Hasil untuk "Physical geography"

Oussama Jabrane, Ilias Obda, Driss El Azzab et al.

The detection of underground cavities and dissolution features is a critical component in assessing geohazards within karst terrains, particularly where natural processes interact with long-term human occupation. This study investigates two contrasting sites in the Sefrou region of northern Morocco: Binna, a rural travertine-dolomite system shaped by Quaternary karstification, and the urban Old Medina of Bhalil, where traditional cave dwellings are carved into carbonate formations. A combined geophysical and geological approach was applied to characterize subsurface heterogeneities and assess the extent of near-surface void development. Vertical electrical soundings (VES) at Binna site delineated high-resistivity anomalies consistent with air-filled cavities, dissolution conduits, and brecciated limestone horizons, all indicative of an active karst system. In the Bhalil old Medina site, ground-penetrating radar (GPR) with low-frequency antennas revealed strong reflection contrasts and localized signal attenuation zones corresponding to shallow natural cavities and potential anthropogenic excavations beneath densely constructed areas. Geological observations, including lithostratigraphic logging and structural cross-sections, provided additional constraints on cavity geometry, depth, and spatial distribution. The integrated results highlight a high degree of subsurface karstification across both sites and underscore the associated geotechnical risks for infrastructure, cultural heritage, and land-use stability. This work demonstrates the value of combining electrical and radar methods with geological analysis for mapping hazardous subsurface voids in cavity-prone Quaternary landscapes, offering essential insights for risk mitigation and sustainable urban and rural planning.

Yi Cheng, Zongli Lin

The $q$-state Potts model is a fundamental model in statistical physics that generalizes the Ising model and plays a key role in the study of phase transitions, critical phenomena, complex systems, and combinatorial optimization. Sampling low-energy configurations of the $q$-state Potts model is essential to these studies, but it remains challenging. While physics-inspired dynamical sampling has been extensively explored for the Ising case ($q=2$) in the form of Ising machines, its generalization to general $q$-state Potts models remains largely unexplored. To fill this gap, we propose a class of physics-inspired dynamical samplers that directly target general $q$-state Potts models, which we refer to as the oscillator Potts machine (OPM). We show, through theoretical analysis and numerical experiments, that the OPM exhibits a systematic low-energy bias with respect to the underlying Potts energy landscape. Furthermore, we demonstrate, via phase perturbation analysis, that the OPM, as overdamped Langevin dynamics, can be realized with a network of self-sustaining oscillators, demonstrating that the OPM is naturally realizable in hardware using standard technology such as CMOS. We design a small-scale ring-oscillator circuit that implements a three-state OPM and validate its operation through transistor-level simulation. Leveraging the low-energy bias of the OPM for Potts models, we then apply it to large-scale max-$K$-cut problems by mapping these instances to $q$-state Potts Hamiltonians and compare its performance against established algorithms. Our results position the OPM as a promising, physically grounded dynamical system framework for multi-state sampling and combinatorial optimization.

Eugene A. Eliseev, Anna N. Morozovska, Sergei V. Kalinin et al.

Proximity ferroelectricity is a novel paradigm for inducing ferroelectricity, where a non-ferroelectric polar material, which is unswitchable with an external field below the dielectric breakdown field, becomes a practically switchable ferroelectric in direct contact with a thin switchable ferroelectric layer. Here, we develop a Landau-Ginzburg-Devonshire approach to study the proximity effect of local piezoelectric response and polarization reversal in wurtzite ferroelectric multilayers under a sharp electrically biased tip. Using finite element modeling we analyze the probe-induced nucleation of nanodomains, the features of local polarization hysteresis loops and coercive fields in the Al1-xScxN/AlN bilayers and three-layers. Similar to the wurtzite multilayers sandwiched between two parallel electrodes, the regimes of "proximity switching" (where the multilayers collectively switch) and the regime of "proximity suppression" (where they collectively do not switch) are the only two possible regimes in the probe-electrode geometry. However, the parameters and asymmetry of the local piezo-response and polarization hysteresis loops depend significantly on the sequence of the layers with respect to the probe. The physical mechanism of the proximity ferroelectricity in the local probe geometry is a depolarizing electric field determined by the polarization of the layers and their relative thickness. The field, whose direction is opposite to the polarization vector in the layer(s) with the larger spontaneous polarization (such as AlN), renormalizes the double-well ferroelectric potential to lower the steepness of the switching barrier in the "otherwise unswitchable" polar layers. Tip-based control of domains in otherwise non-ferroelectric layers using proximity ferroelectricity can provide nanoscale control of domain reversal in memory, actuation, sensing and optical applications.

