bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Synthesis and inversion method for Stokes Parameters in the solar context
Authors: Agudelo Ortiz Juan Esteban , Morales Suarez Germain Nicolás , Vargas Domínguez Santiago , Shelyag Sergiy
Published: March 2024

The arrival of new and more powerful spectropolarimetric instruments such as DKIST, the development of better magnetohydrodinamic (MHD) simulation codes and the creation of newly inversion methods, are coming with the demands of increasing amounts of computational time and power. This, with increasing generation of data, will come with even years of processing that will stop the advance of scientific investigations on mid-late stages. The arrival of Machine Learning models able to replicate patterns in data come with the possibilites of them to adapt to different types of datasets, such as those for classification or for creation of sequences like the seq2seq models, that once trained, they are able to give results according to previous methods that differ on order of magnitude in time processing, being a lot faster. Some work has been done within this field for creating machine learning inversion methods using data obtained from actual inversion codes applied on observational data, and using data from radiative transfer codes for synthesis, reducing both computational demands and time processing. This work attempts to follow onto this steps, using in this case datasets obtained from simulation codes like MURaM and their correspondent Stokes parameters obtained from non-lte radiative transfer codes like NICOLE, training forward (synthesis) and backward (inversion) some neural network models to test whether or not they can learn their physical behaviours and at what accuracy, for being used in the future to process actual data obtained from newly simulation codes and for real solar observations, being another step into the future for creating a new paradigm on how to invert and sunthesize quantities in Physics in general.
A high-resolution 3-D circulation model in a complex archipelago on the coastal Scotian Shelf
Authors: Feng Tao , Stanley Ryan , Wu Yongsheng , Kenchington Ellen
Published: March 2024

A high-resolution coastal Finite-Volume Community Ocean Model (FVCOM) has been configured to simulate the water circulation in the Eastern Shore Islands (ESI) archipelago on the coastal Scotian Shelf. Circulation in this area is characterized by complex interactions between the irregular coastline, a dense archipelago, tides, wind, and subtidal currents.  Model outputs show close agreement with the tides, subtidal current and hydrographic observations. Two circulation regimes within the study area were identified ‘inshore’ and ‘offshore’ of the 60-m isobath. The balance between pressure gradient and Coriolis effect controls the dominant southwestward current (Nova Scotia Current) in the offshore. Rotary spectra and numerical experiments showed that the tidal current was an important component to the circulation in the inshore. Within the study area there are several clockwise and counter-clockwise gyres related to the Coriolis effect, surface wind stress, pressure gradient and the interaction between the irregular topography and current. The combined effects of topography, wind, tide and Nova Scotia Current regulate the inshore circulation. The topographic features complex the cross-shore transport. The increased bathymetric slope and strengthened relative vorticity contribute to the inshore cross-shore current. Here, we found that the joint effect of baroclinicity and bottom relief drives the cross-isobath transport. The ability of our model to resolve complex coastal circulation patterns provides an important basis on which to better understand how physical oceanography influences the unique ecological processes of this coastal archipelago and ultimately will help to evaluate dispersal and connectivity of coastal species in this area.
Land-Atmosphere Interactions in Human-Natural Indian Summer Monsoon System
Authors: Ghosh Subimal
Published: March 2024

The Indian Summer Monsoon Rainfall (ISMR) holds pivotal importance in the predominantly agrarian landscape of India, occurring from June to September. While the influence of large-scale atmospheric circulation on the monsoon has been extensively studied, the role of land surface processes remained largely unexplored until the early 2000s. In order to assess the impact of land surface evapotranspiration on monsoon rainfall in terms of recycled precipitation from June to September, we employed a dynamic recycling model. Our investigation revealed that land evapotranspiration contributes 20-25% of moisture to the late monsoon rainfall in September, specifically in Central and Northeast India. It is important to note that, as the recycling model relied on a reanalysis dataset, it does not account for contributions from land water management practices, such as irrigation.To comprehensively address the human water management component within the human-natural water cycle in South Asia, we implemented a coupled land-atmosphere regional framework using the Weather Research Forecasting – Community Land Model (WRF-CLM). The primary drawbacks of the state-of-the-art irrigation schemes in land surface models, applied to Indian case studies, included the absence of provisions for considering paddy fields, which typically maintain a submerged cropland. Additionally, they did not consider India-specific irrigation practices, driven not by soil moisture measurements or agricultural necessity but by electricity and water availability, often uncontrolled and characterized by randomness. Moreover, existing irrigation datasets developed and used in the literature for South Asian regions considered the wrong crop season, focusing on pre-monsoon summer rather than the monsoon crop season, leading to misleading findings. By incorporating India-specific scenarios, our study demonstrated that alterations in land irrigation practices induce changes in atmospheric circulation, consequently influencing monsoon rainfall patterns, primarily in September. To substantiate these observations, we constructed a causal network among land-atmosphere variables across different river basins in India. Causal discovery methods revealed connections from land to atmosphere within a basin, atmosphere to atmosphere across basins, and atmosphere to land within a basin. This highlights that two neighboring river basins, traditionally assumed to be hydrologically independent when designing water management practices, are, in fact, interconnected through intricate land-atmosphere-land connections. These findings underscore the necessity for a systematic evaluation of India’s proposed large-scale river interlinking project, emphasizing the importance of addressing land-atmospheric feedback to ensure the project's success and sustainability.
Near real-time drillhole data analysis using non-destructive mineral exploration tools
Authors: Zekri Hamid , Cohen David , Rutherford Neil , Thomas Matilda
Published: March 2024

