpolated according to prescribed CO2 and insolation reconstructions, as well as modelled ice-sheet geometry, thereby implicitly including the temperature-albedo and precipitation-topography feedbacks.We show that forcing the model with the combination of CO2 and insolation can capture the 40 ka cycles before the MPT and the 100 ka cycles after the MPT, without requiring a change in the ice-sheet model set-up. Deglaciations are initiated when the combination of CO2 and insolation creates a warm enough climate. Before the MPT, these conditions are met in almost all 40 ka cycles, as interglacial CO2 levels are high enough to cause deglaciations. After the MPT, interstadial CO2 levels tend to be low enough not to trigger a deglaciation during orbital maxima, resulting in longer glacial cycles. Results are most sensitive to the parameterization of the basal friction. Increased basal friction leads to more merged cycles before the MPT. Decreased basal friction will result in an increased likelihood for interstadial CO2 and insolation levels to result in complete melt of the North American ice sheet.
A Comparative mineralogical and geochemical studies of Eocene and Maikop oil shales in Eastern Azerbaijan: Stratigraphic controls on formation of oil and gas hydrocarbons in the South Caspian basin
Authors: Abbasov Orhan R. , Aliyev Adil A. , Baloglanov Elnur E.
Published: March 2024

The South Caspian Basin, subject to intense sedimentation due to its location in the Arabian-Eurasian collision zone, is known worldwide for its rich oil and gas deposits. It is also the region with the densest concentration of mud volcanoes in the world. On the western flank of the basin (East Azerbaijan), numerous surface oil-bearing occurrences and more than 100 oil shale outcrops are recorded. The results of studies carried out to date indicate the role of predominantly Upper Maikop (Lower Miocene) sediments in the formation of rich oil fields. However, the extraction of industrially important oil from Eocene deposits in the western part of the country makes one think positively about their prospects in East Azerbaijan.For the first time, we study the mineralogical and geochemical characteristics of oil shale rocks in the rock-ejecta of mud volcanoes as well as surface outcrops of Eastern Azerbaijan and compare the formation characteristics, and oil and gas potential of the Eocene and Upper Maikop sediments at the Paleogene-Miocene units.The results of our research revealed for the first time the high oil-generation potential of the Middle Eocene oil shale sedimentary complex containing type II kerogen, characterized by a thickness of 200-300 m. We believe that a major contribution to the formation of gas fields in the South Caspian basin is made by the Upper Maikop oil shales, which are formed under conditions of more intense input of terrigenous materials and preserve kerogens of types II-III and III. Compared to the Maikop oil shales, the richness of organic matter in the Eocene oil shales is due to the closer connection of the paleobasin with the sea, and the influence of volcanic ash and higher primary paleobioproductivity on sedimentation.
Implementing and verifying the algorithm used for generating Swarm L2 Fast-track data products
Authors: Rauberg Jan , Michaelis Ingo , Rother Martin , Korte Monika , Kervalishvili Guram
Published: March 2024

The Swarm mission of the European Space Agency (ESA) consists of three identical satellites named Alpha (A), Bravo (B), and Charlie (C), launched in a near-polar orbit on 22 November 2013. It is the first constellation mission for Earth Observation at Low Earth Orbit (LEO), which achieved the initial constellation on 17 April 2014, with Swarm A and C flying side-by-side at an altitude of about 470 km and Swarm B at an altitude of around 520 km. All of the satellites in the Swarm mission are equipped with six high-precision instruments which are identical and provide high-level data products for the past decade. These instruments include an absolute scalar and vector field magnetometer, a star tracker, an electric field instrument (Langmuir probe and thermal ion imager), a GPS receiver, and an accelerometer.The Swarm L1b fast-track (FAST) operational chain data are distributed more rapidly and frequently in comparison with the standard product provision (OPER), which is typically available after three days. The concept of FAST data products refers to the reduced time interval between the occurrence of an event and its detection or measurement. This significantly increases the applicability of Swarm data in the field of space weather monitoring and forecasting. We performed a quality check of FAST data against OPER data for L1b products that are required as an input for the GFZ L2 data product processing chain. Here, several GFZ Swarm L2 FAST data products are shown that have been tested and implemented for operational maintenance. The quality check and operational readiness have been analysed for geomagnetically quiet and disturbed periods. Overall, these products are suitable for the FAST operational chain.
Monitoring compound drought-heat events over Brazil’s Pantanal wetland
Authors: Martins do Amaral Cunha Ana Paula
Published: March 2024

