bluuebunny/crossref_metadata_2025 huggingface dataset:
Geodynamic controls on sediment-hosted lead-zinc deposits in continental rifts
Authors: Glerum Anne C. , Brune Sascha , Magnall Joseph M. , Weis Philipp , Gleeson Sarah A.
Published: March 2024

The growing global demand for metal resources requires new high-grade ore deposit discoveries. Known large sediment-hosted clastic-dominated base metal deposits predominantly occur in failed continental rifts and the passive margins of successful rifts. Understanding the large-scale geodynamic controls on rift-related mineralizing processes occurring on much smaller spatial and temporal scales can thus help identify new areas for exploration.We numerically model 2D rift systems from inception to break-up with the geodynamic code ASPECT (Kronbichler et al., 2012; Heister et al., 2017) coupled to the landscape evolution model FastScape (Braun and Willett, 2013; Neuharth et al., 2022). With ~300-m resolution simulations, we investigate how rift type and the efficiency of sedimentary processes affect the formation of potential metal source and host rock domains, identified by their lithology and temperature. We subsequently analyse the optimal alignment of these domains where metals are respectively leached and deposited  with faulting events providing potential fluid pathways between them (e.g., Rodríguez et al., 2021). For favourable co-occurrences of source, pathway and host, we identify the tectonic conditions that predict the largest clastic-dominated lead-zinc deposits.We show that the largest potential for metal endowment is expected in narrow asymmetric rifts at a distance of several tens of kilometres to the shore (Glerum et al., 2023). Characterized by rift migration, these rifts generate a wide and a narrow conjugate margin. On the narrow margin, the long-lived border fault accommodates a thick submarine package of sediments, including deep permeable continental sediments and shallower layers of organic-rich sediments. Elevated temperatures from continued thinning could lead to fluids leaching metals from the permeable sediments. Both the border fault and later synthetic faults can provide fluid pathways from the source to the shallow host rock in potential short-lived mineralisation events. In wide rifts with rift migration, these favourable configurations occur less frequently and less potential source rock is produced, limiting potential metal endowment. In simulations of narrow symmetric rifts, the potential for ore formation is low. Based on these insights, exploration programs should prioritize identifying exhumed ancient narrow margins formed in asymmetric rift systems. Braun and Willett 2013. Geomorphology 180–181. 10.1016/j.geomorph.2012.10.008.Glerum et al. preprint. EGUsphere 1-40. 10.5194/egusphere-2023-2518.Heister et al. 2017. Geophys. J. Int. 210 (2): 833–51. 10.1093/gji/ggx195.Kronbichler et al. 2012. Geophys. J. Int. 191: 12–29. 10.1111/j.1365-246X.2012.05609.x.Neuharth et al. 2022. Tectonics 41 (3): e2021TC007166. 10.1029/2021TC007166.Rodríguez et al. 2021. Gcubed 22: 10.1029/2020GC009453.
Economic growth and projected effects of air pollution on human health over Europe
Authors: Kushta Jonilda , Giannakis Elias , Violaris Angelos , Paisi Niki , Lelieveld Jos
Published: March 2024

In this work we analyze the effects of inter-industry linkages on air pollution and human health associated with the expected growth of economic sectors towards 2030. A combined toolbox consisting of environmentally-extended input-output models, a regional atmospheric chemistry model (WRF-Chem) and a global exposure mortality model (GEMM) is deployed to conduct an economy-wide assessment of air pollution and attributable mortality in the European Union (EU). Preliminary evaluation of the atmospheric model reveals the significance of the accurate representation of residential combustion activities and carbonaceous aerosols, especially under a differential toxicity framework. Direct and indirect air pollution intensities of the economic sectors included in the study exhibit significant differences across EU countries. The highest pollutant intensity per unit of economic output, is created by shipping and reaches more than 20 tonnes/million Euro for NOx. This valus is 4-5 times higher than the respective intensity for industry and power generation. However, industry and power generation lead to the largest (direct and indirect) increases in PM2.5 concentrations in absolute terms. The most affected areas, in terms of surface PM2.4 levels, influenced by substantial effects of the projected industrial growth, are found in Germany and northern Italy. While the greatest impacts of the energy sector’s expansion will occur in central Europe, Finland, Estonia and major urban areas in southern Europe. Subsequently, the mortality burden of air pollution towards 2030 is primarily localized in the central and northern parts of Europe. These integrated analyses can help focus tailored mitigation efforts in sectors with significant (direct and indirect) emission intensities, rather than those with relatively low emission intensities and substantial economic contributions.
Role of Ocean Memory in Subpolar North Atlantic Decadal Variability
Authors: Khatri Hemant , Williams Richard , Woollings Tim , Smith Doug
Published: March 2024

