WATER VAPOR MIXING RATIO DISTRIBUTION INVERSION BY RAMAN LIDAR IN BEIJING

BEIJING SiQi Yu1, 2, Dong Liu2 , JiWei Xu2, ZhenZhu Wang2, DeCheng Wu2, Yingjian Wang 2,1 1School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei, Anhui 230026, China 2Key Laboratory of Atmospheric optics, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, Anhui 230031, China *Email: dliu@aiofm.ac.cn ABSTRACT


INTRODUCTION
Water vapor plays a very important role at climate change. Global water vapor amounts increase in a warmer climate, leading to a positive feedback via its enhanced greenhouse effect [1] . Lidars (DIAL and Raman) are the only instruments available for high temporal and vertical resolution of continuous WVMR measurements [2] . What's more, obtaining a dataset of atmospheric water vapor content with high spatial and temporal coverage conduce to understand the vertical structure [3] .
In the current study, the water vapor mixing ratio profiles obtained by the means of Water Aerosol Raman Lidar-Ⅱ in Nanjiao station. Observation period from September 2017 to August 2018. The lidar and the data set, as well as the inversion approach to get water vapor mixing ratio and water ratio are described in Section 2. The results are presented in Section 3, including the relationship between water vapor mixing ratio and water ratio, as well as the statistical results of water vapor mixing ratio.

Experimental site and instrumentation
The instrument used to detect atmosphere is Water Aerosol Raman Lidar-Ⅱ (named as WARL-Ⅱ), which has been installed at the Nanjiao observation station, Beijing, China. Nanjiao station (39.81N,116.48E) located in North China Plain, which experiences distinct seasons, namely, winter (December, January and February), spring (March, April and May), summer (June, July and August) and autumn (September, October and November). Figure1 gives the schematic diagram of WARL-Ⅱ system. WARL-Ⅱ emits at 532nm (output energies per pulse of 150 mJ) and receive elastic channels at parallel and perpendicular polarization channels at 532 nm as well as Raman-shifted channels at 607nm (from N2) and 660nm (from H2O). The spatial and temporal resolution of WARL-Ⅱ is 7.5m and 5minutes, respectively. The ground-based passive device continuously measured aerosol and cloud vertical distribution and humidity profiles during the studied period.

Ground-based LIDAR
The Raman lidar is an efficient measurement tool of the mixing ratio of water vapor to dry air. A classical retrieval approach of water vapor mixing ratio(WVMR) provided by Ansmamn et al. [4] at 1992,which can be defined as follows [5] : (1) Where, the P denotes the Raman-shifted return lidar signals from distance z at the laser wavelength for the water vapor (660 nm) and the nitrogen(607 nm). The ᆁ denotes the light extinction at wavelength , as well as 'aer' and 'mol' is represent for aerosol extinction and molecular extinction respectively. The water vapor mixing ratio calibration constant K = ഊలబళ ഊలలబ could determine from a comparison of the lidar measurement with critically evaluated data from a radiosonde ascent.
Generally, the Raman signal are operated more conveniently during night time. This is because, the lidar return signal is dominated by noise during day-time.

Radiosondes
The Radiosonde water ratio(WR) profile retrieval is according to equation(2,3), which are used by Wu et al.2016 [6] . Where, RH denotes relative humidity, S denotes specific humidity. P is the atmospheric pressure, and PS is the saturated vapor pressure (mb) at temperature T ( ) and can be calculated by equation (3).  Figure 2 is the comparison results between WARLand radiosonde. It is obtained for profile by the linear regression method. The regression analysis results used the data of three days of October ,2017, 13,19 and 23 respectively. The correlation coefficient is 0.939 and that means the calibration of WARL-Ⅱ measurement can give a reasonably accurate estimate of water vapor profile for the routine observation.

statistical results of water vapor vertical distribution
As shown in Figure 3, statistical analysis results of Water Vapor Mixing Ratio (WVMR) measured by lidar among spring, summer, autumn and winter. Atmospheric observations of autumn were performed from 1 September to 30 November 2017. The period of winter is between 00:00 LST on 1 December 2017 and 24:00 LST on 28   [7] . Nanjiao station is at the monsoon zone, which with seasonal rainfall variability. In order to explain the relationship of water vapor mixing ratio and precipitation, seasonal mean precipitation at 116.48E,39.81N from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalyzed data are examined in Fig. 4. The four seasons of Figure 4 cover the same time period of lidar observation. According to Figure 3 and figure 4, water vapor mixing ratio measured by lidar have a good consistency with precipitation. The nocturnal value of WVMR in summer is the largest, while in winter is minimum. The reason for the difference obvious for the monsoon. Figure 5 reveals the correlation between monthly mean WVMR and monthly mean total cloud cover.
To ensure the accuracy of the measurement, the measured the water vapor profiles measured by WARL-Ⅱ statistic from 00:00 LST to 06:00 LST and 18:00 LST to 24:00LST. The data of monthly mean total cloud cover is from (NCEP/NCAR) website. Exclude October 2017 and January 2018, red line and blue line have consistent trend. Frequency that occurs during the day of Clouds may contribute to the result.