Surface Grid Research Articles

A kernel-free boundary integral method for the nonlinear Poisson-Boltzmann equation

This work proposes a boundary integral formulation based Cartesian grid method for the nonlinear Poisson-Boltzmann (PB) interface problem in biophysics. The method (a) does not have the limitation associated with the standard finite difference method for complex interfaces, (b) avoids the generation of any unstructured volume or surface grids needed by the finite element method, and (c) solves the nonlinear and variable coefficient PDE in the framework of boundary integral equations. The method solves the nonlinear PB equation with the Newton iterative method. It first reformulates the linearized PB equation in each Newton iteration as a Fredholm system of two boundary integral (BI) equations of the second kind, which is well-conditioned, and then solves the BI system with a Krylov subspace method. The evaluation of boundary and volume integrals involved in the solution of the BI system is done with a kernel-free method, which does not need to know Green's function associated with the variable coefficient PB equation. The kernel-free method evaluates volume and boundary integrals by solving equivalent simple interface problems on Cartesian grids with either a fast Fourier transform based Poisson solver or a geometric multigrid preconditioned conjugate gradient solver, either of which involves computational work essentially linearly proportional to the number of nodes on the Cartesian grid. Numerical examples in both two and three space dimensions are presented to demonstrate the efficiency and accuracy of the proposed numerical method.

Long-term exposure to summer specific humidity and cardiovascular disease hospitalizations in the US Medicare population

IntroductionMost climate-health studies focus on temperature; however, less is known about health effects of exposure to atmospheric moisture. Humid air limits sweat evaporation from the body and can in turn exert strain on the cardiovascular system. We evaluated associations of long-term exposure to summer specific humidity with cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization. MethodsWe built an open cohort consisting of ∼63 million fee-for-service Medicare beneficiaries, aged ≥65, living in the contiguous US (2000–2016). We assessed zip code level summer average specific humidity and specific humidity variability, based on daily estimates from the Gridded Surface Meteorological dataset (∼4km spatial resolution). To estimate associations of summer specific humidity with first CVD, CHD, and CBV hospitalization, we used Cox-equivalent Poisson models adjusted for individual and area-level socioeconomic status indicators, temperature, and winter specific humidity. ResultsHigher summer average specific humidity was associated with an increased risk of CVD, CHD, and CBV hospitalization. We found hazard ratios (HRs) of 1.07 (95%CI: 1.07, 1.08) for CVD hospitalization, 1.08 (95%CI: 1.08, 1.09) for CHD hospitalization, and 1.07 (95%CI: 1.07, 1.08) for CBV hospitalization per IQR increase (4.0 g of water vapor/kg of dry air) in summer average specific humidity. Associations of summer average specific humidity were strongest for beneficiaries eligible for Medicaid and for beneficiaries with an unknown or other race. Higher summer specific humidity variability was also associated with increased risk of CVD, CHD, and CBV hospitalization. Associations were not affected by adjustment for temperature and regions of the US, as well as exclusion of potentially prevalent cases. ConclusionLong-term exposure to higher summer average specific humidity and specific humidity variability were positively associated with CVD hospitalization. As global warming could increase humidity levels, our findings are important to assess potential health impacts of climate change.

Larger and Denser: An Optimal Design for Surface Grids of EMG Electrodes to Identify Greater and More Representative Samples of Motor Units.

