bluuebunny/crossref_metadata_2025 huggingface dataset:
Modelling the mountain boundary layer: Does higher resolution improve model performance?
Authors: Goger Brigitta , Dipankar Anurag
Published: March 2024

The horizontal grid spacing of numerical weather prediction models keeps decreasing towards the hectometric range, where topography, land-use, and other static parameters are well-resolved. Still, models have to be evaluated over complex terrain, because it cannot be assumed that higher horizontal resolution automatically yields better model performance. In this study, we perform limited-area simulations with the ICON model across horizontal grid spacings (1 km, 500 m, 250 m, 125 m) in the Inn Valley, Austria. Simulations are ran with two turbulence schemes - a 1D parameterization and a 3D Smagorinsky-type scheme. We evaluate the model across scales with observations of the valley boundary layer from the CROSSINN measurement campaign. This allows us to investigate whether increasing the horizontal resolution automatically improves the representation of the thermally-induced circulation, surface exchange, and other mountain boundary layer processes. Results suggest that the valley topography is already well-represented at the kilometric range, but the simuations in the hectometric range show a more detailed representation of the vertical valley atmosphere structure and the up-valley flow. Across resolutions, the model struggles with the correct representation of interactions between larger and smaller scales. The two turbulence schemes show a similar performance, but the 3D Smagorinsky scheme simulates a delayed evening transition of the up-valley flow. It is argued that the major difference between schemes actually emerges from the different surface transfer schemes, and the choice of boundary layer parameterization is secondary.
Evolving Chemistry of Lithospheric Mantle Based on Oxygen Isotope and Trace Element Analyses of Olivines from Mantle Xenoliths across Earth’s History
Authors: Bindeman Ilya , Batanova Valentina , Sobolev Alexander , Ionov Dmitri , Danyushevsky Leonid
Published: March 2024

Oxygen is the most abundant element in the terrestrial mantle and crust. We have recently reported on a 0.2‰ δ18O decrease of continental mantle peridotites from the original primary Bulk Silicate Earth-Moon value of 5.57‰ [1] in the mid-Archean to the Phanerozoic explained by the initiation of surface recycling (linked to intensity and style of plate tectonics) sometime in the Archean. Even small variations in the volatile mass balance are critical in explaining phenomena such as the Great Oxidation Event at ~2.4 Ga that may have mantle origin. As low-δ18O subduction fluids are derived by the dehydration (and potentially oxidation) of low-δ18O interiors of subducted slabs, this work further explores this process to observe temporal changes related to the progressive input of volatile elements and potential lithospheric mantle oxidation. This study presents a record of trace elements measured in same olivines (Li, Na, Al, P, Ca, Sc, Ti, V, Cr, Mn, Co, Ni, Cu, Ga, Y, Zr) including oxidation-sensitive elemental ratios V/Sc and Zn/Fe for this collection. Prior melt-depletion of mantle peridotites, estimated using bulk Al2O3 content of the xenoliths, increases with age from ~25 to 35%, leading to depletion of Yb, Y, Co, Mn, Ca, P, with smaller effects on the elemental ratios.  We observe significant ranges of V/Sc (0.2-14), Li/Y and other ratios, not related to prior melt depletion that may be linked to subduction-related re-distribution of incompatible elements by subduction [2], and scattered correlation with age and δ18O values. Further trends will be analyzed during the talk after considering craton-specific domains and global trends. This work can potentially contribute to constraining a global mass balance of crustal growth and recycling based on co-variations of isotopes of a major element oxygen and trace elements in the predominant lithospheric reservoir of subcontinental mantle.[1]Bindeman ea, (2022) Nat Comm 13, 3779; [2] Doucet ea, (2020) NatGeosci 13, 511.
Comparison of SWAT and a deep learning model in nitrate load simulation at the Tuckahoe creek watershed in the United States
Authors: Lee Jiye , Kim Dongho , Hong Seokmin , Yun Daeun , Kwon Dohyuck , Hill Robert , Pachepsky Yakov , Gao Feng , Zhang Xuesong , Lee Sangchul , Cho KyungHwa
Published: March 2024

Simulating nitrate fate and transport in freshwater is an essential part in water quality management. Numerical and data-driven models have been used for it. The numerical model SWAT simulates daily nitrate loads using simulated flow rate. Data-driven models are more flexible compared to SWAT as they can simulate nitrate load and flow rate independently. The objective of this work was evaluating the performance of SWAT and a deep learning model in terms of nutrient loads in cases when deep learning model is used in (a) simulating flow rate and nitrate concentration independently and (b) simulating both flow rate and nitrate concentration. The deep learning model was built using long-short-term-memory and three-dimensional convolutional networks. The input data, weather data and image data including leaf area index and land use, were acquired at the Tuckahoe Creek watershed in Maryland, United States. The SWAT model was calibrated with data over the training period (2014-2017) and validated with data over the testing period (2019) to simulate flow rate and nitrate load. The Nash-Sutcliffe efficiency was 0.31 and 0.40 for flow rate and -0.26 and -0.18 for the nitrate load over training and testing periods, respectively. Three data-driven modeling scenarios were generated for nitrate load. Scenario 1 included the flow rate observation and nitrate concentration simulation, scenario 2 included the flow rate simulation and nitrate concentration observation, and scenario 3 included the flow rate and nitrate concentration simulations. The deep learning model outperformed SWAT in all three scenarios with NSE from 0.49 to 0.58 over the training period and from 0.28 to 0.80 over the testing period. Scenario 1 showed the best results for nitrate load. The performance difference between SWAT and the deep learning model was most noticeable in fall and winter seasons. The deep learning modeling can be an efficient alternative to numerical watershed-scale models when the regular high frequency data collection is provided.
Telecommunication – a blind spot in disaster resilience science, yet essential for disaster mitigation and recovery
Authors: Witvliet Ben
Published: March 2024

