Lidar Attenuation Research Articles

A comparison of the Information Content of Orthogonally Polarized Components of Lidar Echo Signal for Evaluating Hydrooptical Characteristics of the Near-Surface Layer

A series of lidar measurements were conducted at stations with a homogeneous vertical distribution of hydrooptical char acteristics in the near-surface layer using a two-channel shipborne polarization lidar PLD-1. Lidar sounding was accompanied by synchronous contact measurements of a number of hydrooptical characteristics. A large dataset of measurement data was obtained in waters where hydrooptical characteristics varied widely. As a result of the statistical processing of these data, regression relationships were obtained linking the seawater beam attenuation coefficient c, absorption coefficient a, and diffuse attenuation coefficient Kd to the lidar attenuation coefficients of the co- and cross-polarized components. In most cases, a linear relationship between hydrooptical characteristics and the lidar attenuation coefficients of the polarized components is observed. These rela tionships are characterized by high values of the coefficient of determination — from 0.8 to 0.95. An exception is the relationship between the seawater beam attenuation coefficient c and the lidar attenuation coefficient of the cross-polarized component, where a second-degree polynomial is used to describe this relationship (coefficient of determination is 0.88). Data on the hydrooptical characteristics obtained using the cross-polarized component of the lidar echo signal mostly duplicate the data of the co-polarized component. However, the use of a two-channel optical receiving system increases the reliability and accuracy of the obtained data and provides the possibility of controlling the homogeneity of the underwater section of the sounding path.

Simultaneous sensing profiles of beam attenuation coefficient and volume scattering function at 180° using a single-photon underwater elastic-Raman lidar.

Lidar has emerged as a promising technique for vertically profiling optical parameters in water. The application of single-photon technology has enabled the development of compact oceanic lidar systems, facilitating their deployment underwater. This is crucial for conducting ocean observations that are free from interference at the air-sea interface. However, simultaneous inversion of the volume scattering function at 180° at 532 nm (βm) and the lidar attenuation coefficient at 532 nm (K l i d a r m) from the elastic backscattered signals remains challenging, especially in the case of near-field signals affected by the geometric overlap factor (GOF). To address this challenge, this work proposes adding a Raman channel, obtaining Raman backscattered profiles using single-photon detection. By normalizing the elastic backscattered signals with the Raman signals, the sensitivity of the normalized signal to variations in the lidar attenuation coefficient is significantly reduced. This allows for the application of a perturbation method to invert βm and subsequently obtain the K l i d a r m. Moreover, the influence of GOF and fluctuations in laser power on the inversion can be reduced. To further improve the accuracy of the inversion algorithm for stratified water bodies, an iterative algorithm is proposed. Additionally, since the optical telescope of the lidar adopts a small aperture and narrow field of view design, K l i d a r m tends to the beam attenuation coefficient at 532 nm (cm). Using Monte Carlo simulation, a relationship between cm and K l i d a r m is established, allowing cm derivation from K l i d a r m. Finally, the feasibility of the algorithm is verified through inversion error analysis. The robustness of the lidar system and the effectiveness of the algorithm are validated through a preliminary experiment conducted in a water tank. These results demonstrate that the lidar can accurately profile optical parameters of water, contributing to the study of particulate organic carbon (POC) in the ocean.

Sensing profiles of the volume scattering function at 180° using a single-photon oceanic fluorescence lidar.

