bluuebunny/crossref_metadata_2025 huggingface dataset:
On various effects of dust on the concentration of dissolved organic carbon in the sea
Authors: van Kaam Rianne , Kölling Martin , Hinrichs Kai-Uwe , Zabel Matthias
Published: March 2024

After input from rivers, the aeolian input of particles is probably the main source of nutrients in the ocean. Dust also plays an important role in the transport of organic material into the deep sea. However, little is known about the adsorption capacity of mineral dust for dissolved organic material (DOM). In this study, we investigate the effects of dust-seawater interaction on the carbon cycle. We collected dust samples in the form of silty crusts (grainsize < 63 µm) from the ephemeral rivers Kuiseb and Omaruru in Namibia, Southern Africa. To characterize the source material, we analysed for total organic carbon (TOC), specific organic compounds, 13C/12C isotope ratio, elemental composition and specific surface area. Sorption experiments were performed through time series and isotope analysis. We added different amounts of dust to a mixture of artificial seawater with DOM and 13C labelled DOM, both extracted from Spirulina algae and each in naturally occurring concentration. Experiments with a moderate amount of dust showed a decline in dissolved organic carbon (DOC) over time. This finding was also confirmed by analyses of 13C/12C isotope ratio on dust samples, before and after suspension in seawater DOM solution. Both results indicate that dust adsorbed a significant portion organic carbon from the Spirulina DOM solution. However, the net uptake of DOM on mineral particle surfaces depends on the ratio between DOM concentration and the amount of dust used. If dust already contains organic components, which was the case in our experiment, at least some of these organic compounds will dissolve in contact with seawater if the ratio between the amount of dust or primary organic material contained and the DOM concentration in the initial test solution exceeds a certain value. In this case, the input of dust represents a source of DOM in the near surface seawater. Our study reveals that terrestrial, mineral dust may act as both a sink and a source for DOM in surface waters of the ocean. Subsequent studies will have to clarify the extent of the impact of these effects on the carbon cycle. 
Unexpected decoupling between biodiversity and standing stocks in marine calcifying phytoplankton 
Authors: de Vries Joost , Monteiro Fanny , Wolf Levi
Published: March 2024

For many ecosystems, biodiversity promotes productivity. Global biodiversity loss due to anthropogenic climate change has thus raised concerns about its resulting impact on productivity since ecosystem services like carbon sequestration are key in limiting climate change. Our oceans are especially important in this context, as they sequester more carbon than terrestrial ecosystems. Nonetheless, our understanding of how biodiversity relates to productivity in oceanic ecosystems is limited and hitherto undescribed for coccolithophores, a main ocean calcifier which plays a key role in the ocean carbon cycle. Here, by combining a new comprehensive coccolithophore abundance data set and species distribution models we illustrate that biodiversity is decoupled from standing stocks for coccolithophores. We show this is because the processes driving coccolithophore diversity do not influence coccolithophore standing stocks. Our results contribute new knowledge about the relationship between productivity for a key marine planktonic microorganism, highlighting that diversity loss due to anthropogenic carbon emission does not necessitate reduced ocean standing stocks and productivity. This result is important for climate models, suggesting that they do not need to capture our ocean’s full diversity to capture key biogeochemical processes such as calcification and carbon fixation.   
Parametric study for self-sustained Andean-type subduction speed
Authors: Assunção Jamison , Riel Nicolas , Piccolo Andrea , Sacek Victor
Published: March 2024

The relation between subduction dynamics, plate rheology and geometry is still not well understood. To numerically assess how subduction convergence velocity develops, a wide range of simulations is required to quantify any correlation between physical parameters and kinematic behavior of a subduction system. In this study, we performed a set of 2D numerical simulations designed to better constrain the range of rheological and geometrical conditions necessary to model subduction dynamics. We used the parallel numerical code LaMEM to simulate thermo-mechanical convection. In addition, we coupled these numerical simulations with MAGEMin to compute a self-consistent mineral assemblage of the asthenospheric mantle and the plates, and we parameterized the lower mantle using a linear equation, following the Clapeyron slope from Faccenda and Zilio (2017). The modeled region is 9300 km wide and accounts for both the upper and whole lower mantle. We consider an Andean type subduction system where our baseline scenarios are defined by a partially subducting oceanic plate beneath a continental plate. Once the simulation starts, the subducted portion of the oceanic plate triggers the subduction thanks to a weak zone between the lower and upper plate. The subduction is sustained by the negative buoyancy of the lower plate with respect to the surrounding mantle. We aim to simulate subduction dynamics that exhibit convergence velocities and long term behavior, including lower mantle penetration, similar to what is observed in nature. We investigate the role of the length of the subducting plate, the geometry of its composing lithological units, and the viscosity of the asthenosphere and the lower mantle. We find that the subduction velocity is inversely correlated with the non subduction length of the oceanic plate, and that a less viscous asthenospheric mantle increases the subduction speed. 
Scientific debunking of institutional and corporate communication
Authors: Husson Laurent ,   Scientifiques en Rébellion collective
Published: March 2024

