bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Orchard Classification Accuracy through Object-Level Confidence Metrics: A Case Study in Automatic Orchard Identification in Valencia, Spain
Authors: Izquierdo Sanz Héctor , Moltó garcía Enrique , Morell Monzó Sergio
Published: March 2024

Effective agricultural management policies rely heavily on accurate crop identification across various scales. This is particularly challenging in highly fragmented agricultural landscapes, such as those found in many European regions, particularly for fruit tree orchard identification. While solutions exist, the confidence in individual orchard classification is often overlooked, despite its importance in enhancing classification accuracy (precision, recall and specificity).Several confidence metrics at pixel level have been proposed by estimating the probabilities of a pixel to belong to each of the possible classes. The higher the probability of class membership for a given class, the greater the confidence associated with that class. In this sense, a measure of confidence can be based in the differences of probability between the first two highest values (sometimes called the distance to the second cluster).This study introduces an innovative methodological approach to build a classification confidence metric at object (orchard) level. Once segmentation is completed, all pixels whose confidence is not above a certain threshold are masked out. Then, each orchard is initially assigned to a class by computing the mode of the unmasked pixels inside its perimeter. In a subsequent step, a confidence metric at orchard level is estimated, based on the number of mode class pixels, the total number of pixels completely inside the orchard, and the proportion of the mode pixels and unmasked pixels within the orchard. This confidence metric allows for a balance between increased precision and a reduction in the number of classified orchards (those with insufficient confidence in their classification).The proposed method, fully implemented in Google Earth Engine, was tested in a highly fragmented area in Valencia (Spain). The system’s performance was assessed by using a Random Forest classification algorithm on Fourier coefficients of spectral indexes time-series at pixel-level plus a specific spatial cross-validation procedure. By setting a 70% orchard classification confidence level, the mean overall accuracy increased from 88.74 ± 3.03% to 93.58 ± 2.85%, and the Kappa index from 0.78 ± 0.06% to 0.87 ± 0.05%, albeit at the cost of leaving 12.60 ± 7.18 % of orchards unclassified.
Isotope applications in the Critical Zone across Europe: the latest activities of the WATSON COST Action
Authors: Penna Daniele , van Meerveld Ilja ,   WATSON Extended Core Group
Published: March 2024

The COST Action WATSON - Water isotopes in the Critical Zone: from groundwater recharge to plant transpiration (CA19120; www.watson-cost.eu) is an European network of researchers and stakeholders who use the stable isotopes of hydrogen and oxygen to trace water fluxes to better understand hydrological, hydrogeological, and ecological systems. WATSON currently includes more than 250 members from 38 countries. The Action aims to integrate and synthesize current interdisciplinary scientific knowledge on the use of the stable isotopes of water to understand the mixing and partitioning of water in the Earth’s Critical Zone. The network is organized into four working groups (WGs) that focus on major scientific challenges: 1) groundwater recharge and soil water mixing processes; 2) vegetation water uptake and transpiration; and 3) catchment-scale residence time and travel times. A fourth WG is in charge of the communication and dissemination activities.WATSON started in 2020 and is currently in its final year. In this contribution, we synthetize the most recent results and the current and planned activities. WG1 is analyzing different isotope-based methods to calculate groundwater recharge in various environments, preparing training and educational material, and a review paper on isotope methods to assess groundwater recharge and subsurface mixing processes. WG2 is analyzing the data from two Europe-wide isotope sampling campaigns to estimate the sources of water uptake of beech trees and spruce trees. Moreover, WG2 is finalizing a review paper on isotope sampling, extraction, and isotopic analysis methods to study vegetation water use. WG3 is comparing different isotope-based methods to calculate transit times, and preparing training scripts and educational guidelines. WG4 is in charge of many dissemination and communication activities, including the monthly seminar series, updating the website and the social media accounts with the latest information, videos, and technical and scientific material. In addition, all WGs are involved in the preparation of an online, interactive, and open data-map showing locations where isotope samples have been collected.The WATSON activities will conclude with a large, final online conference, where all WATSON members (and beyond) will be invited to share their knowledge, experience, findings, and recommendations in using stable isotopes to advance our understanding of water fluxes in the Critical Zone. 
Ionospheric Impact on GNSS Reflectometry: A correction approach for the PRETTY satellite data
Authors: Moreno Mario , Semmling Maximilian , Stienne Georges , Hoque Mainul , Wickert Jens
Published: March 2024

