bluuebunny/crossref_metadata_2025 huggingface dataset:
Dusty secrets: REE unveil hidden trends in foliar plant nutrition under rising CO2
Authors: Lokshin Anton
Published: March 2024

Dusty secrets: REE unveil hidden trends in foliar plant nutrition under rising CO2 Anton Lokshin1,2, Avner Gross2, Daniel Palchan1 1Department of Civil Engineering, Ariel University, Ariel 40700, Israel2 Department of Geography and Environmental Development, Ben Gurion University of the Negev, Beer Sheva 8410501, Israel The emerging phenomenon of direct foliar nutrient uptake, where dust deposits replenish plant ionome under stress, holds potential as a significant adaptation in a changing world. Dust's rapid leaf deposition, bypassing soil contact, offers a unique nutrient source, particularly relevant in soils of limited fertility. Rising CO2, known to hinder root nutrient uptake, along with an expected decrease in soil fertility, further underscores the potential importance of this pathway. Here, we present findings from laboratory experiments in which chickpea plants were treated with atmospheric particles used as natural fertilizers. These particles, including fire ash, volcanic ash, and desert dust, were applied to plant foliage under ambient and elevated CO2 conditions. We examined the foliar nutrient pathway from the Rare Earth Elements (REE) perspective and demonstrated that REEs serve as an excellent tool for its exploration. Analysis of the REE within the treated plants showed enrichment in Light REE compared to Heavy REE concurrent with higher biomass and improved carbon assimilation – proving the nutrients were assimilated into the plant rather than just surface retention. Finally, our results elucidate a couple of trends in the foliar nutrient uptake pathway: (1) under elevated CO2 levels, the foliar uptake is larger, and (2) nutrient transport from dust to plant is in the following order- volcanic ash > desert dust > fire ash. Analysis of REE patterns and ratios, alongside other biological parameters, provides novel insights into the extent and dynamics of foliar nutrient uptake across dust types and CO2 levels, shedding light on previously unexplored aspects of this crucial adaptation.
Origins of Barents-Kara sea-ice interannual variability modulated by the Atlantic pathway of ENSO
Authors: Luo Binhe , Xiao Cunde , Luo Dehai , Dai Aiguo , Simmonds Ian , Wu Lixin
Published: March 2024

Winter Arctic sea-ice concentration (SIC) decline plays an important role in Arctic amplification which, in turn, influences Arctic ecosystems, midlatitude weather and climate. SIC over the Barents-Kara Seas (BKS) shows large inter- annual variations, whose origin is still unclear. Here we find that interannual variations in winter BKS SIC have significantly strengthened in recent decades likely due to increased amplitudes of the El Niño-Southern Oscillation (ENSO) in a warming climate. La Niña leads to enhanced Atlantic Hadley cell and a positive phase North Atlantic Oscillation-like anomaly pattern, together with concurring Ural blocking, that transports Atlantic ocean heat and atmospheric moisture toward the BKS and promotes sea-ice melting via intensified surface warming. The reverse is seen during El Niño which leads to weakened Atlantic poleward transport and an increase in the BKS SIC. Thus, interannual varia- bility of the BKS SIC partly originates from ENSO via the Atlantic pathway.
Iron-magnesium silicates in rocky planetary interiors: Have we really discovered them all?
Authors: Bindi Luca
Published: March 2024

The study of iron-magnesium silicates within rocky planetary interiors has been a cornerstone of mineralogy, petrology and planetary science, offering insights into the composition and evolution of celestial bodies. The talk will present an exploration of the current understanding of these silicates and critically examines the question: Have we truly discovered them all?Recent advancements in analytical techniques, including high-pressure experiments and computations, have challenged conventional assumptions about the ubiquity and diversity of iron-magnesium silicates. During the talk, key discoveries on Earth, Mars, and other celestial bodies will be reviewed revealing unexpected mineralogical variations and prompting a reevaluation of existing models.
Introduction of tropospheric chemistry in the CNRM Earth System Model (ESM): towards methane emission-driven capability.
Authors: Cussac Martin , Michou Martine , Nabat Pierre , Josse Béatrice , Sophie Pelletier
Published: March 2024

