scholarly journals A New Criterion to Improve Operational Drizzle Detection with Ground-Based Remote Sensing

2019 ◽  
Vol 36 (5) ◽  
pp. 781-801 ◽  
Author(s):  
Claudia Acquistapace ◽  
Ulrich Löhnert ◽  
Maximilian Maahn ◽  
Pavlos Kollias
Keyword(s):  
Liquid Water ◽  
Positive Zero ◽  
Doppler Spectrum ◽  
Fall Velocity ◽  
Cloud Droplets ◽  
Particle Sedimentation ◽  
Boundary Layer Dynamics ◽  
Cloud Evolution ◽  
New Criterion

AbstractLight shallow precipitation in the form of drizzle is one of the mechanisms for liquid water removal, affecting cloud lifetime and boundary layer dynamics and thermodynamics. The early formation of drizzle drops is of particular interest for quantifying aerosol–cloud–precipitation interactions. In models, drizzle initiation is represented by the autoconversion, that is, the conversion of liquid water from a cloud liquid water category (where particle sedimentation is ignored) into a precipitating liquid water category. Various autoconversion parameterizations have been proposed in recent years, but their evaluation is challenging due to the lack of proper observations of drizzle development in the cloud. This work presents a new algorithm for Classification of Drizzle Stages (CLADS). CLADS is based on the skewness of the Ka-band radar Doppler spectrum. Skewness is sensitive to the drizzle growth in the cloud: the observed Gaussian Doppler spectrum has skewness zero when only cloud droplets are present without any significant fall velocity. Defining downward velocities positive, skewness turns positive when embryonic drizzle forms and becomes negative when drizzle starts to dominate the spectrum. CLADS identifies spatially coherent structures of positive, zero, and negative skewness in space and time corresponding to drizzle seeding, drizzle growth/nondrizzle, and drizzle mature, respectively. We test CLADS on case studies from the Jülich Observatory for Cloud Evolution Core Facility (JOYCE-CF) and the Barbados Cloud Observatory (BCO) to quantitatively estimate the benefits of CLADS compared to the standard Cloudnet target categorization algorithm. We suggest that CLADS can provide additional observational constraints for understanding the processes related to drizzle formation better.

scholarly journals Supercooled liquid water and secondary ice production in Kelvin–Helmholtz instability as revealed by radar Doppler spectra observations

2021 ◽  
Author(s):  
Haoran Li ◽  
Alexei Korolev ◽  
Dmitri Moisseev
Keyword(s):  
Liquid Water ◽  
Supercooled Liquid ◽  
Mixed Phase ◽  
Ice Crystals ◽  
Radiation Budget ◽  
Doppler Spectrum ◽  
Droplet Growth ◽  
Liquid Droplets ◽  
Cloud Droplets ◽  
Ice Particles

Abstract. Mixed-phase clouds are globally omnipresent and play a major role in the Earth's radiation budget and precipitation formation. The existence of liquid droplets in presence of ice particles is microphysically unstable and depends on a delicate balance of several competing processes. Understanding mechanisms that govern ice initiation and moisture supply are important to understand the life-cycle of such clouds. This study presents observations that reveal the onset of drizzle inside a ∼600 m deep mixed-phase layer embedded in a stratiform precipitation system. Using Doppler spectra analysis, we show how large supercooled liquid droplets are generated in Kelvin-Helmholtz (K-H) instability despite ice particles falling from upper cloud layers. The spectral width of supercooled liquid water mode in radar Doppler spectrum is used to identify a region of increased turbulence. The observations show that large liquid droplets, characterized by reflectivity values larger than −20 dBZ, are generated in this region. In addition to cloud droplets, Doppler spectral analysis reveals the production of the columnar ice crystals in the K-H billows. The modelling study estimates that the concentration of these ice crystals is 3 ∼ 8 L−1, which is at least one order of magnitude higher than that of primary ice nucleating particles. Given the detail of the observations, we show that multiple populations of secondary ice particles are generated in regions where larger cloud droplets are produced and not at some constant level within the cloud. It is therefore hypothesized that K-H instability provides conditions favorable for enhanced droplet growth and formation of secondary ice particles.

scholarly journals Supercooled liquid water and secondary ice production in Kelvin–Helmholtz instability as revealed by radar Doppler spectra observations

