Detection And Analysis Of Precipitable Water Vapor Based On All-time Raman Lidar

Atmospheric water vapor is an important meteorological parameter, which is the most active component of the atmosphere. Water vapor is an indispensable factor in the precipitation process, and plays an important role in the global hydrological cycle, meteorology and atmospheric dynamics, which are closely related to the change of precipitable water and its spatial and temporal distribution. Taking into account the rapid spatial and temporal variations of water vapor, the measurements of atmospheric water vapor with high precision and all-time have important scientific significance and application value for the research of precipitation,diffusion of atmospheric pollutants and haze formation and dissipation and so on.Aiming at the problem of the interference from the strong solar background light in daytime measurement, beginning at the existing Raman lidar system, simulation analysis is firstly carried out in the paper, and the influence of the main factors such as the field of view and the filter bandwidth on system performance is discussed in detail,and thus the all-time detection Raman lidar system was optimized design and achieved. According to the characteristics of the lidar echo signal and noise, the solar background suppression method based on wavelet denoising is proposed, and the choose and the effects of decomposition level,wavelet basis function, threshold function and threshold value on the denoising results are discussed in detail. Via a large amount of data analysis and denoising evaluation, we can get suitable decomposition level and threshold for water vapor Raman signals,which is that the wavelet basis is chosen as sym6-8, decomposition layer of 5, and improved threshold and the improved threshold function are adopted, we can achieve a better denoising effect. All-time measurement are carried out and the results show that the detection distance of water vapor can be increased from 1.5-2km to 3km during the daytime, which verifies the validity of the wavelet denoising algorithm and the feasibility of all-time water vapor detection.Based on the data from meteorological station and the water vapor lidar data from the center of lidar remote sensing of Xi'an University of technology from November 2013 to July 2016, long term statistical analysis of atmospheric water vapor in Xi'an area are obtained. The precepitable water vapor in different height range and corresponding ratio is analyzed, and the temporal and spatial variation characteristics and seasonal variation characteristics of precepitable water vapor is also investigated, the variation trend of precepitable water vapor before and after the special weather process (such as rainfall, snowfall) was discussed as well.In addition, the correlation between precipitable water vapor and meteorological factors was analyzed, including the surface temperature, dew point and water vapor pressure, and the pressure. And there is also a strong correlation between precipitation, precipitation days and precipitation efficiency, which provides a foundation for the fields of agricultural production guide and artificial precipitation.