A New Global Tropospheric Delay Model Considering the Spatiotemporal Variation Characteristics of ZTD With Altitude Coefficient

Abstract. The zenith tropospheric delay (ZTD) is an important atmospheric parameter in the wide application of GNSS technology in geoscience. Given that the temporal resolution of the current Global Zenith Tropospheric Delay model (GZTD) is only 24 h, an improved model GZTD2 has been developed by taking the diurnal variations into consideration and modifying the model expansion function. The data set used to establish this model is the global ZTD grid data provided by Global Geodetic Observing System (GGOS) Atmosphere spanning from 2002 to 2009. We validated the proposed model with respect to ZTD grid data from GGOS Atmosphere, which was not involved in modeling, as well as International GNSS Service (IGS) tropospheric product. The obtained results of ZTD grid data show that the global average Bias and RMS for GZTD2 model are 0.2 cm and 3.8 cm respectively. The global average Bias is comparable to that of GZTD model, but the global average RMS is improved by 3 mm. The Bias and RMS are far better than EGNOS model and the UNB series models. The testing results from global IGS tropospheric product show the Bias and RMS (−0.3 cm and 3.9 cm) of GZTD2 model are superior to that of GZTD (−0.3 cm and 4.2 cm), suggesting higher accuracy and reliability compared to the EGNOS model, as well as the UNB series models.

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Measuring spatiotemporal accessibility for pediatric clinical services with multimodal transport modes: an exploratory analysis in Nanjing, China

10.21203/rs.3.rs-34168/v1 ◽

2020 ◽

Author(s):

Xinxin Zhou ◽

LinWang Yuan ◽

Changbin Wu ◽

Zhaoyuan Yu ◽

Lei Wang

Keyword(s):

Healthcare Services ◽

Spatiotemporal Variation ◽

Distribution Data ◽

Dynamic Traffic ◽

Web Mapping ◽

Traffic Conditions ◽

Pediatric Clinic ◽

Multimodal Transport ◽

Variation Characteristics ◽

Transport Modes

Abstract Background: Healthcare accessibility research is developing towards a focus on multimodal transport modes (MTM) and spatiotemporal variation. Dynamic traffic conditions lead residents to make distinct traveling decisions in different timepoints, which has an impact on the spatiotemporal accessibility of healthcare. Pediatric clinic services (PCS) are one of the typical healthcare services that require a diagnosis through a professional physician clinic.Results: This paper aims to examine a methodological framework for the spatiotemporal accessibility of PCS (STA-PCS) and obtains its spatiotemporal variation characteristics. We design a spatial time impedance of multimodal transport modes (STI-MTM) model, which considers residential transport mode choices and adopt a gravity model based on web mapping data and population spatial distribution data to measure STA-PCS. We selected Nanjing, China, as the study area to estimate the STA-PCS value at four timepoints. The results indicate that the spatial aggregate of PCS is evident, and dynamic traffic factors influence the volatility of STA-PCS.Conclusions: This work holds pragmatic implications for policymakers on the STA-PCS considered travel characteristics based on georeferenced social media data.

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Development of a regional tropospheric delay model for GPS-based navigation with emphasis to the Indian Region

Radio Science ◽

10.1029/2007rs003782 ◽

2008 ◽

Vol 43 (4) ◽

pp. n/a-n/a ◽

Cited By ~ 2

Author(s):

K. Parameswaran ◽

Korak Saha ◽

C. Suresh Raju

Keyword(s):

Indian Region ◽

Tropospheric Delay ◽

Delay Model

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Spatiotemporal variation characteristics of analysis accuracy in two-dimensional ultrasonic-measurement-integrated blood flow analysis

The Proceedings of the Dynamics & Design Conference ◽

10.1299/jsmedmc.2016.716 ◽

2016 ◽

Vol 2016 (0) ◽

pp. 716

Author(s):

Hiroko KADOWAKI ◽

Toshiyuki HAYASE ◽

Suguru MIYAUCHI ◽

Kosuke INOUE

Keyword(s):

Blood Flow ◽

Flow Analysis ◽

Spatiotemporal Variation ◽

Ultrasonic Measurement ◽

Two Dimensional ◽

Variation Characteristics ◽

Blood Flow Analysis

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Empirical Orthogonal Function Analysis and Modeling of Global Tropospheric Delay Spherical Harmonic Coefficients

Remote Sensing ◽

10.3390/rs13214385 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4385

Author(s):

Yongchao Ma ◽

Hang Liu ◽

Guochang Xu ◽

Zhiping Lu

Keyword(s):

