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Hironobu Iwabuchi, Soichiro Yamada, Shuichiro Katagiri, Ping Yang, and Hajime Okamoto

Abstract

An optimal estimation–based algorithm is developed to infer the global-scale distribution of cirrus cloud radiative and microphysical properties from the measurements made by the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) at three infrared (IR) window bands centered at 8.5, 11, and 12 μm. Cloud-top and underlying surface temperatures, as a priori information, are obtained from the MODIS operational products. A fast-forward model based on semianalytical equations for the brightness temperature is used. The modeling errors in brightness temperature are mainly from the uncertainties in model parameters including surface emissivity, precipitable water, and cloud-base temperature. The total measurement–model errors are well correlated for the three bands, which are considered in the retrieval. The most important factors for the accurate retrieval of cloud optical thickness and the effective particle radius are cloud-top and surface temperatures, whereas model parameter uncertainties constitute a moderately significant error source. The three-band IR method is suitable for retrieving optical thickness and effective radius for cloud optical thicknesses within a range of 0.5–6, where the typical root-mean-square error is less than 20% in optical thickness and less than 40% in effective particle radius. A tropical-region case study demonstrates the advantages of the method—in particular, the ability to be applied to more pixels in optically thin cirrus in comparison with a solar-reflection-based method—and the ability of the optimal estimation framework to produce useful diagnostics of the retrieval quality. Collocated comparisons with spaceborne active remote sensing data exhibit reasonable consistency with respect to retrieved particle size.

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Maki Hirakata, Hajime Okamoto, Yuichiro Hagihara, Tadahiro Hayasaka, and Riko Oki

Abstract

This study analyzed the global and seasonal characteristics of cloud phase and ice crystal orientation (CTYPE-lidar) by using the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). A dataset from September 2006 to August 2007 was used to derive the seasonal characteristics. The discrimination scheme was originally developed by Yoshida et al., who classified clouds mainly into warm water, supercooled water, and randomly oriented ice crystals or horizontally oriented ice plates. This study used the following products for the comparison with CTYPE-lidar: (i) the vertical feature mask (VFM) of the National Aeronautics and Space Administration (NASA), (ii) the Moderate Resolution Imaging Spectroradiometer (MODIS), and (iii) European Centre for Medium-Range Weather Forecasts (ECMWF). Overall, the results showed that the CTYPE-lidar discrimination scheme was consistent with the outputs from VFM, MODIS, and ECMWF. The zonal mean water cloud cover in daytime from this study showed good agreement with that derived from MODIS; the slope of the linear regression was 1.06 and the offset was 0.002. The CTYPE-lidar ice cloud occurrence frequency and the ECMWF ice supersaturation occurrence frequency were also in good agreement; the slope of the linear regression of the two products was 1.02 in the temperature range −60°C ≤ T ≤ −30°C. The maximum occurrence frequencies in this study and ECMWF were recognized around −60°C of the equator, with their peak shifted from several degrees north (~9°N) in September–November (SON) to south (~9°S) in December–February (DJF) and back to north (~7°N) in March–May (MAM) and June–August (JJA).

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Woosub Roh, Masaki Satoh, Tempei Hashino, Hajime Okamoto, and Tatsuya Seiki

Abstract

A new evaluation method for the thermodynamic phases of clouds in cloud-system-resolving models is presented using CALIPSO observations and a satellite simulator. This method determines the thermodynamic phases using the depolarization ratio and a cloud extinction proxy. For the evaluation, we introduced empirical parameterization of the depolarization ratio of ice and water clouds using temperatures of a reanalysis dataset and total attenuated backscatters of CALIPSO. We evaluated the mixed-phase clouds simulated in a cloud-system-resolving model over the Southern Ocean using single-moment and double-moment bulk cloud microphysics schemes, referred to as NSW6 and NDW6, respectively. The NDW6 simulations reproduce supercooled water clouds near the boundary layer that are consistent with the observations. Conversely, the NSW6 simulations failed to reproduce such supercooled water clouds. Consistencies between the cloud classes diagnosed by the evaluation method and the simulated hydrometeor categories were examined. NDW6 shows diagnosed water and ice classes that are consistent with the simulated categories, whereas the ice category simulated with NSW6 is diagnosed as liquid water by the present method due to the large extinction from the ice cloud layers. Additional analyses indicated that ice clouds with a small effective radius and large ice water content in NSW6 lead to erroneous values for the fraction of the diagnosed liquid water. It is shown that the uncertainty in the cloud classification method depends on the details of the cloud microphysics schemes. It is important to understand the causes of inconsistencies in order to properly understand the cloud classification applied to model evaluations as well as retrievals.

