bluuebunny/crossref_metadata_2025 huggingface dataset:
Reconciling Top-Down and Bottom-Up Estimates of the Effective Radiative Forcing from Aerosol-Cloud Interactions
Authors: soden brian , park chanyoung
Published: March 2024

Anthropogenic aerosols and their interactions with clouds play a crucial role in regulating the Earth's radiation balance and introduce significant uncertainties in climate change projection. The effective radiative forcing due to aerosol-cloud interactions (ERFaci) is particularly difficult to quantify, leading to uncertainties in model projections of cloud feedback and climate sensitivity. Analysis of CMIP6 model simulations indicate that models with a strongly-positive cloud feedback tend to be offset with strongly negative ACI, leading to similar projections of global mean temperatures during the historical period. However, because anthropogenic aerosol primarily occur in the Northern Hemisphere, the hemispheric asymmetry in warming (NH-SH) differs significantly between low and high ACI models, with observed trends being more consistent with low ACI (weak cloud feedback) models. However, recent satellite estimates of ERFaci based on cloud controlling factors (CCF) is more consistent with high ACI models.  We evaluate the CCF approach using a series of perfect model experiments. The magnitude of ERFaci depends on two factors: the amount of aerosol loading between the pre-industrial and present day, and the susceptibility of cloud albedo and cloud lifetime to that aerosol loading. By comparing observationally-constrained estimates of ERFaci with CMIP6 model simulations, we quantify the contributions of aerosol loading differences and cloud susceptibility to the inter-model spread. We find that explicitly accounting for the role of aerosol activation on cloud droplet formation is essential to obtaining accurate estimates of ERFaci, and when this is done, the satellite constrained estimates of ERFaci are more consistent with low ACI models.
An open online simulation strategy for hydrological ensemble forecasting
Authors: He Yuanqing , Chen Min
Published: March 2024

Hydrological ensemble forecasting is crucial for regional or urban flood forecasting. The development of real-time hydrological ensemble forecasting methods and early warning systems that produce accurate and timely forecasts and flood warnings is of paramount importance for effective disaster risk reduction and the mitigation of loss of life.However, the majority of current hydrological ensemble forecasting systems are centralized, requiring researchers to collect data, download executable programs for models and related methods, and configure the runtime environment on local computers based on specific scenarios (e.g., simulation and forecasting of a specific city or watershed). This method is extremely time-consuming and labour-intensive, and there is a high level of coupling between modelling resources such as data, models (or methods), and parameters. When researchers simulate other scenarios, the models used in certain hydrological processes may not be applicable to the new environment due to changes in the natural environment, and new models may need to be implemented (for instance, the models for runoff yield under saturated storage and runoff yield under excess infiltration conditions are distinctly different). Substantial amounts of time and effort must be invested in recollecting and deploying forecasting resources in local computer, which leads to repetitive labour. This involves downloading models, configuring the operating environment for each ensemble forecasting process, collecting pertinent data, compiling data and model adaptation methods, designing optimization schemes and evaluating the model based on results.Therefore, to change the current complicated download and installation usage patterns associated with hydrological ensemble forecasting and to facilitate the seamless replacement and integration of various hydrological process model components, we propose an open online simulation strategy. This strategy utilizes a service-oriented web architecture to support the online sharing, invocation, integration, and optimization of simulation resources at the three perspectives: model, input data, and model parameters. Specifically, we explore (1) a service-oriented hydrological ensemble forecasting model sharing method and a document-based model service integration and management method, (2) a hydrological ensemble forecasting data sharing and Python-based data adaptation method, and (3) an online optimization and recommendation method for model parameters. By applying the strategy proposed in this paper to hydrological ensemble forecasting, it is possible to reduce the cost of using models, encourage the sharing of hydrological resources and the exchange of knowledge, and ultimately improve the accuracy of flood forecasting.
Adsorption Kinetics and Contaminant Removal Efficiency of Nitrate and Phosphate Using Various Adsorbents.
Authors: Roohmoney Roohmoney , Chakma Sumedha , Kaur Ravinder
Published: March 2024

Nitrate and phosphate play critical functions in plant development, yet their extensive usage in agriculture and industry pollutes water. This not only leads to diseases like cancer but also promotes the environmentally harmful process of eutrophication. Despite significant studies on phosphate and nitrate ion removal from water, the problem is in developing highly selective adsorbents to improve removal efficiency. This study provides a thorough evaluation of the effectiveness of nitrate and phosphate removal from synthetic solutions using three different adsorbents: Powdered activated carbon (PAC), modified activated carbon (MAC), and Activated Alumina (AA). Batch adsorption experiments were carried out across a variety of time periods and doses to investigate the dynamic interactions between the adsorbents and pollutants. The results showed that MAC treated with FeCl3 had the best nitrate removal effectiveness of 97%, outperforming PAC and AA. Conversely, AA demonstrated superior phosphate removal efficiency, outperforming MAC and PAC. The pseudo-second-order kinetic model was shown to be the best fit for modeling the adsorption kinetics, offering useful insights into the time-dependent adsorption processes for both nitrate and phosphate. This study's findings not only help in the optimization of water treatment operations but also highlight the significance of selecting the suitable adsorbent for certain pollutants. The findings of this study benefit environmental science and water treatment technologies by offering practical insights into the comparative performance of commonly utilized adsorbents. The discovery of MAC as a powerful nitrate removal agent and AA as a phosphate removal agent has implications for the development of efficient, customized water treatment applications.
Stagnation and pseudostagnation lines for separating 3D groundwater flow systems in Tothian basins
Authors: Zhang Zhi-Yuan , Jiang Xiao-Wei , Zhou Peng-Yu , Batelaan Okke , Wang Xu-Sheng , Han Peng-Fei , Wan Li
Published: March 2024

