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Keywords = space-time varying coefficient models

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21 pages, 11774 KB  
Article
Research on the Mechanical Properties of Mechanically Connected Splices of Prestressing Screw Bars Under Monotonic and Cyclic Loads
by Liangyu Lei, Yue Ma, Bo Xie, Jing Bai, Mei Hu and Zhezhuo Guo
Buildings 2025, 15(19), 3614; https://doi.org/10.3390/buildings15193614 - 9 Oct 2025
Viewed by 217
Abstract
The mechanical properties of screw-thread steel bars used for prestressing concrete and their threaded ribs’ bearing mechanism have not been quantitatively studied, in contrast to the extensive qualitative research on ordinary steel mechanical connection splices. A quantitative investigation was conducted under various design [...] Read more.
The mechanical properties of screw-thread steel bars used for prestressing concrete and their threaded ribs’ bearing mechanism have not been quantitatively studied, in contrast to the extensive qualitative research on ordinary steel mechanical connection splices. A quantitative investigation was conducted under various design parameters and working conditions to examine the mechanical connection splices of screw-thread steel bars used for prestressing concrete. The splices’ connection performance and their threaded ribs’ bearing mechanism were also examined. Analyzing the force on the threads of the splices under monotonic tensile loading allowed for the theoretical computation of the axial force coefficients for threaded ribs. The validated revised three-dimensional numerical model of splices is based on the findings of the theoretical calculations. Afterwards, rigorous numerical simulations of monotonic tensile loading, repeated tensile and compressive loading with high stress, and repeated tensile and compressive loading with large strain were performed on 45 splices with varying nominal rebar diameters, coupler outer diameters and lengths, and thread rib spacings. The results show that rebar pullout and rebar fracture are the two main ways in which splices might fail. After cyclic loading, the splices’ ultimate bearing capacity changed by 0.83% to 2.81%, and their ductility changed by 2.13% to 4.75% compared to after monotonic tensile loading. Although the splice load-carrying capacity and plastic deformation capacity were reduced by 2.11%~7.48% and 3.98%~25.78%, respectively, when the thread rib spacing was increased from the specified value to 0.6~0.8 times the nominal diameter of the rebar, the splice connection performance was still able to meet the requirements for class I splices. Approximately half of the splices’ load-bearing capability is provided by the 1–2 turns of threads close to the coupler ends; after cyclic loading, their stress rises by between 4.52% and 12.63% relative to monotonic tension. Stresses in all threaded ribs of the splices are increased by 5.49% to 27.76% as the distance between the threaded ribs increases to 1.0 and 1.2 times the nominal diameter of the rebar, which reduces the splice’s load-bearing capacity. Full article
(This article belongs to the Section Building Structures)
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32 pages, 898 KB  
Article
Heat Conduction Model Based on the Explicit Euler Method for Non-Stationary Cases
by Attila Érchegyi and Ervin Rácz
Entropy 2025, 27(10), 994; https://doi.org/10.3390/e27100994 - 24 Sep 2025
Viewed by 297
Abstract
This article presents an optimization of the explicit Euler method for a heat conduction model. The starting point of the paper was the analysis of the limitations of the explicit Euler scheme and the classical CFL condition in the transient domain, which pointed [...] Read more.
