scholarly journals A New Technique to Categorize and Retrieve the Microphysical Properties of Ice Particles above the Melting Layer Using Radar Dual-Polarization Spectral Analysis

2008 ◽  
Vol 25 (3) ◽  
pp. 482-497 ◽  
Author(s):  
A. L. J. Spek ◽  
C. M. H. Unal ◽  
D. N. Moisseev ◽  
H. W. J. Russchenberg ◽  
V. Chandrasekar ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Elevation Angle ◽  
Retrieval Algorithm ◽  
Dual Polarization ◽  
Melting Layer ◽  
Microphysical Properties ◽  
Ice Particles ◽  
Distribution Parameters ◽  
A New Technique ◽  
Doppler Power

Abstract In this study, a dual-polarization spectral analysis for retrieval of microphysical properties of ice hydrometeors is developed. It is shown that, by using simultaneous Doppler polarimetric observations taken at a 45° elevation angle, it is possible to discriminate between different types of ice particles. Particle size distribution parameters for maximally two dominating types of ice particles (aggregates and plates) observed above the melting layer are retrieved. Prior to the retrieval algorithm, a selection of possible types of ice particles based on environmental conditions is carried out. The retrieval procedure is based on a least squares optimization that simultaneously minimizes fit residuals in a Doppler power spectrum and spectral differential reflectivity. The proposed method is illustrated on transportable atmospheric radar (TARA) observations of stratiform rain collected on 19 September 2001 at Cabauw, Netherlands.

Dual-Polarization Spectral Analysis for Retrieval of Effective Raindrop Shapes

2006 ◽  
Vol 23 (12) ◽  
pp. 1682-1695 ◽  
Author(s):  
D. N. Moisseev ◽  
V. Chandrasekar ◽  
C. M. H. Unal ◽  
H. W. J. Russchenberg
Keyword(s):  
Spectral Analysis ◽  
Optimization Problems ◽  
Spatial Scales ◽  
Elevation Angle ◽  
Ambient Air ◽  
Retrieval Algorithm ◽  
Dual Polarization ◽  
Radar Observations ◽  
Raindrop Size ◽  
Parameter Retrieval

Abstract Dual-polarization radar observations of precipitation depend on size–shape relations of raindrops. There are several studies presented in literature dedicated to the investigation of this relation. In this work a new approach of investigating raindrop size–shape relation on short time and spatial scales from radar observations is presented. The presented method is based on the use of dual-polarization Doppler power spectral analysis. By measuring complete Doppler spectra at a sufficiently high elevation angle at two polarization settings, namely, horizontal and vertical, it is possible to retrieve drop size distribution (DSD) parameters, ambient air velocity, spectral broadening, and the slope of the assumed linear dependence of raindrop size–shape relation. This paper is mainly focused on the development of the retrieval algorithm and analysis of its performance. As a part of the proposed method an efficient algorithm for DSD parameter retrieval was developed. It is shown that the DSD parameter retrieval method, which usually requires the solution of five-parameter nonlinear optimization problems, can be simplified to a three-parameter nonlinear least squares problem. Furthermore, the performance of the proposed retrieval technique is illustrated on the dual-polarization measurements collected by the S-band Transportable Atmospheric Radar (TARA) at Cabauw, Netherlands, and by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar from Greeley, Colorado.

scholarly journals Synergistic radar and sub-millimeter radiometer retrievals of ice hydrometeors in mid-latitude frontal cloud systems

2021 ◽  
Author(s):  
Simon Pfreundschuh ◽  
Stuart Fox ◽  
Patrick Eriksson ◽  
David Duncan ◽  
Stefan A. Buehler ◽  
...  
Keyword(s):  
Climate Models ◽  
Single Scattering ◽  
Gas Absorption ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Sensor Calibration ◽  
Cloud Systems ◽  
Microphysical Properties ◽  
Ice Particles ◽  
Increased Sensitivity