Gerd Kortemeyer, Julian Nöhl

This study explores the use of artificial intelligence in grading high-stakes physics exams, emphasizing the application of psychometric methods, particularly Item Response Theory (IRT), to evaluate the reliability of AI-assisted grading. We examine how grading rubrics can be iteratively refined and how threshold parameters can determine when AI-generated grades are reliable versus when human intervention is necessary. By adjusting thresholds for correctness measures and uncertainty, AI can grade with high precision, significantly reducing grading workloads while maintaining accuracy. Our findings show that AI can achieve a coefficient of determination of $R^2\approx 0.91$ when handling half of the grading load, and $R^2 \approx 0.96$ for one-fifth of the load. These results demonstrate AI's potential to assist in grading large-scale assessments, reducing both human effort and associated costs. However, the study underscores the importance of human oversight in cases of uncertainty or complex problem-solving, ensuring the integrity of the grading process.

S. M. Hossain, S. S. Rahaman, H. Gujrati et al.

Disorder is ubiquitous in any quantum many-body system and is usually considered to be an obstacle to the elucidation of the underlying physics of complex systems, but its presence can often introduce exotic phases of matter that cannot generally be realized in a clean system. We report here a detailed experimental and theoretical study of magnetic properties of highly disordered Sr$_3$CuNb$_2$O$_9$ material which exhibits random site mixing between Cu and Nb. The magnetic moments (Cu$^{2+}$) are arranged in a quasi-cubic (three-dimensional) manner, leading to a high degree of frustration with a Curie-Weiss temperature ($θ_{CW}$) of about -60 K without any long-range magnetic ordering down to 466 mK. These observations suggest that Sr$_3$CuNb$_2$O$_9$ is a candidate for a quantum spin liquid. More interestingly, the susceptibility ($χ= M/μ_0H$) and the $C_m/T$ ($C_m$ is the magnetic part of the heat capacity) follow a power-law behavior with decreasing temperature. In addition, $M(T,μ_0H)$ and $C_m(T,μ_0H)/T$ show scaling relationships over a wide temperature and field range. This unusual behavior with respect to the conventional behavior of a QSL can be discussed qualitatively as the coexistence of a disorder-induced random spin singlet (RSS) state and a QSL state. A quantitative description has been given by numerical calculations considering a power-law probability distribution $P(J) \propto J^{-γ}$ ($J$ is the exchange interaction) of random spin singlets. The parameters extracted from the numerical calculations are in excellent agreement with the experimental data. Furthermore, the analytical results are also consistent with the power-law and scaling behavior of $χ$ and $C_m(T,μ_0H)/T$ as a whole. Thus, our comprehensive experimental and theoretical analysis provides evidence for the stabilization of the RSS state in a three-dimensional lattice.

Hazel Knight, Carl Stevenson, Marco Maffione et al.

Anisotropy of Magnetic Susceptibility (AMS) fabrics within many individual granite plutons have previously been interpreted as recording the regional syn-magmatic tectonic strain field. To test this hypothesis, we compiled a regional database of AMS data from multiple granite complexes across two orogens, the French Massif Central and the British and Irish Caledonides, and critically evaluated the degree to which the magnetic fabric of the granite plutons recorded the known, regional tectonic strain. AMS fabrics from nine plutons from the French Massif Central show that all intrusions recorded the syn-magmatic late Variscan extensional collapse, with the maximum susceptibility axes (i.e., magnetic lineation) aligned with the NW-SE regional stretching direction. AMS fabrics from ten late Caledonian ‘Newer Granite’ plutons appear to reliably record the changing tectonic regimes between 430 and 390 Ma, including the switch from transpression to transtension following Iapetus closure, and then the return to transpression following the onset of the Acadian Orogeny at 400 Ma. This study indicates that comparisons between AMS fabrics and regional tectonics is best achieved qualitatively by comparing the orientation of the susceptibility axes to the known strain field, and more quantitatively through Woodcock analysis. Overall, our results indicate that pluton-scale AMS fabrics from multiple complexes spaced across an orogen can record a complex and changing regional tectonic strain field. This indicates there is significant potential to utilise pluton-scale AMS studies, alongside precise geochronological ages, to refine the timings of an orogen’s tectonic evolution.

