Advances in coastal ocean boundary layer detection technology and equipment in China.

Accurate and comprehensive knowledge of the atmospheric environment and its evolution within the coastal ocean boundary layer are necessary for understanding the sources, chemical mechanisms, and transport processes of air pollution in land, sea, and atmosphere. We present an overview of coastal ocean boundary layer detection technology and equipment in China and summarize the progress and main achievements in recent years. China has developed a series of coastal ocean boundary layer detection technologies, including Light Detection and Ranging (LIDAR), turbulent exchange analyzer, air-sea flux analyzer, stereoscopic remote sensing of air pollutants, and oceanic aerosol detection equipment to address the technical bottleneck caused by harsh environmental conditions in coastal ocean regions. Advances in these technologies and equipment have provided scientific assistance for addressing air pollution issues and understanding land-sea-atmosphere interactions over coastal ocean regions in China. In the future, routine atmospheric observations should cover the coastal ocean boundary layer of China.

Validation of the polarized Monte Carlo model of shipborne oceanic lidar returns.

The polarized Monte Carlo (PMC) model has been applied to study the backscattering measurement of oceanic lidar. This study proposes a PMC model for shipborne oceanic lidar simulation. This model is validated by the Rayleigh scattering experiment, lidar equation, and in-situ lidar LOOP (Lidar for Ocean Optics Profiler) returns [Opt. Express30, 8927 (2022)10.1364/OE.449554]. The relative errors of the simulated Rayleigh scattering results are less than 0.07%. The maximum mean relative error (MRE) of the simulated single scattering scalar signals and lidar equation results is 30.94%. The maximum MRE of simulated total scattering signals and LOOP returns in parallel and cross channels are 33.29% and 22.37%, respectively, and the maximal MRE of the depolarization ratio is 24.13%. The underwater light field of the laser beam is also simulated to illustrate the process of beam energy spreading. These results prove the validity of the model. Further analyses show that the measured signals of shipborne lidar LOOP are primarily from the particle single scatterings. This model is significant for analyzing the signal contributions from multiple scattering and single scattering.

Estimation of turbulence parameters in the atmospheric boundary layer of the Bohai Sea, China, by coherent Doppler lidar and mesoscale model.

Obtaining turbulence parameters in the marine atmospheric boundary layer (MABL) is limited by the observation environment and cost. Therefore, estimating based on the weather forecast model or combining the model output with limited observations is a more flexible choice. We conducted cruise observation experiments in the Bohai Sea, China, from May 17 to June 4, 2021. On the basis of the wind profile observed by the coherent Doppler lidar and the temperature, as well as pressure profiles output by the Weather Research and Forecasting (WRF) model, we implemented the Tatarskii turbulence model to estimate the refractive index structure constant C n2 in the atmospheric boundary layer of the Bohai Sea under clear sky. The temporal and spatial variations of turbulence in the Bohai Sea atmospheric boundary layer are studied by combining the vertical velocity variance σ w2, skewness Ske and kurtosis Kur. The performance of simulated C n2 and meteorological parameters in the WRF in the atmospheric boundary layer at the Bohai Sea is evaluated through the experimental measurements of UAV-borne (unmanned aerial vehicle) radiosonde and lidar. Finally, we give the model of the C n2 variation with height in the atmospheric boundary layer at the Bohai Sea. The results show that WRF can better simulate C n2 in most cases. The bias between the measured and simulated C n2 is within one order of magnitude, and the root mean square error ( RMSE ) is within two orders of magnitude. Due to the potential uncertainty of the WRF, the RMSE between the measured and simulated wind speed is 4 ms-1 to 6 ms-1, which is almost two times of the result in previous studies on the underlying land surface. The overall changes of C n2 and σ w2 are similar when the turbulence is well mixed and developed, which shows the consistency in both of optical and dynamics turbulence. But this consistency is not absolute. The temperature difference between the sea surface and the atmosphere leads to the widespread existence of an inversion layer from the sea surface to hundreds of meters in the Bohai Sea. The suppression of the inversion layer weakens the near sea surface turbulence. There is an enhancement of turbulence intensity below the inversion layer and a decrease from the upper inversion layer to top of the boundary layer among the entire boundary layer, also, the position of the inflection point is determined by the height of top of the inversion layer. The main results of this study are the reference significance for further understanding the development and change characteristics of turbulence in the MABL.

Spatio-temporal discrimination of molecular, aerosol and cloud scattering and polarization using a combination of a Raman lidar, Doppler cloud radar and microwave radiometer.