Abstract. Accurate measurements of ice hydrometeors are required to improve the representation of clouds and precipitation in weather and climate models. In this study, a newly developed, synergistic retrieval algorithm that combines radar with passive millimeter and sub-millimeter observations is applied to observations of three frontally-generated, mid-latitude cloud systems in order to validate the retrieval and asses its capabilities to constrain the properties of ice hydrometeors. To account for uncertainty in the assumed shapes of ice particles, the retrieval is run multiple times while the assumed shape is varied. Good agreement with in situ measurements of ice water content and particle concentrations for particle maximum diameters larger than 200 μm is found for one of the flights for the Large Plate Aggregate and the 6-Bullet Rosette shapes. The variational retrieval fits the observations well although small systematic deviations are observed for some of the sub-millimeter pointing towards issues with the sensor calibration or the modeling of gas absorption. We find that the quality of the fit to the observations is independent of the assumed ice particle shape, indicating that the employed combination of observations is insufficient to constrain the shape of ice particles in the observed clouds. Compared to a radar-only retrieval, the results show an improved sensitivity of the synergistic retrieval to the microphysical properties of ice hydrometeors at the base of the cloud. Our findings indicate that the synergy between active and passive microwave observations improve remote-sensing measurements of ice hydrometeors and may thus help to reduce uncertainties that affect currently available data products. Due to the increased sensitivity to their microphysical properties, the retrieval may also be a valuable tool to study ice hydrometeors in field campaigns. The good fits obtained to the observations increases confidence in the modeling of clouds in the Atmospheric Radiative Transfer Simulator and the corresponding single scattering database, which were used to implement the retrieval forward model. Our results demonstrate the suitability of these tools to produce realistic simulations for upcoming sub-millimeter sensors such as the Ice Cloud Image or the Arctic Weather Satellite.

Nonparametric Estimation of Raindrop Size Distributions from Dual-Polarization Radar Spectral Observations

2007 ◽  
Vol 24 (6) ◽  
pp. 1008-1018 ◽  
Author(s):  
Dmitri N. Moisseev ◽  
V. Chandrasekar
Keyword(s):  
Elevation Angle ◽  
Power Spectra ◽  
High Elevation ◽  
Size Distributions ◽  
Dual Polarization ◽  
Mean Velocity ◽  
Colorado State University ◽  
Raindrop Size ◽  
Drop Size Distributions ◽  
Doppler Power

This paper presents a method to retrieve raindrop size distributions (DSD) from slant profile dual-polarization Doppler spectra observations. It is shown that using radar measurements taken at a high elevation angle raindrop size distributions can be retrieved without making an assumption on the form of a DSD. In this paper it is shown that drop size distributions can be retrieved from Doppler power spectra by compensating for the effect of spectrum broadening and mean velocity shift. To accomplish that, spectrum deconvolution is used where the spectral broadening kernel width and wind velocity are estimated from spectral differential reflectivity measurements. Since convolution kernel is estimated from dual-polarization Doppler spectra observations and does not require observation of a clear-air signal, this method can be used by most radars capable of dual-polarization spectra measurements. To validate the technique, sensitivity of this method to the underlying assumptions and calibration errors is evaluated on realistic simulations of radar observations. Furthermore, performance of the method is illustrated on Colorado State University–University of Chicago–Illinois State Water Survey radar (CSU–CHILL) measurements of stratiform precipitation.

scholarly journals Arctic Mixed-Phase Cloud Properties from AERI Lidar Observations: Algorithm and Results from SHEBA

2005 ◽  
Vol 44 (4) ◽  
pp. 427-444 ◽  
Author(s):  
D. D. Turner
Keyword(s):  
Liquid Water ◽  
Heat Budget ◽  
Single Layer ◽  
Precipitable Water ◽  
Mixed Phase ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Cloud Optical Depth ◽  
Microphysical Properties ◽  
Ice Particles

Abstract A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 μm, whereas liquid water is more absorbing than ice from 16 to 25 μm. MIXCRA retrievals are only valid for optically thin (τvisible < 6) single-layer clouds when the precipitable water vapor is less than 1 cm. MIXCRA was applied to the Atmospheric Emitted Radiance Interferometer (AERI) data that were collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment from November 1997 to May 1998, where 63% of all of the cloudy scenes above the SHEBA site met this specification. The retrieval determined that approximately 48% of these clouds were mixed phase and that a significant number of clouds (during all 7 months) contained liquid water, even for cloud temperatures as low as 240 K. The retrieved distributions of effective radii for water and ice particles in single-phase clouds are shown to be different than the effective radii in mixed-phase clouds.

