Using global navigation satellite system data for real-time moisture analysis and forecasting over the Australian region I. The system

2019 ◽  
Vol 69 (1) ◽  
pp. 161 ◽  
Author(s):  
John Le Marshall ◽  
Robert Norman ◽  
David Howard ◽  
Susan Rennie ◽  
Michael Moore ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Real Time ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Australian Region ◽  
Moisture Analysis ◽  
Global Navigation Satellite ◽  
Resolution Data

The use of high spatial and temporal resolution data assimilation and forecasting around Australia’s capital cities and rural land provided an opportunity to improve moisture analysis and forecasting. To support this endeavour, RMIT University and Geoscience Australia worked with the Bureau of Meteorology (BoM) to provide real-time GNSS (global navigation satellite system) zenith total delay (ZTD) data over the Australian region, from which a high-resolution total water vapour field for SE Australia could be determined. The ZTD data could play an important role in high-resolution data assimilation by providing mesoscale moisture data coverage from existing GNSS surface stations over significant areas of the Australian continent. The data were used by the BoM’s high-resolution ACCESS-C3 capital city numerical weather prediction (NWP) systems, the ACCESS-G3 Global system and had been used by the ACCESS-R2-Regional NWP model. A description of the data collection and analysis system is provided. An example of the application of these local GNSS data for a heavy rainfall event over SE Australia/Victoria is shown using the 1.5-km resolution ACCESS-C3 model, which was being prepared for operational use. The results from the test were assessed qualitatively, synoptically and also examined quantitatively using the Fractions Skills Score which showed the reasonableness of the forecasts and demonstrated the potential for improving rainfall forecasts over south-eastern Australia by the inclusion of ZTD data in constructing the moisture field. These data have been accepted for operational use in NWP.

scholarly journals Corrigendum to: Using global navigation satellite system data for real-time moisture analysis and forecasting over the Australian region I. The system

2020 ◽  
Vol 70 (1) ◽  
pp. 394
Author(s):  
John Le Marshall ◽  
Robert Norman ◽  
David Howard ◽  
Susan Rennie ◽  
Michael Moore ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Real Time ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Australian Region ◽  
Moisture Analysis ◽  
Global Navigation Satellite ◽  
Resolution Data

The use of high spatial and temporal resolution data assimilation and forecasting around Australia’s capital cities and rural land provided an opportunity to improve moisture analysis and forecasting. To support this endeavour, RMIT University and Geoscience Australia worked with the Bureau of Meteorology (BoM) to provide real-time GNSS (global navigation satellite system) zenith total delay (ZTD) data over the Australian region, from which a high-resolution total water vapour field for SE Australia could be determined. The ZTD data could play an important role in high-resolution data assimilation by providing mesoscale moisture data coverage from existing GNSS surface stations over significant areas of the Australian continent. The data were used by the BoM’s high-resolution ACCESS-C3 capital city numerical weather prediction (NWP) systems, the ACCESS-G3 Global system and had been used by the ACCESS-R2-Regional NWP model. A description of the data collection and analysis system is provided. An example of the application of these local GNSS data for a heavy rainfall event over SE Australia/Victoria is shown using the 1.5-km resolution ACCESS-C3 model, which was being prepared for operational use. The results from the test were assessed qualitatively, synoptically and also examined quantitatively using the Fractions Skills Score which showed the reasonableness of the forecasts and demonstrated the potential for improving rainfall forecasts over south-eastern Australia by the inclusion of ZTD data in constructing the moisture field. These data have been accepted for operational use in NWP.

scholarly journals Variational Analysis of Simulated Ocean Surface Winds from the Cyclone Global Navigation Satellite System (CYGNSS) and Evaluation Using a Regional OSSE