During Hurricane Katrine in New Orleans in 2005, the failure of telecommunication systems was a disaster by itself, creating chaos and seriously hampering mitigation measures during and directly after the event. Half of the telecom towers was destroyed by the heavy wind, the electrical grid was destroyed and an area as large as The Netherlands and Belgium combined was flooded. The rest of the telecom towers ceased operation 48 hours later, when their backup power was depleted. In some parts of New Orleans the water stood 4.5 meters high, and debris was making roads impassable, blocking emergency repairs. This created a disaster in a disaster, leaving local authorities and first responders without intercommunication and status updates, rendering well-informed and coordinated actions impossible.Similarly, during Hurricane Irma in 2017, on the island of St. Maarten, 50% of the telecom towers were blown over, seriously hampering communications in large sections of the island. Fortunately, the sea cables connecting the island to the rest of the world remained unharmed, although even that was a close shave. Therefore, while the mobile phone network failed in large areas, the Emergency Support Functions of the government could still communicate with the outside world via the internet, to ask for support and specific equipment for emergency repairs (such as new telecom towers).Similarly, after the Nepal earthquake in 2015, roads were rendered impassable by debris and all telecommunication networks were silenced, and the electrical grid destroyed. The first messages to the outside world were conveyed by radio amateurs, via ionospheric radio. Several inland villages remained isolated for several days, with no means to issue a call for assistance or medical help.Despite these and other examples, most of the models and impact chains drawn by scientist to investigate disaster events ignore the role of telecommunication failure that aggravates the situation in the field. Also, scientific tools to predict risks and support decisions when the disaster unfolds and directly after it, are often provided via internet links, ignoring the likelihood of them being inaccessible when they are needed most, due to a telecom blackout.It is therefore of the utmost importance to draw more attention of researcher to the role of telecommunications in impact chains, even when that is not their direct competence, and to interact with telecommunication experts and emergency organizations in the field to better prepare for telecommunication failure during and after disasters. A good example of such an initiative was shown in PARATUS, a scientific project on societal resilience, where information gathering on St. Maarten specifically included telecommunication during disasters. Crossing these boundaries between sectors will greatly amplify the practical impact of the scientific work.
Detecting spatio-temporal dynamics of western European heatwaves using deep learning
Authors: Happe Tamara , Wijnands Jasper , Fernández-Torres Miguel Ángel , Scussolini Paolo , Muntjewerf Laura , Coumou Dim
Published: March 2024

Heatwaves over western Europe are increasing faster than elsewhere, which recent studies have attributed at least partly to changes in atmospheric dynamics. To increase our understanding of the dynamical drivers of western European heatwaves, we developed a heatwave classification method taking into account the spatio-temporal atmospheric dynamics. Our deep learning approach consists of several steps: 1) heatwave detection using the Generalized Density-based Spatial Clustering of Applications with Noise (GDBSCAN) algorithm; 2) dimensionality reduction of the spatio-temporal heatwave samples using a 3D Variational Autoencoder (VAE); and 3) a clustering of heatwaves using K-means, a Gaussian Mixture Model, and opt-SNE. We show that a VAE can extract meaningful features from high-dimensional climate data. Furthermore, we find four physically distinct clusters of heatwaves that are interpretable with known circulation patterns, i.e. UK High, Scandinavian High, Atlantic High, and Atlantic Low. Our results indicate that the heatwave phase space, as found with opt-SNE, is continuous with soft boundaries between these circulation regimes, indicating that heatwaves are best categorized in a probabilistic way.
Mapping the hydrology of Greenland’s crevasses with deep learning 
Authors: Chudley Thomas , Winterbottom Thomas , Stokes Chris , Lea James
Published: March 2024