Field-based data acquired from drillholes by pXRF, spectrometer, and wireline loggings can provide prompt, relatively inexpensive and precise information about the geochemistry, mineralogy and petrophysical properties of geological units. When on-site data capture is followed by proper visualisation and statistical analyses, these non-destructive methods can assist in rapid interpretations and decision makings.Identification of distinctive units and critical zones in exploration under cover can be challenging for even experienced geologists when dealing with drilling chips. This study presents a data-driven framework for rapid boundary detection from drillhole cuttings through a combination of geochemical, mineralogical, and geophysical data. The workflow was tested on two drillholes during a drilling campaign conducted by Mineral Exploration Cooperative Research Centre (MinEx CRC) for Geoscience Australia's Exploring for the Future program in the Delamerian orogeny located in far western New South Wales, Australia.A multivariate change point detection technique was applied to the 30 effective attributes retained from various geochemical variables, spectral scalars, and petrophysical parameters obtained through field-based instruments. These include major (e.g., Al, K, Ca, Fe etc.), conserved (Ti and Zr), and trace elements (e.g., Cu, Pb, and Zn), as well as spectral features associated with ferric oxides, kaolinite, micas, smectite, chlorites, and epidote. Natural gamma, electrical conductivity and resistivity, and magnetic susceptibility were also used as petrophysical parameters. Various interfaces between the weathered profile and basement rocks were detected at two scales providing useful insights into the stratigraphy and detailed geochemical logs previously carried out by the field geologists. Using different data types resulted in more reliable boundary detection compared to the limitations of using each data type on its own. This approach was also able to delineate a critical zone in the saprock zone above the fresh basement where elevated concentrations of lead and zinc are accumulated, providing guidance for more detailed sampling and analysis.This framework can be utilised for data-driven stratigraphy/lithology logging, regolith characterisation, identification of the key horizons for further sampling and studies and can facilitate decision-making during exploration drilling campaigns. 
A multi-disciplinary approach to investigate particle dynamics in the South Atlantic Magnetic Anomaly
Authors: Girgis Kirolosse , Hada Tohru , Yoshikawa Akimasa , Matsukiyo Shuichi
Published: March 2024

The South Atlantic Anomaly (SAA) represents the minimum magnetic field intensity on Earth, influencing the energetic particle motion within the radiation belts, drawing them closer to our planet. The anomaly region serves as a key location for understanding the dynamics of the radiation belts affected by the magnetospheric response to solar activity.Our investigation relied mainly on our recent numerical simulation results of the inner radiation belt during two magnetic storm events: May 15, 2005, and February 3-4, 2022. We developed a test particle simulation code to compute the 70-180 MeV proton trajectories in the inner magnetosphere. The IGRF and Tsyganenko models provided the background time-dependent electromagnetic field in response to the input solar conditions. The AP8 model and SAC-C satellite observation confirmed the numerical results. We summarize that protons tend to concentrate more in the SAA’s southern region, while further research found that electrons exhibit a higher tendency to populate the SAA’s northern region due to wave-particle interaction. In light of this conclusion, we identified prolonged Pc5 waves in the ground magnetic field data acquired from stations near the SAA’s northern region provided by MAGDAS/CPMN network.Examining the particle dynamics inside the SAA is crucial for predicting the radiation environment of LEO missions, forecasting the thermosphere’s response to intense space weather, and anticipating the possible long-term climate changes.
The impact of land use change on soil organic carbon pools: A multi-method assessment
Authors: Schiedung Marcus , Barré Pierre , Poeplau Christopher
Published: March 2024

Soil organic carbon (SOC) is significantly affected by land use change (LUC), which can lead to either SOC losses or gains. In consequence, LUC is a major controlling factor of total SOC contents and its dynamics. In general, LUC from forest or grassland to permanent cropland results in losses of SOC, while the reverse can result in long-term gains. Several methods have been developed to assess distinct SOC pools. This includes particle size separation, thermal analysis and soil reflectance spectroscopy. The responses of such defined SOC pools to LUC have rarely been studied comprehensively, while doing so is a straightforward way to reveal their biogeochemical relevance. Here we used 23 sites covering six different LUC (i.e. forest-cropland, grassland-cropland, grassland-forest, cropland-grassland, cropland-forest and cropland-perennial Miscanthus) to assess SOC pool changes. We used particle size fractionation to obtain coarse (>50µm) and fine (
Unraveling Geomorphological Processes and Anthropogenic Activity at the Eastern Border of the Carpathian Basin: Insights from the Bronze Age Tell site Toboliu, Romania
Authors: Zickel Mirijam , Nett Janina J. , Röpke Astrid , Reimann Tony
Published: March 2024