Stagnation points have been found to be useful in characterizing groundwater flow regimes in 2D or 3D domains. However, in 3D basins with complicated water table undulation and/or fluctuation, knowledge on stagnation points is limited. In this study, we first derived transient solution of basinal flow under spatially undulating and periodically changing water table in 3D Tóthian basins and examined the occurrence of stagnation points. Based on the analysis of groundwater flow systems distribution in simple 3D basins, we extend the method of delineating groundwater flow systems in 2D profiles using stagnation points to delineating 3D groundwater flow systems using stagnation or pseudostagnation lines, which consist of a series of stagnation or pseudostagnation points. This novel approach was successfully applied to 3D synthetic basins with more complex water table configuration (with undulations in all directions). Based on the transient hydraulic head solution in 3D Tóthian basins with a periodically fluctuating water table, it was found that the evolution of (pseudo)stagnation lines are controlled by the combination of hydraulic diffusivity and the period of the water table fluctuation, both of which determine the dimensionless response time. The change in shape of (pseudo)stagnation lines, induced by spatial undulations and/or temporal fluctuations of the water table, also reflects the variation of groundwater flow systems in penetration depth and horizontal range. The method proposed here improves the efficiency of partitioning groundwater flow systems in 3D domains, and our analytical study of (pseudo)stagnation lines partially fills the knowledge gap between stagnation points and stagnation zones.
Comparative Study of Supervised Learning Algorithms on Rainfall Prediction using NEX-GDDP-CMIP6 Data
Authors: Prasetya Ratih , Harmoko Saputro Adhi , Sukma Permana Donaldi , Florida Riama Nelly
Published: March 2024

This study explores the transformative potential of supervised machine learning algorithms in improving rainfall prediction models for Indonesia. Leveraging the NEX-GDDP-CMIP6 dataset's high-resolution, global, and bias-corrected data, we compare various machine learning regression algorithms. Focusing on the EC Earth3 model, our approach involves an in-depth analysis of five weather variables closely tied to daily rainfall. We employed a diverse set of algorithms, including linear regression, K-nearest neighbor regression (KNN), random forest regression, decision tree regression, AdaBoost, extra tree regression, extreme gradient boosting regression (XGBoost), support vector regression (SVR), gradient boosting decision tree regression (GBDT), and multi-layer perceptron. Performance evaluation highlights the superior predictive capabilities of Gradient Boosting Decision Tree and KNN, achieving an impressive RMSE score of 0.04 and an accuracy score of 0.99. In contrast, XGBoost exhibits lower performance metrics, with an RMSE score of 5.1 and an accuracy score of 0.49, indicating poor rainfall prediction. This study contributes in advancing rainfall prediction models, hence emphasizing the improvement of methodological choices in harnessing machine learning for climate research.
Influence of lateral variations of décollement strength on the structure of orogenic wedges: insights from experimental viscous wedge models
Authors: Roy Sreetama , Willingshofer Ernst , Bose Santanu
Published: March 2024

Fold-and-thrust belts (FTBs) evolve over a mechanically weak basal décollement that separates overlying intensely deformed rocks from the underlying less deformed or undeformed rocks. Although fold-and-thrust belts are often considered laterally cylindrical in nature, a closer inspection reveals remarkable variations in structural style (e.g., fold geometry) both along and across the strike of mountain belts. Using crustal scale thin-sheet laboratory experiments, this study focuses on the role of laterally varying coupling strength of the basal décollement on the evolution of structural styles in natural FTBs. In this study, we used a rectangular slab of silicon putty, a linear viscous material, of uniform thickness in all experiments to simulate the crustal section and the models were deformed at a uniform convergence velocity of ~7.649 × 10-5 ms-1. Analyses of experimental results show remarkable changes in the wedge growth with the introduction of along strike variations in décollement strength. The segment of the deforming wedge over weakly coupled décollement propagates at a faster rate towards the frontal direction compared to the laterally continuous segment over a strongly coupled décollement, leading to an overall sinuous geometry of the deformation front. In contrast, an approximately linear deformation front represents a condition of uniform along-strike coupling strength at the basal décollement. Based on our experimental results, we argue that the broad arcuation of the mountain front along the eastern margin of the Zagros fold-thrust belt (i.e., Fars arc region) might have resulted due to along strike variations in the décollement strength, while the occurrence of a linear deformation front from the central to western margin of the fold-and-thrust belt represents a segment of the wedge with a uniform coupling strength at the basal décollement. Our experimental results can be carefully used to explain the cause of strike-wise segmentation of tectonic processes in orogenic belts, variations in topography and earthquake activities.   
Evidence of Paleo ANF and crustal architecture beneath the Narcondam: Insights from High-Resolution Reflection Seismic Data and Gravity modeling
Authors: Srivastav Harshad , Ghosal Dibakar , Kumar Pankaj
Published: March 2024