A novel oceanic fluorescence lidar technique has been proposed and demonstrated for remotely sensing the volume scattering function at 180° (βf), which can be used to further retrieve the profiles of the absorption coefficient of phytoplankton (aph) at 532 nm and chlorophyll concentration (Chl). This scheme has these features. 1) The single-photon detection technology is employed to enhance the detection sensitivity to the single-photon level, enabling the oceanic lidar to obtain fluorescence backscatter profiles. 2) In terms of algorithms, the Raman backscattered signals of the water are utilized to normalize the backscattered signals of chlorophyll fluorescence, effectively minimizing the depth-dependent variation of the differential lidar attenuation coefficient (Δ K l i d a r f r). To reduce the contamination of fluorescence signals in the Raman backscatter signals, a Raman filter with a bandwidth of 6 nm was chosen. Subsequently, a perturbation method is utilized to invert the βf of the fluorescence lidar. Finally, aph and Chl profiles can be inverted based on empirical models. 3) The value of Δ K l i d a r f r used in inversion is obtained through a semi-analytic Monte Carlo simulation. According to theoretical analysis, the maximum relative error of βf for Chl ranging from 0.01 mg/m3 to 10 mg/m3 is less than 13 %. To validate this approach, a field experiment was conducted aboard the R/V Tan Kah Kee in the South China Sea from September 4th to September 5th, 2022, resulting in continuous subsurface profiles of βf, aph, and Chl. These measurements confirm the robustness and reliability of the oceanic single-photon fluorescence lidar system and the inversion algorithm.

Lidar attenuation coefficient in the global oceans: insights from ICESat-2 mission.

The attenuation coefficient of natural waters plays a significant role in our understanding of hydrology from both the oceanographic and biological point of view. The advent of near-continuous observations by sophisticated space-based lidars now offers an unprecedented opportunity to characterize attenuation coefficients over open oceans on global and regional scales. At present, however, literature reports of lidar-derived attenuation coefficient estimates (klidar, m-1) in oceanic waters are very limited. In this study, we present a global survey of klidar derived from ATLAS/ICESat-2 nighttime measurements. Our results augment the existing passive sensor ocean color data set with a new diurnal component and extend the record to now include previously unavailable polar nighttime observations. The values of ATLAS measured klidar at 532 nm are between 0.045 and 0.39 m-1 with the higher values (>0.15 m-1) correlated with coastal waters and sea ice covered oceans. The average klidar in clearest oligotrophic ocean gyres is ∼0.058 ± 0.012 m-1 at 532 nm. The results reported here demonstrate the feasibility of using ATLAS/ICESat-2 lidar measurements for global klidar studies, which will in turn provide critical insights that enable climate models to correctly describe the amount of light present under sea ice, and for heat deposition studies in the upper ocean.

Sensing the profile of particulate beam attenuation coefficient through a single-photon oceanic Raman lidar.

A lidar technique has been proposed and demonstrated for remotely sensing particulate beam attenuation coefficient (cp) profiles using the Raman backscattered signal from water. In Raman lidar, the backscatter coefficient at 180° can be considered constant, allowing for the determination of the lidar attenuation coefficient (Klidar) from the Raman backscattered signal. This scheme has these features. 1) The bandwidth of the filter that used to extract the Raman component from the backscattered signal of the lidar was optimized to ensure sufficient lidar signal strength while minimizing the influence of chlorophyll fluorescence on inversion. 2) A receiving telescope with narrow field of view (FOV) and small aperture was utilized to suppress multi-scattering components in the backscattered signal. 3) A relationship between the beam attenuation coefficient (c) and Klidar was established after simulations via a semi-analytic Monto Carlo. 4) The value of cp was obtained by subtracting the attenuation coefficient of pure seawater (cw) from c. According to the theoretical analysis, the maximum relative error of cp is less than 15% for chlorophyll concentrations up to 10 mg/m3. Due to the water Raman backscattered signal being several orders of magnitude lower than the elastic backscattered signal, a single-photon detector is required to significantly improve the detection sensitivity to the single-photon level. To validate this approach, a field experiment was conducted aboard the R/V Tan Kah Kee in the South China Sea from September 4th to September 5th, 2022, and continuous subsurface profiles of cp were obtained. These measurements confirm the robustness and reliability of the oceanic single-photon Raman lidar system and the inversion method.

