A Troposphere Constraint Method To Improve PPP Ambiguity-Resolved Height Solution

2013 ◽  
Vol 67 (2) ◽  
pp. 249-262 ◽  
Author(s):  
Junbo Shi ◽  
Yang Gao
Keyword(s):  
Meteorological Data ◽  
A Priori ◽  
Precipitable Water ◽  
Conventional Approach ◽  
Integer Ambiguity ◽  
Convergence Time ◽  
Precipitable Water Vapour ◽  
Positioning Accuracy ◽  
Constraint Method ◽  
Decoupled Clock Model

Integer ambiguity resolution is able to improve positioning accuracy and reduce convergence time in Precise Point Positioning (PPP). Although significantly improved horizontal positioning accuracy has been demonstrated, the height solution improvement is found to be less significant, and improving this requires further investigation. In this paper, a troposphere constraint method using precise troposphere corrections is proposed to improve the PPP ambiguity-resolved height solution. This is different from the conventional approach that typically applies meteorological data to calculate the a priori troposphere delay and estimates the residual troposphere delay. The effects of the troposphere delay on PPP ambiguity-resolved height solutions are first studied. Numerical analysis is conducted to ambiguity-resolved positioning results based on the decoupled clock model and hourly Global Positioning System (GPS) observations from a Canadian PPP-inferred troposphere precipitable water vapour system. The results show that by using the proposed method the PPP ambiguity-resolved height accuracy can be further improved to 3·86 cm compared to 5·32 cm using the conventional approach.

scholarly journals On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

2015 ◽  
Vol 3 (6) ◽  
pp. 3861-3895 ◽  
Author(s):  
P. Benevides ◽  
J. Catalao ◽  
P. M. A. Miranda
Keyword(s):  
Water Vapour ◽  
Meteorological Data ◽  
Simple Algorithm ◽  
Precipitable Water ◽  
False Alarms ◽  
Precipitable Water Vapour ◽  
Temporal Behaviour ◽  
Nearby Region ◽  
Single Station ◽  
Rain Events

Abstract. The temporal behaviour of Precipitable Water Vapour (PWV) retrieved from GPS delay data is analysed in a number of case studies of intense precipitation in the Lisbon area, in the period 2010–2012, and in a continuous annual cycle of 2012 observations. Such behaviour is found to correlate positively with the probability of precipitation, especially in cases of severe rainfall. The evolution of the GPS PWV in a few stations is analysed by a least-squares fitting of a broken line tendency, made by a temporal sequence of ascents and descents over the data. It is found that most severe rainfall event occurs in descending trends after a long ascending period, and that the most intense events occur after steep ascents in PWV. A simple algorithm, forecasting rain in the 6 h after a steep ascent of the GPS PWV in a single station is found to produce reasonable forecasts of the occurrence of precipitation in the nearby region, without significant misses in what concerns larger rain events, but with a substantial amount of false alarms. It is suggested that this method could be improved by the analysis of 2-D or 3-D time varying GPS PWV fields, or by its joint use with other meteorological data relevant to nowcast precipitation.

scholarly journals Tropical and Extratropical Cyclone Detection Using Deep Learning

2020 ◽  
Vol 59 (12) ◽  
pp. 1971-1985
Author(s):  
Christina Kumler-Bonfanti ◽  
Jebb Stewart ◽  
David Hall ◽  
Mark Govett
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Meteorological Data ◽  
A Priori ◽  
Precipitable Water ◽  
Extratropical Cyclone ◽  
Detection Accuracy ◽  
Heuristic Model ◽  
Large Sets ◽  
Gfs Model