The spinal motor neurons are the only neural cells whose individual activity can be noninvasively identified. This is usually done using grids of surface electromyographic (EMG) electrodes and source separation algorithms; an approach called EMG decomposition. In this study, we combined computational and experimental analyses to assess how the design parameters of grids of electrodes influence the number and the properties of the identified motor units. We first computed the percentage of motor units that could be theoretically discriminated within a pool of 200 simulated motor units when decomposing EMG signals recorded with grids of various sizes and interelectrode distances (IEDs). Increasing the density, the number of electrodes, and the size of the grids, increased the number of motor units that our decomposition algorithm could theoretically discriminate, i.e., up to 83.5% of the simulated pool (range across conditions: 30.5-83.5%). We then identified motor units from experimental EMG signals recorded in six participants with grids of various sizes (range: 2-36 cm2) and IED (range: 4-16 mm). The configuration with the largest number of electrodes and the shortest IED maximized the number of identified motor units (56 ± 14; range: 39-79) and the percentage of early recruited motor units within these samples (29 ± 14%). Finally, the number of identified motor units further increased with a prototyped grid of 256 electrodes and an IED of 2 mm. Taken together, our results showed that larger and denser surface grids of electrodes allow to identify a more representative pool of motor units than currently reported in experimental studies.

Wind power estimation on local scale—A case study of representativeness of reanalysis data and data-driven analysis

IntroductionWith hydropower being the dominant source of renewable energy in Austria and recent years being disproportionally dry, alternative renewable energy sources need to be tapped to compensate for the reduction of fossil fuels and account for dry conditions. This becomes even more important given the current geopolitical situation. Wind power plays an essential role in decarbonizing Austria's electricity system. For local assessments of historic, recent, and future wind conditions, adequate climate data are essential. Reanalysis data, often used for such assessments, have a coarse spatial resolution and could be unable to capture local wind features relevant for wind power modeling. Thus, raw reanalysis data need post-processing, and the results need to be interpreted with care. The purpose of this study is to assess the quality of three reanalysis data sets, such as MERRA-2, ERA5, and COSMO-REA6, for both surface level and hub height wind speed and wind power production at meteorological observation sites and wind farms in flat and mountainous terrain. Furthermore, the study aims at providing a first knowledge baseline toward generating a novel wind speed and wind power atlas at different hub heights for Austria with a spatial resolution of 1 × 1 km and for an experimental region with sub-km resolution. Thus, the study tries to answer (i) the questions if the reanalysis and analysis data can reproduce surface-level wind speed and (ii) if wind power calculations based on these data can be trusted, providing a knowledge base for future wind speed and wind power applications in complex terrain.MethodsFor that purpose, a generalized additive model (GAM) is applied to enable a data-driven gridded surface wind speed analysis as well as extrapolation to hub heights as a first step toward generating a novel wind speed atlas. In addition, to account for errors due to the coarse grid of the re-analysis, the New European Wind Atlas (NEWA) and the Global Wind Atlas (GWA) are used for correction using an hourly correction factor accounting for diurnal variations. For the analysis of wind power, an empirical turbine power curve approach was facilitated and applied to five different wind sites in Austria.Results and discussionThe results showed that for surface-level wind speed, the GAM outperforms the reanalysis data sets across all altitude levels with a mean average error (MAE) of 1.65 m/s for the meteorological sites. It even outperforms the NEWA wind atlas, which has an MAE of 3.78 m/s. For flat regions, the raw reanalysis matches the production data better than NEWA, also for hub height wind speeds, following wind power. For the mountainous areas, a correction of the reanalysis data based on the NEWA climatology, or even the NEWA climatology itself, significantly improved wind power evaluations. Comparisons between modeled wind power time series and real data show mean absolute errors of 8% of the nominal power in flat terrain and 14 or 17% in mountainous terrain.

Simulation of a Radio Signal Scattered from a Rough Surface by the Method of Stationary Points