Greenwashing sounds like a trivial manoeuvre that can easily be circumvented. In practice, private companies and institutions deploy a wealth of inventiveness to take away your vigilance. As a canonical example, it took forever before it was realized and admitted that the tobacco industry had a tremendous health burden. As scientists, we have the means to scrutinize the borderline communication, that stands half way between journalistic investigation and activism. That is the purpose of Scientist Rebellion in particular, which is particularly concerned with environmental challenges. Of course, it often requires to go beyond our daily scientific expertises, that we are trained for. Using two recent examples, I will showcase two case studies from Scientist Rebellion in France. The first one deals with the analysis of financial institutions regarding their oil and gas strategies, and the subsequent media coverage of activist communication, and an insider view on the impact of it had on the orientation of their strategies. The second one is an exploration of the governmental communication on adaptation strategies to climate change, with consideration on its political implications. 
Meta-analytic evidence on effective farming practices for climate change mitigation
Authors: Bosco Simona , Schievano Andrea , Pérez-Soba Marta , Montero-Castaño Ana , Chen Mathilde , Tamburini Giovanni , Catarino Rui , Guerrero Irene , Bielza Maria , Angileri Vincenzo , Assouline Michael , Koeble Renate , Mantegazza Otho , Dentener Frank , Van der Velde Marijn , Parracchini Maria Luisa , Weiss Franz , Terres Jean-Michel , Makowski David
Published: March 2024

In the context of climate change, high expectations have been put on the agricultural sector for reducing greenhouse gas (GHG) emissions and enhance carbon sequestration. Consequently, a large and growing number of studies have evaluated the efficacy of various agricultural practices for climate change mitigation. However, the scientific evidence is often heterogeneous and frequently contradictory, making it difficult to use to support policy decisions. Meta-analyses synthesise large data sets and have become the gold standard for providing scientific evidence to inform environmental and agricultural policies. However, a growing number of meta-analyses are now available on a specific topic, occasionally with conflicting conclusions, requiring a further level of synthesis to consolidate the findings.We present the results of a systematic review of 693 published meta-analyses on the effect of farming practices on climate change mitigation. After a systematic search and review of the literature, we extracted data assessing the climate impacts of 34 farming practices and 123 comparisons of sub-practices with corresponding control practices, for a wide range of cropping and livestock systems around the world. From this dataset, we selected the farming practices that showed overall significantly positive effects on the reduction of GHG emission and/or on the increase of carbon sequestration. For cropland and grassland, we were able to identify a set of 35 mitigation sub-practices , including cover and catch crops, intercropping, leguminous crops, the use of enhanced efficiency fertilisers, soil amendment with lime and gypsum, different crop residue management techniques, water management practices, different conservation, restoration and management measures in grasslands, conservation and restoration of peatlands and wetlands, the conservation and creation of landscape features, as well as organic farming systems. For livestock, we identified seven effective mitigation practices, including livestock feeding techniques, manure land application techniques, manure storage techniques. A limited number meta-analyses reported the effect of a given practice on more than one GHG or on GHGs coupled with carbon sequestration together, limiting the exploration of interacting effects.The systematic evidence map provides robust and encompassing literature based evidence on farming practices with established positive effect on climate change mitigation to support a wide community of inventory compilers, modellers and policymakers. Our review also identifies farming practices with remaining knowledge gaps and research priorities.
Long-term changes in water resources: the challenge of disentangling water management, climate change, and natural variability
Authors: Humphrey Vincent , Egli Marius , Wittholm Johanna , Jensen Laura , Sippel Sebastian , Eicker Annette , Ghiggi Gionata , Knutti Reto
Published: March 2024

Every year, natural climate variability leads to droughts and floods which have significant impacts for ecosystems and societies. Water reservoirs like soil moisture, lakes, and groundwater act as natural buffers and balance these fluctuations by providing water supply during dry conditions and by storing water surplus after rain and snow events. Such natural fluctuations unfold over time scales that can reach several decades, making it challenging to assess the extent to which trends in water reservoirs observed over the recent past are caused by anthropogenic modifications. Such modifications can themselves be further partitioned into different terms. For instance, one can contrast the contribution of regional land and water management on the one hand, and the contribution of climate change on the other. Another frequent framework is to causally relate changes in water storage to individual changes in precipitation, evapotranspiration, and runoff.In this contribution, we review the strengths and weaknesses of recent approaches used to causally attribute observed as well as projected changes in water availability. Ensembles of model simulations and factorial experiments typically represent a powerful way of assessing individual responses to drivers and developing a plausible and mechanistic understanding. However, contradictions also quickly emerge between global hydrological model simulations, which typically represent water reservoirs and water management more thoroughly, and Earth system (climate) model simulations, which include biogeochemical effects, like CO2 fertilization, that are typically neglected by hydrological models. We will show that these two incomplete modeling worlds can be reconciled with large-scale satellite observations in only a few regions, while very large uncertainties remain in other parts of the world and in particular over tropical areas.
Development of a System Dynamics based Irrigation Demand Model
Authors: Das Aurobrata , Sahoo Bhabagrahi , Panda Sudhindra Nath
Published: March 2024