Multi-sensor airborne lidar requires intercalibration for consistent estimation of light attenuation and plant area density

Leaf area is a key structural characteristic of forest canopies because of the role of leaves in controlling many biological and physical processes occurring at the biosphere-atmosphere transition. High pulse density Airborne Laser Scanning (ALS) holds promise to provide spatially resolved and accurate estimates of plant area density (PAD) in forested landscapes, a key step in understanding forest functioning: phenology, carbon uptake, transpiration, radiative balance etc. Inconsistencies between different ALS sensors is a barrier to generating globally harmonised PAD estimates. The basic assumption on which PAD estimation is based is that light attenuation is proportional to vegetation area density. This study shows that the recorded extinction strongly depends on target detectability which is influenced by laser characteristics (power, sensitivity, wavelength). Three different airborne laser scanners were flown over a wet tropical forest at the Paracou research station in French Guiana. Different sensors, flight heights and transmitted power levels were compared. Light attenuation was retrieved with an open source ray-tracing code (http://amapvox.org). Direct comparison revealed marked differences (up-to 25% difference in profile-averaged light attenuation rate and 50% difference at particular heights) that could only be explained by differences in scanner characteristics. We show how bias which may occur under various acquisition conditions can generally be mitigated by a sensor intercalibration. Alignment of light weight lidar attenuation profiles to ALS reference attenuation profiles is not always satisfactory and we discuss what are the likely sources of discrepancies. Neglecting the dependency of apparent light attenuation on scanner properties may lead to biases in estimated vegetation density commensurate to those affecting light attenuation estimates. Applying intercalibration procedures supports estimation of plant area density independent of acquisition characteristics.

Precise detection of water surface through the analysis of a single green waveform from bathymetry LiDAR.

Determination of the correct water surface height (WSH) from green laser (532 nm) echoes alone in bathymetry LiDAR is challenging, as the green laser return near the water surface involves both specular reflection from the air-water interface and backscattered return from the water volume. In this paper, a low-complexity method based on linear approximation of the leading edge (LLE) is proposed. The results of this LLE method were compared with those of three common algorithms of peak detection, half peak power, and surface-volume-bottom implemented on airborne datasets with various surface roughness conditions. In addition, the method was evaluated in waters with a wide range of optical properties through a controllable tank experiment. The uncertainties in the WSHs of all algorithms were greater when the water volume backscattering dominated the surface return; they were sensitive to variations in the optical properties of water, and increased exponentially with decreasing LiDAR attenuation coefficient (KLiDAR). Comparatively, the LLE algorithm had the fastest computational speed and demonstrated the best performance in situations where specular reflection or volume backscatter return was dominant, with average and maximum errors of less than 0.06 and 0.13 m, respectively.

Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks

Abstract. In mixed-phase clouds, the variable mass ratio between liquid water and ice as well as the spatial distribution within the cloud plays an important role in cloud lifetime, precipitation processes, and the radiation budget. Data sets of vertically pointing Doppler cloud radars and lidars provide insights into cloud properties at high temporal and spatial resolution. Cloud radars are able to penetrate multiple liquid layers and can potentially be used to expand the identification of cloud phase to the entire vertical column beyond the lidar signal attenuation height, by exploiting morphological features in cloud radar Doppler spectra that relate to the existence of supercooled liquid. We present VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn), a retrieval based on deep convolutional neural networks (CNNs) mapping radar Doppler spectra to the probability of the presence of cloud droplets (CD). The training of the CNN was realized using the Cloudnet processing suite as supervisor. Once trained, VOODOO yields the probability for CD directly at Cloudnet grid resolution. Long-term predictions of 18 months in total from two mid-latitudinal locations, i.e., Punta Arenas, Chile (53.1∘ S, 70.9∘ W), in the Southern Hemisphere and Leipzig, Germany (51.3∘ N, 12.4∘ E), in the Northern Hemisphere, are evaluated. Temporal and spatial agreement in cloud-droplet-bearing pixels is found for the Cloudnet classification to the VOODOO prediction. Two suitable case studies were selected, where stratiform, multi-layer, and deep mixed-phase clouds were observed. Performance analysis of VOODOO via classification-evaluating metrics reveals precision > 0.7, recall ≈ 0.7, and accuracy ≈ 0.8. Additionally, independent measurements of liquid water path (LWP) retrieved by a collocated microwave radiometer (MWR) are correlated to the adiabatic LWP, which is estimated using the temporal and spatial locations of cloud droplets from VOODOO and Cloudnet in connection with a cloud parcel model. This comparison resulted in stronger correlation for VOODOO (≈ 0.45) compared to Cloudnet (≈ 0.22) and indicates the availability of VOODOO to identify CD beyond lidar attenuation. Furthermore, the long-term statistics for 18 months of observations are presented, analyzing the performance as a function of MWR–LWP and confirming VOODOO's ability to identify cloud droplets reliably for clouds with LWP > 100 g m−2. The influence of turbulence on the predictive performance of VOODOO was also analyzed and found to be minor. A synergy of the novel approach VOODOO and Cloudnet would complement each other perfectly and is planned to be incorporated into the Cloudnet algorithm chain in the near future.

