bluuebunny/crossref_metadata_2025 huggingface dataset:
Monitoring Severe Storm Impacts and Climate Trends in the Southeastern US using Satellite-Based Proxy Indicators: A Case Study of Hurricane Sally
Authors: Khosravi Ali , Ghorbani Zahra , Maghsoudi Yasser
Published: March 2024

The southeastern U.S. is frequently impacted by severe thunderstorms, which are known for producing damaging winds, hail, and tornadoes. The National Oceanic and Atmospheric Administration (NOAA) reports that this region experiences the highest frequency of thunderstorms in the country. In recent decades, these storms have shown a trend of increasing both in frequency and intensity. Moreover, the southeastern states are susceptible to hurricanes and tropical storms, which have been intensifying due to warmer ocean temperatures. The escalating severity of these weather events poses significant risks to public safety, infrastructure, and the economy in the southeast. Our proposed study uses advanced satellite technology, specifically Interferometric Synthetic Aperture Radar (InSAR), to map storm-induced flooding and damage from October 2019 to August 2021. This period includes Hurricane Sally, which caused significant destruction in Alabama on September 16, 2020. By analyzing satellite images taken before and after hurricanes, we aim to identify affected areas and assess infrastructural damage. The study employs Sentinel-1 InSAR data processed by the COMET-LiCSAR system and the LiCSBAS processing package, generating surface deformation time series. We also integrate optical images to examine soil moisture and climate changes, correlating them with displacement and radar coherence data from SAR images. This research will classify and discuss the impact of hurricanes on infrastructure and roadways, providing critical information to prioritize emergency response and inform repair and reconstruction planning.
Predicting Soil Bulk Density in Boreal Podzolic Soil using Ground-Penetrating Radar and Electromagnetic Induction
Authors: Pathirana Sashini , Galagedara Lakshman , Lambot Sébastien , Krishnapillai Manokararajah , Smeaton Christina , Cheema Mumtaz
Published: March 2024

Soil compaction is one of the major challenges in sustainable agriculture, primarily due to the use of heavy farming machinery. Tillage and soil compaction influence soil properties, state variables, and processes, ultimately affecting soil health, crop growth, and yield. Traditional methods to estimate soil compaction level, like bulk density (BD) and penetration resistance, are laborious, destructive, time-consuming and provide point-scale measurements only. Near-surface geophysical techniques like Ground-Penetrating Radar (GPR) and Electromagnetic Induction (EMI) are being increasingly utilized to estimate soil properties and state variables in the agricultural landscape since GPR and EMI can address some of drawbacks of traditional methods. However, there is a lack of studies with GPR and EMI examining the BD change associated with tillage and soil compaction. We hypothesize that proxies from GPR and/or EMI can be used to predict BD as an indicator of soil compaction. The objectives were to: 1) evaluate the impact of BD change on dielectric constant (Kr) and direct ground wave amplitude (A) measured from GPR, and apparent electrical conductivity (ECa) measured by EMI; and 2) assess the predictive capability of GPR and EMI for BD determination. The experiment was conducted on a loamy sand textured soil at a boreal podzolic site in Newfoundland, Canada. Proxy data (i.e., Kr, A and ECa) were collected using a 500 MHz center frequency GPR system and an EMI sensor representing three compaction treatments (i.e., after tillage, after 4- and 10-time roller passes). Treatment effects and relationships between proxies and the average BD of 0-30 cm soil depth were tested using analysis of variance (ANOVA) and correlation analysis. A Random Forest (RF) regression approach was employed to identify the most significant variables for predicting BD. Subsequently, simple, and multiple linear regression models (LRM) were developed. The accuracy of these LRMs was assessed by comparing predicted and measured BD values. ANOVA results reveal that the measured BD and proxies are significantly different at all three compaction levels. The average BD strongly correlated with soil proxies; Kr(r=0.72), A (r=0.71), and ECa(r=0.89). Based on RF, ECa and Kr are the most important variables to predict BD for the studied data set. Therefore, ECaand Kr were used to develop simple and multiple LRMs. The simple LRM developed with ECa showed a higher coefficient of determination, R2=0.80, compared to Kr (R2=0.63), while the multiple LRM showed the highest R2 (R2=0.83). The model predicted BDs did not deviate from 1:1 line with a root mean square error of
Assessing Groundwater Sustainability in the Arabian Peninsula and its Impact on Gravity Fields through GRACE Measurements 
Authors: Mohasseb Hussein A. , Shen Wenbin , Abd-Elmotaal Hussein A. , Jiao Jiashuang
Published: March 2024

