bluuebunny/crossref_metadata_2025 huggingface dataset:
A Community Dataset for Comparing Automated Coronal Hole Detection Schemes and its Imprint on Magnetic Models
Authors: Majumdar Satabdwa , Reiss Martin , Muglach Karin , Mason Emily , Davies Emma , Chakraborty Shibaji ,   S2-01 ISWAT Team
Published: March 2024

It is now known that the fast solar wind streams originating from coronal holes can have a significant contribution to geomagnetic activity, particularly during periods of low solar activity. Moreover, coronal holes, many of which are long lived and overall time steady structures, have proven to be ideal hunting grounds for understanding the fast solar wind. In this regard, automated detection schemes are nowadays a standard approach for locating coronal holes in EUV images from the Solar Dynamics Observatory (SDO). However, several inevitable factors make this automatic identification challenging. While discrepancies between detection schemes have been noted in the literature, a comprehensive assessment of these discrepancies, which is still lacking, is of equal importance. Here we present the first community dataset for comparing automated coronal hole detection schemes. This dataset consists of 29 SDO images, all of which were selected by experienced observers to challenge automated schemes. We then use this dataset as input to 14 widely-applied automated schemes to study coronal holes and collect their detection results. From this, we select and study three SDO images that exemplify the most important lessons learned from this effort. We find that different detection schemes highlight significantly different physical properties of coronal holes. Motivated by these outcomes, we look into the effect of these results on the inferred magnetic connectivity in the corona by comparing the detected coronal hole boundaries to magnetic model solutions. These results, along with the database, will provide rich inputs to our understanding of coronal holes and their connection to the solar wind.
Modelling of Air Pollution and Quality (Pm 2.5) in Bursa Urban Area via Machine Learning
Authors: Akbas Abdullah
Published: March 2024

In this study, it is aimed to model the meteorological conditions that play a role in the temporal distribution of air pollution parameter PM 2.5 by machine learning. For this purpose, daily PM 2.5 data were obtained from the database of the Ministry of Environment, Urbanisation and Climate Change between 2013-2015. In addition, in this study, a model was established between the daily maximum-minimum temperature obtained from the General Directorate of Meteorology and daily average temperature, pressure, wind speed and daily total precipitation. From this database, the days with no measurements were completed with missing data imputation. The database with missing data estimated was then made ready for the machine learning method. Support vector machine (SVM) is one of the most effective machine learning methods. These daily air pollution data and meteorological data were established using support vector regression radial kernel and then the best parameters were determined by applying tuning process. Accordingly, a correlation of 0.8 between the modelled and observed data and a Root Mean Square Error of 9.03 were obtained. This shows that the observation and modelling are quite consistent. In addition, the contribution of meteorological parameters in the model was determined. In this respect, pressure, minimum temperature, wind speed, average temperature, maximum temperature and precipitation are effective respectively. The effect of pressure conditions on the station, especially on the plain, is closely related to the inversion conditions.
Evolution of sheaths and magnetic obstacle from the inner to the outer heliosphere. 
Authors: Larrodera Carlos , Temmer Manuela
Published: March 2024

Our study covers a comprehensive analysis of Interplanetary Coronal Mass Ejections (ICMEs) across a wide distance from 0.25-5.42 AU and temporal range from 1975-2022. Our primary focus is a statistical examination of a variety of physical parameters for the structures within ICMEs, specifically the sheath and magnetic obstacle (MO). Our methodological approach integrates data merging from 13 individual ICME catalogs into a unified catalog, facilitating a comprehensive evaluation of in-situ measurements obtained from diverse spacecraft. This approach offers an opportunity to discern variances across different solar cycles. Our empirical findings provide intriguing insights. Notably, MOs preceded by a sheath exhibit a marked increase in size upon reaching 1 AU from the Sun. Furthermore, both structures, MO and sheath, experience a strong increase in size around 0.75 AU, correlating with a decrease in the measured density at this distance. Moreover, our analysis reveals a shift in the spatial positioning of material accumulation proximate to the sheath interface. This transformation suggests a potential transition in the underlying mechanism governing sheath formation, indicating a shift from externally driven to internally accumulated material processes.
Comparative effect of incorporated and surface spread crop residues, poultry manure and their biochars on soil health indicators along a soil profile 
Authors: Shahzad Tanvir , Mir Rummana Basit , Fiaz Umme Aiman , Shahid Huma , Arshad Fiza , Sanaullah Muhammad
Published: March 2024