The interdisciplinary project, titled 'Living together or apart? Unravelling the development, internal organization, and social structure of a complex Bronze Age tell settlement at Toboliu, western Romania,' seeks to analyse Bronze Age settlement activity in Toboliu, located in the easternmost Carpathian Basin. Key aspects of the study include associated land-use and landscape evolution, making the reconstruction of the tell's surroundings a focal point. The study area is dominated by loess and significantly influenced by both modern and prehistoric agricultural practices. Thus, it is a major challenge to differentiate between landscape features caused by natural soil-landscape formation processes and human activity especially for the investigated period. Within this context we focussed our research on closed depressions surrounding the tell and investigated two hypotheses regarding their formation: i) closed depressions result from human activities (such as daub extraction pits) and ii) formed through natural soil-geomorphological processes (like loess dolines or periglacial relicts). Based on core drillings, we made use of Optically Stimulated Luminescence (OSL), radiocarbon-supported, and palynological chronostratigraphical analyses. In addition, we took advantage of spatial analysis involving a high-resolution LIDAR elevation model, multispectral WorldView-3 imagery, and magnetographic data to thoroughly testing both hypotheses. Our results suggest that the examined closed depressions exhibit characteristics reminiscent of specific periglacial relict forms, more commonly known from northern European landscapes. Details will be discussed within the presentation.
Development of a high-resolution land data assimilation system with integrated machine learning
Authors: Lu Hui , Tian Jiaxin , Jiang Ruijie
Published: March 2024

Land data assimilation systems, by assimilating land surface remote sensing observations, such as soil moisture (SM) products from SMAP, SMOS, and AMSR2, and combining the advantages of the land surface model, are able to produce spatiotemporally seamless data on the state of the land surface, including soil moisture and temperature in the surface layer and rooting zone, as well as energy fluxes at the surface. However, because of the coarse resolution of prevailing passive microwave soil moisture remote sensing products as well as the lesser accuracy of high-resolution soil moisture products, there is no high-resolution land data assimilation system available.In this study, we developed a high-resolution land data assimilation system by using a machine learning algorithm in combination with a dual-cycle assimilation system. We first used random forests to generate high-resolution soil moisture products from passive microwave soil moisture, and then used the dual-cycle assimilation system to correct the bias of the soil moisture products and assimilated them into the land surface model, and finally produced high-resolution land surface state datasets.  The high-resolution assimilation system was validated on observations from three soil moisture observation networks on the Tibetan Plateau. The results show that the system is capable of producing reliable soil moisture products at different resolutions, such as 5 km, 10 km, etc., with ubRMSE less than 0.06m3/m3.
An integrated, scale-invariant model to forecast global urban growth and transportation network development
Authors: Ahasan Rakibul , Güneralp Burak
Published: March 2024

Urban growth and infrastructure development, especially road network growth, are two interactive, coevolving processes, and to understand long-term urban growth dynamics, it is crucial to model these two processes codependently. Hence, in this study, we present a modeling framework that is capable of capturing the feedback between urban land and road network in forecasting the amount and spatial patterns at large regional scales. While this proposed model with road length as a model parameter forecasts up to 1.2 times new urban areas globally under different scenarios, traditional models with no road length consideration forecasted 1.5–3.7 times more urban areas in 2050. We also forecasted the growth in road network length and pattern considering urban areas as the attraction point. Our model forecasted a substantial amount of new roads to be added to existing global road inventory by 2050– ranging between 1.67 million km and 3.37 million km under five Shared Socio-economic Pathways (SSPs) scenarios. We present Nigeria, Brazil and Bangladesh as case studies where significant new road development is forecasted in currently underdeveloped areas. The overall output from this codependent modeling process will inform the updated connectivity pattern along with an urban growth forecast. This approach enables us to capture the influence of transportation development and the ongoing large-scale transportation infrastructure development projects on urban growth at large, regional- and global- levels for more realistic assessments of the impacts of these projects on the environment.
Analysis of time variations in the Global Electric Circuit parameters from the EGATEC model and Świder atmospheric electricity data
Authors: Odzimek Anna , Tacza José , Pawlak Izabela , Kępski Daniel
Published: March 2024

