A Multi-Station Troposphere Modelling Method Based on Error Compensation Considering the Influence of Height Factor

Global Navigation Satellite System (GNSS) signals arrive at the Earth in a nonlinear and slightly curved way due to the refraction effect caused by the troposphere. The troposphere delay of the GNSS signal consists of hydrostatic and wet parts. In particular, tropospheric wet delay prediction and interpolation are more difficult than those of the dry component due to the rapid temporal and spatial variation of the water vapor content. Wet delay estimation and interpolation with a sufficient accuracy is an important issue for all parameters obtained by GNSS positioning techniques. In particular, in real-time positioning applications, errors caused by interpolation of the wet troposphere delay are reflected in the height component of about 1 to 2 cm. Furthermore, the amount of water vapor in the troposphere is very important information in weather forecast applications obtained as a function of wet delay. Therefore, real-time monitoring of the troposphere can be achieved with a higher resolution and accuracy by utilizing neural network models for interpolation of the wet tropospheric delay. In addition, in the absence of the GNSS station, wet delays can be interpolated by means of the surrounding stations to the desired location. In this study, a back propagation artificial neural network (BPNN) model based on meteorological parameters obtained from The New Austrian Meteorological Measuring Network (TAWES) was used to interpolate wet troposphere delay. Analysis was carried out at 40 reference stations of the Echtzeit Positionierung Austria (EPOSA) GNSS Network covering the whole of Austria. The interpolation of zenith wet delays based on the artificial neural network was performed by using latitude, longitude, altitude and meteorological parameters (temperature, pressure, weighted mean temperature, and water vapor pressure). These parameters were then subtracted from the artificial neural network model one by one and six different artificial neural networks were designed. In addition, the linear interpolation method (LIN) and inverse distance weighted interpolation method (IDW) were used as conventional interpolation methods. In order to investigate the effect of the network density on interpolation methods, three networks, including 40, 30, and 20 reference stations, were formed and the increased distance effect on interpolation methods was evaluated. In addition, analyses were conducted in winter, spring, and summer to evaluate the seasonal effects on interpolation methods. According to the statistical analysis, the root mean square error (RMSE) values of the IDW, LIN, and BPNN methods were found to be 12.6, 13.4, and 5.9 mm, respectively.

Accurate tropospheric delays are of great importance for both Global Navigation Satellite System (GNSS)-based positioning and precipitable water vapor monitoring. The gridded tropospheric delay products, including zenith hydrostatic delays (ZHD) and zenith wet delays (ZWD), are the most ideal method for accessing accurate tropospheric delays. The vertical adjustment method is critical for implementing the gridded tropospheric products. In this work, we consider the different models used for grid products and assess their performance over Yunnan mountains with complex topography. We summarize the main results as follows: (1) The products can provide accurate ZHD with mean biases of −2.6 mm and mean Standard Deviation (STD) of 1.5 mm while the ZWD results from grid products show a performance with biases of −0.4 mm and STD of 1.3 cm over the Yunnan area. (2) The Tv-based model shows a better performance than the T0-based model and IGPZWD in rugged areas with large height differences. The grid products can provide hourly ZHD with biases of 3 mm and wet delay with mean biases of within 2 cm and mean STD of below 3 cm in the Yunnan mountains, which exhibit a large height difference of around 1.5 km. (3) The radiosondes results confirm that the Tv-based model has an obvious advantage in calculating ZHD height corrections for differences within 2 km while the T0-model suffers from a loss in accuracy in the case of large height differences. If the site is located more than 1 km below the reference height, the IGPZWD model can provide a better ZWD with a mean bias of 1.5 cm and a mean STD of 1.7 cm. With vertical reduction models, the grid products can provide accurate ZHD and ZWD in real time, even if in complex area.

The single-baseline solution (SBS) model has been widely adopted by the existing global navigation satellite system (GNSS) deformation monitoring systems due to its theoretical simplicity and ease of implementation. However, the SBS model neglects the mathematical correlation between baselines, and the accuracy and reliability can be degraded for baselines with long length, large height difference or frequent satellite signal occlusion. When monitoring large-area ground settlement or long-spanned linear objects such as bridges and railroads, multiple reference stations are frequently utilized, which can be exploited to improve the monitoring performance. Therefore, this paper evaluates the multi-baseline solution (MBS) model, and constrained-MBS (CMBS) model that has a prior constraint of the spatial-correlated tropospheric delay. The reliability and validity of the MBS model are verified using GPS/BDS datasets from ground settlement deformation monitoring with a baseline length of about 20 km and a height difference of about 200 m. Numerical results show that, compared with the SBS model, the MBS model can reduce the positioning standard deviation (STD) and root-mean-squared (RMS) errors by up to (47.4/51.3/66.2%) and (56.9/60.4/58.4%) in the north/east/up components, respectively. Moreover, the combined GPS/BDS positioning performance for the MBS model outperforms the GPS-only and BDS-only positioning models, with an average accuracy improvement of about 13.8 and 25.8%, with the highest accuracy improvement of about 41.6 and 43.8%, respectively. With the additional tropospheric delay constraint, the CMBS model improves the monitoring precision in the up direction by about 45.0%.