Brazil’s Pantanal wetland is one of the most threatened Brazilian ecosystems from direct anthropogenic pressures and climate change. In this study, the overarching research question is to explore whether compound drought-heat events (CDHEs) have become more recurrent, intense, and widespread over Brazil’s Pantanal wetland in recent decades. For this, two different approaches were proposed and tested using validated long-term time series of monthly precipitation, temperature, and the satellite-based Vegetation Health Index (VHI) to characterize the spatiotemporal pattern of CDHEs over Pantanal. The Standardized Precipitation Index (SPI), Standardized Temperature Index (STI), and Standardized Precipitation Evapotranspiration Index (SPEI) from 1981 to 2021 were calculated. The results showed that using both approaches, the frequency of events is higher in the moderate category, which is expected since the criteria are less restrictive. In addition, the highest frequency of CDHE events occurs at the end of the dry season. The results also indicated that CDHE events have been more recurrent and widespread since 2000 in Pantanal. Besides, considering all methods for identifying the CDHEs, the probability density function indicates a shift pattern to warmer and drier conditions in the last 40 years. The Mann-Kendall tests also confirmed the assumption that there is a significantly increasing trend in the compound drought-heat events in the Pantanal. Developing methodologies for monitoring compound climate events is crucial for assessing climate risks in a warming climate. Besides, it is expected that the results contribute to convincing the urgent need for environmental protection strategies and disaster risk reduction plans for the Pantanal.
A Reanalysis-Based Global Tropical Cyclone Tracks Dataset for the Twentieth Century (RGTrack-20C)
Authors: Ye Guiling , Leung Jeremy Cheuk-Hin , Dong Wenjie , Xu Jianjun , Li Weijing , Qian Weihong , Zhang Banglin
Published: March 2024

Given the large impacts of tropical cyclones (TCs) on human society, the response of TC activity to climate change has widely drawn attention from both society and scientists. However, assessing how historical TC activity, especially intensity, evolved with climate change has proven challenging due to incomplete TC records in the early years. Here, we introduce the Reanalysis-Based Global Tropical Cyclone Tracks Dataset for the Twentieth Century (RGTracks-20C), which is reconstructed from the National Oceanic and Atmospheric Administration (NOAA) Twentieth Century Reanalysis (20CRv3) using two tropical cyclone tracking algorithms. Validations based on observations in the modern satellite era verify the ability of the RGTracks-20C to capture the climatology and long-term variability of TC numbers, tracks, duration, and intensity across various ocean basins. Furthermore, the RGTracks-20C fills the gaps of the incomplete TC track information, including position and intensity, in the early observational data. The RGTracks-20C is the first publicly available reanalysis-based century-long global TC track dataset, providing an alternative data reference for future research about climate change and TC-related disasters.
Thermal and thermohaline variable-density flow and salt transport in a 2D flow tank: Experiments, visualization and modelling
Authors: Graf Thomas , Basten Alexander , Cirpka Olaf A. , Neuweiler Insa , Rahmann Mohammad A. , Spitzenberg Frank
Published: March 2024

