scholarly journals Precipitation Water Vapour Variation in the East Java Region from Data CORS Using GIPSY

2021 ◽  
Vol 936 (1) ◽  
pp. 012001
Author(s):  
Eko Yuli Handoko ◽  
Akbar Kurniawan ◽  
Putra Maulida ◽  
Norma Aji Cemara

Abstract The Global Navigation Satellite System is being developed as an atmospheric remote sensing system through the calculation of Zenith Total Delay. The development of the Continous Operating Reference Station encourages research investigations into Zenith Tropospheric Delay with continuous data and good spatial resolution. This research studies the characteristics of spatial and temporal variations of the Zenith Wet Delay in East Jawa. The case study in East Jawa Province uses 16 Continous Operating Reference Stations. As a comparison, meteorological data from the Badan Meteorologi, Klimatologi, and Geofisika stations are used.The Zenith Total Delay and Zenith Wet Delay values from the Continous Operating Reference Station data are calculated using GIPSY 6.4 Software. The Zenith Wet Delay values are gridded using the kriging method with the size of the grids being 0,25 x 0,25. The ZWD value comparison from the Continous Operating Reference Station and meteorology data has a strong correlation with a coefficient value of 0,712. The mean of Zenith Wet Delay’s trend is increasing by about 0,712 mm/yr. The characteristics of the spatial and temporal variations of the ZWD value are influenced by the monsoon of Asia-Australian, which causes dry and rainy seasons, global phenomena such as El Nino and La Nina, rainfall, local meteorological conditions such as temperature and humidity, weather, and the topography of the stations.

2020 ◽  
Author(s):  
◽  
Juan Manuel Aragón Paz

En el presente trabajo de tesis se desarrolla el diseño e implementación de un sistema de cálculo, en tiempo casi real, de parámetros troposféricos mediante técnicas de navegación global por satélite (GNSS, del inglés Global Navigation Satellite System) para Sudamérica. El desarrollo de la llamada Meteorología GNSS se remonta a principios de la década del 90 donde se encuentran los trabajos fundacionales de esta disciplina. Con el correr de los años, nuevas contribuciones han ido definiendo los reales alcances de esta técnica, poniendo en práctica metodologías cada vez más contrastadas con los métodos de medición tradicionales. En los últimos años los esfuerzos se han enfocado en el desarrollo de procedimientos de cálculo que permitan la utilización de los datos GNSS, cada vez más numerosos, en la asimilación para modelos meteorológicos (en especial los de corto plazo), permitiendo así anticipar eventos con alto impacto a la sociedad civil (tormentas con granizo, inundaciones repentinas, eventos convectivos de mesoescala, etc). Numerosos trabajos se han centrado en la implementación de la meteorología GNSS en Europa, Estados Unidos y Japón. Para la región Sudamericana existen pocos y recientes antecedentes de la aplicación de estas metodologías. Se desarrolló un sistema de cálculo, que permite hacer uso de infraestructura existente en la región, tanto meteorológica como geodésica, enfocado en la obtención de las variables de interés meteorológico como son el retardo troposférico cenital (ZTD, del inglés Zenith Total Delay) y el vapor de agua integrado (IWV, del inglés Integrated Water Vapor). Por otra parte, se han realizado estudios en la aplicación del ZTD y el IWV a índices que permitan dar información rápida acerca de posibles eventos meteorológicos severos. En este trabajo se desarrollan las estrategias diseñadas para la adquisición de los datos, su disponibilidad y alcance. Las problemáticas en la disponibilidad de los mismos, de acuerdo a su procedencia, son descriptas y sorteadas. Seguidamente se brinda una detallada descripción de la metodología de estimación de las observaciones, haciendo especial foco en los parámetros de retardo troposférico cenital (ZTD, del ingles Zenith Tropospheric Delay) y vapor de agua integrado (IWV, del inglés Integrated Water Vapor) mediante el procesamiento de las observaciones GNSS y meteorológicas. Una vez que se tienen los resultados, la presentación de los mismos y los posibles formato de intercambio con las instituciones potenciales usuarias del dato son discutidos. Finalizando esta sección se hace un análisis de la performance del sistema de procesamiento contra las técnicas de radio sondeo (convencionales) y alguno de los modelos de reanálisis mas utilizados. En una segunda etapa se explora las distintas capacidades del IWV GNSS para representar las variaciones temporales y espaciales de la distribución del vapor de agua atmosférico frente a distintas situaciones meteorológicas. También, se describe el desarrollo de posibles índices de alerta que hagan utilización de la información disponible a partir del IWV GNSS. Basándose en bibliografía actualizada se comparan las distintas posibilidades de aplicación a la región de estudio en función de la frecuencia temporal y espacial de las observaciones. Los resultados son presentados analizando un evento de interés meteorológico para la región central de Argentina. Finalmente, los puntos mas salientes del presente trabajo son presentados en las conclusiones. Las mismas abarcan desde el sistema de descarga de datos hasta la implementación de los índices de alerta. Se formulan las posibles derivaciones del trabajo y sus implicancias en la mejora continua de este sistema, que en tiempo casi real, provee información sobre los parámetros de ZTD e IWV. Una sección final describe cuáles son las recomendaciones que permitirían mejoras en la utilización de los datos provistos para conseguir un máximo aprovechamiento de los mismos.