The decadal variability in the subpolar North Atlantic Ocean heat content is significantly influenced by the atmosphere. The impact of seasonal-annual atmospheric perturbations lasts for many years in the oceans due to the ocean's long memory. The anomalous air-sea heat fluxes and winds associated with atmospheric perturbations first rapidly modify upper ocean temperatures, initiating a short-term or local ocean response. Subsequently, these modifications can alter meridional heat transport rates, leading to anomalous heat convergence persisting for several years—a long-term or far-field ocean response—in the subpolar ocean (Khatri et al., 2022, Geophys Res Lett).We propose a novel technique that incorporates these two ocean responses to evaluate ocean memory and examine its role in driving decadal ocean variability. Here, we combine heat budget analysis with linear response theory to examine how the North Atlantic Oscillation (NAO), which captures about 40% of atmospheric variability, controls the decadal variability in upper ocean temperatures and quantify the associated ocean memory. Utilising CMIP6 climate model outputs and observations, our estimations suggest ocean memory for the subpolar North Atlantic to be between 10 to 20 years. Furthermore, we find that the NAO strongly influences long-term ocean variability, explaining 30% to 40% of subpolar ocean heat content variability on decadal timescales. Specifically, the impact of seasonal atmospheric events on the ocean persists for more than a decade through a combination of local and far-field ocean responses. The proposed ocean memory-based framework, integrating local and far-field ocean effects into a single metric, can be utilised to analyse how relatively short-timescale atmospheric variability drives changes in the ocean state over decadal timescales.
Concealed hydrothermal alteration zones provide mechanical weaknesses within lava domes
Authors: Troll Valentin , Walter Thomas R. , Darmawan Herlan , Heap Michael J. , Harnett Claire E. , Deegan Frances M. , Seraphine Nadhirah , Geiger Harri , Müller Daniel
Published: March 2024

Catastrophic lava dome collapse is considered an unpredictable volcanic hazard because the physical properties, stress conditions, and internal structure of lava domes are not well understood. To better explain the locations of recent dome instability events at Merapi volcano, Indonesia (1), we combined geochemical and mineralogical analyses, rock physical property measurements, drone-based photogrammetry, and numerical modelling. We show that a linear fissure and a horseshoe-shaped alteration zone that formed in 2014 was buried by lava extrusion in 2018. The linear fissure controlled the location of the new lava dome, while the horseshoe shaped zone influenced subsequent instability. Geomechanical, mineralogical, and geochemical data suggest that such alteration zones are characterised by mechanically weak, hydrothermally altered materials, and we show that the new lava dome is collapsing along this now-hidden horseshoe shaped and comparatively weak alteration zone (2). To derive an improved general understanding of this phenomenon, we then combined recent laboratory data for the mechanical behaviour of dome rocks with discrete element method models to show that the presence of weak zones within lava domes increases instability, which is exacerbated when the size of the zone increases or when the zone is positioned off-centre (3). Our results highlight that improved understanding of dome architecture and compositional variations due to hydrothermal alteration within domes is essential for assessing hazards associated with dome and edifice failure at volcanoes worldwide.
Regional coupled and decoupled day-night compound hot extremes over the mid-lower reaches of the Yangtze River: characteristics and mechanisms
Authors: Guo Yixuan , Fu Zuntao
Published: March 2024

Hot extremes impose severe effects on human health and the ecosystem, especially when high-temperature extremes sequentially occur in both daytime and nighttime within 1 day, known as Compound Hot Extremes (CHEs). Although a number of studies have focused on independent hot extremes, not enough work is devoted to compound ones, not to mention the coupling strength in covariations between the two variables (daytime and nighttime temperature: Tmax and Tmin) over a given region. The instantaneous coupling strength can be derived by Dynamical System (DS) approach from covariations between Tmax and Tmin over a given region, and used to classify CHEs into coupled and decoupled types. Results show that coupled CHEs tend to be more intense with prolonged duration and extensive spatial extent compared with decoupled CHEs. Also, the mechanisms behind these two types of CHEs are largely different. Coupled CHEs are accompanied by a significant intensification and westward extension of the western North Pacific subtropical high (WNPSH), and the extremely high-temperature is mainly caused by receiving more solar radiation under the corresponding anticyclone. It is found that barotropic structure, weak jet stream and developing La Niña are conducive to the enhancement and persistence of WNPSH, in favor of the occurrence of long-lasting CHEs. Decoupled CHEs are associated with strong sea-land breeze (SLB), whose diurnal cycle could weaken the persistent large-scale circulation and suppress covariations between Tmax and Tmin. This kind of decoupled hot extremes are attributed to the combined effect of receiving more solar radiation during the day and trapping more long-wave radiation at night, where moisture and cloud cover play an important role.
A near-global multiyear climate data record of the fine-mode and coarse-mode components of atmospheric pure-dust
Authors: Proestakis Emmanouil , Gkikas Antonis , Georgiou Thanasis , Kampouri Anna , Drakaki Eleni , Ryder Claire L. , Marenco Franco , Marinou Eleni , Amiridis Vassilis
Published: March 2024