This groundbreaking study addresses the imperative to comprehend gravity shifts resulting from Groundwater Storage (GWS) variations in the Arabian Peninsula. Despite the critical importance of water resource sustainability and its relationship with gravity, limited research emphasizes the need for expanded exploration. The investigation explores the impact of GWS extraction on the gravity field, utilizing Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data in addition to validation using WaterGAP Global Hydrology Model (WGHM). Spanning April 2002 to June 2023, the study predicts GWS trends over the next decade using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model.  The comprehensive time-series Analysis reveals a huge GRACE-derived GWS trend about -4.90±0.32 mm/year during the period of study. This significantly influences the gravity anomaly GA values, demonstrating a corresponding fluctuation in GWS time series. The projected GWS indicates a depletion rate of 14.51 km³/year over the next decade. The correlation between GWS and GA is substantial at 0.80, while GA and rainfall correlation is negligible due to low precipitation rates. Employing multiple linear regression explains 80.61% of the variance in gravity anomaly due to GWS, precipitation, and evapotranspiration. The study investigates climate change factors—precipitation, temperature, and evapotranspiration—providing a holistic understanding of forces shaping GWS variations. Precipitation and evapotranspiration exhibit nearly equal values, limiting GWS replenishment opportunities. This research holds significance in studying extensive GWS withdrawal in the Arabian Peninsula, particularly concerning crust mass stability. Integrating GRACE and hydrological models’ datasets furnishes a comprehensive understanding, contributing valuable foresight into the future trajectory of GWS. The results illuminate intricate relationships between GWS, gravity anomalies, and climate factors, presenting a robust framework for sustainable water resource management. 
Modeling ice and olivine CPO evolution and its affect on large-scale flow in two-way coupled simulations
Authors: Rathmann Nicholas , Lilien David , Hvidberg Christine , Grinsted Aslak , Dahl-Jensen Dorthe , Mosegaard Klaus , Bekkevold Ivanka , Prior David
Published: March 2024

We present a spectral-space CPO model that allows for efficient and seamless simulation of anisotropic polycrystalline flows at large scale, relevant for ice sheets and Earth’s upper mantle. The CPO model is two-way coupled with a bulk orthotropic power-law rheology using a linear grain homogenization scheme, making analytical and frame-independent calculations of CPO-induced viscous anisotropy possible and computationally cheap. The effect of two-way coupling flow and CPO evolution is explored in idealized finite element simulations of ice stream flow and mantle thermal convection. In both cases, we find that strain-rate fields are non-trivially affected, and we briefly discuss the consequences for ice-stream self-reinforcement and the coupling between plate motions and the sublithospheric mantle.This contribution is mainly focused on introducing our modeling framework “specfab” to the wider community.
Enhancing Urban Stormwater Resilience: A Comparative Study of Permeable Asphalt, Concrete, and Interlocking Pavers for Sustainable Flood Mitigation
Authors: Salem Ali , Abduljaleel Yasir , Amen Ehab Mohammad
Published: March 2024

The escalating challenges posed by rapid urbanization and climate change have intensified the quest for sustainable stormwater management strategies. Permeable pavement practices have emerged as a pivotal solution to effectively control stormwater runoff and address the associated flooding issues. This study delves into the comparative analysis of three prevalent permeable pavement types—permeable asphalts (PA), permeable concretes (PC), and permeable interlocking concrete pavers (PICP)—with the overarching goal of identifying the most efficient solution for alleviating the negative impacts of surface runoff.In pursuit of this objective, the study conducts simulations for three distinct scenarios, each representing different extreme storm events within a designated catchment area. The evaluation encompasses the performance of PA, PC, and PICP, both with and without the integration of permeable pavements, utilizing the sophisticated Personal Computer Stormwater Management Model (PCSWMM). The selected catchment area is situated in King County, Washington, USA, providing a real-world context for the investigation.The validation of the PCSWMM model attests to its reliability in predicting peak discharges within the study reach, establishing a robust foundation for subsequent analyses. The outcomes reveal that all three forms of permeable pavement effectively prevent flooding, with PA emerging as the most formidable solution, showcasing a remarkable average reduction of 51.25% in peak flow and 65% in total flow. In contrast, PC demonstrates a slightly more modest improvement, with average reductions of 21.75% in peak flow and 34.25% in overall flow. Furthermore, PICP exhibits the lowest reduction in peak flow (7.0%) and total runoff volume (15.75%). In conclusion, this study offers valuable insights into the comparative effectiveness of permeable pavements in urban stormwater management, emphasizing the critical role of thoughtful pavement selection in sustainable urban planning endeavors.
Leaf carbon monoxide emission under field conditions: a potential stress indicator?
Authors: Yakir Dan , Muller Jonathan , Stern Rafael , Qubaja Rafat , Bohak Yasmin
Published: March 2024

Carbon monoxide (CO) is produced in living plants and can act as a stress-signaling molecule in both animals and plants. While CO emissions from soil, litter decomposition, and incomplete combustion have been extensively studied, there is a scarcity of research on CO flux from living vegetation, particularly under field conditions. We present the results of continuous CO fluxes measurements (together with those of water, CO2, and COS) using twig chambers in summer-droughted and in non-droughted (irrigated) Pinus halepensis trees across the seasonal cycle. We found significant CO emissions from leaves, which were correlated with environmental parameters (radiation, leaf temperature, and VPD). It peaked under the stressful summer conditions at the study site, when CO2 exchange and leaf conductance were at a minimum.  The CO fluxes were strongly correlated to twig transpiration and were enhanced under irrigated treatment. It is speculated that leaf CO emission is related to biotic reactions, such as heme degradation, which is enhanced under stress conditions and is possibly associated with photorespiration. Our results provide a rare, high-resolution, annual scale study of the environmental factors controlling leaf CO emissions under field conditions and indicate that including it in plant gas exchange studies may provide additional means to interpret their response to stress.
The movement and deformation of the Jiangcuo fault before the 2021 MS7.4 Maduo earthquake reflected by GPS and InSAR data
Authors: Zhao Jing , Yuan Zhengyi , Wang Yue
Published: March 2024

