The current cloud thermodynamic phase discrimination by Cloud-Aerosol Lidar Pathfinder Satellite Observations (CALIPSO) is based on the depolarization of backscattered light measured by its lidar [Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)]. It assumes that backscattered light from ice crystals is depolarizing, whereas water clouds, being spherical, result in minimal depolarization. However, because of the relationship between the CALIOP field of view (FOV) and the large distance between the satellite and clouds and because of the frequent presence of oriented ice crystals, there is often a weak correlation between measured depolarization and phase, which thereby creates significant uncertainties in the current CALIOP phase retrieval. For water clouds, the CALIOP-measured depolarization can be large because of multiple scattering, whereas horizontally oriented ice particles depolarize only weakly and behave similarly to water clouds. Because of the nonunique depolarization–cloud phase relationship, more constraints are necessary to uniquely determine cloud phase. Based on theoretical and modeling studies, an improved cloud phase determination algorithm has been developed. Instead of depending primarily on layer-integrated depolarization ratios, this algorithm differentiates cloud phases by using the spatial correlation of layer-integrated attenuated backscatter and layer-integrated particulate depolarization ratio. This approach includes a two-step process: 1) use of a simple two-dimensional threshold method to provide a preliminary identification of ice clouds containing randomly oriented particles, ice clouds with horizontally oriented particles, and possible water clouds and 2) application of a spatial coherence analysis technique to separate water clouds from ice clouds containing horizontally oriented ice particles. Other information, such as temperature, color ratio, and vertical variation of depolarization ratio, is also considered. The algorithm works well for both the 0.3° and 3° off-nadir lidar pointing geometry. When the lidar is pointed at 0.3° off nadir, half of the opaque ice clouds and about one-third of all ice clouds have a significant lidar backscatter contribution from specular reflections from horizontally oriented particles. At 3° off nadir, the lidar backscatter signals for roughly 30% of opaque ice clouds and 20% of all observed ice clouds are contaminated by horizontally oriented crystals.

[1] The relative importance of ice clouds in the climate system is highly uncertain. Measurements of their microphysical properties are sparse, especially given their complex structure and large variability in particle size, shape, and density. To better understand the role of ice clouds in the climate system, parameterizations of their radiative properties are needed. The shortwave bulk optical properties of seven ice particle shapes, or ''habits,'' are parameterized as a function of the effective ''radius'' and ice water content by integrating the scattering properties over 30 in situ size distributions. The particle habits are solid and hollow hexagonal columns, hexagonal plates, two-and three-dimensional bullet rosettes, aggregates of columns, and dendrites. Parameterizations of the volume extinction coefficient, single-scattering albedo, and the asymmetry parameter are presented for 6, 24, and 56 band shortwave schemes from 0.2 to 5.0 mm. Applications to downwelling flux and upwelling radiance calculations indicate that differences in fluxes for various habits can be more than 15%, and differences in retrievals of cloud optical depth from satellite visible reflectances can be more than 50%.INDEX TERMS: 3359

Abstract. Anthropogenic dusts are those produced by human activities on disturbed soils, which are mainly cropland, pastureland, and urbanized regions, and are a subset of the total dust load which includes natural sources from desert regions. Our knowledge of anthropogenic dusts is still very limited due to a lack of data. To understand the contribution of anthropogenic dust to the total global dust load, it is important to identify it apart from total dust. In this study, a new technique for distinguishing anthropogenic dust from natural dust is proposed by using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) dust and planetary boundary layer (PBL) height retrievals along with a land use data set. Using this technique, the global distribution of dust is analyzed and the relative contribution of anthropogenic and natural dust sources to regional and global emissions are estimated. Results reveal that local anthropogenic dust aerosol due to human activity, such as agriculture, industrial activity, transportation, and overgrazing, accounts for about 25 % of the global continental dust load. Of these anthropogenic dust aerosols, more than 53 % come from semiarid and semi-wet regions. Annual mean anthropogenic dust column burden (DCB) values range from 0.42 g m −2 , with a maximum in India, to 0.12 g m −2 , with a minimum in North America. A better understanding of anthropogenic dust emission will enable us to focus on human activities in these critical regions and with such knowledge we will be more able to improve global dust models and to explore the effects of anthropogenic emission on radiative forcing, climate change, and air quality in the future.