The ground-level potential gradient (PG) or the atmospheric electric field, the air-Earth current density as well as the main Global Electric Circuit (GEC) parameters such as the ionospheric potential, global resistance and the total current, can be obtained from the EGATEC engineering model of the GEC (Odzimek et al. 2010) at the resolution of 3 hours. The model input data based on satellite cloud and lightning observation datasets from the period 1998-2006 for evaluating the activity of the GEC cloud generators, and the summer/winter and low/high solar activity conductivity model of Tinsley and Zhou (2006) allow calculating the GEC parameters in the summers and winters of the period. In this work we compare the modelling results to observations from the Stanislaw Kalinowski Geophysical Observatory in Świder, Poland (52°07' N, 21°14' E) of the ground-level potential gradient and conduction current density calculated from the newly digitised PG and positive conductivity data from 1965-2005. We also look for connections in the time variations of the model meteorological input and atmospheric electricity observational data. The work is supported by the Polish National Science Centre grant no 2021/41/B/ST10/04448.
Mapping Soil Strength Markers at Field Scale Using Proximal Sensors
Authors: Khatkar Ameesh , Beucher Amélie , Koganti Triven , Munkholm Lars Juhl , Lamandé Mathieu
Published: March 2024

The current agricultural system allows farm machinery to operate randomly, thus compacting around 23-33% of the land with critical levels in Europe. To tackle this issue, the European Union (EU) has launched the mission ‘A Soil Deal for Europe’ under the Horizon Europe program, this mission aims to have healthy soil by 2030. Mitigating soil compaction to improve soil structure has been selected as one of the eight objectives of this mission. It is evident from past research that with the increasing size and weight of farm machinery, soil compaction has become a significant threat to top and sub-soil; however, subsoil compaction is even more persistent and cumulative than topsoil. Therefore, within the SOLGRAS project, we emphasize both surface and sub-surface soil compaction. The ability of soil to withstand the soil compaction is governed by its soil strength. This soil strength depends on many soil properties, such as soil water content, bulk density, texture, and organic matter content. We aim to map these soil properties as a first step before predicting soil strength at the field level. Since proximal sensors provide rapid, low-cost, non-destructive measurements, they have significantly enhanced digital soil mapping. In this project, we have used geophysical sensors based on electromagnetic induction and gamma-ray radiometric principles to predict the above-mentioned soil properties at the field level in Denmark. The geophysical survey and collection of soil samples were performed on the same day for each of the three chosen farmer fields. Here, we present our results of predicted soil properties obtained via the proximal sensors and a limited number of laboratory-measured values. Samples of 100 cc undisturbed soil cores and bags were collected from the surface (15-cm depth) and sub-surface (40-cm depth) at 23 sampling sites for each field. Data from these sampling sites are used to train and validate our models for predicting soil properties associated with soil strength. These predicted high-resolution maps produced at the field level will enable us to set up optimum vehicular specifications and routes before entering the field.
Exploring the deep Earth and planetary interiors by high-pressure experiments
Authors: Hirose Kei
Published: March 2024

While the deep Earth is not directly accessible, it can be explored by laboratory experiments under high-pressure and -temperature (P-T) combined with geophysical observations and geodynamical modeling. We conduct experiments using a laser-heated diamond-anvil cell (DAC) which can generate static high P-T beyond conditions at the center of the Earth. Combining such DAC experiments with in-situ X-ray observations at synchrotron sources and thermal/electrical conductivity measurements and ex-situ textural and chemical characterizations of recovered samples, we have been trying to uncover the structures, chemical compositions, physical properties, dynamics, and evolution of the deep Earth and planetary interiors. The lowermost part of the Earth’s mantle, sometimes called the D” layer, have been the most enigmatic region inside our planet, but the discovery of its main constituent crystals of post-perovskite dramatically improved our understanding of this mysterious layer. Recent hot debates on the core include its thermal conductivity and the mechanism of its convection that have sustained the planetary magnetic field since early history of the Earth. In addition, the Earth’s core is known to include substantial amounts of light elements such as sulfur, silicon, oxygen, carbon, and hydrogen, but its exact chemical composition has been highly controversial since Birch (1952). Hydrogen could be one of the important core light elements when considering that a large amount of water may have been delivered to the growing Earth and hydrogen is strongly siderophile (iron-loving) under high pressure. Nevertheless, the phase diagram and properties of iron hydrides are little known since hydrogen is least soluble into iron at ambient conditions. I will introduce these high-pressure studies on the deep mantle and core materials including our recent work on iron hydrides and discuss the possible ranges of Earth’s core composition.
Gisser-Sánchez revisited: optimal groundwater withdrawal under irrigation including groundwater-surface water interaction and externalities.
Authors: Bierkens Marc , van Beek Rens , Wanders Niko
Published: March 2024

