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 A Technique for the Automatic Detection of Insect Clutter in Cloud Radar Returns

2008 ◽  
Vol 25 (9) ◽  
pp. 1498-1513 ◽  
Author(s):  
Edward P. Luke ◽  
Pavlos Kollias ◽  
Karen L. Johnson ◽  
Eugene E. Clothiaux
Keyword(s):  
Great Plains ◽  
Department Of Energy ◽  
Cloud Base ◽  
Doppler Spectrum ◽  
Southern Great Plains ◽  
Radar Echoes ◽  
Neural Network Algorithm ◽  
Atmospheric Radiation Measurement ◽  
Automated Technique ◽  
Research Facilities

Abstract The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates 35-GHz millimeter-wavelength cloud radars (MMCRs) in several climatologically distinct regions. The MMCRs, which are centerpiece instruments for the observation of clouds and precipitation, provide continuous, vertically resolved information on all hydrometeors above the ARM Climate Research Facilities (ACRF). However, their ability to observe clouds in the lowest 2–3 km of the atmosphere is often obscured by the presence of strong echoes from insects, especially during the warm months at the continental midlatitude Southern Great Plains (SGP) ACRF. Here, a new automated technique for the detection and elimination of insect-contaminated echoes from the MMCR observations is presented. The technique is based on recorded MMCR Doppler spectra, a feature extractor that conditions insect spectral signatures, and the use of a neural network algorithm for the generation of an insect (clutter) mask. The technique exhibits significant skill in the identification of insect radar returns (more than 92% of insect-induced returns are identified) when the sole input to the classifier is the MMCR Doppler spectrum. The addition of circular polarization observations by the MMCR and ceilometer cloud-base measurements further improve the performance of the technique and form an even more reliable method for the removal of insect radar echoes at the ARM site. Recently, a 94-GHz Doppler polarimetric radar was installed next to the MMCR at the ACRF SGP site. Observations by both radars are used to evaluate the potential of the 94-GHz radar as being insect free and to show that dual wavelength radar reflectivity measurements can be used to identify insect radar returns.

scholarly journals Differences between Nonprecipitating Tropical and Trade Wind Marine Shallow Cumuli

2016 ◽  
Vol 144 (2) ◽  
pp. 681-701 ◽  
Author(s):  
Virendra P. Ghate ◽  
Mark A. Miller ◽  
Ping Zhu
Keyword(s):  
Surface Fluxes ◽  
Cloud Base ◽  
Trade Wind ◽  
Cumulus Clouds ◽  
Wind Speeds ◽  
Lower Cloud ◽  
Observational Site ◽  
Velocity Scale ◽  
Atmospheric Radiation Measurement ◽  
The Mean

Abstract Marine nonprecipitating cumulus topped boundary layers (CTBLs) observed in a tropical and in a trade wind region are contrasted based on their cloud macrophysical, dynamical, and radiative structures. Data from the Atmospheric Radiation Measurement (ARM) observational site previously operating at Manus Island, Papua New Guinea, and data collected during the deployment of ARM Mobile Facility at the island of Graciosa, in the Azores, were used in this study. The tropical marine CTBLs were deeper, had higher surface fluxes and boundary layer radiative cooling, but lower wind speeds compared to their trade wind counterparts. The radiative velocity scale was 50%–70% of the surface convective velocity scale at both locations, highlighting the prominent role played by radiation in maintaining turbulence in marine CTBLs. Despite greater thicknesses, the chord lengths of tropical cumuli were on average lower than those of trade wind cumuli, and as a result of lower cloud cover, the hourly averaged (cloudy and clear) liquid water paths of tropical cumuli were lower than the trade wind cumuli. At both locations ~70% of the cloudy profiles were updrafts, while the average amount of updrafts near cloud base stronger than 1 m s−1 was ~22% in tropical cumuli and ~12% in the trade wind cumuli. The mean in-cloud radar reflectivity within updrafts and mean updraft velocity was higher in tropical cumuli than the trade wind cumuli. Despite stronger vertical velocities and a higher number of strong updrafts, due to lower cloud fraction, the updraft mass flux was lower in the tropical cumuli compared to the trade wind cumuli. The observations suggest that the tropical and trade wind marine cumulus clouds differ significantly in their macrophysical and dynamical structures.