This article presents an optimization of the explicit Euler method for a heat conduction model. The starting point of the paper was the analysis of the limitations of the explicit Euler scheme and the classical CFL condition in the transient domain, which pointed to the oscillation occurring in the intermediate states. To eliminate this phenomenon, we introduced the No-Sway Threshold given for the Fourier number (K), stricter than the CFL, which guarantees the monotonic approximation of the temperature–time evolution. Thereafter, by means of the identical inequalities derived based on the Method of Equating Coefficients, we determined the optimal values of Δt and Δx. Finally, for the construction of the variable grid spacing (M2), we applied the equation expressing the R of the identical inequality system and accordingly specified the thickness of the material elements (Δξ). As a proof-of-concept, we demonstrate the procedure on an application case with major simplifications: during an emergency shutdown of the Flexblue® SMR, the temperature of the air inside the tank instantly becomes 200 °C, while the initial temperatures of the water and the steel are 24 °C. For a 50.003 mm × 50.003 mm surface patch of the tank, we keep the leftmost and rightmost material elements of the uniform-grid (M1) and variable-grid (M2) single-line models at constant temperature; we scale the results up to the total external surface (6714.39 m2). In the M2 case, a larger portion of the heat power taken up from the air is expended on heating the metal, while the rise in the heat power delivered to the seawater is more moderate. At the 3000th min, the steel-wall temperature in M1 falls between 26.229 °C and 25.835 °C, whereas in M2 the temperature gradient varies between 34.648 °C and 30.041 °C, which confirms the advantage of the combination of variable grid spacing and the No-Sway Threshold. Full article
(This article belongs to the Special Issue Dissipative Physical Dynamics)
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24 pages, 3024 KB  
Article
Varying-Coefficient Additive Models with Density Responses and Functional Auto-Regressive Error Process
by Zixuan Han, Tao Li, Jinhong You and Narayanaswamy Balakrishnan
Entropy 2025, 27(8), 882; https://doi.org/10.3390/e27080882 - 20 Aug 2025
Viewed by 630
Abstract
In many practical applications, data collected over time often exhibit autocorrelation, which, if unaccounted for, can lead to biased or misleading statistical inferences. To address this issue, we propose a varying-coefficient additive model for density-valued responses, incorporating a functional auto-regressive (FAR) error process [...] Read more.
In many practical applications, data collected over time often exhibit autocorrelation, which, if unaccounted for, can lead to biased or misleading statistical inferences. To address this issue, we propose a varying-coefficient additive model for density-valued responses, incorporating a functional auto-regressive (FAR) error process to capture serial dependence. Our estimation procedure consists of three main steps, utilizing spline-based methods after mapping density functions into a linear space via the log-quantile density transformation. First, we obtain initial estimates of the bivariate varying-coefficient functions using a B-spline series approximation. Second, we estimate the error process from the residuals using spline smoothing techniques. Finally, we refine the estimates of the additive components by adjusting for the estimated error process. We establish theoretical properties of the proposed method, including convergence rates and asymptotic behavior. The effectiveness of our approach is further demonstrated through simulation studies and applications to real-world data. Full article
(This article belongs to the Section Information Theory, Probability and Statistics)
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11 pages, 1936 KB  
Communication
Diffusion of C-O-H Fluids in a Sub-Nanometer Pore Network: Role of Pore Surface Area and Its Ratio with Pore Volume
by Siddharth Gautam and David Cole
C 2025, 11(3), 57; https://doi.org/10.3390/c11030057 - 1 Aug 2025
Viewed by 916
Abstract
Porous materials are characterized by the pore surface area (S) and volume (V) accessible to a confined fluid. For mesoporous materials NMR measurements of diffusion are used to assess the S/V ratio, because at short times, only [...] Read more.
Porous materials are characterized by the pore surface area (S) and volume (V) accessible to a confined fluid. For mesoporous materials NMR measurements of diffusion are used to assess the S/V ratio, because at short times, only the diffusivity of molecules in the adsorbed layer is affected by confinement and the fractional population of these molecules is proportional to the S/V ratio. For materials with sub-nanometer pores, this might not be true, as the adsorbed layer can encompass the entire pore volume. Here, using molecular simulations, we explore the role played by S and S/V in determining the dynamical behavior of two carbon-bearing fluids—CO2 and ethane—confined in sub-nanometer pores of silica. S and V in a silicalite model representing a sub-nanometer porous material are varied by selectively blocking a part of the pore network by immobile methane molecules. Three classes of adsorbents were thus obtained with either all of the straight (labeled ‘S-major’) or zigzag channels (‘Z-major’) remaining open or a mix of a fraction of both types of channel blocked, resulting in half of the total pore volume being blocked (‘Half’). While the adsorption layers from opposite surfaces overlap, encompassing the entire pore volume for all pores except the intersections, the diffusion coefficient is still found to be reduced at high S/V, especially for CO2, albeit not so strongly as would be expected in the case of wider pores. This is because of the presence of channel intersections that provide a wider pore space with non-overlapping adsorption layers. Full article
(This article belongs to the Section Carbon Cycle, Capture and Storage)
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21 pages, 3639 KB  
Article
Research on Data Prediction Model for Aerodynamic Drag Reduction Effect in Platooning Vehicles
by Zhexin Wang, Xuepeng Guo, Ning Yang, Lingjun Su, Lu’an Chen, Zhao Zhang and Chengyu Zhu
Processes 2025, 13(7), 2056; https://doi.org/10.3390/pr13072056 - 28 Jun 2025
Viewed by 790
Abstract
With the development of intelligent transportation systems, platooning can reduce vehicle aerodynamic drag by decreasing spacing between vehicles, improving transportation efficiency and reducing emissions. However, it is difficult for existing models to enable dynamic adjustment and real-time feedback. Therefore, this study proposes a [...] Read more.