Dust aerosols play a key role in the Earth’s radiation budget, in climate system, environmental conditions, and human health. However, the complex role of dust depends not only on the physical and chemical properties, but in addition to the particle size distribution, spanning from less than 0.1 μm to more than 100 μm in diameter. Larger mineral dust particles are more efficiently removed through dry deposition close to the source regions and act more efficiently as CCN and/or IN than fine-mode dust particles, whereas fine dust particles are more prominent to long-range transport, resulting to degradation of air-quality and induced negative disorders on human health.Here, a new four-dimensional, multiyear, and near-global climate data record of the submicrometer and supermicrometer (in terms of diameter) components of atmospheric pure-dust, is presented. The separation of the two modes of dust is based on a combination of (1) the total pure-dust product provided by the ESA-LIVAS database and (2) the supermicrometer-mode component of pure-dust provided by the first-step of the two-step POLIPHON technique, developed in the framework of EARLINET. The submicrometer-mode component of pure-dust is extracted as the residual between the LIVAS total pure-dust and the supermicrometer-mode component of pure-dust. The decoupling scheme is applied to CALIPSO observations at 532nm. The final products consist of the submicrometer-mode and supermicrometer-mode of atmospheric pure-dust, of quality-assured profiles of backscatter coefficient at 532nm, extinction coefficient at 532nm, and mass concentration. The datasets are established primarily with the original L2 horizontal (5 km) and vertical (60 m) resolution of CALIOP along the CALIPSO orbit-path, and secondly in averaged profiles of seasonal-temporal resolution, 1o×1o spatial resolution, and with the original vertical resolution of CALIPSO, between 70oS and 70oN and covering more than 15-years of Earth Observation (06/2006-12/2021).The climate data record is unique with respect to a wide range of potential applications, including climatological, time-series, and trend analysis over extensive geographical domains and temporal periods, validation of atmospheric dust models and reanalysis datasets, assimilation activities, and investigation of the role of airborne dust on radiation and air quality.
Demonstrating a large UAV for Antarctic environmental science
Authors: Jordan Tom , Robinson Carl
Published: March 2024

Airborne survey is one of the most important observational techniques in environmental science. This is especially true in polar settings where access is challenging and observational requirements, such as ice sounding radar, in situ study of turbulent atmospheric processes, cloud cover, or requirements for high resolution potential field data, limit use of satellite data. Although critical, airborne survey using traditional platforms, such as the versatile twin otter aircraft operated by the British Antarctic Survey (BAS), come with a relatively high logistical, financial, and environmental (CO2) footprint. Larger UAV’s offer an alternative, but as yet un-realised, lower impact platform to deliver the same, if not more scientific data.Through the Innovate UK SWARM project BAS is collaborating with Windracers to trial their large (10 m wing span) Ultra UAV as a platform for environmental science. Making use of the large (700 L/max 100 kg), easily accessible payload bay and a series of interchangeable payload floors this trial will be carried out in February/March 2023. The science payloads will include: Atmospheric (turbulence probe), environmental (hyperspectral and visual cameras), cryosphere (600-900 MHz accumulation radar), and potential field geophysics (gravity/magnetic sensors). The missions, between 10 and 330 km long, will be flown beyond visual line of sight (BVLOS) of the operator using the Distributed Avionics autopilot, including take-off and landing, which will be overseen by an in-field safety pilot.Here we present the first results of this trial, including our experience integrating BVLOS UAV operations with traditional aircraft in an Antarctic context and initial results and lessons learned from the four trailed instrument suites. Our demonstration will be an important milestone in the transition to widespread use of larger UAVs for environmental science. We will discuss how the reduced environmental and logistical impact can open up new opportunities in Antarctic and beyond.
A novel framework for the selection of spectral input to pixel-based river discharge estimation model using Sentinel-2 imagery
Authors: Tayebi-Alashti Amirhossein , Danesh-Yazdi Mohammad
Published: March 2024

While access to discharge data is key to hydrologic studies, it is a serious obstacle in ungauged basins. Currently, Sentinel-2 imagery at high spatiotemporal resolution offers a unique opportunity to infer the relation between pixel-based discharge rate and surface reflectance. One promising approach in this respect has been to find the complex relationship between river discharge and the spectral ratio between two benchmark pixels, namely the wet and dry pixels, whose dynamics resembles river discharge variation. However, this has been challenging due to the adverse impact of soil moisture and mixed land cover on the spectral behavior of the dry pixel. The selection of the wet pixel must also guarantee sufficient sensitivity of its spectral response to water depth fluctuations. To tackle the above issues, in this study, we developed a novel framework that automatizes the selection of the wet and dry pixels by using Sentinel-2 imagery. We also introduced the Normalized Difference Discharge Index (NDDI), as the best band combination, to predict river discharge. We used linear regression with leave-one-out cross-validation as the prediction model, which leverages limited satellite data due to the cloud cover. By implementing the developed framework at multiple gauged points across the continental United States, the best location of the dry pixel was consistently found in urban pixels whose longwave reflectance fall within a certain range. By analyzing the pixel-wised correlation coefficient between surface reflectance at NIR band and river discharge across the studied river widths, we found that the best wet pixels are located along river banks with shallow water depth. These pixels were characterized by the average reflectance higher than the 98th percentile in the green band. Finally, by testing over 4000 band combinations as input to the river discharge prediction model, we found that the normalized difference between B11 and B4 for the wet pixel, as well as the B11 ratioing between the dry and wet pixels yielded the most accurate predictions with R2 = 0.88 and R2 = 0.73, respectively.
Efficiency of Biological Carbon Pump: Insights from Compound-Specific Amino Acid δ15N
Authors: Li Chen , Jian Zhimin , Dang Haowen
Published: March 2024