The 2021 Maduo MS7.4 earthquake occurred in the Jiangcuo fault with left-lateral strike-slip movement. In order to study the movement and deformation characteristics of the Jiangcuo fault before the Maduo earthquake and further analyze the seismogenesis process of the continental strong earthquake, the large-scale strain rate field distribution in western China, the locking degree and the evolution of slip deficit rate of the Jiangcuo fault, and the rupture mechanism of seismogenic fault are analyzed and discussed in this paper using the GPS velocity field on a long time scale and InSAR dynamic velocity field. The results show that: (1) The strain rate field in EW direction shows that the Maduo earthquake is located at the edge of the EW direction strong compression zone of Bayanhar block. The eastern part of the Maduo earthquake is a compression strain accumulation zone, and the western part is a gradual transition from weak compression to tension strain. The results of the maximum shear strain rate field show that the Maduo earthquake is located at the edge and high gradient zone of the high value area of the maximum shear strain rate field. (2) The inversion results of the locking degree show that deep unlocking occurs in some regions in the east and west of the epicenter of the fault during 2015-2021, gradually transitioned to a completely locked state in the middle of the fault, and the focal point of Maduo earthquake is at the edge of the completely locked region in the transition region. The dynamic results from 2015 to 2017 and 2017 to 2019 were basically stable. The whole fracture plane was basically in a state of strong locking, and only partial unlocking with a depth below 15km existed in local areas. From 2019 to 2021, some faults in the east and west of the epicenter have deep and shallow unlocking phenomena, including the overall unlocking of most areas of the western section and the local deep unlocking of the East section of the ruptured fault, while the rapid unlocking of the two sides of the epicenter may contribute to the occurrence of the main earthquake. This work was supported by Science for earthquake resilience (XH23047A).
Propagation of climate extremes across global value chains
Authors: Guichoud Serine , Li Laurent , Dumas Patrice
Published: March 2024

This paper presents a theoretical frame relying on the graph theory for assessing extreme weather events relative damage to global value chains. The approach is defined in three steps: the first part of the paper presents the intuition inspiring the defined model and associated theory , the second part is focused on a scenario analysis declining extreme events relative severity by countries, the third part leverages on the graph theory to translate the damages associated to these events into macro-sectorial value chains disruptions. A numerical application is then run by estimating drought global damages.We consider damage as a score based on extreme events occurrence, calibrated in this article with historical data. Using the graph theory, we incorporate these damages to a network of countries moving from a stationary state of constant flows before a distribution of extreme events, to a modified state considering the extreme events occurrence. The spread of these production damages is modeled as a contagion applied to a network representing intermediate consumption financial flows, to assess the cumulative effect of a damage to value chains. 
Different orbital rhythms in loess grain-size records across the Chinese Loess Plateau
Authors: Zhao Deai , Xiao Guoqiao , Hao Qingzhen , Tian Shaohua , Wu Zhipeng , Lu Hao , Dai Gaowen , Peng Shuzhen , Huang Chunjv , Yin Qiuzhen
Published: March 2024

The thick loess-paleosol sequences on the Chinese Loess Plateau (CLP) are among the best terrestrial archives for the understanding of the global paleoenvironment and East Asian monsoon changes. In particular, orbital-scale variations characterized by major periodicities of ~100 kyr, ~40 kyr and ~20 kyr are recorded by various proxies in the loess, which is often suggested to reflect the orbital control on East Asian climate. However, whether these climate periods could be affected by the signals from the dust source areas remains unknown. Here we present the spectrum results of grain size records from the Baoji loess section spanning the past 400 ka in the southeastern part of the CLP, and compare with the previous results in the western CLP (to the west of the Liupanshan Mts.), including Gulang, Menyuan, Lanzhou, Linxia, Jingyuan loess sections, and loess sections in the eastern CLP (to the east of the Liupanshan Mts.), including Luochuan, Xifeng, Lantian, and Weinan sections. The results show that the dominant periods in different sections are spatially different, and the ~20-kyr precession cycle from the western CLP is significantly stronger than that in eastern CLP. Albeit dust accumulation rates in the Jingbian loess section from the eastern CLP are very high, the lack of precession signal suggests that high sedimentation rate is not the main factor for occurrence of precession cycle in grain size records. The results also suggest that the dust source areas for the eastern and western CLP are different, specifically, the loess deposits in western CLP were mainly sourced from the NE Tibetan Plateau, while the loess deposits in eastern CLP were significantly fed by the deserts to the north CLP (including deserts in Northern China and Southern Mongolia). As the dust production and transportation in NE Tibetan Plateau and the deserts to the north CLP were significantly driven by the ~20-kyr local summer insolation and the ~100-kyr ice age cycle, respectively, we argue that the climate cycle in loess grain size of the CLP indeed reflects the climate signals of their source areas, rather than the deposition areas. Our results suggest that caution should be taken when explaining the meaning of the loess grain size records.
Application of GPU-accelerated Particle-in-cell Simulations in Magnetic Reconnection Associated with Energy Conversion between Field and Particles
Authors: Xiong Qiyang , Huang Shiyong
Published: March 2024