Greenland’s crevasse fields transfer nearly half of the seasonal runoff to the bed of the ice sheet, with implications for ice rheology, subglacial hydrology, and subsequent feedbacks in ice dynamics. The hydrological behaviour of crevasses has been shown to be complex and spatially heterogenous, but the drainage mechanics are poorly understood, particularly in comparison to other water pathways (lake drainage, moulins, and finer-scale fractures). To better understand crevasse drainage processes at scale, we develop a convolutional neural network (CNN) to map water-filled crevasses from 10 metre resolution Sentinel-2 MSI imagery. Training and validation datasets are produced using NDWI-based approaches that are accurate but require time-consuming and scene-specific manual tuning. In contrast, our scaleable CNN approach allows for the seasonal and multiannual evolution of ponded crevasse fields to be efficiently monitored. After constructing a comprehensive, time-evolving dataset of crevasse field hydrology, we aim to quantify controls (strain rate, melt rate, etc.) on the time-evolving filling and drainage of crevasses. Our ultimate objective is to use these derived relationships to improve the parameterisation of spatially heterogenous crevasse hydrological behaviour into coupled models of Greenland Ice Sheet hydrology-dynamics. 
Exploring the World of Multi-Hazard Susceptibility Mapping With Deep Learning
Authors: Tiggeloven Timothy , Ferrario Davide , Jäger Wiebke , Claassen Judith , Shapovalova Yuliya , Koyama Maki , de Ruiter Marleen , Daniell James , Torresan Silvia , Ward Philip
Published: March 2024

A crucial component of disaster preparedness is the development of a multi-hazard susceptibility map, which plays a vital role in comprehensive risk assessment, resource allocation, land use planning, emergency management, community preparedness, and decision-making. Recently deep learning methods have been showing potential to map susceptibility at a finer resolution. While prior research has predominantly focused on advanced single-hazard or simplified multi-hazard susceptibility mapping, an approach to explore multi-hazard susceptibility mapping using deep learning methods and explainable AI’s remains lacking to date. Addressing this gap, our research employs an ensemble Convolutional Neural Networks, to develop a multi-hazard susceptibility map. Leveraging diverse datasets and the MYRIAD-HESA framework, our analysis considers a range of hazards and their interactions, offering a more integrated view of the complex risk landscape faced by communities. Using Japan as a case study, the resulting susceptibility map serves as a valuable tool for informing land use and urban planning, resilient infrastructure development, and identification of suitable locations for critical facilities. Furthermore, it supports emergency management by facilitating resource prioritization, coordination, evacuation planning, and community awareness. This research contributes to evidence-based decision-making, policy development, and global disaster preparedness efforts.
Thermosphere-ionosphere effects due to forcing from “above” and “below” as captured by TIEGCM-ICON
Authors: Maute Astrid , Forbes Jeffrey , Cullens Chihoko , Harding Brian , Immel Thomas
Published: March 2024

The lower to upper atmosphere vertical coupling via atmospheric solar tides is very variable and affects the dynamics, composition and electrodynamics of thermosphere-ionosphere (TI) system. In addition, complex solar wind forcing is always impacting the high latitude region and its effects can extend to the mid- and low latitude region.  The Ionospheric Connection (ICON) explorer mission provides almost 3 years of data and an opportunity to examine the variation in the TI due to lower atmospheric and MI forcing. This is facilitated by the ICON Level4 product, the thermosphere-ionosphere-electrodynamics general circulation model (TIEGCM) driven by tides fitted to ICON observations via the Hough Mode Extension (HME) method. The effects of the upward propagating tides can be isolated by examining the difference between two TIEGCM simulations with and without tidal HME forcing at the model’s lower boundary, while the effects of solar and magnetospheric variability can be estimated by the difference to a simulation with constant solar and geomagnetic forcing.In this presentation we use over 2 years of TIEGCM simulations to evaluate the model by comparing primarily to ICON observations and examine the captured TI variations. A special focus in our comparison will be on the neutral wind and its two-way coupling to ion drift and plasma distribution. For specific time period we will delineate the contributions due to lower atmospheric tidal forcing from the one due to solar and magnetospheric forcing and quantify the separate effects on the neutral wind, ion drift, and plasma variation.
Assessing adaptation strategies for potato cultivation in Morocco: modeling approaches at the field scale
Authors: Lozzi Assia , Ouedraogo Amandine , Darrhal Nassima , Dhassi Khalid , Drissi Saad
Published: March 2024

Climate change is set to reshape the environmental parameters governing crop growth, necessitating the implementation of revised management practices at the field scale. This study focuses on the adaptation and evaluation of the APSIM model for simulating the phenological growth, development, and yield prediction of potato (Solanum tuberosum L.) in response to climate variability in Morocco. Recognizing the critical role of potatoes in global food systems, and the increasing pressures of climate change, the research aims to accurately forecast the growth and yield responses of potato crops to these environmental shifts. The calibration phase of the APSIM model was rigorously conducted using local datasets, including climate patterns, soil properties, plant phenological data, and cropping practices. The model's accuracy was demonstrated through its high determination coefficients in simulating key growth stages and biomass accumulation of the potato crop. The findings showcase the model's capability in predicting potato yield and phenological responses to climate variability, providing strategic insights for enhancing agricultural practice efficiency. Overall, this study underlines the APSIM model's efficacy in developing strategies for climate-resilient potato farming, offering a robust tool for adapting agricultural practices under changing environmental conditions.
Sensitivity of Long-Wavelength Dynamic Topography and Free-Air Gravity to Lateral Variations in Lower Mantle Viscosity
Authors: Conrad Clinton P. , Ramirez Florence
Published: March 2024