Biochar is being touted as a wonderful amendment for improving soil health. However, its effectiveness for alkaline soils that are poor in organic matter has rarely been evaluated, particularly in long term field experiments. We laid down a field experiment based on wheat-maize crop rotation where we either incorporate or spread on surface the residues of the previous crop (wheat or maize), poultry manure or biochar(s) derived from these organic amendments. They are applied at the rate of 2 tons ha-1 before sowing each crop. It was hypothesized that the organic amendments applied in their feedstock or biochar form will considerably differ in space and time vis-à-vis soil health indicators. Moreover, tillage (incorporation i.e., conventional tillage vs surface spreading i.e., no tillage) would significantly alter the effect of these organic amendments. Over two years and four cropping seasons, the CO2-C emissions from the field were significantly higher (12-17%) when residues or biochar were incorporated. However, the feedstocks (residues/manure) induced significantly higher CO2-C emissions than their respective biochars across the tillage treatments (13-23%). Furthermore, the ammonia emissions were significantly reduced when biochars were added (5-11%) where surface spreading, or incorporation didn’t induce any difference. First soil sampling was done till 75 cm in depth increments of 15 cm, after two years of the experiment (Nb: the experiment is running). Microbial biomass (MBC) was significantly higher in upper layers (0-15 cm, 15-30 cm) in the plots incorporated with residues while all other amendments or tillage treatments showed similar MBC. No change in MBC was observed below 30 cm in any treatment. The soil organic carbon content (& stocks) were slightly but significantly higher (by 5-14%) in upper layers where biochars were incorporated, whereas incorporating residues increased soil organic carbon compared to biochar surface spreading. The extracellular enzymatic activity particularly of β-glucosidase, was significantly altered to 60 cm in some treatments with residue addition (incorporation or spreading) inducing higher activity. The leucine aminopeptidase activity remained unchanged throughout the soil profile in most of the treatments. However, chitinase activity was significantly higher in some biochar amended soils. These preliminary results indicate that residues/manure as well as their biochar significantly improve soil health indicators and that their method of application (incorporation vs spreading) significantly alter their effects. However, it must be noted that both types of amendments have improved different soil health indicators at this stage of the experiment.  
Looking below the ground: analyzing the processes that drive spatiotemporal variation of wet channels in dynamic river networks using a physics-based hydrological model
Authors: Zanetti Francesca , Botter Gianluca , Camporese Matteo
Published: March 2024

Non-perennial streams, i.e., rivers that periodically cease to flow, are the focus of increasing research attention. Understanding how the spatiotemporal dynamics of runoff generation drives expansions and contractions of their active stream network is still challenging, due to the complex interplay among climate, topography, and geology. In this context, experimental data on the spatiotemporal variations of the wet channels of a river network are very valuable to study the joint variations of active stream length (L) and discharge at the catchment outlet (Q) and to analyze the processes driving such complex L-Q patterns. However, experimental data usually do not provide insights on what happens below the catchment surface; therefore, important insights can be gained by integrated surface-subsurface hydrological modeling (ISSHM), whereby the spatial configuration of the wet channels, the corresponding catchment discharge and the processes that drive the wetting and drying of different portions of the stream network can be simulated across the whole surface-subsurface continuum. In this study, we used CATHY (CATchment HYdrology) to simulate the stream network dynamics of two virtual catchments with the same, spatially homogeneous, subsurface characteristics (hydraulic conductivity, porosity, water retention curves, depth to bedrock) but different morphology (shape and slope). By running simulations under transient and steady-state conditions for different levels of antecedent catchment wetness, we investigated the role of topography, climate, and morphology on the resulting L-Q relation and on the processes that lead to the emergence of wet channels while comparing the numerical results with corresponding outcomes from simplified analytical formulations. Overall, we show that ISSHMs are useful tools to identify the main physical drivers of non-perennial streams, thanks to their capability of accurately describing the spatiotemporal variations of the storages and fluxes across the landscape, which eventually control network dynamics.
The Amazon plume in 2020-2023: its shelf carbon budget and water origin revisited 
Authors: Reverdin Gilles , Olivier Léa , Boutin Jacqueline , Waelbroeck Claire , Leseurre Coraline , Bretel Patrice , Demange Jérôme , Fin Jonathan , Pesant Stéphane , Huber Paula , Sarmento Hugo , Vandemark Doug , Hunt Chris , Iudicone Daniele , Govin Aline , Speich Sabrina
Published: March 2024

The Amazon shelf of South America is known to be highly contrasted in its surface carbon dioxide concentrations, from very high concentrations near the estuary, and very low concentrations downstream in the saltier Amazon plume, which results in a great contrast in carbon dioxide exchange with the atmosphere. During three cruises in 2020-2023 (Eurec4A-OA, Tara-Microbiomes legs 5, 6 and 7, Amaryllis), dissolved inorganic carbon (DIC) concentration, its isotopic composition (δ13C-DIC), the water isotopic composition (d18O-H2O and d2H-H2O), as well as inorganic nutrients and surface CO2 partial pressure (pCO2) were measured on the Amazon shelf of South America during three cruises in different seasons. These data are used to better understand mixing in the continuum between river water and open-ocean waters, and the biogeochemical processes taking place on the shelf close to the Amazon and Para river estuaries. The water isotopes are furthermore used to identify different freshwater origins.The accuracy of the data is discussed as well as its representativeness. The data are then combined to first identify large variations of the river freshwater sources, compatible with 2021 being a year of very large discharge, and 2023 a year of exceptional low discharge. In addition, the data mostly from August and September 2021 identify a smaller influence of sources and sinks of dissolved inorganic carbon in the mixing shelf region than what had been earlier observed during the Amasseds cruise data in November-December 1991, a much lower river discharge period. This indicates that there might be a larger seasonal and/or interannual variability of these processes than what was earlier assessed. Measured pCO2 data on the Amazon shelf in 2021 are then discussed in this context.
Sectoral differentiation of CH4 footprints by using the ICON-ART model – A feasibility study
Authors: Mamtimin Buhalqem , Rösch Thomas , Ellerhoff Beatrice , Jiménez de la Cuesta Otero Diego , Kaiser-Weiss Andrea K.
Published: March 2024