The ionosphere, spanning 60 to 2000 km above the Earth’s surface, plays a crucial role in Global Navigation Satellite System (GNSS) signal propagation, as signals traverse this layer on their path from the GNSS satellite to the receiver. In GNSS Reflectometry (GNSS-R), coherent observations are prominent in regions with smooth reflecting surfaces and grazing elevation angles (5° - 30°). However, within this elevation range, higher ionospheric effects (e.g., delay biases) are expected due to the longer path signals travel through the atmosphere.Dual-frequency receivers can mitigate first-order ionospheric effects by using an ionosphere-free linear combination of code or carrier measurements. Single-frequency receivers, on the other hand, rely on a model to compensate for ionospheric refraction. In this study, the Neustrelitz Electron Density Model (NEDM2020) has been employed to estimate the slant total electron content (slant TEC) along the direct, incident, and reflected ray paths. The reflection events have been simulated using the orbit data from the Spire Global CubeSat constellation.In preparation for the single-frequency GNSS-R ESA “PRETTY” mission data, this study conducts a comprehensive characterization of relative ionospheric delay, Doppler shift, and variations in the heights at which the maximum electron density is found along the ray paths. The investigation spans different elevation angle ranges, latitude-dependent regions, diurnal changes, and solar activity conditions. The results span a wide range of slant TEC values from 10 TECU between the reflection point and receiving satellite at moderate elevations (15°) to 300 TECU between transmitter and receiver (direct path) at very low elevations (5°). These results correspond to periods of low solar activity (March 2021). The ongoing study focuses on identifying and correcting the ionosphere impact in satellite data of the CyGNSS and PRETTY missions based on the developed simulation scheme.
Dynamical Complexity in Swarm-Derived Storm and Substorm Activity Indices Using Information Theory: Further Evidence for Interhemispheric Asymmetry
Authors: Papadimitriou Constantinos , Balasis Georgios , Boutsi Adamantia Zoe , Potirakis Stelios , Daglis Ioannis A. , Giannakis Omiros
Published: March 2024

In November 2023, the ESA Swarm constellation mission celebrated 10 years in orbit, offering one of the best-ever surveys of the topside ionosphere. Among other important achievements, it has been recently demonstrated that Swarm data can be used to derive space-based geomagnetic activity indices. These can be used like the standard ground-based geomagnetic indices for monitoring magnetic storm and magnetospheric substorm activity. Given the fact that the official ground-based index for the substorm activity (i.e., the Auroral Electrojet – AE index) is constructed by data from 12 ground stations, solely in the northern hemisphere, it can be said that this index is predominantly northern, while the Swarm-derived AE index may be more representative of a global state, since it is based on measurements from both hemispheres. Recently, many novel concepts originated in time series analysis based on information theory have been developed, partly motivated by specific research questions linked to various domains of geosciences, including space physics. Here, we apply information theory approaches (i.e., Hurst exponent and a variety of entropy measures) to analyze the Swarm-derived magnetic indices around intense magnetic storms. We show the applicability of information theory to study the dynamical complexity of the upper atmosphere, through highlighting the temporal transition from the quiet-time to the storm-time magnetosphere, which may prove significant for space weather studies. Our results suggest that the spaceborne indices have the capacity to capture the same dynamics and behaviors, with regard to their informational content, as the traditionally used ground-based ones. A few studies have addressed the question of whether the auroras are symmetric between the northern and southern hemispheres. Therefore, the possibility to have different Swarm-derived AE indices for the northern and southern hemispheres respectively, may provide, under appropriate time series analysis techniques based on information theoretic approaches, an opportunity to further confirm the recent findings on interhemispheric asymmetry. Here, we also provide evidence for interhemispheric energy asymmetry based on the analyses of Swarm-derived auroral indices AE North and AE South.
Countries with future highest exposure to unprecedented climate extremes 
Authors: Spinoni Jonathan , Chiani Leonardo , Dosio Alessandro , Emmerling Johannes , Ghirri Jacopo , Mastropietro Marta , Tavoni Massimo
Published: March 2024

In the last decades, the World experienced an increasing frequency and severity of weather-related extremes. Such events can remarkably affect multiple sectors as food, energy, and biosphere. In the framework of the activities of the ERC project EUNICE, and in order to understand the possible future impacts caused by climate extremes on population and socio-economic indicators, we firstly constructed a global database of climate indicators including eleven hazards (e.g., heatwaves, droughts, rainfall extremes, and windstorms), ranging from 1881 to 2100. For each grid point (0.5°), we provided different metrics as frequency, intensity, and number of unprecedented events at annual scale, dividing the future into five SSPs (plus two including temperature overshoot), and using the bias-adjusted CMIP6-based ISIMIP3b dataset as input. We therefore aggregated the parameters at country-scale - for each hazard - and we focused on the exposure of population and GDP to unprecedented future climate extremes, i.e. events never recorded in the past. We performed the analyses for two 30-year periods (2041-2070 and 2071-2100) and four Global Warming Levels (GWLs from 1.5 °C to 4 °C). Depending on the selected SSP and period, we present a structured ranking of countries that show the highest socioeconomic exposure to single or combined climate impact drivers. In this presentation, we also discuss the cost, in terms of cumulated events, of temperature overshoot above the 1.5 °C level to comply with Paris Agreement's goals. At a later stage, this new set of climate indicators will be also used to quantify the added value of including climate extremes in dedicated damage functions.
Tectonic erosion along a continental subduction-collision zone revealed by compositions and metamorphism of mafic granulite in the Sulu orogen
Authors: Liu Lishuang
Published: March 2024

