The other finding is that the seasonal shift off the west coast of North Africa observed by satellites, i.e., the latitude of the maximum optical thickness moves seasonally, is also reproduced in consideration of a mixed state of soil dust and carbonaceous aerosols.

International audienceThe collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint ESA-JAXA EarthCARE satellite mission, scheduled for launch in 2017, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, CALIPSO, and Aqua. Specifically, EarthCARE's Cloud Profling Radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle and raindrop fall speeds. EarthCARE's 355-nm High Spectral Resolution Lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The Multi-Spectral Imager will provide a context for, and the ability to construct the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross-section. The consistency of the retrievals will be assessed to within a target of ±10 W m⁻² on the (10 km²) scale by comparing the multi-view Broad-Band Radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains

[1] A profiling retrieval algorithm for ice cloud properties, such as effective radius (r e ), ice water content (IWC), and an extinction coefficient, has been developed to use combined CloudSat radar reflectivity factor (Ze) and CALIPSO attenuated backscattering coefficient measurements based on an optimal estimation framework. Developed as an operational standard data product for the CloudSat project, the algorithm can treat a wide range of ice cloud situations from optically tenuous cirrus in the upper troposphere to geometrically and optically thick anvil clouds. It is designed to consider the attenuation of thick clouds in the radar and lidar forward model equations and multiple scattering in the lidar data. An optimal estimation approach allows for inversion of the forward model equations so that the uncertainty due to the assumptions can be evaluated. A sensitivity study shows that lidar multiple scattering has to be accounted for carefully. As for all ice cloud retrieval algorithms, assumptions regarding particle habits and size distribution shapes are critical to the accuracy of the results. The deviation in simulated Ze among different size distribution assumptions is smaller than among different habit assumptions, which indicates that the uncertainty due to particle habits is larger than the size distribution assumption. Those uncertainties are included in the forward model error covariance matrix to analyze the retrieval error. The algorithm is applied to CloudSat-CALIPSO data as well as lidar and radar data collected by the ER-2 during the Tropical Composition, Cloud and Climate Coupling Experiment mission on 22 July 2007. The retrieved r e , IWC, and extinction are shown to compare favorably with coincident in situ measurements collected by instruments on the NASA DC-8. This algorithm is expected to be complementary to the set of standard data products that is already being produced by the CloudSat project.

[1] A method for discriminating cloud particle types was developed using lidar backscattering copolarization and cross-polarization channel measurements from Cloud-Aerosol Lidar With Orthogonal Polarization (CALIOP) on board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). In spaceborne lidar measurements, significant multiple scattering effects discriminate between cloud water and ice difficult using the depolarization ratio (d). We theoretically estimated the relationship between d and cloud extinction on the basis of the backward Monte Carlo method. Cloud particle type was determined by the combined use of d and the ratio of attenuated backscattering coefficients for two vertically consecutive layers. Ice particles were further classified into two categories: randomly oriented ice crystals (3-D ice) and horizontally oriented plates (2-D plate). The method was applied to CALIOP data for September-November 2006. We found that 3-D ice generally occurred colder than −20°C, whereas 2-D plate occurred between −10°C and −20°C, with high-occurrence frequency in high-latitude regions. We compared the results to those obtained using the vertical feature mask (VFM). The VFM tended to show a homogeneous cloud type through the entire cloud layer in vertical directions and misclassified 2-D plate as water. The ratio of water particles relative to ice particles decreased with decreasing temperature. By the proposed method, water cloud occurrence in subtropical and high-latitude regions was greater (up to 20%) than in the other regions below −10°C; however, the VFM results did not show such dependence on latitude. Comparison of ice and water cloud between our results and Moderate Resolution Imaging Spectroradiometer (MODIS) products showed better agreement for water cloud than for ice cloud.Citation: Yoshida, R., H. Okamoto, Y. Hagihara, and H. Ishimoto (2010), Global analysis of cloud phase and ice crystal orientation from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data using attenuated backscattering and depolarization ratio,

Abstract. We intensively observed the atmospheric boundary layer with a polarization lidar, a Sun photometer, and a high-volume sampler at a coastal area of Tokyo Bay. The purpose of the observation is to investigate a phenomenon discovered in the past summer: relatively high depolarization ratio events (•10% at peak) in the lower atmosphere associated with sea breeze. From the chemical analyses of the simultaneously sampled aerosols, we found that the depolarization ratio might be related to crystallized sea salt and dust particles. A boundary structure was clearly revealed by the depolarization ratio in the lower atmosphere, which might correspond to the mixed layer (the internal boundary layer) or the sea breeze in which crystallized sea salt and/or dust particles were diffused. We also presented the first numerical calculation on the depolarization ratio of the cubic particles to apply crystallized sea-salt (NaC1) particles by the dipole discrete approximation (DDA) method: the calculation yields 8-22% of depolarization ratio for the effective size larger than 0.8 •m at the investigated wavelength (532 nm). IntroductionWe have routinely observed the troposphere, mainly to study the atmospheric boundary layer (ABL) (also referred as the planetary boundary layer (PBL)), with a lidar at Tokyo University of Mercantile Marine (TUMM) (35ø40'N, 139ø47'E) since 1993. Our observation site is located in the center of Tokyo and close to Tokyo Bay, as shown in Figure 1. A large amount of aerosols is locally emitted from anthropogenic origins and greatly affects the local air quality and visibility. This site is suited for the study of the urban atmospheric boundary layer, the boundary layer aerosols, the air pollution meteorology, and the sea-land breeze circulation. Aerosols in ABL, except in spring when Asian dust exists, normally dominate the optical thickness of the atmosphere in this area. Therefore the optical property of the aerosols in the urban ABL is one of the most important targets to estimate the direct and indirect effects of the tropospheric aerosols on the radiation budget.The lidar depolarization technique has been extensively applied to cloud research, e.g., to discriminate the phase of clouds (i.e., water or ice clouds) [Sassen, 1991[Sassen, , 1999. However, the application of this technique to the tropospheric aerosol is relatively rare [Sassen, 1999]. We explored the importance of the lidar depolarization technique in the boundary layer me- teorology and characterization of boundary layer aerosols. One of the advantages of the boundary layer study is that we can relate lidar data to meteorological data and in situ measurements of aerosols at the ground level, although the boundary layer aerosols are mixed with various kinds of aerosols and therefore complex. For the upper atmosphere case we need radiosonde observations and airborne sampling of aerosols for a direct comparison with lidar data, which would be highly expensive.In this paper we define the directly observed total depolarization ratio as...