Introduction. Many radar and radio navigation problems require adequate (i.e., corresponding to the physics of radio wave scattering under a certain set of conditions) simulation of a radio signal scattered from a rough surface. At present, four categories of mathematical models are used for these purposes, with each corresponding to a particular group of methods for solving the scattering problem. These methods include those based on a rigorous solution of the electrodynamic equations (methods of moments, finite elements, finite differences); approximate methods for solving electrodynamic problems (methods of small perturbations, tangent plane (Kirchhoff method), two-scale model); those of statistical equivalents; and phenomenological models. In the former two categories, the electromagnetic field is computed on a surface grid, whose step must be much smaller than the signal wavelength. This makes the simulation of a scattered radio signal effectively unrealizable for two-dimensional rough surfaces. The method of statistical equivalents is based on the calculation of the probabilistic characteristics of a scattered signal. Difficulties arising in this case narrow the possibilities of simulation, largely due to the impossibility of obtaining closed expressions for the required characteristics without significant simplifications. In addition, carrying out analytical calculations, the solution is restricted to the class of surfaces with the Gaussian distribution of roughness heights. Phenomenological models, although providing for a qualitative analysis of signal scattering from a rough surface, fail to take the physics of the scattering process into account.Aim. To create a simple and adequate model of a signal scattered from a two-dimensional rough surface using the tangent plane approximation of the boundary conditions (the Kirchhoff method), which can be realized on modern computers.Materials and methods. The proposed model of the scattered signal is based on its representation as a sum of signals reflected from stationary points on the surface, i.e., those points where the law of specular reflection of the incident electromagnetic wave is locally fulfilled.Results. The implementation of the model is reduced to determination of the positions of stationary points on a twodimensional rough surface. This problem is solved on modern computers quite simply without computations with complex numbers. It turns out that the number of stationary points, even with a large surface roughness, rarely exceeds two. This fact, along with the simplicity of finding the coordinates of stationary points, makes this model suitable for long series of statistical runs.Conclusion. The proposed model is easy to implement and can be used to study the accuracy of low-altitude target estimation, altimeters, Doppler and correlation speed and drift angle estimators.

Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Superresolution Convolutional Neural Networks

Abstract Surrogate modeling is one of the most promising applications of deep learning techniques in meteorology. The purpose of this study was to downscale surface wind fields in a gridded format at a much lower computational load. We employed a superresolution convolutional neural network (SRCNN) as a surrogate model and created a 20-member ensemble by training the same SRCNN model with different random seeds. The downscaling accuracy of the ensemble mean remained stable throughout a year and was consistently better than that of the input wind fields. It was confirmed that 1) the ensemble spread was efficiently created and that 2) the ensemble mean was superior to individual ensemble members and 3) robust to the presence of outlier members. Training, validation, and test data for 10 years were computed via our nested mesoscale weather forecast models not derived from public analysis datasets or real observations. The predictands were 1-km gridded surface zonal and meridional winds, of which the domain was defined as a 180 km × 180 km area around Tokyo, Japan. The predictors included 5-km gridded surface zonal and meridional winds, temperature, humidity, vertical gradient of the potential temperature, elevation, and land-to-water ratio as well as 1-km gridded elevation and land-to-water ratio. Although a perfect surrogate of the weather forecast model could not be achieved, the SRCNN downscaling accuracy could likely enable us to apply this approach in high-resolution advection simulations, considering its overwhelmingly high prediction speed.

Segmented research and parameter optimization of double-layer vibrating screen

PurposeThe purpose of this paper is to study the screen surface parameters of the double deck vibrating screen, in sections, to determine the influence of each part of the screen surface on the screening efficiency of the vibrating screen. Finally, the best screening parameters were calculated to obtain the best screening performance.Design/methodology/approachIn this paper, the discrete element method is used to simulate the process of two-layer subsection screening. Response surface test was used to analyze the influence of various factors and their interactions on screening results. Finally, based on the binomial regression model of screening efficiency, the optimal combination of vibration parameters is calculated.FindingsIn the screening process of vibrating screen, due to the different screening environments in each area of the screen surface, the single-layer linear vibrating screen with equal screen surface parameters cannot obtain the best screening performance. Among the single factors, the effect of vibration frequency is the most significant.Originality/valueTo address the issue of single layer linear vibrating screens with equal screen surface parameters being unable to maintain optimal screening performance when handling large amounts of materials. This article proposes a double layer vibrating screen with different screen surface grids and screen surface angles to address the problem of low screening performance of traditional single layer linear vibrating screens.