The seismically active Andaman-Sumatra subduction zone hosts a prolonged back-arc basin, with the Andaman Sea encompassing several volcanoes, notably the active Barren volcano and the dormant Narcondam volcano. Metamorphic features like the Alcock Rise and Sewell Rise are prominent in this region, experiencing oblique subduction between the Indo-Australian and Eurasian plates alongside backarc seafloor spreading. This convergence has led to significant crustal-scale fault systems like the Great Sumatra Fault, the Andaman Nicobar Fault, and the Sagaing faults. Due to limited geophysical datasets, particularly offshore Narcondam, we utilized three reflection lines (Line 1: 30 km, Line 2: 36 km, and Line 3: 36 km) derived from industry and corresponding satellite gravity data to complete the objectives of this study. We employed F-K and parabolic Radon filtering methods on the seismic data, eliminating noise and seawater multiples from the lengthy east-west 2D seismic profile lines. Subsequently, semblance-based conventional processing techniques were applied to visualize the subsurface. The water depths in the basin range from 1262 to 1554 meters along the profile, with the thickest sediment (~2.35 km) observed at CDP-2877 on Line 1. Satellite gravity data aided in deciphering the crustal architecture of the study area using gravity modeling. The crust's nature beneath Narcondam remains a subject of debate, whereas below Alcock Rise, some authors suggest either oceanic or island arc crust. Our integrated geophysical approach, encompassing gravity modeling, seismic interpretation, and focal mechanism solutions, pivots in evaluating evidence related to the paleo ANF. This comprehensive method allowed for an in-depth examination of the crustal architecture and upper mantle structure beneath both Narcondam Island and the northern part of Alcock Rise. The interpreted seismic section along with the focal mechanism interpretation in the basin indicates the presence of the Paleo ANF, spanning the basin and extending to the Moho. Its significance lies in facilitating fluid migration and influencing depocenter variation during the basin's evolution.
Seismic and Gravity Data Analysis of Oceanic Core Complexes in the West Philippine Basin: Insights into Along-Strike Variations and Formation Processes
Authors: Zhao Jingyan , Zhao Yanghui , Ding Weiwei , Manatschal Gianreto
Published: March 2024

This study explores the formation of Oceanic Core Complexes (OCCs), hypothesized to arise from long offset, active normal faults that exhume the lower crust and upper mantle to the ocean floor. OCCs are predominantly observed in asymmetric crustal accretion zones, especially where magma supply is limited, such as in slow-spreading mid-ocean ridges. Traditional observational approaches, mostly perpendicular to these ridges, have suggested that spreading rates are a critical factor in OCC genesis. However, a lack of comprehensive data along the strike of mid-ocean ridges has limited our understanding of the interaction between tectonic and magmatic processes in OCC formation.Our investigation commenced with the utilization of recently acquired seismic data from the spreading center of the West Philippine Basin. This exceptional dataset has allowed us to chronologically trace the development of multiple distinct OCC structures along the mid-ocean ridge. Complemented by satellite gravity data, we further verified the interpretation of the OCC. The results indicate significant density variability within OCCs, ranging from 2.55 to 3.3 g/cm^3, in contrast to the narrower range of 2.74 to 3.1 g/cm^3 observed in normal oceanic crust. The integration of seismic interpretation and gravity data inversion exposes an alternating sequence of magma-poor and magma-rich segments along the ridge axis. This sequence demonstrates a shift in magmatic activity, transitioning from Penrose-type to Chapman-type crust, characterized by the sequential development of detachment faults and OCCs, ultimately reverting to Penrose-type in the eastern segment. Consequently, our findings propose that, in addition to spreading rates, the localization and delocalization of strain along structural strikes play a pivotal role in OCC evolution. This perspective provides a nuanced understanding of the dynamic interactions between tectonic and magmatic processes that shape the oceanic crust.
A Catchment-Based Hierarchical Spatial Tessellation Approach to a Better Representation of Land Heterogeneity for Hyper-Resolution Land Surface Modeling 
Authors: Lina Huang , Shupeng Zhang
Published: March 2024