Magnetic reconnection is a fundamental physical process of rapidly converting magnetic energy into particles in space physics. The electron diffusion region (EDR), which can be split into the inner EDR and outer EDR, is the crucial region during magnetic reconnection. The inner EDR, where the magnetic field is dissipated, is responsible for the heating and acceleration of the electrons. The outer EDR also plays a crucial role where the electrons are decelerated and return the energy to the magnetic field in the pileup region behind the reconnection front (RF). Here we present the studies associated with energy conversions around EDR using fully kinetic particle-in-cell (PIC) simulations of advanced GPU-accelerated computing and Magnetospheric Multiscale (MMS) mission observations. It is found that part of the electrons in the outer EDR are forced backward to the inner EDR by the magnetic tension force to be accelerated again, which we name it by magnetic Marangoni effect. And we also report a novel crater structure of magnetic field behind the RF caused by the continuous impact of the high-speed outflow electron jets. Our PIC simulation scheme based on the GPU architecture can achieve high performance computing and fast accessibility to the simulation results. The scientific findings in our studies propose various approaches for the particle acceleration and energy conversion during magnetic reconnection.
Recent Sea Level Rise and Variability in Singapore Region Derived from Tide Gauges and Satellite Altimetry
Authors: Tkalich Pavel , Luu Quang-Hung
Published: March 2024

Sea level in the Southeast Asia (SEA) seas is driven by various phenomena at global,  regional and local scales. The latest tide gauge and satellite data revealed its most recent spatial and temporal patterns. The trend of global sea level rise in Singapore region is hindered by dominant variability of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Indian Ocean Dipole (IOD), as well as associated modulation of Asian Monsoon. It was confirmed that positive sea-level anomalies in the southern and western areas of Southeast Asia seas were significantly high (~10 cm) during the northeast monsoon, especially in the Gulf of Thailand (~25 cm). The sea level trends for these regions were basically reversed during the southwest monsoon but with a smaller magnitude of negative sea-level anomalies. The regional sea-level trend in the Sunda Shelf differed from region to region, with the rates varied greatly from 1.4 to more than 4.8 mm/year. Interestingly, the rates on the east-western side of the region were roughly 3.0-4.5 mm/year, which were higher than the ones at other regions, being 2.5-3.5 mm/year. The presentation discuss the causes and consequences of sea level rise and variability in SEA and Singapore region in particular.This Research is supported by Singapore’s National Research Foundation and National Environment Agency under the National Sea Level Programme Funding Initiative (Award No. USS-IF-2020-4).
AI-Driven Hydro-Insights: Proactive Water Resource Management for Sustainable Agriculture in the Face of Climate Change
Authors: Kow Pu Yun , Chang Yu-Wen , Chang Fi-John
Published: March 2024

Climate change profoundly affects natural water resources by increasing extreme rainfall and persistent drought events. This impact has led to a rising likelihood of over-extraction of groundwater by Taiwanese farmers due to insufficient water resources. Quantifying groundwater pumping activities is challenging, thereby prompting this study to introduce a hybrid AI model combining a Convolutional-based Autoencoder with LSTM. The objective is to explore the spatiotemporal relationship between hydrometeorology and groundwater for providing a quantitative assessment of groundwater resources.To construct the model, a comprehensive dataset spanning two decades (2000-2019) is utilized, incorporating information from 33 groundwater monitoring wells in the Jhuoshuei River basin of Taiwan. Two types of datasets, observation and simulation, are employed for a robust analysis. The hybrid AI model yields accurate three-month-ahead forecasts for shallow groundwater in the Jhuoshuei River basin, with R2 performance ranging from 0.70 to 0.87 for T+1 (short-term forecasts) and from 0.42 to 0.69 for T+3 (long-term forecasts).The significance of these forecasts lies in their potential to empower farmers to increase crop cultivation efficiency. The long-term forecasts aid in formulating strategic plans for crop cultivation and fallow periods, promoting efficient agricultural management. Simultaneously, the short-term forecasts empower farmers to enhance irrigation efficiency, leading to a reduction in regional water consumption. This proactive approach aligns with Sustainable Development Goals (SDGs) 11 and 12, fostering sustainable water resource management practices. In essence, this hybrid AI model emerges as a valuable tool for proactive and adaptive water resource management, particularly crucial in the context of evolving climate conditions.Keywords: Groundwater management, AI, Deep Learning, regional forecast, machine learning, SDGs, Taiwan
Estimate of seismic fracture surface energy from pseudotachylyte-bearing faults
Authors: Aldrighetti Silvia , Di Toro Giulio , Pennacchioni Giorgio
Published: March 2024