Roles of chemistry modification for surface wettability of Polyether-Ether-Ketone (PEEK) by ultraviolet laser ablation

Tailoring the functionality of Polyether-ether-ketone (PEEK) is critical for enhancing its application, which can be accomplished by the modification of surface morphology and chemistry. In the present work, we experimentally demonstrate the correlation of modified chemical composition of textured PEEK surface by 355 nm UV nanosecond pulsed laser ablation with enhanced surface wettability. Specifically, the impact of UV laser processing parameters on microgroove morphology and ablated surface quality of PEEK surface is evaluated, with which high precision grid surface textures with uniform ablation quality are fabricated. The modification of chemical elements and functional groups of textured PEEK surface by the laser ablation is further analyzed by XPS spectra characterization, which demonstrates the substantial change of C=O and O–C=O bonds, as well as freshly generated polar carboxylic acid groups. Experimental results indicate that the surface composition modification greatly increases surface polarity and surface free energy of textured PEEK surface accompanied by enhanced surface wettability.

Boxes-Based Representation and Data Sharing of Road Surface Friction for CAVs

Vehicles can easily lose control unexpectedly when encountering unforeseen hazardous road friction conditions. With automation and connectivity increasingly available to assist drivers, vehicle performance can significantly benefit from a road friction preview map, particularly to identify where and how friction ahead of a vehicle may be suddenly decreasing. Although many techniques enable the vehicle to measure the local friction as driving upon a surface, these encounters limit the ability of a vehicle to slow down before a low-friction surface is already encountered. Using the connectivity of connected and autonomous vehicles (CAVs), a global road friction map can be created by aggregating information from vehicles. A challenge in the creation of these global friction maps is the very large quantity of data involved, and that the measurements populating the map are generated by vehicle trajectories that do not uniformly cover the grid. This paper presents a road friction map generation strategy that aggregates the measured road-tire friction coefficients along the individual trajectories of CAVs into a road surface grid. In addition, through clustering the friction grids further, an insight of this work is that the friction map can be represented compactly by rectangular boxes defined by a pair of corner coordinates in space, a friction value, and a confidence interval within the box. To demonstrate the method, a simulation is presented that integrates traffic simulations, vehicle dynamics and on-vehicle friction estimators, and a highway road surface, where friction is changing in space, particularly over a bridge segment. The experimental results indicate that the road friction distribution can be measured effectively by collecting and aggregating the friction data from CAVs.

Synthesizing Sea Surface Temperature and Satellite Altimetry Observations Using Deep Learning Improves the Accuracy and Resolution of Gridded Sea Surface Height Anomalies

AbstractGridded sea surface height (SSH) maps estimated from satellite altimetry are widely used for estimating surface ocean geostrophic currents. Satellite altimeters observe SSH along one‐dimensional tracks widely spaced in space and time, making accurately reconstructing the two‐dimensional (2D) SSH field challenging. Traditionally, SSH is mapped using optimal interpolation (OI). However, OI artificially smooths the SSH field leading to high mapping errors in regions with rapidly‐evolving mesoscale features such as western boundary currents. Motivated by the dynamical relation between SSH and sea surface temperature (SST) and the notion that even the chaotic evolution of mesoscale ocean turbulence may contain repeating patterns, we outline a deep learning (DL) approach where a neural network is trained to reconstruct 2D SSH by synthesizing altimetry and SST observations. In the Gulf Stream Extension region, dominated by mesoscale variability, our DL method substantially improves the SSH reconstruction compared to existing methods. Our SSH map has 17% lower root‐mean‐square error and resolves spatial scales 30% smaller than OI compared against independent altimeter observations. Surface geostrophic currents calculated from our map are closer to surface drifter observations and appear qualitatively more realistic, with stronger currents, a clearer separation between the Gulf Stream and neighboring eddies, and the appearance of smaller coherent eddies missed by other methods. Our map yields significant re‐estimations of important dynamical quantities such as eddy kinetic energy, vorticity, and strain rate. Applying our DL method to produce a global SSH product may provide a more accurate and higher resolution product for studying mesoscale ocean turbulence.