Water resources globally are under severe threat due to population growth, intensive socio-economic development, change in climatic condition and increasing level of conflict among multiple water users. Under this context, an accurate and efficient supply-demand management of this critical resource is highly essential to ensure the water security of a region. Agriculture being the major water user, needs to be given primary importance. However, in canal command areas, there is an inefficient management of irrigation system without considering the real-time irrigation demand while supplying the irrigation water from the reservoir. This leads to either surplus or deficit irrigation supply throughout the year affecting both the water sector and the crop yield of the command. The real-time irrigation demand of a command depends upon the type of crops grown, antecedent soil moisture content and meteorological variables along with the social attributes of the stakeholders. Hence, this current study tries to develop a dynamic irrigation demand model comprising of all the afore-mentioned variables under system thinking approach. The causal feedback among the system elements were developed initially through causal loop diagram and the model variables were subsequently transformed into stocks and flows, representing the dynamic state of the system in order to develop the conceptual model. The developed model was tested in the Hirakud canal command located in the eastern part of India simulating the real system effectively. This developed model can be used by the water managers for efficient irrigation planning in a canal command ensuring overall water and food security of the region.
Increased irrigation frequency reduces N2O, but not overall denitrification losses (N2O+N2) from an intensively managed pasture following ruminant urine deposition and nitrogen fertilisation.
Authors: Friedl Johannes , De Rosa Daniele , Scheer Clemens , Fitzgerald Michael , Grace Peter R. , Rowlings David W.
Published: March 2024

Intensively managed pasture systems receive large inputs of nitrogen (N) in the form of fertiliser and through the  deposition of ruminant urine, creating hot-spots for denitrification which results in variable amounts of nitrous oxide (N2O) and dinitrogen (N2) emitted. Here we investigated the potential of increased  irrigation frequency to reduce N2O and N2 emissions from an intensively managed pasture in the subtropics after ruminant urine deposition. Irrigation volumes were estimated to replace evapotranspiration and were applied either once (Low-Frequency) or split into four applications (High-Frequency). This irrigation schedule was applied 3 times over the 60 day monitoring period, and fluxes of N2O and N2 were  measured using the 15N gas flux method. In line with farming practice, simulated urine patches (equivalent of 80 g N m-2 applied) were also fertilised three times with 2 g urea N m-2 to show the combined effects of urinary and fertiliser N on N2O and N2 emissions. Highest N2O emissions of up to 60 mg N2O-N m-2 day-1 were observed briefly after urine deposition, decreasing thereafter, resulting in cumulative N2O losses of 169.9 mg N2O-N m-2 from the Low-Frequency treatment. Denitrification was dominated by N2, accounting for more than 89% of  N2O+N2 emitted. Irrigation treatments had no effect on cumulative N2 losses of more than 2700 mg N2-N m-2. However, High frequency irrigation reduced cumulative N2O losses by 35%. Our findings suggest that under conditions of high N availability, increased irrigation frequency can reduce the environmental impact (N2O) of denitrification, but not overall N losses via this pathway. The response of N2O emissions may further indicate that less frequent, but more intense rainfall events will shift the product ratio of denitrification towards N2O, increasing environmentally harmful N losses from intensively managed pasture systems.
OurMED PRIMA-funded Project: Sustainable Water Storage and Distribution in the Mediterranean
Authors: Jomaa Seifeddine , Rouhani Amir , Schade Maria , Gómez-Hernández J. Jaime , Moya Diez Antonio , Oueslati Maroua , Guelmami Anis , Karatzas George P. , Varouchakis Emmanouil A , Tanda Maria Giovanna , Roggero Pier Paolo , Manfreda Salvatore , Hamidan Nashat , Madani Yousra , Lourenço Patrícia , Khlifi Slaheddine , Daloglu Cetinkaya Irem , Rode Michael , Copty Nadim K
Published: March 2024