We revisit the classic problem of determining economically optimal groundwater withdrawal rates for irrigation. The novelty compared to previous mathematical analyses is the inclusion of non-linear groundwater-surface water interaction that allows for incorporating the impact of capture, i.e. the fact that all or part of the pumped groundwater comes out of reduced surface water flow or increased recharge. We additionally included the option to internalize environmental externalities (e.g. streamflow depletion) and maximize social welfare rather than farmer’s profit. This analysis results in a fixed optimal groundwater withdrawal rate qopt when withdrawal q remains smaller than some critical withdrawal rate (maximum capture) qcrit and provides depletion trajectories, either under competition or optimal control, if q is larger than qcrit. Based on the relative value of q, qcrit and qopt it also yields four quadrants of distinct withdrawal strategies. Using global hydrogeological and hydroeconomic datasets we map the global occurrence of these four quadrants and provide global estimates of optimal groundwater withdrawal rates and depletion trajectories. For the quadrants with groundwater depletion (q >qcrit) we derive and compare depletion trajectories under competition, optimal control and optimal control including environmental externalities, and assessed globally where the differences between these depletion modes are small, which is known as the Gisser-Sánchez effect. We find that the Gisser-Sánchez effect is globally ubiquitous, but only if environmental externalities are ignored. The inclusion of environmental externalities in optimal control withdrawal result in notably reduced groundwater decline and larger values of social welfare in many of the major depletion areas.
Assessing the impact of stratospheric aerosol injection on warm spell characteristics
Authors: Glade Ivy , Hurrell James
Published: March 2024

The urgency to limit continued global mean temperature rise has prompted the emergence of methods of solar climate intervention (SCI) to cool the planet. Stratospheric aerosol injection (SAI) is a method of SCI that would cool the planet by injecting aerosols into the stratosphere to reflect a small amount of incoming solar radiation away from Earth. There is not yet a complete understanding of how the impacts and risks of SAI on human and natural systems compare to those of climate change alone. While there has been some work that has examined the potential impact of SAI on extreme weather events, none has thoroughly examined the potential impact of SAI on warm spells, defined as prolonged periods of anomalously warm temperature that may occur at any time of the year. Warm spells have detrimental impacts that are projected to worsen with continued climate warming including risks to human health, agriculture and ecosystems. Here, the impact of SAI on the frequency, magnitude, intensity, and duration of warm spells is investigated globally using the ARISE-SAI simulations. Specifically, future projections of warm spells under ARISE-SAI are compared to those under climate change alone following the moderate SSP2-4.5 emissions scenario.  The ARISE-SAI simulations indicate that increases in the frequency, magnitude, intensity and duration of warm spells could be limited if SAI were to be deployed, although there is significant regional variability. 
Air quality improvements can strengthen China's food security
Authors: Liu Xiang , Chu Bowen , Tang Rong , Liu Yifan , Li Xing , Xiao Jingfeng , Desai Ankur , Wang Haikun
Published: March 2024

China, with nearly 20% of the world's population, achieves self-sufficiency in major grain production using only about 10% of the global arable land. To further ensure food security in China, it is crucial to gain a deep understanding of the driving factors behind grain production. Climate change, water scarcity, and air pollution pose serious threats to food production. Air quality in China is among the poorest in the world, thus quantifying its impact on grain production not only holds significance for maintaining its food security but also provides valuable insights into future air quality management policies. Here, we conducted a comprehensive analysis of the impact of aerosols and ozone on crop growth by integrating long-term, high spatial-temporal resolution remote sensing SIF data, crop planting information, and nationwide air pollution concentration data using nonlinear functional relationships and a two-way fixed-effects statistical model. The results show a consistent negative impact of ozone pollution on crop growth, while the effect of aerosols is varied by crop type and geographic location. By establishing a quantitative response relationship between crop growth and pollutant concentrations, we found that when China reaches the standard of 35 µg m-3 PM2.5, the average yields of corn, rice, and wheat nationwide will change by 0.45 ± 0.8%, 0.70 ± 0.22%, and −5.28 ± 2.97%, respectively. At the same time, reaching a warm-season ozone concentration of 60 µg m-3 in China will result in average national yield increases of 7.40 ± 1.32%, 3.40 ± 0.56%, and 8.71 ± 1.85% for corn, rice, and wheat, respectively. If China simultaneously meets both air pollution standards, the average daily per capita calorie intake of the three major crops will increase by 4.51%. Finally, our study suggests that, compared to reducing PM2.5, reducing ozone can more effectively increase domestic grain supply and further maintain China’s food security.
Quantifying microplastic residence times in lakes using mesocosm experiments and 1D random walk model
Authors: Elagami Hassan , Frei Sven , Boos Jan-Pascal , Trommer Gabriele , Gilfedder Benjamin S.
Published: March 2024

Microplastic residence time in lakes is governed by complex and interrelated processes. In this work, we have used a series of in-lake mesocosm experiments combined with random walk modeling to understand microplastic residence times in the lake water column. Three size ranges of green fluorescent microplastic (1-5, 28-48, and 53-63 µm) were added to a 12m deep mesocosm and detected using fluorescence detectors. Experiments were conducted over one year capturing thermal stratification in summer as well as lake turnover in autumn. The measured residence times in summer ranged between ~1 and 24 days and depended mainly on particle size. The modeled residence time for the smallest particles (>200d) was considerably longer than the measured residence times in the mesocosm (~24d). This could be due to interactions between the small microplastic particles and existing particles in the lake. In contrast, during lake turnover large Rayleigh numbers showed that instabilities in the water column likely led to turbulent convective mixing and rapid sinking within the mesocosm.
Revealing a systematic bias in percentile-based temperature extremes
Authors: Brunner Lukas , Voigt Aiko
Published: March 2024