In this study, we present an ICON-ART (ICOsahedral Non-hydrostatic Aerosols and Reactive Trace gases) model based sectoral differentiation of CH4 concentration in terms of a feasibility study. ICON-ART is an extension of the numerical weather prediction model ICON used by DWD. The physical parameterizations and numerical methods of ICON used in ICON-ART, which simulated the interactions between trace subtances and the state of the atmosphere.The motivation for the sectoral differentiation based on the model is directed towards the comparison of the field measurements, with the assumption that the modeled simulations could represent a response signal of how each sector contributes to the measured concentration on the Integrated Carbon Observation System (ICOS) stations of interest.The CH4 concentrations for various economic sectors of Europe and of Germany are simulated using ICON-ART model. In order to compare the model results and against measurements  from the Integrated Carbon Observation System (ICOS) stations, the model equivalents have been extracted at the locations of the ICOS monitoring stations. We test our experimenal setup in a feasibility study, which shows benefits of using the ICON-ART model to comprehend emissions from various sectors.
Improving the long-term Δ47 reproducibility of the Thermo Scientific 253 Plus 10 kV IRMS using a prototype Peltier cooling device
Authors: Rinyu László , Czébely Andrea , Kiss Diána , Kele Sándor , Túri Marianna
Published: March 2024

Carbonate clumped isotope analysis, a relatively new methodology, is still developing rapidly, that is well described by the frequency of changes in the applied methodological conventions. The extent of development is also characterized by the growing, sometimes special, nature of the application areas. Innovations, while promising, can present unforeseen challenges and sometimes brings unexpected difficulties, such as the integration of 1013 Ohm resistance in the amplification circuits of Thermo Scientific 253 Plus 10 kV Isotope Ratio Mass Spectrometer (IRMS).The goal of this improvement was that even very small ion beams can be analyzed with the factor of 3 better signal to noise ratio, which is an important aspect from the point of view of clumped isotope analysis. Unfortunately, 1013 Ohm resistance has a significant temperature dependency, which highly influences the magnitude of the detected intensities as well as on the overall long-term stability of the measurement. The daily temperature fluctuation in summer is very significant in Hungary. Under extreme conditions, when the lab's air conditioning could not maintain the desired temperature range, the long-term Δ47 reproducibility of the system achieved an SD = 60 ppm value.In order to reduce this effect a prototype Peltier cooling device has been installed on the surface of the detector house of our IRMS. To demonstrate the achieved accuracy, precision, and long-term stability (SD
Global SV wave upper mantle model.
Authors: durand stephanie , ricard yanick , dubuffet fabien , debayle eric
Published: March 2024

We present the latest update of the global SV model developed by our team, in Lyon. It is based on the waveform modeling of more than 3 millions Rayleigh waves recorded since 1976. The tomographic model is built using the same automated scheme as was presented in Debayle et al., GRL 2016, while the number of data has increased by a factor larger than 2. For each seismogram, we obtain a path average shear velocity and quality factor model, and a set of fundamental and higher-mode dispersion and attenuation curves from 40s to 250s. We incorporate the resulting set of path average shear velocity models into a tomographic inversion. Due to the drastic increase of data, this second step of inversion became too computationally costly. We rewrote it so that the largest matrix to invert has now a size (number of geographical point)**2 instead of (number of data)**2. Thanks to these improvements we reduced the correlation lengths from 4 deg down to 1deg.  We will focus in several geographical areas and geological objects, to emphasize the improvement in precision of this new model. We will also present our new online tool (https://fascil.univ-lyon1.fr/) available to explore this tomographic model and to compare with existing ones.
Atmospheric circulation sensitivity to changes in Arctic soil thermodynamics and hydrology
Authors: Martínez-Vila Alex , Gonzalez-Rouco J. Fidel , Meabe-Yanguas Nagore , García-Pereira Felix , Jungclaus Johann , Lorenz Stephan , de Vrese Philipp
Published: March 2024