With the development of intelligent transportation systems, platooning can reduce vehicle aerodynamic drag by decreasing spacing between vehicles, improving transportation efficiency and reducing emissions. However, it is difficult for existing models to enable dynamic adjustment and real-time feedback. Therefore, this study proposes a digital twin system for real-time drag coefficient prediction using stacking ensemble learning. First, 2000 datasets of pressure distributions and drag coefficients under varying spacings were obtained through simulations. Then, an online prediction model for the aerodynamic performance of platooning vehicles was then constructed, realizing real-time drag coefficient prediction, and verifying the model performance using computational fluid dynamics data. The results indicate that the model proposed achieves 98.56% prediction accuracy, significantly higher than that of the traditional BP model (75.78%), and effectively captures the nonlinear relationship between vehicle spacing and drag coefficient. The influence mechanism of vehicle spacing on the aerodynamic performance of platooning vehicles revealed in this study enables high-precision real-time prediction under dynamic parameters. Full article
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13 pages, 1785 KB  
Article
Space-Time Varying Coefficient Model on Longitudinal Data of the Dengue Fever in Bandung City
by Bertho Tantular, Budi Nurani Ruchjana, Yudhie Andriyana and Anneleen Verhasselt
Mathematics 2025, 13(12), 1995; https://doi.org/10.3390/math13121995 - 17 Jun 2025
Viewed by 521
Abstract
Research on the spread of dengue fever is typically measured periodically, producing longitudinally structured data. The varying coefficient model for longitudinal data allows the coefficient to vary as a smooth function of time. The data in this study have a longitudinal structure that [...] Read more.
Research on the spread of dengue fever is typically measured periodically, producing longitudinally structured data. The varying coefficient model for longitudinal data allows the coefficient to vary as a smooth function of time. The data in this study have a longitudinal structure that offers a long-term presentation of dengue fever in Bandung City, Indonesia, influenced by a set of covariates that vary over time and space. The former are temperature, rainfall, and humidity, and the latter is residential location, such as vector index and population density. Considering space- and time-varying effects, a space-time varying coefficient model was proposed. The model parameters were estimated by minimizing the P-splines quantile objective function. The results implemented on the data show that the model and method satisfy the condition of the data, which means the coefficients vary over space and time. Based on the three quantile levels, each subdistrict in Bandung City has a different level of incidence rate category. Due to differences in covariate effects both over time and over space, Bandung City also exhibits a heterogeneous incidence rate pattern based on its three quantile levels. The result provides a quantile pattern that can be used as a guide for high-performance dengue fever classification. Full article
(This article belongs to the Section D1: Probability and Statistics)
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22 pages, 56507 KB  
Article
Study on the Correlations Between Spatial Morphology Parameters and Solar Potential of Old Communities in Cold Regions with a Case Study of Jinan City, Shandong Province
by Fei Zheng, Peisheng Liu, Zhen Ren, Xianglong Zhang, Yuetao Wang and Haozhi Qin
Buildings 2025, 15(8), 1250; https://doi.org/10.3390/buildings15081250 - 10 Apr 2025
Cited by 1 | Viewed by 568
Abstract
Currently, urban development has entered the stage of renewal and transformation. Energy transition is an important trend for sustainable urban development, and the assessment of solar energy potential in old residential areas in cold regions is of great significance. This study selects 47 [...] Read more.