Worsening temperature extremes are among the most severe impacts of human-induced climate change. To quantify such extremes and their changes various methods have been applied over the years. One frequently used approach is to define extremes relative to the local temperature distribution as exceedances of a given percentile threshold. For hot extremes, the Expert Team on Climate Change Detection and Indices (ETCCDI) defines TX90p relative to the 90th percentile of maximum temperature on each calendar day in the 30-year period 1961-1990. To increase the number of samples available for the percentile calculation a 5-day running window is recommended leading to a total of 30x5=150 samples for each calendar day. However, this still limited number of samples can lead to internal variability being mixed into the percentile and cause a strongly varying extreme threshold, which is undesirable. Therefore, many studies do not follow the ETCCDI recommendation and use longer seasonal windows of 15- or even 31-days to increase the number of samples available for the percentile calculation. We show that the use of such long seasonal windows introduces a systematic bias that leads to a striking underestimation of the expected extreme frequency. This expected exceedance frequency is 10% for the 90th percentile when evaluating the extreme frequency in the same period as the threshold is calculated (in-base). For ERA5 the 1961-1990 average, global average temperature extreme frequency is only 9% – a relative bias of -10%. In individual regions and seasons, the bias can be considerably larger, exceeding -75%. We develop a simple bias correction and use it to show that the bias generally decreases in a warming climate in CMIP6. It, therefore, also affects estimates of future temperature and related heatwave changes. The decrease of the bias can lead to an overestimation of changes in the heatwave frequency by as much as 30%. Based on these results, we strongly warn against the use of long seasonal windows without correction when calculating extreme frequencies and their changes.
Years in-situ mass balance study of Pensilungpa Glacier from 2016 to 2022 in Suru River Valley, Ladakh Himalaya, India. 
Authors: Kunmar Pankaj , Mehta Manish , Kumar Vinit , Rana Ajay , Nainwal HC
Published: March 2024

Recent studies of Himalayan glacier recession indicate that there is wide variability in terminus retreat rate and mass balance in the different sectors of the mountain range, primarily linked to the topography and climate of the region. Variable retreat rates of glacier termini and inadequate supporting field data (e.g. mass balance, ice thickness, velocity, etc.) in the Himalayan glaciers make it difficult to develop a coherent picture of climate change impacts. The mass balance measurements of the Pensilungpa Glacier were conducted from 2016-2017 to 2021-2022 and the study was carried out by using the glaciological method, including fixed date measurement of net accumulation. The glaciological method includes measurements at stakes and in snow pits, which are interpolated to glacier-wide balance estimates. This six-year mass balance study shows a negative trend with an average rate of specific balance is -0.46 m water equivalent (w.e.) and annual mean mass balance was -4.1 x106 m3 w.e. The Glacier lost ~45 ±18 m lengths with an average rate of 6.4 ±3 ma-1, and 24.97 x106 m3 w.e. cumulative volume loss. Also, results show that Pensilungpa Glacier declined the ELAs 20 m from the year 2016.
Revisiting the iceberg thickness distribution in Southern Ocean simulations.
Authors: Olivé Abelló Anna , Mathiot Pierre , Jourdain Nicolas , Kostov Yavor , Holland Paul
Published: March 2024

The acceleration of glaciers in the Antarctic ice sheet amplifies the flow of icebergs into the Southern Ocean. The presence of these icebergs has a significant impact on the penetration of warm water toward ice shelves and can also induce the formation of large polynyas when grounded, thereby promoting dense water formation. The existing implementation of the Lagrangian iceberg module in NEMO does not consider the Antarctic ice-shelf thicknesses from which the icebergs are originated, so the model cannot represent whether icebergs are thin enough to cross the shallow bathymetric ridges. In the present model, the iceberg masses, thicknesses, and size distribution are prescribed a priori as input parameters irrespective of the source ice-shelf characteristics. In addition, the categorization of iceberg classes and the scaling of smaller icebergs are not optimized, which is a strong limitation for climate modelling. Hence, the main aim of this study is to improve the thickness distribution of the calved icebergs based on ice shelf characteristics, decrease the computational cost of the model, and assess how these improvements alter the lifespan of the icebergs and their freshwater flux distribution across Antarctica.The new approach has been implemented in a 0.25° Southern Ocean configuration of the NEMO ocean–sea-ice model. We used a power-law probability distribution function of iceberg occurrence as a function of iceberg area and a tabular iceberg definition to establish the thickness distribution for the small iceberg categories, imposing that each class exhibits the same total mass. In order to reduce computational costs, we constrained the frequency of icebergs released per class so that the smaller classes of multiple icebergs are gathered into one particle. Our preliminary results show that the iceberg thickness distribution, implemented as a function of areas, is supported by in-situ observations measured from high-resolution SAR-1 satellite images. The released icebergs display a typical thickness per class depending on the ice shelf's source, with a broader distribution when more calving classes are established. Ultimately, the findings reveal that accounting for realistic Antarctic ice-shelf thicknesses leads to thicker icebergs, particularly in larger classes, consequently increasing the mass that each transports westward around Antarctica. Future iceberg simulations, carried out for 25 years, will assess the iceberg's sensitivity to the maximum iceberg area, the number of different sizes and the area bounds used to define each size, among others. It is also expected that these simulations will also unveil high-melting regions and high iceberg densities in regions where icebergs ground, and will determine if fragmentation processes are needed to achieve realistic iceberg lifespans.
Modeling hydrosedimentary transport in the eastern English Channel under extreme weather conditions
Authors: Alekseenko Elena , Sentchev Alexei
Published: March 2024