A. A. Araújo Filho

This study focuses on investigating a regular black hole within the framework of Verlinde's emergent gravity. In particular, we explore the main aspects of the modified Simpson--Visser solution. Our analysis reveals the presence of a unique physical event horizon under certain conditions. Moreover, we study the thermodynamic properties, including the Hawking temperature, the entropy, and the heat capacity. Based on these quantities, our results indicate several phase transitions. Geodesic trajectories for photon-like particles, encompassing photon spheres and the formation of black hole shadows, are also calculated to comprehend the behavior of light in the vicinity of the black hole. Additionally, we also provide the calculation of the time delay and the deflection angle. Corroborating our results, we include an additional application in the context of high-energy astrophysical phenomena: neutrino energy deposition. Finally, we investigate the quasinormal modes using third-order WKB approximation.

Kosmas Pavlopoulos, Daniel Moraetis, Michael Foumelis et al.

Abstract Eustatic sea level changes and vertical tectonic movements are producing uplifted paleoshorelines. Along subduction zones, uplifted terraces are used to study fault activities and, overall, allow to interpret the tectonic history of plate convergence. Northeastern Oman is experiencing plate convergence following the late Cretaceous obduction of the Semail Ophiolite. Post‐obduction shallow‐marine carbonates have been uplifted to different elevations from 133 to >2,000 m. The present study employs a multidisciplinary approach to elucidate the variability in relief and to introduce a geodynamic model that extends beyond the temporal constraints imposed by the late Quaternary age of the sediments found on the uplifted terraces. Stratigraphic and fault analyses produced a post‐obductional geodynamic model to advance the existing regional models in the framework of the subduction of the Arabian Plate in the Makran Zone. In addition, we rely on imaging geodesy, geomorphology and dating to explain the late Quaternary uplift scenario. Overall, analyses of geomorphology, stratigraphy, and fault patterns reveal spatially heterogeneous post‐late Cretaceous uplift in the region. Compartmentalization by major faults created individual blocks and relief variability. Within the timeframe of marine terrace formation (late Quaternary), we also observed spatially varied displacements. Ground displacements by Interferometric Synthetic Aperture Radar document an ongoing spatial heterogenous uplift at approximately 1.3 mm/a. Finally, temporal variability was evident during the late Quaternary by unusually high late Pleistocene (<40 ka) uplift rates averaging ≥2 mm/a in younger terraces, while for older terraces (>40 ka) the uplift rate is distinctly lower (<1 mm/a).

Weiguo Wang, Zhan Zhang, John P. Cangialosi et al.

This paper summarizes the progress and activities of tropical cyclone (TC) operational forecast centers during the last four years (2018–2021). It is part II of the review on TC intensity change from the operational perspective in the rapporteur report presented to the 10th International Workshop on TCs (IWTC) held in Bali, Indonesia, from Dec. 5–9, 2022. Part I of the review has focused on the progress of dynamical model forecast guidance. This part discusses the performance of TC intensity and rapid intensification forecasts from several operational centers. It is shown that the TC intensity forecast errors have continued to decrease since the 9th IWTC held in 2018. In particular, the improvement of rapid intensification forecasts has accelerated, compared with years before 2018. Consensus models, operational procedures, tools and techniques, as well as recent challenging cases from 2018 to 2021 identified by operational forecast centers are described. Research needs and recommendations are also discussed.

Bingwei Wang, Qigen Lin, Tong Jiang et al.