Methane (CH4) is the second most important greenhouse gas after carbon dioxide (CO2), and improving the representation of its cycle in climate models is a key step to reduce uncertainties in climate projections. Its main sink is chemical removal through oxidation with hydroxyl radicals (OH) in the troposphere, which are produced during the photolysis of ozone (O3) in presence of water vapour. This process is an example of the complex interactions between methane and climate system, highlighting the necessity to have an explicit and interactive representation of atmospheric composition in Earth System Models. Here we present the introduction of two tropospheric/stratospheric chemical schemes of various complexities in ARPEGE-Climat 7.0, the future version of the atmospheric component of CNRM-ESM, and the impact on methane representation. This work includes the addition and changes of multiple processes at stakes in the troposphere, for instance emissions, deposition or production of NOx by lightning strikes. We first present an evaluation of tropospheric air composition in our model including all the aforementioned developments. Diagnostics from both chemical schemes in AMIP-type simulations are compared to observations and to state of the art atmospheric composition reanalyses such as the CAMS reanalysis. We highlight, in particular, the performance of both chemical schemes in terms of biases and seasonal cycles of major tropospheric tracers like O3, CO or NO2. We also compute from RFMIP-type simulations the ozone ERF, and compare it to previous estimates. Secondly, we present an evaluation of the behaviour of pre-industrial simulations in a methane “emission-driven” mode. These simulations are compared to more classical “concentration-driven” simulations in terms of global methane budget and methane chemical lifetime.
Hybrid approaches to model salinity in Gatun Lake
Authors: Castrellón María Gabriela , Wang Zheng Bing , Solomatine Dimitri , Popescu Ioana
Published: March 2024

Gatun Lake, located in central Panama, is the main source of freshwater for the operations of the Panama Canal. It also provides drinking water for nearly 600,000 people which is about 15% of Panama’s population. Historically, the lake has maintained a salinity well below 0.1 PSU, but since the inauguration of the Neo-Panamax locks in 2016, salinity in the lake has rapidly increased. This is a concern not only for drinking water supply and human health but for biodiversity as well. Accurately modelling salinity concentration and transport mechanisms in Gatun Lake is crucial for understanding its response to climate change and anthropogenic activities and to design effective management and mitigation strategies. However, current modelling techniques, both process-based (PB) and data-driven (DD), are limited in their ability to provide fast and accurate results with small amounts of data, especially in situations when boundary conditions are unknown or uncertain. Therefore, hybrid models have emerged as a potential solution to bridge the gap between these two approaches. The work presented here explores hybrid modelling approaches to estimate the magnitude of saltwater intrusion through the Neo-Panamax locks and calculate a salinity mass balance for Gatun Lake. Understanding these processes is useful for personnel at the Panama Canal Authority as it will inform their decision-making regarding management of Gatun Lake’s water quality and quantity.
Forest microbiomes and aboveground forest functioning 
Authors: Anthony Mark Alan ,   ICP Forests Microbiome Collaboration
Published: March 2024

Forest soils and roots harbor hyper-diverse microbiomes which strongly shape the growth and development of plant communities. How the biodiversity and functional capacities of the microbiome influence emergent ecosystem functioning is an important next frontier in the biogeosciences with implications for conservation, ecosystem management, and microbiome engineering. Directly testing hypotheses between microbiome diversity and forest functioning has been obstructed by a lack of paired data on microbiomes and in situ observations of forest growth and health. Here, I will synthesize findings from two large-scale European forest soil and root sampling efforts where we identified features of the mycorrhizal fungal, soil fungal, and bacterial communities linked to variation in forest tree growth and nutrition. We sampled roots and/or soils across 285 forest monitoring plots spanning 18 European countries, sequenced full-length fungal ITS and prokaryotic 16S amplicons to relate microbiomes to high resolution observations of tree growth, foliar nitrogen and phosphorus content, and aboveground carbon stocks. We show that the composition, richness, and traits of both root and soil inhabiting symbiotrophic fungal guilds is tightly linked to variation in tree growth, nutrition, and aboveground biomass carbon stocks while the biodiversity of free-living microbiomes was not tightly coupled to these key metrics of aboveground forest functioning. We also produced a roster of fungal biodiversity and compositional traits which are strong positive and negative bioindicators of forest carbon storage and nutrition. These large-scale observations lay important groundwork for experimental studies and demonstrate that soil microbiomes capture unique variation in emergent forest functions that cannot be explained by other physical, chemical, and biological properties.
Towards regional CH4 inversions with ICON-ART assimilating satellite TROPOMI data over Europe
Authors: Ho David , Steiner Michael , Koene Erik , Gałkowski Michał , Marshall Julia , Gerbig Christoph
Published: March 2024