AbstractExtracting valuable information from large sets of diverse meteorological data is a time-intensive process. Machine-learning methods can help to improve both speed and accuracy of this process. Specifically, deep-learning image-segmentation models using the U-Net structure perform faster and can identify areas that are missed by more restrictive approaches, such as expert hand-labeling and a priori heuristic methods. This paper discusses four different state-of-the-art U-Net models designed for detection of tropical and extratropical cyclone regions of interest (ROI) from two separate input sources: total precipitable water output from the Global Forecast System (GFS) model and water vapor radiance images from the Geostationary Operational Environmental Satellite (GOES). These models are referred to as International Best Track Archive for Climate Stewardship (IBTrACS)-GFS, Heuristic-GFS, IBTrACS-GOES, and Heuristic-GOES. All four U-Nets are fast information extraction tools and perform with an ROI detection accuracy ranging from 80% to 99%. These are additionally evaluated with the Dice and Tversky intersection-over-union (IoU) metrics, having Dice coefficient scores ranging from 0.51 to 0.76 and Tversky coefficients ranging from 0.56 to 0.74. The extratropical cyclone U-Net model performed 3 times as fast as the comparable heuristic model used to detect the same ROI. The U-Nets were specifically selected for their capabilities in detecting cyclone ROI beyond the scope of the training labels. These machine-learning models identified more ambiguous and active ROI missed by the heuristic model and hand-labeling methods that are commonly used in generating real-time weather alerts, having a potentially direct impact on public safety.

scholarly journals On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall

2015 ◽  
Vol 15 (12) ◽  
pp. 2605-2616 ◽  
Author(s):  
P. Benevides ◽  
J. Catalao ◽  
P. M. A. Miranda
Keyword(s):  
Water Vapour ◽  
Meteorological Data ◽  
Simple Algorithm ◽  
Precipitable Water ◽  
False Alarms ◽  
Precipitable Water Vapour ◽  
Temporal Behaviour ◽  
Nearby Region ◽  
Single Station ◽  
Rain Events

Abstract. The temporal behaviour of precipitable water vapour (PWV) retrieved from GPS delay data is analysed in a number of case studies of intense precipitation in the Lisbon area, in the period 2010–2012 and in a continuous annual cycle of 2012 observations. Such behaviour is found to correlate positively with the probability of precipitation, especially in cases of severe rainfall. The evolution of the GPS PWV in a few stations is analysed by a least-squares fitting of a broken line tendency, made by a temporal sequence of ascents and descents over the data. It is found that most severe rainfall events occur in descending trends after a long ascending period and that the most intense events occur after steep ascents in PWV. A simple algorithm, forecasting rain in the 6 h after a steep ascent of the GPS PWV in a single station, is found to produce reasonable forecasts of the occurrence of precipitation in the nearby region, without significant misses in what concerns larger rain events, but with a substantial amount of false alarms. It is suggested that this method could be improved by the analysis of 2-D or 3-D time-varying GPS PWV fields or by its joint use with other meteorological data relevant to nowcast precipitation.

scholarly journals Millimetre Astronomy from the High Antarctic Plateau: Site Testing at Dome C

1999 ◽  
Vol 16 (2) ◽  
pp. 167-174 ◽  
Author(s):  
L. Valenziano ◽  
G. Dall'Oglio
Keyword(s):  
Wind Speed ◽  
Meteorological Data ◽  
Large Fraction ◽  
Precipitable Water ◽  
South Pole ◽  
Site Testing ◽  
The South ◽  
Precipitable Water Vapour ◽  
Average Wind Speed ◽  
Antarctic Plateau

AbstractPreliminary site testing results at Dome C (Antarctica) are presented, using both Automatic Weather Station (AWS) meteorological data (1986–1993) and Precipitable Water Vapour (PWV) measurements made by the authors. A comparison with the South Pole and other sites is made. The South Pole is a well established astrophysical observing site, where extremely good conditions are reported for a large fraction of time during the year. Dome C, where Italy and France are building a new scientific station, is a potential observing site in the millimetre and submillimetre range. AWS are operating at both sites and they have been continuously monitoring temperature, pressure and wind speed and direction for more than ten years. Site testing instruments are already operating at the South Pole (AASTO, Automated Astrophysical Site-Testing Observatory), while light experiments have been running at Dome C (APACHE, Antarctic Plateau Anisotropy CHasing Experiment) during summertime. A direct comparison between the two sites is planned in the near future, using the AASTO. The present analysis shows that the average wind speed is lower at Dome C (∼1 ms−1) than at the South Pole (∼2 ms−1), while temperature and PWV are comparable.