When the heating pipelines have a large height difference on the way of laying, which is lead to increase the resistance of heating network and make hydraulic regime complicated. This paper presents a feasibility study of the long-distance heating pipeline project from Yangcheng Power Plant in Shanxi Province to Jincheng city which is carried out through the comparative analysis of the hydraulic pressure diagram. According to the optimal route, the following four schemes are proposed: (1) First-stage pressurization of the first station. (2) Multi-stage pressurization of relay-pump station. (3) Setting up intervals-pressure heat exchange station. (4) Combination of relay-pump station and intervals-pressure heat exchange station. The advantages and disadvantages of them are analyzed, respectively. As a result, only Scheme 4 meets the requirements of hydraulic conditions and the optimal location of the relay-pump station is determined be 9550 m away from the first station. This paper is intended to contribute a solution to the long-distance central heating with large height difference.

본 연구에서는 인천만의 장기간 조위관측자료를 웨이블릿 방법을 통해 분석하여 평균해수변 결정을 위한 최적의 기간을 제시하고, 적정기간에 대한 우리나라의 수직기준을 새롭게 결정하였다. 그 후 결정된 평균해수면과 연안의 지상기준점(ICGP) 간의 정밀한 높이차를 결정하기 위하여 해수면에 대한 직접적인 레이저 관측을 수행하였으며, 결정된 높이차를 전체 조위관측자료에 대해 선형보간법으로 보정하여 ICGP의 정표고를 계산하였다. 최종적으로는 계산된 ICGP의 정표고를 정밀 GPS 관측과 중력지오이드모델을 이용한 GPS 수준측량 방법을 통해 수준원점 (ORBM)과 연결하고, 새로운 평균해수변 기준의 수준원점 정표고를 결정하였다. 그 결과, 본 연구에서 결정된 인천만의 평균해수면은 1910년대의 평균해수면에 비해 약 0.026m가 변동된 것으로분 석되었으며, 새로운 평균해수면을 기준으로 GPS 수준측량에 의해 재정의된 ORBM 성과는기존성과와 약 0.035m의 차이를 나타내었다. 새로운 ORBM 성과에서 나타난 0.009m의 연결오차는 GPS 수준측량시 GPS 타원체고 결정오차와 지오이드모델링 오차 등에 기인한 것으로 판단된다. 본 연구를 통해서 정밀한 GPS 수준측량만으로 새로운 평균해수변에 기준한 ORBM 정표고 성과를 정밀하게 결정할 수 있었으며, 향후 정표고 체계로의 효율적인 전환을 위해서는 장기간의 조위관측자료를 이용한 수직기준 결정과 함께 GPS 수준측량을 통한 수준성과의 연결을 적극적으로 고려할 필요가 있다. In this study, we suggested the period of tide observations is proper to calculate the mean sea level(MSL) precisely on Incheon tide station using wavelet analysis, and newly determined then the vertical reference surface of Korea using the calculated MSL. In order to calculate the height difference between the calculated MSL and specific ground station (ICGP) near the Incheon tide stations, we performed the laser measurements directly to the sea surface where located below ICGP. The orthometric-height of ICGP was determined that corrected the height difference to the calculated MSL using linear interpolation method. Finally, we connected the orthometric-height of ICGP with the original benchmark (ORBM) using GPS leveling methods for determining the new orthometric-height of ORBM. As the results, there is a variation amount of 0.026m between the new MSL was calculated in this study and old MSL was calculated in 1910's. Also, there is a difference of 0.035m between the new and old orthometric-heights of ORBM. The connection (or leveling) error of 0.009m was revealed in new orthometric height of ORBM with consideration of MSL variation which may caused by the error of GPS ellipsoid height and/or geoid model. In this study, we could be determined precisely the orthometric-height of ORBM based on the new MSL of Incheon Bay using only GPS leveling method, not a spirit leveling method. Therefore, it is necessary to determine the vertical datum strictly using long-term and continuously tide observations more than 19 years and to use the GPS leveling method widely in the height leveling work for the effective changeover from the orthonormal to the orthometric in national height system.