Changes in modes of atmospheric circulation contribute to shape climate at regional scale by interacting with orography. Earth System Models (ESM) tackle the response of these modes to global warming. However, there exists considerable uncertainty regarding the magnitude and impact of the changes in modes of variability. This uncertainty is mainly due to internal variability, and inter-model variability related to the different resolution and parametrisation of physical processes in ESMs. One example of the latter is the representation of soil thermodynamics and hydrology in the Arctic. Different representations of Arctic dynamics have the potential to affect the circulation, not only locally in the Arctic, but also at mid-latitudes and the tropics via a series of teleconnections. The physical processes linking Arctic warming and sea-ice loss to lower latitude climate variability are still not well understood. This study addresses how changes in Arctic soil thermodynamics and hydrology affect the global atmospheric circulation. To do so, a modified version of the Max Plank Institute Earth System Model (MPI-ESM) was used to produce an ensemble of simulations with different set-ups of its Land Surface Model (JSBACH). These configurations consider different representation of the Arctic thermo-hydrodynamics leading to comparatively drier or wetter states. Preliminary analysis show sensitivity of atmospheric circulation to changes in the Arctic Amplification. Results are shown for a comparison of the response of extratropical (Arctic and Antarctic oscillations) and intertropical (monsoons and ENSO) modes across the ensemble of simulations.
Best of SIDFEx: Highlights and lessons learned from six years of sea-ice drift forecasting
Authors: Reifenberg Simon F. , Ludwig Valentin , Goessling Helge F. ,   SIDFEx Team
Published: March 2024

We showcase the Sea Ice Drift Forecast Experiment (SIDFEx) database. SIDFEx is a collection of close to 225,000 lagrangian drift forecasts for the trajectories of assets (mostly buoys) on the Arctic and Antarctic sea ice, at lead times from daily to seasonal with mostly daily resolution. The forecasts are based on systems with varying degrees of complexity, ranging from free-drift forecasts to forecasts by fully coupled dynamical general circulation models. Combining several independent forecasts allows us to construct a best-guess consensus forecast, with a seamless transition from systems with lead times of up to 10 days to systems with seasonal lead times. The forecasts are generated by 13 research groups using 23 distinct forecasting systems and sent regularly to the Alfred-Wegener-Institute, where they are archived and evaluated. Many groups send forecasts operationally in near-real time.In our presentation, we will introduce the motivation behind and setup of SIDFEx, as well as an overview on the general forecast skill. We will focus on selected highlights, comprising the operational support of research cruises, short-term predictions of sea-ice deformation and regular contributions to the Sea Ice Outlook competition.
Influence of fault system geometry and slip rates on earthquake triggering and recurrence variability, insights from Coulomb stress interactions during historical earthquake sequences in Italy
Authors: Sgambato Claudia , Faure Walker Joanna P. , Roberts Gerald P. , Mildon Zoë K. , Meschis Marco
Published: March 2024

We investigate the Coulomb stress changes due to 30 strong earthquakes occurring on normal faults since 1509 A.D. in Calabria, Italy, including the influence of both coseismic and interseismic loading in our modelling. We compare the results to existing studies of stress interaction from the Central and Southern Apennines, Italy. The three normal fault systems have different geometries and long-term slip-rates. The Central Apennines hosts a complex fault system, with many faults across strike, so that when an earthquake occurs, many of the surrounding faults experience a stress decrease. The Southern Apennines and Calabria have a simpler geometry, with fewer faults, and faults are located predominantly along strike, therefore when an earthquake occurs the dominant process on the neighbouring faults is stress increase. We investigate how stress transfer may influence the occurrence of future earthquakes and what factors may govern the variability in earthquake recurrence in different fault systems. Within the analysed time period, the Calabrian, Central Apennines, and Southern Apennines fault systems have 91%, 73% and 70% of faults with a mean positive cumulative Coulomb stress change, respectively; this is due to fewer faults across strike, more across strike stress reductions, and greater along-strike spacing in the three regions respectively. In regions with close along strike spacing or few faults across strike, such as Calabria and Southern Apennines, the stress loading history is mostly dominated by interseismic loading and most faults are positively stressed before an earthquake occur on them (96% of all faults that ruptured in Calabria; 94% of faults in the Southern Apennines), and some of the strongest earthquakes occur on faults with the highest mean cumulative stress of all faults prior to the earthquake. In the Central Apennines, where across strike interactions are the predominant process, 79% of the earthquakes occur on faults that are positively stressed. The results highlight that fault system geometry plays a central role in characterizing the stress evolution associated with earthquake recurrence, and can possibly influence the occurrence of propagating triggered earthquake sequences.
Multitemporal and Multispectral Drone Data for Classifying Tree Species in an Austrian Riparian Forest
Authors: Mihatsch Noah , Lechner Michael , Daryaei Ardalan , Immitzer Markus , Atzberger Clement
Published: March 2024