Inversion modeling is a top-down technique to infer greenhouse gas (GHG) emissions using atmospheric observations. In particular, the use of satellite retrievals have been attractive due to their advantage in dense spatial coverage compared to typically sparse surface networks.The goal of this study is to assimilate satellite data at high spatial resolution to independently locate and quantify GHG sources and sinks, which can be used as a reference for carbon budget studies and policy makers. The findings also contribute as groundwork for the development of the Integrated GHG Monitoring System for Germany (ITMS).For this purpose, we coupled the numerical weather prediction and atmospheric transport model ICON-ART with an Ensemble Kalman Filter (EnKF) based inversion system, using the CarbonTracker Data Assimilation Shell (CTDAS). We use column data (XCH4) measured by the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, targeting anthropogenic CH4 fluxes over Europe. Prior anthropogenic emissions are taken from the EDGARv4.3.2 inventory, while natural fluxes were derived from peatlands, mineral soils, lakes, oceans, biofuels, biomass burning, termites, and geology. We first present a synthetic study of our system by performing an ensemble simulation forward in time with randomly perturbed emission fields. CH4 fluxes were retrieved at 0.25° x 0.25° resolution, and prior emissions are scaled to optimally fit the measured values. With this idealized experiment, we demonstrate that the system is capable of capturing the prescribed spatial pattern applied onto the emission field, using pseudo-observations of satellite retrievals with realistic coverage. In addition, we report on the results of assimilating real observations into the system, including emission estimates and their associated uncertainties. This study demonstrates the potential of incorporating satellite retrievals into inverse modeling, enabling us to extend its application to other GHG species. It also serve as a preparation work for the planned Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) satellite mission.
A computational framework for irrigation scheduling of a winter wheat – summer maize rotation system
Authors: Fan Xiangyu , Schütze Niels
Published: March 2024

One of the solutions for the current problem of limited arable land and growing demand for food is the increase of the land use intensity, e.g., by crop rotation. However, it can lead to excessively high agricultural water demand. We evaluate a winter wheat-summer maize crop rotation system, the main cropping system in the North China Plain, and develop a computational framework for optimal irrigation of two consecutive crop growth periods within a single year. The framework considers the impact of climate variability and considers limited agricultural water allocation.  In a case study for a site in the North China Plain, the framework is implemented using Aquacrop-OS that simulates the soil water balance and the interactions between two consecutive cropping seasons. A two-stage optimization ensures the maximum global crop water productivity, considering the food risk and yield stability. The developed framework can be used for optimal irrigation scheduling and as a tool for estimating minimum irrigation water demands and crop productivity for more sustainable water resources management on a regional level.
Benchmarking simulations of forest regrowth across Europe
Authors: Dinh Thi Lan Anh , Goll Daniel , Ciais Philippe , Carvalhais Nuno , Lauerwald Ronny
Published: March 2024

Dynamic global vegetation models (DGVMs) are essential for quantification of the response of land carbon storage to changes in atmospheric chemistry, climate, and land cover. While DGVMs are often evaluated concerning carbon responses to changes in CO2 and climate, local responses to changes in land cover have received less attention. This is of concern as DGVMs are needed to project the long-term consequence of afforestation or deforestation on the land carbon balance under climate. Here, we present an assessment of the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) model, one of the state-of-the-art DGVMs, aiming to evaluate the simulated growth in forest biomass carbon stocks across the European Union against comprehensive observational data.We conduct a model-data comparison of biomass growth using databases that contain paired observations of above-ground biomass (AGB) and plant age, categorized across various age groups spanning from very young (0-19 years) to old (>99 years) forests for boreal and temperate forests. The biomass dataset encompasses a harmonized collection from multiple open forest inventory databases, comprising 603 sites across Europe for six plant functional types (PFTs). On average, the stands are approximately 58 years old, with a mean AGB of 6.4 kgC.m-2. The findings indicate that simulations replicate the observed trend: AGB increases rapidly in young stands (60 years old). However, the observed AGBs exhibit broader ranges and have more extremes than the simulated values. This is expected as observations refer to individual species, while our simulations are on the level of PFTs, which are an assemblage of species. Moreover, the comparisons reveal that the model underestimates AGB for temperate needleleaf evergreen forests, with a median deviation of approximately 60% from observed values. We propose a recalibration of the maximal rate of carboxylation and gross primary production fraction lost as growth respiration to reduce this deviation to less than 10%.Our study highlights the potential of using observational biomass data to assess and calibrate DGVMs. This approach significantly enhances the ability of DGVMs to accurately reproduce the short-term land carbon sink response to reforestation. We provide a protocol that can easily be adapted to evaluate and recalibrate other DGVMs for the same purpose.
Storylines of high-impact climate events
Authors: Shepherd Theodore
Published: March 2024