Deflection of the Earth’s surface supported by mantle flow, known as dynamic topography, is associated with a free-air gravity anomaly because such topography is not isostatically compensated. Consequently, the ratio of the gravity anomaly to the dynamic topography, known as the admittance, has been used to estimate the amplitude of dynamic topography, which can be difficult to measure directly. However, at long wavelengths (e.g., spherical harmonic degrees 2 to 6) both dynamic topography and gravity anomalies, and thus the admittance, are sensitive to the mantle’s viscosity structure. Previous studies [e.g., Colli et al., 2016] demonstrate a reversal in sign of the free-air gravity anomaly resulting from lower mantle structures as the viscosity of the lower mantle is increased. This indicates potential complexity for inferring long-wavelength dynamic topography from observations of gravity anomalies, because the upper-lower mantle viscosity contrast is poorly constrained. We further investigated the relationship between dynamic topography and gravity anomalies by introducing lateral viscosity variations into a finite element model of global mantle flow. We find that the gravity anomaly above lower mantle density heterogeneity can change dramatically as we begin to introduce different models for lateral viscosity variations into the upper and lower mantle viscosity fields. In such models we find that the sign of the admittance varies laterally, with the horizontal gradients in mantle viscosity perturbing mantle flow patterns in ways that produce large changes gravity anomalies and smaller changes in dynamic topography. A spatially-varying admittance will greatly complicate estimation of dynamic topography from observed gravity, and may help to explain mismatches between observations of dynamic topography and predictions made using global mantle flow models. On the other hand, the reconciliation of such mismatches may help to constrain viscosity heterogeneity in the lower mantle.Colli, L., S. Ghelichkhan, and H. P. Bunge (2016), On the ratio of dynamic topography and gravity anomalies in a dynamic Earth, Geophysical Research Letters, 43(6), 2510-2516, doi:10.1002/2016GL067929.
Longitudinal Extent of 3He-rich Solar Energetic Particle Events near 1 AU
Authors: Ho George , Mason Glenn , Kouloumvakes Athanasios , Allen Robert , Wimmer-Schweingruber Robert , Rodríguez-Pacheco Javier
Published: March 2024

Ever since the first 3He-enhanced solar energetic particle (SEP) event was reported in the literature in 1970, the exact mechanism by which the isotope is enhanced orders of magnitude higher than its solar wind value remains unknown.  But the source, acceleration, and transport of SEP events can only be studied by multi-point simultaneous in-situ measurement within the heliosphere.  However, multi-spacecraft observations of 3He-rich solar energetic particle (SEP) event are scarce.  Further observations are much needed in order to understand and properly constrain the source and transport of the remarkable enriched 3He SEP event. In this paper, we report six 3He-rich SEP events that were detected by ACE, STEREO and Solar Orbiter near 1 au during Solar Orbiter’s aphelion pass at the end of 2022 and early 2023.  Many of these events were detected simultaneously by at least two or three spacecraft at up to ~40° longitudal separation, while some events were detected by only a single spacecraft even though an adjacent spacecraft was less than 20° away. These fortuitous multi-spacecraft observations of 3He-rich SEP events thus provide us observational constraint on the acceleration and propagation of this special class of SEP events. In addition, we will show in this paper how multi-spacecraft measurements could also be used to constraint the solar source region of 3He-rich SEP event.
Insolation and ice volume induced extreme cooling events in East Asia during glacial times 
Authors: Lu Hao , Guo Jingjing , Fuchs Louise , Yin Qiuzhen , Sun Youbin , Peterse Francien
Published: March 2024

Our current understanding of past changes in East Asian monsoon climate variability is largely based on loess-paleosol sequences and speleothem δ18O records. Although most records have provided insight on the strength of summer monsoon precipitation, past temperature variations over East Asia are so far relatively poorly understood. Here we quantitatively reconstruct a high-resolution land temperature for central China covering the past 250 kyr, based on soil bacterial lipid signatures, co-called branched glycerol dialkyl glycerol tetraethers (brGDGTs) preserved in a loess-paleosol sequence at Mangshan on the eastern Chinese Loess Plateau (CLP). We find that the brGDGT-based temperature is dominated by precession cycles (21 kyr), except during the last deglaciation when temperature change was mainly driven by obliquity due to low eccentricity, consistent with model outputs. Notably, our record provides first evidence of extreme cooling events during glacial times when summer insolation decreases to a critical value as predicted by model simulations. Furthermore, the degree of cyclization (DC) of brGDGTs, which is suggested to indicate moisture availability, also shows clear precession cycles but does not show extreme events in response to the critical low insolation values. Our results thus indicate that the warm season temperature and moisture are mainly forced by precession, and extreme cooling events could be triggered by low summer insolation during glacial times.
BOSSE: The Biodiversity Observing System Simulation Experiment for Remote Sensing
Authors: Pacheco-Labrador Javier , Gomarasca Ulisse , Webber Ulrich , Li Wantong , Hamdi Zayd , Pabon Daniel , Loos Daniel , Jung Martin , Duveiller Gregory
Published: March 2024

