Depolarization ratio and attenuated backscatter for nine cloud types: analyses based on collocated CALIPSO lidar and MODIS measurements

Classification of atmospheric aerosols and clouds by use of dual-polarization lidar measurements

Accurate identification of aerosols and cloud from remote sensing observations is of importance for quantitatively evaluating their radiative forcing and related impacts. Even though polarization lidar has exhibited a unique advantage of classifying atmospheric aerosols and clouds over the past several decades, polarization measurements are often achieved at one wavelength (UV or VIS) using laser remote sensing. To better identify the types of aerosols and clouds, we developed a ground-based dual-polarization lidar system that can simultaneously detect polarization measurements at wavelengths of 355 nm and 532 nm. Our results show that the volume depolarization ratios (VDRs) at 355 nm and 532 nm markedly differ for typical types of aerosols and clouds in the atmosphere. For non-spherical particles, the ratio of VDRs at 532 nm and 355 nm are 2.87 ± 1.35 for ice cloud and 1.51 ± 0.29 for dust-dominated aerosols, respectively. However, for spherical particles, the ratios are 0.43 ± 0.26 for water cloud and 0.56 ± 0.05 for air pollutants. Consequently, we proposed a simple reliable method for classifying atmospheric aerosols and clouds from polarization measurements observed by the developed lidar system. The proposed method first distinguishes clouds from aerosols using a combination of the color ratio (CR, 532 nm/355 nm) and attenuated backscattering coefficients (ABC) at 532 nm. Then, subtypes of clouds and aerosols are identified based on the ratio of VDRs at 532 nm and 355 nm. The results showed that dual-polarization lidar measurements can remarkably improve the classification of atmospheric aerosols and clouds, compared with results using a traditional method. This study illustrates that more information on atmospheric aerosols and clouds can be obtained from polarization measurements at multiple wavelengths by active remote sensing.

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.

Comparison of Aqua/Terra MODIS and Himawari-8 Satellite Data on Cloud Mask and Cloud Type Classification Using Split Window Algorithm

Cloud classification is not only important for weather forecasts, but also for radiation budget studies. Although cloud mask and classification procedures have been proposed for Himawari-8 Advanced Himawari Imager (AHI), their applicability is still limited to daytime imagery. The split window algorithm (SWA), which is a mature algorithm that has long been exploited in the cloud analysis of satellite images, is based on the scatter diagram between the brightness temperature (BT) and BT difference (BTD). The purpose of this research is to examine the usefulness of the SWA for the cloud classification of both daytime and nighttime images from AHI. We apply SWA also to the image data from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua and Terra to highlight the capability of AHI. We implement the cloud analysis around Japan by employing band 3 (0.469 μm) of MODIS and band 1 (0.47 μm) of AHI for extracting the cloud-covered regions in daytime. In the nighttime case, the bands that are centered at 3.9, 11, 12, and 13 µm are utilized for both MODIS and Himawari-8, with somewhat different combinations for land and sea areas. Thus, different thresholds are used for analyzing summer and winter images. Optimum values for BT and BTD thresholds are determined for the band pairs of band 31 (11.03 µm) and 32 (12.02 µm) of MODIS (SWA31-32) and band 13 (10.4 µm) and 15 (12.4 µm) of AHI (SWA13-15) in the implementation of SWA. The resulting cloud mask and classification are verified while using MODIS standard product (MYD35) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. It is found that MODIS and AHI results both capture the essential characteristics of clouds reasonably well in spite of the relatively simple scheme of SWA based on four threshold values, although a broader spread of BTD obtained with Himawari-8 AHI (SWA13-15) could possibly lead to more consistent results for cloud-type classification than SWA31-32 based on the MODIS sensors.

Overview of MPLNET Version 3 Cloud Detection

The National Aeronautics and Space Administration Micropulse Lidar Network Version 3 cloud detection algorithm is described and its differences relative to the previous version highlighted. Clouds are identified from normalized Level 1 signal profiles using two complementary methods. The first considers signal derivatives vertically for resolving low-level clouds. The second, which resolves high-level clouds like cirrus, is based on signal uncertainties given the relatively low signal-to-noise ratio exhibited in the upper troposphere by eye-safe network instruments, especially during daytime. Furthermore, a multi-temporal averaging scheme is used to improve cloud detection under conditions of weak signal-to-noise. Diurnal and seasonal cycles of cloud occurrence frequency based on one year of measurements at the Goddard Space Flight Center (Greenbelt, MD) site are compared for the new and previous versions. The largest differences, and perceived improvement, in detection occurs for high clouds (above 5-km, mean sea level) which increase in occurrence by nearly 6%. There is also an increase in the detection of multi-layered cloud profiles from 9% to 20%. Macrophysical properties and estimates of cloud optical depth are presented for a transparent cirrus dataset. However, the limit to which molecular signal can be reliably retrieved above cirrus clouds occurs between cloud optical depths of 0.5 and 0.8.