scholarly journals Towards the connection between snow microphysics and melting layer: Insights from multi-frequency and dual-polarization radar observations during BAECC

2020 ◽  
Author(s):  
Haoran Li ◽  
Jussi Tiira ◽  
Annakaisa von Lerber ◽  
Dmitri Moisseev
Keyword(s):  
Doppler Radar ◽  
Strong Dependence ◽  
Precipitation Intensity ◽  
Dual Polarization ◽  
Radar Observations ◽  
Melting Layer ◽  
Microphysical Properties ◽  
Microphysical Processes ◽  
Biogenic Aerosols ◽  
The Impact

Abstract. In stratiform rainfall, the melting layer is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the melting layer and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured melting layer properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide an additional constraint on the retrieval of ice cloud microphysical properties, we have investigated this link. This study is divided into two parts. Firstly, surface-based snowfall measurements are used to devise a method for classifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. In the second part, this classification is used in combination with multi-frequency and dual-polarization radar observations to investigate the impact of precipitation intensity, aggregation, riming, and dendritic growth on melting layer properties. The radar-observed melting layer characteristics show strong dependence on precipitation intensity as well as detectable differences between unrimed and rimed snow. This study is based on the data collected during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) experiment, that took place in 2014 in Hyytiala, Finland.

The influence of WSR-88D intra-volume scanning strategies on thunderstorm observations and warnings in the dual-polarization radar era: 2011-2020

2021 ◽  
Author(s):  
Michael M. French
Keyword(s):  
Lead Time ◽  
Elevation Angle ◽  
Large Majority ◽  
Dual Polarization ◽  
Severe Thunderstorm ◽  
Low Level ◽  
Tornado Warnings ◽  
Scanning Strategies ◽  
The Cost ◽  
Organized Convection

Abstract The Weather Surveillance Radar - 1988 Doppler (WSR-88D) network has undergone several improvements in the last decade with the upgrade to dual-polarization capabilities and the ability for forecasters to re-scan the lowest levels of the atmosphere more frequently through the use of Supplemental Adaptive Intra-volume Scanning (SAILS). SAILS reduces the revisit period for scanning the lowest 1 km of the atmosphere but comes at the cost of a longer delay between scans at higher altitudes. This study quantifies how often radar Volume Coverage Patterns (VCPs) and all available SAILS options are used during the issuance of 148,882 severe thunderstorm and 18,263 tornado warnings, and near 10,474 tornado, 58,934 hail, and 127,575 wind reports in the dual-polarization radar era. A large majority of warnings and storm reports were measured with a VCP providing denser low-level sampling coverage. More frequent low-level updates were employed near tornado warnings and reports compared to severe thunderstorm warnings and hail or wind hazards. Warnings issued near a radar providing three extra low-level scans (SAILSx3) were more likely to be verified by a hazard with a positive lead time than warnings with fewer low-level scans. However, extra low-level scans were more frequently used in environments supporting organized convection as shown using watches issued by the Storm Prediction Center. Recently, the number of mid-level radar elevation scans is declining per hour, which can adversely affect the tracking of convective polarimetric signatures, like ZDR columns, which were found above the 0.5° elevation angle in over 99% of cases examined.

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 Microphysical properties and fall speed measurements of snow ice crystals using the Dual Ice Crystal Imager (D-ICI)

2020 ◽  
Vol 13 (3) ◽  
pp. 1273-1285 ◽  
Author(s):  
Thomas Kuhn ◽  
Sandra Vázquez-Martín
Keyword(s):  
Remote Sensing ◽  
Vertical Direction ◽  
Ice Crystals ◽  
Ice Crystal ◽  
Double Exposure ◽  
Shape Information ◽  
Microphysical Properties ◽  
Ice Particles ◽  
Crystal Properties ◽  
Fall Speed