Subduction erosion present in oceanic subduction zones has been reported recently in continental subduction-collision zones, but the response of the upper plate remains enigmatic. The Dabie-Sulu orogen is considered to have formed by deep northward subduction of the Yangtze Block (YB) beneath the North China Block (NCB). However, the Haiyangsuo complex within the Northern Sulu ultrahigh-pressure (UHP) belt has intriguingly been accepted as Neoarchean–Paleoproterozoic metamorphic basement from the NCB. We examined petrography, mineral chemistry and geochronological data for the Haiyangsuo mafic granulites to decipher their multiperiod metamorphic evolution. The mineral assemblage from the first episode features coarse-grained Grt1 + Cpx1 ± Opx1 ± Amp1 + Pl1 + Ilm that formed under high-temperature (HT) granulite-facies conditions (7.3–8.3 kbar and 830–895 ℃). The second episode produced “red-eye socket” Grt2 + Cpx2 + Pl2 ± Amp2 + Qtz + Rut generated during high-pressure (HP) granulite-facies metamorphism (12.2–17.2 kbar and 800–875 ℃). Grt1 contains high heavy rare earth elements (HREEs) and oxygen isotopes in equilibrium with late Paleoproterozoic metamorphic zircons, while Grt2 has lower HREEs and oxygen isotopes, similar to Triassic metamorphic minerals in the Dabie-Sulu orogen. P-T estimates from pseudosection modeling and geothermobarometry show that Triassic HP granulite-facies metamorphism was followed by rapid decompression and slow cooling; these rocks resemble but mostly differ from the UHP eclogites due to non-UHP conditions. The above characteristics collectively imply that the metamorphic basement from the NCB was subducted to lower crustal to upper mantle depths (50–60 km) while the YB was subducted deeply; thus, tectonic erosion can indeed occur during continental subduction and collision.
Stability of microbial necromass in soil is controlled by necromass chemical composition
Authors: Walrond Sam , Whitaker Jeanette , Peacock Caroline , Ostle Nick
Published: March 2024

Reversing the trend of decreasing soil carbon stocks is important to help mitigate current environmental challenges. Improving knowledge on the mechanisms that control the stabilisation and persistence of soil organic carbon will provide a foundation to tackle the issue. This includes the mechanisms controlling the stability of organomineral associations, considered to be the most persistent pool of soil carbon. Uncertainties remain in how the composition of carbon involved in mineral associations can control the persistence of this soil organic carbon (SOC) pool.With the mineral associated pool being dominated by soil carbon derived from microbial necromass, composition of microbes and their cell components will have a significant impact on organomineral stability. This study aims to investigate whether differences in cell wall composition between fungi, gram-positive and gram-negative bacteria, contribute to contrasting stability of the organominerals synthesised using necromass of these microbial groups.Organominerals composed of ferrihydrite and montmorillonite minerals and three types of necromass were synthesised and tested for their stability. This was done using chemical washes that bring about desorption (NaOH) and oxidation (NaOCl) of the necromass C. Solid fraction C and N were measured before and after chemical wash treatments to determine the extent of organic carbon (OC) destabilisation, and Fourier transform infrared (FTIR) spectroscopy was used to semi-quantitatively assess changes in OC functional groups before and after destabilisation.Results indicate that organominerals containing fungal necromass have greater stability compared to organominerals containing gram-positive and gram-negative bacterial necromass. The most stable fraction within organominerals was C rich and did not comprise N-containing necromass components. The results imply that necromass derived from soil fungi could enhance the persistence of the mineral-associated pool of SOC.
Impact of Hermodice carunculata (Pallas, 1766) (Polychaeta: Amphinomidae) on artisanal fishery: A case study from the Mediterranean Sea
Authors: Mancini Emanuele , Martellucci Riccardo , Marino Sebastiano , Lombardo Bianca Maria , Scacco Umberto , Tiralongo Francesco
Published: March 2024

Invasive species can cause severe economic damages, ecosystem alterations, and can even threat human health. In the global warming scenario, which can act as a driving force for the expansion of thermophilic species, we investigated for the first time the economic damage caused by the invasive bearded fireworm, Hermodice carunculata, to artisanal longline fishery in the Mediterranean Sea. We focused on bottom longline fishery targeting the highly prized white seabream Diplodus sargus, investigating catch composition of the fishing gear and Catch Per Unit Effort (CPUE) of species caught, with particular emphasis on the economic damage caused by the bearded fireworm, H. carunculata, in relation to water temperature. Our results clearly indicated direct and indirect economic damage to fishing activities practiced in the southeastern coast of Sicily (Ionian Sea). Type and extent of the damage caused by the invasive worm (H. carunculata) were discussed in relation to temporal scale and overall yields obtained by this traditional artisanal fishery, and some solutions are proposed. However, the actual situation requires special attention because it is expected to worsen in the context of the global warming future scenarios, such that further studies are urgently needed. 
P-T-t evolution of the Pulkau and Pleißing Nappes, Thaya Window, Lower Austria
Authors: Hauzenberger Christoph , Findl Martin , Skrzypek Etienne , Gallhofer Daniela , Linner Manfred , Fritz Harald
Published: March 2024