2018 ◽  
Vol 35 (8) ◽  
pp. 1571-1584 ◽  
Author(s):  
S. Mark Leidner ◽  
Bachir Annane ◽  
Brian McNoldy ◽  
Ross Hoffman ◽  
Robert Atlas
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Global Navigation Satellite System ◽  
Wind Field ◽  
Variational Analysis ◽  
Satellite System ◽  
Navigation Satellite ◽  
Directional Information ◽  
Wind Speeds ◽  
Global Navigation Satellite

AbstractA positive impact of adding directional information to observations from the Cyclone Global Navigation Satellite System (CYNGSS) constellation of microsatellites is observed in simulation using a high-resolution nature run of an Atlantic hurricane for a 4-day period. Directional information is added using a two-dimensional variational analysis method (VAM) for near-surface vector winds that blends simulated CYGNSS wind speeds with an a priori background vector wind field at 6-h analysis times. The resulting wind vectors at CYGNSS data locations are more geophysically self-consistent when using high-resolution 6-h forecast backgrounds from a Hurricane Weather Research and Forecast Model (HWRF) control observing system simulation experiment (OSSE) compared to low-resolution 6-h forecasts from an associated Global Forecast System (GFS) model control OSSE. An important contributing factor is the large displacement error in the center of circulation in the GFS background wind fields that produces asymmetric circulations in the associated VAM analyses. Results of a limited OSSE indicate that CYGNSS winds reduce forecast error in hurricane intensity in 0–48-h forecasts compared to using no CYGNSS data. Assimilation of VAM-CYGNSS vector winds reduces maximum wind speed error by 2–5 kt (1 kt = 0.51 m s−1) and reduces minimum central pressure error by 2–5 hPa. The improvement in forecast intensity is notably larger and more consistent than the reduction in track error. The assimilation of VAM-CYGNSS wind vectors constrains analyses of surface wind field structures during OSSE more effectively than wind speeds alone. Because of incomplete sampling and the limitations of the data assimilation system used, CYGNSS scalar winds produce unwanted wind/pressure imbalances and asymmetries more often than the assimilation of VAM-CYGNSS data.

APLICAÇÃO DE GEOTECNOLOGIAS NA ANÁLISE DE VIABILIDADE TÉCNICA E ECONÔMICA DO PROJETO DE IMPLANTAÇÃO DO IFMA - CAMPUS ITAQUI-BACANGA.

2021 ◽  
Vol 14 (2) ◽  
pp. 105
Author(s):  
Maelckson Bruno Barros Gomes ◽  
André Luis Silva Santos
Keyword(s):  
Real Time ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
Real Time Kinematic ◽  
Global Navigation ◽  
Global Navigation Satellite

<p class="04CorpodoTexto">Este artigo tem por objetivo aplicar geotecnologias para obtenção de informações planialtimétricas a fim de avaliar a viabilidade de implantação do campus Centro Histórico/Itaqui-Bacanga do IFMA. Considerando que para realização de levantamento por métodos tradicionais é recomendado que seja realizado o destocamento e a limpeza do terreno previamente, avaliou-se a realização do levantamento planialtimétrico a partir de um par de receptores <em>Global Navigation Satellite System</em> (GNSS) pelo método <em>Real Time Kinematic</em> (RTK) pós processado e também a partir da realização de levantamento fotogramétrico, utilizando aeronave remotamente pilotada (ARP), popularmente conhecida como drone. Esta análise permitiu demonstrar que o aerolevantamento com a ARP pode ser aplicado na concepção inicial de um projeto de engenharia, conforme classificação do Tribunal de Contas da União (TCU) para níveis de precisão, pois obteve-se uma diferença orçamentária de 19% entre os projetos elaborados a partir das duas geotecnologias.</p><div> </div>

scholarly journals Determination of the Stability of High-Steep Slopes by Global Navigation Satellite System (GNSS) Real-Time Monitoring in Long Wall Mining