The Mediterranean Region is a unique mosaic of different cultures and climates that shape its peoples, natural environment, and species diversity. However, rapid population growth, urbanisation and increased anthropogenic pressures are threatening water quantity, quality, and related ecosystem services. Known as a climate change hotspot, the Mediterranean region is increasingly experiencing intensifying droughts, diminished river flows, and drier soils making water management even more challenging. This situation calls for an urgent need for water management to shift from a mono-sectoral water management approach based on trade-offs, to more balanced multisectoral management that considers the requirement of all stakeholders. This means that sustainable water management requires ensuring that water is stored and shared fairly across all sectors at the basin scale.The research project OurMED (https://www.ourmed.eu/) is part of the Partnership for Research and Innovation in the Mediterranean Area (PRIMA) Programme supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 2222. The project was launched in June 2023 and will continue for three years with a grant of 4.4 million euros to develop a holistic water storage and distribution approach tightly integrated into ecosystem services at the river basin scale.OurMED builds on the multidisciplinary skills of 15 consortium Partners and comprises universities, NGOs, research centres and SMEs from ten countries with complementary expertise in hydrology, hydrogeology, agronomy, climate change, social sciences, remote sensing, digital twins, ecology, and environmental sciences, among others, making it a truly interdisciplinary project. OurMED includes eight distinct demo sites, representing diverse water-related ecosystem properties of the Mediterranean landscape. These include the catchment areas of Bode (Germany), Agia (Crete, Greece), Konya (Turkey), Mujib (Jordan), Medjerda (Tunisia), Sebou (Morocco), Arborea (Sardinia, Italy), and Júcar (Spain). The Mediterranean basin, as a whole, is considered as an additional regional demo site to ensure replicability and reproducibility of proposed solutions at larger scales. OurMED vision combines not only technologically-advanced monitoring, smart modelling and optimization capabilities, but also provides data fusion and integrated digital twin technologies to make optimized solutions readily available for decision making. OurMED concept and its implementation to the different demo sites will be presented and discussed.
Stability of radially spreading extensional flows and ice shelves
Authors: Stern Lielle , Sayag Roiy
Published: March 2024

Ice shelves that spread into the ocean can develop rifts, which can trigger ice-berg calving and enhance ocean-induced melting. Fluid mechanically, this system is analogous to the radial propagation of a non-Newtonian, strain-rate-softening fluid representing ice that displaces a relatively inviscid and denser fluid that represents an ocean. Laboratory experiments showed that rift patterns can emerge in such systems and that the number of rifts declines in time. Such a dynamics was confirmed theoretically, but only for the earlier stage of the flow and for a fluid layer of uniform thickness. We investigate numerically the stability and late-time evolution of radially spreading, axisymmetric fluid layer of non-uniform thickness. We validate the two dimensional finite-element Úa model using similarity solutions of radially spreading layers of Newtonian fluid that were found consistent with laboratory experiments. We then explore the stability of the flow by introducing geometric perturbations to the initial front and tracing their evolution. Our simulations show that the front of Newtonian fluids is stable, though memory of the perturbation spectral form persists.
Development of a drone-based measurement system for real-time monitoring of volcanic gas composition
Authors: Hoffmann Thorsten , Bobrowski Nicole , Karbach Niklas
Published: March 2024

Studying volcanic gas emissions is an important method to obtain information about volcanic systems and providing insight into magmatic processes. MultiGAS instruments allow to measure SO2 and CO2, alongside meteorological data which are important parameters in volcanic monitoring. In the past decade, these MultiGAS instruments have been adapted to be carried on drones, which enables the researchers to measure the gas composition from a safe distance as the drone operator can operate from farther away, probably even from a parking lot, therefore eliminating the need to reach the sampling site by foot. Additional, drone based measurements improve the possibility to undertake source specific measurements with a negligible influence of soil - as well as fumarole degassing. Frequent calibrations, preferably with the same environmental parameters (T, RH, p) that prevail during the measurement, are important to measure correct concentrations. However, as calibration equipment can be quite heavy and takes a long time to set up, it is not practical to carry calibration equipment to a regular used measurement site.We therefore propose to build a stationary measurement station with the aim of quickly taking correct measurements with minimal preparation and operating effort. The station will contain the aforementioned calibration equipment, a solar power supply for charging, a base station for all radio communications with the drone and sensors, and a data server with internet access to view the measurement data remotely. In addition to a typical MultiGAS instrument, a drone-based DOAS system will further expand the station’s capabilities. The two instruments will be easily exchangeable by attaching the sensors with rails to the main body of the drone.
Detection of Forest disturbances using multi source Remote sensing data. 
Authors: Tufail Basil , Dorigatti Emilio , Claus Michele , Jacob Alexander , James Peter
Published: March 2024

With recent impacts due to the climate crisis, the number of extreme events has increased globally. Floods, droughts, windthrows, and landslides are affecting the environment around us, increasing the difficulty of mapping and monitoring its conditions.  Forests are particularly suffering from such events and the ones affected by repeated damage usually don’t have enough time to recover and become more vulnerable to other threats. The 2018 Vaia storm, the subsequent snow breaks, and the spread of bark beetles in the forests of Trentino-South Tyrol are prominent examples that caused large-scale disturbances in the region. In this research, we focus on the detection of forest disturbances caused by such extreme events. Approaches like Breaks for Additive Season and Trend (Bfast) have been implemented to detect breaks and vegetation response patterns [1] whereas Continuous Change detection and Classification (CCDC) also performs well with long-term optical time series data like Landsat and Sentinel-2 to monitor vegetation phenology [2]. However, only a few studies have focused on advances in Synthetic Aperture Radar (SAR) data for detecting changes in radar datasets [3]. SAR data can provide timely information on disturbances in areas where frequent cloud cover makes it impossible to map the changes with optical data for long periods. Thus, the ability to acquire imagery regardless of clouds and severe weather conditions makes SAR data a viable solution to map such disturbances, though this still requires further testing. This study aims at benchmarking methodologies applied using open-source software's to create change detection maps with freely available data including both optical and SAR. Using various, already established change detection methods implemented in FAIR (Findability, Accessibility, Interoperability, and Reusability) manner to evaluate the added benefit of fusing data from different kinds of sensors. 

