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 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.

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 Evaluation of Gamma Raindrop Size Distribution Assumption through Comparison of Rain Rates of Measured and Radar-Equivalent Gamma DSD

2014 ◽  
Vol 53 (6) ◽  
pp. 1618-1635 ◽  
Author(s):  
Elisa Adirosi ◽  
Eugenio Gorgucci ◽  
Luca Baldini ◽  
Ali Tokay
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Hydrological Cycle ◽  
Drop Size Distribution ◽  
Dual Polarization ◽  
Raindrop Size Distribution ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Rain Rates

AbstractTo date, one of the most widely used parametric forms for modeling raindrop size distribution (DSD) is the three-parameter gamma. The aim of this paper is to analyze the error of assuming such parametric form to model the natural DSDs. To achieve this goal, a methodology is set up to compare the rain rate obtained from a disdrometer-measured drop size distribution with the rain rate of a gamma drop size distribution that produces the same triplets of dual-polarization radar measurements, namely reflectivity factor, differential reflectivity, and specific differential phase shift. In such a way, any differences between the values of the two rain rates will provide information about how well the gamma distribution fits the measured precipitation. The difference between rain rates is analyzed in terms of normalized standard error and normalized bias using different radar frequencies, drop shape–size relations, and disdrometer integration time. The study is performed using four datasets of DSDs collected by two-dimensional video disdrometers deployed in Huntsville (Alabama) and in three different prelaunch campaigns of the NASA–Japan Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) ground validation program including the Hydrological Cycle in Mediterranean Experiment (HyMeX) special observation period (SOP) 1 field campaign in Rome. The results show that differences in rain rates of the disdrometer DSD and the gamma DSD determining the same dual-polarization radar measurements exist and exceed those related to the methodology itself and to the disdrometer sampling error, supporting the finding that there is an error associated with the gamma DSD assumption.

scholarly journals A Robust Dual-Frequency Radar Profiling Algorithm

2011 ◽  
Vol 50 (7) ◽  
pp. 1543-1557 ◽  
Author(s):  
Mircea Grecu ◽  
Lin Tian ◽  
William S. Olson ◽  
Simone Tanelli
Keyword(s):  
Synthetic Data ◽  
Optimization Procedure ◽  
Correction Method ◽  
Single Frequency ◽  
Retrieval Algorithm ◽  
Dual Frequency ◽  
Ka Band ◽  
Radar Observations ◽  
Distribution Shape ◽  
Ku Band

AbstractIn this study, an algorithm to retrieve precipitation from spaceborne dual-frequency (13.8 and 35.6 GHz, or Ku/Ka band) radar observations is formulated and investigated. Such algorithms will be of paramount importance in deriving radar-based and combined radar–radiometer precipitation estimates from observations provided by the forthcoming NASA Global Precipitation Measurement (GPM) mission. In GPM, dual-frequency Ku-/Ka-band radar observations will be available only within a narrow swath (approximately one-half of the width of the Ku-band radar swath) over the earth’s surface. Therefore, a particular challenge is to develop a flexible radar retrieval algorithm that can be used to derive physically consistent precipitation profile estimates across the radar swath irrespective of the availability of Ka-band radar observations at any specific location inside that swath, in other words, an algorithm capable of exploiting the information provided by dual-frequency measurements but robust in the absence of Ka-band channel. In the present study, a unified, robust precipitation retrieval algorithm able to interpret either Ku-only or dual-frequency Ku-/Ka-band radar observations in a manner consistent with the information content of the observations is formulated. The formulation is based on 1) a generalized Hitschfeld–Bordan attenuation correction method that yields generic Ku-only precipitation profile estimates and 2) an optimization procedure that adjusts the Ku-band estimates to be physically consistent with coincident Ka-band reflectivity observations and surface reference technique–based path-integrated attenuation estimates at both Ku and Ka bands. The algorithm is investigated using synthetic and actual airborne radar observations collected in the NASA Tropical Composition, Cloud, and Climate Coupling (TC4) campaign. In the synthetic data investigation, the dual-frequency algorithm performed significantly better than a single-frequency algorithm; dual-frequency estimates, however, are still sensitive to various assumptions such as the particle size distribution shape, vertical and cloud water distributions, and scattering properties of the ice-phase precipitation.