We carried out laboratory experiments of free thermal and thermohaline convection in homogeneous isotropic media using a laboratory-scale two-dimensional tank filled with glass beads representing a porous medium. Glass beads of different diameter were used in different experiments to achieve different permeabilities of the porous medium. Density and viscosity of the fluid were changed by initially introducing a salt (NaCl) solution, and by applying a heating device placed inside the tank. Fluid temperature inside the tank was measured over time on multiple thermocouples placed inside the tank on the inner glass walls. The fluid was dyed with two color tracers in order to visualize the emerging free convective flow pattern. The convective flow pattern was captured using a digital camera for the tracer distribution, and an IR camera for the temperature distribution. In subsequent numerical simulations, the experiments were successfully simulated numerically including density/viscosity variations and heat loss of the tank to the laboratory air across the back and front glass panes. Flow and transport parameters were calibrated using the results of the experiments with constant salinity. The set of calibrated parameter values was applied to successfully validate a thermohaline experiment with no need for further calibration. The processes of salt (NaCl) transport and heat transfer were both very accurately simulated in a single simulation. Analysis of flow velocities and streamlines showed that flow packages in a convection cell mostly follow a closed path such that there is little radial mixing. The approaches and results presented here can be used for interpretation, testing, and analysis of other simulation software of free thermohaline flow and transport.
Temporal and spatial analysis of landslide-triggering rainfall conditions in Qinghai-Tibet Plateau, China
Authors: Yao Kezhen , Gariano Stefano Luigi , Yang Saini
Published: March 2024

Landslide on the Qinghai-Tibet Plateau (QTP) is expected to be more affected by climate change due to the sensitivity of this unique climatic and geomorphological area to variations in temperature and precipitation. As an important response signal to climate change, a systematic framework for the assessment of landslide hazard and risk in QTP is necessary to investigate the potential impacts of climate change on landslides and related exposures.The study aims to establish an integrated model that synthesizes spatial and temporal landslide prediction, using statistical analysis, machine learning, and quantitative methods. The temporal landslide prediction is made by means of empirical rainfall thresholds, based on satellite rainfall estimates, whose feasibility for defining landslide-triggering rainfall thresholds was proved by several studies.A well-documented hazard database of the QTP provided by the China Geological Survey (4519 records from 2001 to 2022) indicates that landslides occurred here are mostly induced by rainfall from April to October, with an obvious seasonal characteristic, resulting in fatalities, damage, and affected population. According to the database, 3542 landslides are associated to a rainfall trigger. Based on the satellite-based rainfall product of CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data, version 2.0 final) daily data, we find that the rainfall of the occurrence day and the antecedent rainfall over the seven days before the landslides are significant indicators for the rainfall induced hazard. Using the frequentist method, the event duration-cumulated event rainfall (ED) thresholds at different non-exceedance probabilities for landslide triggering are calculated for the whole QTP area and for different environmental subdivisions within it. The thresholds show a robust definition with low parameter uncertainty. This is the first attempt to define empirical rainfall thresholds for landslide occurrence specifically for the QTP.Given the long-term of the used database, temporal and spatial analyses are conducted, to search for variations in the rainfall triggering conditions according to landslide locations and time of occurrence. Variations in the seasonal distribution and in the annual trends (using 5-year moving windows from 2007 to 2002) are evaluated. The impact of variations in rainfall patterns due to climate change making the landscape of the QTP more prone to landslides during the recent-most ten years is demonstrated by the gradual change of thresholds with lower intercepts and slopes. That means, for a certain rainfall duration, there is a tendency of lower rainfall threshold to trigger a landslide.The thresholds here defined are further combined with landslide susceptibility map based on Random Forest to derive a landslide hazard map for the interested area.
Study of Martian Ionospheric Plasma Depletion Events using MAVEN and Mars Express Spacecraft
Authors: Basuvaraj Praveen , Němec František , Fowler Christopher , Regoli Leonardo , Němeček Zdeněk , Šafránková Jana
Published: March 2024