scholarly journals MU Radar and Lidar Observations of Clear-Air Turbulence underneath Cirrus

2010 ◽  
Vol 138 (2) ◽  
pp. 438-452 ◽  
Author(s):  
Hubert Luce ◽  
Takuji Nakamura ◽  
Masayuki K. Yamamoto ◽  
Mamoru Yamamoto ◽  
Shoichiro Fukao
Keyword(s):  
Convective Instability ◽  
Radar Data ◽  
Ice Crystals ◽  
Shear Instability ◽  
Cloud Base ◽  
Doppler Spectrum ◽  
Cirrus Cloud ◽  
Air Turbulence ◽  
Mu Radar ◽  
Generation Mechanisms

Abstract Turbulence generation mechanisms prevalent in the atmosphere are mainly shear instabilities, breaking of internal buoyancy waves, and convective instabilities such as thermal convection due to heating of the ground. In the present work, clear-air turbulence underneath a cirrus cloud base is described owing to coincident observations from the VHF (46.5 MHz) middle and upper atmosphere (MU) radar, a Rayleigh–Mie–Raman (RMR) lidar, and a balloon radiosonde on 7–8 June 2006 (at Shigaraki, Japan; 34.85°N, 136.10°E). Time–height cross section of lidar backscatter ratio obtained at 2206 LT 7 June 2006 showed the presence of a cirrus layer between 8.0 and 12.5 km MSL. Downward-penetrating structures of ice crystals with horizontal and vertical extents of 1.0–4.0 km and 200–800 m, respectively, have been detected at the cirrus cloud base for about 35 min. At the same time, the MU radar data revealed clear-air turbulence layers developing downward from the cloud base in the environment of the protuberances detected by the RMR lidar. Their maximum depth was about 2.0 km for about 1.5 h. They were associated with oscillatory vertical wind perturbations of up to ±1.5 m s−1 and variances of Doppler spectrum of 0.2–1.5 m−2 s−2. Analysis of the data suggests that the turbulence and the downward penetration of cloudy air were possibly the consequence of a convective instability (rather than a dynamical shear instability) that was likely due to sublimation of ice crystals in the subcloud region. Downward clear-air motions measured by the MU radar were associated with the descending protuberances, and updrafts were observed between them. These observations suggest that the cloudy air might have been pushed down by the downdrafts of the convective instability and pushed up by the updrafts to form the observed protuberances at the cloud base. These structures may be virga or perhaps more likely mamma as reported by recent observations of cirrus mamma with similar instruments and by numerical simulations.

scholarly journals Estimation of liquid water path below the melting layer in stratiform precipitation systems using radar measurements during MC3E

2019 ◽  
Vol 12 (7) ◽  
pp. 3743-3759 ◽  
Author(s):  
Jingjing Tian ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Christopher R. Williams ◽  
Peng Wu
Keyword(s):  
Liquid Water ◽  
Department Of Energy ◽  
Cloud Base ◽  
Retrieval Algorithm ◽  
Doppler Velocity ◽  
Liquid Water Path ◽  
Water Path ◽  
Melting Layer ◽  
Stratiform Precipitation ◽  
Cloud Particles

Abstract. In this study, the liquid water path (LWP) below the melting layer in stratiform precipitation systems is retrieved, which is a combination of rain liquid water path (RLWP) and cloud liquid water path (CLWP). The retrieval algorithm uses measurements from the vertically pointing radars (VPRs) at 35 and 3 GHz operated by the US Department of Energy Atmospheric Radiation Measurement (ARM) and National Oceanic and Atmospheric Administration (NOAA) during the field campaign Midlatitude Continental Convective Clouds Experiment (MC3E). The measured radar reflectivity and mean Doppler velocity from both VPRs and spectrum width from the 35 GHz radar are utilized. With the aid of the cloud base detected by a ceilometer, the LWP in the liquid layer is retrieved under two different situations: (I) no cloud exists below the melting base, and (II) cloud exists below the melting base. In (I), LWP is primarily contributed from raindrops only, i.e., RLWP, which is estimated by analyzing the Doppler velocity differences between two VPRs. In (II), cloud particles and raindrops coexist below the melting base. The CLWP is estimated using a modified attenuation-based algorithm. Two stratiform precipitation cases (20 and 11 May 2011) during MC3E are illustrated for two situations, respectively. With a total of 13 h of samples during MC3E, statistical results show that the occurrence of cloud particles below the melting base is low (9 %); however, the mean CLWP value can be up to 0.56 kg m−2, which is much larger than the RLWP (0.10 kg m−2). When only raindrops exist below the melting base, the average RLWP value is larger (0.32 kg m−2) than the with-cloud situation. The overall mean LWP below the melting base is 0.34 kg m−2 for stratiform systems during MC3E.