The combined data from the ESA Mobile Raman Polarization and Water Vapor Lidar (EMORAL), the LATMOS Bistatic Doppler Cloud Radar System for Atmospheric Studies (BASTA), and the INOE Microwave Radiometer (HATPRO-G2) have been used to explore the synergy for the spatio-temporal discrimination of polarization and molecular, aerosol and cloud scattering. The threshold-based methodology is proposed to perform an aerosol-cloud typing using the three instruments. It is demonstrated for 24 hours of observations on 10 June 2019 in Rzecin, Poland. A new scheme for target classification, developed collaboratively by the FUW and the OUC, can help determine molecules, aerosol (spherical, non-spherical, fine, coarse), cloud phase (liquid, ice, supercooled droplets) and precipitation (drizzle, rain). For molecular, aerosol, and cloud discrimination, the thresholds are set on the backward scattering ratio, the linear particle depolarization ratio and the backscatter colour ratio, all calculated from lidar signals. For the cloud phase and precipitation categorization, the thresholds are set on the reflectivity and the Doppler velocity derived from cloud radar signals. For boundary layer particles, precipitation, and supercooled droplets separation, the thresholds are set on the profiles of temperature and relative humidity obtained by the microwave radiometer. The algorithm is able to perform separation even under complicated meteorological situation, as in the presented case study.

Development of an Automatic Polarization Raman LiDAR for Aerosol Monitoring over Complex Terrain.

High temporal and spatial resolution profiling of aerosol properties is required to study air pollution sources, aerosol transport, and features of atmospheric structures over complex terrain. A polarization Raman LiDAR with remote operation capability was developed for this purpose and deployed in the Vipava Valley, Slovenia, a location in the Alpine region where high concentrations of aerosols originating from a number of different local and remote sources were found. The system employs two high-power Nd:YAG pulsed lasers at 355 nm and 1064 nm as transmitters and provides the capability to extract the extinction coefficient, backscatter coefficients, depolarization ratio, Ångström exponent, and LiDAR ratio profiles. Automatized remote operation in an indoor environment provides a high duty cycle in all weather conditions. In addition to the detailed description of the device, an assessment of its potential and the retrieval uncertainties of the measured quantities is discussed. System optimization and performance studies include calibration of the depolarization ratio, merging of near-range (analog) and far-range (photon counting) data, determination of overlap functions, and validation of the retrieved observables with radiosonde data. Two cases for assessing LiDAR performance under specific weather conditions (during rain and in the presence of mineral dust) are also presented.

Mobile multi-wavelength polarization Raman lidar for water vapor, cloud and aerosol measurement.

Aiming at the detection of atmospheric water vapor mixing ratio, depolarization ratio, backscatter coefficient, extinction coefficient and cloud information, the Water vapor, Cloud and Aerosol Lidar (WACAL) is developed by the lidar group at Ocean University of China. The lidar consists of transmitter, receiver, data acquisition and auxiliary system. For the measurement of various atmospheric physical properties, three channels including Raman channel, polarization channel and infrared channel are integrated in WACAL. The integration and working principle of these channels are introduced in details. The optical setup, the housekeeping of the system and the data retrieval routines are also presented. After the completion of the construction of the lidar, the WACAL system was installed in Ocean University of China (36.165°N, 120.5°E), Qingdao for the measurement of atmosphere during 2013 and 2014. The measurement principles and some case studies corresponding to various atmospheric physical properties are provided. Finally, the result of one continuous measurement example operated on 13 June 2014 is presented. The WACAL can measure the aerosol and cloud optical properties as well as the water vapor mixing ratio. It is useful for studying the direct and indirect effects of the aerosol on the climate change.

Iodine-filter-based high spectral resolution lidar for atmospheric temperature measurements.

This paper presents a method for measuring atmosphere temperature profile using a single iodine filter as frequency discriminator. This high spectral resolution lidar (HSRL) is a system reconfigured with the transmitter of a mobile Doppler wind lidar and with a receiving subsystem redesigned to pass the backscattering optical signal through the iodine cell twice to filter out the aerosol scattering signal and to allow analysis of the molecular scattering spectrum, thus measuring temperatures. We report what are believed to be the first results of vertical temperature profiling from the ground to 16 km altitude by this lidar system (power-aperture product=0.35 Wm(2)). Concurrent observations of an L band radiosonde were carried out on June 14 and August 3, 2008, in good agreement with HSRL temperature profiles.

Low-altitude atmospheric wind measurement from the combined Mie and Rayleigh backscattering by Doppler lidar with an iodine filter.

This paper briefly discusses the mobile ground-based incoherent Doppler wind lidar system, with iodine filters as receiving frequency discriminators, developed by the Ocean Remote Sensing Laboratory, Ocean University of Qingdao, China. The presented result of wind profiles in October and November 2000, retrieved from the combined Mie and Rayleigh backscattering, is the first report to our knowledge of wind measurements in the troposphere by such a system, where the required independent measurement of aerosol-scattering ratio can also be performed. A second iodine vapor filter was used to lock the laser to absolute frequency reference for both wind and aerosol-scattering ratio measurements. Intercomparison experiments of the lidar wind profile measurements were performed with pilot balloons. Results showed that the standard deviation of wind speed and wind direction, for the 2-4 km altitude range, were 0.985 m/s and 17.9 degrees, respectively.