Investigation of Precipitable Water Vapor Obtained by Raman Lidar and Comprehensive Analyses with Meteorological Parameters in Xi’an

Abstract

To evaluate the potential of Raman lidar observations for measuring precipitable water vapor (PWV), PWV variations and distribution characteristics were investigated in Xi'an (34.233 • N, 108.911 • E), and its comparisons with meteorological parameters were also analysed. Comparisons of lidar PWV with radiosonde PWV verified the ability and accuracy of using Raman lidars for PWV measurements. The diurnal and monthly variation trends in PWV in different layers are first discussed via the statistical analysis of lidar data from November 2013 to July 2016; different proportions of PWV were found in different layers, and the PWV in each layer presented a slight diurnal change trend and consistent seasonal variation, which was relatively rich in summer, less so in spring and autumn, and relatively deficient in winter. Furthermore, correlation analyses between lidar PWV and meteorological parameters are explored. Water vapor pressure and surface temperature revealed the same inter-seasonal oscillation of PWV, with a correlation coefficient of~0.90. However, incomplete synchronization was found between PWV and relative humidity and precipitation parameters. Higher humidity appeared in the late summer and the beginning of autumn of each year, which was also the case for precipitation and precipitation efficiency. In addition, atmospheric water vapor density profiles and the obtained PWV by Raman lidar are discussed employing a rainfall case, and a comprehensive analysis with meteorological parameters is undertaken. The intensifying characteristics of vertical change in water vapor and the accumulation of PWV in the lower troposphere can be captured by lidar before the onset of rainfall. In contrast to the obvious diurnal change trend, such meteorological parameters as relative humidity, water vapor pressure, and dew-point temperature difference are accompanied with stable trends with a change rate of close to 0 in the rainfall processes; they also show high correlated variations with lidar PWV. Thus, with the advantage of lidar detection, investigation of water vapor profiles and PWV by Raman lidar, and the comprehensive correlation analyses with synchronic meteorological parameters can prove to be good indications of rainfall.

Storage Method of Multi-Channel Lidar Data Based on Tree Structure

“…The data retrieval process is shown in Figure 9. The experimental data comes from the ultraviolet Raman lidar system in the Center for Lidar Remote Sensing Research of Xi'an University of Technology [29]. In the experiment, an industrial control cabinet Pxie-1071 and a data acquisition card Pxi-5105 shown in Figure 10 (a) and (b), developed by NI company, are used as data acquisition equipment, with the main parameters shown in Table 2, which are suitable for the data acquisition in the multi-parameter integrated detection lidar system.…”

Temporal Analysis of GNSS-Based Precipitable Water Vapor during Rainy Days over the Philippines from 2015 to 2017

“…It has been reported that PWV sharply increases before the rainfall event [16,[41][42][43]. There are also reports where PWV has a noticeable decrease in response to heavy rainfall and after its passing [17,[44][45][46][47].…”

Algorithm to Predict the Rainfall Starting Point as a Function of Atmospheric Pressure, Humidity, and Dewpoint

“…As the temperature increases, more vapor pressure can be contained in the air [42,43]. This can be expressed by the Clausius-Clapeyron relationship [44,45].…”