A Shipborne Photon-Counting Lidar for Depth-Resolved Ocean Observation

Depth-resolved information is essential for ocean research. For this study, we developed a shipborne photon-counting lidar for depth-resolved oceanic plankton observation. A pulsed fiber laser with frequency doubling to 532 nm acts as a light source, generating a single pulse at the micro-joule level with a pulse width of less than 1 ns. The receiver is capable of simultaneously detecting the elastic signal at two orthogonal polarization states, the Raman scattering from seawater, and the fluorescence signal from chlorophyll A. The data acquisition system utilizes the photon-counting technique to record each photon event, after which the backscattering signal intensity can be recovered by counting photons from multiple pulses. Benefitting from the immunity of this statistical detection method to the ringing effect of the detector and amplifier circuit, high-sensitivity and high-linearity backscatter signal measurements are realized. In this paper, we analyze and correct the after-pulse phenomenon of high-linearity signals through experiments and theoretical simulations. Through the after-pulse correction, the lidar attenuation coefficient retrieved from the corrected signal are in good agreement with the diffuse attenuation coefficients calculated from the in situ instrument, indicating the potential of this shipborne photon-counting lidar for ocean observation applications.

Lidar Attenuation Through a Physical Model of Grass-Like Vegetation

Abstract Off-road autonomous vehicles face a unique set of challenges compared to those designed for road use. Lane markings and road signs are unavailable, with soft soils, mud, steep slopes, and vegetation taking their place. Autonomy struggles with shrubbery, saplings, and tall grasses. It can be difficult to determine if this vegetation or what it obscures is drivable. Modeling and simulation of autonomy sensors and the environments they interact with enhances and accelerates autonomy development, but analytical models found in the literature and our in-house simulation software did not agree on how well lidar penetrates grass-like vegetation. To test our simulator against the analytical model, we constructed vegetation mock-ups that conform to the assumptions of the analytical model and measured the pass-through rate on calibrated lidar targets. Vegetation density, lidar-to-vegetation distance, and target reflectivity were varied. A random effects model was used to address the dependence introduced by repeated measures, which increased accuracy while reducing time and cost. Stem density impacted total beam return count and grass patch pass-through rate. Target reflectivity results varied by lidar unit, and three-way factor interaction was significant. Results suggest benchmarking experiments could be useful in autonomy development. Permission to publish was granted by Director, Geotechnical & Structures Laboratory.

Shipborne variable-FOV, dual-wavelength, polarized ocean lidar: design and measurements in the Western Pacific.