Effects of laser-structured and APS flash-coated CoNiCrAlY bondcoats on the furnace cycle lifetime of double-layered Y2O3-stabilized ZrO2/MgAl2O4 abradable coatings

Improving the mechanical interlocking within the layers of an abradable and a thermal barrier coating (TBC) plays a key role in extending its lifetime. This can be achieved by increasing the surface profile of the bondcoat using laser ablation and flash coating. To this end, this work analyzes the impact of laser-ablated and atmospherically plasma-sprayed flash-coated CoNiCrAlY bondcoats on the furnace cycle lifetime of double-layered Y2O3-stabilized ZrO2/MgAl2O4 abradable coatings. The three different bondcoat modifications studied in this work are, namely, a laser-ablated vacuum plasma sprayed bondcoat with a square-shaped grid surface structure, a laser-ablated vacuum plasma sprayed bondcoat with an additional atmospheric plasma sprayed fine flash-coat for increased micro-roughness, and a standard vacuum plasma sprayed bondcoat with a coarse and a subsequent fine atmospherically plasma sprayed flash-coat. As a reference sample, a standard vacuum plasma sprayed bondcoat is used. A detailed analysis of the optimal laser parameters to manufacture homogenous laser-structured bondcoats is presented, while furnace cycle tests at 1100 °C are used to identify the performance of the different bondcoat/ceramic topcoat systems. The obtained results show that the cycling lifetime improved for all three modified bondcoats compared to the standard bondcoat. However, the two laser-structured bondcoats present the most significant increase by almost three times. X-ray diffraction and scanning electron microscope results further reveal that the laser ablation process has no considerable effect on the material composition. Furthermore, roughness measurements highlight that the bondcoat's macro-roughness has a more pronounced effect on the cycling life than its micro-roughness. The furnace cycle tests, moreover, show that both laser-structured bondcoats have different failure modes, but similar cycling lifetime.

Novel grid surface for creating solid-state electrogenerated chemiluminescence sensor based on Ru(II) complex doped onto AuNPs decorated Ru(II)/poly(tyramine) film

Novel grid surface for creating solid-state electrogenerated chemiluminescence sensor based on Ru(II) complex doped onto AuNPs decorated Ru(II)/poly(tyramine) film

STRESS-STRAIN STATE AND WEAR MODELLING FOR FUEL ROD – GRID CONTACT

The paper presents an approach for effective solution of the stress-strain state and wear prediction problem for the case of contact between fuel rod and grid surfaces of a nuclear reactor. Boundary-initial value elastic-plastic problem statement, due to the quasi-static character of the forced oscillations, which was approved by eigen frequencies analysis, was reduced to boundary one. The influence of inhomogeneous temperature field and varying pressure in the outer surface of fuel rod’s shell are considered. For this, a sequence of special procedures for searching the most effective ways of numerical simulation with limited computational resources was considered. The method of weighted residuals and the finite difference method were used to solve the problem of nonlinear forced oscillations under periodic loading of the fuel rod, described as beam under bending. The analytical solution for the fuel rod’s shell displacements in thermo-elasticity problem is obtained, approximated for spatial case and added to the general three-dimensional Finite Element model. The same procedure was adopted for the maximum amplitude values of the displacements which were obtained in the geometrically nonlinear beam problem solution. After that the general elastic-plastic contact problem of the interaction between the fuel rod and the grid surfaces was solved, taking into account preliminary obtained stress distributions achieved by temperature and amplitude displacements influence. The theory of plasticity of an isotropic material with isotropic hardening was used as a model. The limits of linear solutions for beam deflections as well as deflection dependencies upon time are demonstrated and analyzed. The numerically obtained distributions of strains and stresses are presented. By use of the obtained maximum stress values an attempt for the wear estimation in contact zone was done and the fuel rod’s operating time without critical wear during the contact with the grid surface was determined. The obtained results may be considered as corresponding to practical operating data.