[1] Watts, Laura M., and Shawn W. Laffan. "Effectiveness of the BFAST algorithm for detecting vegetation response patterns in a semi-arid region." Remote Sensing of Environment 154 (2014): 234-245. 

[2] Zhou, Qiang, Jennifer Rover, Jesslyn Brown, Bruce Worstell, Danny Howard, Zhuoting Wu, Alisa L. Gallant, Bradley Rundquist, and Morgen Burke. "Monitoring landscape dynamics in central us grasslands with harmonized Landsat-8 and Sentinel-2 time series data." Remote Sensing 11, no. 3 (2019): 328. 

[3] Hirschmugl, Manuela, Janik Deutscher, Carina Sobe, Alexandre Bouvet, Stéphane Mermoz, and Mathias Schardt. "Use of SAR and optical time series for tropical forest disturbance mapping." Remote Sensing 12, no. 4 (2020): 727. 
Plastics Affect the Ocean's Uptake of Atmospheric CO₂ across the Marine Boundary Layer
Authors: Galgani Luisa , Tzempelikou Eleni , Kalantzi Ioanna , Tsiola Anastasia , Tsapakis Manolis , Pitta Paraskevi , Esposito Chiara , Tsotskou Anastasia , Magiopoulos Iordanis , Benavides Roberto , Steinhoff Tobias , Boldrini Amedeo , Polvani Alessio , Loiselle Steven A.
Published: March 2024

Microplastics can support biomass production by acting as substrates for microbial activity. This may imply potentially relevant effects for the sea-surface microlayer, the interface mediating air-sea gas exchange and where biological organic compounds can accumulate.We tested this hypothesis by using six large scale mesocosms to simulate a future “high plastic ocean”. During the course of a 12-days experiment, we explored microbial organic matter dynamics in the sea-surface microlayer in the presence and absence of microplastics in the underlying water. We used as a reference a known number of polystyrene beads of 30 µm diameter and compared the three treatment mesocosms to an equal number of plastic-free control mesocosms.The presence of microplastics represented a spur for microbial activity, and in the treated mesocosms biomass production was enhanced, leading to an increased concentration of organic compounds accumulating in the sea-surface microlayer. This initial boost in biological productivity led to a ∼3 % reduction of dissolved CO₂ in the underlying water, which we could imagine potentially reversed once the degradation phase took off. Based on our results and on other recent studies, we will discuss potential interference of plastic with the composition of the sea-surface microlayer, with direct and indirect impacts on the uptake of CO₂ and the marine carbon cycle. 
Exploiting the wealth of satellite radar altimeter data to calibrate regional, high-resolution hydrodynamic models
Authors: Slobbe Cornelis , Guarneri Henrique , Verlaan Martin
Published: March 2024

To exploit the wealth of satellite radar altimeter data in calibrating the regional, high-resolution 2D tide-surge Dutch Continental Shelf Model version 7 (DCSM) model covering the northeast Atlantic including the North Sea and Wadden Sea requires an approach that can be applied to the separate water level variability contributors. In this study, we aim to improve DCSM's ability in representing the low-frequency water level variability by assimilating data acquired by the TOPEX/Poseidon and Jason (TPJ) satellites. This variability, caused by physical processes not included in the model’s governing equations or forcing terms, is a major source of errors in the operational forecasting of water levels. To validate the impact of the data assimilation, we used i) S3-derived water levels acquired over the southern North Sea and Wadden Sea that were produced in the context of ESA’s HYDROCOASTAL project, and ii) tide gauge records required at 149 locations throughout the DCSM model domain. The results show that the impact of the assimilation is substantial. At the tide gauge locations, the median SD of the residual monthly-mean water levels reduced from 6.2 cm to 2.8. The impact cannot be assessed from the HYDROCOASTAL data. The most likely explanation is the fact that these data are still impacted by the tidal errors in the DCSM-derived tide-surge water levels.
Exploring how a warmer Mediterranean Sea affects the origin and development of destructive Tropical-Like Cyclones IANOS and DANIEL
Authors: Redaelli Gianluca , Liguori Giovanni , Cavicchia Leone , Miglietta Mario Marcello , Bonaldo Davide , Carniel Sandro , Calvo-Sancho Carlos , Martin Maria Luisa , Gonzalez-Aleman Juan Jesus , Ferretti Rossella , Ricchi Antonio
Published: March 2024