As a vital component of the global carbon cycle, the ocean’s biological carbon pump determines the amount of carbon fixed by primary production in the surface waters. The efficiency of this biological pump is closely interconnected with the nitrogen cycle, which regulates nutrient inventory and primary productivity rates. Additionally, the structure of the upper ocean ecosystem influences the efficiency of the biological pump by determining how much fixed carbon is exported to the deep ocean. Compound-specific nitrogen isotope (δ15NAA) is a novel proxy that could provide valuable insights into both aspects of these questions. The δ15NAA could unravel isotopic information of source nitrogen and show δ15N changes associated with trophic processes. This study generates sedimentary δ15NAA, as well as bulk sediment δ15N and organic δ15N records from a western equatorial Pacific site (MD10-3340) covering the last 140 kyr. Our results demonstrate an overall agreement among three proxies, all indicating distinct precessional variations in source nitrate δ15N and potential changes in nutrient inventory. More importantly, the δ15NAA signatures suggest an inverse relationship between animal trophic activity in the surface water and the degradation of organic matter precipitating through the water column. Higher ecosystem trophic position is found during glacial periods, accompanied by inactive organic matter recycling, which implies a greater potential for carbon burial in deep reservoirs. Together, we suggest that the δ15NAAsignatures can provide a detailed picture of carbon cycle coupled with nitrogen cycle.
GA-OGS-ARSO Transfrontier CE3RN AdriaArray Seismicity Experiment (GOAT-CASE): results of the first year of data collection and analysis
Authors: Pesaresi Damiano , Horn Nikolaus , Pahor Jurij
Published: March 2024

GeoSphere Austria (GA, formerly ZAMG), the Italian National Institute of Oceanography and Applied Geophysics (OGS) and the Slovenian Environment Agency (ARSO) are the agencies dedicated to real-time seismological monitoring of Austria, north-eastern Italy and Slovenia, in cooperation with the respective civil protection authorities. In 2014, GA (then ZAMG), OGS and ARSO founded the “Central and Eastern Europe Earthquake Research Network” (CE3RN, http://www.ce3rn.eu/) to 1) formally establish the cross-border network, 2) define the rules of conduct for the management, improvement, extension and expansion of the network, 3) improve seismological research in the region and 4) support civil protection activities. As part of CE3RN, GA, OGS and ARSO have adoptd the “Antelope” software package for collecting, archiving, analysing and sharing seismological data.In 2022, the international AdriaArray experiment was launched, following on from the previously successful AlpArray experiment. AdriaArray is a multinational effort to map the Adriatic plate and its active margins in the central Mediterranean with a dense regional array of seismic stations to understand the causes of active tectonics and volcanic fields in the region. GA, OGS and ARSO are actively involved in the AdriaArray experiment by providing data from their seismic monitoring networks and - in the case of OGS - also by installing and managing dedicated seismic stations. As part of the AdriaArray experiment, several additional seismic stations have been set up in Austria and north-eastern Italy. It is therefore to be expected that the additional seismic stations installed will improve the earthquake localization capabilities of GA, OGS and ARSO. This certainly applies to Austria and north-eastern Italy, but also to Slovenia, as a large part of its seismicity lies on the border with Italy.The GOAT-CASE experiment aims to quantify the improvement in earthquake localization capability across the entire area. The underlying methodology is to locate earthquakes also using the additional seismic stations and to compare the results. The workload for the detections is distributed among the three partners, while the mapping is done centrally. An attempt will be made to use artificial intelligence to detect earthquakes and compare the results with the standard routines of the agencies.The AdriaArray experiment is planned for a duration of 3 years starting around mid-2022. In this presentation we will illustrate the results of the first year of the experiment, from 01/07/2022 to 30/06/2023.
Greenhouse Gas Flux Patterns from Abandoned Peat Extraction Sites and Recently Restored Peatlands in Estonia
Authors: Yıldız Kadir , Okiti Isaac , Kull Ain , Pindus Mihkel , Kohv Marko , Kasak Kuno
Published: March 2024