Estimation of Muscle Fiber Direction by Multi-channel Surface EMG Conductiong Wave Analysis Using Grid Surface Electrodes

Skeletal muscle is a set of motor units (MU). Muscle contractile activity is carried out by regulating the firing frequency of MU and the types of muscle fibers to be mobilized. Multi-channel surface electromyogram (sEMG) contains many conducting waves that represent a single motor unit action potentials (MUAP). In previous study, we proposed a method to extract conducting waves quantitatively and automatically. This method is useful for elucidating mobilized MUs and can be applied to kinematic analysis and diagnosis of muscle diseases. In multi-channel sEMG measurement, rows of electrodes need to be applied along the direction of the muscle fibers. However, the electrodes are difficult to set because the direction of the muscle fibers cannot be visually confirmed on the skin. This study investigated a method for estimating muscle fiber direction by analyzing conducting waves from two-dimensional multichannel surface electromyograms using grid-shaped surface electrodes. By examining the number of conducting waves acquired in each direction of the electrode row, it was suggested that the direction of muscle fiber may be estimated from the direction with the largest number of propagating wave acquisitions. It was also found that the method of acquiring differential potential signals has a significant impact on the analysis of propagation direction.

멀티 블록 격자 재분할이 자동차 공기역학에 미치는 영향

The impact of multi-block mesh refinement on automobile aerodynamics was investigated using three refinement methods: (1) overall mesh refinement, (2) ground mesh refinement, and (3) prism layer control. The open source CFD code, OpenFOAM V10, was utilized and simulations were conducted on the full-scale Notchback DrivAer model. For each method, the effects of mesh refinement were analyzed by refining different regions. In the overall mesh refinement study, successive multi-block grid refinement regions were established - the grid size becomes finer as the block is closer to the car surface. The lift coefficient was affected by grid refinement in regions near the automobile body. The ground mesh refinement study was conducted by controlling two grid sizes related to the ground region: volume mesh and surface mesh. The prediction of drag coefficient was fairly robust with ground region refinement, and the lift coefficient was more accurate with a smaller ground region grid. However, an excessively small surface grid reduced the accuracy of both drag and lift coefficients. In the prism layer study, the accuracy of the drag coefficient was independent of the prism layer setup, while the layer thickness and expansion ratio had a significant impact on the lift coefficient.

Influence of electrodes' geometrical properties on the neutron production rate of a discharge fusion neutron source

Trapping ions, such as deuterium and tritium, inside a potential well to generate neutrons is a well-established technology through electric and magnetic fields via the inertial electrostatic confinement fusion (IECF) and the tokamak, respectively. In the IECF, the straightforward configuration is a concentric cathode connected to a negative bias, surrounded by a grounded anode that serves as a vacuum vessel. Theoretically, neutrons are generated inside the vessel through fusion between ions that are accelerated by applying several tens kV voltage and tens mA current. Many parameters affect the plasma conditions and fusion in the system, hence the neutron production rate (NPR). This study investigates the cathode transparency and the number of apertures effect on NPR. For this end, eleven cathodes were fabricated from stainless steel in three different groups with different transparency and number of apertures. NPRs were investigated as a function of the cathode transparency and number of apertures at low power operating mode ∼1 kW. Experimental results revealed that higher NPR was produced from lower grid transparency and vice versa; this behavior was explained through beam–surface fusion with grid surface. In addition, a higher NPR was generated from the grid with many apertures; this was attributed to the effect of the deuterium ionization improvement by the number of ionizing electrons through the grid channels.