Currently, urban development has entered the stage of renewal and transformation. Energy transition is an important trend for sustainable urban development, and the assessment of solar energy potential in old residential areas in cold regions is of great significance. This study selects 47 old residential communities in Jinan, a cold region of China, as case samples. Using clustering algorithms based on spatial form characteristic parameters, the study divides the samples into five categories. The study then uses the Ladybug tool to simulate the distribution and total solar energy utilization potential of buildings in the five categories and analyzes the correlation between eight spatial form parameters and building solar energy potential. A linear regression model is established, and strategies for the application of BIPV in community buildings are proposed. The study finds that factors such as plot ratio, building density, open space ratio, volume-to-surface ratio, and form coefficient have a significant impact on the solar energy potential of residential communities; the p-values are −0.785, −0.783, 0.783, −0.761, and 0.724, respectively. Among these, building density (BD) is the most crucial factor affecting the solar energy potential of building facades. Increasing by one unit can reduce the solar energy utilization potential by 28.00 kWh/m2/y. At the same time, installing photovoltaic panels on old residential buildings in cold regions can reduce building carbon emissions by approximately 48%. The research findings not only provide methodological references for photovoltaic technology application at varying neighborhood scales in urban settings but also offer specific guidance for low-carbon retrofitting of aging urban communities, thereby facilitating progress in urban carbon emission reduction. Full article
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23 pages, 6073 KB  
Article
A VMD-SVM Method for LEO Satellite Orbit Prediction with Space Weather Parameters
by Hao Xu, Jiahao Liao, Yufei Luo and Yunhe Meng
Remote Sens. 2025, 17(5), 746; https://doi.org/10.3390/rs17050746 - 21 Feb 2025
Viewed by 1245
Abstract
The technology of satellite orbit prediction (OP) is crucial in space engineering. However, it is difficult to precisely predict medium and long-term orbit for the low Earth-orbit (LEO) satellites because of time-varying space weather and inaccurate atmospheric density models. To address the problem, [...] Read more.
The technology of satellite orbit prediction (OP) is crucial in space engineering. However, it is difficult to precisely predict medium and long-term orbit for the low Earth-orbit (LEO) satellites because of time-varying space weather and inaccurate atmospheric density models. To address the problem, a novel intelligent OP method based on the variational mode decomposition-support vector machine (VMD-SVM) framework is presented. First, the concept of a pseudo-drag coefficient is defined, transforming the OP problem into a pseudo-drag coefficient prediction problem. Second, the relationship between space weather parameters and the pseudo-drag coefficient is analyzed using the VMD method, from which a strong correlation is shown. Furthermore, an SVM model combined with space weather characteristic parameters is employed to predict the pseudo-drag coefficient, significantly improving the precision of OP when further integrated into the orbital dynamics model. Experiments with data from engineering applications show that VMD-SVM medium and long-term OP technology is practical and effective. Full article
(This article belongs to the Special Issue Autonomous Space Navigation (Second Edition))
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36 pages, 8468 KB  
Article
A Novel Magnetic Integration High-Efficiency Converter with Low Ripple and High Dynamic Response for the Hybrid Power Supply Systems of All-Electric Aircraft
by Li Chen, Haifeng Gao, Fengjie Shen, Yiyi Zhang, Liangjie Qiu and Lei Wang
Aerospace 2024, 11(12), 965; https://doi.org/10.3390/aerospace11120965 - 25 Nov 2024
Viewed by 1432
Abstract
With the continuous improvement of battery energy density and converter power density, as well as the miniaturization and lightweighting of related airborne electrical equipment, all-electric aircraft with hybrid power supply systems provide more trade-off space and possibilities for the design of future aircraft. [...] Read more.