Intact peatlands sequester and store substantial amounts of carbon over the long-term period. However, if these peatlands are drained for various purposes, e.g., peat mining, agricultural use, or forestry, they become significant greenhouse gas sources. In Estonia, there are still large areas where peat extraction stopped decades ago, and no significant restoration activities have been implemented. All these areas are significant greenhouse gas sources. Restoring such areas into wetlands may turn these large CO2 sources into sinks and mitigate climate change. However, there remains considerable uncertainty as to whether these sites will become net carbon sinks and to what degree restoration and management methods affect CO2 sequestration efficiency and potential increase in CH4 emissions. Our current study focuses on carbon fluxes from abandoned peat extraction sites and recently restored peatlands in Estonia. Both sites (Lavassaare and Ess-soo bogs) were used for peat mining and were abandoned more than 30 years ago. Ess-soo bog was successfully rewetted in 2021. However, the Lavassaare site is currently abandoned, with restoration works scheduled to begin in late 2024. Here, we use eddy covariance towers to synthesize the continuous CO2 and CH4 flux data from both study sites using open path analyzers (LI-7500 and LI-7700, LICOR Biosciences). The eddy towers were installed at the Lavassaare site in September 2022 and Ess-soo in June 2023. Our results showed that Lavassaare abandoned peat extraction area is still a significant carbon source with annual emissions of 125 g CO2-C m-2 y -1 and 1.5 g CH4-C m-2 y -1. Preliminary results from Ess-soo restored bog indicate reduced CO2 loss and increased CH4 flux. However, the vegetation is still under development. This study shows that abandoned peat extraction sites are continuous carbon sources to the atmosphere, while simply rewetting these sites could remarkably reduce CO2 loss.
Isotope analysis of snowpack nitrate in coastal Antarctica; evidence of nitrate photolysis and preservation.
Authors: Bond Amelia , Frey Markus M. , Kaiser Jan , Marca Alina , Squires Freya
Published: March 2024

Photolysis of snowpack nitrate results in emission of the reactive nitrogen species NOx and HONO. These are important pre-cursors of HOx radicals and ozone, and thereby affect the oxidising capacity of the lower atmosphere above remote snow-covered areas. This is of particular importance in the polar regions as the usual OH radical formation pathway (ozone photolysis and reaction of O(1D) with H2O) is limited by the low water vapour concentration. Isotope analysis of atmospheric reactive nitrogen species and snow nitrate is proving to be a crucial tool for elucidating mechanisms of reactive nitrogen cycling in and above snow.The first snowpit profiles of nitrate stable isotopes (δ15N, δ18O) and concentration at Halley VI Research Station in coastal Antarctica will be presented. The observed isotope fractionation provides evidence of photochemical loss of nitrate and allows estimation of the photolytic isotope fractionation constant at the site. At this high accumulation site, the peak in nitrate concentration from the previous summer is preserved below the snow surface, unlike at low accumulation sites on the Antarctic Plateau. Combining measurements of nitrate concentration and its isotopic compositions preserved in snow helps disentangle the isotope signature of seasonal changes in atmospheric nitrate sources from post-depositional isotope fractionation occurring even at high snow accumulation sites.
A Neural Network to Reduce Subsurface Uncertainty Based on Ground Deformation Measurements
Authors: Guo Tian , Wu Haiqing , Vilarrasa Víctor
Published: March 2024

Subsurface uncertainty is large because we have limited access to it. Reducing uncertainty is important for geo-energies in order to increase the reliability of the simulation results used to define safe operation conditions. In particular, subsurface uncertainty can be reduced by analyzing ground deformation. A clear example of this is the CO2 storage project at In Salah, Algeria, where a double lobe ground deformation shape revealed the presence of a vertical fault zone at depth. Here, we propose a workflow to reduce subsurface uncertainty by inferring the subsurface characteristics from ground deformation measurements. As a foundation step of the workflow, we train a supervised neural network-based regression approach for predicting ground deformation caused by reservoir pressurization due to fluid injection. To train the neural network, we use a recently developed analytical solution to assess ground displacement in response to pressurization of a reservoir that is intersected by a permeable or an impermeable fault (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4503451). The instantaneous solution provided by the analytical solution allows us to generate a large dataset to train the neural network. We have varied eleven variables, including fault and reservoir geometry and mechanical properties. Simultaneously, a simplified parametric space analysis is also performed. Results show that the reservoir thickness, Biot´s coefficient, and the pore pressure buildup impact the displacement the most. This study highlights that an appropriately trained neural network can effectively predict the ground deformation and give insights into the corresponding subsurface characteristics.
Xylogenesis responses to drought stress in Quercus ilex L. at Mediterranean site
Authors: Liyaqat Iqra , Balzano Angela , Niccoli Francesco , Battipaglia Giovanna
Published: March 2024

Droughts are becoming more frequent in the Mediterranean forests due to warmer climate and longer periods without precipitation. In the Mediterranean region, cambial activity is mostly determined by water availability and it occurs during favorite seasons. However, a few studies have focused on the seasonal patterns of wood formation (xylogenesis) response to ongoing climatic conditions in pure stand oak forests. To investigate tree growth response under predicted climate change scenarios, xylogenesis was assessed in Quercus ilex L. trees growing at a site located in the Vesuvio National Park, southern Italy. Sample were taken every two weeks for two consecutive years, and quantitative wood anatomy was used to study the progressive production of cambium, wood and phloem cells. The primary xylogenesis phases (cambium cell formation, occurrence of post-cambial cells, cell-wall thickening, and maturity) were linked to the climate data over 5 to 15 days’ time periods. In helm oak, cambial activity onset in early April, with the development of wood and secondary phloem simultaneously and stopped in early August. Early June was a favorable season for both late wood and late phloem production. Cell wall thickening increased in June to July and August to September as the temperature rose, and vapor pressure decreased in these months. In conclusion, warm climatic conditions and high evaporation rate during spring and summer enhanced plant growth. Herein, earlier growth peaks in helm oak and maximum responsiveness to spring-summer season allowed mediterranean species to mitigate the impact of summer drought.
Half of global burned area is due to managed anthropogenic fire: findings from a coupled socio-ecological modelling approach 
Authors: Perkins Oliver , Kasoar Matthew , Voulgarakis Apostolos , Edwards Tamsin , Millington James
Published: March 2024