Earthquakes are the result of propagation at ∽km s-1 of a rupture and associated slip at ∽m s-1 along a fault. The total energy involved in a seismic event is unknown, but qualitatively most of it is dissipated by rock fracturing and frictional heat. Seismic fracture energy G (J m-2) is the energy dissipated in the rupture propagation and can be estimated by the inversion of seismic waves. However, its physical significance remains elusive. G may include the contributions of both rock fracturing (energy to form new rock surfaces US, J m-2) and fault frictional heating (Q, J m-2) per unit fault area. Here we determine both US and Q in natural and experimental pseudotachylyte-bearing faults, following the approach used by Pittarello et al. (2008). In fact, in pseudotachylytes, or solidified frictional melts produced during seismic slip, (i) US is proportional to the surface of new fragments produced in both the slip zone and in the wall rocks, and (ii) Q is proportional to the volume of frictional melt.The selected natural pseudotachylytes belong to the east-west-striking, dextral, strike-slip Gole Larghe Fault Zone (Adamello, Italian Alps). To estimate US we employed Electron Back-Scatter Electrons (EBSD), High Resolution Mid Angle Back-Scattered Electrons (HRMABSD) and Cathodoluminescence-Field Emission Scanning Electron Microscopy (CL-FESEM). In particular, CL-FESEM imaging reveals a microfracture network in the wall rocks that cannot be detected with the other techniques. In the pseudotachylyte-bearing fault, the microstructural analysis reveals (i) a high degree of fragmentation of the wall rock adjacent to the pseudotachylyte fault vein (formed along the slip surface), with clast size down to
Representing systematic and random errors of eddy covariance measurements in suitable likelihood models for robust model selection 
Authors: Weber Tobias Karl David , Schade Alexander , Rauch Robert , Gayler Sebastian , Ingwersen Joachim , Nowak Wolfgang , Diamantopoulos Efstathios , Streck Thilo
Published: March 2024

The importance of evapotranspiration (ET) fluxes for the terrestrial water cycle is demonstrated by an overwhelming body of literature. Unfortunately, errors in their measurement contribute significantly to (model) uncertainties in quantifying and understanding ecohydrological systems. Measurements of surface-atmosphere fluxes of water at the ecosystem scale, the eddy covariance method can be considered a powerful technique and considered an important tool to validate ET models. Spatially averaged fluxes of several hundred square meters may be obtained. While the eddy-covariance technique has become a routine method to estimate the turbulent energy fluxes at the soil-atmosphere boundary, it remains not error free. Some of the inherent errors are quantifiable and may be partitioned into systematic and stochastic errors. For model-data comparison, the nature of the measurement error needs to be known to derive knowledge about model adequacy. To this end, we compare several assumptions found in the literature to describe the statistical properties of the error with newly derived descriptions, in this study. We are able to show, how sensitive the assumptions about the error are on the model selection process. We demonstrate this by comparing daily agro-ecosystem ET fluxes simulated with the detailed agro-hydrological model Expert-N to data gathered using the eddy-covariance technique.
Solar granulation-generated chromospheric heating and plasma outflows in two-fluid magnetic arcade
Authors: Kumar Mayank , Murawski Kris , Kuźma Blazej , Kadowaki Luis , Kilpua Emilia , Poedts Stephan , Erdelyi Robertus
Published: March 2024

Context. The heating of the solar chromosphere, the associated plasma outflows, and the origin of the solar wind are key issues in heliophysics. In this paper, we provide a new perspective on their connection to the propagation and dissipation of waves generated by solar granulation.Aims. The primary objective of this paper is to conduct 2.5-D numerical simulations of the partially ionized lower solar atmosphere, investigating the propagation and dissipation of granulation-generated waves in the context of plasma outflows and the related heating of the chromosphere, which is due to ion-neutral collisions.Methods. We use the JOint ANalytical and Numerical Approach (JOANNA) code to solve the two-fluid model equations. We take into account partially ionized hydrogen plasma composed of ions (protons) and neutrals (H atoms), which are coupled via ion-neutral collisions. We focus on a quiet region of the solar chromosphere which is gravitationally stratified and magnetically constrained by an initially set magnetic Plasma flows and solar chromosphere heating arcade. Solar convection situated beneath the photosphere is the main source of these waves that are propagating through the simulated solar atmosphere.Results. The numerical results obtained in our study reveal an important process in the lower solar atmosphere. The naturally evolving convection generates waves and a portion of the wave energy is dissipated due to ion-neutral collisions in the solar chromosphere. This dissipation of waves, in turn, leads to the release of thermal energy, resulting in the heating of the solar atmosphere. This phenomenon is also associated with upward-directed plasma flows, which may play a role in the formation of the solar wind. Furthermore, our analysis of the dominant wave periods in the various layersof the solar atmosphere closely aligns with observational data from Wiśniewska et al. (2016) and Kayshap et al. (2018). This alignment underscores the crucial role ion-neutral collisions play in facilitating the energy release process, shedding light on the intricate dynamics of the solar atmosphere.Conclusions. Based on our numerical simulations, we can draw the following conclusions: The dissipation of waves in the two-fluid plasma caused by ion-neutral collisions in the two-fluid plasma model leads to plasma outflows and increased heating in the chromosphere. These plasma outflows may play a role in the generation of the solar wind and the accompanying heating.
Schmidt hammer exposure dating (SHD) the Last Glacial-Interglacial Transition in Wester Ross, Scotland 
Authors: Curry Alastair , Bartlett Olly , Newitt Jonathan
Published: March 2024