Plasma Depletion Events (PDEs), characterized by a significant reduction (at least tenfold) in ion number density, are known to occur in the Martian ionosphere. Since its launch in September 2014, the MAVEN spacecraft has spotted around 1000 PDEs, primarily located in the nightside ionosphere and regions with strong crustal magnetic fields. We show that dayside PDEs are associated with an increased level of electrostatic fluctuations and suggest their formation through ambipolar diffusion triggered by the sudden escape of suprathermal electrons. We further investigate possible concurrent detections of PDEs by MAVEN and Mars Express. For this purpose, local electron density measurements from Mars Express near the MAVEN-identified PDEs are systematically checked. We present the first multi-spacecraft observations of PDEs, and we use them to discuss their spatio-temporal extents.
Analysis of Thermal Evolution History of Source Rocks and Natural Gas Accumulation Periods of Upper Paleozoic in the Wuqi Area of the Ordos Basin,China
Authors: Zhao Fanfan , Cui Junping
Published: March 2024

The distribution of oil and gas resources in the Upper Paleozoic of the Ordos basin is extensive, with well-developed source rocks. However, there is currently a lack of systematic research on source rocks in the Wuqi area, which greatly limits the oil and gas exploration work in this area. This study aims to restore the burial and thermal evolution history of the region, clarify the accumulation periods of source rocks, and promote the fine exploration and development process of oil and gas. It provides a basis for understanding and improving the oil and gas accumulation laws of the Upper Paleozoic in the entire basin. Research suggests that the Wuqi area has undergone four periods of erosion since the Upper Paleozoic, including the end of the Triassic, middle Jurassic, end of the Jurassic, and end of the Cretaceous. The first three periods of erosion were relatively small, mainly distributed between 100-200m, and the end of the Cretaceous period was characterized by significant erosion, which was the main erosion event. The interval transit time method was used to recover the erosion thickness at the end of the Cretaceous period in this study, mainly distributed in the range of 600-1500 m, and the overall erosion amount gradually decreased from east to west. We used vitrinite reflectance to restore palaeogeotherm and PetroMod software combined with parameters such as stratigraphy, lithology, erosion thickness, and boundary condition to reconstruct the burial history and thermal evolution history of the Wuqi area by basin simulation methods. Microscopic observation and combined with fluid inclusion homogenization temperature data were used to further determine the oil and gas accumulation period through a combination of forward and reverse analysis. According to the inclusions and homogenization temperature, it is reflected that there are mainly early and late inclusions in the Upper Paleozoic mudstone in the Wuqi area. Early fluid inclusions are mainly distributed on the secondary enlargement edge of quartz, with temperatures mainly ranging from 110 to 140 ℃; The late stage fluid inclusions are mainly distributed in quartz particle fractures, with temperatures mainly ranging from 100 to 160 ℃, which is the main charging period. The temperature distribution of the two phases of inclusions is continuous process. In conclusion, there were two consecutive oil and gas changes in the Upper Paleozoic in the Wuqi area of the Ordos basin: the first oil and gas charging period was in the Middle Jurassic; The second oil and gas charging period was in the Early Cretaceous.
Characterizing Nonlinearities in ENSO Dynamics Using Hybrid Machine Learning Models
Authors: Schlör Jakob , Thuemmel Jannik , Capotondi Antonietta , Newman Matthew , Goswami Bedartha
Published: March 2024

Event-to-event differences of the El Niño Southern Oscillation (ENSO) result in different patterns of extreme climate conditions globally, which requires ENSO forecasts that accurately predict both the likelihood and the type of an event. One question regarding predictable ENSO dynamics is the extent to which they may be captured by multivariate linear dynamics and, relatedly, whether predictable nonlinearities must be accounted for or may be treated stochastically.In this study, we combine Recurrent Neural Networks with the Linear Inverse Model (LIM) to assess the role of predictable nonlinearities and non-Markovianity in the evolution of tropical Pacific sea surface temperature anomalies. We observe that modeling nonlinearities significantly enhances the forecast accuracy, particularly in the western tropical Pacific within a 9 to 18-month lag time. Our results indicate that the asymmetry of warm and cold events is the main source of the nonlinearity. Moreover, we demonstrate that the predictability of the Hybrid-model can be reliably inferred from the theoretical skill of the LIM whereas a similar assessment is not possible in pure deep learning models.