The climate crisis is threatening native forests all over Europe and a change in the composition of species can be expected in the future. Diversity of tree species is one key aspect of resilience against the climatic stress caused by the climate crisis. To maintain one of the last huge floodplains in Europe – the Danube Floodplain – for future generations, it is necessary to monitor the change of the species distribution and the development of eco-systems. Remote sensing is widely used for establishing a constant monitoring of forests, including tree species classification (TSC). Currently, Unmanned Aerial Vehicles (UAVs) offer very high-resolution data together with temporal flexibility and cost efficiency which can be used in the management practice of forests and national parks in particular. However, due to the extensive diversity inherent in different forest types and tree species, the results obtained in the state-of-art research in TSC via very high-resolution optical data cannot be generalised. As there is still a gap in research in the field of TSC in riparian forests, this study aims at filling this gap with preliminary results of TSC in a riparian forest, namely the Danube Floodplain National Park (Austria). Therefore, three drone flights were conducted during October, September, and May spanning the years 2021 and 2022 together with a simultaneous collection of reference data in the field. Tree crowns were delineated manually in two different ways: point-buffered and exact delineation of the crown shape. Multiple object-based Random Forest models were performed, comparing mono- and multitemporal data as well as two different spatial resolutions (3.0 cm and 6.4 cm) and the two different levels of detail of the delineation of tree crowns. Highest Overall Accuracy (OA) for 12 different tree species and one dead wood class could be reached by the multitemporal model at 82.1 % (kappa = 80.8 %) with the higher spatial resolution (3.0 cm) and the exact delineation of the reference data. Producer’s Accuracy (PA) and User’s Accuracy (UA) varied between 50 % and 100 % for different classes. Promising results from this study showed that the presented method can be used for precise monitoring of tree species diversity in the Danube Floodplain National Park. Further improvement could be reached by merging data from different sensors.
Estimation of Lateral River Aquifer Exchanges with Physics Informed Neural Networks
Authors: Bajpai Mayank , Mehulkumar Rajkumar Lakhadive , Mishra Shreyansh , Gaur Shishir
Published: March 2024

This study introduces a novel approach for estimating lateral river-aquifer exchanges by employing Physics Informed Neural Networks (PINNs). The methodology compares the predictive capabilities of neural networks with the physics-based modeling provided by MODFLOW's Horizontal Flow Barrier (HBF) package, implemented through FloPy. As a foundation, the HBF package in MODFLOW establishes a baseline model, serving as a benchmark for performance comparison.The integrated model leverages observed data and the fundamental principles of hydrogeology, enabling a robust estimation of lateral exchanges. The synergy of PINNs and MODFLOW HBF enhances the model's adaptability to diverse hydrogeological conditions, providing accurate predictions of intricate river-aquifer interactions. The comparative analysis with the MODFLOW HBF package underscores the efficacy of the proposed approach, offering insights for improved water resource management and environmental decision-making.
Surface air temperature sensitibily to changes in land surface model thermodynamics and hydrology
Authors: Meabe-Yanguas Nagore , González-Rouco Jesus Fidel , García-Pereira Félix , Steinert Norman , de Vrese Phillip , Jungclaus Johann , Lorenz Stephan
Published: March 2024

The Arctic region is particularly sensitive to global warming due to snow and sea ice dynamics, as well as to the strong positive feedback mechanisms that amplify Arctic warming response to forcing, such as ice-snow-albedo feedback or lapse-rate feedback. The presence of permafrost makes the Arctic also relevant for global climate, since Arctic soils contain large quantities of carbon with radiative feedback implications. Improved representation of the physical processes in frozen soils  and considering different model variants allows for assesing uncertainties in permafrost related processes. In this study several experiments with different set-ups of the Arctic thermo-hydrodynamics will be analyzed in order to understand how different parametrizations in permafrost areas affect Earth’s climate and in particular the surface temperature in the Arctic. Those set-ups also account for different vertical discretizations of the land model. The different model configurations lead to relatively different climate background states in the Arctic, with the different vertical discretization set-ups playing a minor role. A positive sea-ice-snow-albedo feedback is shown to enhance the warming signal under a climate change scenario. The magnitude of the feedback depends on the background state and available snow and sea-ice. By assessing the Arctic amplification ratio (AA) we conclude that all configurations show considerable (internal) AA variabillity in the 20th and the first quarter of the 21st century, but end up converging to a factor of 2-3 times larger warming in the Arctic regions than globally by the end of the century. This suggests that high AA values recently found in observations are related to internal variability.
Using fracture-scarp lineations as kinematic indicators on active normal fault scarps
Authors: Andrews Billy , Mildon Zoë , Lukas Diercks Manuel , Mitchell Sam , Roberts Gerald , Rodriguez Piceda Constanza , Robertson Jenni
Published: March 2024

