scholarly journals Extinction-ice water content-effective radius algorithms for CALIPSO

2005 ◽  
Vol 32 (10) ◽  
Author(s):  
Andrew J. Heymsfield
Keyword(s):  
Water Content ◽  
Effective Radius ◽  
Ice Water Content ◽  
Ice Water

scholarly journals Effective Radius of Ice Particles in Cirrus and Contrails

2011 ◽  
Vol 68 (2) ◽  
pp. 300-321 ◽  
Author(s):  
U. Schumann ◽  
B. Mayer ◽  
K. Gierens ◽  
S. Unterstrasser ◽  
P. Jessberger ◽  
...  
Keyword(s):  
Water Content ◽  
Effective Radius ◽  
Cross Sectional Area ◽  
Sectional Area ◽  
Small Particles ◽  
Particle Volume ◽  
Cross Sectional ◽  
Ice Particles ◽  
Ice Water Content ◽  
Ice Water

Abstract This paper discusses the ratio C between the volume mean radius and the effective radius of ice particles in cirrus and contrails. The volume mean radius is proportional to the third root of the ratio between ice water content and number of ice particles, and the effective radius measures the ratio between ice particle volume and projected cross-sectional area. For given ice water content and number concentration of ice particles, the optical depth scales linearly with C. Hence, C is an important input parameter for radiative forcing estimates. The ratio C in general depends strongly on the particle size distribution (PSD) and on the particle habits. For constant habits, C can be factored into a PSD and a habit factor. The PSD factor is generally less than one, while the habit factor is larger than one for convex or concave ice particles with random orientation. The value of C may get very small for power-law PSDs with exponent n between −4 and 0, which is often observed. For such PSDs, most of the particle volume is controlled by a few large particles, while most of the cross-sectional area is controlled by the many small particles. A new particle habit mix for contrail cirrus including small droxtal-shape particles is suggested. For measured cirrus and contrails, the dependence of C on volume mean particle radius, ambient humidity, and contrail age is determined. For cirrus, C varies typically between 0.4 and 1.1. In contrails, C = 0.7 ± 0.3, with uncertainty ranges increasing with the volume radius and contrail age. For the small particles in young contrails, the extinction efficiency in the solar range deviates considerably from the geometric optics limit.

scholarly journals On the relationship of polar mesospheric cloud ice water content, particle radius and mesospheric temperature and its use in multi-dimensional models

2009 ◽  
Vol 9 (22) ◽  
pp. 8889-8901 ◽  
Author(s):  
A. W. Merkel ◽  
D. R. Marsh ◽  
A. Gettelman ◽  
E. J. Jensen
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Computational Cost ◽  
Cloud Microphysics ◽  
Effective Radius ◽  
Local Temperature ◽  
Decadal Scale ◽  
Ice Water Content ◽  
Ice Water ◽  
The Relationship

Abstract. The distribution of ice layers in the polar summer mesosphere (called polar mesospheric clouds or PMCs) is sensitive to background atmospheric conditions and therefore affected by global-scale dynamics. To investigate this coupling it is necessary to simulate the global distribution of PMCs within a 3-dimensional (3-D) model that couples large-scale dynamics with cloud microphysics. However, modeling PMC microphysics within 3-D global chemistry climate models (GCCM) is a challenge due to the high computational cost associated with particle following (Lagrangian) or sectional microphysical calculations. By characterizing the relationship between the PMC effective radius, ice water content (iwc), and local temperature (T) from an ensemble of simulations from the sectional microphysical model, the Community Aerosol and Radiation Model for Atmospheres (CARMA), we determined that these variables can be described by a robust empirical formula. The characterized relationship allows an estimate of an altitude distribution of PMC effective radius in terms of local temperature and iwc. For our purposes we use this formula to predict an effective radius as part of a bulk parameterization of PMC microphysics in a 3-D GCCM to simulate growth, sublimation and sedimentation of ice particles without keeping track of the time history of each ice particle size or particle size bin. This allows cost effective decadal scale PMC simulations in a 3-D GCCM to be performed. This approach produces realistic PMC simulations including estimates of the optical properties of PMCs. We validate the relationship with PMC data from the Solar Occultation for Ice Experiment (SOFIE).

scholarly journals The Evaluation of CloudSat and CALIPSO Ice Microphysical Products Using Ground-Based Cloud Radar and Lidar Observations

