A Classification of Ice Crystal Habits Using Combined Lidar and Scanning Polarimeter Observations during the SEAC4RS Campaign

2020 ◽  
Vol 37 (12) ◽  
pp. 2185-2196
Author(s):  
Natalie Midzak ◽  
John E. Yorks ◽  
Jianglong Zhang ◽  
Bastiaan van Diedenhoven ◽  
Sarah Woods ◽  
...  
Keyword(s):  
Atmospheric Composition ◽  
Crystal Habit ◽  
Ice Crystal ◽  
Cloud Physics ◽  
Cloud Particle ◽  
Clustering Technique ◽  
Ice Crystal Habits

AbstractUsing collocated NASA Cloud Physics Lidar (CPL) and Research Scanning Polarimeter (RSP) data from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign, a new observational-based method was developed which uses a K-means clustering technique to classify ice crystal habit types into seven categories: column, plates, rosettes, spheroids, and three different type of irregulars. Intercompared with the collocated SPEC, Inc., Cloud Particle Imager (CPI) data, the frequency of the detected ice crystal habits from the proposed method presented in the study agrees within 5% with the CPI-reported values for columns, irregulars, rosettes, and spheroids, with more disagreement for plates. This study suggests that a detailed ice crystal habit retrieval could be applied to combined space-based lidar and polarimeter observations such as CALIPSO and POLDER in addition to future missions such as the Aerosols, Clouds, Convection, and Precipitation (A-CCP).

scholarly journals Classification of Ice Crystal Habits Observed From Airborne Cloud Particle Imager by Deep Transfer Learning

2019 ◽  
Vol 6 (10) ◽  
pp. 1877-1886 ◽  
Author(s):  
Haixia Xiao ◽  
Feng Zhang ◽  
Qianshan He ◽  
Pu Liu ◽  
Fei Yan ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Ice Crystal Habits

A Comprehensive Habit Diagram for Atmospheric Ice Crystals: Confirmation from the Laboratory, AIRS II, and Other Field Studies

2009 ◽  
Vol 66 (9) ◽  
pp. 2888-2899 ◽  
Author(s):  
Matthew P. Bailey ◽  
John Hallett
Keyword(s):  
Field Studies ◽  
Crystal Habit ◽  
Ice Crystal ◽  
Comprehensive Description ◽  
Cloud Particle ◽  
In Situ Observations ◽  
Ice Crystal Habits ◽  
Habit Modification ◽  
Recent Laboratory

Abstract Recent laboratory experiments and in situ observations have produced results in broad agreement with respect to ice crystal habits in the atmosphere. These studies reveal that the ice crystal habit at −20°C is platelike, extending to −40°C, and not columnar as indicated in many habit diagrams found in atmospheric science journals and texts. These diagrams were typically derived decades ago from laboratory studies, some with inherent habit bias, or from combinations of laboratory and in situ observations at the ground, observations that often did not account for habit modification by precipitation from overlying clouds of varying temperatures. Habit predictions from these diagrams often disagreed with in situ observations at temperatures below −20°C. More recent laboratory and in situ studies have achieved a consensus on atmospheric ice crystal habits that differs from the traditional habit diagrams. These newer results can now be combined to give a comprehensive description of ice crystal habits for the atmosphere as a function of temperature and ice supersaturation for temperatures from 0° to −70°C, a description dominated by irregular and imperfect crystals. Cloud particle imager (CPI) habit observations made during the Second Alliance Icing Research Study (AIRS II) and elsewhere corroborate this comprehensive habit description, and a new habit diagram is derived from these results.

scholarly journals A Coupled Cloud Physics–Radiation Parameterization of the Bulk Optical Properties of Cirrus and Its Impact on the Met Office Unified Model Global Atmosphere 5.0 Configuration

2014 ◽  
Vol 27 (20) ◽  
pp. 7725-7752 ◽  
Author(s):  
Anthony J. Baran ◽  
Peter Hill ◽  
Kalli Furtado ◽  
Paul Field ◽  
James Manners
Keyword(s):  
Optical Properties ◽  
Atmospheric Temperature ◽  
Unified Model ◽  
Crystal Habit ◽  
Temperature Structure ◽  
Ice Crystal ◽  
Cloud Physics ◽  
Shape Distribution ◽  
Temperature Bias ◽  
Ice Water

