Quality Assessment of Tropospheric Delay Estimated by Precise Point Positioning in the Korean Peninsula

Park, Han-Earl; Roh, Kyoung Min; Yoo, Seung‐Hwan; Choi, Byung‐Kyu; Chung, Jong‐Kyun; Cho, Jungho

doi:10.11003/jpnt.2014.3.4.131

Cited by 10 publications

(7 citation statements)

References 14 publications

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“…Previous studies have proved that the accuracy of absolute ZTD derived from GAMIT/GLOBK software based on double-differenced observations was better than ±1 cm 39 while the internal accuracy of ZTD derived from PPP module of the Bernese software based on un-differenced observations was better than ±1.3 mm 40 with the mean bias of 7 mm 41 . Therefore, the ZTD parameter estimated from two softwares mentioned above is considered as a reference to evaluate the developed PPP software.…”

Section: The Retrieval Of Ztd and Accuracy-testingmentioning

confidence: 98%

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

Zhao

Yao

2018

Sci Rep

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GPS-based Zenith Tropospheric Delay (ZTD) estimation should be easily obtained in a cost-effective way, however, the most previous studies focus on post-processed ZTD estimates using satellite orbit and clock products with at least 3–9 hours latency provided by International GNSS Service (IGS), which limits the GNSS meteorological application for nowcasting. With the development of IGS’s real-time pilot project (RTPP), this limitation was removed by April, 2013 as real-time satellite orbit and clock products can be obtained on-line. In this paper, on the one hand, the GPS-derived ZTD estimation was evaluated using the IGS final and real-time satellite products based on independently developed PPP software. On the other hand, the analysis of the time series of GPS-derived ZTD by least-square fitting of a broken line tendency for a full year of observations, and a forecasting method for precipitation is proposed based on the ZTD slope in the ascending period. The agreement between ZTD slope and the ground rainfall records suggested that the proposed method is useful for the assisted forecasting, especially for short-term alarms.

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Section: The Retrieval Of Ztd and Accuracy-testingmentioning

confidence: 98%

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

Zhao

Yao

2018

Sci Rep

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“…More details regarding the data processing of GNSS-ZTD in this study are listed in Table II. It has been proven by several studies that the root mean square (RMS) of the differences between the ZTDs estimated by the Bernese and other software used for IGS products (in which different strategies may be used) is in the range from 5 to 7 mm [37], [73], [74].…”

Section: B Data Processing Of Gnss-ztdmentioning

confidence: 99%

An Improved Model for Detecting Heavy Precipitation Using GNSS-Derived Zenith Total Delay Measurements

Wang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In recent years, precipitable water vapor (PWV) have been widely used in heavy precipitation prediction, which is obtained from a conversion of the zenith total delay (ZTD) of the GNSS signal. Since the parameter directly estimated for the tropospheric delay from GNSS data processing is the ZTD, this study investigated the feasibility of directly using ZTD to predict heavy precipitation. Based on the finding that, prior to a heavy precipitation events, ZTD was likely to start with a duration of continuous rise followed by a sharp drop, a new heavy precipitation detection model containing seven predictors derived from ZTD was established. The seven predictors reflect not only the ascending and descending trends, but also long-term and short-term variations in the ZTD time series. Three criteria, representing differnet situations for the formation of heavy precipitation, were also constructed using the predictors to detect heavy precipitation. The optimal set of thresholds for the seven predictors for each summer month were determined based on hourly ZTD and precipitation records at a pair of co-located GNSS/weather station−HKSC-KP in Hong Kong over the period 2010−2017. The model was evaluated using the predictions in 2018 and 2019 to compare against the corresponding precipitation records. Results showed that the new model correctly predicted 98.8% of the heavy precipitation events, with a mean lead time of 4.37 h. Compared with the existing models, the new model also reduced the false alarms by 32.3%. Similar results were also

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“…The ground‐based GNSS observation data were collected from the IGS networkʼs BJFS station and were processed with Bernese Software Version 5.2 with a data sampling rate of 300 s and a direct reference to these data. The Precise Point Positioning module of the Bernese Software can estimate ZTD with an internal coincidence accuracy of ±1.3 mm (Wilgan, ) and an average deviation of ±77 mm (Park et al ., ), and the accuracy meets the meteorological needs. The PM 2.5 , AQI, PM 10 , NO 2 , CO, O 3 and SO 2 data came from the Temple of Heaven monitoring station in Beijing (data source Beijing Environmental Protection Agency), and the AQI and PM 2.5 data were collected every hour.…”

Section: Basic Concepts and Theoriesmentioning

confidence: 99%

A method for predicting short‐time changes in fine particulate matter (PM_2.5) mass concentration based on the global navigation satellite system zenith tropospheric delay

Guo

Zhang

Xia

2019

Meteorological Applications

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In this study, a method of haze prediction has been developed based on zenith tropospheric delay (ZTD). The relationship between ZTD and fine particulate matter (PM2.5, the main component of haze) during hazy periods in Beijing from 2015 to 2018 was analysed. The correlation between ZTD and the PM2.5 series was analysed based on data from three hazy periods with relatively stable weather conditions, no heavy rainfall and relatively continuous data, and the correlation coefficient between ZTD and the PM2.5 series was maintained in the range [0.5207, 0.7883]. The analysis showed a strong correlation between them based on data from three hazy periods with relatively stable weather conditions. To enhance the correlation between ZTD and the PM2.5 sequence, the standard orthogonal wavelet Daubechies (db5) method was used in this research. By removing the influence of the high frequency signal using the method, the ZTD and PM2.5 sequences were reconstructed using the fourth‐layer low frequency coefficients, their correlation coefficient was maintained in the range [0.5540, 0.9067] and the percentage range of the correlation coefficient was increased to [2.46, 16.69]. Finally, the reconstructed PM2.5, ZTD, relative humidity, average wind speed and NO2 series through db5 were used to establish a multiple regression model to predict the change in the PM2.5 mass concentration. The experimental results show that the multivariate regression model after wavelet analysis is superior to the traditional multivariate regression method in predicting the short‐term change of PM2.5 through four statistics values (R2, F, P, S2) of the regression model and that it is effective and feasible for predicting short‐term haze.

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Quality Assessment of Tropospheric Delay Estimated by Precise Point Positioning in the Korean Peninsula

Cited by 10 publications

References 14 publications

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

An Improved Model for Detecting Heavy Precipitation Using GNSS-Derived Zenith Total Delay Measurements

A method for predicting short‐time changes in fine particulate matter (PM_2.5) mass concentration based on the global navigation satellite system zenith tropospheric delay

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Quality Assessment of Tropospheric Delay Estimated by Precise Point Positioning in the Korean Peninsula

Cited by 10 publications

References 14 publications

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

Real-time precise point positioning-based zenith tropospheric delay for precipitation forecasting

An Improved Model for Detecting Heavy Precipitation Using GNSS-Derived Zenith Total Delay Measurements

A method for predicting short‐time changes in fine particulate matter (PM2.5) mass concentration based on the global navigation satellite system zenith tropospheric delay

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A method for predicting short‐time changes in fine particulate matter (PM_2.5) mass concentration based on the global navigation satellite system zenith tropospheric delay