The vertical distribution of the aerosol layers is depicted by using the lidar data in Jinhua city from 2013 to 2014. The lidar installed in Jinhua is a dual-wavelength Mie polarization Raman lidar. Aerosol layers are searched through gradient method. At the same time, HYSPLIT model is used to tracing the aerosol trajectories. The results show that different heights of aerosol layers have different transportation route. By a case study, the lidar data on December 30, 2013 and May 1, 2014 reveal several vertical aerosol layers. According to the 24-hour backward trajectory of HYSPLIT model, different aerosol layers comes from different places, and this may relate to the winter monsoon in China.
A high sensitivity and global covered observation of carbon dioxide (CO2) is expected by space-borne integrated path differential absorption (IPDA) lidar which has been designed as the next generation measurement. The stringent precision of space-borne CO2 data, for example 1ppm or better, is required to address the largest number of carbon cycle science questions. Spectral purity, which is defined as the ratio of effective absorbed energy to the total energy transmitted, is one of the most important system parameters of IPDA lidar which directly influences the precision of CO2. Due to the column averaged dry air mixing ratio of CO2 is inferred from comparison of the two echo pulse signals, the laser output usually accompanied by an unexpected spectrally broadband background radiation would posing significant systematic error. In this study, the spectral energy density line shape and spectral impurity line shape are modeled as Lorentz line shape for the simulation, and the latter is assumed as an unabsorbed component by CO2. An error equation is deduced according to IPDA detecting theory for calculating the system error caused by spectral impurity. For a spectral purity of 99%, the induced error could reach up to 8.97 ppm.
Lidar is a kind of active optical remote sensing instruments , can be applied to sound atmosphere with a high spatial and temporal resolution. Many parameter of atmosphere can be get by using different inverse algorithm with lidar backscatter signal. The basic setup of a lidar consist of a transmitter and a receiver. To make sure the quality of lidar signal data, the lidar must be calibrated before being used to measure the atmospheric variables. It is really significant to character and analyze lidar optical subsystem because a well equiped lidar optical subsystem contributes to high quality lidar signal data. we pay close attention to telecover test to character and analyze lidar optical subsystem.The telecover test is called four quadrants method consisting in dividing the telescope aperture in four quarants. when a lidar is well configured with lidar optical subsystem, the normalized signal from four qudrants will agree with each other on some level. Testing our WARL-II lidar by four quadrants method ,we find the signals of the four basically consistent with each other both in near range and in far range. But in detail, the signals in near range have some slight distinctions resulting from overlap function, some signals distinctions are induced by atmospheric instability.