Globally, vegetation fires are a key component of many ecosystems and have substantial impacts on carbon emissions. Yet humans also use and manage fires for a huge range of purposes around the world, dependent on numerous social and biophysical factors. Existing representations of anthropogenic fire in dynamic global vegetation models (DGVMs) have been highly simplified, with readily available global variables (e.g. population density) used to estimate numbers of anthropogenic ignitions. Here, we present results from a novel coupled socio-ecological modelling approach to improve understanding of how human and biophysical factors combine to drive the spatio-temporal distribution of global fire regimes. Specifically, we present the integration of two process-based models. The first is the Wildfire Human Agency Model (WHAM!1), which draws on agent-based approaches to represent anthropogenic fire use and management. The second model is JULES-INFERNO2, a fire-enabled DGVM, which takes a physically-grounded approach to the representation of vegetation-fire dynamics.The new WHAM-INFERNO model ensemble suggests that as much as half of all global burned area is generated by managed anthropogenic fires - typically small fires that are lit and spread according to specific land use objectives (such as crop residue burning). Furthermore, we demonstrate that including representation of managed anthropogenic fires in a coupled socio-ecological simulation can improve understanding of the biophysical drivers of unmanaged wildfires, by allowing clearer recognition of the role of anthropogenic land management in global fire regimes. Hence, WHAM-INFERNO is applied to understand how landscape fragmentation, wider land use change, and changes in human fire management have together led to observed recent declines in global burned area despite the warming climate. Overall, findings presented here have substantial implications for understanding of present and future fire regimes, indicating that changes to socio-economic systems are at least as important a consideration as climate change.  1. Perkins, O., Kasoar, M., Voulgarakis, A., Smith, C., Mistry, J., and Millington, J. (2023). A global behavioural model of human fire use and management: WHAM! v1.0. EGUsphere, 1–42. 10.5194/egusphere-2023-2162.2. Mangeon, S., Voulgarakis, A., Gilham, R., Harper, A., Sitch, S., and Folberth, G. (2016). INFERNO: a fire and emissions scheme for the UK Met Office’s Unified Model. Geosci. Model Dev. 9, 2685–2700. 10.5194/gmd-9-2685-2016.
Predicting biomass partitioning and maximum tree height based on optimality principles
Authors: Ding Ruijie , Nóbrega Rodolfo , Prentice Iain Colin
Published: March 2024

Carbon (C) allocation is the process by which photosynthate is partitioned to different functional pools, including leaves, woody tissues and fine roots. A long-standing, qualitative theory explains patterns of C allocation as maximizing growth subject to the availability of different resources. Here we outline a quantitative model based on this theory. We define net carbon profit (NCP) as the total C taken up by photosynthesis, minus the costs of constructing and maintaining leaves and the below-ground C investments required to supply them with water and nutrients. We hypothesize that leaf area index (LAI) tends to the value that maximizes gross primary production; this leads to an explicit prediction of maximum (energy-limited) LAI. We assume that the demands of leaf and root production are satisfied with highest priority, and that excess C is allocated to stems in such a way as to maximize height growth and therefore competitive success. High NCP is predicted not only in tropical and subtropical forests, but also in the Pacific Northwest of the USA and in SE Australia, where the tallest trees are found. Moreover, wood density can be related to woody biomass turnover time, τ (estimated from biomass data and net primary production) – trees with denser wood have longer lifespans. In highly productive ecosystems τ tends to be small, e.g. tropical forests; τ can be larger in temperate and boreal forests. We combine predicted τ with biomass-density relationships and mechanical constraints to predict maximum tree heights, testing our predictions using the global Forest Carbon database (ForC) and observations of maximum vegetation height.
Simulating pore-scale nonlinear reactions at the fluid-solid interface using random walk particle tracking
Authors: Aquino Tomas
Published: March 2024

Random walk particle tracking (RWPT) methods employ a Lagrangian discretization of solute plumes into point particles to numerically solve the advection-dispersion equation. Their recognized advantages over more traditional grid-based Eulerian methods regarding numerical stability and numerical dispersion make them ideal candidates to simulate complex reactive fronts in heterogeneous media. However, handling nontrivial boundary conditions remains a challenge, restricting the range of interface processes that can be simulated. We derive and validate a new collision-based approach to implement a broad class of generalized Robin-type boundary conditions, representing the balance between diffusive fluxes and an arbitrary nonlinear function of the transported and surface reactant concentrations. This formulation allows for modeling arbitrary coupled sets of nonlinear surface reactions within the classical RWPT framework, thus opening new opportunities for simulating pore-scale reactive transport in the subsurface. The collision-based nature of the proposed technique allows for estimating surface reaction rates based on single-particle collisions with the reactive interface. Thus, it does not require concentration field reconstructions or multi-particle searches. We verify the method for a coupled set of nonlinear mass-action reactions under pure diffusion and for nonlinear kinetics representing calcite dissolution in a model porous medium.
Regional impacts poorly constrained by climate sensitivity 
Authors: Swaminathan Ranjini , Schewe Jacob , Walton Jeremy , Zimmermann Klaus , Betts Richard , Burton Chantelle , Jones Chris , Jones Colin , Mengel Matthias , Reyer Christopher , Turner Andrew , Weigel Katja
Published: March 2024