Machine learning models are gradually replacing traditional techniques used for landslide susceptibility assessment. This study aims to comprehensively compare multiple models, including linear, nonlinear, and ensemble models, based on 5281 historical landslides in southwest China, the area most severely affected by the landslide disaster. Linear models represented by logistic regression (LR), nonlinear models represented by support vector machine (SVM), artificial neural network (ANN) and classification 5.0 decision tree (C5.0 DT), and ensemble models represented by random forest (RF) and categorical boosting (Catboost) were selected. The correlation coefficient, variance inflation factor (VIF), and relative important analysis were used to select the dominate landslide conditioning factors. Using multiple statistical indicators (e.g. Area Under the Receiver Operating Characteristic curve (AUC) and Kappa), cross-validation and qualitative methods to evaluate the models’ performance. The findings are: (1) Regarding the model predictive performance, the best predictive performance was demonstrated by the ensemble models Catboost (AUC = 0.823 and Kappa = 0.593) and RF (AUC = 0.821 and Kappa = 0.582), followed by the nonlinear models SVM (AUC = 0.775 and Kappa = 0.520), ANN (AUC = 0.770 and Kappa = 0.486) and C5.0 DT (AUC = 0.751 and Kappa = 0.497), while the linear model LR (AUC = 0.756 and Kappa = 0.456) had a more limited performance. The ensemble model, which uses a tree as its baseline classifier, has a lot of potential for studies into the landslide susceptibility. (2) Regarding the model robustness, the three types of models in nonspatial cross-validation (CV) performed relatively similarly in terms of predictive power, while in spatial cross-validation (SPCV), the linear model LR (median AUC = 0.714) achieved better results than the ensemble and nonlinear models. It implies that when the distribution of landslides is not homogeneous, linear models may be the most robust. It is advisable to consider various evaluation metrics from different perspectives and integrate them with specialist qualitative geomorphological empirical knowledge to determine the best model. (3) The Gini index-based RF model suggests that road density was the dominant factor in the frequency of landslides in the study area.

Sina Khani, Clinton N. Dawson

Abstract Mesoscale eddies play an important role in transport of heat and biogeochemical tracers in the global ocean circulation. Resolving these energetic eddies, however, is challenging in ocean general circulation models (OGCM) because it requires a horizontal grid spacing of ≲1/8° that is computationally expensive. As a result, we are required to parameterize mesoscale eddy effects on large‐scale ocean flows. In this work, we introduce a new subgrid‐scale (SGS) model that is developed based on a Taylor series expansion of resolved variables to parameterize subgrid mesoscale eddy transports and momentum fluxes in OGCM. We have performed an a priori study to evaluate the performance of our new gradient model using high‐resolution ocean simulations. Our results show that the gradient model well predicts the actual SGS thickness fluxes in the zonal and meridional directions in coarse‐resolution simulations with the grid spacing ≳1/4°. The unresolved kinetic energy at the ocean surface is also skillfully estimated. More importantly, unlike current mesoscale eddy parameterizations, which are mainly developed based on an assumption of flat bottom ocean, our new SGS model can capture the structure of unresolved standing meanders at the ocean surface. We have also developed a dynamic procedure for setting in non‐dimensional parameters in our new parameterization through a non‐ad hoc and tuning‐free method. Overall, this work suggests that implementing the gradient model in OGCM can improve the model accuracy with an affordable computational cost in eddy‐permitting and non‐eddying simulations.

U. C. Perera, A. V. Afanasjev

The detailed investigation of microscopic mechanisms leading to the formation of bubble structures in the nuclei has been performed in the framework of covariant density functional theory. The main emphasis of this study is on the role of single-particle degrees of freedom and Coulomb interaction. In general, the formation of bubbles lowers the Coulomb energy. However, in nuclei this trend is counteracted by the quantum nature of the single-particle states: only specific single-particle states with specific density profiles can be occupied with increasing proton and neutron numbers. A significant role of central classically forbidden region at the bottom of the wine bottle potentials in the formation of nuclear bubbles (via primarily the reduction of the densities of the $s$ states at $r=0$) has been revealed for the first time. Their formation also depends on the availability of low-$l$ single-particle states for occupation since single-particle densities represent the basic building blocks of total densities. Nucleonic potentials disfavor the occupation of such states in hyperheavy nuclei and this contributes to the formation of bubbles in such nuclei. Additivity rule for densities has been proposed for the first time. It was shown that the differences in the densities of bubble and flat density nuclei follow this rule in the $A\approx 40$ mass region and in superheavy nuclei with comparable accuracy. This strongly suggests the same mechanism of the formation of central depression in bubble nuclei of these two mass regions. Nuclear saturation mechanisms and self-consistency effects also affect the formation of bubble structures. The detailed analysis of different aspects of bubble physics strongly suggests that the formation of bubble structures in superheavy nuclei is dominated by single-particle effects.