High-impact climate events are generally expected to be exacerbated by climate change. For heatwaves, heavy precipitation, and evaporatively-driven drought, the IPCC AR6 made very strong general statements about changes in hazard. But as soon as one attempts to attribute high-impact climate events, the particular details of those events (which are inevitably compound events) and of the human-managed environment take centre stage. Because real-world events are not independent and identically distributed, one cannot reliably apply a general statement to a particular event. This basic aspect of statistical inference, widely recognized in other fields, seems not well appreciated within the climate science community. Physical climate storylines (physically-based unfoldings of past climate or weather events, or of plausible future events or pathways) offer a way to respect the complexity of high-impact climate events and the multiple causal factors involved, of which climate change will only be one. Indeed, identifying the non-climatic factors that affect vulnerability and exposure is essential for good decision-making around climate adaptation. In this talk I will describe the rationale behind the use of storylines for high-impact climate events from the broader perspective of attribution, and explain how conditional attribution allows probability and risk to enter in a physically interpretable and meaningful way.
Applying institutional grammar to analyze the institutional structure of water resources governance in interstate river basins
Authors: Lai Chee Hui , Zhao Jianshi
Published: March 2024

Due to increased climate uncertainty, political instability and economic turbulence, many interstate river basins are in the midst of transforming their water governance strategies to embrace the aforementioned challenges. A prerequisite of achieving such transformation is to understand various types of rules that build the water governance structure of the river basins. Therefore, we demonstrate an institutional analysis approach that combines the institutional grammar and the institutional analysis and development framework’s rule typology to identify the various type of formal rules regulating the water resources in Australia’s Murray-Darling Basin (MDB). The institutional feature and key actors of the basin’s water governance structure under different water governance situations are also explored. The approach is built on an institutional content analysis tool named institutional grammar and the institutional analysis and development framework’s rule typology. Using the approach, we dissect the Murray-Darling Basin Agreement of Australian Government’s Water Act 2007 to generate data for institutional analysis and subsequently, identifying the number and types of rules that form MDB’s water governance structure. We identify that MDB’s water governance structure stresses on choice rules and information rules that regulate actors’ choice of actions and the flow of information. Nevertheless, there are rules that only present in certain water governance situations, which indicating its institutional features. For instance, the position rules that create the basin’s water resource administrative units are found only in the action situation of administration. The scope rules that delineate the physical outcome to be produced are found dominating the action situations of water resource appropriation. The co-thinking type of aggregation rules that control the requirement of stakeholder consultation are mostly found in the situation of basin planning. In conclusion, the proposed approach able to generate the quantitative and qualitative information that can be used to analyze the complex structure of water resource governance in a river basin. Therefore, the research contributes to the development of a systematic water institution analysis tool.
Comparison and analysis of the influence of geological differences on sediment runoff volumes from watersheds -case study of plutonic and metamorphic rocks in two sediment disasters in Japan-
Authors: Akita Hromi
Published: March 2024

This study examined the sediment characteristics of areas where landslides occurred due to heavy rains between 2014 and 2019. A total of 5 types of geology in two geographic regions in Japan were examined using LiDAR LP topography data before and after the disasters occurred to estimate the changes in elevation. In addition, the volume of sediment runoff for each case was estimated for watershed areas ranging from 0.01 up to 0.1 km2. The influence of geological differences on the sediment runoff volume within the basin using indicators such as the density of landslide occurrence, landslide volume, and watershed erosion intensity was also assessed. The results showed that, for all geology types, as the watershed area increases, the relief ratio decreases and the sediment runoff volume increases; however, the magnitude of this increase in sediment runoff volume differs depending on the underlying geology. In addition, the density of landslide occurrence was high in plutonic and metamorphic rocks. The landslide volume and the total eroded sediment volume within a watershed can be regressed using the linear equation y=ax. Since the average total eroded sediment volume within a watershed is approximately twice that of the landslide volume, there is a proportional relationship of 1:2. The relationship between the relief ratio and watershed erosion intensity shows that the watershed erosion intensity increases gradually as the relief ratio increases, and the rate of increase is larger in plutonic rocks (granite and granodiorite) than in the other groups. Metamorphic rocks had a relatively low watershed erosion intensity; these geological differences are reflected in differences in the degree of erosion of stream beds and banks by flood flows.
Statistical Study of Electron Kinetic Entropy Generation at Earth's Quasi-perpendicular Bow Shock
Authors: Lindberg Martin , Wallner Alice , Berglund Sofie , Vaivads Andris
Published: March 2024

We use the Magnetospheric Multiscale mission to study electron kinetic entropy across Earth's quasi-perpendicular bow shock. We perform a statistical study of how the change in electron entropy depends on the different plasma parameters associated with a collisionless shock crossing. We find that the change in electron entropy exhibits strong correlations with upstream electron plasma beta, Alfvén Mach number, and electron thermal Mach number. The source of entropy generation is investigated by correlating the change in electron entropy across the shock to the measured electric and magnetic field wave power strengths for different frequency intervals within different regions in the shock transition layer. The electron entropy change is observed to be greater for higher electric field wave power within the shock ramp and shock foot for frequencies between the lower hybrid frequency and electron cyclotron frequency. This implies electrostatic waves are important for electron kinetic entropy generation at Earth's quasi-perpendicular bow shock but also for the non-adiabatic electron heating at quasi-perpendicular shocks.
Using space-based NO2 observations to indirectly estimate anthropogenic CO2 emissions
Authors: Lin Xiaojuan , van der A Ronald , de Laat Jos , Eskes Henk , Huijnen Vincent , Mijling Bas , Ding Jieying , Liu Zhu
Published: March 2024