Climate risk assessments must account for a wide range of possible future changes, so scientists often use many climate models in order to fully explore the range of potential changes in regional climates and their impacts. Many of the latest-generation global climate models have high values of effective climate sensitivity (EffCS), which are unlikely according to independent estimates of EffCS. It has been argued that these “hot” models are unrealistic and should therefore be excluded from analyses of climate change impacts. However, whether this would really improve regional impact assessments, or actually make them worse, is unclear. Here we show that there is no universal relationship between EffCS and projected changes in important climatic impact drivers. Analysing three different impacts - heavy rainfall, meteorological drought, and fire weather in important world regions, we find a significant correlation with EffCS only in some regions and for some metrics. Moreover, even in those cases, internal variability has a larger effect on projected changes than has EffCS. This means that impact studies should not select climate models based solely on their EffCS, which does not help constrain projections and may potentially neglect realistic impacts in models deemed “unrealistic” on the basis of their sensitivity. We recommend that model selection or filtering must be based on a more specific evaluation of models vis-à-vis the impact of interest.
Investigation of changes in precipitation extremes and implications for hydrological design: the Italian case study
Authors: Mazzoglio Paola , Viglione Alberto , Ganora Daniele , Claps Pierluigi
Published: March 2024

According to the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC), there is a low agreement on the type of change in heavy precipitation for the Mediterranean area. The challenge lies in comparing studies that employ different time scales. While most of the research works are conducted on a daily scale due to the abundance of data at this resolution, only a limited number of studies delve into shorter (sub-daily) durations because of the scarcity of historical data in digital format at high temporal resolution.A breakthrough in this challenge comes from the Improved Italian-Rainfall Extreme Dataset (I2-RED), a systematic collection of short-duration (1 to 24 hours) annual maximum rainfall depths recorded by more than 5000 rain gauges located all over Italy from 1916 up to the present.This dataset has enabled a comprehensive analysis of temporal trends in extreme precipitation using spatial scales that range from the national to the regional to the local ones. The Mann-Kendall test and the Sen’s slope estimator were first applied to each individual station to investigate at-site statistically significant trends. Regional- and national-scale variations were instead investigated with the record-breaking analysis and the Regional Kendall test.The results confirm that rainfall extremes of different durations are not increasing uniformly over Italy and that separate tendencies emerge in different sectors, even at close distances.The tendencies obtained in this work are used, within the framework of the Italian National Recovery and Resilience Plan RETURN (multi-Risk sciEnce for resilienT commUnities undeR a changiNg climate) project, to identify critical infrastructures that will be likely affected by more severe rainfall extremes in the near future. These results have the potential to be used in revising hydrological design approaches to enable adaptation of the infrastructures to future precipitation conditions.
A multi-dataset trend analysis of precipitation characteristics over Europe
Authors: Beranova Romana , Huth Radan
Published: March 2024

Understanding long-term changes in precipitation is essential for climate research. However, it is a well-established fact that various types of data (station, gridded, reanalysis) can yield different results in extreme and trend statistical analyses. In this contribution, we investigate the long-term changes in precipitation characteristics across different data sources, focusing on the European land area. Our study incorporates station data from the ECA&D project, station data interpolated onto a regular grid (Eobs, Regen) and reanalyses (NCEP/NCAR, 20CR, ERA5). The objective is to explore the seasonal trends of precipitation total amounts, intensity, and probability. The analysis concentrates on the long-term trends of these precipitation characteristics from 1961 to 2010, with emphasis on winter and summer. Trends are estimated using the nonparametric Sen’s slope estimator, and the Mann-Kendall test is applied to assess the statistical significance of these trends. In general, a similar trend pattern is evident within the ECA&D, Eobs and ERA5 datasets. Conversely, the NCEP/NCAR and 20CR reanalyses exhibit the most significant disparities in trends for all precipitation characteristics. Our aim is not only to identify differences between the data sources but also to pinpoint the causes behind these differences.
Simulated radiocarbon cycle revisited by considering the bipolar seesaw and benthic 14C data
Authors: Köhler Peter , Skinner Luke , Adolphi Florian
Published: March 2024