scholarly journals Calibrations and Performance of the Airborne Cloud Extinction Probe

2014 ◽  
Vol 31 (2) ◽  
pp. 326-345 ◽  
Author(s):  
Alexei Korolev ◽  
Alex Shashkov ◽  
Howard Barker
Keyword(s):  
Crystal Surface ◽  
Theoretical Calculations ◽  
Light Attenuation ◽  
Spherical Particles ◽  
Nonspherical Particles ◽  
Cloud Droplets ◽  
Fine Crystal ◽  
A New Technique ◽  
And Performance ◽  
Scattering Phase Function

Abstract A new airborne instrument that measures extinction coefficient β in clouds and precipitation has been designed by Environment Canada. The cloud extinction probe (CEP) utilizes the transmissometric method, which is based on direct measurement of light attenuation between the transmitter and receiver. Transmissometers are known to be susceptible to forward scattering, which becomes increasingly significant as the particle size increases. A new technique for calibrating transmissometers was developed here in order to determine the response function of the probe. Laboratory calibrations show that CEP-derived β may be underestimated by a factor of 2 for circular particles with diameters greater than 100 μm. Results for spherical particles are in good agreement with theoretical predictions. For nonspherical particles, however, estimates of β can deviate significantly from those derived for spheres that have the same projected area. For in situ observations of ice particles, CEP measurements often deviate significantly from theoretical calculations, whereas for small cloud droplets agreement is good. It is hypothesized that CEP-derived estimates of β for ice clouds depend much on variations in the scattering phase function that arise from details in ice crystal surface roughness and fine crystal structure. This would complicate greatly the estimation of β from transmissometers for ice-bearing clouds.

scholarly journals An Observational Study on Cloud Spectral Width in North China

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 109 ◽  
Author(s):  
Yuan Wang ◽  
Shengjie Niu ◽  
Chunsong Lu ◽  
Yangang Liu ◽  
Jingyi Chen ◽  
...  
Keyword(s):  
Size Range ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Spectral Width ◽  
Relative Dispersion ◽  
Cloud Base ◽  
Cloud Droplets ◽  
Factors Affecting ◽  
Cloud Droplet Size Distribution ◽  
Stratiform Clouds

Cloud droplet size distribution (CDSD) is a critical characteristic for a number of processes related to clouds, considering that cloud droplets are formed in different sizes above the cloud-base. This paper analyzes the in-situ aircraft measurements of CDSDs and aerosol concentration ( N a ) performed in stratiform clouds in Hebei, China, in 2015 to reveal the characteristics of cloud spectral width, commonly known as relative dispersion ( ε , ratio of standard deviation (σ) to mean radius (r) of the CDSD). A new algorithm is developed to calculate the contributions of droplets of different sizes to ε . It is found that small droplets with the size range of 1 to 5.5 μm and medium droplets with the size range of 5.5 to 10 μm are the major contributors to ε, and the medium droplets generally dominate the change of ε. The variation of ε with N a can be well explained by comparing the normalized changes of σ and r ( k σ / σ and k r / r ), rather than k σ and k r only ( k σ is Δσ/Δ N a and k r is Δr/Δ N a ). From the perspective of external factors affecting ε change, the effects of N a and condensation are examined. It is found that ε increases initially and decreases afterward as N a increases, and “condensational broadening” occurs up to 1 km above cloud-base, potentially providing observational evidence for recent numerical simulations in the literature.

scholarly journals Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign

2019 ◽  
Vol 36 (6) ◽  
pp. 921-940 ◽  
Author(s):  
M. Christian Schwartz ◽  
Virendra P. Ghate ◽  
Bruce. A. Albrecht ◽  
Paquita Zuidema ◽  
Maria P. Cadeddu ◽  
...  
Keyword(s):  
High Performance ◽  
Environmental Research ◽  
High Spectral Resolution ◽  
Cloud System ◽  
Cloud Base ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
System Evolution ◽  
Microphysical Properties ◽  
Fuzzy Logic Technique

AbstractThe Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR’s High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved using the HCR reflectivity, HSRL backscatter, and the HCR Doppler spectrum width after it is corrected for the aircraft speed. These indicate that as the boundary layers deepen and cloud-top heights increase toward the equator, both the cloud and rain fractions decrease.