[1] We developed a cloud mask scheme that combines measurements from CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites. First, we developed a cloud mask scheme for CALIPSO using a threshold of the attenuated total backscattering coefficient and a spatial continuity test. We then developed a combined CloudSat-CALIPSO cloud mask. These cloud masks were applied to 3 months of data from September to November 2006, and the vertical distributions of zonal mean cloud fractions and cloud coverage were analyzed. We also examined the standard vertical feature mask (VFM) cloud scheme. The VFM occasionally made false detections because of its horizontal averaging procedure and seemed to misclassify noise or aerosols as clouds. In addition, the VFM appeared to significantly overestimate low-level clouds. Below 2 km, the cloud fraction differed by as much as 25% between the VFM and our combined scheme. We also compared the zonal mean cloud coverage for the topmost layer detected by the sensors using our CALIPSO scheme, the VFM, our combined CloudSat-CALIPSO scheme, and the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) results. For low-level clouds (>680 hPa), the MODIS result was larger than that of our CloudSat-CALIPSO scheme, and results from the VFM and our CALIPSO scheme differed by as much as 15%. The CALIPSO, CloudSat-CALIPSO, and MODIS results were similar for total cloud coverage, but the VFM result was different. Because of possible misclassification at low levels, the VFM showed the largest cloud coverage in middle and low latitudes.Citation: Hagihara, Y., H. Okamoto, and R. Yoshida (2010), Development of a combined CloudSat-CALIPSO cloud mask to show global cloud distribution,

[1] We describe a method to evaluate cloud microphysics simulated with a global cloud-resolving model against CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite data. Output from the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) is run through a satellite-sensor simulator (Joint Simulator for Satellite Sensors), then directly compared to the radar and lidar signals from CloudSat and CALIPSO. The forward approach allows for consistency in cloud microphysical assumption involved in the evaluation. To investigate the dependence of the signals on the temperature, we use temperature extensively as the vertical coordinate. The global statistical analysis of the radar reflectivity shows that the simulation overestimates all the percentiles above À50°C and that snow category contributes significantly to low reflectivity values between À80 and À40°C. The simulated lidar signals have two modes associated with cloud ice and snow categories, though the observations have only one mode. The synergetic use of radar reflectivity and lidar backscatter enables us to determine the relative magnitudes of ice/liquid water contents and effective radii without use of retrievals. The radar-and-lidar diagnosis for cloud tops shows that, due to snow category, NICAM overestimates the mass-equivalent effective radius and underestimates ice water content. Also, the diagnosis was shown to be useful to investigate sensitivities of the parameters of bulk microphysical schemes on the water contents and sizes. The nonspherical scattering of ice particles was shown to affect the above radar-and-lidar diagnosis for large reflectivity ranges but not to alter most of the other diagnoses for this simulation.

Vertical profiles of ice water content (IWC) can now be derived globally from spaceborne cloud satellite radar (CloudSat) data. Integrating these data with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data may further increase accuracy. Evaluations of the accuracy of IWC retrieved from radar alone and together with other measurements are now essential. A forward model employing aircraft Lagrangian spiral descents through mid-and low-latitude ice clouds is used to estimate profiles of what a lidar and conventional and Doppler radar would sense. Radar reflectivity Z e and Doppler fall speed at multiple wavelengths and extinction in visible wavelengths were derived from particle size distributions and shape data, constrained by IWC that were measured directly in most instances. These data were provided to eight teams that together cover 10 retrieval methods. Almost 3400 vertically distributed points from 19 clouds were used. Approximate cloud optical depths ranged from below 1 to more than 50. The teams returned retrieval IWC profiles that were evaluated in seven different ways to identify the amount and sources of errors. The mean (median) ratio of the retrieved-to-measured IWC was 1.15 (1.03) Ϯ 0.66 for all teams, 1.08 (1.00) Ϯ 0.60 for those employing a lidar-radar approach, and 1.27 (1.12) Ϯ 0.78 for the standard CloudSat radar-visible optical depth algorithm for Z e Ͼ Ϫ28 dBZ e . The ratios for the groups employing the lidar-radar approach and the radar-visible optical depth algorithm may be lower by as much as 25% because of uncertainties in the extinction in small ice particles provided to the groups. Retrievals from future spaceborne radar using reflectivity-Doppler fall speeds show considerable promise. A lidarradar approach, as applied to measurements from CALIPSO and CloudSat, is useful only in a narrow range of ice water paths (IWP) (40 Ͻ IWP Ͻ 100 g m Ϫ2 ). Because of the use of the Rayleigh approximation at high reflectivities in some of the algorithms and differences in the way nonspherical particles and Mie effects are considered, IWC retrievals in regions of radar reflectivity at 94 GHz exceeding about 5 dBZ e are subject to uncertainties of Ϯ50%.