Since anthropogenic NOx (NOx=NO+NO2) and CO2 are co-emitted species for anthropogenic sources, some studies have used the NOx emissions retrieved from satellite observations to infer the anthropogenic CO2 emissions. However, these studies did not consider the fact that satellites measure total NO2 concentrations and their inferred emissions encompass both biogenic and anthropogenic sources. In this study, we introduce a method to distinguish soil NOx emissions from satellite-based total NOx emissions. The total NOx emissions are derived by the state-of-the-art inverse algorithm DECSO (Daily Emission estimation Constrained by Satellite Observations, Mijling and van der A, 2012; Ding et al., 2017a) from TROPOMI observations. Using the characteristic seasonal cycle of soil emissions we derive these emissions for representative regions with only biogenic emissions, which are then applied to nearby regions according land-use fractions. To evaluate this approach, we compared the deviation between the tropospheric NO2 concentration observed by satellite and two atmospheric composition model simulations: one using the satellite-derived soil NOx emissions and another with the Copernicus Atmosphere Monitoring Service (CAMS) global soil emissions inventory (CAMS-GLOB-SOIL). Once the soil NOx emissions are derived, they can be subtracted from the total emissions to get anthropogenic NOx emissions. Subsequently anthropogenic CO2 emissions can be estimated using known CO2/NOx factors from bottom-up inventories. The annual CO2 emissions derived from DECSO (called DECSO-CO2) in our study area (large part of Europe) is 3.7 Gt in 2019, which is comparable with the 3.2 Gt of the CAMS CO2 inventory (called CAMS-CO2). The DECSO-CO2 and CAMS-CO2 are comparable for most large sources and cities, but the DECSO-CO2 show a larger number of low emission spots than the CAMS-CO2. The results demonstrate the potential for DECSO to expand its application to other regions in the world with less information on anthropogenic CO2 emissions.
What happens before eruption? Effect of strong crystal content and time dependence of permeability at very low gas content in immobile silicic magmas
Authors: Theurel Anna , Collombet Marielle , Burgisser Alain , Martel Caroline , Arbaret Laurent , Champallier Rémi
Published: March 2024

Magmatic outgassing plays a crucial role in the eruptive dynamics of silicic volcanoes. Gas escape from the volcanic conduit is facilitated by the coalescence of gas bubbles, leading to permeable bubble chains that are usually constrained by a crystalline framework within the magma. Our research provides experimental evidence of decompression-induced permeability in gas-poor crystal-rich silicic magmas that are not subjected to external strains. Synthetic samples were produced in Internally Heated Pressure Vessels (IHPV) to constrain and compare gas behavior with varying crystal content and size, and dwelling time. The permeable samples have a mean gas permeability of 10-14 m² for bulk porosity lower than 10% and bulk crystal contents of up to 75 vol%. Our results show that outgassing is possible in stagnant conduit at greater depths than initially assumed. This outgassing occurs even at low gas content, provided that the high crystallinity contains at least a microlite population with possible phenocrysts. Results also reveal a strong time dependence of the permeable bubble-chain lifetime in a closed magmatic system. If the dwelling time is too short, the coalescence process is incomplete, whereas if it is too long, the bubble chains resorb and become impermeable. Even with no magma deformation, the phenomenon of coalescence and percolation, therefore, remains dynamic. Our findings imply a new mechanism of deep outgassing for immobile magmas dominated by capillary forces, which has key implications on the explosive–effusive transition.
Effect of supply and demand conditions on the storage utilization for the ATES Triplet
Authors: van Esch Thijs , Bloemendal Martin , Hartog Niels , Vardon Phil
Published: March 2024