To represent the physical processes at hillslope scales for hyper-resolution land surface modeling, we propose a hierarchical, catchment-based spatial tessellation method. The land surface is divided into a hierarchical structure: catchments, height bands along hillslopes within a catchment, and land cover patches within a height band. This catchment-based structure explicitly represents hillslope drainage networks and can be applied at various resolutions determined by a pre-defined maximum height band size. The proposed tessellation method is superior to the conventional grid-based structure in representing land surface heterogeneity, resulting in a higher aggregation skill through the height band representation. The spatial variations in air temperature, leaf area index, saturated soil hydraulic conductivity, and soil porosity are generally lower within a height band than those in a conventional rectangular grid, reflecting the nature of topographic control on climate, vegetation, and soil distribution. The improvement in aggregation skill depends on resolutions and terrain slope angle, more pronounced at 1/6° model resolution and over steeper terrains. Finally, we demonstrate that our proposed catchment-based structure performs better than the grid-based structure through modeling tests over the Columbia River basin at resolutions of 1/2°, 1/6°, and 1/20° and a global test at 1/2° using the ILAMB model evaluation metrics.
Responses of soil organic carbon to wetland restoration—A global meta-analysis
Authors: Wu Yanan , Zhang Ruiyang , Niu Shuli
Published: March 2024

Wetlands are an important part of the terrestrial carbon pool in the global carbon cycle, and exploring the impact of wetland restoration on soil organic carbon (SOC) is of great significance for implementing effective wetland restoration measures to mitigate global warming. We conducted a global meta-analysis to analyze the response of SOC content to different wetland restoration approaches by comparing restored wetlands with degraded and natural wetlands, respectively. We also aimed to identify their temporal evolution, driving factors and potential mechanisms of wetland restoration. The results of this study showed that natural restoration methods, such as farmland abandonment and grazing prohibition, were effective in increasing wetland SOC. Specifically, the SOC contents of wetlands restored using these methods were significantly higher than those of degraded wetlands. Wetland restoration initially caused SOC to show a rapid growth trend, peaking in years 10-20, before levelling off over a longer period of time. After 40 years of restoration, wetland SOC levels were able to approach those of natural wetlands. Important factors driving wetland SOC restoration include total nitrogen, mean annual temperature, and mean annual precipitation. This study would provide insights for mitigating climate change through wetland SOC restoration.
Modeling Iron-Copper Cycling in Photochemically Aged Organic Aerosol Particles
Authors: Kilchhofer Kevin , Mishra Ashmi , Alpert Peter A. , Iezzi Lucia , Bertram Allan K. , Berkemeier Thomas , Ammann Markus
Published: March 2024

Photochemical aging of redox-active transition metals in organic aerosol (OA) particles contributesto an increase in oxidative potential and changes their atmospheric fate. We evaluated thepoorly characterized role of copper as a highly emitted transition metal in a well-established iron-containing proxy for SOA material (citric acid with iron citrate). Here, we computationallymodel photochemical aging experiments from a coated-wall flow-tube to derive an iron-copper cy-cling mechanism that explains the enhanced aging with copper found in scanning transition X-raymicroscope measurements. Aging was carried out under UV light irradiation (λ = 365 nm) at at-mospherically relevant residence times as a function of relative humidity. We measure volatilizedCO2as the first decarboxylation product of iron citrate to quantify the rate of photochemical ironredox cycling. For kinetic modeling, we utilized the kinetic multilayer model of aerosol surface andbulk chemistry (KM-SUB) for films, in which we incorporated chemical reaction mechanismsbuilt on previous work. The model explicitly treats photo- and redox chemistry along with themass transfer of reactants and products between the condensed and gas phase, and is used todescribe CO2production in the flow reactor. The model was applied to data from experimentsusing iron citrate alone and to mixed iron and copper citrate experiments. We tested chemicalmechanisms for iron-copper cycling found in the literature and a newly developed mecha-nism [3]. Inverse modeling and global optimization techniques were used to constrain kineticparameters and optimize the chemical reaction mechanism. In addition, some physical para-meters were quantified anew by measuring the viscosity of aged and non-aged iron-copper citricacid particles. This supports the KM-SUB modeling, including exact microphysical properties un-der different humidity and/or aging conditions. The new model uniquely includes redox reactionsbetween iron and copper complexes in a multiphase system, which may elucidate the role of photo-chemically active OA in the atmosphere. In future work, the model will also be used for similaraging processes with SOA such as α-pinene and OA particles containing nitrate and/or iodinespecies. 
Digital Twin of the North Sea and modular approach for reuse in other applications
Authors: Krijger Tjerk , Thijsse Peter , Schaap Dick , van den Barg Jasper
Published: March 2024