2020 ◽  
Vol 10 (6) ◽  
pp. 1952 ◽  
Author(s):  
Xugang Lian ◽  
Zoujun Li ◽  
Hongyan Yuan ◽  
Haifeng Hu ◽  
Yinfei Cai ◽  
...  
Keyword(s):  
Real Time ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
Slope Movement ◽  
Navigation Satellite ◽  
Real Time Monitoring ◽  
Uniform Deformation ◽  
Working Face ◽  
Global Navigation Satellite ◽  
Steep Slopes

Surface movement and deformation induced by underground coal mining causes slopes to collapse. Global Navigation Satellite System (GNSS) real-time monitoring can provide early warnings and prevent disasters. A stability analysis of high-steep slopes was conducted in a long wall mine in China, and a GNSS real-time monitoring system was established. The moving velocity and displacement at the monitoring points were an integrated response to the influencing factors of mining, topography, and rainfall. Underground mining provided a continuous external driving force for slope movement, the steep terrain provided sufficient slip conditions in the slope direction, and rainfall had an acceleration effect on slope movement. The non-uniform deformation, displacement field, and time series images of the slope body revealed that ground failure was concentrated in the area of non-uniform deformation. The non-uniform deformation was concentrated ahead of the working face, the speed of deformation behind the working face was reduced, the instability of the slope body was increased, and the movement of the top of the slope was larger than at the foot. The high-steep slope stability in the mine was influenced by the starting deformation (low stability), iso-accelerated deformation (increased stability), deformation deceleration (reduced stability), and deformation remaining unchanged (improved stability).

scholarly journals Situational Awareness: Mapping Interference Sources in Real-Time Using a Smartphone App

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4130 ◽  
Author(s):  
Hong Nguyen ◽  
Micaela Troglia Gamba ◽  
Emanuela Falletti ◽  
Tung Ta
Keyword(s):  
Real Time ◽  
Global Navigation Satellite System ◽  
Situational Awareness ◽  
Satellite System ◽  
Smartphone App ◽  
Navigation Satellite ◽  
The Past ◽  
Global Navigation ◽  
Global Navigation Satellite

In the past years, many techniques have been researched and developed to detect and identify the interference sources of Global Navigation Satellite System (GNSS) signals. In this paper, we utilize a simple and portable application to map interference sources in real-time. The results are promising and show the potential of the crowdsourcing for monitoring and mapping GNSS interference distribution.

scholarly journals Flood Inundation Mapping by Combining GNSS-R Signals with Topographical Information

2020 ◽  
Vol 12 (18) ◽  
pp. 3026 ◽  
Author(s):  
S L Kesav Unnithan ◽  
Basudev Biswal ◽  
Christoph Rüdiger
Keyword(s):  
High Resolution ◽  
Global Navigation Satellite System ◽  
Satellite System ◽  
North India ◽  
Navigation Satellite ◽  
Flood Inundation ◽  
Threshold Values ◽  
Inundation Maps ◽  
Global Navigation ◽  
Global Navigation Satellite

The Cyclone Global Navigation Satellite System (CYGNSS) mission collects near-global hourly, pseudo-randomly distributed Global Navigation Satellite System - Reflectometry (GNSS-R) signals in the form of signal-to-noise ratio (SNR) point data, which is sensitive to the presence of surface water, due to their operating frequency at L-band. However, because of the pseudo-random nature of these points, it is not possible to obtain continuous flood inundation maps at adequately high resolution. By considering topological indicators, such as height above nearest drainage (HAND) and slope of nearest drainage (SND), which indicate the probability of a certain area being prone to flooding, we hypothesize that combining static topographic information with the dynamic GNSS-R signals can result in large-scale, high-resolution flood inundation maps. Flood mapping was performed and validated with flood extent derived using available Sentinel-1A synthetic aperture radar (SAR) data for flooding in Kerala during August 2018, and North India during August 2017. The results obtained after thresholding indicate that the model exhibits a flooding accuracy ranging from 60% to 80% for lower threshold values. We observed significant overestimation error in mapping inundation across the flooding period, resulting in an optimal critical success index of 0.22 for threshold values between 17–19.

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