2010 ◽  
Vol 27 (5) ◽  
pp. 793-810 ◽  
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
E. J. O’Connor ◽  
T. S. L’Ecuyer
Keyword(s):  
Water Content ◽  
Statistical Method ◽  
Air Temperature ◽  
Number Concentration ◽  
Effective Radius ◽  
Vertical Profiles ◽  
Statistical Relationship ◽  
Ice Clouds ◽  
Ice Water Content ◽  
Ice Water

Abstract In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.

scholarly journals Microphysical properties and high ice water content in continental and oceanic Mescoscale Convective Systems and potential implications for commercial aircraft at flight altitude

2013 ◽  
Vol 13 (8) ◽  
pp. 22535-22574
Author(s):  
J.-F. Gayet ◽  
V. Shcherbakov ◽  
L. Bugliaro ◽  
A. Protat ◽  
J. Delanoë ◽  
...  
Keyword(s):  
Water Content ◽  
Convective Cloud ◽  
Effective Radius ◽  
Convective System ◽  
Commercial Aircraft ◽  
Microphysical Properties ◽  
Maximum Reflectivity ◽  
Ice Water Content ◽  
Ice Water

Abstract. Two complementary case studies are conducted to analyse convective system properties in the region where strong cloud-top lidar backscatter anomalies are observed as reported by Platt et al. (2011). These anomalies were reported for the first time using in-situ microphysical measurements in an isolated continental convective cloud over Germany during the CIRCLE2 experiment (Gayet et al., 2012). In this case, quasi collocated in situ observations with CALIPSO, CloudSat and Meteosat-9/SEVIRI observations confirm that regions of backscatter anomalies represent the most active and dense convective cloud parts with likely the strongest core updrafts and unusual high values of the particle concentration, extinction and ice water content (IWC), with the occurrence of small ice crystal sizes. Similar spaceborne observations are then analyzed in a maritime mesoscale cloud system (MCS) on 20 June 2008 located off the Brazil coast between 0° and 3° N latitude. Near cloud-top backscatter anomalies are evidenced in a region which corresponds to the coldest temperatures with maximum cloud top altitudes derived from collocated CALIPSO/IIR and Meteosat-9/SEVIRI infrared brightness temperatures. The interpretation of CALIOP data highlights significant differences of microphysical properties from those observed in the continental isolated convective cloud. Indeed, SEVIRI retrievals in the visible confirm much smaller ice particles near-top of the isolated continental convective cloud, i.e. effective radius (Reff) ~15 μm against 22–27 μm in the whole MCS area. 94 GHz Cloud Profiling Radar observations from CloudSat are then used to describe the properties of the most active cloud regions at and below cloud top. The cloud ice water content and effective radius retrieved with the CloudSat 2B-IWC and DARDAR inversion techniques, show that at usual cruise altitudes of commercial aircraft (FL 350 or ~10 700 m level), high IWC (i.e. up to 2 to 4 g m−3) could be identified according to specific IWC-Z relationships. These values correspond to a maximum reflectivity factor of +18 dBZ (at 94 GHz). Near-top cloud properties also indicate signatures of microphysical characteristics according to the cloud-stage evolution as revealed by SEVIRI images to identify the development of new cells within the MCS cluster. It is argued that the availability of real time information of the km-scale cloud top IR brightness temperature decrease with respect to the cloud environment would help identify MCS cloud areas with potentially high ice water content and small particle sizes against which onboard meteorological radar may not be suitable to provide timely warning.

scholarly journals A Comparison among Four Different Retrieval Methods for Ice-Cloud Properties Using Data from CloudSat, CALIPSO, and MODIS

2011 ◽  
Vol 50 (9) ◽  
pp. 1952-1969 ◽  
Author(s):  
Thorwald H. M. Stein ◽  
Julien Delanoë ◽  
Robin J. Hogan
Keyword(s):  
Water Content ◽  
Effective Radius ◽  
Retrieval Algorithm ◽  
Empirical Formulas ◽  
Mean Values ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
The Mean ◽  
Ice Water

AbstractThe A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function.

scholarly journals Microphysical properties and high ice water content in continental and oceanic mesoscale convective systems and potential implications for commercial aircraft at flight altitude