Hydrological Effects of Spatial Harvest Patterns in a Small Catchment Covered by Fast-Growing Plantations in the Neotropics

<em>Eucalyptus</em> forests are expanding worldwide and concerns exist about their impact on water resources. There is a lack of information about the hydrological effects of spatial harvest patterns in terms of their effects on streamflow. In this paper, we examined harvest amount and hillslope position effects on flow indices (Q70; Q50 and Q10) and water yield in a small catchment covered with a fast-growing <em>Eucalyptus</em> plantation. To do that, we used the Gridded Surface Subsurface Hydrologic Analysis (GSSHA), a physical-based distributed hydrological model, to simulate harvesting scenarios with different harvest amounts (30% and 70% of the forest plantation) at two hillslope positions (downslope and upslope). We also verified the influence of the amount of rainfall on peak flows for all scenarios. The results showed that the increase in water yield is positively related to the harvest amount and that, under the same harvest amount, harvests in downslope areas caused a larger increase in water yield than harvests in upslope areas. Downslope harvests led to a greater increase in peak flow under the 30% harvest. For the 70% harvest, no substantial effects of harvest position on peak flow could be detected. Incorporating harvest amounts and spatial patterns in <em>Eucalyptus</em> plantations management practices may be useful to mitigate their effects on water resources, especially in regions where water availability is generally lower.

Efficient Parallel Dynamic Overset Unstructured Grid for Flow Simulation with Moving Bodies

The overset grid method for simulation of unsteady flow with moving bodies faces several issues, including low assembly efficiency for a large number of bodies, difficult parallel implementation, and the requirement of manual intervention. To address these issues, in this paper, we develop an efficient, automatic, and robust parallel dynamic overset-unstructured-grid assembly method. It is achieved by parallelizing its two main steps: hole cutting, and identification of interpolation stencils. The hole cutting is simply implemented in parallel by identifying the active zone of each grid with a criterion of the global minimum wall distance. The global minimum wall distance is efficiently calculated on each process with the oriented-bounding-box-based -dimensional (-D) trees of the wall surface grids. For identification of the interpolation stencil, we use the results of the first step, optimally define the interpolation boundary nodes, and determine their candidate donor partitions in each process. This efficiently minimizes the number of query nodes and their donor cell candidates. The donor cell search is efficiently performed in parallel in each candidate donor partition by using the oriented-bounding-box-based -D tree of the field volume grid. Several cases are adopted to test the efficiency and capability of the proposed parallel dynamic overset-unstructured-grid assembly approach.

Assessment of High-Resolution Surface Soil Moisture Products over the Qinghai–Tibet Plateau for 2009–2017

The surface soil moisture over the Qinghai–Tibet Plateau (QTP) has an important impact on the weather and climate of East Asia. Under climate warming, the imbalance of solid–liquid water of QTP has become a research hotspot, but the surface soil moisture dynamics over QTP are not clear owing to the lack of precise measurements over a large scale. In this paper, the quality of gridded surface soil moisture products including CSSPv2 high-resolution (6 km) simulation, ESA CCI satellite retrieval, ERA5 land-atmosphere coupled reanalysis, and GLDAS2.1 land reanalysis products (Noah, Catchment, VIC) is analyzed over QTP by comparison with the in situ measurements at 140 stations during 2009–2017. We find that the CSSPv2 product shows a higher correlation than the global satellite and reanalysis products, with correlation increased by 7.7%–115.6%. The root mean squared error of the CSSPv2 product is lower than that of other products, with the error decreased by 13.4%–46.3%. The triple collocation analysis using high-resolution simulation, global reanalysis, and satellite retrieval products over the entire plateau shows that the error of CSSPv2 is the lowest, followed by ESA CCI, while ERA5 is the highest. The soil moisture products of ESA CCI, ERA5, and CSSPv2 all show an increasing trend from April to September of 2009 to 2017, with wetting in the west and drying in the east. This study indicates that the CSSPv2 high-resolution surface soil moisture product has better performance over QTP than other global products, and the global satellite and reanalysis products may overestimate the surface soil moisture dynamics.

Evaluation of the Effectiveness and Impact of Wetting the Surface of the Collector Grid on the Process of Collecting Atmospheric Fog

Evaluation of the Effectiveness and Impact of Wetting the Surface of the Collector Grid on the Process of Collecting Atmospheric Fog