The eastern English Channel (EEC) experiences a dynamic interplay of extreme events, including powerful winds, tides, and complex bottom relief features, collectively shaping the region's hydrosedimentary transport dynamics. Extreme winds, frequently observed in the EEC, play a pivotal role in influencing surface currents and wave patterns. Coupled with strong tidal forcing, these events lead to intricate interactions with the seafloor topography, creating a complex hydrodynamic environment. The resulting effects on sediment transport are significant, with the potential for altered erosion and deposition patterns along the coastal areas of the EEC. Understanding this multiscale interaction is crucial for predicting and managing the impact of extreme events on hydrosedimentary transport, contributing to effective management of coastal ocean environment. In order to study all these processes, we used a 3D hydrodynamic model (MARS3D, IFREMER) coupled with a sediment transport model (MUSTANG, IFREMER) and calibrated it for the English Channel. This model employs nested grids of different extents and resolutions: (i) the northwest European continental shelf area with a 5 km resolution, (ii) the English Channel area with a 1 km resolution, and (iii) local zones along the eastern coast of the English Channel with a 100m resolution. The larger model transfers boundary conditions to the higher-resolution model. Such a cascade of resolutions allows for the consideration of both large-scale hydrodynamic processes and the replication of smaller-scale processes (eddies, turbulent current oscillations). Four fractions of suspended matter, including two size classes of mud and two size classes of fine sand, were specifically chosen for modeling based on in-situ data. The model then has been validated using the data collected in 2020-2021. The model can be employed to replicate the dynamics and sedimentary processes over a multi-year period. This enabled the estimation of the quantity and flux of suspended matter, as well as potential changes in the sediment transport regime induced by extreme weather conditions. The modeling outcomes highlighted tides as the primary driving force behind hydrosedimentary transport, surpassing the influence of wind. This effect is evident in the formation of eddies near capes, emerging for a few hours after the onset of the tide phase. These eddies create a counterflow of matter along the French coasts, opposing the general current direction that moves toward the North Sea. In the regions characterized by the highest velocities in offshore areas, larger particles (sands) prevail within the eddies, while the slower sections closer to the coast are predominantly composed of finer mud particles. Additionally, the wind introduces instabilities in the current structure, leading to an increased resuspension of fine sediments.
Seasonality of Feedback Mechanisms Involved in Pacific Coastal Niño Events
Authors: Rudloff Daniel , Wahl Sebastian , Lübbecke Joke
Published: March 2024

The 2017 Pacific Coastal Niño Event was the strongest of its type. It caused torrential rainfall and devastating flooding in Peru and Ecuador and thus rapidly caught the attention of the scientific community. Multiple studies have been conducted focusing on the causes and consequences of this event. While the strong connection between SST anomalies and local rainfall, especially during boreal spring, is well established, the causes of the extreme warming are still a subject of discussion. In this study, we focus on the seasonality of the effectiveness of mechanisms and feedbacks involved in coastal Niño Events, utilising reanalysis products and historical model simulations from the Flexible Ocean and Climate Infrastructure (FOCI).The 2017 event stands out due to its strength and timing as it occurred earlier in the year than most other events. We find that the atmospheric conditions during this time of year are very different due to the presence of atmospheric convection which modulates the SST-cloud feedback. Further, the event coincided with the season of strongest wind-driven upwelling. This combination enables a different forcing of a short but strong event. Additional model sensitivity experiments are performed for a better understanding of underlying mechanisms. We show how the same local wind stress forcing acts differently in different seasons, with its strongest impact during the months of strongest entrainment. Events forced by local heat fluxes and wind stress forcing only do not show any subsurface warming, which is found to be the main reason for their rapid decay. Even though the atmospheric response to a coastal warming varies seasonally, without any subsurface forcing, e.g., the events cannot be sustained through atmospheric feedbacks.
Why do oceanic nonlinearities play a weak role in Extreme El Niño events?
Authors: Liu Fangyu , Vialard Jérôme , V. Fedorov Alexey , Éthé Christian , Person Renaud , Lengaigne Matthieu
Published: March 2024