Abstract. Accurate predictions of snowfall require good knowledge of the microphysical properties of the snow ice crystals and particles. Shape is an important parameter as it strongly influences the scattering properties of the ice particles, and thus their response to remote sensing techniques such as radar measurements. The fall speed of ice particles is another important parameter for both numerical forecast models as well as representation of ice clouds and snow in climate models, as it is responsible for the rate of removal of ice from these models. We describe a new ground-based in situ instrument, the Dual Ice Crystal Imager (D-ICI), to determine snow ice crystal properties and fall speed simultaneously. The instrument takes two high-resolution pictures of the same falling ice particle from two different viewing directions. Both cameras use a microscope-like setup resulting in an image pixel resolution of approximately 4 µm pixel−1. One viewing direction is horizontal and is used to determine fall speed by means of a double exposure. For this purpose, two bright flashes of a light-emitting diode behind the camera illuminate the falling ice particle and create this double exposure, and the vertical displacement of the particle provides its fall speed. The other viewing direction is close-to-vertical and is used to provide size and shape information from single-exposure images. This viewing geometry is chosen instead of a horizontal one because shape and size of ice particles as viewed in the vertical direction are more relevant than these properties viewed horizontally, as the vertical fall speed is more strongly influenced by the vertically viewed properties. In addition, a comparison with remote sensing instruments that mostly have a vertical or close-to-vertical viewing geometry is favoured when the particle properties are measured in the same direction. The instrument has been tested in Kiruna, northern Sweden (67.8∘ N, 20.4∘ E). Measurements are demonstrated with images from different snow events, and the determined snow ice crystal properties are presented.

Insights into the Evolving Microphysical and Kinematic Structure of Northeastern U.S. Winter Storms from Dual-Polarization Doppler Radar

2017 ◽  
Vol 145 (3) ◽  
pp. 1033-1061 ◽  
Author(s):  
Matthew R. Kumjian ◽  
Kelly A. Lombardo
Keyword(s):  
Doppler Radar ◽  
Elevation Angle ◽  
Model Performance ◽  
Radar Data ◽  
Added Value ◽  
Dual Polarization ◽  
Differential Phase Shift ◽  
Winter Storms ◽  
Microphysical Processes ◽  
Ice Production

The recent Weather Surveillance Radar-1988 Doppler (WSR-88D) network upgrade to dual-polarization capabilities allows for bulk characterization of microphysical processes in northeastern U.S. winter storms for the first time. In this study, the quasi-vertical profile (QVP) technique (wherein data from a given elevation angle scan are azimuthally averaged and the range coordinate is converted to height) is extended and applied to polarimetric WSR-88D observations of six Northeast winter storms to survey their evolving, bulk vertical microphysical and kinematic structures. These analyses are supplemented using hourly analyses from the Rapid Refresh (RAP) model. Regions of ascent inferred from QVPs were consistently associated with notable polarimetric signatures, implying planar crystal growth when near −15°C, and riming and secondary ice production at higher temperatures. The heaviest snowfall occurred most often when ascent and enhanced propagation differential phase shift ([Formula: see text]) occurred near −15°C. When available, limited surface observations confirmed heavy snowfall rates and revealed large snow-to-liquid ratios at these times. Other cases revealed sudden, large melting-layer excursions associated with precipitation-type transitions near the surface. RAP analyses failed to capture such complex evolution, demonstrating the added value of dual-polarization radar observations in these scenarios and the potential use of radar data for assessing model performance in real time. These insights are a preliminary step toward better understanding the complex processes in northeastern U.S. winter storms.

A New Technique for Optimization of Product Acceptance Process in Terms of Misclassification Probability

2018 ◽  
pp. 1-32
Author(s):  
Nicholas A. Nechval ◽  
Konstantin N. Nechval
Keyword(s):  
Weibull Distribution ◽  
Optimization Technique ◽  
Parametric Uncertainty ◽  
Lifetime Distribution ◽  
Statistical Quality Control ◽  
Misclassification Probability ◽  
Distribution Parameters ◽  
A New Technique ◽  
Two Parameter

A product acceptance process is an inspecting one in statistical quality control or reliability tests, which are used to make decisions about accepting or rejecting lots of products to be submitted. This process is important for industrial and business purposes of quality management. To determine the optimal parameters of the product acceptance process under parametric uncertainty of underlying lifetime models (in terms of misclassification probability), a new optimization technique is proposed. The most popular lifetime distribution used in the field of product acceptance is a two-parameter Weibull distribution, with the assumption that the shape parameter is known. Such oversimplified assumptions can facilitate the follow-up analyses, but may overlook the fact that the lifetime distribution can significantly affect the estimation of the failure rate of a product. Therefore, the situations are also considered when both Weibull distribution parameters are unknown. An illustrative numerical example is given.

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