In a complex contest of climate change, we observe the evolution of extreme events that greatly challenge many areas of human life. Although the Mediterranean Sea is a relatively mild basin, it is however characterized by, occasionally intense cyclones with tropical-like characteristics known as Tropical-Like Cyclones (TLC). Many studies have highlighted that sea surface temperature (SST) distribution play a crucial role in modulating the intense air-sea exchange, hence controlling both development and evolution of TLCs. However, given the complex interplay among ocean mixed layer, heat content and temperature, the role of the mixed layer depth (MLD) and SST Anomaly is of paramount importance. In this study we investigated the role of both SST anomaly, horizontal gradients and MLD profile on the origin and evolution of a recent record-breaking TLC (named IANOS and DANIEL). IANOS and DANIEL are originated over the southern Ionian Sea. The first made landfall over Greece mainland coast and DANIEL made landfall over Libyan coasts. These TLCs developed over a basin where a positive SST anomaly up to 4 °C was detected, which coincided with the sea area where it reached the maximum intensification and strength. We conducted a series of experiments using an atmospheric model (WRF - Weather Research and Forecasting system) driven by underlying SST (standalone configuration), either with daily update or coupled to a simple mixed-layer ocean model (SLAB ocean), with SST calculated at every time step using the SLAB ocean for a given value of the MLD. Sensitivity tests were performed increasing or decreasing MLD depth by 10 m, 30 m, 50 m, 75 m, 100 m, removing the horizontal gradients, removing the SST anomaly. Then, possible past and future climatological scenarios of MLD thickness were identified and tested. Preliminary results show that the MLD influences not only the intensity of the cyclone but also the structure of the precipitation field both in terms of magnitude and location. The fundamental role of the SST anomaly was also found to be essential to provide intense characteristics to IANOS and DANIEL. Results deserve further investigation in the context of climate change scenarios that can provide useful insights into impact on coastal civil and economics in the whole Mediterranean region.
An open-source tool based on Google Earth Engine for spatially explicit crop yield modelling 
Authors: crecco lorenzo , bajocco sofia , di giulio mara , bregaglio simone
Published: March 2024

Process-based crop models can predict harvested yield by reproducing the effects of the environment on plant phenology and physiology. Accurate yield forecasts are essential to support strategic and tactical actions in public and private sectors. Applications span from detecting critical areas for food security issues to optimizing selling/buying prices of crop products in main producing regions, to informing farmers on the best agricultural management practices. Most crop models are point-based and must be integrated in a spatially explicit environment to provide the yield information in a target area at the desired spatial resolution. Remote sensing (RS) represents an invaluable resource to inform crop models with actual vegetation dynamics based on consistent and timely views of Earth's surface with time and space continuity. The main advantage of incorporating RS data into crop models is hence the representation of the missing spatial information and the reliable description of the crop’s health condition throughout the growing season. This study presents, an open-source tool developed within the Google Earth Engine environment to monitor crop growth and estimate crop yield. It is based on a generic model (SIMPLE) executed over large areas at run-time and is easily adapted to different crops by adjusting a few physiological parameters. SIMPLE algorithmic implementation uses ERA5-Land as weather source and derives the leaf area index (LAI, unitless) and the actual crop evapotranspiration (ETc, mm day-1) using data from the MODIS Normalized Difference Vegetation Index (NDVI). Results show that integrating RS data into the SIMPLE model allowed currently identifying the limits of the growing season and mapping seasonal crop phenology evolution in the Piedmont region. Abiotic stresses have been correctly spotted, and aboveground and yield of winter wheat and maize have aligned with reference data. Our findings have significant implications for improving yield estimations by identifying spatial patterns of crop growth productivity for summer and winter crops. This tool also shows potential for near-real-time monitoring of crop growth dynamics in response to abiotic stresses in sensitive phenological phases.
Heatwaves and compound extremes under atmospheric blocking
Authors: Mittermeier Magdalena , Suarez-Gutierrez Laura , Guo Yixuan , Fischer Erich
Published: March 2024

In early September 2023, Europe was under the influence of a pronounced atmospheric block in the shape of the Greek letter “omega”. Such an omega-blocking is characterized by a persistent anticyclone in the center flanked by two low pressure systems to the south in the west and east. The omega-block interrupts the mean westerly flow and leads to prolonged persistent conditions lasting for at least five days. The core of the omega-blocking in September 2023 was located over Central Europe and Southern Scandinavia, which experienced a heatwave in the first week of September 2023. On the other hand, the regions positioned at the eastern flanks of the omega-blocking (Greece, Bulgaria, Libya) were hit by heavy precipitation resulting in major floods.While omega-blocking situations can result in severe spatially compounding extremes, there is still a research gap on current and future dynamics of (omega) blocking. Current generations of climate models underestimate blocking frequencies – especially over Europe. This makes it difficult to derive robust statistics about blocking related compound extremes under current and future climate, because the observational record only offers a limited number of event examples and atmospheric blocking underlies a high natural climate variability.We employ the novel method of ensemble boosting to explicitly boost blocking situations in the Community Earth System Model 2 (CESM2) large ensemble. With this model re-initialization method initial conditions 10 to 30 days before the event are slightly perturbed, which results in hundreds of coherent physical event trajectories (event storylines). This allows to study following research questions: Is the CESM2 model capable of reproducing an omega blocking event with spatially compounding extremes in the magnitude of the September 2023 event? Could the September 2023 event have been even more devastating by chance? Have we experienced anything close to the most intense compound omega-blocking event possible under current climatic conditions? In our poster, we present our research concept as well as preliminary results.
CFD modeling of wind flow in a real urban site under low wind conditions
Authors: Alam Boulos , Feiz Amir Ali , Ngae Pierre , Chpoun Amer
Published: March 2024