With the continuous improvement of battery energy density and converter power density, as well as the miniaturization and lightweighting of related airborne electrical equipment, all-electric aircraft with hybrid power supply systems provide more trade-off space and possibilities for the design of future aircraft. It is indispensable to search for a more valuable topology and apply it to airborne power supply. This paper proposes an airborne high-gain unidirectional DC-DC converter suitable for between low-voltage unit and high-voltage bus, which consists of interleaved magnetic integrated switched coupled inductor units and improved switch capacitor units. This paper first analyzes the steady-state operating characteristics under different modes; the new topology has higher voltage gain and lower stress. Secondly, in response to the challenges of high efficiency and high power density, we propose a magnetic integration design method and comprehensive experimental scheme based on the EIE-type magnetic core structure. This successfully integrates multiple discrete inductors into a single magnetic core. Furthermore, based on the comprehensive consideration of steady-state, transient performance and power density, the general design criteria for a high-gain switched coupled inductor are summarized through the equivalent mathematical model of reverse flux coupling. Additionally, by adjusting the coupling coefficient, the converter can achieve zero-voltage switching under light load conditions, demonstrating versatility and scalability and better meeting the application requirements of electric aircraft. The proposed prototype can provide voltage gain in the range of 12–22 times the input voltage gain by varying the input voltage from a 12–24 V fuel cell. The comprehensive performance of the converter, including steady-state, transient, and efficiency, was tested under D < 0.5 and D > 0.5. The experimental results show that the proposed converter possesses advantages such as high gain and low stress, a high dynamic response and low ripple, and high efficiency and high power density, which can provide a more advantageous DC-DC converter solution for airborne hybrid power supply systems. Full article
(This article belongs to the Special Issue Electric Power Systems and Components for All-Electric Aircraft)
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15 pages, 7833 KB  
Article
Spatial and Temporal Characterization of Near Space Temperature and Humidity and Their Driving Influences
by Wenhui Luo, Jinji Ma, Miao Li, Haifeng Xu, Cheng Wan and Zhengqiang Li
Remote Sens. 2024, 16(22), 4307; https://doi.org/10.3390/rs16224307 - 19 Nov 2024
Viewed by 1470
Abstract
Near space refers to the atmospheric region 20–100 km above Earth’s surface, encompassing the stratosphere, mesosphere, and part of the thermosphere. This region is susceptible to surface and upper atmospheric disturbances, and the atmospheric temperature and humidity profiles can finely characterize its complex [...] Read more.
Near space refers to the atmospheric region 20–100 km above Earth’s surface, encompassing the stratosphere, mesosphere, and part of the thermosphere. This region is susceptible to surface and upper atmospheric disturbances, and the atmospheric temperature and humidity profiles can finely characterize its complex environment. To analyze the relationship between changes in temperature and humidity profiles and natural activities, this study utilizes 18 years of temperature and water vapor data from the TIMED/SABER and AURA/MLS instruments to investigate the variations in temperature and humidity with altitude, time, and spatial distribution. In addition, multiple linear regression analysis is used to examine the impact mechanisms of solar activity, the El Niño–Southern Oscillation (ENSO), and the Quasi-Biennial Oscillation (QBO) on temperature and humidity. The results show that in the mid- and low-latitude regions, temperature and water vapor reach their maxima at an altitude of 50 km, with values of 265 K and 8–9 × 10⁻⁶ ppmv, respectively; the variation characteristics differ across latitudes and altitudes, with a clear annual cycle; the feedback effects of solar activity and the ENSO index on temperature and humidity in the 20–40 km atmospheric layer are significantly different. Among these factors, solar activity is the most significant influence on temperature and water vapor, with response coefficients of −0.2 to −0.16 K/sfu and 0.8 to 4 × 10⁻⁶ ppmv/sfu, respectively. Secondly, in the