Carbon cycle models used to interpret the IntCal20 compilation of atmospheric Δ14C have so far neglected a key aspect of the millennial-scale variability connected with the thermal bipolar seesaw: changes in the strength of the Atlantic meridional overturning circulation (AMOC) related to Dansgaard/Oeschger and Heinrich events. Here we implement such AMOC changes in the carbon cycle box model BICYCLE-SE to investigate how model performance over the last 55 kyr is affected, in particular with respect to available 14C and CO2 data. Constraints from deep ocean 14C suggest that the AMOC in the model during Heinrich stadial 1 needs to be highly reduced or even completely shutdown. Ocean circulation and sea ice coverage combined are the processes that almost completely explain modelled changes in deep ocean 14C age, and these are also responsible for a glacial drawdown of ~60 ppm of atmospheric CO2. A further CO2 drawdown of ~25 ppm is caused by the colder ocean surface at the last glacial maximum. We find that the implementation of AMOC changes in the model setup that was previously used for the calculation of the non-polar mean surface marine reservoir age, Marine20, leads to differences of less than ±100 14C years. The representation of AMOC changes therefore appears to be of minor importance for deriving mean ocean radiocarbon calibration products such as Marine20, where atmospheric carbon cycle variables are forced by reconstructions. However, simulated atmospheric CO2 exhibits minima during AMOC reductions in Heinrich stadials, in disagreement with ice core data. This mismatch supports previous suggestions that millennial-scale changes in CO2 were probably mainly driven by biological and physical processes in the Southern Ocean. By modifying the 14C production rate (Q), between one that varies so as to fit simulated atmospheric ∆14C to IntCal20 and an alternative constant Q, we can furthermore show that in our model setup the variability in deep ocean 14C age, especially during the Bølling/Allerød—Younger Dryas—Early Holocene climate transition, has its root cause in the carbon cycle, while a Q that achieves agreement with the IntCal20 atmospheric ∆14C record only enhances deep ocean age anomalies and thus optimizes agreement with the benthic 14C data.
Towards understanding dominant controls on Earth system processes across observations and models
Authors: Reinecke Robert , Pianosi Francesca , Wagener Thorsten
Published: March 2024

We are in a simultaneous state of exuberance and starvation of Earth system data. Model ensembles of increasing complexity provide petabytes of output, while remote sensing products offer terabytes of new data every day. On the other hand, we still lack data on some key processes that are more challenging to observe, like groundwater recharge, or only from particular regions of the world (often regions already heavily impacted by anthropogenic change). This leaves us with highly imbalanced datasets. Our ability to produce and collect mountains of data contrasts with our progress in improving scientific process understanding. How can we harness model simulations and data alike to enhance our knowledge and test scientific hypotheses about process relationships despite data gaps and poorly known biases in modelled and observational datasets? Our talk discusses methods to approach this problem while being agnostic to the data source (model simulations or observations). We present a new approach to interrogate a given dataset and identify correlational and possibly causal relationships between its variables. We test the method on an ensemble of complex global hydrological model simulations and observations from the ISIMIP experiments, and demonstrate its usefulness and limitations. We show that our approach can provide powerful insights into dominant process controls while scaling with large amounts of data.
Deriving Daily Transpiration from Instantaneous Measurements in Almond Orchards with Varied Water Stress and Production Systems
Authors: Quintanilla-Albornoz Manuel , Bellvert Rios Joaquim , Nieto Solana Hector , Pelecha Ana , Miarnau Prim Xavier
Published: March 2024

For the purpose of managing irrigation water and raising agricultural water yield, the daily transpiration (Td) monitoring is essential. The estimation of evapotranspiration (ET) and its components, which include crop transpiration (T) and soil evaporation (E), for a variety of crops has shown to be robust when using remote sensing energy balance models. However, as measurements from remote sensing are instantaneous, daily upscaling methods are required in order to estimate Td from remote sensing models. Although upscaling methods for daily ET have been validated by multiple studies, those techniques have not been validated for estimating Td separately in woody crops. The purpose of this study is to assess upscaling methods for recovering Td in almond crops with varying water status and production systems. Sap flow sensors were used to monitor the T in-situ (T-SF), allowing for a continuous measurement for each plant every 15 minutes. The stem water potential (Ψs), stomatal conductance (gs) and leaf transpiration (Eleaf) were also measured at 7:00, 9:00, 12:00, 14:00 and 16:00 solar time for two days in the same trees where sap flow sensors were installed. High-resolution images were used to estimate hourly T using the two-source energy balance model (TSEB). The upscaling methods were evaluated with in situ sap flow data and then implemented to the TSEB estimations. The evaluated upscaling methods were the simulated evaporative fraction variable (EFsim), irradiance (Rs) and potential evapotranspiration (ETp) methods. As a results, the EFsim and ETp methods were more correlated with T-SF, reducing the observed potential underestimation using the Rs method. The improvement was especially important at midday in the tress subjected to severe water stress, where the EFsim reduced the error by 17.61% and the ETp reduced it by 10.6% compared to the Rs method, respectively. Nevertheless, the daily T-SF revealed significant differences across production systems that the daily upscaling methods used in the TSEB were unable to identify. One issue in determining Td on surfaces with discontinuous architectural features was the insufficient sensitivity of daily TSEB between production systems. This issue might be resolved by applying more sophisticated ETp models or enhanced ETp as an upscaling parameter, since ETp can account for variations in canopy structures that have an impact on daily T curves.