Abstract A new coupled cloud physics–radiation parameterization of the bulk optical properties of ice clouds is presented. The parameterization is consistent with assumptions in the cloud physics scheme regarding particle size distributions (PSDs) and mass–dimensional relationships. The parameterization is based on a weighted ice crystal habit mixture model, and its bulk optical properties are parameterized as simple functions of wavelength and ice water content (IWC). This approach directly couples IWC to the bulk optical properties, negating the need for diagnosed variables, such as the ice crystal effective dimension. The parameterization is implemented into the Met Office Unified Model Global Atmosphere 5.0 (GA5) configuration. The GA5 configuration is used to simulate the annual 20-yr shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere (TOA), as well as the temperature structure of the atmosphere, under various microphysical assumptions. The coupled parameterization is directly compared against the current operational radiation parameterization, while maintaining the same cloud physics assumptions. In this experiment, the impacts of the two parameterizations on the SW and LW radiative effects at TOA are also investigated and compared against observations. The 20-yr simulations are compared against the latest observations of the atmospheric temperature and radiative fluxes at TOA. The comparisons demonstrate that the choice of PSD and the assumed ice crystal shape distribution are as important as each other. Moreover, the consistent radiation parameterization removes a long-standing tropical troposphere cold temperature bias but slightly warms the southern midlatitudes by about 0.5 K.

scholarly journals Ice Crystal Linear Growth Rates from −20° to −70°C: Confirmation from Wave Cloud Studies

2012 ◽  
Vol 69 (1) ◽  
pp. 390-402 ◽  
Author(s):  
Matthew Bailey ◽  
John Hallett
Keyword(s):  
Growth Rates ◽  
Volume Growth ◽  
Field Studies ◽  
Atmospheric Conditions ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Simple Method ◽  
Laboratory Results ◽  
Ice Crystal Habits

Abstract As a result of recent comprehensive laboratory and field studies, many details have been clarified concerning atmospheric ice crystal habits below −20°C as a function of temperature, ice supersaturation, air pressure, and growth history. A predominance of complex shapes has been revealed that is not reflected in most models, with symmetric shapes often incorrectly emphasized. From the laboratory study, linear (maximum dimension), projected area, and volume growth rates of complex and simple habits have been measured under simulated atmospheric conditions for temperatures from −20° to −70°C. Presently, only a few in situ cases of measured ice crystal growth rates are available for comparison with laboratory results. Observations from the Interaction of Aerosol and Cold Clouds (INTACC) field study of a well-characterized wave cloud at −24°C are compared with the laboratory results using a simple method of habit averaging to derive a range of expected growth rates. Laboratory results are also compared with recently reported wave cloud results from the Ice in Clouds Experiment–Layer Clouds (ICE-L) study between −20° and −32°C, in addition to a much colder wave cloud at −65°C. Considerable agreement is observed in these cases, confirming the reliability of the laboratory measurements. This is the first of two companion papers that compare laboratory growth rates and characteristics with in situ measurements, confirming that the laboratory results effectively provide a predictive capability for cloud particle and particle ensemble growth.

Optimized intelligent algorithm for classifying cloud particles recorded by a Cloud Particle Imager

2021 ◽  
Author(s):  
Zepei Wu ◽  
Shuo Liu ◽  
Delong Zhao ◽  
Ling Yang ◽  
Zixin Xu ◽  
...  
Keyword(s):  
Processing Speed ◽  
Cloud Microphysics ◽  
Parameter Analysis ◽  
Ice Crystals ◽  
Support Vector ◽  
Svm Classifier ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Average Accuracy ◽  
Cloud Particles

AbstractCloud particles have different shapes in the atmosphere. Research on cloud particle shapes plays an important role in analyzing the growth of ice crystals and the cloud microphysics. To achieve an accurate and efficient classification algorithm on ice crystal images, this study uses image-based morphological processing and principal component analysis, to extract features of images and apply intelligent classification algorithms for the Cloud Particle Imager (CPI). Currently, there are mainly two types of ice-crystal classification methods: one is the mode parameterization scheme, and the other is the artificial intelligence model. Combined with data feature extraction, the dataset was tested on ten types of classifiers, and the highest average accuracy was 99.07%. The fastest processing speed of the real-time data processing test was 2,000 images/s. In actual application, the algorithm should consider the processing speed, because the images are in the order of millions. Therefore, a support vector machine (SVM) classifier was used in this study. The SVM-based optimization algorithm can classify ice crystals into nine classes with an average accuracy of 95%, blurred frame accuracy of 100%, with a processing speed of 2,000 images/s. This method has a relatively high accuracy and faster classification processing speed than the classic neural network model. The new method could be also applied in physical parameter analysis of cloud microphysics.

scholarly journals Characterising optical array particle imaging probes: implications for small-ice-crystal observations

2021 ◽  
Vol 14 (3) ◽  
pp. 1917-1939
Author(s):  
Sebastian O'Shea ◽  
Jonathan Crosier ◽  
James Dorsey ◽  
Louis Gallagher ◽  
Waldemar Schledewitz ◽  
...  
Keyword(s):  
Field Experiments ◽  
Field Measurements ◽  
Sample Volume ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Ice Clouds ◽  
Cloud Properties ◽  
Imaging Probes ◽  
New Methodologies ◽  
Particle Imaging

Abstract. The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (< 200 µm) in certain conditions. This work suggests that the observational evidence for a ubiquitous mode of small ice particles in ice clouds is likely due to a systematic instrument bias. Size distribution parameterisations based on OAP measurements need to be revisited using these improved methodologies.