low-latitude stratospheric region, the temperature response to ENSO is approximately −1.5 K/MEI, while in the high-latitude region, a positive response of 3 K/MEI is observed. The response of water vapor to ENSO varies between −1 × 10⁻⁷ and −4 × 10⁷ ppmv/sfu. In the low-latitude stratospheric region, the temperature and humidity responses to the QBO index exhibit significant differences, ranging from −1.8 to −0.6 K/10 m/s. Additionally, there are substantial differences in responses between the polar regions and the low-latitude equatorial region. Finally, a three-dimensional model coefficient was constructed to illustrate the influence of solar activity, ENSO, and QBO on temperature and humidity in the near space. The findings of this study contribute to a deeper understanding of the temperature and humidity variation characteristics in near space and provide valuable data and model references for predicting three-dimensional parameters of temperature and humidity in this region. Full article
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28 pages, 3037 KB  
Article
Design of Input Signal for System Identification of a Generic Fighter Configuration
by Mehdi Ghoreyshi, Pooneh Aref and Jürgen Seidel
Aerospace 2024, 11(11), 883; https://doi.org/10.3390/aerospace11110883 - 26 Oct 2024
Cited by 1 | Viewed by 1524
Abstract
This article investigates the design of time-accurate input signals in the angle-of-attack and pitch rate space to identify the aerodynamic characteristics of a generic triple-delta wing configuration at subsonic speeds. Regression models were created from the time history of signal simulations in DoD [...] Read more.
This article investigates the design of time-accurate input signals in the angle-of-attack and pitch rate space to identify the aerodynamic characteristics of a generic triple-delta wing configuration at subsonic speeds. Regression models were created from the time history of signal simulations in DoD HPCMP CREATETM-AV/Kestrel software. The input signals included chirp, Schroeder, pseudorandom binary sequence (PRBS), random, and sinusoidal signals. Although similar in structure, the coefficients of these regression models were estimated based on the specific input signals. The signals covered a wide range of angle-of-attack and pitch rate space, resulting in varying regression coefficients for each signal. After creating and validating the models, they were used to predict static aerodynamic data at a wide range of angles of attack but with zero pitch rate. Next, slope coefficients and dynamic derivatives in the pitch direction were estimated from each signal. These predictions were compared with each other as well as with the ONERA wind tunnel data and some CFD calculations from the DLR TAU code provided by the NATO Science and Technology Organization research task group AVT-351. Subsequently, the models were used to predict different pitch oscillations at various mean angles of attack with given amplitudes and frequencies. Again, the model predictions were compared with wind tunnel data. Final predictions involved responses to new signals from different models. A feed-forward neural network was then used to model pressure coefficients on the upper surface of the vehicle at different spanwise sections for each signal and the validated models were used to predict pressure data at different angles of attack. Overall, the models predict similar integrated forces and moments, with the main discrepancies appearing at higher angles of attack. All models failed to predict the stall behavior observed in the measurements and CFD data. Regarding the pressure data, the PRBS signal provided the best accuracy among all the models. Full article
(This article belongs to the Special Issue Recent Advances in Applied Aerodynamics)
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25 pages, 10343 KB  
Article
Exploration of Deep-Learning-Based Error-Correction Methods for Meteorological Remote-Sensing Data: A Case Study of Atmospheric Motion Vectors
by Hang Cao, Hongze Leng, Jun Zhao, Xiaodong Xu, Jinhui Yang, Baoxu Li, Yong Zhou and Lilan Huang
Remote Sens. 2024, 16(18), 3522; https://doi.org/10.3390/rs16183522 - 23 Sep 2024
Cited by 3 | Viewed by 2380
Abstract
Meteorological satellite remote sensing is important for numerical weather forecasts, but its accuracy is affected by many things during observation and retrieval, showing that it can be improved. As a standard way to measure wind from space, atmospheric motion vectors (AMVs) are used. [...] Read more.