Effective use of data driven intelligence for planning and decision making requires solutions that enable stakeholders to better understand the type of information that the data systems provide. In many cases stakeholders have limited expertise on a specific technical subject, but still need to understand and interpret the data driven intelligence to be able to act on limitations, consequences and alternatives.Three-dimensional data and environment visualization in a virtual web environment can be such an innovation that helps to interpret data by emerging the user in a virtual world where the data is visualized realistically. And by being web-based, accessible via a normal web browser, a large audience can be targeted. An example of such an environment is a planned offshore wind farm, where the user is able to move and look around freely to examine energy yields, effects on fisheries, shipping industries and ecology.At MARIS we have developed, with Deltares and for Rijkswaterstaat, a 3D digital twin of a wind farm in the North Sea using the game-engine Unity for the web. This 3D digital twin assists marine spatial planning in the surrounding area and allows the user to freely move around in the Prinses Amalia wind farm that is made to scale. It includes real time information on the water, waves and air temperature, the wind speed and direction and the energy yields of the wind turbines, and the application on screen responds “live” to this in visualised wave height, direction, turbine speed, graphs, etc. The wind farm contains multiple 3D assets for the turbines, local fish, vessels and more that the user can highlight for more information. The application runs smoothly in the browser on regular computers making it accessible to as many people as possible. In the developments of this 3D environment, a modular approach is applied, such that parts of the application, like the combination of mean sea level and waves, can be reused in other applications.Digital twins have been a hot topic over the last years and will be for next years, with a focus mostly on the models and data behind them. The visualisation and user interfacing is still largely understated. With our developments we want to show what kind of 3D visualizations can be achieved using the blueprint environment in Unity. Because of the modular approach, the visualizations can be extended to include other available types of data and models and serve other types of use cases and applications, such as for marine protected areas - our next pilot in development under the Horizon Europe EFFECTIVE project.
Perscribing Antarctic landfast sea ice in a sea ice-ocean model.
Authors: Pirlet Noé , Fichefet Thierry , Vancoppenolle Martin , Rousset Clément , Mathiot Pierre , Fraser Alexander , Barthélemy Antoine , Kittel Christoph
Published: March 2024

The coastal polynyas of the Southern Ocean play a crucial role in the formation of dense water and have an impact on the stability of ice shelves. Therefore, it is important to accurately simulate them in climate models. To achieve this goal, the relationship between grounded icebergs, landfast ice and polynyas appears to be central. Indeed, grounded icebergs and landfast ice are believed to be key drivers of coastal polynyas. However, ESMs do not simulate Antarctic landfast ice. Moreover, at a circumpolar scale, there are no observations of grounded icebergs available. Hence, we must seek model representations that can overcome these issues. To address these gaps, we conducted a study using an antarctic circumpolar configuration of the ocean–sea ice model NEMO4.2-SI–3 at the 1/4° resolution. We ran two simulations for the period 2001–17, with the only difference being the inclusion or exclusion of landfast ice information based on observations. All other factors, including initial conditions, resolution and atmospheric forcings, were kept the same. We then compared the results of these simulations with observations from the advanced microwave scanning radiometer to evaluate the performance of the new simulation. Our analysis allowed us to determine the extent to which prescribing the distribution of landfast ice and setting the sea ice velocity to zero on landfast ice regions influenced various aspects of the sea ice, such as polynyas, landfast ice and sea ice distribution in the model. In the future, we plan to look at the impact on the ocean and to develop a physical parameterization in order to model landfast ice and consequently polynyas on a permanent basis.
A pseudo-streamer unveiled by a jet and its interaction with a CME
Authors: Schmieder Brigitte , Guo Jinhan , Devi Pooja , Chandra Ramesh , Guo Yang , Poedts Stefaan
Published: March 2024

 We revisit the observations of filament eruption,   extreme-ultraviolet (EUV) wave,  and  CME which originated from the active region (AR) NOAA 12887 on 28 October 2021. We analyze  a jet which initiated close to the flare loop footpoints, and its impact on neighboring loops. The event was observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) satellite at various wavebands and by the Solar TErrestrialRElations Observatory-Ahead (STEREO-A) with its Extreme-Ultraviolet Imager( EUVI) and COR1 instruments with a different view angle from SDO.We show that the EUV-wave event consists of several waves as well as non-wave phenomena. The wave componentsinclude: the fast-mode part of the EUV wave event, creation of oscillations in nearby loops, and the appearance of wave trains. The non wave component consists of stationary fronts. We analyze selected oscillating loops and find that the periods of these oscillations range from 230 – 549 s. On the other hand the jet material lights loops which form a 3D null point. We evidence the existence of a  pseudo-streamer and its relationship with the CME (flux rope).Our numerical MHD simulations with high resolution evidence  the existence of a pseudo-streamer, and its relationship with the CME (flux rope). We   catch the dynamic reconnection process between the flux rope and the pseudo-streamer and discuss the validity of our method compared to static methods.
Integrated Assessment of Climate Change and Forest Management Impacts on Carbon Fluxes and Biomass in a Southern Boreal Forest 
Authors: Islam Md Rafikul , Jönsson Anna Maria , Bergkvist John , Lagergren Fredrik , Lindeskog Mats , Mölder Meelis , Scholze Marko , Kljun Natascha
Published: March 2024

