Yuichiro Hagihara

Using in-situ airborne measurements to evaluate three cloud phase products derived from CALIPSO

We compare the cloud detection and cloud phase determination of three independent climatologies based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) to airborne in situ measurements. Our analysis of the cloud detection shows that the differences between the satellite and in situ measurements mainly arise from three factors. First, averaging CALIPSO Level l data along track before cloud detection increases the estimate of high- and low-level cloud fractions. Second, the vertical averaging of Level 1 data before cloud detection tends to artificially increase the cloud vertical extent. Third, the differences in classification of fully attenuated pixels among the CALIPSO climatologies lead to differences in the low-level Arctic cloud fractions. In another section, we compare the cloudy pixels detected by colocated in situ and satellite observations to study the cloud phase determination. At midlatitudes, retrievals of homogeneous high ice clouds by CALIPSO data sets are very robust (more than 94.6% of agreement with in situ). In the Arctic, where the cloud phase vertical variability is larger within a 480 m pixel, all climatologies show disagreements with the in situ measurements and CALIPSO-General Circulation Models-Oriented Cloud Product (GOCCP) report significant undefined-phase clouds, which likely correspond to mixed-phase clouds. In all CALIPSO products, the phase determination is dominated by the cloud top phase. Finally, we use global statistics to demonstrate that main differences between the CALIPSO cloud phase products stem from the cloud detection (horizontal averaging, fully attenuated pixels) rather than the cloud phase determination procedures.

Joint analysis of cloud top heights from CloudSat and CALIPSO: New insights into cloud top microphysics

We examined the differences in the cloud top heights (CTHs) detected by the CloudSat radar and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar. Theoretical estimates have shown that CloudSat has higher sensitivity than CALIPSO does when large particles exist. In such case it might be possible that CloudSat-determined CTHs are larger than CALIPSO-determined CTHs. We compared the global distribution of CTHs detected by CloudSat and CALIPSO (version 3, V3) using our cloud mask schemes after carefully selecting data during September–November 2006. The global mean fraction of clouds where CloudSat-determined CTHs were larger than CALIPSO-determined CTHs turned out to be unexpectedly large. The fractions were 26% and 39% at low level and midlevel, and the corresponding CTH differences were 0.56 km and 0.86 km, respectively. On the western coasts of continents, these clouds occurred within temperature inversions. Accounting for the differences in sensitivity to particle size between CloudSat and CALIPSO, the existence of such clouds indicates that the cloud tops consist of large particles with small number concentration. The discovery of such clouds was revealed by our joint analysis of CloudSat and CALIPSO. When the standard vertical feature mask (VFM) V3 was used, these clouds were also found but the fractions were less pronounced. The differences were partly attributed to the overestimation of cloud fraction in the VFM V3, although the degree of misidentification in V3 was reduced compared with that of V2.

Comparison of Global and Seasonal Characteristics of Cloud Phase and Horizontal Ice Plates Derived from CALIPSO with MODIS and ECMWF

AbstractThis 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 E...

Vertical grid spacing necessary for simulating tropical cirrus clouds with a high‐resolution atmospheric general circulation model

The distribution of simulated cirrus clouds over the tropics is affected by the particular models vertical grid spacing. To examine this effect, we use a high-resolution atmospheric general circulation model with 28 km and 14 km horizontal meshes. We show that a vertical grid spacing of 400 m or less is necessary to resolve the bulk structure of cirrus clouds. As one reduces the vertical grid spacing below about 1000 m, the visible cirrus cloud fraction decreases, the cloud thins (optically and geometrically), the cloud top height lowers, and consequently, the outgoing longwave radiation increases. These effects are stronger over the tropics. When using a vertical grid spacing of 400 m or less, the vertical profiles of effective radii and ice water content converge toward measurements (CloudSat satellite and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation).

Testing hydrometeor particle type discrimination derived from CloudSat and CALIPSO

We developed a test version of algorithm that discriminate cloud/precipitation phase and ice cloud particle shape (hereafter, hydrometeor particle type) from the synergy use of the cloud profiling radar (CPR) onboard CloudSat satellite and the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. We used the CALIOP classification algorithm that was developed by Yoshida et al. (2010) and modified by Hirakata et al. (2014). The CPR algorithm mainly consisted of the following steps: (1) initial discrimination by the look-up-table derived from the match-up statistical analysis of the CPR radar reflectivity, CALIOP cloud particle type and Tropical Rainfall Measuring Mission (TRMM) precipitation, and (2) precipitation correction of initial discrimination by unattenuated surface radar reflectivity. Lastly, the CPR and CALIOP synergy particle type was discriminated, simply by selecting the hydrometeor type that was ...