Climate change and human activities jeopardize ecosystems’ biodiversity, functions, and services. However, biodiversity monitoring is resource-intensive and unable to provide the coverage and resolution necessary to understand biodiversity responses to these drivers. Remote sensing can contribute to monitoring plant biodiversity status and change by exploiting the variability of the spectral imagery acquired from space platforms. Still, several gaps must yet be solved regarding what approaches, metrics, sensors, and techniques can provide reliable biodiversity maps. One of the main challenges is the generation of field datasets with the spatial coverages and temporal resolutions necessary to determine the best methods.To overcome this problem from a theoretical point of view, we have developed BOSSE, a biodiversity observing system simulation experiment. BOSSE simulates dynamic scenes in time where vegetation properties change as a function of meteorological conditions and adopt different spatial patterns. High-spatial resolution scenes can be used to quantify plant functional diversity from plant traits. Moreover, BOSSE can simulate hyperspectral reflectance factors, sun-induced chlorophyll fluorescence, and land surface temperature that are coherent with plant traits of meteorology. Spectral imagery can be generated at different spatial and temporal resolutions, allowing us to test different approaches, metrics, and methods to estimate plant functional diversity.We have used BOSSE to determine the best approaches to characterize plant functional diversity of large areas, which is a fundamental step prior to assessing the links between remote sensing and ecosystem functions. Additional analyses have compared the capability of different spectral signals to capture plant functional diversity, the role of spatial resolution, and the role of seasonality in those estimates. We expect BOSSE to contribute to solving hypotheses and test methods and help determine what field datasets would be necessary to validate remote sensing biodiversity products.
Hydropeaking Mitigation with Re-Regulation Reservoirs
Authors: Mchayk Ali , Torabi Haghighi Ali , Marttila Hannu , Klöve Björn
Published: March 2024

The role of hydropower as a renewable and balancing power source is expected to significantly increase in a scenario of Net Zero Emissions by 2050. As a common phenomenon in hydropower plants, hydropeaking will become more prominent, resulting in additional stresses on the ecological status of rivers. Here we propose a novel engineering approach to operate auxiliary reservoirs, termed re-regulation reservoirs to address the challenges posed by hydropeaking on river flow regimes. A re-regulation reservoir aims at smoothing flow fluctuations caused by hydropeaking by diverting and retaining parts of high flows and returning them back to river corridors during low flows. The regulatory performance of re-regulation reservoirs is a function of its geometry and volume availability, and It is defined and optimized by restricting the thresholds of various flow components.In this study we developed a methodology and an open-access algorithm to operate re-regulation reservoirs using data from Kemijoki River, one of the most regulated rivers in Finland. The theoretical foundation of the algorithm was based on two main objectives, with the first aiming to reduce the hourly peak flow and increase the minimum hourly flow induced by hydropeaking. While the second objective aims to reduce the up- and down- ramping rates to increase the timespan of water level changes in the river’s corridor. Thus, the algorithm establishes a hierarchy of conditions to restrict peak flow, minimum flow, up-ramping rates, and down-ramping rates. However, as the ideal flow conditions for various ecosystem services may be different, a range of thresholds was utilized in each of the algorithm’s conditions resulting in thirty-five possible hydropeaking mitigation scenarios.In all of the thirty-five tested scenarios, the re-regulation reservoir limits peak and minimum hourly flows and ramp rates according to thresholds defined by the algorithm. The results demonstrated that in most cases the required volume of the re-regulation reservoir increased as the thresholds for flow components became more stringent. However, for some scenarios this trend was not observed, indicating that matching the peak and minimum hourly flow with the ramping rates thresholds is required to achieve optimal re-regulation reservoir design. Nonetheless, our calculations show clear theoretical possibilities for regulating hydropeaking with re-regulation reservoirs.Compared to other mitigation measures, such as the installation of downstream flow control devices or modifying the operation of hydropower facilities, re-regulation reservoirs offer greater flexibility and adaptability to changing environmental conditions, power, and water demand without increasing the operational cost of power systems.
Assessing Model Relevance: Agroclimatic Indices Across Different CORDEX Domains for Enhanced Climate Projections in the Houceima-Tanger-Tétouan Region
Authors: Qacami Meryem , Bourgault Marc-André , Chikhaoui Mohamed , Badard Thierry , Trudel Mélanie , Najat Bhiry
Published: March 2024