Boreal forests play a crucial role in global carbon sequestration and storage, yet their vulnerability to climate change remains a significant concern. We present results from simulations with the process-based dynamic global vegetation model LPJ-GUESS of the combined effects of climate change and forest management on the carbon sink capacity of a boreal forest in southern Sweden. We compared two future climate change scenarios (RCP 4.5 and RCP 8.5) along with four forest management options against a baseline scenario without management interventions. Our findings indicate that projected temperature increases (+2 to +4°C) in the late 21st century will diminish the net carbon sink strength, particularly in old-growth forests. Clear-cut and subsequent reforestation resulted in a substantial decline (57-67%) in vegetation carbon during 2022-2100. The carbon compensation point (CCP) was reached 12-16 years after the clear-cut, indicating a period of carbon debt before the ecosystems resumed acting as a net carbon sink. Specific reforestation strategies, such as pine plantations, enhanced the overall net carbon sink by 7-20% relative to the baseline during 2022-2100. The carbon parity point, without considering harvested carbon, was reached 56-73 years after the clear-cut, highlighting the extended period required for the reforestation to achieve a carbon stock equivalent to the uncut baseline. These findings highlight the substantial influence of forest management on the net carbon budget, surpassing that of climate change alone. The adoption of relevant reforestation strategies could enhance carbon uptake, simultaneously improving forest productivity and ensuring the forest's vital role in carbon sequestration and storage amid a changing climate.
The nucleation of frictional ruptures, theory and experiment
Authors: Fineberg Jay
Published: March 2024

Frictional motion is mediated by rapidly propagating ruptures, akin to shear cracks, that detach the ensemble of contacts that form the interface betweencontacting bodies. While fracture mechanics describe the rapid motion of these singular objects, the nucleation process that creates them is not currently understood. By extending fracture mechanics to explicitly incorporate finite interface widths, we fully describe the nucleation process. We show, experimentally and theoretically, that slow steady creep ensues at a stress threshold. Moreover, as creeping patches approach the interface width, a topological transition occurs where they smoothly transition to rapid fracture. This new picture of the nucleation dynamics of fracture (and friction) is directly relevant to earthquake nucleation dynamics and the transition from aseismic to seismic rupture in natural faults.
The Effect of the Parametric Decay Instability on the Morphology of Coronal Type III Radio Bursts
Authors: Sishtla Chaitanya , Jebaraj Immanuel , Pomoell Jens , Magyar Norbert , Pulupa Marc , Kilpua Emilia , Bale Stuart
Published: March 2024

The nonlinear evolution of Alfvén waves in the solar corona leads to the generation of Alfvénic turbulence. This description of the Alfvén waves involves parametric instabilities where the parent wave decays into slow mode waves giving rise to density fluctuations. These density fluctuations, in turn, play a crucial role in the modulation of the dynamic spectrum of type III radio bursts, which are observed at the fundamental of local plasma frequency and are sensitive to the local density. During observations of such radio bursts, fine structures are detected across different temporal ranges. In this study, we examine density fluctuations generated through the parametric decay instability (PDI) of Alfvén waves as a mechanism to generate striations in the dynamic spectrum of type III radio bursts using magnetohydrodynamic simulations of the solar corona. An Alfvén wave is injected into the quiet solar wind by perturbing the transverse magnetic field and velocity components, which subsequently undergo the PDI instability. The type III burst is modeled as a fast-moving radiation source that samples the background solar wind as it propagates to emit radio waves. We find the simulated dynamic spectrum to contain striations directly affected by the multiscale density fluctuations in the wind.
Identification of strong-velocity pulses in seismic ground motion signals
Authors: Wang Junhao , Li Qingming
Published: March 2024

Seismic ground motions in the near-fault region produce strong pulses in the velocity-time history, resulting in severe damage to structures. To accurately and effectively monitor these ground motion signals with strong pulses, Shock-Waveform (SW) method is introduced to quantitatively extract the largest velocity pulse from a given ground motion. SW method is an energy-based and adaptive signal analysis method, which has proven capability of analyzing different physical and engineering signals initiated by sudden actions. It is suitable to identify pulse components in the signal with low error and high efficiency. Three variables are proposed to classify ground motions, which is combined with the Principal Component Analysis (PCA) for data dimensionality reduction and subsequent analysis. In addition, an optimum classification standard on pulse-like and non-pulse-like ground motion is established. To avoid the subjective judgement induced by manual selection, unsupervised machine learning classification method and Support Vector Machine (SVM) are used successively to find the decision boundary. In this study, about 100 pulse-like ground motions with large-velocity pulses are identified from approximately 1000 near-fault ground motion recorded in PEER Next Generation Attenuation-West2 database. It shows that most of the pulse-like ground motions are caused by the directivity effect. Based on the proposed classification approach, new models are developed to forecast the possibility of a single pulse, multi-pulses, and pulse period for a given earthquake event. 
Using data and findings from natural and social sciences to assess urban heat vulnerability: a comparison of different methodologies.
Authors: Löffler Karina , Damm Andrea , Gallaun Heinz , Köberl Judith , Kortschak Dominik , Miletich Petra , Oberhuber Lena , Strohmaier Manuel
Published: March 2024