Meteorological satellite remote sensing is important for numerical weather forecasts, but its accuracy is affected by many things during observation and retrieval, showing that it can be improved. As a standard way to measure wind from space, atmospheric motion vectors (AMVs) are used. They are separate pieces of information spread out in the troposphere, which gives them more depth than regular surface or sea surface wind measurements. This makes rectifying problems more difficult. For error correction, this research builds a deep-learning model that is specific to AMVs. The outcomes show that AMV observational errors are greatly reduced after correction. The root mean square error (RMSE) drops by almost 40% compared to ERA5 true values. Among these, the optimization of solar observation errors exceeds 40%; the discrepancies at varying atmospheric pressure altitudes are notably improved; the degree of optimization for data with low QI coefficients is substantial; and there remains potential for enhancement in data with high QI coefficients. Furthermore, there has been a significant enhancement in the consistency coefficient of the wind’s physical properties. In the assimilation forecasting experiments, the corrected AMV data demonstrated superior forecasting performance. With more training, the model can fix things better, and the changes it makes last for a long time. The results show that it is possible and useful to use deep learning to fix errors in meteorological remote-sensing data. Full article
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16 pages, 4745 KB  
Article
Influence of Grid Resolution and Assimilation Window Size on Simulating Storm Surge Levels
by Xin Bi, Wenqi Shi, Junli Xu and Xianqing Lv
J. Mar. Sci. Eng. 2024, 12(7), 1233; https://doi.org/10.3390/jmse12071233 - 22 Jul 2024
Viewed by 1226
Abstract
Grid resolution and assimilation window size play significant roles in storm surge models. In the Bohai Sea, Yellow Sea, and East China Sea, the influence of grid resolution and assimilation window size on simulating storm surge levels was investigated during Typhoon 7203. In [...] Read more.
Grid resolution and assimilation window size play significant roles in storm surge models. In the Bohai Sea, Yellow Sea, and East China Sea, the influence of grid resolution and assimilation window size on simulating storm surge levels was investigated during Typhoon 7203. In order to employ a more realistic wind stress drag coefficient that varies with time and space, we corrected the storm surge model using the spatial distribution of the wind stress drag coefficient, which was inverted using the data assimilation method based on the linear expression Cd = (a + b × U10) × 10−3. Initially, two grid resolutions of 5′ × 5′ and 10′ × 10′ were applied to the numerical storm surge model and adjoint assimilation model. It was found that the influence of different grid resolutions on the numerical model is almost negligible. But in the adjoint assimilation model, the root mean square (RMS) errors between the simulated and observed storm surge levels under 5′ × 5′ and 10′ × 10′ grid resolutions were 11.6 cm and 15.6 cm, and the average PCC and WSS values for 10 tidal stations changed from 89% and 92% in E3 to 93% and 96% in E4, respectively. The results indicate that the finer grid resolution can yield a closer consistency between the simulation and observations. Subsequently, the effects of assimilation window sizes of 6 h, 3 h, 2 h, and 1 h on simulated storm surge levels were evaluated in an adjoint assimilation model with a 5′ × 5′ grid resolution. The results show that the average RMS errors were 11.6 cm, 10.6 cm, 9.6 cm, and 9.3 cm under four assimilation window sizes. In particular, the RMS errors for the assimilation window sizes of 1 h and 6 h at RuShan station were 3.9 cm and 10.2 cm, a reduction of 61.76%. The PCC and WSS values from RuShan station in E4 and E7 separately showed significant increases, from 85% to 98% and from 92% to 99%. These results demonstrate that when the assimilation window size is smaller, the simulated storm surge level is closer to the observation. Further, the results show that the simulated storm surge levels are closer to the observation when using the wind stress drag coefficient with a finer grid resolution and smaller temporal resolution. Full article
(This article belongs to the Special Issue Ocean Modeling and Data Assimilation)
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33 pages, 34740 KB  
Article
Spatiotemporal Dynamics of Ecosystem Services and Their Trade-Offs and Synergies in Response to Natural and Social Factors: Evidence from Yibin, Upper Yangtze River
by Chaojie Tian, Liheng Pang, Quanzhi Yuan, Wei Deng and Ping Ren
Land 2024, 13(7), 1009; https://doi.org/10.3390/land13071009 - 7 Jul 2024
Cited by 9 | Viewed by 2286
Abstract
During the rapid urbanization phase, the trade-off between ecosystem services is the most severe and also the most effective stage to implement ecological management. Exploring the natural—social driving mechanisms for trade-offs contributes to the coordinated development of the social economy and nature. Taking [...] Read more.