2014 ◽  
Vol 14 (2) ◽  
pp. 899-912 ◽  
Author(s):  
J.-F. Gayet ◽  
V. Shcherbakov ◽  
L. Bugliaro ◽  
A. Protat ◽  
J. Delanoë ◽  
...  
Keyword(s):  
Water Content ◽  
Convective Cloud ◽  
Effective Radius ◽  
Convective System ◽  
Commercial Aircraft ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
Ice Water ◽  
Reflectivity Factor

Abstract. Two complementary case studies are conducted to analyse convective system properties in the region where strong cloud-top lidar backscatter anomalies are observed as reported by Platt et al. (2011). These anomalies were reported for the first time using in situ microphysical measurements in an isolated continental convective cloud over Germany during the CIRCLE2 experiment (Gayet et al., 2012). In this case, in situ observations quasi-collocated with CALIPSO (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation), CloudSat and Meteosat-9/SEVIRI observations confirm that regions of backscatter anomalies represent the most active and dense convective cloud parts with likely the strongest core updrafts and unusually high values of the particle concentration, extinction and ice water content (IWC), with the occurrence of small ice crystal sizes. Similar spaceborne observations of a maritime mesoscale cloud system (MCS) located off the Brazilian coast between 0° and 3° N latitude on 20 June 2008 are then analysed. Near cloud-top backscatter anomalies are evidenced in a region which corresponds to the coldest temperatures with maximum cloud top altitudes derived from collocated CALIPSO/IIR and Meteosat-9/SEVIRI infrared brightness temperatures. The interpretation of CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) data highlights significant differences in microphysical properties from those observed in the continental isolated convective cloud. Indeed, SEVIRI (Spinning Enhanced Visible and InfraRed Imager) retrievals in the visible spectrum confirm much smaller ice particles near the top of the isolated continental convective cloud, i.e. effective radius (Reff) ~ 15 μm as opposed to 22–27 μm in the whole MCS area. Cloud profiling observations at 94 GHz from CloudSat are then used to describe the properties of the most active cloud regions at and below cloud top. The cloud ice-water content and effective radius retrieved with the CloudSat 2B-IWC and DARDAR (raDAR/liDAR) inversion techniques, show that at usual cruise altitudes of commercial aircraft (FL 350 or ~ 10 700 m level), high IWC (i.e. up to 2 to 4 g m−3) could be identified according to specific IWC–Z (Z being the reflectivity factor) relationships. These values correspond to a maximum reflectivity factor of +18 dBZ (at 94 GHz). Near-top cloud properties also indicate signatures of microphysical characteristics according to the cloud-stage evolution as revealed by SEVIRI images to identify the development of new cells within the MCS cluster. It is argued that the availability of real-time information (on the kilometre-scale) about cloud top IR brightness temperature decreases with respect to the cloud environment would help identify MCS cloud areas with potentially high ice water content and small particle sizes against which onboard meteorological radars may not be able to provide timely warning.

Ice water content assessment in the single-, dual-, and triple-frequency radar scenarios

2021 ◽  
Vol 254 ◽  
pp. 112242
Author(s):  
Eugenio Gorgucci ◽  
Luca Baldini ◽  
Elisa Adirosi ◽  
Mario Montopoli
Keyword(s):  
Water Content ◽  
Content Assessment ◽  
Triple Frequency ◽  
Ice Water Content ◽  
Ice Water

scholarly journals Measuring ice- and liquid-water properties in mixed-phase cloud layers at the Leipzig Cloudnet station

2016 ◽  
Vol 16 (16) ◽  
pp. 10609-10620 ◽  
Author(s):  
Johannes Bühl ◽  
Patric Seifert ◽  
Alexander Myagkov ◽  
Albert Ansmann
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Mass Flux ◽  
Mixed Phase ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Special Focus ◽  
Data Set ◽  
Ice Water Content ◽  
Ice Water

Abstract. An analysis of the Cloudnet data set collected at Leipzig, Germany, with special focus on mixed-phase layered clouds is presented. We derive liquid- and ice-water content together with vertical motions of ice particles falling through cloud base. The ice mass flux is calculated by combining measurements of ice-water content and particle Doppler velocity. The efficiency of heterogeneous ice formation and its impact on cloud lifetime is estimated for different cloud-top temperatures by relating the ice mass flux and the liquid-water content at cloud top. Cloud radar measurements of polarization and Doppler velocity indicate that ice crystals formed in mixed-phase cloud layers with a geometrical thickness of less than 350 m are mostly pristine when they fall out of the cloud.

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