Space heating and cooling is responsible for roughly 25% of our final energy use, therefore it is a necessity to decarbonize our heating and cooling systems. Many technologies for space heating and cooling use a heat pump, making space heating and cooling more dependent on electricity. Since other sectors are similarly becoming more dependent on electricity, a main challenge in the energy transition is electricity grid congestion. This is even more a challenging issue given the season variation within heating and cooling demands.                Hence, there is a need for a technology that disconnects the heating and cooling demand from electricity use. The Aquifer Thermal Energy Storage (ATES) Triplet is a technology that does just that. The ATES Triplet uses local sources for heating and cooling, such as solar collectors and dry coolers, and disconnects the temporal supply and demand asynchrony with subsurface storage. It has a hot well, for when the heat source either has too much or too little supply to match demand, a cold well for the time when a cold source has either too much or too little supply for direct cooling. Furthermore, it has a third well that prevents thermal pollution of the hot and cold well. Because of this integration, the ATES Triplet system can supply heating and cooling without a heat pump.                Parametric simulations are presented to give insight into operational behaviour. A systematic variation of heating and cooling demands, injection temperatures, minimum operation temperatures and return temperatures gives insight into requirements to design and operate an efficient and reliable system. These parameters mostly influence either the heat recovery from the hot well, or the temperature in the third well. A lower heat recovery in the hot well results in a higher need for heat generation, and is mainly influenced by the heating demand, the injection temperature, and the cutoff temperature. A higher temperature in the third well results in a smaller need for heat generation, but a higher need for cold generation, and is influenced by the heating and cooling demands, and the return temperatures.
Storyline attribution and projection of the 2020 spatially compounding flood-heat event in southern China
Authors: Chen Yang
Published: March 2024

Attribution of compound events informs preparedness for emerging hazards. However, the task remains challenging because of complex space-time interactions amongst extremes, climate models’ deficiency in reproducing dynamics of various scales, and uncertainties in dynamic aspects of climate change. During June-July 2020, a historic flood hit the Yangtze River Valley and to its south the hottest summer since 1961 was observed, leading to disproportionate socioeconomic and environmental impacts to southern China. For attributing the recording-breaking spatially compounding event, we conduct a storyline attribution analysis by designing a series of simulation experiments via a weather forecast model, with large-scale dynamics equally constrained and thermodynamics of the climate system modified. We report that given the large-scale dynamic setup, anthropogenic influence has exacerbated the 2020 extreme Mei-yu rainfall by ~6.5% and warmed the southern co-occurring seasonal heat by ~1℃. The framework further details human influence on key elements to the two extremes individually and their coupling in space. If the same compound event unfolds in the 2090s, it is plausible to expect the monsoonal rainfall extremes ~14% wetter and the accompanying South China heat ~2.1°C warmer than observed.This method opens an avenue for attribution of low-likelihood, dynamically-driven, spatially and temporally compounding events.
Modelling detrital cosmogenic nuclide concentrations during landscape evolution in the LEM CIDRE
Authors: Carretier Sebastien , Regard Vincent , Abdelhafiz Youssouf , Plazolles Bastien , Vainer Shlomy
Published: March 2024

The measurement of cosmogenic nuclide (CN) concentrations in riverine sediment has provided breakthroughs in our understanding of landscape evolution. Yet, linking this detrital CN signal and relief evolution is based on hypotheses that are not easy to verify in the field. Models can be used to explore the statistics of CN concentrations in sediment grains. In this work, we present a coupling between the landscape evolution model Cidre and a model of the CN concentration in distinct grains. These grains are exhumed and detached from the bedrock and then transported in the sediment to the catchment outlet with temporary burials and travel according to the erosion-deposition rates calculated spatially in Cidre. The concentrations of various CNs can be tracked in these grains. Because the CN concentrations are calculated in a limited number of grains, they provide an approximation of the whole CN flux. Therefore, this approach is limited by the number of grains that can be handled in a reasonable computing time. Conversely, it becomes possible to record part of the variability in the erosion-deposition processes by tracking the CN concentrations in distinct grains using a Lagrangian approach.  We illustrate the robustness and limitations of this approach by deriving the catchment-average erosion rates from the mean 10Be concentration of grains leaving a synthetic catchment, and comparing them to the erosion rates calculated from sediment flux, for different uplift scenarios. We show that the catchment-average erosion  rates are approximated to within 5% uncertainty in most of the cases with a limited number of grains. This model opens up new possibilities for studying sediment residence times in landscapes, assessing the effect of recycling in calculating paleo-erosion rates, and proposing new methods based on the combination of several isotopes.
The impact of sea ice thickness biases on the projected summer sea ice-free Arctic in CMIP6 ensemble experiments 
Authors: Tian Tian , Yang Shuting
Published: March 2024