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Tempei Hashino, Gijs de Boer, Hajime Okamoto, and Gregory J. Tripoli

Abstract

The number concentration of ice particles in Arctic mixed-phase clouds is a major controlling factor of cloud lifetime. The relationships between ice nucleation mode and ice crystal habit development are not yet constrained by observations. This study uses a habit-predicting microphysical scheme within a 3D large-eddy simulation model to evaluate the relationship between immersion freezing and ice habit in a simulated Arctic mixed-phase cloud case. Three immersion freezing parameterizations are considered: a volume-dependent freezing scheme (VF), a parameterization limited to activated droplets (C-AC), and a parameterization limited to coarse aerosol particles (C-CM). Both C-AC and C-CM are based on classical nucleation theory. The freezing rate with VF is found to be greater in downdraft regions than in updraft regions due to the downdraft having a higher number concentration of large droplets. The C-AC cases show active freezing of small droplets near cloud top, whereas in the C-CM cases, mainly the 8–32-μm-sized droplets freeze in updraft regions near the cloud base. Because the initial crystal size is assumed to affect the axis ratio of hexagonal plates, the VF cases produce crystals with larger axis ratios, resulting in smaller mode radii than the C-AC cases. In all cases, irregular polycrystals dominate near cloud top and a band-like structure develops within the cloud, which qualitatively agrees with previous observations. In the VF and C-CM cases, unactivated large droplets arising from coarse-mode aerosol particles contributed significantly to the freezing rate, producing an important influence on crystal habit.

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Takamichi Iguchi, Teruyuki Nakajima, Alexander P. Khain, Kazuo Saito, Toshihiko Takemura, Hajime Okamoto, Tomoaki Nishizawa, and Wei-Kuo Tao

Abstract

Numerical weather prediction (NWP) simulations using the Japan Meteorological Agency Nonhydrostatic Model (JMA-NHM) are conducted for three precipitation events observed by shipborne or spaceborne W-band cloud radars. Spectral bin and single-moment bulk cloud microphysics schemes are employed separately for an intercomparative study. A radar product simulator that is compatible with both microphysics schemes is developed to enable a direct comparison between simulation and observation with respect to the equivalent radar reflectivity factor Ze, Doppler velocity (DV), and path-integrated attenuation (PIA). In general, the bin model simulation shows better agreement with the observed data than the bulk model simulation. The correction of the terminal fall velocities of snowflakes using those of hail further improves the result of the bin model simulation. The results indicate that there are substantial uncertainties in the mass–size and size–terminal fall velocity relations of snowflakes or in the calculation of terminal fall velocity of snow aloft. For the bulk microphysics, the overestimation of Ze is observed as a result of a significant predominance of snow over cloud ice due to substantial deposition growth directly to snow. The DV comparison shows that a correction for the fall velocity of hydrometeors considering a change of particle size should be introduced even in single-moment bulk cloud microphysics.

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Kazuaki Yasunaga, Kunio Yoneyama, Hisayuki Kubota, Hajime Okamoto, Atsushi Shimizu, Hiroshi Kumagai, Masaki Katsumata, Nobuo Sugimoto, and Ichiro Matsui

Abstract

In this study, cloud profiling radar and lidar were used to determine the frequency distribution of the base heights of cloudy layers with little (or no) falling condensate particles. The data were obtained from stationary observations conducted from Research Vessel Mirai over the tropical western Pacific (around 1.85°N, 138°E) from 9 November to 9 December 2001. The observed cloudy layers had base heights predominantly in the range of 4.5–6.5 km. Almost all cloudy layers with a base in the range of 4.5–6.5 km had thickness thinner than 500 m, and the frequency peak of the base heights of measured cloudy layers is considered to represent the common occurrence of midlevel thin clouds.

Midlevel thin clouds were frequently observed even during the active phase of the Madden–Julian oscillation (MJO). Composite analysis of radiosonde-derived relative humidity and temperature lapse rate indicates that the midlevel thin cloud in the MJO active period is generated via melting within the stratiform cloud, rather than by detrainment of surface-based convection.

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Andrew J. Heymsfield, Alain Protat, Dominique Bouniol, Richard T. Austin, Robin J. Hogan, Julien Delanoë, Hajime Okamoto, Kaori Sato, Gerd-Jan van Zadelhoff, David P. Donovan, and Zhien Wang

Abstract

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 Ze 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) ± 0.66 for all teams, 1.08 (1.00) ± 0.60 for those employing a lidar–radar approach, and 1.27 (1.12) ± 0.78 for the standard CloudSat radar–visible optical depth algorithm for Ze > −28 dBZe. 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 lidar–radar approach, as applied to measurements from CALIPSO and CloudSat, is useful only in a narrow range of ice water paths (IWP) (40 < IWP < 100 g m−2). 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 dBZe are subject to uncertainties of ±50%.

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