Understanding the extent, retreat dynamics and climate-glacier coupling of the Scottish Ice Sheet during the Last Glacial-Interglacial Transition (LGIT) is hampered by a highly fragmentary geomorphological record, and is dependent on a precise and accurate dating framework to constrain deglaciation. On land, readvance of the retreating ice margin is recorded in part of NW Scotland by moraines of the Wester Ross Readvance at ~15.4-15.8 ka, preceding the Lateglacial Interstade and the Loch Lomond Stade ~12.9-11.7 ka. While the number of dated landforms has increased in recent years, the LGIT chronology in NW Scotland is primarily based on a limited number of samples per site, using Terrestrial Cosmogenic Nuclide Dating (TCND) methods that can yield conflicting or uncertain results. This highlights the value of developing complementary dating methods.Previous studies have questioned the reliability of the Schmidt hammer exposure dating (SHD) technique on lithologies other than granite. This research (i) evaluates the use of SHD on sandstone in the NW Scottish Highlands; (ii) develops a local, lithology-specific calibration curve; (iii) applies this to estimate the age of undated surfaces and tests existing interpretations of landscape change during the LGIT. Field results from a 1,500 km2 area of NW Scotland conclude that SHD can detect significant differences (p
Facilitating the Planning of integrated Water-Energy-Food-Environment Systems through Open Software
Authors: Fleischmann Julian , Platzer Werner , Ribbe Lars , Nauditt Alexandra , Blechinger Philipp
Published: March 2024

Addressing climate change, environmental degradation, and resource scarcity while ensuring the basic supply of the growing earth population are fundamental global challenges. In this context, the integration of water, energy, food, and environment systems for tapping cross-sectoral synergies and minimizing trade-offs presents a profound opportunity. However, despite their huge potential, integrated water-energy-food-environment systems (iWEFEs) are rarely put into practice because of, among others, a lack of site-specific data and open tools to describe, model, and plan such integrated infrastructure systems. The project addresses this gap through open software developed in a scientific process and applied to respective case studies.The three main research and software development pillars of the project are the following:1. Conceptualization of open water, energy, food, and environment modeling framework –OWEFE enabling the development of an open iWEFEs component database2. Facilitation and automation of WEFE data collection and analysis - WEFE Site Analyst3. Development of a software-based configurator for site-tailored iWEFEs – iWEFEs ConfiguratorThe open software tools shall support small communities, end-users, and NGOs to improve localwater, energy, and food security while protecting the climate and the environment.
Hydrological Model Performance Assessment across several Moroccan Catchments: Investigating the Effect of Model Attributes, Catchment Features, and Precipitation Inputs
Authors: Jaffar Oumar , Hadri Abdessamad , El Khalki El Mahdi , Ait Naceur Khaoula , Saidi Mohamed El Mehdi , Tramblay Yves , Chehbouni Abdelghani
Published: March 2024

Hydrology research can benefit significantly from large-sample hydrology studies by offering the possibility for better hydrological models’ assessment and by providing a suitable ground for identifying catchment characteristics that influence model performance. In our study, we conducted a performance assessment of eight monthly lumped rainfall-runoff models (GR2M, XM, WM, VUB, abcd, DWBM, GR5M, and Wapaba) in 30 Moroccan catchments, forced by rainfall data from 34 rain gauges. During the study period 1983-2019, we investigated the relationship between model performance (quantified with KGE) and both model complexity and structural attributes. Furthermore, we conducted correlation analysis to explore possible connections between this performance and catchment features (more than 180 features were considered), and we additionally examined how the models respond to three precipitation input data, namely ERA5, CHIRPS, and PERSIANN-CDR. Our findings revealed that no hydrological model was the best (or the worst) across the entire set of catchments. The model performance was found to be more influenced by model structure than by its degree of complexity, and more by hydro-climatic characteristics, particularly those related to calibration and calibration relative to validation, than by non-hydro-climatic factors. Among the investigated features, the Pearson correlation between observed rainfall and runoff was the strongest characteristic influencing model performance. Furthermore, this study (i) emphasized the essential role of rainfall and runoff data richness, in terms of wet and dry years, in enhancing model performance even if the calibration data is only relatively richer than the validation data and (ii) showed that dry periods are more beneficial to model performance than wet ones. Finally, our study revealed a consistent pattern in the models’ responses to the different rainfall forcings; with ERA5 consistently yielding the best model performance and PERSIANN-CDR consistently resulting in underperformance. This consistent behavior of the models was best explained by the linearity between the employed rainfall products and the catchments' observed runoff.
AI/ML Augmented Hyper Local Weather Forecast
Authors: Huang Hung-Lung Allen
Published: March 2024