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.

scholarly journals Regional background O<sub>3</sub> and NO<sub>x</sub> in the Houston-Galveston- Brazoria (TX) region: A decadal-scale perspective

2016 ◽  
Author(s):  
Loredana G. Suciu ◽  
Robert J. Griffin ◽  
Caroline A. Masiello
Keyword(s):  
Spatial Scales ◽  
Lower Troposphere ◽  
Principal Component ◽  
Ground Level ◽  
Ambient Air ◽  
Regional Background ◽  
Time Period ◽  
Decadal Scale ◽  
Many Sources ◽  
Local Emissions

Abstract. Ozone (O3) in the lower troposphere is harmful to people and plants, particularly during summer, when photochemistry is the most active and higher temperatures favor local chemistry. Because of its dependence on the volatile organic compounds (VOCs) to nitrogen oxides (NOx) ratio, ground-level O3 is difficult to control locally, where many sources of these precursors contribute to its mixing ratio. In addition to local emissions, chemistry and transport, larger-scale factors also contribute to local O3 and NOx. These additional contributions (often referred to as "regional background") are not well quantified within the Houston-Galveston-Brazoria (HGB) region, impeding more efficient controls on precursor emissions to achieve compliance with the National Ambient Air Quality Standards for O3. In this study, we estimate regional background O3 and NOx in the HGB region and quantify their decadal-scale trends. We use four different approaches based on principal component analysis (PCA) to quantify background O3 and NOx. Three of these approaches consist of independent PCA on both O3 and NOx for both 1-h and 8-h levels to compare our results with previous studies and to highlight the effect of both temporal and spatial scales. In the fourth approach, we co-varied O3, NOx and meteorology. Our results show that the estimation of regional background O3 has less inherent uncertainty when it was constrained by NOx and meteorology, yielding a statistically significant temporal trend of −0.69 ± 0.27 ppb y−1. Likewise, the estimation of regional background NOx trend constrained by O3 and meteorology was −0.04 ± 0.02 ppb y−1. Our best estimates of 17-y average of season-scale background O3 and NOx were 46.72 ± 2.08 ppb and 6.80 ± 0.13 ppb, respectively. Regional background O3 and NOx both have declined over time in the HGB region. This decline is likely caused by a combination of state of Texas controls on precursor emissions since 2007 and the increase in frequency of flow from the Gulf of Mexico over the same time period.

scholarly journals Determination of Dynamic Brain Connectivity via Spectral Analysis

2021 ◽  
Vol 15 ◽  
Author(s):  
Peter A. Robinson ◽  
James A. Henderson ◽  
Natasha C. Gabay ◽  
Kevin M. Aquino ◽  
Tara Babaie-Janvier ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Brain Structure ◽  
Brain Connectivity ◽  
Spatial Scales ◽  
Effective Connectivity ◽  
Physical Nature ◽  
Building Blocks ◽  
Brain Dynamics ◽  
Compact Representation ◽  
The Brain

Spectral analysis based on neural field theory is used to analyze dynamic connectivity via methods based on the physical eigenmodes that are the building blocks of brain dynamics. These approaches integrate over space instead of averaging over time and thereby greatly reduce or remove the temporal averaging effects, windowing artifacts, and noise at fine spatial scales that have bedeviled the analysis of dynamical functional connectivity (FC). The dependences of FC on dynamics at various timescales, and on windowing, are clarified and the results are demonstrated on simple test cases, demonstrating how modes provide directly interpretable insights that can be related to brain structure and function. It is shown that FC is dynamic even when the brain structure and effective connectivity are fixed, and that the observed patterns of FC are dominated by relatively few eigenmodes. Common artifacts introduced by statistical analyses that do not incorporate the physical nature of the brain are discussed and it is shown that these are avoided by spectral analysis using eigenmodes. Unlike most published artificially discretized “resting state networks” and other statistically-derived patterns, eigenmodes overlap, with every mode extending across the whole brain and every region participating in every mode—just like the vibrations that give rise to notes of a musical instrument. Despite this, modes are independent and do not interact in the linear limit. It is argued that for many purposes the intrinsic limitations of covariance-based FC instead favor the alternative of tracking eigenmode coefficients vs. time, which provide a compact representation that is directly related to biophysical brain dynamics.