To undertake fault-based seismic hazard assessment, we need to accurately identify source faults and assess their slip-rate and kinematics through pertinent data collection. For example, converging slip vectors may be used to deduce whether isolated fault strands are connected at depth. Kinematic (slip vector) data can be collected through offset piercing points or from striations preserved on fault scarps. However, striations are surficial features and may therefore be readily eroded and not preserved or visible on degraded scarps. Tensional fracture networks are ubiquitous on bedrock fault scarps and extend deeper into the scarp, and therefore have a greater preservation potential when compared to striations. In this work we characterise fracture-scarp (F-S) lineation patterns across eight faults in Italy (Central Apennines) and Greece (Perachora Peninsula) to explore how these patterns relate to fault plane geometry and slip-vector.Various fracture-scarp (F-S) lineation patterns (including sinistral/dextral en-echelon arrays, slip-parallel/-perpendicular fractures, and conjugate sets) are recognised. These patterns show evidence of progressive growth during exhumation. This suggests F-S lineations formed near the surface as the footwall uplifts, with larger features becoming more connected and smaller ones remaining ‘isolated’. The orientations of F-S lineations align within a pure or Riedel shear geometry where the shear sense is related to the rake of the slip vector. We propose that the observed patterns are controlled by fault plane orientation relative to a 3D strain ellipsoid and the progressive reduction of effective normal stress during footwall exhumation. As fractures form under the same stress regime as striations, they can serve as a kinematic indicator even on highly degraded active fault scarps.
Detection and characterization of airborne pollen using lidars in Finland
Authors: Shang Xiaoxia , Filioglou Maria , Giannakaki Elina , Bohlmann Stephanie , Komppula Mika
Published: March 2024

Pollen has various effects on human health and the environment. Studies show that lidar (light detection and ranging) can detect the presence of pollen in the atmosphere, and it is possible to track airborne pollen using the depolarization ratio in the absence of other depolarizing non-spherical particles (e.g. dust).Since 2016, several pollen campaigns were performed at Vehmasmäki (62°44'N, 27°33'E, 190 m above sea level) site, a rural forest area located ~18 km from the Kuopio cite centre, in Eastern Finland. The clean air in Finland favours the pollen study. This station is operated by the Finnish Meteorological Institute, and is permanently equipped with a multi-wavelength Raman polarization lidar PollyXT, a Halo Photonics StreamLine Pro Doppler lidar, a Vaisala CL61 ceilometer, and multiple in situ instruments. All three lidars are equipped with polarization channels and enable the investigation of the optical properties at the wavelengths of 355, 532, 910 and 1565 nm. In addition, a Hirst-type Burkard pollen sampler was placed 4 meters above ground level near the lidars, which enabled the microscopic identification of pollen types and the number concentration.During the pollination events, enhanced linear particle depolarization ratios (PDRs) were detected by lidars, suggesting the presence of non-spherical particles. A positive (negative) correlation was found between the pollen concentration (contribution of other aerosols) and PDRs. Depolarization ratios of pollen layers were measured at four wavelengths, allowing investigating its wavelength dependence. This could enable the distinction of pollen from other depolarizing aerosols. Results also highlight the suitability of the PDR at longer wavelengths for pollen detection. We have developed two pollen algorithms for characterizing the optical properties of pure pollen particles, based on PollyXT measurements. They were applied to evaluate the pollen depolarization ratio which is an essential parameter needed to separate pollen backscatter from the background aerosol backscatter. The algorithm was also applied for the aerosol classification, and identified different pollen types.
An assessment of global-scale drivers of climate disaster impacts and risk
Authors: Teber Khalil , Montero David , Mahecha Miguel D.
Published: March 2024

The complex interplay between environmental and anthropogenic factors across the globe results in differing impacts of climate and weather related disasters. Communities living in deprived socioeconomic conditions are usually subjected to severe impacts, as they are more vulnerable to disasters. However, in a world of rapid natural and anthropogenic change, this is not the only cause behind amplified risks and impacts. The aim of this study is to identify the pivotal global-scale factors that make a significant contribution to the impact severity of climate disasters.Using an expansive dataset with disaster impact records, complemented with socioeconomic indicators and climate variables from >6000 events in >150 countries, our work is a global-scale investigation of the roles of hazard severity, exposure, and vulnerability influencing the impacts and risk of climate disasters. We use a spatio-temporal stratified approach to define hazard severity, exposure, and vulnerability with relevant variables at the local, regional and global levels. Then, we determine the main factors contributing to impact severity across regions and disaster types using a robust machine learning pipeline.This study illustrates the importance of considering comprehensive aspects of risk in order to build resilient societies to climate extremes. Our research contributes to advancing scientific understanding of the drivers of climate disaster impacts, with the aim of developing more effective policies. It highlights the importance of integrating diverse data sources and advanced analytical methods to better anticipate, prepare for, and respond to the multifaceted challenges posed by climate disasters in a changing climate.
Investigating deconvolution techniques for deep ice core water isotope profile reconstruction
Authors: Shaw Fyntan , Dolman Andrew M. , Laepple Thomas
Published: March 2024

Deconvolution has been frequently applied to measured water isotope records, enabling reconstructions of the timeseries before diffusion. The most commonly used method, Wiener deconvolution, aims to optimise the frequencies that are restored while minimising the amplification of the measurement noise, which dominates the high frequency variability in deep ice cores. We investigate the effectiveness of Wiener deconvolution, along with modified approaches, at recovering the original climate signal, with a focus on deep, old ice. We use both real data and surrogate timeseries and apply our methods to the bottom of the Dome C d18O record, with the aim of retrieving millennial timescale variability.
BODIUM4Farmers: A tool to assess the impact of management measures on soil functions
Authors: Rüschhoff Judith , Weller Ulrich , König Sara , Franke Leonard , Diel Julius , Wollschläger Ute , Vogel Hans-Jörg
Published: March 2024