Understanding the intricacies of climate behavior is paramount for regions like Houceima-Tanger-Tétouan, where agroclimatic phenomena directly influence socio-economic stability. This study rigorously evaluates the performance of climate models against the ERA5-Land reanalysis data, focusing on two pivotal agroclimatic indices: dry spell and heat wave frequencies. Such indices are integral for regional drought risk management, agricultural planning, and environmental policy formulation.Our approach integrates a dual comparison framework—comparing model outputs against each other (inter-model) and against multiple runs of the same model (intra-model). We also validate the ERA5-Land data against 16 years of in-situ measurements to confirm its aptitude as a benchmark dataset, particularly examining its representation of temperature and precipitation.Findings indicate a strong temperature data correlation with in-situ measurements, affirming the ERA5-Land's reliability for temperature-related indices. However, precipitation data showed considerable variability, necessitating cautious application and potential model adjustments. Among the models, the MOHC-HadGEM2-ES demonstrated notable accuracy in dry spell predictions for selected domains, while the MPI-M-MPI-ESM-MR model stood out for its heat wave frequency projections, especially in the EUR-44 domain.Our results pave the way for selecting the most appropriate models for regional climate projections. They also highlight the necessity of model calibration, especially for precipitation indices, to ensure the precision of climate-related predictions. The study contributes to the field by providing a clear pathway for the utilization of tailored climate models in developing robust adaptive strategies to climate variability in the Houceima-Tanger-Tétouan region.
The value of Iberian Margin paleotemperature records with a novel organic proxy to revisit the bipolar seesaw model
Authors: Davtian Nina , Bard Edouard
Published: March 2024

The last glacial cycle provides the opportunity to investigate large changes in the Atlantic Meridional Overturning Circulation (AMOC) beyond the small fluctuations evidenced from modern measurements. Paleotemperature records from Greenland and the North Atlantic, including the Iberian Margin, show an abrupt variability, called Dansgaard–Oeschger (DO) events, which is associated with abrupt changes of the AMOC. These DO events also have Southern Hemisphere counterparts via the thermal bipolar seesaw, a concept describing the meridional heat transport leading to asynchronous temperature changes between both hemispheres. However, temperature records from the North Atlantic, notably the Iberian Margin, show more pronounced DO cooling events during massive releases of icebergs known as Heinrich (H) events, contrary to ice-core–based temperature records from Greenland.We present high-resolution temperature records over the last 160 kyr using several independent organic proxies (e.g., RI-OH′, TEX86, and UK′37) from three deep-sea sediment cores located in a north-south transect along the Iberian Margin (cores MD99-2331, MD95-2040, and MD95-2042). Over the 160–45 ka BP period, the recent RI-OH′ proxy yields faithful temperature records along the Iberian Margin in comparison with established paleotemperature proxies (e.g., TEX86 and UK′37; Davtian et al., 2021 Paleoceano. Paleoclim. https://doi.org/10.1029/2020PA004077). In the southern Iberian Margin (core MD95-2042), the RI-OH′ and UK′37 proxies faithfully reflect the contrasting DO cooling amplitudes with and without H events over the last glacial cycle (Davtian et al., 2021; Davtian and Bard, 2023 PNAS https://doi.org/10.1073/pnas.2209558120).We also revisit the thermal bipolar seesaw model using two independent temperature records (RI-OH′ and UK′37) from the southern Iberian Margin (core MD95-2042; Davtian and Bard, 2023). We show that temperature records from the southern Iberian Margin better support the classical thermal bipolar seesaw model than do ice-core–based temperature records from Greenland. We also introduce an extended thermal bipolar seesaw model that considers the contrasting DO cooling amplitudes with and without H events in the southern Iberian Margin, and a Bipolar Seesaw Index to distinguish DO cooling events with and without H events. Our data-model comparison emphasizes the role of the thermal bipolar seesaw in the abrupt temperature variability of both hemispheres with a clear enhancement during DO cooling events with H events, implying a relationship that is more complex than a simple flip-flop between two climate states linked to a tipping point threshold.
What's driving change at the Vanderford Glacier, East Antarctica?
Authors: Bird Lawrence , McCormack Felicity , Beckmann Johanna , Mackintosh Andrew , Jones Richard
Published: March 2024

The Aurora Subglacial Basin contains 7 m of global sea level equivalent (SLE). The Totten Glacier is currently the dominant outlet glacier of the Aurora Subglacial Basin; however, neighbouring the Totten Glacier, the smaller Vanderford Glacier drains a region containing 0.67 m of SLE. Vanderford Glacier is the fastest retreating glacier in East Antarctica, with over 18 km of grounding line retreat in the last two decades. The warmest modified circumpolar deep water in East Antarctica has been observed offshore the Vanderford Glacier, highlighting the potential vulnerability of this region to a warming climate. Here, we run transient simulations of the Ice-sheet and Sea-level System Model to examine the sensitivity of the Vanderford Glacier to key drivers of mass loss, namely sub-ice shelf basal melt and ice-front retreat. Simulations show that grounding line retreat is more sensitive to changes in basal melt than ice-front retreat, except for scenarios of extreme ice-front retreat. We show that the rate and extent of grounding line retreat comparable with observations only occurs under high magnitude basal melt conditions, while a similar extent of grounding line retreat occurs under the extreme ice-front retreat scenarios, but the temporal response of the grounding line is lagged. Given that grounding line retreat similar to observations is only achieved with basal melt magnitudes far exceeding those indicated by satellite remote sensing, our results highlight the need for methods to better estimate basal melt in this vulnerable region.
High-resolution multi proxy records across the Plio-Pleistocene boundary: a central Mediterranean perspective
Authors: Zanola Elena , Bonomo Sergio , Ferretti Patrizia , Fornaciari Eliana , Incarbona Alessandro , Rodrigues Teresa , Capraro Luca
Published: March 2024