The IPCC’s 2021 assessment suggested that substantial emissions reduction and limiting global temperature rise to well below 2.0°C could prevent the complete loss of Arctic sea ice in this century. However, these assessments come with large uncertainties. Recent research projects a summer ice-free Arctic by the 2050s even under a low emission scenario by constraining future sea ice area with satellite-derived sea ice concentration (SIC) since 1979. Notably, the climate models in these assessments commonly underestimate the accelerated Arctic warming and the pace of sea ice melting, particularly over the last two decades. Moreover, recent studies indicate that in a warming climate, the thinning of sea ice and snow over sea ice may intensify surface warming, thereby accelerating the melting.In this study, we leverage the increasing availability of observations and recent reanalysis data for Arctic-wide sea ice to investigate the link between changes in sea ice thickness (SIT), sea ice concentration (SIC), and Arctic warming. We employ these datasets to evaluate biases in historical periods and uncertainties in future scenarios within the CMIP6 multi-model ensemble for SIT and SIC. We further investigate the relationship between the thinning of sea ice and the snow layer on sea ice and surface temperature changes on a basin or regional scale. The findings are then used to constrain projected Arctic changes. Our study aims to gain some insights into the impact of model biases in the Arctic on projected climate projections, crucial for decision-making in a changing climate.
Quantifying adaptation strategies: The gate index approach to extreme sea level scenarios in the western Baltic Sea
Authors: Su Jian , Ehlers Birte-Marie , Nielsen Jacob Woge , Madsen Kristine Skovgaard , Larsen Morten Andreas Dahl , Janssen Frank
Published: March 2024

Sea level rise is a significant threat to coastal regions, requiring thorough scientific evaluations to implement effective adaptation planning. Recent incidents of damages to ships and infrastructure in harbours during storm surge events in the western Baltic Sea have highlighted the urgent need for robust adaptation strategies to sea level rise. This study utilizes regional climate simulations, employing five members of the EURO-CORDEX ensembles, to investigate sea level rise scenarios under the RCP4.5 and RCP8.5 scenarios. Using the concept of "gate index", the study quantitatively assesses the frequency and duration of potential closures of storm surge gates in harbours in response to extreme sea level rise events. The results show significant spatial differences in vulnerabilities across the region, with increased risks under the RCP8.5 scenario. The analysis also emphasises substantial uncertainties, stemming from various factors such as variations in global climate models, complexities in ocean-atmosphere interactions, potential changes in ice sheet dynamics, and uncertainties in future greenhouse gas emissions trajectories. In addition, regional factors such as local sedimentation processes, tectonic activities, and land-use changes can further amplify these uncertainties. The interplay of these multifaceted factors underscores the complex nature of projecting sea-level rise, highlighting the need for a cautious and adaptive approach in coastal planning and policy formulation. These findings provide critical insights for policymakers and practitioners engaged in coastal risk assessment and adaptation planning in the vulnerable Baltic Sea region.
Green Panel performance testing – Analysis from one season of monitoring data and implications for urban scale applications
Authors: Vink Karina
Published: March 2024

Most cities have climate goals such as lowering the Urban Heat Island (UHI) effect and reducing flood damages. Green infrastructure (GI) can help mitigate the UHI effects and has the potential to locally delay flood peaks. However, in dense urban infrastructure there is often little space for ground based vegetation. Green roofs are therefore a feasible implementation option even within city centres. While there is a myriad of types of green roofs available for flat roofs, and their performance is tested in various environments, sloped roofs as of yet have few design options available. To this end, Green Panels were developed as a novel type of GI for sloped roofs. As it is a novel design, its performance can be estimated only by literature results of GI applying different designs and materials. To overcome this research gap, in this case study a Green Panel prototype was constructed and its performance was monitored over a period of 3-4 months at the University of Twente, the Netherlands.The experimental setup consisted of 1 m2 of Green Panels, and 1 m2 of regular roof tiles as control area, both at a slope of 45 degrees. The materials of the Green Panels, mounted on the same railing as solar panels, is High Density Polyethylene, while different substrates were tested: soil, rock wool, recycled fabric, and combinations thereof. Applied sensors were a soil moisture and temperature sensor (Truebner SMT50) and an environmental sensor (BME680), including a thermal sensor, both connected to Sensebox Mini dataloggers. The soil moisture sensors were placed in each of 6 Green Panel trays. The environmental sensors were placed above and below the roof tiles in both control and Green Panel locations, as well as above and below the Green Panels themselves. The measured parameters were air temperature, humidity, atmospheric pressure, VOC, soil temperature, and soil moisture. These values were compared to meteorological data from a local weather station at 5km distance. Other benefits such as increased biodiversity were not monitored, though species such as ladybug (family Coccinellidae) and fly (family Muscidae) were observed.Analysis of the results shows that there is a small effect of Green Panels on reducing extreme temperatures, and errors in measurement setup and gaps in data continuity did not affect validity. The implications of this analysis were extrapolated to the urban scale for the city of Enschede to help answer what an appropriate performance monitoring scheme is for cities intending to implement GI and still uncertain about when their climate goals are being met.
Is the fate of Mesoscale Convective Systems written from the start?
Authors: Muller Caroline , Abramian Sophie , Risi Camille , Roca Remy , Fiolleau Thomas
Published: March 2024