The BODIUM model (König et al., 2023) is a systemic soil model which aims to simulate the effect of changing agricultural management practices on soil functions such as yield, water storage and filtration, nutrient recycling, carbon storage and habitat for biodiversity. For this purpose, the influence of crop rotation, soil cultivation, fertilisation as well as the effect of a changing climate is taken into account site-specifically.A version of this model, the BODIUM4Farmers, is intended to serve farmers as an on-site decision support tool for long-term planning of soil management measures in response to actual economic and ecological requirements. The model considers site- and farm-specific conditions and requires a number of input variables: a description of the soil profile, weather and management data.In cooperation with farmers and agricultural advisors, we are currently developing an optimised interface that allows farmers to use the tool as efficiently as possible. Co-design workshops with users from agricultural practice have provided important impulses on technical realization such as database connectivity and graphical user interface design. Furthermore, we discussed potential future management options to be implemented for users in the tool and how to present results in an easy-to-understand manner.With this contribution, we introduce BODIUM4Farmers, present the current state of development and encourage discussions and feedback from scientists experienced in science-to-practice transfer.König, S., U. Weller, B. Betancur-Corredor, B. Lang, T. Reitz, M. Wiesmeier, U. Wollschläger, and H.-J. Vogel (2023): BODIUM – a systemic approach to model the dynamics of soil functions. Europ. J. Soil Sci., doi:10.1111/ejss.134
Attributing the streamflow variation by incorporating glacier mass balance and frozen ground into the Budyko framework in alpine rivers
Authors: Yang Linshan , Wen Xiaohu , Yin Zhenliang , Ning Tingting , Han Tuo
Published: March 2024

The remarkable climate change has profound impact on the alpine hydrology, it remains unclear to date on the role of the changes in glacier and frozen ground degradation to the regional streamflow variation. Here, we incorporated the glacier mass balance and frozen ground degradation into the Budyko framework and used the elasticity method to attribute the variation of annual streamflow for 22 rivers in Qilian Mountains (QLM) from 1982 to 2015. The results indicates the simulated annual streamflow that considering glacier mass balance and frozen ground can explain more than 90% of observed streamflow at a significance of p < 0.01, especially for the rivers with high glacier coverage. The elasticity method revealed the simulated streamflow variation can explain more than 91% of variation in respect to the detected streamflow variation. It indicates the robust of the elasticity method and highlights the ability of capture the variation in streamflow with the Budyko framework that incorporated glacier mass balance and frozen ground. There were 3 classifications was clustered and the contribution of precipitation to streamflow variation in the 3 classifications were consistency to the streamflow variation in the 22 rivers of QLM. The precipitation play as a dominant role for the streamflow increased rivers, and ET0 play as a dominant role for the streamflow decreased rivers in QLM. The impact of vegetation on streamflow variation illustrated the strong regional divergence with the contribution varied between -34.55% and 36.79%. The contribution of glacier and frozen ground degradation on streamflow variation were moderate with negative contributions of frozen ground degradation to the streamflow decrease varying between -31.09% and -0.43%, while the contribution of glacier mass balance to variation in streamflow varied between -2.42% and 11.63% in QLM. The results can utilize for understanding the impacts of climate change on alpine hydrological processes and provide the perspective of water resource management.
Impact of cover crops and conventional and reduced tillage on plant productivity in a bicultural maize-oat cropping system
Authors: De Luca Giulia , Sugar Eszter , Fodor Nándor , Árendás Tamás , Bónis Péter , Sándor Renáta
Published: March 2024

Agricultural crop production plays a key role in satisfying the increasing food demand of our ever-growing population. However, continuous production and certain land use practices often result in the depletion of soil quality. This revelation developed a need to improve soil fertility by enhancing carbon sequestration and storage in our cultivated fields using different methods.Even though the application of green manure crops can significantly increase the amount of carbon stored in the soil while improving its water storage capacity and protecting the surface from erosion, it is still not a widespread method in Hungary due to usual water shortage during their sowing and germination periods. Furthermore, different soil management techniques can also alter the quality and carbon sequestration potential of our soils. The objective of our study is to determine how soil management and the usage of catch crop cover may affect crop productivity.A maize-oat bicultural field trial with two different soil management techniques (conventional ploughing and reduced tillage) combined with four types of cover crops (fallow, trefoils-buckwheat mixture, phacelia and oilseed radish) was established in 2020. Changes in soil water content and temperature were continuously monitored at three depths (5, 25 and 45 cm), while leaf area index (LAI) and chlorophyll content (SPAD) were measured periodically. At the end of the vegetation periods measurements regarding crop quality and quantity were executed as well. Furthermore, soil respiration and additional (soil penetration resistance, SWC, VIgreen index) measurements were carried out during the study period, these results will be presented in a separate poster (Effect of cover cropping and soil tillage on soil CO2 emissions).Our results showed that differences between treatments regarding management techniques and cover crops are more characterized in maize than in oat.
Heat wave vulnerability maps of Naples (Italy) from Landsat images and machine learning
Authors: Flocco Daniela , Piegari Ester , Scafetta Nicola
Published: March 2024