For the requirement of high-precision vertical profile of the polarization and optical properties of natural seawater, a ship-borne variable-FOV, dual-wavelength, polarized ocean lidar system is designed to obtain the volume linear depolarization ratio (VDR), color ratio and optical parameter profiles of seawater. With the high signal-to-noise ratio, which benefits from the high power (355 nm with 120 mJ, 532 nm with 200 mJ) solid-state laser and a photon counting recorder with a sampling rate of 1 GHz, the attenuated backscattered signal of seawater in the western Pacific campaign reaches to the depth of 50 m, where a plankton layer presents. The receiver of lidar is capable of switching to wide and narrow field of view (FOV), respectively, to obtain the lidar attenuation coefficient Klidar, which is in good agreement with the beam attenuation coefficient of seawater c with a narrow FOV and diffuse attenuation coefficient Kd with a wide FOV. Besides, the Klidar, and the VDR, at two wavelengths of 355 nm and 532 nm are compared to explore the possibility of multi-wavelength of laser application in the ocean lidar. The VDR and the color ratio profiles have a desirable correlation with the in-situ measurement of chlorophyll a (Chla) and chromophoric dissolved organic matter (CDOM) profiles, respectively. With the combination of the Klidar, the VDR and the color ratio profiles, measured in different regions and time periods during the campaign, the multi-wavelength and polarization lidar shows its potential to explore various ocean compositions, such as the ocean particles size shape, the species and vertical migration characteristics of planktons, and the profile distribution of the ocean compositions.

A Dual-Wavelength Ocean Lidar for Vertical Profiling of Oceanic Backscatter and Attenuation

Ocean water column information profiles are essential for ocean research. Currently, water column profiles are typically obtained by ocean lidar instruments, including spaceborne, airborne and shipborne lidar, most of which are equipped with a 532 nm laser; however, blue wavelength penetrates more for open ocean detection. In this paper, we present a novel airborne dual-wavelength ocean lidar (DWOL), equipped with a 532 and 486 nm laser that can operate simultaneously. This instrument was designed to compare the performance of 486 and 532 nm lasers in a single detection area and to provide a reference for future spaceborne oceanic lidar (SBOL) design. Airborne and shipborne experiments were conducted in the South China Sea. Results show that—for a 500-frame accumulation—the 486 nm channel obtained volume profiles from a depth of approximately 100 m. In contrast, the vertical profiles obtained by the 532 nm channel only reached in a depth of 75 m, which was approximately 25% less than that of 486 m channel in the same detection area. Results from the inverse lidar attenuation coefficient α(z) for the DWOL show that the maximum value of α(z) ranged from 40 to 80 m, which was consistent with the chlorophyll-scattering layer (CSL) distribution measured by the shipborne instrument. Additionally, α486(z) decreased for depth beyond 80 m, indicating that the 486 nm laser can potentially penetrate the entire CSL.

Design and validation of a shipborne multiple-field-of-view lidar for upper ocean remote sensing

The oceanic lidar, which has the advantage of profiling the properties of the upper ocean, is a promising active remote sensing tool for complementing the passive ocean color remote sensing in the three-dimensional observation of ocean. This paper introduces the design and validation of a shipborne multiple-field-of-view (MFOV) lidar. With the input of simultaneous in situ data, the lidar signals and the retrieved lidar attenuation coefficient α are validated quantitatively using simulation results. The simulation methods include quasi-single-scattering lidar equation, Monte Carlo (MC) method, and analytical model. The experimental lidar signals are consistent with the simulated lidar signals with coefficient of determination R2>0.91, and α retrieved from experimental lidar signals corresponds well with the simulated values with root mean square (RMS) of relative error δ<0.18. The results at different field of view (FOV) indicate the relationship between the beam attenuation coefficient c, diffuse attenuation coefficient Kd, and α. This work is beneficial to the research on the mechanism, retrieval and application of oceanic lidar.

Polarized lidar and ocean particles: insights from a mesoscale coccolithophore bloom.