The central Mediterranean region is traditionally acknowledged as a key reference area for investigating the Northern Hemisphere climate variability over the last few million years.Specifically, the expanded and highly fossiliferous open-marine succession currently exposed along the shoreline of Southern Italy and Sicily offers a pristine sedimentary record of the Neogene to Quaternary interval, which can be tightly constrained in time and deeply investigated by means of a manifold array of paleoenvironmental and paleoclimatic proxies (e.g., Cita et al., 2008; Capraro et al., 2017, 2022). In this context, the Monte San Nicola (MSN) section, located in Southern Sicily, provides an exceptional stratigraphic record for studying the climate evolution throughout the Piacenzian to Gelasian interval. The MSN succession hosts the GSSP for the Gelasian Stage (ca. 2.58 Ma; Rio et al., 1998), which presently marks the base of both the Pleistocene Serie and the Quaternary System (Head et al., 2008). The section is currently under revision, especially in the interval straddling the Gelasian GSSP, which includes the definitive establishment of the Northern Hemisphere Glaciation (NHG), at around 2.6 Ma. This cooling event is marked by a triplet of glacial stages (i.e., MIS 100, 98 and 96) that are found just above the Piacenzian-Gelasian boundary.In the wake of the emerging interest towards the MSN section, we are currently committed to reconstructing a high-resolution multi-proxy record (foraminiferal δ18O and δ13C, Alkenones-derived SSTs, C37total and Alcoholic index) in the lower part of the “Mandorlo” section at MSN (Capraro et al., 2022; Zanola et al., 2024). Results achieved so far provide new insights on the paleoceanographic and paleoclimatic evolution of the central Mediterranean at the sub-orbital scale at the beginning of the NHG.
Towards a large-scale locally relevant flood modelling using adaptive mesh generation and an integrated sub-/super grid channel solver
Authors: Rong Youtong , Bates Paul , Neal Jeffrey
Published: March 2024

Developing reliable and efficient flood modelling systems on a large scale is crucial for addressing errors and inconsistencies in both observations and modelling. However, the computational demands of hydrodynamic models have constrained their widespread application to coarse resolutions (30m-1km), compromising accuracy by neglecting the local and small-scale features that may significantly influence flooding, especially in urban areas. Furthermore, traditional models struggle to effectively incorporate river bathymetry, especially given the significant flood volume conveyed by the river channel during floods. These models often rely on surveyed cross-sections for river channel representation, leading to missing topography between cross-sections and hindering the resolution of complex floodplain flow paths. To resolve small-scale effects in limited areas while simulating large domains, grid adaptation methodologies are implemented in this project to locally adjust the resolution of the computation in a static or a dynamic way. A hybrid 1D-2D flood model is developed, incorporating the static/dynamic adaptive mesh generation and an integrated sub-/super grid channel model. The sub-/super grid channel is applied to accommodate situations where river channel width exceeds or fall below the grid resolution. Parallelized with GPU architecture, the performance of hybrid 1D-2D with either static or dynamics nonuniform structured grid was thoroughly evaluated, benchmarked with the full resolution CPU solver, shedding light on their effectiveness in enhancing flood modelling approach.
The role of biochar in a circular economy: from agriculture to water and wastewater treatment applications
Authors: Regkouzas Panagiotis , Asimakoulas Ioannis , Athanasiadou Eirini , Koukouraki Elisavet , Stefanakis Alexandros
Published: March 2024

Biochar is a sustainable carbonaceous solid material derived from biomass pyrolysis, which abides to circular economy principles in several ways that concern both its production and its several application fields. Biochar is produced by valorizing different organic waste biomass, such as agricultural waste, municipal solid waste, sewage sludge and industrial biowaste, to create a beneficial and valuable product that can then be used in many fields. Thus, biochar production serves perfectly the circularity paradigm as it renders a previously considered waste material to a valuable input material for a new production process. The grounds for the increasing use of and interest in biochars is their favourable physicochemical characteristics, such as the high carbon, macro- and micro- nutrient content, the high porosity and specific surface area, and the abundance of surface functional groups.Biochar can be effectively used as soil amendment providing fertilizing properties to the applied soil that leads to higher crop production and increased crop nutrient content and quality. At the same time, it provides a stable source of carbon to the soil for several years after its application, contributing this way to CO2 mitigation. Biochar can also be used as an adsorbent due to its carbonaceous porous structure to remediate polluted soil, water and wastewater from either organic or/and inorganic pollutants, even in low pollutant concentrations.Τhis abstract will present a comprehensive range of studies on biochar production from different sources and its use in different sectors. One of the latest applications is its use as a substrate in Constructed Wetlands for sustainable wastewater treatment, in order to enhance the various pollutant removal/transformation processes. Three different research studies will be presented where biochar was produced from green waste (e.g., olive tree branches) and used as substrate in various Constructed Wetland pilot units that treat domestic wastewater, landfill leachate and olive mill wastewater as an ecological treatment technology.Furthermore, an agronomic application of biochar as soil amendment in a pot experiment for the cultivation of lettuce will be shown. Finally, the environmental application of biochar produced from sewage sludge as adsorbent will be presented towards the decontamination of water and wastewater from organic emerging micro-contaminants.
A Foray of Dynamics into the Realm of Statistics: A Review of Ensemble Forecasting
Authors: Toth Zoltan , Feng Jie , Zhang Jing , Pena Malaquias
Published: March 2024