Two NW-SE trending profiles across the Pleißing and Pulkau nappes were investigated in detail and 56 samples from the Pernegger trench, 31 samples from the Pulkau and 32 samples from the Thaya valleys recovered. The Pleißing nappe exhibits amphibole-gneiss, metapelite, orthogneiss / metatuffite and marble with the corresponding mineral assemblages of hornblende - mica - feldspar - quartz - titanite - ilmenite; staurolite - garnet - mica ± graphite ± turmaline ± monazite; mica - biotite -epidote -kalifeldspar – quartz - ilmenite ± garnet ± chlorite; and calcite - biotite -mica -quartz -epidote - titanite ± amphibole. Grt-amphibolites, partly retrograded to greenschists, metapelite / phyllonite, and orthogneiss / metatuffite are recognized in the Pulkau nappe with the mineral assemblages amphibole -epidote - chlorite - rutile - ilmenite -quartz - titanite; mica - biotite - garnet - hornblende -quartz -plagioclase -ilmenite - monazite ± staurolite; mica - biotite - chlorite -Kfeldspar -quartz -ilmenite -magnetite ± turmaline.P-T estimates from the Thaya valley profile are 580-620 °C / 0.8-0.9 GPa for the Pleißing nappe and 600-640 °C / ca. 0.5-0.8 GPa for the Pulkau nappe. Two phase garnets occur in some grt-metapelite from the Pleißing nappe. Garnet cores indicate P-T conditions of ca. 550 °C / 0.5 GPa and garnet rims in equilibrium with matrix minerals give ca. 590 °C / 0.9 GPa. P-T estimates along the Pulkau valley are 590-630 °C and 0.8-0.9 GPa for the Pleißing nappe and 540-580 °C / 0.5-0.8 GPa for the Pulkau nappe.U-Pb dating of monazite by LA-ICPMS yielded a metamorphic age of 331 ± 2Ma , similar to the younger monazite age group of Štípská et al. (2015). The Th-U-Pb ages obtained by electron microprobe are slightly younger at 317 ± 6 Ma, which may be related to Pb loss during monazite recrystallization. Zircons from two meta-tuffite samples, one from the Pleißing, the other from the Pulkau nappe yielded concordant ages of 587 ± 8 Ma and 592 ± 8 Ma, respectively, similar to the magmatic age of the Biteš gneiss. The sample from the Pleißing nappe contained in addition a second age group with 620 ± 8 Ma.Based on our geothermobarometric results the Pleißing and Pulkau nappe experienced a nearly identical metamorphic overprint in the northern part of the Thaya window. A slight decrease in metamorphic grade is seen in the southern part of the Pulkau nappe, suggesting a decreasing metamorphic gradient from NE to SW.Štípská, P., Hacker, B. R., Racek, M., Holder, R., Kylander-Clark, A. R. C., Schulmann, K., & Hasalová, P. (2015). Monazite dating of prograde and retrograde P–T–d paths in the Barrovian terrane of the Thaya window, Bohemian Massif. Journal of Petrology, 56(5), 1007-1035.
Enhancing Crop Production and Soil Health: A Dual Approach with Process-Based Modeling and Continuous Soil Health Monitoring in Rainfed and Irrigated Agriculture in Tajikistan
Authors: Visintin Peter , Thier Maximilian , Benedek Cosima , Stoisser Victoria , Konold Oliver , Nolz Reinhard , Mehdi-Schulz Bano , Khudonazarov Faridun , Kassam Shinan , Aminov Sharif , Khojaev Davlatshoh , Khojaev Sharif , Haddad Mira , Akramkhanov Akmal , Strohmeier Stefan
Published: March 2024

Unsustainable agricultural management in Tajikistan's norther Laksh district has caused significant land degradation. Climate change and the related hydrological shifts further disrupt water management, particularly in irrigated systems. The current farming practices such as inefficient furrow irrigation with saline water and conventional soil cultivation hamper the soil's infiltration capacity, intensify runoff, and eventually degrade various ecosystem functions including crop production. Advanced Information and Communications Technology (ICT) based decision support systems e.g. for irrigation scheduling are under development; however, key soil parameters, including soil hydraulic properties, are largely unknown. As part of Caritas Switzerland's Weather, Water, Climate Services (WWCS) initiative, jointly funded with the Swiss Agency for Development and Cooperation, this research combines monitoring and modeling based approaches to investigate the local soil-water-crop processes and to eventually enhance the according management, functionality and productivity in both irrigated and rainfed agricultural systems. Field-assessed soil physical, chemical and biological properties serve as the benchmarks for establishing a Soil Health Index and crafting process-based modeling scenarios. In irrigated systems a surrogate modeling approach is employed combining Hydrus 2D and its ‘Furrow’ submodule with AquaCrop. The establishment of the Soil Health Index is currently underway, with successive monitoring aimed at evaluating changes in soil health over time in relation to selected conservation practices. The assessment of soil hydraulic and physical properties has provided key parameters, including hydraulic conductivity, field capacity and permanent wilting point. Those parameters and knowledge can be directly integrated into ICT applications (e.g. weather-based irrigation advisory services) that optimize the use of scarce inputs (water, fertilizer, etc) within sustainable production systems; and simultaneously enhancing resilience to short term weather changes and longer-term climate change.
Spectral properties of mesoscale fluctuations in ICMEs
Authors: Good Simon , Jylhä Anna-Sofia , Kilpua Emilia , Makelä Timo , Ruohotie Julia , Soljento Juska , Suihkonen Jose
Published: March 2024