Oceanographic lidar can provide remote estimates of the vertical distribution of suspended particles in natural waters, potentially revolutionizing our ability to characterize marine ecosystems and properly represent them in models of upper ocean biogeochemistry. However, lidar signals exhibit complex dependencies on water column inherent optical properties (IOPs) and instrument characteristics, which complicate efforts to derive meaningful biogeochemical properties from lidar return signals. In this study, we used a ship-based system to measure the lidar attenuation coefficient (α) and linear depolarization ratio (δ) across a variety of optically and biogeochemically distinct water masses, including turbid coastal waters, clear oligotrophic waters, and calcite rich waters associated with a mesoscale coccolithophore bloom. Sea surface IOPs were measured continuously while underway to characterize the response of α and δ to changes in particle abundance and composition. The magnitude of α was consistent with the diffuse attenuation coefficient (Kd), though the α versus Kd relationship was nonlinear. δ was positively related to the scattering optical depth and the calcite fraction of backscattering. A statistical fit to these data suggests that the polarized scattering properties of calcified particles are distinct and contribute to measurable differences in the lidar depolarization ratio. A better understanding of the polarized scattering properties of coccolithophores and other marine particles will further our ability to interpret polarized oceanographic lidar measurements and may lead to new techniques for measuring the material properties of marine particles remotely.

Iterative retrieval method for ocean attenuation profiles measured by airborne lidar.

Lidar remote sensing for ocean optical properties has been increasingly applied because of its ability to provide vertical structure information, which cannot be directly obtained by ocean color remote sensing. However, the application of this technology demands an inversion method to infer two quantities, i.e., attenuation and backscatter, from a single measurement. Here, a new iterative retrieval method is demonstrated to deduce the attenuation coefficient from ocean lidar return signals. One calculates the logarithmic backscatter-to-attenuation ratio k by an iterative solution based on a bio-optical model. Procedural examples of lidar-processing results-from raw data to attenuation-are presented, and the inversion results are compared with in situ measurements. The correlation coefficient R between the lidar-retrieval and in situ measurements is 0.8, and the root mean square error (RMSE) is 0.032. We then map the vertical structure of the lidar-retrieved attenuation along airborne lidar flight tracks and discuss the influences of k, the reference depth zm, and the reference value αm. Consequently, the reference value has little influence on the results for high-optical-thickness water, and k is the main error source in lidar return inversion. Primary results indicate that this method provides a more accurate k and improves the inversion accuracy of the lidar attenuation coefficient.

Instrument response effects on the retrieval of oceanic lidar.

Seawater properties can be retrieved from oceanic lidar returns. However, the actual returns include the ideal returns convolved by the instrument response, which inevitably introduces retrieval error. In this paper, instrument response effects on the retrieval of oceanic lidar are analyzed from different aspects. The results demonstrate that the retrieval of the lidar attenuation coefficient near the water surface is affected by the instrument response in homogeneous water. Considering the ratio of the signal distortion region (relative error of attenuation >10%) to the maximum detection depth (three dynamic ranges) is less than 20%, the pulse width of the instrument response should be less than 10-0.042(Kd)-2+0.709(Kd)-1+1.136ns. In addition, an average relative error of 55% will be introduced to the retrieval of phytoplankton layer thickness in the stratified water, which can be reduced to 6% after correcting for the influence of the instrument response. However, a relative error greater than 20% still exists when the instrument response length is two times larger than the layer thickness. These conclusions provide guidelines to a future design of oceanic lidar.

Lidar Remote Sensing of Seawater Optical Properties: Experiment and Monte Carlo Simulation