Mesoscale Convective Systems (MCSs) that become large or have long lifespans contribute disproportionately to extreme rainfall. Gaining a better understanding of the factors that determine whether a system will become large could improve our understanding of extreme weather phenomena. The recent emergence of high-resolution global simulations from the DYAMOND project, coupled with a storm tracking algorithm called TOOCAN, provides a groundbreaking opportunity to study the factors controlling the maximum area of MCSs. In this study we use machine learning algorithms to predict the maximum area of convective systems based on their early development stages and initial environmental conditions. The results reveal that the initial evolution of the system anticipates its maximum area. Factors such as the presence of ice in the system's environment, proximity to surrounding systems, intensity of vertical velocity at 500 hPa, and the migration distance, have been identified as significant factors in improving the accuracy of the prediction. Using a linear model, we investigate the relative role of the environment and of the system itself, in the growth of the system. 
From model development to co-designing user-centered earthquake forecasts
Authors: Dallo Irina , Marti Michèle , Mizrahi Leila , Wiemer Stefan
Published: March 2024

Enhancing societies’ resilience is crucial for saving lives and mitigating losses caused by significant earthquakes. Earthquake forecasting offers an opportunity to inform societies – professionals and the general public – about the probability of earthquakes of certain magnitudes to occur. Particularly following a severe earthquake, earthquake forecasts (in this special case sometimes called aftershock forecasts) play a pivotal role in addressing the common question "What comes next?" posed by various stakeholders, including the media, the public, regional and national authorities. Earthquake forecasts allow to respond quantitatively to this question. Nevertheless, understanding how stakeholders utilize the often very low probabilities of future large earthquakes needs further research to ensure accurate interpretation and effective implementation of the provided forecasts.At the conference, we will present the procedure applied by the Swiss Seismological Service at ETH Zurich in developing and validating the forecasting model, as well as the co-creation and testing of communication materials. In essence, our approach involved conducting an expert elicitation to understand common practices, fostering an international network for continuous knowledge exchange. In parallel, we began formulating and testing the earthquake forecast model tailored to Switzerland and started assessing the needs of Swiss end users. Our ongoing efforts involve designing forecast products intended for duty seismologists, enabling them to respond promptly to media inquiries and to public requests. We also test these products and more simplified prototypes with authorities and the public, providing for instance insights into the likely evolution of an earthquake sequence.Some first insights from the international expert elicitation are that (i) societal stakeholders need support in interpreting the forecasts; (ii) scenarios are a common way to communicate earthquake forecasts; (iii) ideally, earthquake forecasts would be permanently communicated to society; (iv) information needs do not vary significantly between the different stakeholders; and (v) the way earthquake forecasts are communicated to society should be tested and co-designed with the intended users. Regarding the latter, stay tuned for the conference where we present the techniques and methods we have been using for the stakeholder testing in Switzerland.This work was supported by the European Union’s Horizon 2020 research and innovation program under Grant Agreement Number 101021746, sCience and human factOr for Resilient sociEty (CORE), and the Swiss Seismological Service at ETH Zurich.
Convective storms and methane clouds on Uranus & Neptune: sporadicity and latitudinal variations revealed by a 3D cloud-resolving model
Authors: Clement Noe , Leconte Jeremy , Spiga Aymeric , Guerlet Sandrine , Milcareck Gwenael , Le Saux Arthur , Selsis Franck
Published: March 2024

Uranus and Neptune have atmospheres dominated by molecular hydrogen and helium. In the upper troposphere (between 0.1 and 10 bars), methane is the third main molecule and condenses, yielding a vertical gradient in methane. Because it is heavier than the H2/He background, methane condensation can inhibit convection and moist convective storms. Previous studies derived an analytical criterion on the methane vapor amount, above which moist convection is inhibited. In ice giants, this criterion yields a critical methane abundance of 1.2% at 80K (this corresponds approximately to the 1 bar level).Using a 3D cloud-resolving model, we have shown (Clement et al. 2024, submitted in A&A) that this critical methane abundance governs storms inhibition and formation, concluding that the intermittency and intensity of storms depends on the methane abundance. Where methane exceeds this critical abundance in the deep atmosphere (at the equator and the middle latitudes on Uranus, and all latitudes on Neptune), frequent but weak storms form. Where methane remains below this critical abundance in the deep atmosphere (possibly at the poles on Uranus), storms are rarer but more powerful.We use the insights of our 3D small-scale simulations to build a 1D parameterization of diffusion and convection for radiative-convective and global climate models. As 3D cloud-resolving simulations require long computation times, a radiative-convective model is needed to extrapolate heating tendencies. The combined use of these models should enable us to estimate more realistic periods between convective storms and explain the observed latitudinal sporadicity of methane clouds over a long period of time.