scholarly journals Estimation of Precipitable Water Vapour in Nigeria Using NIGNET GNSS/GPS, NCEP-DOE Reanalysis II and Surface Meteorological Data

2017 ◽  
Vol 28 (2) ◽  
pp. 19-29 ◽  
Author(s):  
Oladiran J. Abimbola ◽  
◽  
Oluwasesan A. Falaiye ◽  
Joseph Omojola ◽  
◽  
...  
Keyword(s):  
Water Vapour ◽  
Meteorological Data ◽  
Precipitable Water ◽  
Precipitable Water Vapour

scholarly journals Linear regression models to predict the tropospheric parameters at the Global Positioning systems’ sites over the East African region

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Richard Cliffe Ssenyunzi ◽  
Bosco Oruru ◽  
Florence Mutonyi D’ujanga
Keyword(s):  
Water Vapour ◽  
Meteorological Data ◽  
Precipitable Water ◽  
Similar Degree ◽  
Tropical Region ◽  
East African ◽  
Precipitable Water Vapour ◽  
Positioning Systems ◽  
Weighted Mean Temperature ◽  
Global Positioning

Currently, the East African tropical region has limited information about Precipitable Water Vapour (PWV) data and yet the region has a high potential for its utilization. This is on the grounds that the East African tropical region is profoundly prone to climate change and fluctuation. Existing studies need data on the detailing and performance evaluation of precipitable water vapour models within East Africa. This has been so as a result of the scattered Global Positioning System (GPS) networks and other alternative water vapour measuring equipments, enormous information gaps and the absence of surface meteorological data. The accessibility and precision of surface meteorological estimations is crucial in deriving accurate GPS PWV data. In this study, the daily average, PWV, pressure, temperature and weighted mean temperature () models have been developed utilizing one year (2013) GPS PWV and European Centre for Medium-Range Weather Forecasts (ECMWF) 5th Re- Analysis PWV (ERA5 PWV), total column water vapour (TCWV), surface pressure and 2 meter (2m) temperature data. The purpose of the developed models is to predict PWV over regions with data gaps where the computation of GPS Zenith Tropospheric Delays (ZTD) is impossible and in cases of station outages. In addition, the models will provide meteorological parameter where meteorological sensors are missing. The GPS PWV accuracy obtained with the developed models shows an average RMSE of 1.54 mm and MnB of 0.32 mm in comparison to the measured GPS PWV data. The ERA5 PWV accuracy obtained with the developed models shows an average RMSE of 0.33 mm and MnB of 0.01 mm in comparison to the measured ERA5 PWV data. Based on the RMSE, it was observed that the site-specific models developed can be utilized to provide estimates of nearly a similar degree of precision compared to the measured values at the thirteen stations.

Investigation of Foehn Events on South Georgia Island using Meteorological Surface Data and GNSS Precipitable Water Vapour

2021 ◽  
Author(s):  
Eshetu Erkihune ◽  
Addisu Hunegnaw ◽  
Felix Norman Teferle
Keyword(s):  
Water Vapour ◽  
Meteorological Data ◽  
Precipitable Water ◽  
Satellite System ◽  
Data Sets ◽  
Precipitable Water Vapour ◽  
Near Surface ◽  
South Georgia ◽  
Circumpolar Current ◽  
Global Navigation Satellite

<p>As one of the most important components of the global hydrologic cycle, atmospheric water vapor shows significant variability in both space and time over a large range of scales. This variability results from the interactions of many different factors, including topography and the presence of specific atmospheric processes. One of the key regions for affecting global climatic variations lies in the sub-Antarctic zone over the Southern Ocean with its Antarctic Circumpolar Current and the associated Antarctic Convergence. There, in this cold and maritime region, lies South Georgia Island with its weather and climate being largely affected by both the dominating ocean currents and the westerly winds in this zone. While the island forms an important outpost for various surface observations in this largely under sampled and extremely remote region, it also forms a barrier for these winds due to its high topography. This, in turn, leads to various local meteorological phenomena, such as warm Foehn winds, which have a significant impact on the near-surface meteorology and contribute to the accelerated glacier retreat observed for the northeast of the island.</p><p>Surface meteorological data have been available for several stations near King Edward Point (KEP) in South Georgia for much of the 20<sup>th</sup> century. Since 2013 and 2014, Global Navigation Satellite System (GNSS) data have been available at five locations around the periphery of the island. In this study, we investigate the consistency between the different surface meteorological data sets and along with GNSS Precipitable Water Vapour we use these to analyse historic Foehn events.</p><p> </p>