scholarly journals Extinction coefficients retrieved in deep tropical ice clouds from lidar observations using a CALIPSO-like algorithm compared to in-situ measurements from the Cloud Integrated Nephelometer during CRYSTAL-FACE

2006 ◽  
Vol 6 (5) ◽  
pp. 10649-10672 ◽  
Author(s):  
V. Noel ◽  
D. M. Winker ◽  
T. J. Garrett ◽  
M. McGill
Keyword(s):  
Spatial Scales ◽  
Deep Convection ◽  
Retrieval Algorithm ◽  
Crystal Face ◽  
Ice Clouds ◽  
Extinction Coefficients ◽  
Convective Systems ◽  
Lidar Ratio ◽  
Deep Convective Systems

Abstract. This paper presents a comparison of lidar ratios and volume extinction coefficients in tropical ice clouds, retrieved using observations from two instruments: the 532-nm Cloud Physics Lidar (CPL), and the in-situ Cloud Integrating Nephelometer (CIN) probe. Both instruments were mounted on airborne platforms during the CRYSTAL-FACE campaign and took measurements up to 17 km. Coincident observations from two cases of ice clouds located on top of deep convective systems are compared. First, lidar ratios are retrieved from CPL observations of attenuated backscatter, using a retrieval algorithm for opaque cloud similar to one used in the soon-to-be launched CALIPSO mission, and compared to results from the regular CPL algorithm. These lidar ratios are used to retrieve extinction coefficient profiles, which are compared to actual observations from the CIN in-situ probe, putting the emphasis on their vertical variability. When observations coincide, retrievals from both instruments are very similar. Differences are generally variations around the average profiles, and general trends on larger spatial scales are usually well reproduced. The two instruments agree well, with an average difference of less than 11% on optical depth retrievals. Results suggest the CALIPSO Deep Convection algorithm can be trusted to deliver realistic estimates of the lidar ratio, leading to good retrievals of extinction coefficients.

scholarly journals Blending Surface Currents from HF Radar Observations and Numerical Modeling: Tidal Hindcasts and Forecasts

2015 ◽  
Vol 32 (2) ◽  
pp. 256-281 ◽  
Author(s):  
E. V. Stanev ◽  
F. Ziemer ◽  
J. Schulz-Stellenfleth ◽  
J. Seemann ◽  
J. Staneva ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
German Bight ◽  
Spatial Scales ◽  
Surface Current ◽  
Hf Radar ◽  
Optimal Interpolation ◽  
Kelvin Wave ◽  
Arctic Seas ◽  
Current Estimate ◽  
Radar Observations

AbstractAn observation network operating three Wellen Radars (WERAs) in the German Bight, which are part of the Coastal Observing System for Northern and Arctic Seas (COSYNA), is presented in detail. Major consideration is given to expanding the patchy observations over the entire German Bight on a 1-km grid and producing state estimates at intratidal scales, and 6- and 12-h forecasts. This was achieved with the help of the proposed spatiotemporal optimal interpolation (STOI) method, which efficiently uses observations and simulations from a free model run within an analysis window of one or two tidal cycles. In this way the method maximizes the use of available observations and can be considered as a step toward the “best surface current estimate.” The performance of the analysis was investigated based on the achieved reduction of the misfit between model and observations. The complex dynamics of the study domain was illustrated based on the spatial and temporal changes of tidal ellipses for the M2 and M4 constituents from HF radar observations. It was demonstrated that blending observations and numerical modeling facilitates physical interpretation of processes such as the nonlinear distortion of the Kelvin wave in the coastal zone and in particular in front of the Elbe and Weser estuaries. Comparisons with in situ data acquired outside the area covered by the HF radar demonstrated that the analysis method is able to propagate the HF radar information to larger spatial scales.

Sign in / Sign up

Export Citation Format

Share Document