Validation experiments for the EarthCARE ATLID JAXA Level 2a data products using the ground-based lidar network, the Asian Dust and aerosol lidar observation Network (AD-Net) are described. The ATLID JAXA level 2a standard data product consists of the feature mask, target mask, and optical parameters for aerosols and clouds, and planetary boundary layer height. The ATLID JAXA L2a research data product provides extinction coefficients for aerosol components (water soluble, mineral dust, sea salt, black carbon). Direct comparison with the ground-based 355-nm HSRLs and Raman lidars in AD-Net is the basic method for validating the standard data products for aerosol. A data matching method considering the trajectory of air mass is employed. Statistical comparison in the suitable temporal and spatial regions is employed in the validation of feature mask, target mask and cloud optical parameters, because the spatial distribution scale is small for clouds. In the validation of the research data product (extinction coefficients of aerosol components), multi-wavelength HSR and Raman lidars are employed because the aerosol components can be better estimated with more measurement parameters.
We have developed algorithms to produce JAXA ATLID level two products using data measured by the lidar ATLID and imager MSI onboard the EarthCARE satellite. The algorithms estimate particle optical properties such as extinction, backscatter, and depolarization ratio as well as layer identifier, particle type identifier, and planetary boundary layer height. Furthermore, the algorithm estimates extinction coefficient of four aerosol components, dust, sea-salt, carbonaceous, and water-soluble particles using ATLID data; the other algorithm uses both ATLID and MSI data to estimate the extinction coefficient of the four aerosol components and column-mean mode-radii of fine-mode and coarse-mode aerosols. Prior to the ATLID algorithm development, we have developed a similar aerosol component retrieval algorithm using CALIOP and MODIS data; this technique was introduced into the ATLID algorithm. These algorithms were applied to the CALIOP long-term data, and the estimates have been used for evaluating aerosol radiation effects and data assimilation.
Wind is one of fundamental meteorological elements describing the atmospheric state. Global wind observation is important to improve the initial conditions essential for numerical weather prediction and meteorological studies. A Doppler wind Lidar (DWL) is a promising approach for global wind profiling. We conduct feasibility study to realize global 4D wind observation from space. In the paper, we describe feasibility study of space-based DWL for future global wind profiling.
The paper presents the elements of the light scattering matrix for atmospheric ice aggregated particles, consisting of "bullets" with the number of particles from 1 to 6. The calculation of the scattering matrices was carried out within the geometric optics approximation and single scattering. The spatial orientation of aggregates is random, the refractive index is 1.3116 (for a wavelength of 0.532 μm). The dependence of the light scattering matrix elements on the number of particles in aggregates is presented. The results can be used for interpretation of the data retrieved from laser sensing of crystalline clouds from ground and space.
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