Examining the dispersion of hazardous agents within complex environments, whether situated in urban or remote areas globally, requires a comprehensive analysis of evolving wind patterns and atmospheric stability in hazardous zones on an hourly basis. This investigation is essential to ensure that models employed for risk assessment can furnish a timely and effective response. However, modeling complex scenarios, especially those involving low wind conditions (wind speed < 1-2 m/s) and meandering, poses challenges due to the intricate dynamics of these phenomena.This study aims to conduct numerical modeling of wind flow in an urban area, characterized by sequences of weak winds and meandering. The computational analysis utilizes the atmospheric module of the Code_Saturne Computational Fluid Dynamics (CFD) software developed by EDF R&D. The inquiry originates from a measurement campaign conducted by LMEE (Laboratoire de Mécanique et d'Énergétique d'Évry) in Evry, south of Paris, France, spanning 16 months from September 2008 to December 2009. Statistical analysis of raw measurements from the campaign reveals that almost 45% of the winds are weak, with nearly 50% falling under very stable atmospheric conditions.The CFD model is evaluated against averaged observations obtained from micro-scale measurements using an ultrasonic anemometer. The study encompasses a 1x1 km grid covering the urban area. Subsequently, meso-scale hourly measurements from nearby Météo-France stations, providing essential outputs for the CFD model, are incorporated.
Resilience against the extreme weather: Scaling Anticipatory Action in Southeast Asia Region
Authors: Arsadita Ferosa
Published: March 2024

Anticipatory action is mostly interpreted as responding to impending disasters based on forecast or risk information. The time window between the generation of forecast information and the actual occurrence of a hazard provides opportunities for organisations or individuals to take short-term preparedness actions to mitigate the impact of disasters. In the context of the Southeast Asia region, studies indicate strong evidence and confidence that the frequency and intensity of extreme weather events are on the rise and climate change has become a threat multiplier to the risk of weather-related disasters. Anticipatory action has emerged as a promising approach to enhance resilience and shift the traditional approach in responding to disasters. Despite the shift and advances in weather forecasting, many predicted disasters continue to result in a significant number of casualties. Hence, this research aims to explore 1) In what ways does anticipatory action scale up in Southeast Asia? 2) To what extent do the barriers to successful implementation vary across different countries and contexts?
This research utilises a mixed approach, incorporating scientific literature, policy documents, and in-depth interviews with disaster management professionals, to examine the scaling of anticipatory action at national and regional levels. Qualitative content analysis is used to scrutinize the extent of legal frameworks governing disaster risk reduction and management. Concurrently, an abductive analysis method is employed for an inductive examination of emergent categories based on the expert interview, while also seeking to align these findings with established scaling frameworks.
This study uncovers three distinct ways through which anticipatory action is being scaled in the Southeast Asia region. First, anticipatory action initiatives have grown through replication, expansion, and spontaneous diffusion, originating primarily from community-level pilot projects led by non-state actors. Second, the scaling of anticipatory action has been done through policy adoption, as exemplified by recent legislative developments in the Philippines and also the adoption of the regional framework on anticipatory action by 10 ASEAN Countries. Third, in countries where anticipatory action has not yet been incorporated into the legal framework, the expansion may commence by strategically aligning it with existing programs that share similar objectives.
While scaling anticipatory action is evident in the region, knowledge disparity between state and non-state actors creates a fundamental barrier that impedes the expansion and replication of anticipatory action in the majority of ASEAN countries. Therefore, it is reflected in the existing disaster risk governance which impedes the conduct of anticipatory action. Yet, it may be overcome through targeted exercises, knowledge sharing, and capacity building for seamless integration into the disaster risk management continuum.
Temperature alters the size selectivity of Southern Ocean fish
Authors: Keith Patrick , Hill Simeon , López-López Lucía , Rosenbaum Benjamin , Saunders Ryan , Tarling Geraint , O'Gorman Eoin
Published: March 2024

A primary response of many marine ectotherms to warming is a reduction in body size, to lower the metabolic costs associated with higher temperatures. The impact of such changes on ecosystem dynamics and stability will depend on the resulting changes to community size-structure, but few studies have investigated how temperature affects the relative size of predators and their prey in natural systems. We utilised >3,700 prey size measurements from ten Southern Ocean lanternfish species sampled across >10° of latitude to investigate how temperature influences predator-prey size relationships and size-selective feeding. As temperature increased, predators became closer in size to their prey, driven primarily by a decline in predator size and an increase in the relative abundance of intermediate-sized prey. The potential implications of these changes include reduced top-down control of prey populations and a reduction in the diversity of predator-prey interactions. Both of these factors should reduce the stability of community dynamics and ecosystem resistance to perturbations.
Estimation of CO2 fluxes across different biomes using machine learning approaches
Authors: Goussard Basile , Pique Gaétan , Dussot Sarah
Published: March 2024