Our very recent artificial intelligence – machine learning (AI/ML) augmented wind energy production forecast has successfully demonstrated a consistent >30% wind speed and power generation forecast improvement over the NOAA operational High-Resolution Rapid Refresh (HRRR) standalone capability.So far, we have used a suite of AI/ML algorithms, including 1) artificial neural networks, 2) ridge regression, 3) lasso regression, 4) support vector machines, 5) gradient boosting, 6) elastic networks, 7) nearest neighboring clustering, and 8) random forest (RF) models for wind energy forecasting applications. These AI/ML augmented forecasts significantly improve the management of the power grid distribution, energy trading strategy, and plant operations with training and testing corresponding to 253 sites in Texas and validated on a year of independent testing data. It has shown that each AI/ML model offers significant forecast improvement (+20% mean squared error) skill over the current official HRRR forecasts. Furthermore, an AI/ML model ensemble of different machine learning models is deployed and demonstrated to significantly improve wind speed accuracy during all seasons, times of day, sites tested, and forecast horizon times.This fully matured AI/ML augmented framework has shown to be comprehensive and robust, demonstrating that AI/ML is a natural complement to the existing NWP infrastructure and can be expanded to enhance local forecasts. 
Cenozoic asthenospheric flow history in the Atlantic realm: Insights from Couette/Poiseuille flow models
Authors: Wang Zhirui Ray , Stotz Ingo L. , Bunge Hans-Peter , Vilacís Berta , Hayek Jorge N. , Ghelichkhan Sia , Lebedev Sergei
Published: March 2024

Mantle convection is an essential component of the Earth system. Yet its history is not well known , in part, as the strength of tectonic plates conceals the underlying flow. To date, global mantle convection models have reached an impressive level of sophistication due to significant advancement of computational infrastructures and numerical techniques. This ultimately allows geodynamicists to reconstruct past mantle states through using, for instance, inverse geodynamic models based on adjoint equations. However, key input parameters of these models --- such as thermo-chemical flow properties and rheology --- are complex and poorly known. This in turn limits their ability to effectively interpret the reconstructed mantle flow, thus motivating one to pursue an approach that aims to conceptualize paleo-mantle-flow at a simple analytical level.To this end, the existence of thin, mechanically weak asthenosphere permits one to develop an analytical Couette/Poiseuille model of asthenospheric flow, where flow is associated with moving tectonic plates, and with lateral pressure gradients due to rising plumes and sinking slabs. Here we present estimates of the Cenozoic asthenospheric flow history from such models in the Atlantic realm. We, moreover, link them to azimuthal seismic anisotropy as well as mantle flow retrodiction simulated by inverse geodynamic models. Our analytically derived asthenospheric flow indicates that it is in broad agreement with the orientation of seismic azimuthal anisotropy, and with the large-scale flow patterns from mantle flow retrodictions. In light of these results, our study suggests exploiting a hierarchy of geodynamic models together with growing observational constraints on mantle flow induced surface expressions to gain a better understanding of paleo-mantle-flow.
Strong light scattering of highly oxygenated organic aerosols impacts significantly on visibility degradation
Authors: Liu Li
Published: March 2024

    Secondary organic aerosols (SOAs) account for a large fraction of atmospheric aerosol mass and play significant roles in visibility impairment by scattering solar radiation. However, comprehensive evaluations of SOA scattering abilities under ambient relative humidity (RH) conditions on the basis of field measurements are still lacking due to the difficulty of simultaneously direct quantifications of SOA scattering efficiency in dry state and SOA water uptake abilities. In this study, field measurements of aerosol chemical and physical properties were conducted in winter in Guangzhou using a humidified nephelometer system and aerosol chemical speciation monitor. A modified multilinear regression model was proposed to retrieve dry-state mass scattering efficiencies (MSE, defined as scattering coefficient per unit aerosol mass) of aerosol components. The more oxidized oxygenated organic aerosol (MOOA) with O/C ratio of 1.17 was identified as the most efficient light scattering aerosol component. On average, 34% mass contribution of MOOA to total submicron organic aerosol mass contributed 51% of dry-state organic aerosol scattering. The overall organic aerosol hygroscopicity parameter κOA was quantified directly through hygroscopicity closure, and hygroscopicity parameters of SOA components were further retrieved using multilinear regression model by assuming hydrophobic properties of primary organic aerosols. The highest water uptake ability of MOOA among organic aerosol factors was revealed with κMOOA reaching 0.23, thus further enhancing the fractional contribution of MOOA in ambient organic aerosol scattering. In particular, the scattering abilities of MOOA was found to be even higher than those of ammonium nitrate under RH of
The slowdown of increasing groundwater storage in response to climate warming in the Tibetan Plateau
Authors: Wang Longhuan , Jia Binghao
Published: March 2024

The change of groundwater storage (GWS) on the Tibetan Plateau (TP) is vital for water resources management and regional sustainability, but its estimation has large uncertainty due to insufficient hydrological measurements and diverse future climate scenarios. Here, we employ high-resolution land surface modeling, advanced satellite observations, global climate model data, and deep learning to estimate GWS changes in the past and future. We find a 3.51±2.40 Gt yr-1 increase in GWS from 2002–2018, especially in exorheic basins, attributed to glacier melting. The GWS will persistently increase in the future, but the growth rate is slowing down (0.14 Gt yr-1 for 2079–2100). Increasing GWS is projected over most endorheic basins, which is associated with increasing precipitation and decreasing shortwave radiation. In contrast, decreasing GWS is projected over the headwaters of Amu Darya, Yangtze, and Yellow river basins. These insights have implications for sustainable water resource management in a changing climate.
Delineation of Groundwater Pollution Zones around Sewage Farm in the coastal area of Kerala, South India using Geographic Information System Technique
Authors: Varghese Jainy , Divakaran Sarasamma Jaya
Published: March 2024