Maria Méndez Real, Rubén Salvador

During the last decade, Deep Neural Networks (DNN) have progressively been integrated on all types of platforms, from data centers to embedded systems including low-power processors and, recently, FPGAs. Neural Networks (NN) are expected to become ubiquitous in IoT systems by transforming all sorts of real-world applications, including applications in the safety-critical and security-sensitive domains. However, the underlying hardware security vulnerabilities of embedded NN implementations remain unaddressed. In particular, embedded DNN implementations are vulnerable to Side-Channel Analysis (SCA) attacks, which are especially important in the IoT and edge computing contexts where an attacker can usually gain physical access to the targeted device. A research field has therefore emerged and is rapidly growing in terms of the use of SCA including timing, electromagnetic attacks and power attacks to target NN embedded implementations. Since 2018, research papers have shown that SCA enables an attacker to recover inference models architectures and parameters, to expose industrial IP and endangers data confidentiality and privacy. Without a complete review of this emerging field in the literature so far, this paper surveys state-of-the-art physical SCA attacks relative to the implementation of embedded DNNs on micro-controllers and FPGAs in order to provide a thorough analysis on the current landscape. It provides a taxonomy and a detailed classification of current attacks. It first discusses mitigation techniques and then provides insights for future research leads.

B. Schmidt, J. Sichelschmidt, K. M. Ranjith et al.

While the Heisenberg model for magnetic Mott insulators on planar lattice structures is comparatively well understood in the case of transition metal ions, the intrinsic spin-orbit entanglement of 4f magnetic ions on such lattices shows fascinating new physics largely due to corresponding strong anisotropies both in their single-ion and their exchange properties. We show here that the Yb delafossites, containing perfect magnetic Yb$^{3+}$ triangular lattice planes with pseudospin $s=1/2$ at low temperatures, are an ideal platform to study these new phenomena. Competing frustrated interactions may lead to an absence of magnetic order associated to a gapless spin liquid ground state with a huge linear specific heat exceeding that of many heavy fermions, whereas the application of a magnetic field induces anisotropic magnetic order with successive transitions into different long ranged ordered structures. In this comparative study, we discuss our experimental findings in terms of a unified crystal-field and exchange model. We combine electron paramagnetic resonance (EPR) experiments and results from neutron scattering with measurements of the magnetic susceptibility, isothermal magnetization up to full polarization, and specific heat to determine the relevant model parameters. The impact of the crystal field is discussed as well as the symmetry-compatible form of the exchange tensor, and we give explicit expressions for the anisotropic g factor, the temperature dependence of the susceptibility, the exchange-narrowed EPR linewidth and the saturation field.

V. Abraham, S. Hicks, S. Hicks et al.

<p>The collection of modern, spatially extensive pollen data is important for the interpretation of fossil pollen assemblages and the reconstruction of past vegetation communities in space and time. Modern datasets are readily available for percentage data but lacking for pollen accumulation rates (PARs). Filling this gap has been the motivation of the pollen monitoring network, whose contributors monitored pollen deposition in modified Tauber traps for several years or decades across Europe. Here we present this monitoring dataset consisting of 351 trap locations with a total of 2742 annual samples covering the period from 1981 to 2017. This dataset shows that total PAR is influenced by forest cover and climate parameters, which determine pollen productivity and correlate with latitude. Treeless vegetation produced PAR values of at least 140 grains cm<span class="inline-formula">⁻²</span> yr<span class="inline-formula">⁻¹</span>. Tree PAR increased by at least 400 grains cm<span class="inline-formula">⁻²</span> yr<span class="inline-formula">⁻¹</span> with each 10 % increase in forest cover. Pollen traps situated beyond 200 km of the distribution of a given tree species still collect occasional pollen grains of that species. The threshold of this long-distance transport differs for individual species and is generally below 60 grains cm<span class="inline-formula">⁻²</span> yr<span class="inline-formula">⁻¹</span>. Comparisons between modern and fossil PAR from the same regions show similar values. For temperate taxa, modern analogues for fossil PARs are generally found downslope or southward of the fossil sites. While we do not find modern situations comparable to fossil PAR values of some taxa (e.g. <i>Corylus</i>), <span class="inline-formula">CO₂</span> fertilization and land use may cause high modern PARs that are not documented in the fossil record. The modern data are now publicly available in the Neotoma Paleoecology Database and aid interpretations of fossil PAR data.</p>