The paper focuses on the landscape design of sustainable leisure areas, and the problems faced are mainly based on the original site with a large inherent landscape and a large height difference, analyzing the geographical location and foundation problems of the design scope, and carrying out new de

The purpose of the current study was to examine the effect of bilateral asymmetry of muscle strength on performance (maximal jumping height) of the countermovement jump. In experimental studies, it is impossible to control for muscle strength asymmetry, since it varies widely among individuals. In the current study, we used computer simulation. Two three-dimensional human lower limb neuromusculoskeletal models (model-symmetry and model-asymmetry) were developed. The total muscle strength of the two models was set to be identical. Bilateral muscle strength was set equal in the model-symmetry simulation, while the model-asymmetry simulation was set with a 10% bilateral strength asymmetry. The countermovement jumps were generated successfully, producing jumping heights of 0.416 m for model-symmetry and 0.419 m for model-asymmetry. The small difference in height (0.7%) indicates that bilateral asymmetry by itself does not have a significant effect on jumping performance. With model-asymmetry, the strong leg compensated for the muscle strength deficit of the weak leg by lateral movement of the body to distribute the load proportional to the muscle strength of each leg.

Land surface processes are vital to the performance of regional climate models in dynamic downscaling application. In this study, we investigate the sensitivity of the simulation by using the weather research and forecasting (WRF) model at 10-km resolution to the land surface schemes over Central Asia. The WRF model was run for 19 summers from 2000 to 2018 configured with four different land surface schemes including CLM4, Noah-MP, Pleim-Xiu and SSiB, hereafter referred as Exp-CLM4, Exp-Noah-MP, Exp-PX and Exp-SSiB respectively. The initial and boundary conditions for the WRF model simulations were provided by the National Centers for Environmental Prediction Final (NCEP-FNL) Operational Global Analysis data. The ERA-Interim reanalysis (ERAI), the GHCN-CAMS and the CRU gridded data were used to comprehensively evaluate the WRF simulations. Compared with the reanalysis and observational data, the WRF model can reasonably reproduce the spatial patterns of summer mean 2-m temperature, precipitation, and large- scale atmospheric circulation. The simulations, however, are sensitive to the option of land surface scheme. The performance of Exp-CLM4 and Exp-SSiB are better than that of Exp-Noah-MP and Exp-PX assessed by Multivariable Integrated Evaluation (MVIE) method. To comprehensively understand the dynamic and physical mechanisms for the WRF model’s sensitivity to land surface schemes, the differences in the surface energy balance between Ave-CLM4-SSiB (the ensemble average of Exp-CLM4 and Exp-SSiB) and Ave-NoanMP-PX (the ensemble average of Exp-Noah-MP and Exp-PX) are analyzed in detail. The results demonstrate that the sensible and latent heat fluxes are respectively lower by 30.42 W·m−2 and higher by 14.86 W·m−2 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX. As a result, large differences in geopotential height occur over the simulation domain. The simulated wind fields are subsequently influenced by the geostrophic adjustment process, thus the simulations of 2-m temperature, surface skin temperature and precipitation are respectively lower by about 2.08 ℃, 2.23 ℃ and 18.56 mm·month−1 in Ave-CLM4-SSiB than that in Ave-NoahMP-PX over Central Asia continent.

The wet delay is one of the most difficult sources of error to quantify in global navigation satellite systems (GNSS) due to its spatial and temporal variability. However, its estimation is vital in some applications, such as in Precise Point Positioning (PPP), network real-time kinematic and weather forecast. Such estimation is usually carried out for its projected component along the zenith, defined as the zenith wet delay (ZWD). Prediction of the ZWD is important if there is a break in its estimation, and in providing initial values for future processing. In this paper, prediction modeling for the ZWD is investigated. An autocorrelation study was first performed on ZWD data over three different days at the international GNSS service station ONSALA to provide an insight into the temporal correlations among ZWDs. The choice of this station was based on the availability of reliable ZWD data measured by water vapor radiometers, which provide a reference for assessment of the accuracy of predicted values. Results have shown that successive ZWD estimates are significantly correlated for up to 1.7 hours. Different trend and smoothing prediction models were then investigated. Since prediction of ZWD requires continuous data sequence, interpolation methods of possible missing ZWD values are discussed. The use of linear interpolation or a cubic Hermite polynomial was found to be sufficient for interpolation of ZWD. Test results of prediction models show that the single-exponential smoothing model was the best performer where ZWD estimates were forecasted with a root mean square error of less than 1 cm for up to two hours.

