Monitoring water vapour with GNSS during a heavy rainfall event in the Spanish Mediterranean area

Priego, E.; Jones, Jonathan; Haza, Maria Joaquina Porres de la; Seco, A.

doi:10.1080/19475705.2016.1201150

Cited by 31 publications

(19 citation statements)

References 16 publications

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“…Many studies have confirmed that PWV variations can effectively reveal the occurrences and the life cycles of precipitation events [40]− [43]. For example, an average increase in PWV of around 30 kg/m 2 occurring before the onset of heavy precipitation was clearly presented by Priego et al [44] for three stations on the Mediterranean coast of Spain. By analyzing the temporal variations in PWV time series over the Arabian Sea and the Bay of Bengal, Singh et al [45] concluded that the relatively higher PWV (around 70−90 mm) during the months of May and June is closely correlated with the onset of south-west monsoon.…”

Section: Introductionmentioning

confidence: 89%

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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Section: Introductionmentioning

confidence: 89%

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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“…PWV calculated using the Bevis coefficients are also shown as a comparison. Both series of PWV were calculated using ZWD and T s obtained at RS stations and Equations (2) and (3). Then, we compared them to the in situ measurements of PWV.…”

Section: Impact Of the New Coefficients On The Pwv Estimated At Rs Stmentioning

confidence: 99%

“…It is based on the possibility of converting the ZWD to precipitable water vapor (PWV) [1], which describes the total content of water vapor in the air column above a GNSS antenna. Short-term monitoring of the water vapor variations is an important element in monitoring and studying of rapid changes of weather conditions [2][3][4]. On the other hand, estimation of the PWV long-term parameters can be used as part of investigation of the climate change [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Improved Empirical Coefficients for Estimating Water Vapor Weighted Mean Temperature over Europe for GNSS Applications

Baldysz

Nykiel

2019

Remote Sensing

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Development of the so-called global navigation satellite system (GNSS) meteorology is based on the possibility of determining a precipitable water vapor (PWV) from a GNSS zenith wet delay (ZWD). Conversion of ZWD to the PWV requires application of water vapor weighted mean temperature (Tm) measurements, which can be done using a surface temperature (Ts) and its linear dependency to the Tm. In this study we analyzed up to 24 years (1994–2018) of data from 49 radio-sounding (RS) stations over Europe to determine reliable coefficients of the Tm-Ts relationship. Their accuracy was verified using 109 RS stations. The analysis showed that for most of the stations, there are visible differences between coefficients estimated for the time of day and night. Consequently, the ETm4 model containing coefficients determined four times a day is presented. For hours other than the primary synoptic hours, linear interpolation was used. However, since this approach was not enough in some cases, we applied the dependence of Tm-Ts coefficients on the time of day using a polynomial (ETmPoly model). This resulted in accuracy at the level of 2.8 ± 0.3 K. We also conducted an analysis of the impact of this model on the PWV GNSS. Analysis showed that differences in PWV reached 0.8 mm compared to other commonly used models.

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“…To date, satellite techniques are equated with the term 'GPS'; currently, the term 'GNSS' is more appropriate due to the availability of three additional GNSS systems: the Russian global navigation satellite system (GLONASS), the European Galileo and the Chinese BeiDou. The main research with GNSS solutions' usage is earthquake effects (Levin et al 2010;Rogozhin 2011;Zhang et al 2014), crustal deformations (Cho and Kuwahara 2013;Bhu et al 2014;Trofimenko and Bykov 2014;Bellone et al 2016), tectonic plate activity (Hammond 2005;Uzel et al 2013), velocity estimation (Kulachi 2000;Pospíšil et al 2012), water vapour (Priego et al 2016), volcanic activity (Miller et al 2003;Caliro et al 2004) and landslides (Kadirov et al 2014;Komac et al 2015;Capilla et al 2016). The availability of a large number of permanent GNSS stations-such as the IGS (International GNSS Service), EPN (EUREF Permanent GNSS Network) and many other local network satellite solutions-increases the accuracy of classical geodetic techniques such as tachometry or levelling in relation to reducing cost and measurement results.…”

Section: Introductionmentioning

confidence: 99%

Annual crustal deformation based on GNSS observations between 1996 and 2016

Maciuk

Szombara

2018

Arab J Geosci

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The article examines the quality of reprocessed GNSS data for determination of seasonal effect in a coordinates' time series. The authors are looking for long-term changes of NEU components on the basis of weekly EPN solutions from the years 1996-2016. This is one of the first such in-depth studies using such a long time period and a large number of stations. Amplitude and its RMS values of fitting function are analysed. The analysis shows that there are significant repeatable coordinate variations: 4.7 mm, 2.9 mm and 8.3 mm for the dN, dE and dU components, respectively. The research also shows a group of coordinates' time series with very small RMS values below the coordinates' accuracy (1 mm for horizontal, 3 mm for vertical components), leading to a very good function fitting with relatively small amplitude magnitudes. The authors did not remark any connection with the above described phenomena and geographical location or type of setting up of a base station.

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Monitoring water vapour with GNSS during a heavy rainfall event in the Spanish Mediterranean area

Cited by 31 publications

References 16 publications

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

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

Improved Empirical Coefficients for Estimating Water Vapor Weighted Mean Temperature over Europe for GNSS Applications

Annual crustal deformation based on GNSS observations between 1996 and 2016

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