ICME plasma fluctuates across a broad range of scales, with fluctuations that display many similar spectral properties to other kinds of solar wind. These fluctuations, which may represent turbulence, waves or structures in the plasma, are not well understood holistically in the ICME context. Using data from Parker Solar Probe and Solar Orbiter, we present analysis of magnetic field spectra from ICME flux ropes at scales between the flux rope radial width and the magnetic field correlation length. The presence of the global flux rope causes significant steepening of the spectra at these scales, with spectral indices as steep as -2. The underlying fluctuations, in contrast, show much shallower spectral slopes. Key properties of the fluctuations are determined and compared to those found at the same scales in other solar wind types. Interpretations of the fluctuations as an energy source for turbulence at smaller scales or as mesoscale ICME substructure are discussed.
Cryosphere tipping elements decisive for tipping risks and cascading effects in the Earth system
Authors: Rosser Jonathan , Winkelmann Ricarda , Wunderling Nico
Published: March 2024

The Earth's climate system is a complex system that includes key components such as the Arctic Summer Sea Ice or the El Niño Southern Oscillation as well as climate tipping elements like the continental-scale ice sheets or the Amazon rainforest. Crossing warming thresholds of these elements can lead to a qualitatively different climate state, endangering the stability of human societies. Particularly, the cryosphere elements are vulnerable at current levels of global warming (1.2°C) while also having long response times and large structural uncertainties. Investigating a network of interacting Earth system components using an established conceptual model, we systematically assess which uncertainties of key Earth system component have the largest impacts on tipping risks. We find that the cryosphere tipping elements (the Greenland and the West Antarctica ice sheets) are most decisive for tipping risks and cascading effects within our model. At a global warming level of 1.5°C, neglecting the large cryosphere tipping elements can reduce the mean number of disintegrated Earth system components by as much as 56%. This is concerning as overshooting 1.5°C of global warming is fast becoming inevitable, while current state-of-the-art IPCC-type global circulation models do not (yet) include dynamic ice sheets. Our results suggest that urgent integrated Earth system model development and Earth observation efforts including the large polar ice sheets are necessary and a precautionary measure of meeting stringent climate targets is crucial to limit tipping risks.
Effects of Width Ratio and Offtake Angle on the Morphological Characteristics of an Offtake Channel
Authors: Saiduzzaman Md , Zobeyer A. T. M. Hasan
Published: March 2024

River channel bifurcations play a crucial role in shaping fluvial systems, yet their morphological behavior remains a significant challenge in water resource engineering.  The present study is an attempt to investigate the effects of different off-taking angles (15, 30, 45, 60, 75, and 90 degrees) and width ratios (0.2, 0.4, 0.6, and 0.8) on the morphological behavior of offtake channels through a numerical modeling approach using SRH-2D. To comprehensively understand the morphological behavior of the offtake channel, the discharge ratio and the size of the flow separation area were also analyzed.  The result shows that the discharge ratio increases with an increase of offtake angle up to 75 degrees and the length of the separation zone decreases with the increase of offtake angle for any width ratio. The morphological analysis showed the presence of deposition dominance along the offtake channel for all offtake angle and width ratios. Erosion-deposition patterns varied along different sections of the offtake channel depending on the width ratio. These findings significantly contribute to the understanding of morphological characteristics in offtake channels of river channel bifurcations.
Climate damage projections beyond annual temperature
Authors: Kikstra Jarmo , Waidelich Paul , Batibeniz Fulden , Rising James , Seneviratne Sonia
Published: March 2024

Projections of economic damages from climate change are key for evaluating the benefits of climate mitigation and informing discussions around adaptation needs. So far, global and country-level top-down assessments of GDP damages have focused on annual mean temperature changes and annual precipitation. Recent backward-looking studies have identified further impacts of variability and extremes in precipitation and temperatures on income growth.Here, we examine GDP impacts and uncertainties under different global warming levels by combining empirical dose-response functions for temperature variability, rainfall deviations, and extreme precipitation with climate projections of 33 CMIP6 models. The main contribution of this work is to understand the projected relative contributions of multiple climate variables under many possible future climates.We find that at a +3°C global warming level, global average losses reach 10% of GDP, with worst effects (up to 17%) in poorer, low-latitude countries. Relative to annual temperature damages, which find to seemingly capture heat wave impacts, the additional GDP impacts of projecting variability and extremes are relatively small and dominated by inter-annual variability, especially in lower latitudes. However, accounting for variability and extremes when estimating the temperature dose-response function still raises global GDP losses by nearly 2%-pts and exacerbates tail risks for economic growth.Our results call for region-specific risk assessments and complementary research into climatic extremes not considered here, including their indirect effects on temperature dose-response functions. Additionally, it will be very important to further the work on understanding historical and future persistence and adaptive capacities for these different impact channels.
Laser based observations of key inorganics (LOKI) on-board the UK research aircraft
Authors: Young Stuart , Edwards Pete , Temple Loren , Vallow Jake , Rogers Sam , Grant Eve , Rollins Andrew
Published: March 2024