Detecting the vertical profile of optical properties is an important task in the remote sensing of the upper ocean, especially for 3-D reconstruction. Ocean color remote sensing can only provide surface information, while the light detection and ranging (lidar) technique can provide depth-resolved data. Lidar can provide global-scale observations of the upper ocean for days and nights with minimal atmospheric correction errors. Unfortunately, due to the strong multiple scattering effects that occur when light propagates in seawater, the simple lidar equation may cause some deviations between the actual measurements and the simulation of the lidar signals. In this paper, we present a shipborne oceanic lidar, which was developed to detect the optical properties of seawater. For evaluating the performance of the lidar system, a Monte Carlo (MC) model was established to simulate lidar signals based on the simultaneous in situ inherent optical properties of seawater. The lidar measurements and the MC simulation can provide both the lidar signals and the retrieved lidar attenuation coefficient $\alpha $ . The results of the comparison indicate that the lidar-measured signals correspond well with the MC-simulated signals at different experiment stations in the Yellow Sea and at various receiving fields of view (FOVs). We also observed strong correlations between the lidar-measured $\alpha $ and MC-simulated $\alpha $ at different stations ( $r = 0.95$ ) and at various FOVs ( $r = 0.96$ ). The results indicate the reliability of the developed lidar system.

Multiple scattering effects on the return spectrum of oceanic high-spectral-resolution lidar.

The return spectrum of the oceanic high-spectral-resolution lidar (HSRL) is simulated with a semianalytic spectral Monte Carlo (MC) method. The results show that the spectrum is similar to the single scattering spectrum at the water surface but broadens with the depth due to multiple scattering. Therefore, if the non-spectral MC method that ignores the spectrum broadening is used, deviations will be introduced into the HSRL retrieval, e.g., the effective particulate 180° volume scattering function (backscatter) and lidar attenuation coefficient (attenuation). The simulation indicates that the backscatter and attenuation deviations are within 10% and 2%, respectively, when the HSRL discriminator is the iodine absorption cell, and are within 3% and 1%, respectively, when the discriminator is changed to the field-widened Michelson interferometer.

Ocean Optical Profiling in South China Sea Using Airborne LiDAR

Increasingly, LiDAR has more and more applications. However, so far, there are no relevant publications on using airborne LiDAR for ocean optical profiling in the South China Sea (SCS). The applicability of airborne LiDAR for optical profiling in the SCS will be presented. A total of four airborne LiDAR flight experiments were conducted over autumn 2017 and spring 2018 in the SCS. A hybrid retrieval method will be presented here, which incorporates a Klett method to obtain LiDAR attenuation coefficient and a perturbation retrieval method for a volume scattering function at 180°. The correlation coefficient between the LiDAR-derived results and the traditional measurements was 0.7. The mean absolute relative error (MAE) and the normalized root mean square deviation (NRMSD) between the two are both between 10% and 12%. Subsequently, the vertical structure of the LiDAR-retrieved attenuation and backscattering along airborne LiDAR flight tracks was mapped. In addition to this, ocean subsurface phytoplankton layers were detected between 10 to 20 m depths along the flight track in Sanya Bay. Primary results demonstrated that our airborne LiDAR has an independent ability to survey and characterize ocean optical structure.

Large-and-Sparse-particle Clouds (LSC): Clouds which are subvisible for space-borne lidar and observable for space-borne cloud radar

Large-and-Sparse-particle Clouds (LSC), characterized by large particle size (radius > 50 μm) and small number concentration (<104 m−3), were observed with the space-borne lidar, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and with the space-borne 94-GHz cloud profiling radar (CPR). CALIOP was found to be less sensitive to the LSC as compared to CPR because of the particle size distribution of LSC; hence, the cloud type is different from usual ones because CALIOP is generally more sensitive to clouds as compared to CPR when there is no lidar attenuation. An empirical criterion was introduced to identify the LSC from CALIOP and CPR data. The data analysis showed that the LSC tend to appear at high latitudes. The lifetime of LSC would be in the order of hours, because the terminal velocity of LSC particles exceeded 1 km h−1. LSC would not be fallstreak because no cloud existed above. LSC appeared to destroy supercooled clouds (SC) because their cloud top heights were higher as compared to SC, and because LSC and SC did not tend to coexist. Because of their thin optical depth, LSC did not directly impact radiative forcing; however, LSC may indirectly influence radiative forcing through changes in the distribution of SC.