Олександр Василенко

Formulation of the problem. Currently, interest in the foundation as a gas and oil field facility has increased significantly. The low efficiency of oil and gas exploration in the basement rocks is usually explained by the absence of a generally accepted hypothesis about the genesis of oil and gas and as a result of migration and accumulation of hydrocarbons. One of the main factors of accumulation is the presence of decompression zones of the foundation, as potential hydrocarbon traps. The article is devoted to the problem of identifying oil and gas bearing zones of foundation decompression. Analysis of recent research and publications. A number of scientific articles on the composition, age, structure and oil and gas potential of the foundation are analyzed. The first step in identifying decompression zones is to conduct gravimetric and magnetic surveys and apply various techniques to interpret the resulting mathematical model of the wave field pattern in order to localize the sources of its anomalies. Identification of previously unresolved parts of a common problem. In order to save money when conducting prospecting and exploration for oil and gas, the foundation proposes an improvement in the methodology for separating gas-bearing “vaulted” parts of decompression zones. Formation of the purpose of the article. The aim of the work is to establish a seismic pattern of anomalies in the geophysical fields of the base decompression zones. The object of research is the zone of decompression of the foundation on the northern side of the Dnieper-Donets depression. The subject of the study is a seismic drawing of the anomaly of the geophysical field of the gas-bearing zone of decompression of the foundation of the Rozsoshinsk structure. Report of the main material. The article analyzes a few materials to identify areas of base decompaction in various oil and gas regions. It was found that for localization of decompression zones, the Berezkin “singular points” method and the correlation method of separation of geophysical anomalies are most effective. The essence of these methods is a kind of filtering of field anomalies, where against the background of the "structural" factor, one can distinguish the "non-structural factor", i.e. decompression zone. This zone in wave fields (∆g and ∆Т) is fixed by a seismic pattern, where minima are usually fixed over hydrocarbon accumulations in relation to contouring maxima. Based on the results of the application of these methods, the structure-testing ground of the gas-bearing decompression zone is established. As an illustrative example of the successful localization of ∆g and ∆Т, data are presented on modeling the foundation softening zone in one of the oil and gas regions of the northern side of the Dnieper-Donets depression.

Jia Tian, Shanshan Su, Qingjiu Tian et al.

Non-photosynthetic vegetation (NPV) is an essential component in various vegetation-soil ecosystems. Both phenology and disturbance lead to a transition from photosynthetic vegetation to NPV and vice versa. Due to the similar spectral reflectance of NPV and bare soil (BS) in the visible-near infrared region (400–1000 nm), NPV and BS separation is relying on the shortwave infrared (SWIR) bands in most cases. The lignin and cellulose absorption feature is around 2100 nm, which is the most distinctive feature of NPV. However, the water absorption feature is much stronger in the SWIR, increasing the difficulty for NPV-BS separation when wet. Recently, Sentinel-2/3 satellites add more bands in the near infrared (NIR), which provide an extra opportunity for index building and application. Based on the difference captured by derivative spectra, a spectral index, NPV-Soil Separation Index (NSSI), is proposed to realize the separation using two NIR bands within 750–900 nm range in this study. Using spectra of photosynthetic vegetation (PV), NPV, and BS acquired from world-recognized spectral libraries, NSSI is built and validated as effective for lab-collected data. With the triangle method, one of the linear spectral unmixing methods, the fractional cover of PV, NPV, and BS can be estimated. Over a woodland study area, the fractional cover retrieved by cellulose absorption index (CAI) and NDVI combination of ZY1-02D AHSI hyperspectral image is 26.41%, 37.56%, 36.03% for PV, NPV, and BS in order. With the proposed NSSI-NDVI combination, the corresponding estimated fractional cover is 23.31%, 38.44%, 38.25% using Sentinel-2 MSI and 24.58%, 36.74%, and 38.68% using Sentinel-3 OLCI image. The comparable validation result confirms that the proposed NSSI is effective for NPV-BS separation. Moreover, the triangle method of NSSI-NDVI combination is applied on both grassland and cropland images to examine its feasibility on varied types of typical vegetation-soil ecosystems, and the well-built triangular space supports its feasibility. Relying on NIR bands, NSSI can avoid strong water absorption in the SWIR. Also, the feasibility of NSSI being used on multiple multispectral satellite sensors, especially the Sentinel series, makes continuous mapping for NPV over a large spatial scale possible.