The UK research aircraft is being equipped with flux capable measurements of NO, NO2, SO2 and O3 in the Laser based Observation of Key Inorganics (LOKI) instrument rack. All instruments within the rack are being made in-house.This presentation will discuss the aspects of the new instrumentation as well as the sample inlets used that allow high time resolution (10 Hz), high precision measurements to be made over the working envelope of the aircraft.The need for this improvement in the gas sensing capabilities on board is driven by a number of factors: the increasing desire to use flux measurements to calculate emission rates and identify sources, smaller changes in concentration being of interest (SO2 depletion in clouds) as well as reductions in absolute ambient concentrations of some of these species below the detection limits of currently deployed instrumentation.Laser Induced Fluorescence is used for NO (Rollins et al., 2020), NO2 (converted to NO), SO2 (Rollins et al., 2016), with O3 being monitored using Broadband Cavity Enhanced Absorption Spectroscopy (BBCEAS) (Hannun et al., 2020).
Trans-dimensional Mt. Etna P-wave anisotropic seismic imaging
Authors: Del Piccolo Gianmarco , Lo Bue Rosalia , VanderBeek Brandon Paul , Faccenda Manuele , Cocina Ornella , Firetto Carlino Marco , Giampiccolo Elisabetta , Morelli Andrea , Byrnes Joseph
Published: March 2024

Trans-dimensional inference identifies a class of methods for inverse problems where the number of free parameters is not fixed. In seismic imaging these methods are applied to let the data, and any prior information, decide the complexity of the models and how the inferred fields partition the inversion domains. Monte Carlo trans-dimensional inference is performed implementing the reversible-jump Markov chain Monte Carlo (rjMcMC) algorithm; the nature of Monte Carlo exploration allows the algorithm to be completely non-linear, to explore multiple possibilities among models with different dimensions and meshes and to extensively investigate the under-determined nature of the tomographic problems, showing quantitative evidence for the limitations in the data-sets used. Implementations of this method overcome the main limitations of traditional linearized solvers: the arbitrariness in the selection of the regularization parameters, the linearized iterative approach and in general the collapse of the information behind the solution into a unique inferred model.We present applications of the rjMcMC algorithm to anisotropic seismic imaging of Mt. Etna with P-waves. Mt. Etna is one of the most active and monitored volcanoes in the world, typically investigated under the assumption of isotropic seismic speeds. However, since body waves manifest strong sensitivity to seismic anisotropy, we parametrize a multi-fields inversion to account for the directional dependence in the seismic velocities. Anisotropy increases the ill-condition of the tomographic problem and the consequences of the under-determination become more relevant. When multiple seismic fields are investigated, such as seismic speeds and anisotropy, the data-sets used may not be able to independently resolve them, resulting in non-independent estimates and corresponding trade-offs. Monte Carlo exploration allows for the evaluation of the robustness of seismic anomalies and anisotropic patterns, as well as the trade-offs between isotropic and anisotropic perturbations, key features for the interpretation of tomographic models in volcanic environments. The approach is completely non-linear, free of any explicit regularization and it keeps the computational time feasible, even for large data-sets.
Comprehensive Flood Early Warning Systems: From Modelling to Policy Making Perspectives
Authors: Behzadian Kourosh , Piadeh Farzad , Razavi Saman , Campos Luiza , Gheibi Mohamad , Chen Albert
Published: March 2024