In order to solve the problem of low precision of tropospheric delay interpolation under the long-distance sparse reference station, a method of tropospheric delay interpolation estimation based on support vector machine (SVM) theory was proposed. Firstly, the troposphere was assumed to be an infinitely thin single-layer membrane, and with the known information of reference stations, the puncture point coordinates and zenith tropospheric delay of each reference station on each visible satellite in the single-layer membrane were obtained. Then, the puncture point coordinates and zenith tropospheric delay were taken as training samples to optimize the appropriate core parameters of SVM and establish the SVM model of tropospheric delay. Finally, two sets of network RTK data with different lengths were selected to compare and analyze the effect of the interpolated tropospheric delay. The results showed that under the long-distance reference station, with the SVM tropospheric delay model established in this paper, the tropospheric delay accuracy of the interpolation estimation is better than 2cm, and the estimation error is generally stable, and the interpolation effect of satellite in different systems is basically the same.

There are many cases when absolute measurements of objects with large height differences or height discontinuity is needed. These measurements can not be covered by classical interferometry since the range of non-ambiguity is limited to half the optical wavelength. Several techniques have been already developed for extending of non-ambiguity range. However most of them is based on multi-wavelength methods which demands expensive light sources and special environment conditions. In this work the new interferometric technique for absolute measurements of large steps discontinuities is proposed. Variable wavefront of the illuminating beam and special procedure for calibration of the measurement volume are used for extending of the measurement range without using multispectral sources. Additionally, calibration of the measurement area simplifies fringe processing and quicken measures. Theoretical analysis of this technique, its numerical simulations and experimental verification are presented and discussed.

Growth morphology of {1 1 0} faces of manganese mercury thiocyanate crystals investigated by atomic force microscopy

We report experimental evidence of anomalous kinetic roughening in the stable displacement of an oil-air interface in a Hele-Shaw cell with strong quenched disorder. The disorder consists of a random modulation of the gap spacing that is transverse to the growth direction (tracks). Experiments were performed by varying the average interface velocity and the gap spacing, and measuring the scaling exponents. The following values of the scaling exponents were obtained; beta approximately 0.50, beta* approximately 0.25, alpha approximately 1.0, alpha(loc) approximately 0.5, and z approximately 2. When there is no fluid injection, the interface is driven solely by capillary forces, and a higher value of beta of approximately beta=0.65 is measured. The presence of multiscaling and the particular morphology of the interfaces, characterized by large height differences that follow a Lévy distribution, confirms the existence of anomalous scaling. From a detailed study of the motion of the oil-air interface, we show that the anomaly is a consequence of different local velocities on the tracks plus the coupling in the motion between neighboring tracks. The anomaly disappears at high interface velocities, weak capillary forces, or when the disorder is not sufficiently persistent in the growth direction. We have also observed the absence of scaling when the disorder is very strong or when a regular modulation of the gap spacing is introduced.

Generating high-resolution daily soil moisture by using spatial downscaling techniques: a comparison of six machine learning algorithms

Abstract. Under-canopy mapping is desired to derive critical forest biometrics, such as diameter at breast height (DBH), merchantable height, and debris volume. The main challenge of such under-canopy mapping is the intermittent access to the global navigation satellite system (GNSS) signal, which is crucial to deriving accurately georeferenced mapping products. In this study, we propose two frameworks – Forest Feature LiDAR Simultaneous Localization and Mapping (F2-LSLAM) and Integrated Scan Simultaneous Trajectory Enhancement and mapping (IS2-TEAM) – for 3D LiDAR unit mounted on backpack systems to achieve accurate forest inventory. In the F2-LSLAM strategy, ground/tree trunk features are extracted from individual LiDAR scans. On the other hand, when trajectory information provided by navigation sensors is available, these semantic features are derived from LiDAR points within several scans (i.e., integrated scan) for the IS2-TEAM strategy. Then, local/global least squares adjustment (LSA) using derived features is performed to register LiDAR scans to a common reference frame for both strategies. To evaluate the performance of the proposed strategies, three in-house developed backpack systems with varying specifications were used to collect data in complicated forest environments. Through the comparison with point clouds acquired by a commercial backpack LiDAR system, the proposed frameworks are capable of generating point clouds with satisfactory intra-dataset alignment quality (in the range of 2–4 cm) for all backpack systems in natural forest areas with relatively flat terrain. However, for more challenging areas with dense undergrowth vegetation and/or large height differences, F2-LSLAM framework cannot extract sufficient features, while IS2-TEAM still exhibits good performance.