2021 ◽  
Vol 21 (17) ◽  
pp. 13593-13608
Author(s):  
Haoran Li ◽  
Alexei Korolev ◽  
Dmitri Moisseev
Keyword(s):  
Spectral Analysis ◽  
Liquid Water ◽  
Supercooled Liquid ◽  
Mixed Phase ◽  
Ice Crystals ◽  
Doppler Spectrum ◽  
Liquid Droplets ◽  
Cloud Droplets ◽  
Ice Particles ◽  
Doppler Spectral Analysis

Abstract. Mixed-phase clouds are globally omnipresent and play a major role in the Earth's radiation budget and precipitation formation. The existence of liquid droplets in the presence of ice particles is microphysically unstable and depends on a delicate balance of several competing processes. Understanding mechanisms that govern ice initiation and moisture supply are important to understand the life cycle of such clouds. This study presents observations that reveal the onset of drizzle inside a ∼ 600 m deep mixed-phase layer embedded in a stratiform precipitation system. Using Doppler spectral analysis, we show how large supercooled liquid droplets are generated in Kelvin–Helmholtz (K–H) instability despite ice particles falling from upper cloud layers. The spectral width of the supercooled liquid water mode in the radar Doppler spectrum is used to identify a region of increased turbulence. The observations show that large liquid droplets, characterized by reflectivity values larger than −20 dBZ, are generated in this region. In addition to cloud droplets, Doppler spectral analysis reveals the production of columnar ice crystals in the K–H billows. The modeling study estimates that the concentration of these ice crystals is 3–8 L−1, which is at least 1 order of magnitude higher than that of primary ice-nucleating particles. Given the detail of the observations, we show that multiple populations of secondary ice particles are generated in regions where larger cloud droplets are produced and not at some constant level within the cloud. It is, therefore, hypothesized that K–H instability provides conditions favorable for enhanced droplet growth and formation of secondary ice particles.

scholarly journals Constraints on interactions between aerosols and clouds on a global scale from a combination of MODIS-CERES satellite data and climate simulations

2010 ◽  
Vol 10 (20) ◽  
pp. 9851-9861 ◽  
Author(s):  
X. Ma ◽  
K. von Salzen ◽  
J. Cole
Keyword(s):  
Liquid Water ◽  
Negative Relationship ◽  
Cloud Droplet ◽  
Global Scale ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Cloud Droplets ◽  
Cloud Liquid Water ◽  
Albedo Effect ◽  
Cloud Liquid Water Path

Abstract. Satellite-based cloud top effective radius retrieved by the CERES Science Team were combined with simulated aerosol concentrations from CCCma CanAM4 to examine relationships between aerosol and cloud that underlie the first aerosol indirect (cloud albedo) effect. Evidence of a strong negative relationship between sulphate, and organic aerosols, with cloud top effective radius was found for low clouds, indicating both aerosol types are contributing to the first indirect effect on a global scale. Furthermore, effects of aerosol on the cloud droplet effective radius are more pronounced for larger cloud liquid water paths. While CanAM4 broadly reproduces the observed relationship between sulphate aerosols and cloud droplets, it does not reproduce the dependency of cloud top droplet size on organic aerosol concentrations nor the dependency on cloud liquid water path. Simulations with a modified version of the model yield a more realistic dependency of cloud droplets on organic carbon. The robustness of the methods used in the study are investigated by repeating the analysis using aerosol simulated by the GOCART model and cloud top effective radii derived from the MODIS Science Team.

Refinements to Ice Particle Mass Dimensional and Terminal Velocity Relationships for Ice Clouds. Part II: Evaluation and Parameterizations of Ensemble Ice Particle Sedimentation Velocities

2007 ◽  
Vol 64 (4) ◽  
pp. 1068-1088 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Gerd-Jan van Zadelhoff ◽  
David P. Donovan ◽  
Frederic Fabry ◽  
Robin J. Hogan ◽  
...  
Keyword(s):  
Climate Models ◽  
Doppler Radar ◽  
Terminal Velocity ◽  
Fall Velocity ◽  
Particle Sedimentation ◽  
Cloud Properties ◽  
Wide Range ◽  
Single Moment ◽  
Ice Water Content ◽  
Ice Water

Abstract This two-part study addresses the development of reliable estimates of the mass and fall speed of single ice particles and ensembles. Part I of the study reports temperature-dependent coefficients for the mass-dimensional relationship, m = aDb, where D is particle maximum dimension. The fall velocity relationship, Vt = ADB, is developed from observations in synoptic and low-latitude, convectively generated, ice cloud layers, sampled over a wide range of temperatures using an assumed range for the exponent b. Values for a, A, and B were found that were consistent with the measured particle size distributions (PSD) and the ice water content (IWC). To refine the estimates of coefficients a and b to fit both lower and higher moments of the PSD and the associated values for A and B, Part II uses the PSD from Part I plus coincident, vertically pointing Doppler radar returns. The observations and derived coefficients are used to evaluate earlier, single-moment, bulk ice microphysical parameterization schemes as well as to develop improved, statistically based, microphysical relationships. They may be used in cloud and climate models, and to retrieve cloud properties from ground-based Doppler radar and spaceborne, conventional radar returns.