A ground-based observation system has been developed at the Meteorological Research Institute (MRI) for simultaneous measurements of cloud structure and radiative properties of high-level ice clouds. In this observation system, the cloud microphysical quantities and spectral radiances in the region of the 10um window could be simultaneously observed by a Hydrometeor Video Sonde (HYVIS) and a Fourier Transform Infrared (FTIR) spectro-radiometer. On the basis of the results measured by HYVIS, the size distribution of ice particles was approximated by the power law distribution, and the simulation calculations of observed radiances were made for the some combination of the lower limit of power law distribution (r1) and the optical thickness at 10.5um (Tlo.5). Using these data, the minimum error point is searched in the error map. By this method, we retrieve optical thickness and particle size information. The optically thin, medium and thick cases were analyzed in order to investigate the characteristic of our retrieval method. It is found that the optical thickness determined the magnitude of observed radiance, and size distributions determined the slope of the spectrum in the 860 to 980cm-1 region. The simulated and observed radiances agree within +2mW/(m2 sr cm-1), except the 9.6um ozone band and the root mean squares error 1.2mW/(m2 sr cm-1). The error analysis showed that though 5% systematic error is permitted to optical thickness retrieval in some cases, 1% systematic error causes large errors in the size information retrieval, and that a +500m height error corresponds to 1 to 3% radiance error. Furthermore, the values estimated from the radiance in the region of wavenumber 860 to 980cm-1 were almost the same as those from radiance in the whole region, and the optical thickness may be determined from data in the region 1080 to 1200cm-1 without being affected by the size distribution. We also retrieved 1O.5 and effective radius (reff) using the log-normal size distribution within the same degree of error as obtained by the power law model. Furthermore, we investigated the relationship between the parameters retrieved. The ratio of the visible optical thickness at 0.5,um (T0.5) to the infrared one at 10.5um (T1o.5) on June 22 is 0.4 to 1.0, and that on June 30 is 1.0 to 1.8. There is a tendency that the ratio of T1o.5 to T0.5 becomes large as the effective radius increases. We also investigated the relation between n o.5 and the effective radius (reff) of log-normal size distribution. The relation between them changes case by case. There is a negative correlation between them in the case of June 22. In the case of June 30, the effective radius is scattered between 20 and 85um. Concurrent NOAA-11 satellite data over the Tsukuba area were also analyzed. The results show that observation from the satellite is consistent with the ground based observation, and that the large difference of the brightness temperature observed by the different window channels is closely related to the existence of small ice particles ...

Abstract. The version 6 cloud products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) instrument suite are described. The cloud top temperature, pressure, and height and effective cloud fraction are now reported at the AIRS field-of-view (FOV) resolution. Significant improvements in cloud height assignment over version 5 are shown with FOV-scale comparisons to cloud vertical structure observed by the CloudSat 94 GHz radar and the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). Cloud thermodynamic phase (ice, liquid, and unknown phase), ice cloud effective diameter (D e ), and ice cloud optical thickness (τ ) are derived using an optimal estimation methodology for AIRS FOVs, and global distributions for 2007 are presented. The largest values of τ are found in the storm tracks and near convection in the tropics, while D e is largest on the equatorial side of the midlatitude storm tracks in both hemispheres, and lowest in tropical thin cirrus and the winter polar atmosphere. Over the Maritime Continent the diurnal variability of τ is significantly larger than for the total cloud fraction, ice cloud frequency, and D e , and is anchored to the island archipelago morphology. Important differences are described between northern and southern hemispheric midlatitude cyclones using storm center composites. The infrared-based cloud retrievals of AIRS provide unique, decadal-scale and global observations of clouds over portions of the diurnal and annual cycles, and capture variability within the mesoscale and synoptic scales at all latitudes.