scholarly journals Error handling in GPS data processing

MAUSAM ◽  
2021 ◽  
Vol 62 (1) ◽  
pp. 97-102
Author(s):  
J. K. S. YADAV ◽  
R. K. GIRI ◽  
L. R. MEENA
Keyword(s):  
Monsoon Season ◽  
Meteorological Data ◽  
Elevation Angle ◽  
Precipitable Water ◽  
Gps Data ◽  
New Delhi ◽  
Precipitable Water Vapour ◽  
Diurnal Variability ◽  
Spatially Correlated ◽  
Mean Square Errors

We are aware that the processing of GPS data through GAMIT processing software is not free from errors. Some of them are generated due to different modules involved in processing. The data quality depends so many factors, like quality of met-instrument, which supplies the meteorological data, algorithm of processing which based on the network homogeneity or heterogeneity and location of the site, whether it is free from multi-path etc. The root mean square errors for New Delhi, Mumbai, Kolkata, Guwahati and Chennai GPS stations are spatially correlated and observations are weighted according to the satellite elevation angle. Diurnal variability of Integrated Precipitable Water Vapour (IPWV) has been shown its range from 45 mm to 65 mm for New Delhi during the monsoon season, 2008.

scholarly journals The Effect of BDS-3 Time Group Delay and Differential Code Bias Corrections on Positioning

2020 ◽  
Vol 11 (1) ◽  
pp. 104
Author(s):  
Peipei Dai ◽  
Jianping Xing ◽  
Yulong Ge ◽  
Xuhai Yang ◽  
Weijin Qin ◽  
...  
Keyword(s):  
Group Delay ◽  
Assessment System ◽  
Convergence Time ◽  
Single Frequency ◽  
Positioning Accuracy ◽  
Differential Code Bias ◽  
Receiver Clock ◽  
Code Bias ◽  
Point Positioning ◽  
The Impact

The timing group delay parameter (TGD) or differential code bias parameter (DCB) is an important factor that affects the performance of GNSS basic services; therefore, TGD and DCB must be taken seriously. Moreover, the TGD parameter is modulated in the navigation message, taking into account the impact of TGD on the performance of the basic service. International GNSS Monitoring and Assessment System (iGMAS) provides the broadcast ephemeris with TGD parameter and the Chinese Academy of Science (CAS) provides DCB products. In this paper, the current available BDS-3 TGD and DCB parameters are firstly described in detail, and the relationship of TGD and DCB for BDS-3 is figured out. Then, correction models of BDS-3 TGD and DCB in standard point positioning (SPP) or precise point positioning (PPP) are given, which can be applied in various situations. For the effects of TGD and DCB in the SPP and PPP solution processes, all the signals from BDS-3 were researched, and the validity of TGD and DCB has been further verified. The experimental results show that the accuracy of B1I, B1C and B2a single-frequency SPP with TGD or DCB correction was improved by approximately 12–60%. TGD will not be considered for B3I single-frequency, because the broadcast satellite clock offset is based on the B3I as the reference signal. The positioning accuracy of B1I/B3I and B1C/B2a dual-frequency SPP showed that the improvement range for horizontal components is 60.2% to 74.4%, and the vertical components improved by about 50% after the modification of TGD and DCB. In addition, most of the uncorrected code biases are mostly absorbed into the receiver clock bias and other parameters for PPP, resulting in longer convergence time. The convergence time can be max increased by up to 50% when the DCB parameters are corrected. Consequently, the positioning accuracy can reach the centimeter level after convergence, but it is critical for PPP convergence time and receiver clock bias that the TGD and DCB correction be considered seriously.

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