2021 ◽  
Author(s):  
Vicky Jia Liu ◽  
Maaria Nordman ◽  
Nataliya Zubko

<p>Tropospheric delay is one of the major error sources for space geodetic techniques such as Very Long Baseline Interferometry (VLBI) and Global Navigation Satellite System (GNSS). In this study, we compared the agreement of tropospheric zenith wet delay (ZWD) seasonal variations derived from VLBI and GNSS observations at 8 stations that are located at all around the globe. We have analysed time series of 8 years, starting in 2012 until end of 2019. Results show that VLBI_ZWD present clear seasonal variations which depend on the location of each station, in the tropics the variability is more pronounced than in mid-latitudes or polar regions. Furthermore, the VLBI_ZWD also shows a reasonably good agreement with seasonal fit model. When comparing zenith wet delays derived from co-located GNSS and VLBI stations at  cut-off elevation angle, they agree quite well, which is proved by the high correlation coefficients, varying from 0.6 up to 0.95. The biases between the techniques are in mm level and standard errors of the whole time series are in few centimetres.</p>


2014 ◽  
Vol 577 ◽  
pp. 1189-1192
Author(s):  
Hai Shen Wang ◽  
Chuang Shi ◽  
Yun Chang Cao

In this article, data of stations distributed over China was used to calculate tropospheric delay. The result was compared with the tropospheric zenith delay calculated from model. The rules and Characteristic of tropospheric delay over China was analyzed from the aspect of altitude, climate, and change. The results showed that the tropospheric zenith total delay decreased from the coast to the central and western regions, the Tibetan plateau is minimum. Zenith wet delays computed from the models also show an absolute bias of over 20 mm with respect to that of sounding data. The standard deviation is more than 30 mm in the tropical monsoon zone.


Author(s):  
Mayra Chavez ◽  
Wen-Whai Li

Residents living in near-road communities are exposed to traffic-related air pollutants, which can adversely affect their health. Near-road communities are expected to observe significant spatial and temporal variations in pollutant concentrations. Determining these variations in the surrounding areas can help raise awareness among government agencies of these underserved communities living near highways. This study conducted traffic and air quality measurements along with emission and dispersion modeling of the exposure to transportation emissions of a near-road urban community adjacent to the US 54 highway (US 54), with annual average daily traffic (AADT) of 107,237. The objectives of this study were (i) to develop spatial and temporal patterns of pollutant concentration variation and (ii) to apportion the differences in exposure concentrations to background concentrations and those that are contributed from major highways. It was observed that: (a) particulate matter (PM2.5) in near-road communities is dominated by the regional background concentrations which account for more than 85% of the pollution; and (b) only near-road receptors are affected by the traffic-related air pollutant emissions from major highways while spatial and temporal variations of PM2.5 concentrations in near-road communities are less influenced by local traffic, subsiding rapidly to negligible concentrations at 300 m from the road. Modeled PM2.5 concentrations were compared with monitored data. For better air quality impact assessments, higher quality data such as time-specific traffic volume and fleet information as well as site-specific meteorological data could help yield more accurate concentration predictions. Modeled-to-monitored comparison shows that air quality in near-road communities is dominated by regional background concentrations.


2019 ◽  
Vol 11 (11) ◽  
pp. 1321 ◽  
Author(s):  
Yibin Yao ◽  
Xingyu Xu ◽  
Chaoqian Xu ◽  
Wenjie Peng ◽  
Yangyang Wan

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.


2021 ◽  
Vol 13 (22) ◽  
pp. 4567
Author(s):  
Lorenzo Benvenuto ◽  
Paolo Dabove ◽  
Ilaria Ferrando ◽  
Domenico Sguerso

The Global Navigation Satellite System (GNSS) receiver is one of the many sensors embedded in smartphones. The early versions of the Android operating system could only access limited information from the GNSS, allowing the related Application Program Interface (API) to obtain only the location. With the development of the Android 7.0 (Nougat) operating system in May 2016, raw measurements from the internal GNSS sensor installed in the smartphone could be accessed. This work aims to show an initial analysis regarding the feasibility of Zenith Total Delay (ZTD) estimation by GNSS measurements extracted from smartphones, evaluating the accuracy of estimation to open a new window on troposphere local monitoring. Two different test sites have been considered, and two different types of software for data processing have been used. ZTDs have been estimated from both a dual-frequency and a multi-constellation receiver embedded in the smartphone, and from a GNSS Continuously Operating Reference Station (CORS). The results have shown interesting performances in terms of ZTD estimation from the smartphone in respect of the estimations obtained with a geodetic receiver.


2020 ◽  
Author(s):  
Stefano Barindelli ◽  
Andrea Gatti ◽  
Martina Lagasio ◽  
Marco Manzoni ◽  
Alessandra Mascitelli ◽  
...  