Climate change is causing temperatures around the globe to rise, leading to an increase in the frequency and intensity of hot days and heatwaves. In urban areas, this trend is further exacerbated by urban characteristics, such as the high building density and degree of sealing, the high concentration of anthropogenic heat sources or the reduced outgoing radiation. Extreme heat puts a strain on health, especially for elders and people with pre-existing illnesses. For effective and targeted prevention of heat-related morbidity and mortality, information on the spatial variance of people’s exposure and sensitivity, but also their adaptability towards heat can be of great importance.A common practice for determining the distribution of vulnerable population groups within a city or an area is to construct a spatial Heat Vulnerability Index (HVI) based on findings and data from natural and social sciences, including e.g. socio-economic data, health data, remote sensing data, and climate data. However, there is no standardized workflow but a variety of approaches for the construction of an HVI, which may lead to significant differences in the calculated index ranks. In order to assess the impact of changes in the method design on the resulting index, we test different input data sets, weighting methods and spatial scales for the construction of a spatial HVI for the city of Graz (Austria). The input parameters for the HVI include temperature data, derived from satellite data and weather stations, as well as spatial socio-economic data that describe the population’s sensitivity towards heat and the capability to adapt to high temperatures. By conducting an uncertainty analysis and a global variance-based sensitivity analysis, the partial contribution of changing input variables, chosen weighting methods and different spatial scales to the output’s variance is determined. In addition, a local sensitivity analysis compares the application of land surface temperature derived from thermal satellite imagery to the use of station temperature data for the construction of an HVI.
KNMI’23 climate scenarios for the Netherlands: storyline scenarios of regional climate change
Authors: van der Wiel Karin , Beersma Jules , van den Brink Henk , Krikken Folmer , Selten Frank , Severijns Camiel , Sterl Andreas , van Meijgaard Erik , Reerink Thomas , van Dorland Rob
Published: March 2024

We will present the methodology for the construction, and the outcomes, of the KNMI’23 national climate scenarios for the Netherlands. The KNMI’23 national climate scenarios consist of six scenarios that cover a substantial part of the uncertainty in CMIP6 projections of future climate change in the region. They form a detailed storyline of plausible future climates in the Netherlands. The resulting data is used for impact calculations and assessments by stakeholders, and will be used to inform policy making in different sectors of Dutch society.We have disentangled different sources of uncertainty as much as possible, partly by means of a storyline approach. Uncertainty in future emissions is covered by making scenarios conditional on different SSP scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). For each SSP scenario and time horizon (2050, 2100, 2150), we determine a global warming level based on the median of the constrained estimates of climate sensitivity from IPCC AR6. The remaining climate model uncertainty of the regional climate response at these warming levels is covered by two storylines, which are designed with a focus on the annual and seasonal mean precipitation response (a dry-trending and wet-trending variant for each SSP). This choice was motivated by the importance of future water management to society. For users with specific interests we provide means how to account for the impact of the uncertainty in climate sensitivity. Since CMIP6 GCM data do not provide the required spatial detail for impact modelling, we reconstruct the CMIP6 responses by resampling internal variability in a GCM-RCM initial-condition ensemble.More information on: https://www.knmi.nl/klimaatscenarios (see ‘toolkit’ for material in English).
Differential arrival times for source location with DAS arrays: tests on data selection and automatic weighting procedure
Authors: Bozzi Emanuele , Piana Agostinetti Nicola , Saccorotti Gilberto , Fichtner Andreas , Gebraad Lars , Kiers Tjeerd , Nishimura Takeshi
Published: March 2024

Distributed Acoustic Sensing (DAS) technology is currently used to monitor seismic activity, offering a unique spatially-dense representation of the along-the-cable strain wavefield. Traditional seismic networks typically rely on the timing of specific seismic phases to estimate source locations. In this context, DAS arrays may fail to provide accurate traveltimes because of spatially-heterogeneous waveforms. The motivations are (but not limited to) the directional sensitivity, the heterogeneous cable ground-coupling and the enhanced sensitivity to lateral variations in the medium elastic properties. The resulting fluctuations in signal-to-noise ratios of the dense DAS channels pose significant challenges in the automatic picking of body phases, e.g., P-wave Absolute Arrival Times (P-ARTs). Consequently, the complex distribution of the estimated traveltimes impacts the accuracy of event locations, especially if incorrect assumptions on error statistics (e.g., Normal distribution) are considered. In this study, we address this issue by exploiting the intrinsic DAS measurements' spatial density and testing selected P-wave Differential Arrival Times (P-DATs) for source location. We estimate P-DATs for all the possible DAS channel pairs by identifying the time delay corresponding to the peak of each cross-correlation function. Subsequently, we select P-DATs based on two criteria: interchannel distance and cross-correlation index value. This procedure is often employed to reduce the risk of mixing delay times from coherent and incoherent waveforms. As a first test, using a probabilistic inversion (Hamiltonian Monte Carlo method), we demonstrate how the selected P-DATs provide a better constraint on the event's azimuthal direction compared to P-ARTs. Then, as a second experiment, we move from a subjective selection of P-DATs. To do so, we test a fully-automated and data-driven covariance matrix weighting procedure, in a probabilistic inversion scheme. Specifically, we compute posterior probability distributions for both the physical parameters (event location) and hyperparameters related to data features (interchannel distance and cross-correlation index thresholds). In this scheme, the hyperparameters define each weight along the diagonal of the covariance matrix. These tests offer useful insights into the utilization of P-DATs for event location with DAS. Moreover, we provide an automatic approach to avoid subjective biases based on pre‐conceptions in the a-priori data selection.
Elevated atmospheric CO2 increased soil plant available and soil organic phosphorus in a mature temperate oak (Quercus robur L.) forest
Authors: Soltangheisi Amin , Pinder Adam , Blazey Keegan , Grzesik Robert T. , Marshall Miles , Kourmouli Angeliki , Mayoral Carolina , Hart Kris M. , Ullah Sami , Hartley Iain P. , MacKenzie A. Robert , Smith Andy R.
Published: March 2024