Quantifying CO2 fluxes over terrestrial land is crucial to better understand the global carbon cycle and the contribution of ecosystems to climate change. In addition, ecosystems such as croplands and forests have the potential to sequester carbon in the soil and vegetation. Robust tools to simulate CO2 fluxes with high accuracy are needed to identify best practices and management for carbon sequestration.In this study, the Net Ecosystem Exchange (NEE) from different networks (ICOS, NEON) is used to develop machine learning (ML) approaches to simulate daily CO2 fluxes. These biome specific approaches use as input high spatial and temporal resolution optical remote sensing products combined with meteorological data. The biomes considered are cropland, deciduous forest, evergreen forest and grassland. Different ML models were tested and the ExtraTreesRegression model seems to be better suited for all biomes except grassland where an SVR model was more appropriate. The features identified as most important among the remote sensing products are NDVI and NDMI while among meteorological variables, global radiation, air temperature and fraction of diffuse radiation appears as more relevant. The predicted results show good agreement with daily observations, with R2 of 0.82 over cropland. The performance of the model in simulating CO2 fluxes over forests is more contrasted with good accuracy over deciduous forests (R2 of 0.72) but low confidence over evergreen forests (R2 of 0.29). Finally the model was also applied to grassland, but the small size of the dataset combined with the high heterogeneity of soil and climatic conditions of grassland sites led to low correlation with observations (R2 of 0.44).This work demonstrates the potential of a machine learning-based method to assess CO2 fluxes across different biomes, and should be further explored due to its ease of use and application.
A Robust Satellite Technique for monitoring landslides impact on electrical infrastructures
Authors: Tramutoli Valerio , Kazemi Garajeh Mohammad , Guariglia Annibale , Paridad Parivash , Santangelo Raffaele , Satriano Valeria
Published: March 2024

Natural disasters, in recent years, are increasinglyaffecting critical infrastructures and, particularly, electric and gas supply pipelineswhich play a vital role in modern society. In order to enable effectivedisaster response, ensure the safety of affected populations, and facilitatethe recovery and rebuilding process following sudden-onset disasters, it is crucialto have accurate and timely information on infrastructure damage. This studyimplements an advanced multi-temporal technique to detect even small landslideaffecting electrical poles.  Land-coverinformation obtained by the Multispectral Instrument (MSI) sensor aboard theCopernicus Sentinel-2 platforms are used to timely (within days/weeks) identifysuch events. To this end, long-term satellite data are processed in the GoogleEarth Engine (GEE) environment to preliminarily characterize unperturbed soilconditions before to implement the RST (Robust Satellite Techniques) foranomalous soil conditions identification. Our findings reveal that severalelectrical poles had been affected by landslides in Sicily from 2016-2023. Theresults of this study also confirmed the efficiency of an RST-likeapproach  for landslide detection.
Anomaly detection within the 2021-2023 deformation pattern of the Campi Flegrei (Italy) caldera through the analysis of DInSAR and GNSS data
Authors: Giudicepietro Flora , Bonano Manuela , De Luca Claudio , De Martino Prospero , Di Traglia Federico , Di Vito Mauro Antonio , Lanari Riccardo , Macedonio Giovanni , Manunta Michele , Monterroso Fernando , Striano Pasquale , Casu Francesco
Published: March 2024

The Campi Flegrei caldera (southern Italy) is an active volcano whose last eruption occurred in 1538. This caldera is characterized by ground displacements (subsidence or uplift), often referred to with the term "bradyseism". Over the last two decades the Campi Flegrei caldera was affected by a phase of uplift which became progressively more intense over time and was accompanied by increasing seismicity and geochemical anomalies. The Campi Flegrei deformation pattern generally shows a bell-like shape, with the zone of maximum uplift in the central area corresponding to Rione Terra, that is the historic district of Pozzuoli. In the 2021-2023 period the OV-INGV seismic network detected significant seismicity and the GNSS and DInSAR measurements highlighted a high uplift rate of the central area of the Caldera. In this period, seismicity was distinctly felt by the population several times (maximum magnitude Md = 4.2) and the uplift of the central sector of the caldera reached a level that made it difficult to enter the ancient fishermen's port of Pozzuoli (about 120 cm compared to the ground level in 2005). We have carried out a detailed analysis of the ground deformations relevant to the 2021-2023 time interval. Our study has highlighted a local anomaly of the caldera deformation pattern in the Solfatara-Pisciarelli-Olibano hydrothermal area. This anomaly became well recognizable in 2022 and it further developed during 2023. Moreover, it affects the area in which the earthquakes with greater magnitude occurred in the Campi Flegrei. We interpret this zone as a possible weakness area in the crustal structure of the Caldera and, therefore, we believe that a detailed monitoring of this zone is foreseen because it may provide some relevant insights on the caldera dynamics and the related hazard.