Ryan Sayer, Alexandru Maries, Chandralekha Singh

Learning quantum mechanics is challenging, even for upper-level undergraduate and graduate students. Research-validated interactive tutorials that build on students' prior knowledge can be useful tools to enhance student learning. We have been investigating student difficulties with quantum mechanics pertaining to the double-slit experiment in various situations that appear to be counterintuitive and contradict classical notions of particles and waves. For example, if we send single electrons through the slits, they may behave as a "wave" in part of the experiment and as a "particle" in another part of the same experiment. Here we discuss the development and evaluation of a research-validated Quantum Interactive Learning Tutorial (QuILT) which makes use of an interactive simulation to improve student understanding of the double-slit experiment and strives to help students develop a good grasp of foundational issues in quantum mechanics. We discuss common student difficulties identified during the development and evaluation of the QuILT and analyze the data from the pretest and post test administered to the upper-level undergraduate and first-year physics graduate students before and after they worked on the QuILT to assess its effectiveness. These data suggest that on average, the QuILT was effective in helping students develop a more robust understanding of foundational concepts in quantum mechanics that defy classical intuition using the context of the double-slit experiment. Moreover, the upper-level undergraduates outperformed physics graduate students on the post test. One possible reason for this difference in performance may be the level of student engagement with the QuILT due to the grade incentive. In the undergraduate course, the post test was graded for correctness while in the graduate course, it was only graded for completeness.

Innocent Lugodisha, Hans C. Komakech, Shinji Nakaya et al.

In Arusha urban, northern Tanzania, groundwater contributes about 80% of the water supply. However, elevated fluoride levels and evidence of anthropogenic pollution have been reported in the groundwater around Mount Meru which is a water source for Arusha urban. This study aims at understanding the recharge areas and flow pathways of groundwater in what has been a poorly monitored area. The study uses the isotopic ratio of oxygen and hydrogen to estimate the groundwater recharge area and flow pathway. The results show the recharge elevation of groundwater is between 1,800 and 3,500 m above mean sea level on the slopes of Mount Meru. The average fluoride contents in the study area are 5.3 ± 0.4 mg/L greater than the limits of 1.5 mg/L set by the World Health Organization (WHO) and Tanzania. The nitrate concentration of 83.9 mg/L at the lower elevation areas (<1,400 m above mean sea level) exceeds the 50 mg/L WHO limit. The relationship of F− with δ18O and NO3− suggests the leaching of fluoride in high altitudes and dilution in lower altitudes. HIGHLIGHTS Management of groundwater resources is essential to maintain the supply of freshwater.; Adequate and precise demarcation of the groundwater area for protection is critical.; Isotopic ratio of oxygen and hydrogen is used to estimate the recharge area and flow pathway.; Meteoric water is the source of groundwater recharge in Mount Meru watershed.;

R. Rios‐Berrios, B. Medeiros, G. H. Bryan

Abstract Aquaplanet experiments are important tools for understanding and improving physical processes simulated by global models; yet, previous aquaplanet experiments largely differ in their representation of subseasonal tropical rainfall variability. This study presents results from aquaplanet experiments produced with the Model for Prediction Across Scales‐Atmosphere (MPAS‐A)—a community model specifically designed to study weather and climate in a common framework. The mean climate and tropical rainfall variability simulated by MPAS‐A with varying horizontal resolution were compared against results from a recent suite of aquaplanet experiments. This comparison shows that, regardless of horizontal resolution, MPAS‐A produces the expected mean climate of an aquaplanet framework with zonally symmetric but meridionally varying sea‐surface temperature. MPAS‐A, however, has a stronger signal of tropical rainfall variability driven by convectively coupled equatorial waves. Sensitivity experiments with different cumulus parameterizations, physics packages, and vertical grids consistently show the presence of those waves, especially equatorial Kelvin waves, in phase with lower‐tropospheric convergence. Other models do not capture such rainfall‐kinematics phasing. These results suggest that simulated tropical rainfall variability depends not only on the cumulus parameterization (as suggested by previous studies) but also on the coupling between physics and dynamics of climate and weather prediction models.