Development of Algorithm for Discriminating Hydrometeor Particle Types With a Synergistic Use of CloudSat and CALIPSO

We developed a method for classifying hydrometeor particle types, including cloud and precipitation phase and ice crystal habit, by a synergistic use of CloudSat/Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)/Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). We investigated how the cloud phase and ice crystal habit characterized by CALIOP globally relate with radar reflectivity and temperature. The global relationship thus identified was employed to develop an algorithm for hydrometeor type classification with CPR alone. The CPR-based type classification was then combined with CALIPSO-based type characterization to give CPR-CALIOP synergy classification. A unique aspect of this algorithm is to exploit and combine the lidars sensitivity to thin ice clouds and the radars ability to penetrate light precipitation to offer more complete picture of vertically resolved hydrometeor type classification than has been provided by previous studies. Given the complementary nature of radar and lidar detections of hydrometeors, our algorithm delivers thirteen hydrometeor types: warm water, supercooled water, randomly-oriented ice crystal (3D-ice), horizontally-oriented plate (2D-plate), 3D-ice+2D-plate, liquid drizzle, mixed-phase drizzle, rain, snow, mixed-phase cloud, water+liquid drizzle, water+rain and unknown. The global statistics of three-dimensional occurrence frequency of each hydrometeor type revealed that 3D-ice contributes the most to the total cloud occurrence frequency (53.8%), followed by supercooled water (14.3%), 2D-plate (9.2%), rain (5.9%), warm water (5.7%), snow (4.8%), mixed-phase drizzle (2.3%), and the remaining types (4.0%). This hydrometeor type classification provides useful observation-based information for climate model diagnostics in representation of cloud phase and their microphysical characteristics.

Evaluating Arctic cloud radiative effects simulated by NICAM with A-train

Evaluation of cloud radiative effects (CREs) in global atmospheric models is of vital importance to reduce uncertainties in weather forecasting and future climate projection. In this paper, we describe an effective way to evaluate CREs from a 3.5 km mesh global nonhydrostatic model by comparing it against A-train satellite data. The model is the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), and its output is run through a satellite-sensor simulator (Joint Simulator for satellite sensors) to produce the equivalent CloudSat radar, CALIPSO lidar, and Aqua Clouds and the Earths Radiant Energy System (CERES) data. These simulated observations are then compared to real observations from the satellites. We focus on the Arctic, which is a region experiencing rapid climate change over various surface types. The NICAM simulation significantly overestimates the shortwave CREs at top of atmosphere and surface as large as 24 W m−2 for the month of June. The CREs were decomposed into cloud fractions and footprint CREs of cloud types that are defined based on the CloudSat-CALIPSO cloud top temperature and maximum radar reflectivity. It turned out that the simulation underestimates the cloud fraction and optical thickness of mixed-phase clouds due to predicting too little supercooled liquid and predicting overly large snow particles with too little mass content. This bias was partially offset by predicting too many optically thin high clouds. Offline sensitivity experiments, where cloud microphysical parameters, surface albedo, and single scattering parameters are varied, support the diagnosis. Aerosol radiative effects and nonspherical single scattering of ice particles should be introduced into the NICAM broadband calculation for further improvement.

Synergy Use of MODIS, CloudSat and CALIPSO for Improved Retrieval of Liquid Water Cloud Microphysical Properties

In this paper, we retrieved microphysics of water clouds from MODIS on Aqua combined with the information of cloud top height from CloudSat and CALIPSO. This approach was different from the conventional method that used cloud top height from object analysis data. For the determination of the cloud top height, we developed radar‐lidar fusion cloud mask scheme based on the one for ground observation described by Okamoto et al. [1]. The cloud mask from MODIS standard product was also evaluated against CloudSat and CALIPSO data. Then, the improved version of the algorithm developed by Nakajima and Nakajima [2] and Kawamoto et al. [3] was applied to MODIS with the cloud top height derived from CloudSat and CALIPSO instead of that derived from NCEP/NCAR reanalysis data and global analysis of liquid water cloud properties was carried out from the MODIS over A‐train orbit path. We studied the statistical differences in cloud top height and microphysics between the results by the synergy approach and the conventio...

Relationship between ice supersaturation and ice microphysics inferred from CloudSat, CALIPSO and AIRS

Super saturation of ice clouds was investigated by using CloudSat, CALIPSO and AIRS on Aqua. Global distributions of relative humidity and temperature were first retrieved by using Ishimoto 2009 AIRS algorithm that used 110 channels and 46 channels for temperature and humidity retrievals, respectively. Retrievals have been conducted between 600hPa and 200hPa and also above clouds when cloud top height was below 800hPa. We relied on the information of clouds, i.e., cloud location and ice water content, from CloudSat radar and CALIOP lidar. The water vapor density from AIRS had been sampled along CloudSat and CALIPSO tracks in order to retrieve relative humidity in the vicinity of ice clouds. Relative humidity when ice formation occurred was estimated by using ice water content and the water vapor density near ice clouds.

Development of level 2 algorithms for EarthCARE CPR/ATLID

We develop algorithms that can be applied to EarthCARE Cloud Profiling Radar (CPR) and Atmospheric backscatter LIdar (ATLID) and discuss about the expected products. EarthCARE will carry CPR and ATLID and these combination corresponds to the CloudSat and CALIPSO for the A-train. Due to the similarities between the EarthCARE and the A-train, it will be possible to apply the similar types of algorithms that have been already developed and extensively used for the analyses of the A-train satellites and it is therefore expected to obtain the similar cloud products for the EarthCARE. On the other hand, there are some differences between the EarthCARE and A-train satellites, e.g., the EarthCRAE CPR has better sensitivity compared with the CloudSat. And Doppler capability of the EarthCARE-CPR is a new element and is expected to provide the better constraint for the retrievals of cloud/precipitation microphysics. And the vertical air motion and sedimentation velocity of cloud particles will be inferred.