Uncertain quantities are often described through statistical samples. Can samples for numerical weather forecasts be generated dynamically? At a great expense, they can. With statistically constrained perturbations, a cloud of initial states are created and then integrated forward in time. By now, this technique has become ubiquitous in weather and climate research and operations. Ensembles are widely used, with demonstrated value. The atmosphere evolves in a multidimensional phase space. Does a cloud of ensemble solutions encompass the evolution of the real atmosphere? Theoretically, random perturbations in high dimensional spaces have negligible projection on any direction, including the error in the best estimate, therefore consistently degrading it. As the bulk of the perturbation variance lies in the null-space of error, samples in multidimensional space do not contain reality. An evaluation suggests that initial and short-range forecast error and ensemble perturbations are random draws from a high dimensional domain we call the subspace of possible error. Error in any initial condition is a result of stochastic observational and assimilation noise, while perturbations explore other, mostly independent directions from the subspace of possible error that may have resulted from other configurations of stochastic noise. What benefits may arise from the deterministic projection of such noise? 
Probing the Depths of Spatial and Temporal Variability in Jupiter from Juno Microwave Radiometer Observations
Authors: Orton Glenn , Zhang Zhimeng , Levin Steven , Fletcher Leigh , Oyafuso Fabiano , Li Cheng , Brueshaber Shawn , Wong Michael H. , Momary Thomas , Bolton Scott , Baines Kevin , Dahl Emma , Sinclair James
Published: March 2024

    Juno’s Microwave Radiometer (MWR) is providing the unprecedented opportunity to explore the dynamical properties and composition of Jupiter’s deep atmosphere, which is arguably one of the most visibly heterogeneous and time variable in the solar system. Since its arrival on 27 August 2016, the MWR has observed variability in microwave emission at wavelengths between 1.3 and 50 cm, sensing from 0.7 bar to over 100 bars of atmospheric pressure at over 57 close approaches to the atmosphere, known as “perijoves”. There has been a concerted effort to collect contextual information from other Juno instruments, as well as ground- and space-based observations to help interpret the MWR results. The space-based observations have included those from Juno’s own visible camera (JunoCam) and its Jupiter Infrared Auroral Mapper (JIRAM), as well as the Hubble Space Telescope (HST). The ground-based observations have included images and spectra from both professional and citizen-science astronomers.     We report here observations that are constrained to spatial resolutions of 2 degrees in latitude or better, and have been subject to recent improvements in the calibration drift for all MWR’s channels with an improved relative calibration uncertainty of 0.5% or better over the entire mission.  This has allowed us to evaluate zonal-mean temperatures and variability with improved confidence that these are real and not an artifact of receiver drift. The region that by far shows the greatest variability from a zonal mean is the North Equatorial Belt, (NEB: 12oN-16oN planetocentric) with a 2% standard deviation from the mean at all levels sensed by the MWR except for the 50-cm channel that senses variability in temperature and ammonia and water composition at pressures in excess of 100 bars of pressure. Among the strongest variability associated with discrete features in the atmosphere is a major upwelling and subsequent clearing of cloud cover in the North Temperate Belt (NTB: 20oN-26oN) in August-September of 2020.  In general, the microwave antenna temperature variability often but not always correlates with visible or near- to mid-infrared variability. In some regions, such as the Equatorial Zone (EZ: 3oS-6oN), substantial variability is detected not only in regions above the level of the water-condensate cloud (~10 bars) but also at great depth (>100 bars). An important part of our next steps will be to examine where variabilities in the zonal-mean microwave brightness are the result of zonally discrete features in the atmosphere, particularly the NEB.
Climatic controls on the stream network topology
Authors: Li Minhui , Seybold Hansjörg , Fu Xudong , Wu Baosheng , Kirchner James
Published: March 2024

Stream networks are striking expressions of how Earth’s hydraulic cycle shapes topography, yet the degree to which different geomorphological processes are visible in their ramified structure remains debated. Here we analyzed 18,030 river networks across the contiguous United States as mapped by the high resolution National Hydrographic Dataset, measuring the Tokunaga parameter c, which characterizes the degree of side-branching, in order to quantify the stream networks' topologies. We find that stream networks with more side branches tend to occur in wetter climates while channel networks in arid regions are less "feathered". As side branches tend to be steeper than the main channel, the aridity-induced dependence of slope ratio identified in recent studies may indicate inherent topological differences between stream networks in arid and humid regions. Such climatic signatures in the planform morphology of stream networks may help to better understand landscape evolution on the continental scale, and may also hold clues for the climatic history of other planetary bodies such as Mars or Titan.