Extreme El Niño events exhibit outsized impacts worldwide and considerably enhance the El Niño Southern Oscillation (ENSO) warm/cold phase asymmetries. While many mechanisms were proposed, no consensus has been reached and the relative role of atmospheric and oceanic processes remains to be illustrated. Here we quantitatively assess the contribution of oceanic nonlinearities through a state-of-the-art oceanic general circulation model, which realistically simulates extreme El Niño related characteristics and the oceanic nonlinear processes responsible for ENSO skewness. An effective way is developed to isolate sea surface temperature (SST) nonlinear response based on paired experiments forced with opposite wind stress anomalies. We demonstrate that the overall oceanic nonlinearities play a marginal role on extreme El Niño amplitude, which largely arises from the compensation between positive contributors from tropical instability waves (TIWs) and nonlinear dynamic heating (NDH) and negative contributors from subsurface processes and air-sea fluxes. The physical processes keep robust when using the other mixing scheme or mixed layer option for the heat budget. Our findings quantitively reveal the subtle contribution of oceanic nonlinearities, yielding strong evidence for the paramount role of atmospheric nonlinearities in shaping extreme El Niño events.
Is the NAO signal-to-noise paradox exacerbated by severe winter windstorms?
Authors: Degenhardt Lisa , Leckebusch Gregor C. , Scaife Adam A. , Smith Doug , Hardiman Steve
Published: March 2024

The signal-to-noise paradox is known to be a limitation in multiple seasonal and decadal forecast models where the model ensemble mean predicts observations better than individual ensemble members. This ‘paradox’ occurs for different parameters, like the NAO, temperature, wind speed or storm counts in multiple seasonal and decadal forecasts. However, investigations have not yet found the origin of the paradox. First hypotheses are that weak ocean – atmosphere coupling or a misrepresentation of eddy feedback in these models is responsible.Our previous study found a stronger signal-to-noise error in windstorm frequency than for the NAO despite highly significant forecast skill. In combination with the underestimation of eddy feedback in multiple models, this led to the question: Might the signal-to-noise paradox over the North-Atlantic be driven by severe winter windstorms?To assess this hypothesis, the signal-to-noise paradox is investigated in multiple seasonal forecast suites from the UK Met Office, ECMWF, DWD and CMCC. The NAO is used to investigate the changes in the paradox depending on the storminess of the season. The results show a significant increase of the NAO-signal-to-noise error in stormy seasons in GloSea5. Other individual models like the seasonal model of the DWD or CMCC do not show such a strong difference. A multi-model approach, on the other hand, shows the same tendency as GloSea5. Nevertheless, these model differences mean that more hindcasts are needed to conclusively demonstrate that the signal-to-noise error arises from Atlantic windstorms.
Buttertubs spilled during the July 2021 flood as plastic transport tracers in the Dutch Meuse river
Authors: Hauk Rahel , van der Ploeg Martine , Teuling Adriaan J , de Winter Winnie , van Emmerik Tim HM
Published: March 2024

Rivers play a substantial role in plastic pollution transport and storage but the transport processes that determine macroplastic fate in the riverine environment are not fully understood yet. Usually it is unknown when and where specific plastic litter items entered the environment, therefore macroplastic transport is often studied via e.g. GPS trackers. However, the July 2021 flood provided an unique opportunity of spilled macroplastic items, with clearly known time and space of emission.In July 2021 severe floods affected multiple European river catchments, including the Meuse catchment in Belgium. A dairy company located at the Meuse tributary Vesdre was flooded, with parts of their facilities and a lot of material washed away. Among the washed away material was also ~8 million empty dairy packages ("buttertubs"), which have a printed ID code that can be traced to their emission point. During macroplastic sampling immediately after the flood event, and in the following two years, we found 617 of these buttertubs along the Dutch section of the Meuse river (~66 - 328 km downstream of the dairy company). We used the buttertubs as tracers for macroplastic transport in the period that includes the flood event, and the following two years. Within 20 days of the flood event, some of the buttertubs were transported ~328 km and were found close to the Rhine-Meuse-Delta. However, the majority of buttertubs was transported less than 100 km within these 20 days, with an average transport distance between 9.75 - 18.25 km/day. Over the following two years the average transport distance decreased to 0.23 km/day. Which could imply that the buttertubs either were only transported across smaller distances in the following two years, or even not remobilized at all after being deposited during the flood event. Some of the buttertubs we also collected, and we investigated their mass and fragmentation development over time. In this unique opportunistic study, we found that the buttertubs mean transport distance moved downstream over the course of two years. The majority of them however, was deposited rather close to their emission point, even given the extreme flood situation. 