Todays, early warning systems are widely applied in real-time flood forecasting operations as valuable non-structural tools for mitigating the impacts of floods [1].  Although many research works have perfectly could review recent advances in this era, current review papers tend to focus narrowly on specific perspectives, such as water quantity or quality [2]. Therefore, there is a pressing need for a more comprehensive and multi-disciplinary approach that not only explores various potential aspects of flood early warning system applications but also reveals the interconnections between these aspects [3]. This paper aims to bridge this gap by mapping out diverse applications and presenting significant trends, past initiatives, and future directions across a wide range of domains. By adopting such an approach, our goal is to provide a more holistic understanding of flood early warning systems and pave the way for further exploration in this critical field.This papers, as state-of-art, suggests that a comprehensive framework may include all these aspects to meet all desired task and also ensure that all aspect of sustainability, reliability, resiliency, and accuracy have been fulfilled: (1) using recent input data extracted from both well known resources such as ground station and satellite stations, and novel but local resources i.e. IoT-based remote sensing, drones, USV and even social media and qualitative data; (2) Advance modelling with focusing on hybrid deep learning and physics-informed neural networks for different type of flood i.e. fluvial, pluvial or surface run-off. Also, application of data mining for data screening still have required more attention; (3) Adding concept of water quality as target and outputs of EWS especially with focusing on emerging pollutants, biological pollutants and micro-plastics; (4) Interconnection of EWS with optimisation techniques, decision support systems, and multi criteria decision making processes; (5) Appropriate sensitivity/uncertainty analysis especially due to requirement for developing dynamic retrainable or self-trainable EWS; (6) Application of post modelling tools including virtual/augmented/mixed reality or digital twin to including stakeholder engagement.References[1] Piadeh, F., Behzadian, K., Chen, A.S., Kapelan, Z., Rizzuto, J., Campos, L.C. (2023). Enhancing urban flood forecasting in drainage systems using dynamic ensemble-based data mining. Water Research, 247, p.120791.[2] Piadeh, F., Behzadian, K., Chen, A.S., Campos, L.C., Rizzuto, J., Kapelan, Z. (2023). Event-based decision support algorithm for real-time flood forecasting in urban drainage systems using machine learning modelling. Environmental Modelling & Software, 167, p.105772.[3]  Ringo, J., Sabai, S., Mahenge, A. (2024). Performance of early warning systems in mitigating flood effects. A review. Journal of African Earth Sciences, 210, p.105134.
Global Validation of the Data-Assimilative VERB-3D code
Authors: García Peñaranda Marina , Shprits Yuri , Castillo Tibocha Angélica M. , Drozdov Alexander , Mátyás Szabó-Roberts Matyas
Published: March 2024

Radiation belt electron dynamics show high variability in space and time during geomagnetically active periods, which could potentially damage the satellites though deep dielectric and surface charging. In the past years, numerous physics-based models have been developed to describe the evolution of phase space density in the radiation belts, however they are subject to uncertainties and errors in the initial and boundary conditions. Data assimilation provides to be a reliable technique for blending satellite data and the output of physics-based models, creating a more reliable reconstruction with all the available information about the environment.We present a preliminary global validation of the data-assimilative VERB-3D code for a geomagnetic event in September 2017. We assimilated Arase measurements into the VERB-3D code via a split-operator Kalman Filter, and validated the results against measurements obtained from the RBSP satellites.  The results provide very valuable insights into the accuracy and performance of the data assimilative model and its capability to replicate the radiation belt environment, showing the great potential for data assimilation techniques in space weather applications.
Satellite-based remote sensing and multitemporal modeling approach for mapping soil erosion hotspots in global mountain grasslands under climate change
Authors: Straffelini Eugenio , Luo Jian , Tarolli Paolo
Published: March 2024

Mountain grasslands play a pivotal role in delivering both economic and cultural ecosystem services, including food production, carbon sequestration, the provision of clean water, and preserving local traditions. However, these ecosystems are facing increasing threats from climate change around the world. Among the main challenges is the intensification of extreme precipitation events. They can aggravate the process of soil erosion and trigger landslides in mountain grasslands, with possible negative consequences on both ecosystems and human activities. However, the high variability of these ecosystems, as well as their wide distribution, makes it complex to adequately map their locations and investigate possible soil erosion hotspots, especially under future scenarios with varied rainfall regimes. In this context, the use of remote sensing technologies and modeling approach could open new frontiers to investigate critical areas and therefore guide mitigation solutions. The satellite Earth Observation (EO) through international space missions, coupled with cloud-based data analysis platforms like Google Earth Engine (GGE), facilitates ecosystem mapping at a resolution and frequency previously inaccessible. Furthermore, the utilization of multi-temporal models for potential soil erosion analysis in present and future scenarios can enhance our understanding of erosion dynamics attributed to climate change. In this research, we first map at high resolution the global mountain grasslands distribution taking advantage of Sentinel-based EO’s products. In such locations, we evaluate the multi-temporal soil erosion dynamics caused by water employing diverse climate scenarios (RUSLE model; 2015 vs. 2070-RCP8.5). Our findings indicate a potential global escalation in soil erosion within mountain grasslands, notably in South America and Africa, alongside identifiable localized hotspots. Remote sensing-based research paired with a modeling approach aimed at mapping critical areas and analyzing environmental challenges in ecosystems is therefore imperative. Such investigations not only delineate vulnerable regions but also guide targeted solutions crucial for safeguarding these ecosystems and their ecosystem services in the face of climate change.
Can we understand the variability in flood-induced displacement using process-based global flood modelling? 
Authors: Zimmermann Sandra , Frieler Katja , Schewe Jacob ,   ISIMIP Team
Published: March 2024