Empirical Orthogonal Function ◽

Spherical Harmonic ◽

Function Analysis ◽

Meteorological Data ◽

Regional Scale ◽

Global Scale ◽

Tropospheric Delay ◽

Delay Model ◽

Product Model ◽

Orthogonal Function

Based on the ERA-5 meteorological data from 2015 to 2019, we establish the global tropospheric delay spherical harmonic (SH) coefficients set called the SH_set and develop the global tropospheric delay SH coefficients empirical model called EGtrop using the empirical orthogonal function (EOF) method and periodic functions. We apply tropospheric delay derived from IGS stations not involved in modeling as reference data for validating the dataset, and statistical results indicate that the global mean Bias of the SH_set is 0.08 cm, while the average global root mean square error (RMSE) is 2.61 cm, which meets the requirements of the tropospheric delay model applied in the wide-area augmentation system (WAAS), indicating the feasibility of the product strategy. The tropospheric delay calculated with global sounding station and tropospheric delay products of IGS stations in 2020 are employed to validate the new product model. It is verified that the EGtrop model has high accuracy with Bias and RMSE of −0.25 cm and 3.79 cm, respectively, with respect to the sounding station, and with Bias and RMSE of 0.42 cm and 3.65 cm, respectively, with respect to IGS products. The EGtrop model is applicable not only at the global scale but also at the regional scale and exhibits the advantage of local enhancement.

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Establishment of a Real-Time Local Tropospheric Fusion Model

Remote Sensing ◽

10.3390/rs11111321 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1321 ◽

Cited By ~ 3

Author(s):

Yibin Yao ◽

Xingyu Xu ◽

Chaoqian Xu ◽

Wenjie Peng ◽

Yangyang Wan

Keyword(s):

Real Time ◽

Meteorological Data ◽

Rapid Development ◽

Water Vapor Pressure ◽

Auxiliary Information ◽

Satellite System ◽

Tropospheric Delay ◽

Navigation Systems ◽

Delay Model ◽

Fusion Model

The tropospheric delay is one major error source affecting the precise positioning provided by the global navigation satellite system (GNSS). This error occurs because the GNSS signals are refracted while travelling through the troposphere layer. Nowadays, various types of model can produce the tropospheric delay. Among them, the globally distributed GNSS permanent stations can resolve the tropospheric delay with the highest accuracy and the best continuity. Meteorological models, such as the Saastamoinen model, provide formulae to calculate temperature, pressure, water vapor pressure and subsequently the tropospheric delay. Some grid-based empirical tropospheric delay models directly provide tropospheric parameters at a global scale and in real time without any auxiliary information. However, the spatial resolution of the GNSS tropospheric delay is not sufficient, and the accuracy of the meteorological and empirical models is relatively poor. With the rapid development of satellite navigation systems around the globe, the demand for real-time high-precision GNSS positioning services has been growing dramatically, requiring real-time and high-accuracy troposphere models as a critical prerequisite. Therefore, this paper proposes a multi-source real-time local tropospheric delay model that uses polynomial fitting of ground-based GNSS observations, meteorological data, and empirical GPT2w models. The results show that the accuracy in the zenith tropospheric delay (ZTD) of the proposed tropospheric delay model has been verified with a RMS (root mean square) of 1.48 cm in active troposphere conditions, and 1.45 cm in stable troposphere conditions, which is significantly better than the conventional tropospheric GPT2w and Saastamoinen models.

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Spatial and temporal variations of precipitation during 1979–2015 in Jinan City, China

Journal of Water and Climate Change ◽

10.2166/wcc.2017.029 ◽

2017 ◽

Vol 9 (3) ◽

pp. 540-554 ◽

Cited By ~ 4

Author(s):

Xiaodong Chang ◽

Zongxue Xu ◽

Gang Zhao ◽

Tao Cheng ◽

Sulin Song

Keyword(s):

Urban Areas ◽

Temporal Variations ◽

Spatiotemporal Variation ◽

Trend Test ◽

Mountainous Area ◽

Plain Area ◽

Increasing Trend ◽

Variation Characteristics ◽

Jinan City ◽

Northern Plain

Abstract The spatiotemporal variation of precipitation significantly affects regional hydrological processes and the management of water resources worldwide, indirectly contributing to an aggravation in the frequency and intensity of extreme events, especially in urban areas. To analyze the spatiotemporal variation characteristics of precipitation during 1979–2015 in Jinan City, the China Meteorological Forcing Dataset and 12 precipitation-related indices are adopted and analyzed by using Mann–Kendall trend test, Sen's slope estimator and Pettitt test in this study. The results show that: (1) the annual mean precipitation (AMP) shows a gradual increasing trend from the northern plain area to the southern mountainous area; (2) the heaviest summer precipitation occurs in the southern part of downtown with a high frequency, resulting in the drastic amplification of urban rainstorm flood disasters; (3) the spatial distributions of most indices show a gradual increasing trend from the northern plain area to the southern mountainous area, while consecutive dry days show the opposite tendency; and (4) most indices roughly show similar spatiotemporal variation characteristics with AMP, i.e., decreases in southwestern area, but increases in the eastern mountainous region and the north plain area, exhibiting an overall increasing trend at the 1% significance level.

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