During the rapid urbanization phase, the trade-off between ecosystem services is the most severe and also the most effective stage to implement ecological management. Exploring the natural—social driving mechanisms for trade-offs contributes to the coordinated development of the social economy and nature. Taking the typical mountainous city (Yibin) that is currently in the rapid urbanization phase and ecologically fragile as an example, utilizing a combination of difference comparison, trade-off–synergy index (TSI), optimal-parameter-based geographical detector model (OPGD), and multi-scale geographically weighted regression (MGWR), we spatially assess the nature and intensity of ES relationships and explore its social–natural driving mechanisms. Our findings reveal the following: (1) Varied geospatial patterns of four ESs—habitat quality (HQ), carbon storage (CS), soil conservation (SC), and water yield (WY)—with the greatest fluctuations in WY. (2) Significant changes in the nature and intensity of ES relationships over time, showing predominant positive synergies between WY-HQ, WY-SC, and HQ-CS, and negative synergies between HQ and SC, and trade-offs between WY-CS and SC-CS. (3) Distinct, time-varying driving factors for different ES relationships: climate and topography for WY, vegetation and topography for CS, topography and economic factors for HQ, and climate and topography for SC. Rapid urbanization has diminished the role of natural factors. (4) The regression coefficients reveal the local mechanisms of various driving factors, based on which targeted recommendations can be proposed. For instance, the establishment of interconnected small wetlands and green spaces in urban areas contributes to the enhancement of multiple ESs. The purpose of this study is to provide scientific insights into the driving mechanisms and optimizations of the key ecosystem services’ relationships in areas that are currently undergoing rapid urbanization. Full article
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21 pages, 18584 KB  
Article
A New Grid Zenith Tropospheric Delay Model Considering Time-Varying Vertical Adjustment and Diurnal Variation over China
by Jihong Zhang, Xiaoqing Zuo, Shipeng Guo, Shaofeng Xie, Xu Yang, Yongning Li and Xuefu Yue
Remote Sens. 2024, 16(11), 2023; https://doi.org/10.3390/rs16112023 - 4 Jun 2024
Cited by 3 | Viewed by 1449
Abstract
Improving the accuracy of zenith tropospheric delay (ZTD) models is an important task. However, the existing ZTD models still have limitations, such as a lack of appropriate vertical adjustment function and being unsuitable for China, which has a complex climate and great undulating [...] Read more.
Improving the accuracy of zenith tropospheric delay (ZTD) models is an important task. However, the existing ZTD models still have limitations, such as a lack of appropriate vertical adjustment function and being unsuitable for China, which has a complex climate and great undulating terrain. A new approach that considers the time-varying vertical adjustment and delicate diurnal variations of ZTD was introduced to develop a new grid ZTD model (NGZTD). The NGZTD model employed the Gaussian function and considered the seasonal variations of Gaussian coefficients to express the vertical variations of ZTD. The effectiveness of vertical interpolation for the vertical adjustment model (NGZTD-H) was validated. The root mean squared errors (RMSE) of the NGZTD-H model improved by 58% and 22% compared to the global pressure and temperature 3 (GPT3) model using ERA5 and radiosonde data, respectively. The NGZTD model’s effectiveness for directly estimating the ZTD was validated. The NGZTD model improved by 22% and 31% compared to the GPT3 model using GNSS-derived ZTD and layered ZTD at radiosonde stations, respectively. Seasonal variations in Gaussian coefficients need to be considered. Using constant Gaussian coefficients will generate large errors. The NGZTD model exhibited outstanding advantages in capturing diurnal variations and adapting to undulating terrain. We analyzed and discussed the main error sources of the NGZTD model using validation of spatial interpolation accuracy. This new ZTD model has potential applications in enhancing the reliability of navigation, positioning, and interferometric synthetic aperture radar (InSAR) measurements and is recommended to promote the development of space geodesy techniques. Full article
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