Every year, disasters force millions of people around the world to leave their homes. Disaster-induced displacement often leads to humanitarian hardship and imposes substantial costs on vulnerable, low-income societies in the Global South. With anthropogenic climate change increasing the intensity and number of extreme events in many regions globally, understanding and projecting disaster-induced displacement becomes increasingly important. Floods are among the main causes of disaster-induced displacements. However, the causes of variability in flood displacement over time and space are not well understood. Therefore, it is not known to what extent climate change has already affected displacement in the past, making it difficult to produce reliable estimates of future displacement risk.In our study, we address the question of how much of the observed variability can be explained on the basis of process-based flood hazard modeling. We use the output of state-of-the-art global hydrological models forced with observational climate and direct human forcings to derive flood extents from the global hydrodynamic model CaMa-Flood. We first assess how well modelled flood hazards can explain annual variations in past displacement as recorded by the Internal Displacement Monitoring Center at a global as well as national scale, before also accounting for different vulnerabilities of communities by applying spatially-disaggregated vulnerability factors derived from comparing the simulated number of people affected by flooding to observational displacement data. We hence provide a comprehensive assessment of the explanatory power of the process-based fluvial flood hazard component concerning displacement.
Subsoil management as tool for climate-change adapted agriculture
Authors: Amelung Wulf , Seidel Sabine , Schweitzer Kathlin , Baumecker Michael , Gocke Martina , Bauke Sara , Schmittmann Oliver
Published: March 2024

Agricultural production in Central Europe increasingly suffers from extreme drought events. Improving root access to nutrient and water resources in the subsoil below the plow layer is a potential option to maintain productivity during dry summers. Here, we tested a strip-wise subsoil amelioration system that combines subsoil loosening with injections of 50 t per hectare fresh weight organic matter incorporation into the subsoil (biowaste or green waste compost) and compared it with a treatment comprising only subsoil loosening or a non-ameliorated control. Randomized block design field experiments were conducted on Luvisols and Retisols with an argic (Bt) horizon and rotations of spring barley and winter wheat as well as of rye and maize, respectively. We then monitored yields, protein contents as well as physical and chemical soil properties including changes in stable isotope composition as indicators for plant stress and nutrient uptake. We found that subsoil amelioration has the potential to prevent yield losses of up to 20% for cereals and up to 50% for maize after biowaste compost injection, particularly in dry summers, i.e., depending on weather conditions. These benefits were accompanied by a decrease in soil bulk density at the depth of compost incorporation when biowaste compost was used, but not when green waste compost had been incorporated. In contrast, nutrient stocks, nutrient availability, and microbial biomass were not consistently affected by the subsoil amelioration, but root growth was. Differences in crop development could not be explained by any single soil parameter, suggesting that it was rather a combined effect of loosened subsoil and better supply of subsoil resources that increased subsoil root length density and subsequent better crop performance when the summer was dry.
A 20-meter root-zone soil moisture dataset using Earth Observations and water balance modelling
Authors: Kittel Cecile M.M. , Guzinski Radoslaw M. , Bojesen Mikkel H.
Published: March 2024

At the interface of the surface energy balance and land surface hydrology, soil moisture is a key descriptor for hydrology, ecosystem dynamics and climate variables. Monitoring of soil moisture is of high value in multiple contexts, including water resources management through irrigation detection and quantification, and in land management and climate initiatives. In Denmark, drained organic low-lying soils represent 7% of agricultural land but are responsible for around 50% of the greenhouse gas emissions from agriculture. Soil moisture monitoring is key to prioritizing the decommissioning of relevant farmland. Soil moisture can be observed from space with radar or radiometer instruments; however, applications are often limited by the sensor penetration depth, which restricts the vertical spatial resolution to the top few centimeters of the soil. Spatial sampling is often in the order of kilometers, and too coarse for field-scale screening.In this study, we propose to use the widely applied FAO-56 soil water balance model for crop evapotranspiration (ET) estimates and use it to estimate soil moisture in the root zone through reverse modelling. Using EO estimates of ET at high resolution derived from Sentinel-2 optical images, downscaled Sentinel-3 thermal images, and the TSEB (Two-Source Energy Balance) ET model, we derive a map of soil moisture in Denmark at 20 m daily resolution. Precipitation is obtained from ECMWF Era-5 and the OpenLand soil texture and characteristics dataset is used to parameterize the soil column. Landuse information at parcel scale from the Danish Agricultural Agency is used to estimate the root zone depth along with time series of Leaf Area Index. The approach is based on optical observations which have limited applicability in cloudy regions and winter months. We therefore apply gap filling using temporal interpolation of the ET time series or assumptions on soil moisture conditions to obtain the final decadal and monthly soil moisture time series.The map is validated against probe measurements of soil moisture at 21 different sites across Denmark. Overall, the RMSE is around 5% m3/m3 and spatio-temporal patterns are well captured. The main limitations can be attributed to the soil parameterization as well as uncertainties in the coarser climate forcing. This study presents a unique dataset at national scale using publicly available datasets and combining Earth Observations with physical and conceptual modelling to obtain a key hydrological and biophysical parameter. The approach can be extended to most farm and grasslands and can be adjusted, where more precise local parameterization is available. The dataset as presented here, is used to inform a screening and management tool for the Danish Environmental Protection Agency to evaluate the impact of decommissioning low-lying farmlands, and to support research efforts in quantifying nitrogen dioxide emissions from poorly drained soils.