Atmospheric Water Monitoring by Using Ground-Based GPS during Heavy Rains Produced by TPV and SWV

Abstract

The time series of precipitable water (PW) in 30 min intervals has been determined through experimentation and operational application of a ground-based global positioning system (GPS) network in Chengdu Plain, which is used for precise and reliable meteorological research. This study is the first to apply PW to the southwest vortex (SWV) and heavy rain events by using the data from an intensive SWV experiment conducted in summer 2010. The PW derived from the local ground-based GPS network was used in the monitoring and analysis of heavy rain caused by the SWV and the Tibetan Plateau vortex (TPV). Results indicate that an increase in GPS precipitable water (GPS-PW) occurs prior to the development of the TPV and SWV; rainfall occurs mainly during high levels of GPS-PW. The evolution features of GPS-PW in rainfall process caused by different weather systems over the Tibetan Plateau (TP) also differ. These results indicate the reference values for operational applications of GPS-PW data in short-term forecasting and nowcasting of high-impact weather in addition to further investigation of heavy rain caused by the TPV, SWV, and other severe weather systems over the TP.

Comparison of GPS precipitable water vapor and meteorological parameters during rainfalls in Tehran

“…Previous studies showed the relation between rainfall types and intensities in different situations with ground-based GPS PWV variation. In most of the studies, increasing of PWV before rainfall occurrences has been reported (Liou and Huang 2000;Foster et al 2003;Li and Deng 2013). Sharma et al (2009) based on the values of the PWV, lifted index, mean relative humidity and mean refraction of the GPS Radio Occultation (GPS RO) profiles showed that the lifted index, PWV and the relative humidity with up to 90 %, gives the probability of precipitation events.…”

“…Most papers have reported an increase in the PWV values during rain or storms (e.g., Foster et al 2003;Li and Deng 2013) while there are many cases that PWV values have reached the maximum with no rainfall. Here, one of the main goals is to study the meteorological parameters behavior where PWV has a maximum value but the rainfall does not occur.…”

Diurnal variations in integrated water vapor derived from a GPS ground network in the Volga–Ural region of Russia

“…It is now established that assimilation of GPS IWV in numerical weather prediction models improves short-range forecasts of cloudiness and relative humidity at different vertical levels (Bennitt and Jupp, 2012;Smith et al, 2007). In addition, GPS IWV data are useful in situations with high convection for prediction of the development of atmospheric vortices and heavy rainfall (Li and Deng, 2013;Means, 2013;Moore et al, 2015). However, it is noted that weather prediction models are poor predictors of the diurnal course of IWV without GPS data (Radhakrishna et al, 2015).…”

Synthesis Analysis of One Severe Convection Precipitation Event in Jiangsu Using Ground-Based GPS Technology

“…Radhakrishna [19] predicted a convective event 3 h before its occurrence by monitoring GPS-PWV variations. Through analyzing two main systems (the plateau vortex and southwest vortex) that affect the precipitation in South China, Li et al [20] found that GPS-PWV increased rapidly before the development of the plateau vortex and southwest vortex, and precipitation mainly occurred during the time periods with high GPS-PWV levels. Moore et al [21] found that a dense GPS-PWV monitoring network could play a very important role in the timely release of information about floods, debris flows, and other disasters, and such data could effectively complement the 1-6 h numerical forecasting results.…”

“…Previous domestic and overseas studies on the application of GPS-PWV in severe convection weather mainly discovered that there is a close relationship between the total water vapor in the atmosphere, as measured by remote sensing, and the local precipitation, i.e., there is typically significant change in PWV before and after precipitation. However, under severe convection weather, the configuration and movement speed of the synoptic situation will have an important influence on the water vapor transfer rate, dynamic lifting, and thermodynamic variation [20], with the variation among the three determining the start time, development strength, duration, and other weather characteristics. Since current research on practical synoptic processes using GPS-PWV is mostly limited to the correspondence between the PWV variation and the actual rainfall, and research on the physical mechanisms involved is lacking, there are considerable uncertainties regarding this relationship (e.g., there can be a 3-16 h difference between the GPS-PWV and the precipitation peak), making an effective forecast difficult.…”