Enhanced productivity of forest ecosystems in response to rising levels of anthropogenically generated atmospheric carbon dioxide (CO2) has the potential to mitigate against climate change by sequestering carbon in woody biomass and soils. However, the physiological response of trees to elevated atmospheric CO2 may be constrained by the availability of soil nutrients, predominantly nitrogen and phosphorus (P). Here, we assess the impact of elevated atmospheric CO2 on P cycling in a temperate 180-year-old oak (Quercus robur L.) forest exposed to free-air CO2 enrichment (ambient + 150 ppm) for six years. Soil cores were collected to a depth of 1 m in July 2023 and separated into three horizons and three layers (O, A, B, 30-50, 50-70, 70-100 cm) before analysis using the Hedley1 sequential P fractionation and the DeLuca2biological based P extraction techniques. Plant available P in soil pore water and total organic P from the O horizon increased by 84 and 128%, respectively, whilst organic P extracted with phosphatase increased by 62% under elevated CO2. Total organic P in soil horizons beyond the B horizon (> 15 cm) decreased under elevated CO2 in comparison with ambient CO2. As soil organic P is derived from the turnover of both vegetation and microbial biomass, increased soil organic P in the O horizon may be due to the faster turnover of organic matter or an increase in the net primary productivity of the forest. Soil P cycling in this forest ecosystem appears to be predominantly influenced by biological rather than chemical processes, since elevated CO2 only affected the organic P and not inorganic P fractions. Forest productivity may be constrained by P limitation in future elevated CO2 environments, if there is faster organic matter turnover which is probably the case in our study.1Hedley, M. J., Stewart, J. W. B., & Chauhan, B. (1982). Changes in inorganic and organic soil phosphorus fractions induced by cultivation practices and by laboratory incubations. Soil Science Society of America Journal, 46(5), 970-976.2DeLuca, T. H., Glanville, H. C., Harris, M., Emmett, B. A., Pingree, M. R., de Sosa, L. L., Cerdá-Moreno, C. & Jones, D. L. (2015). A novel biologically-based approach to evaluating soil phosphorus availability across complex landscapes. Soil Biology and Biochemistry, 88, 110-119.
Real-time forecast of temperature-related excess mortality at small-area level: A conceptual framework
Authors: Mistry Malcolm N. , Gasparrini Antonio
Published: March 2024

Development of innovative tools for real-time monitoring and forecast of environmental health impacts is central to effective public health interventions and resource allocation strategies. Though a need for such generic tools has been previously echoed by public health planners and regional authorities responsible for issuing anticipatory alerts, a comprehensive, robust and scalable real-time operational framework for predicting temperature-related excess deaths at local scale has not been developed yet. Filling this gap, we propose a flexible conceptual framework for coupling publicly available operational weather forecasts with temperature-mortality risk functions specific to small census-based zones, the latter derived using state-of-the-art environmental epidemiological models. Utilising high-resolution temperature data forecast by a leading European meteorological centre, we demonstrate a real-time application to forecast the excess mortality during the July 2022 heatwave over England and Wales. The output by way of expected temperature-related excess deaths at small geographic areas on different lead times, can be automated to generate maps at various spatio-temporal scales, thus facilitating preventive action and allocation of public-health resources in advance. While the real-case example discussed here demonstrates an application for predicting (expected) heat-related excess deaths, the framework can also be adapted to other weather-related health risks and to different geographical areas, provided data on both meteorological exposure and the underlying health outcomes are available to calibrate the associated risk functions. The proposed framework addresses an urgent need for predicting the short-term environmental health burden on public health systems globally, especially in low- and middle-income regions, where rapid response to mitigate adverse exposures and impacts to extreme temperatures are often constrained by available resources.