ORCID Profile
0000-0002-4540-1698
Current Organisation
Kyushu University
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Publisher: American Geophysical Union (AGU)
Date: 19-10-2017
DOI: 10.1002/2017JD027113
Publisher: American Meteorological Society
Date: 10-2014
DOI: 10.1175/JTECH-D-13-00245.1
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).
Publisher: American Meteorological Society
Date: 2008
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%.
Publisher: American Meteorological Society
Date: 08-2015
DOI: 10.1175/BAMS-D-12-00227.1
Abstract: The 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 h er the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, 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, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling 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 multispectral 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 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.
Publisher: American Geophysical Union (AGU)
Date: 04-05-2021
DOI: 10.1029/2020JD033562
Abstract: We study horizontal ice plates in clouds using satellite lidar measurements of the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This study investigates global microphysical and geographical properties of horizontal ice plates to obtain insights into ice‐plate climatology based on lidar’s long‐term measurements during 2006–2014. We then summarize the effects of the lidar's viewing angle change from 0.3° to 3.0° in 2007 on satellite particle phase/shape classifications. Using a classification algorithm developed in the previous studies, we show that the ice plate detection decreases by 81.7% due the tilting. With an updated version of this algorithm, 30.8% of these are recovered, although 50.8% remain undetected. Nevertheless, this study also shows that geographical characteristics of ice plates are still preserved during the off‐nadir period (within the remaining 50%), suggesting the undiscovered climatological information on ice plates in the post‐2007 observations. According to our analysis, the tilting mainly affects horizontal ice plate detection, while the impacts on water and randomly oriented ice detections are limited. The temperature of the ice plates ranges from −25.5°C and −7.5°C, with a mode temperature of −13.5°C, although the ice plates also occur ubiquitously across mid‐ to high‐latitudes between −20°C and −40°C, which is much colder than what found in previous nadir studies. This study offers a detailed discussion on the fundamental characteristics of horizontal ice plates that will provide robust information for the algorithm preparation for future satellite lidar observations such as the Earth, Clouds, Aerosol and Radiation Explorer (EarthCARE).
Publisher: Author(s)
Date: 2017
DOI: 10.1063/1.4975526
No related grants have been discovered for Hajime Okamoto.