Automatic Detection and Classification of Ischemic Stroke Using K-Means Clustering and Texture Features

2016 ◽  
pp. 441-461
Author(s):  
N. Hema Rajini ◽  
R. Bhavani
Keyword(s):  
Ischemic Stroke ◽  
Life Support ◽  
Texture Features ◽  
Support Vector ◽  
Clustering Technique ◽  
Computed Tomography Images ◽  
Brain Extraction ◽  
Third Stage ◽  
The Brain

Computed tomography images are widely used in the diagnosis of ischemic stroke because of its faster acquisition and compatibility with most life support devices. This chapter presents a new approach to automated detection of ischemic stroke using k-means clustering technique which separates the lesion region from healthy tissues and classification of ischemic stroke using texture features. The proposed method has five stages, pre-processing, tracing midline of the brain, extraction of texture features and feature selection, classification and segmentation. In the first stage noise is suppressed using a median filtering and skull bone components of the images are removed. In the second stage, midline shift of the brain is calculated. In the third stage, fourteen texture features are extracted and optimal features are selected using genetic algorithm. In the fourth stage, support vector machine, artificial neural network and decision tree classifiers have been used. Finally, the ischemic stroke region is extracted by using k-means clustering technique.

scholarly journals Lidar multiple scattering factors inferred from CALIPSO lidar and IIR retrievals of semi-transparent cirrus cloud optical depths over oceans

2015 ◽  
Vol 8 (7) ◽  
pp. 2759-2774 ◽  
Author(s):  
A. Garnier ◽  
J. Pelon ◽  
M. A. Vaughan ◽  
D. M. Winker ◽  
C. R. Trepte ◽  
...  
Keyword(s):  
Particle Size ◽  
Multiple Scattering ◽  
Infrared Absorption ◽  
Satellite Observations ◽  
Orthogonal Polarization ◽  
Cirrus Cloud ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Scattering Factor ◽  
Infrared Radiometer

Abstract. Cirrus cloud absorption optical depths retrieved at 12.05 μm are compared to extinction optical depths retrieved at 0.532 μm from perfectly co-located observations of single-layered semi-transparent cirrus over ocean made by the Imaging Infrared Radiometer (IIR) and the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) flying on board the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite. IIR infrared absorption optical depths are compared to CALIOP visible extinction optical depths when the latter can be directly derived from the measured apparent two-way transmittance through the cloud. An evaluation of the CALIOP multiple scattering factor is inferred from these comparisons after assessing and correcting biases in IIR and CALIOP optical depths reported in version 3 data products. In particular, the blackbody radiance taken in the IIR version 3 algorithm is evaluated, and IIR retrievals are corrected accordingly. Numerical simulations and IIR retrievals of ice crystal sizes suggest that the ratios of CALIOP extinction and IIR absorption optical depths should remain roughly constant with respect to temperature. Instead, these ratios are found to increase quasi-linearly by about 40 % as the temperature at the layer centroid altitude decreases from 240 to 200 K. It is discussed that this behavior can be explained by variations of the multiple scattering factor ηT applied to correct the measured apparent two-way transmittance for contribution of forward-scattering. While the CALIOP version 3 retrievals hold ηT fixed at 0.6, this study shows that ηT varies with temperature (and hence cloud particle size) from ηT = 0.8 at 200 K to ηT = 0.5 at 240 K for single-layered semi-transparent cirrus clouds with optical depth larger than 0.3. The revised parameterization of ηT introduces a concomitant temperature dependence in the simultaneously derived CALIOP lidar ratios that is consistent with observed changes in CALIOP depolarization ratios and particle habits derived from IIR measurements.

A Bulk Microphysics Parameterization with Multiple Ice Precipitation Categories

2005 ◽  
Vol 44 (4) ◽  
pp. 445-466 ◽  
Author(s):  
Jerry M. Straka ◽  
Edward R. Mansell
Keyword(s):  
Parameter Tuning ◽  
Precipitation Process ◽  
Ice Crystal ◽  
Cloud Droplets ◽  
Microphysics Scheme ◽  
Convective Storms ◽  
Single Moment ◽  
Warm Rain Process ◽  
Ice Crystal Habits ◽  
Cloud Ice

Abstract A single-moment bulk microphysics scheme with multiple ice precipitation categories is described. It has 2 liquid hydrometeor categories (cloud droplets and rain) and 10 ice categories that are characterized by habit, size, and density—two ice crystal habits (column and plate), rimed cloud ice, snow (ice crystal aggregates), three categories of graupel with different densities and intercepts, frozen drops, small hail, and large hail. The concept of riming history is implemented for conversions among the graupel and frozen drops categories. The multiple precipitation ice categories allow a range of particle densities and fall velocities for simulating a variety of convective storms with minimal parameter tuning. The scheme is applied to two cases—an idealized continental multicell storm that demonstrates the ice precipitation process, and a small Florida maritime storm in which the warm rain process is important.

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