Geographic Information System (GIS), a computer-based technique is used in groundwater management, especially for the estimation of groundwater vulnerability to contamination. The objective of the present study was to delineate the groundwater contamination zones around the Sewage Farm using Geographic Information System. The study area lies between North Latitude 8° 26ʹ 26ʺ to 8° 29' 29" and East Longitude 76° 54ʹ 51ʺ to 76° 57ʹ 33ʺ. Inverse Distance Weighted Method (IDW) interpolation technique was used for the delineation of groundwater pollution zones in the study area. The sampling locations were mapped with the help of Survey of India toposheet of the scale 1:25000 and a handheld Global Positioning System (GPS). Groundwater pollution (stress) zonation in the study area was done on the basis of the selected water quality parameters of 42 groundwater samples (29 dug wells and 13 tube wells) during pre-monsoon, monsoon and post-monsoon seasons. The highly significant water quality parameters selected for the present study included pH, total dissolved solids (TDS), total hardness (TH), total alkalinity (TA) and total coliforms (TC). TC was given more weightage among the selected parameters. Based on the analysis, the entire study area was classified into three distinct zones, viz., low, moderate and high pollution zones. The results of the present study suggested that the extent of groundwater pollution was relatively lower during monsoon, compared to pre-monsoon and post-monsoon seasons, which might be a reflection of enhanced dilution due to heavy monsoon rainfall occurring in the region. Further, during post-monsoon and pre-monsoon seasons, the areal extent of high pollution zone showed close similarity. From the GIS-based analysis for the delineation of groundwater pollution zones over the area, it was inferred that multiple sources such as Sewage Farm, leachates from soak pits/septic tanks and Parvathy Puthanar, a man-made canal, governed the deterioration of groundwater quality in the study area.
New Early Carboniferous paleomagnetic results from the Qaidam Block, Northern Tibetan Plateau
Authors: Chai Ruiyang , Zhou Yanan , Wu Hanning
Published: March 2024

The Qaidam Block, situated in the North Tibetan Plateau, is the nexus of the Tarim and North China Blocks. Since the scarcity of geological records documenting the collision age between the Qaidam and Tarim Blocks, the drift history of the Qaidam Block becomes imperative for gaining insights into the formation of East Eurasia. In this study, rock magnetic and paleomagnetic studies were performed on the early Carboniferous sedimentary rocks in the Huaitoutala area. A stable characteristic remanent magnetization component, carried by magnetite, was isolated from 24 sites (204 samples). This component passed the fold tests at a high level a mean yielding the paleopole position at λ=-24.9°N, φ=123.7°E, A95=3.9°. It corresponds to a paleolatitude of ~22.5°N for the QB about 350 Ma. Combined with paleomagnetic data and geological evidence from Qaidam Block and its adjacent regions, we suggest that a convergence between the Qaidam Block and the North China Block at 430-400 Ma, subsequently merged with the Tarim Block at approximately 260-250 Ma.
Simulating the Earth system with interactive aerosols at the kilometer scale
Authors: Weiss Philipp , Stier Philip
Published: March 2024

Aerosols originate from natural processes and human activities. They scatter and absorb radiation but also act as condensation nuclei in clouds. How these interactions influence the climate is still uncertain. New climate simulations at the kilometer-scale allow us to examine long-standing questions related to these interactions such as the complex effects on convective clouds. To perform kilometer-scale simulations with interactive aerosols, we developed the reduced-complexity aerosol module HAM-lite and coupled it to the climate model ICON-Sapphire. HAM-lite is based on and fully traceable to the complex aerosol module HAM. Aerosols are represented as an ensemble of log-normal modes with prescribed sizes and compositions.We present first global simulations with ICON-Sapphire and HAM-lite at resolutions of about five kilometers and over periods of a few months. The sea surface temperature and sea ice are prescribed with boundary conditions of AMIP, and the initial conditions of the atmosphere and land are derived from the operational analysis of ECMWF. The aerosols are represented by two pure modes, one of dust and one of sea salt, and two internally mixed modes, both of organic carbon, black carbon, and sulfate. The first mixed mode represents aerosols from biomass burning emissions and the second mixed mode represents aerosols from anthropogenic and volcanic emissions.The simulations capture key elements of the global aerosol cycle, of which some are missing entirely in coarse-scale simulations. For example, cold pool fronts drive intense dust storms over the Sahara and tropical cyclones interact with sea salt aerosols in the Pacific. We observe the transport of dust aerosols across the ocean, the wash out of sea salt aerosols by rain bands, and the updraft of biomass burning aerosols over land. We evaluate the observations with a combination of remote-sensing and in-situ data. We also compare the results to coarse-scale climate simulations. To understand processes like updraft by convection or deposition by rain, we examine the distribution of aerosols throughout the vertical column.