A reconfigurable all-fiber polarization-diversity coherent Doppler lidar: principles and numerical simulations

This paper shows an efficient adaptation of a polarization diversity optical front-end, commonly used in high-speed fiber-optic communications, in a coherent Doppler lidar (CDL). The adopted architecture can be employed in a modified transceiver design for an all-fiber micropulsed coherent Doppler wind lidar where the performance limits of such systems are pushed beyond the conventionally available wind CDLs. As a result, either a longer measurement range, crucial in clear-air environments with low concentration of aerosols, or a shorter integration time (resulting in a faster scanning) can be achieved. Alternatively, in certain aerosol loading conditions where the presence of nonspherical aerosols is considerable, the system can be reconfigured on the fly to analyze the cross polarization of the backscatter optical signal. The result is the capability to analyze the nature of aerosol particles for the detected range of interest. Due to full utilization of the backscatter signal, i.e., detection of co-polarization and cross polarization components, the signal-to-noise-ratio (SNR) as well as detection range is improved in this configuration. Moreover, the system is capable of providing a more reliable estimation of the aerosol backscatter coefficient when compared with the contemporary CDLs. This system employs robust and compact all-fiber subsystems, which are cost effective and widely available as off-the-shelf components.

Interference phenomena at backscattering by ice crystals of cirrus clouds

It is shown that light backscattering by hexagonal ice crystals of cirrus clouds is formed within the physical-optics approximation by both diffraction and interference phenomena. Diffraction determines the angular width of the backscattering peak and interference produces the interference rings inside the peak. By use of a simple model for distortion of the pristine hexagonal shape, we show that the shape distortion leads to both oscillations of the scattering (Mueller) matrix within the backscattering peak and to a strong increase of the depolarization, color, and lidar ratios needed for interpretation of lidar signals.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r_e ) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r_e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the "r_e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the "r_e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r_e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

Layers of quasi-horizontally oriented ice crystals in cirrus clouds observed by a two-wavelength polarization lidar

Layers of quasi-horizontally oriented ice crystals in cirrus clouds are observed by a two-wavelength polarization lidar. These layers of thickness of several hundred meters are identified by three attributes: the backscatter reveals a sharp ridge while the depolarization ratio and color ratio become deep minima. These attributes have been justified by theoretical calculations of these quantities within the framework of the physical-optics approximation.

The depolarization-attenuated backscatter relationship for dust plumes

This study identified the relationship between the layer-integrated attenuated backscatter coefficient and layer-integrated depolarization ratio of dust plumes and compared it with that of cloud, using CALIPSO LIDAR measurements. The histogram distribution of the integrated color ratio for dust and cloud was also examined. On the basis of the layer-integrated attenuated backscatter coefficient and layer-integrated depolarization ratio relation, a simple method of detecting dust plumes was developed. A case study of dust identification over the Taklimakan Desert was conducted and compared with the current CALIPSO products. The result shows that the proposed method can significantly improve the classification of cloud and dust plumes and can supplement the current space-borne LIDAR discrimination approach, especially over dust source regions. In addition, The zonal and meridional mean occurrence derived by the proposed method and the CALIPSO's method were compared for Asian dust over East Asia region (30°N -45°N, 80°E -180°E) using the night measurements of CALIPSO from March to May, 2007. The comparison showed that the dust occurrence obtained from the proposed method is larger than that of CALIPSO's method. The dust could be found up to around 6-8 km (Above Sea Level, ASL) near the Taklimakan desert region, and maximum occurrence is over 80%. The transport altitude remained at 3 km-7 km (ASL) as the dust was transported across the Pacific Ocean.

Observations of specular reflective particles and layers in crystal clouds

In the present article, results of observations of high crystal clouds with high spatial and temporal resolution using the ground-based polarization LOSA-S lidar are described. Cases of occurrence of specularly reflective layers formed by particles oriented predominantly in the horizontal plane are demonstrated. Results of measuring echo-signal depolarization are compared for linear and circular polarization states of the initial laser beam.

Specular scattering by preferentially oriented ice crystals

Scattered light for preferentially oriented ice crystals is divided into specular and diffuse components, where the specular scattering is created by horizontally oriented facets of fluttering crystals. The specular component for a fluttering thin plate modeling these crystals is found analytically. The solution obtained is a two-dimensional (2D) convolution of a geometric optics pattern depending only on flutter and an independent diffraction function. The geometric optics pattern is explicitly expressed through the probability density for particle tilts, and the diffraction function is taken in the Fraunhofer diffraction approximation. The 2D convolution calculated numerically reveals a cumulative enhancement of scattered light in the scattering domain center. Certain possibilities to retrieve both flutter parameters and particle sizes from the specular patterns are discussed.