Maps of land surface temperature of the area of Naples (Southern Italy) show large spatial variation of temperature anomalies. In particular, the metropolitan area of Naples is generally characterized by higher temperatures than the rest of the area considered.Since heat waves have become more frequent in the last decade, the creation of heat maps helps to understand the location where a town’s population may be more affected by them. Ideally, this kind of maps would provide residents with accurate information about the health problems they may face.Large temperature anomalies variations are caused by multiple or competing factors, leaving uncertainty in identifying vulnerable areas at this time.To overcome this limitation and identify areas more vulnerable to the effects of heat waves, not only in the city of Naples but also in its suburbs, we combine the use of Landsat data with unsupervised machine learning algorithms to provide detailed heat wave vulnerability maps. In particular, we develop a procedure based on a combined use of hierarchical and partitional cluster analyses that allows us to better identify areas characterized by temperature anomalies that are more similar to each other than to any other all over the year. This has important implications allowing discrimination between locations that potentially would be impacted higher or lower energy consumption.
Assessing vegetation dynamics in global high-mountain ecotones
Authors: Zou Linqing , Schaepman-Strub Gabriela , Tian Feng , Liang Tianchen
Published: March 2024

As the climate warms, vegetation within treeline ecotones is responding. The high-mountain ecotones, which are less affected by anthropogenic disturbances, present an optimal environment for investigating the effects of climate change on terrestrial ecosystems. Accurately delineating the trends of vegetation in high-mountain ecotones is pivotal for a comprehensive understanding how climate change affects these ecosystems. Remote sensing technology has a significant potential in detecting and quantifying vegetation variation. While previous studies have identified greening trends within certain mountainous regions, there remain a gap in global-scale analysis concerning vegetation dynamics in high-mountain ecotones.In this study, we utilize long time-series Landsat imagery to monitor and analyze vegetation dynamics in high-mountain ecotones. Our approach includes assessing changes in the physiological properties of the vegetation and analyzing temporal patterns in spatial distribution changes. The results reveal a consistent trend of increased vegetation density and enhanced greening of vegetation in global high-mountain ecotones under the influence of climate change.
Stellar wind impact on early atmospheres around unmagnetized Earth-like planets
Authors: Canet Ada , Gómez de Castro Ana Inés
Published: March 2024

Stellar rotation at early ages plays a crucial role in the survival of primordial atmospheres around Earth-mass exoplanets. Earth-like planets orbiting fast-rotating stars may undergo complete photoevaporation within the first few hundred Myr driven by the enhanced stellar XUV radiation, while planets orbiting low-rotating stars are expected to experience difficulty to lose their primordial envelopes. Besides the action of stellar radiation, stellar winds induce additional erosion on these primordial atmospheres, altering their morphology, extent, and causing supplementary atmospheric losses. In this paper, we study the impact of activity-dependent stellar winds on primordial atmospheres to evaluate the extent at which the action of these winds can be significant in the whole planetary evolution at early evolutionary stages. We performed 3D magnetohydrodynamical (MHD) simulations of the interaction of photoevaporating atmospheres around unmagnetized Earth-mass planets in the time-span between 50 and 500 Myr, analyzing the joint evolution of stellar winds and  atmospheres for both fast- and slow-rotating stars. Our results reveal substantial changes in the evolution of primordial atmospheres when influenced by fast-rotating stars, with a significant reduction in extent at early ages. In contrast, atmospheres embedded in the stellar winds from slow-rotating stars remain largely unaltered. The interaction of the magnetized stellar winds with the ionized upper atmospheres of these planets allows to evaluate the formation and evolution of different MHD structures, such as double-bow shocks and induced magnetospheres. This work will shed light to the first evolutionary stages of Earth-like exoplanets, that are of crucial relevance in terms of planet habitability.
The global influence of ice-ocean interactions in Antarctica
Authors: Silvano Alessandro
Published: March 2024

In this seminar, I will explore the oceanic processes that drive melting of the Antarctic Ice Sheet, and consequent global sea level rise. Different processes lead certain areas of the Antarctic Ice Sheet to be more susceptible to rapid ocean-driven melting, while other areas to be more resilient. I will also show the emergence of a feedback between the ice sheet and Southern Ocean: increased melting leads to warming of the oceanic waters surrounding Antarctica, with consequences for future sea level rise. I will conclude by describing how increased melting of the Antarctic Ice Sheet as well as changes in sea ice affect the global ocean abyss and its ability to store anthropogenic heat and carbon.