The indispensable access to real turbulent wake behavior is provided by the pulsed coherent Doppler Light Detection and Ranging (LIDAR) which operates by transmitting a laser beam and detecting the radiation backscattered by atmospheric aerosol particles. The Doppler shift in the frequency of the backscattered signal is analyzed to obtain the line-of-sight (LOS) velocity component of the air motion. From the LOS velocities the characteristic of the turbulent wake can be deduced. The Coherent Doppler LIDAR (CDL) is based on all-fiber laser technology and fast digital-signal-processing technology. The 1.5 µm eye-safe Doppler LIDAR system has a pulse length of 200ns and a pulse repetition frequency of 10 kHz. The speed measurement range is ±50m/s and the speed measurement uncertainty is 0.3 m/s. The 2-axis beam scanner and detection range of 3000m enable the system to monitor the whole wind farming filed. Because of the all-fiber structure adoption, the system is stable, reliable and high-integrated. The wake vortices of wind turbine blades with different spatial and temporal scales have been observed by LIDAR. In this paper, the authors discuss the possibility of using LIDAR measurements to characterize the complicated wind field, specifically wind velocity deficit and terrain effects.
Vertical profiles of the linear particle depolarization ratio p δ of cloud and aerosol in the Tibet Plateau were measured during the Tibetan Plateau atmospheric expedition experiment campaign with water vapor, cloud and aerosol lidar system, which is capable of depolarization ratio measurement. The atmospheric comprehensive observations were performed during July of 2013 at Litang (30.03°N,100.28°E), which is 3949 meters above the mean sea level, Sichuan province, China. It was the first time to detect and obtain the Tibetan Plateau cloud and aerosol lidar depolarization profiles to our knowledge. After completing the plateau experiment campaign, the lidar system measured the atmosphere above coastal area in Qingdao (36.165°N,120.4956°E). In this year, we continued to participate in the plateau experiment campaign in Nagchu (31.5°N,92.05°E), which is 4600 meters above the mean sea level, The Tibet Autonomous Region from 1st, July to 1st, September. Since particle size, shape and refractive index have an impact on linear particle depolarization ratio, one can classify the aerosol types and cloud phase in turn in the Tibetan Plateau and Qingdao area using linear particle depolarization ratio data. Generally, two calibration methods were applied: comparison of the lidar measurement data and CALIPSO simultaneous data method and half-wave plate ±45°switch method. In this paper we applied the comparison calibration method. The correlation coefficient between lidar measurement data and CALIPSO data reaches up to 84.92%, which shows great linear relation. Finally, after the calculation and calibration of the linear particle depolarization ratio measured during the plateau experiment campaign and observation in coastal area, the ice-water mixed cloud (0.15< p δ <0.5), water cloud ( p δ <0.15) and dusty mix(0.2< p δ <0.35) in Tibetan Plateau were occurred and classified. Meanwhile, the cirrus clouds ( p δ <0.5), water cloud, smoke and urban pollution (0.05< p δ <0.2) and dusty mix in Qingdao area were also occurred and classified.
Spaceborne integrated path differential absorption (IPDA) lidar is an active-detection system which is able to perform
global CO2 measurement with high accuracy of 1ppmv at day and night over ground and clouds. To evaluate the
detection performance of the system, simulation of the ground return signal and retrieval algorithm for CO2
concentration are presented in this paper. Ground return signals of spaceborne IPDA lidar under various ground surface
reflectivity and atmospheric aerosol optical depths are simulated using given system parameters, standard atmosphere
profiles and HITRAN database, which can be used as reference for determining system parameters. The simulated
signals are further applied to the research on retrieval algorithm for CO2 concentration. The column-weighted dry air
mixing ratio of CO2 denoted by XCO2 is obtained. As the deviations of XCO2 between the initial values for simulation
and the results from retrieval algorithm are within the expected error ranges, it is proved that the simulation and retrieval
algorithm are reliable.