<p>InSAR derived Atmospheric Phase Screens (APSs) contain the difference between the atmospheric delay along the SAR sensor line-of-sight of two acquisition epochs: the slave and the master epochs. Using estimates of the atmospheric state at the master epoch, coming from independent sources, the APSs can be transformed into maps of tropospheric Zenith Total Delay (ZTD), that is related to the columnar atmospheric water vapor content. Assimilation experiments of such products into numerical weather prediction (NWP) models have shown a positive impact in the prediction of convective storms.</p><p>In this work, a systematical comparison between various APS and ZTD products aims at determining the optimal procedure to go from APSs to InSAR-derived absolute ZTD maps, i.e. to estimate the master delay map. Two different approaches are compared.</p><p>The first is based on a stack of ZTD maps produced with the assimilation of GNSS ZTD observations into an NWP model. This acts as a physically based interpolator of the GNSS values, which have a spatial resolution much coarser than the InSAR APS one.</p><p>The second is based on a stack of ZTD maps derived by an Iterative Tropospheric Decomposition (ITD) model, as implemented in the GACOS service. In this case, the high-resolution ZTD maps are obtained by an iterative interpolation of a global atmospheric circulation model values and GNSS values where available.</p><p>The results of the comparisons and sensitivity tests on the number of ZTD maps needed to derive the unknown master delay map are shown.</p><p> </p><p> </p><p> </p><p><strong> </strong></p><p><strong> </strong></p>


2020 ◽  
Vol 12 (21) ◽  
pp. 3497
Author(s):  
Pengfei Xia ◽  
Jingchao Xia ◽  
Shirong Ye ◽  
Caijun Xu

A new concept is proposed for estimating the zenith wet delay (ZWD) and atmospheric weighted average temperature by inputting the temperature, total pressure, and specific humidity from surface weather data. In addition, a new ZWD integral method is described for highly accurate calculation of the ZWD from radiosonde observation. To evaluate the advantages of the new discrete integral formula, we utilized the 8-year radiosonde profiles of 85 stations in China from 2010 to 2017 to validate the accuracy of the radiosonde-derived ZWD. The results showed that the mean accuracy of the ZWD derived from radiosonde data was 4.28 mm. Next, the new ZWD model was assessed using two sets of reference values derived from radiosonde data and GNSS precise point positioning in China. The results confirm that the new development improved the accuracy of the estimation of the tropospheric wet delay from the surface meteorological data. The performance of this new model can be seen as an important step toward accurately correcting the tropospheric delay in Global Navigation Satellite System (GNSS) real-time navigation and positioning. It can also be used in GNSS meteorology for weather forecasting and climate research.


2021 ◽  
Vol 13 (5) ◽  
pp. 838
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Chaoyang Zhang ◽  
Yitao Li ◽  
Jun Li

The delays of radio signals transmitted by global navigation satellite system (GNSS) satellites and induced by neutral atmosphere, which are usually represented by zenith tropospheric delay (ZTD), are required as critical information both for GNSS positioning and navigation and GNSS meteorology. Establishing a stable and reliable ZTD model is one of the interests in GNSS research. In this study, we proposed a regional ZTD model that makes full use of the ZTD calculated from regional GNSS data and the corresponding ZTD estimated by global pressure and temperature 3 (GPT3) model, adopting the artificial neutral network (ANN) to construct the correlation between ZTD derived from GPT3 and GNSS observations. The experiments in Hong Kong using Satellite Positioning Reference Station Network (SatRet) were conducted and three statistical values, i.e., bias, root mean square error (RMSE), and compound relative error (CRE) were adopted for our comparisons. Numerical results showed that the proposed model outperformed the parameter ZTD model (Saastamoinen model) and the empirical ZTD model (GPT3 model), with an approximately 56%/52% and 52%/37% RMSE improvement in the internal and external accuracy verification, respectively. Moreover, the proposed method effectively improved the systematic deviation of GPT3 model and achieved better ZTD estimation in both rainy and rainless conditions.


2019 ◽  
Vol 11 (16) ◽  
pp. 1893 ◽  
Author(s):  
Zhangyu Sun ◽  
Bao Zhang ◽  
Yibin Yao

Precise modeling of tropospheric delay and weighted mean temperature (Tm) is critical for Global Navigation Satellite System (GNSS) positioning and meteorology. However, the model data in previous models cover a limited time span, which limits the accuracy of these models. Besides, the vertical variations of tropospheric delay and Tm are not perfectly modeled in previous studies, which affects the performance of height corrections. In this study, we used the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis from 1979 to 2017 to build a new empirical model. We first carefully modeled the lapse rates of tropospheric delay and Tm. Then we considered the temporal variations by linear trends, annual, and semi-annual variations and the spatial variations by grids. This new model can provide zenith hydrostatic delay (ZHD), zenith wet delay (ZWD), and Tm worldwide with a spatial resolution of 1° × 1°. We used the ECMWF ERA-Interim data and the radiosonde data in 2018 to validate this new model in comparison with the canonical GPT2w model. The results show that the new model has higher accuracies than the GPT2w model in all parameters. Particularly, this new model largely improves the accuracy in estimating ZHD and Tm at high-altitude (relative to the grid point height) regions.


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