Separating Cloud and Drizzle Radar Moments during Precipitation Onset Using Doppler Spectra

2013 ◽  
Vol 30 (8) ◽  
pp. 1656-1671 ◽  
Author(s):  
Edward P. Luke ◽  
Pavlos Kollias
Keyword(s):  
Cloud Base ◽  
Doppler Spectrum ◽  
Retrieval Algorithm ◽  
Cloud Droplets ◽  
Gaussian Shape ◽  
Model Parameterization ◽  
Atmospheric Radiation Measurement ◽  
Shape Property ◽  
A New Technique ◽  
Turbulence Parameters

Abstract The retrieval of cloud, drizzle, and turbulence parameters using radar Doppler spectra is challenged by the convolution of microphysical and dynamical influences and the overall uncertainty introduced by turbulence. A new technique that utilizes recorded radar Doppler spectra from profiling cloud radars is presented here. The technique applies to areas in clouds where drizzle is initially produced by the autoconversion process and is detected by a positive skewness in the radar Doppler spectrum. Using the Gaussian-shape property of cloud Doppler spectra, the cloud-only radar Doppler spectrum is estimated and used to separate the cloud and drizzle contributions. Once separated, the cloud spectral peak can be used to retrieve vertical air motion and eddy dissipation rates, while the drizzle peak can be used to estimate the three radar moments of the drizzle particle size distribution. The technique works for nearly 50% of spectra found near cloud top, with efficacy diminishing to roughly 15% of spectra near cloud base. The approach has been tested on a large dataset collected in the Azores during the Atmospheric Radiation Measurement Program (ARM) Mobile Facility deployment on Graciosa Island from May 2009 through December 2010. Validation of the proposed technique is achieved using the cloud base as a natural boundary between radar Doppler spectra with and without cloud droplets. The retrieval algorithm has the potential to characterize the dynamical and microphysical conditions at cloud scale during the transition from cloud to precipitation. This has significant implications for improving the understanding of drizzle onset in liquid clouds and for improving model parameterization schemes of autoconversion of cloud water into drizzle.

scholarly journals EQUILIBRIUM CONDITIONS IN BEACH WAVE INTERACTION

1972 ◽  
Vol 1 (13) ◽  
pp. 62 ◽  
Author(s):  
H. Raman
Keyword(s):  
Wave Interaction ◽  
Experimental Results ◽  
Laboratory Studies ◽  
Regular Waves ◽  
Equilibrium Conditions ◽  
Wave Characteristics ◽  
New Criterion ◽  
Constant Characteristics ◽  
Stable Points

Laboratory studies were conducted in an attempt to find out a relationship between beach and wave characteristics when equilibrium conditions are reached in beach wave interaction for the simple case of regular waves acting normal to the beach. Experimental results indicate the existence of stable points on beach profiles where the coordinates of the profile do not change with time when waves of constant characteristics act on the beach. Emperical relationship between the wave and beach properties are proposed. A new criterion for classification of beach profiles is indicated.

scholarly journals A new classification of satellite derived liquid water cloud regimes at cloud scale

2019 ◽  
Author(s):  
Claudia Unglaub ◽  
Karoline Block ◽  
Johannes Mülmenstädt ◽  
Odran Sourdeval ◽  
Johannes Quaas
Keyword(s):  
Liquid Water ◽  
Smooth Transition ◽  
Cloud Base ◽  
Cloud Parameters ◽  
Stratiform Clouds ◽  
Inhomogeneity Parameter ◽  
Water Cloud ◽  
Cloud Regimes ◽  
Cloud Base Height

Abstract. Clouds are highly variable in time and space affecting climate sensitivity and climate change. To study and distinguish the different influences of clouds on the climate system it is useful to separate clouds into individual cloud regimes. In this work we present a new cloud classification for liquid water clouds at cloud scale defined using cloud parameters retrieved from combined satellite measurements from CloudSat and CALIPSO. The idea is that cloud heterogeneity is a measure that allows to distinguish cumuliform and stratiform clouds, and cloud base height a measure to distinguish cloud altitude. The approach makes use of a newly-developed cloud-base height retrieval. Using three cloud base height intervals and two intervals of cloud top variability as an inhomogeneity parameter provides six new liquid cloud classes. The results show a smooth transition between marine and continental clouds as well as between stratiform and cumuliform clouds in different latitudes at the high spatial resolution of about 20 km. Analyzing the micro- and macrophysical cloud parameters from collocated combined MODIS, CloudSat and CALIPSO retrievals shows distinct characteristics for each cloud regimes that are in agreement with expectation and literature. This demonstrates the usefulness of the classification.