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.

Evaluation of the GOES-R ABI LAP Retrieval Algorithm Using the GOES-13 Sounder

2014 ◽  
Vol 31 (1) ◽  
pp. 3-19 ◽  
Author(s):  
Yong-Keun Lee ◽  
Zhenglong Li ◽  
Jun Li ◽  
Timothy J. Schmit
Keyword(s):  
Microwave Radiometer ◽  
Precipitable Water ◽  
Retrieval Algorithm ◽  
Earth Observing System ◽  
Radiosonde Observation ◽  
Global Positioning ◽  
Atmospheric Radiation Measurement ◽  
Atmospheric Profile ◽  
Infrared Radiances ◽  
Environmental Prediction

Abstract A physical retrieval algorithm has been developed for deriving the legacy atmospheric profile (LAP) product from infrared radiances of the Advanced Baseline Imager (ABI) on board the next-generation Geostationary Operational Environmental Satellite (GOES-R) series. In this study, the GOES-R ABI LAP retrieval algorithm is applied to the GOES-13 sounder radiance measurements (termed the GOES-13 LAP retrieval algorithm in this study) for its validation as well as for potential transition of the GOES-13 LAP retrieval algorithm for the operational processing of GOES sounder data. The GOES-13 LAP retrievals are compared with five different truth measurements: radiosonde observation (raob) and microwave radiometer–measured total precipitable water (TPW) at the Atmospheric Radiation Measurement Cloud and Radiation Testbed site, conventional raob, TPW measurements from the global positioning system–integrated precipitable water NOAA network, and TPW measurements from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). The results show that with the GOES-R ABI LAP retrieval algorithm, the GOES-13 sounder provides better water vapor profiles than the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) forecast fields at the levels between 300 and 700 hPa. The root-mean-square error (RMSE) and standard deviation (STD) of the GOES-13 sounder TPW are consistently reduced from those of the GFS forecast no matter which measurements are used as the truth. These substantial improvements indicate that the GOES-R ABI LAP retrieval algorithm is well prepared to provide continuity of quality to some of the current GOES sounder products, and the algorithm can be transferred to process the current GOES sounder measurements for operational product generation.

scholarly journals On the limits of Köhler activation theory: how do collision and coalescence affect the activation of aerosols?

2017 ◽  
Vol 17 (13) ◽  
pp. 8343-8356 ◽  
Author(s):  
Fabian Hoffmann
Keyword(s):  
Critical Radius ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Aerosol Concentration ◽  
Cloud Base ◽  
Cloud Droplets ◽  
Activation Theory ◽  
Large Eddy ◽  
Kohler Theory ◽  
Additional Process

Abstract. Activation is necessary to form a cloud droplet from an aerosol, and it is widely accepted that it occurs as soon as a wetted aerosol grows beyond its critical radius. Traditional Köhler theory assumes that this growth is driven by the diffusion of water vapor. However, if the wetted aerosols are large enough, the coalescence of two or more particles is an additional process for accumulating sufficient water for activation. This transition from diffusional to collectional growth marks the limit of traditional Köhler theory and it is studied using a Lagrangian cloud model in which aerosols and cloud droplets are represented by individually simulated particles within large-eddy simulations of shallow cumuli. It is shown that the activation of aerosols larger than 0. 1 µm in dry radius can be affected by collision and coalescence, and its contribution increases with a power-law relation toward larger radii and becomes the only process for the activation of aerosols larger than 0. 4–0. 8 µm depending on aerosol concentration. Due to the natural scarcity of the affected aerosols, the amount of aerosols that are activated by collection is small, with a maximum of 1 in 10 000 activations. The fraction increases as the aerosol concentration increases, but decreases again as the number of aerosols becomes too high and the particles too small to cause collections. Moreover, activation by collection is found to affect primarily aerosols that have been entrained above the cloud base.

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