scholarly journals Particle Center Supported Plane for Subsurface Target Classification based on Full Polarimetric Ground Penetrating Radar

2019 ◽  
Vol 11 (4) ◽  
pp. 405
Author(s):  
Xuan Feng ◽  
Haoqiu Zhou ◽  
Cai Liu ◽  
Yan Zhang ◽  
Wenjing Liang ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Decomposition Methods ◽  
Support Vector ◽  
Classification Methods ◽  
Target Classification ◽  
Data Set ◽  
Particle Center ◽  
Ground Penetrating ◽  
New Criterion

The subsurface target classification of ground penetrating radar (GPR) is a popular topic in the field of geophysics. Among the existing classification methods, geometrical features and polarimetric attributes of targets are primarily used. As polarimetric attributes contain more information of targets, polarimetric decomposition methods, such as H-Alpha decomposition, have been developed for target classification of GPR in recent years. However, the classification template used in H-Alpha classification is preset depending on the experience of synthetic aperture radar (SAR); therefore, it may not be suitable for GPR. Moreover, many existing classification methods require excessive human operation, particularly when outliers exist in the sample (the data set containing the features of targets); therefore, they are not efficient or intelligent. We herein propose a new machine learning method based on sample centers, i.e., particle center supported plane (PCSP). The sample center is defined as the point with the smallest sum of distances from all points in the same sample, which is considered as a better representation of the sample without significant effect of the outliers. In this proposed method, particle swarm optimization (PSO) is performed to obtain the sample centers; the new criterion for subsurface target classification is achieved. We applied this algorithm to full polarimetric GPR data measured in the laboratory and outdoors. The results indicate that, comparing with support vector machine (SVM) and classical H-Alpha classification, this new method is more efficient and the accuracy is relatively high.

Classification of precipitation types using fall velocity-diameter relationships from 2D-video distrometer measurements

2015 ◽  
Vol 32 (9) ◽  
pp. 1277-1290 ◽  
Author(s):  
Jeong-Eun Lee ◽  
Sung-Hwa Jung ◽  
Hong-Mok Park ◽  
Soohyun Kwon ◽  
Pay-Liam Lin ◽  
...  
Keyword(s):  
Fall Velocity

scholarly journals The NCAR–FAA Snow Machine: An Artificial Snow-Generation System

2018 ◽  
Vol 35 (11) ◽  
pp. 2159-2168
Author(s):  
Scott D. Landolt ◽  
Roy M. Rasmussen ◽  
Alan J. Hills ◽  
Warren Underwood ◽  
Charles A. Knight ◽  
...  
Keyword(s):  
Mass Balance ◽  
Size Distribution ◽  
Liquid Water ◽  
Generation System ◽  
Fall Velocity ◽  
Atmospheric Research ◽  
Controlled Conditions ◽  
Precipitation Gauge ◽  
Cold Chamber ◽  
Over Time

AbstractThe National Center for Atmospheric Research (NCAR) developed an artificial snow-generation system designed to operate in a laboratory cold chamber for testing aircraft anti-icing fluids under controlled conditions. Flakes of ice are produced by shaving an ice cylinder with a rotating carbide bit; the resulting artificial snow is dispersed by turbulent airflows and falls approximately 2.5 m to the bottom of the device. The resulting fine ice shavings mimic snow in size, distribution, fall velocity, density, and liquid water equivalent (LWE) snowfall rate. The LWE snowfall rate can be controlled using either a mass balance or a precipitation gauge, which measures the snowfall accumulation over time, from which the computer derives the LWE rate. LWE snowfall rates are calculated every 6 s, and the rate the ice cylinder is fed into the carbide bit is continually adjusted to ensure that the LWE snowfall rate matches a user-selected value. The system has been used to generate LWE snowfall rates ranging from 0 to 10 mm h−1 at temperatures from −2 to −30°C and densities of approximately 0.1–0.5 g cm−3. Comparisons of the snow-machine fluid tests with the outdoor fluid tests have shown that the snow machine can mimic natural outdoor rates under a broad range of conditions.

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