scholarly journals Disdrometer, Polarimetric Radar, and Condensation Nuclei Observations of Supercell and Multicell Storms on 11 June 2018 in Eastern Nebraska

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 770
Author(s):  
Matthew Van Den Broeke
Keyword(s):  
Particle Concentration ◽  
Rain Rate ◽  
Radar Data ◽  
Convective Cell ◽  
Observation Time ◽  
Precipitation Intensity ◽  
Polarimetric Radar ◽  
Condensation Nuclei ◽  
Supercell Storm ◽  
Differential Reflectivity

Disdrometer and condensation nuclei (CN) data are compared with operational polarimetric radar data for one multicell and one supercell storm in eastern Nebraska on 11 June 2018. The radar was located ~14.3 km from the instrumentation location and provided excellent observation time series with new low-level samples every 1–2 min. Reflectivity derived by the disdrometer and radar compared well, especially in regions with high number concentration of drops and reflectivity <45 dBZ. Differential reflectivity also compared well between the datasets, though it was most similar in the supercell storm. Rain rate calculated by the disdrometer closely matched values estimated by the radar when reflectivity and differential reflectivity were used to produce the estimate. Concentration of CN generally followed precipitation intensity for the leading convective cell, with evidence for higher particle concentration on the edges of the convective cell associated with outflow. The distribution of CN in the supercell was more complex and generally did not follow precipitation intensity.

scholarly journals Assimilation of Polarimetric Radar Data in Simulation of a Supercell Storm with a Variational Approach and the WRF Model

2021 ◽  
Vol 13 (16) ◽  
pp. 3060
Author(s):  
Muyun Du ◽  
Jidong Gao ◽  
Guifu Zhang ◽  
Yunheng Wang ◽  
Pamela L. Heiselman ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Cross Correlation ◽  
Weather Prediction ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Differential Phase ◽  
Supercell Storm ◽  
Convective Scale ◽  
Differential Reflectivity ◽  
Forward Operator

Polarimetric radar data (PRD) have potential to be used in numerical weather prediction (NWP) models to improve convective-scale weather forecasts. However, thus far only a few studies have been undertaken in this research direction. To assimilate PRD in NWP models, a forward operator, also called a PRD simulator, is needed to establish the relation between model physics parameters and polarimetric radar variables. Such a forward operator needs to be accurate enough to make quantitative comparisons between radar observations and model output feasible, and to be computationally efficient so that these observations can be easily incorporated into a data assimilation (DA) scheme. To address this concern, a set of parameterized PRD simulators for the horizontal reflectivity, differential reflectivity, specific differential phase, and cross-correlation coefficient were developed. In this study, we have tested the performance of these new operators in a variational DA system. Firstly, the tangent linear and adjoint (TL/AD) models for these PRD simulators have been developed and checked for the validity. Then, both the forward operator and its adjoint model have been built into the three-dimensional variational (3DVAR) system. Finally, some preliminary DA experiments have been performed with an idealized supercell storm. It is found that the assimilation of PRD, including differential reflectivity and specific differential phase, in addition to radar radial velocity and horizontal reflectivity, can enhance the accuracy of both initial conditions for model hydrometer state variables and ensuing model forecasts. The usefulness of the cross-correlation coefficient is very limited in terms of improving convective-scale data analysis and NWP.

scholarly journals Validation of a Multilag Estimator on NJU-CPOL and a Hybrid Approach for Improving Polarimetric Radar Data Quality

2020 ◽  
Vol 12 (1) ◽  
pp. 180
Author(s):  
Shiqing Shao ◽  
Kun Zhao ◽  
Haonan Chen ◽  
Jianjun Chen ◽  
Hao Huang
Keyword(s):  
Theoretical Analysis ◽  
Correlation Coefficient ◽  
Hybrid Method ◽  
Radar Data ◽  
Noise Power ◽  
Signal Power ◽  
Polarimetric Radar ◽  
Moment Estimation ◽  
Spectrum Width ◽  
Differential Reflectivity

For the estimation of weak echo with low signal-to-noise ratio (SNR), a multilag estimator is developed, which has better performance than the conventional method. The performance of the multilag estimator is examined by theoretical analysis, simulated radar data and some specific observed data collected by a C-band polarimetric radar in previous research. In this paper, the multilag estimator is implemented and verified for Nanjing University C-band polarimetric Doppler weather radar (NJU-CPOL) during the Observation, Prediction and Analysis of Severe Convection of China (OPACC) field campaign in 2014. The implementation results are also compared with theoretical analysis, including the estimation of signal power, spectrum width, differential reflectivity, and copolar correlation coefficient. The results show that the improvement of the multilag estimator is little for signal power and differential reflectivity, but significant for spectrum width and copolar correlation coefficient when spectrum width is less than 2 ms−1, which implies a large correlation time scale. However, there are obvious biases from the multilag estimator in the regions with large spectrum width. Based on the performance analysis, a hybrid method is thus introduced and examined through NJU-CPOL observations. All lags including lag 0 of autocorrelation function (ACF) are used for moment estimation in this algorithm according to the maximum usable lag number. A case study shows that this hybrid method can improve moment estimation compared to both conventional estimator and multilag estimator, especially for weak weather echoes. The improvement will be significant if SNR decreases or the biases of noise power in the conventional estimator increase. In addition, this hybrid method is easy to implement on both operational and non-operational radars. It is also expected that the proposed hybrid method will have a better performance if applied to S-band polarimetric radars which have twice the maximum useable lags in the same conditions with C-band radars.

scholarly journals Sensitivities of Quantitative Precipitation Forecasts for Typhoon Soudelor (2015) near Landfall to Polarimetric Radar Data Assimilation

2020 ◽  
Vol 12 (22) ◽  
pp. 3711
Author(s):  
Chih-Chien Tsai ◽  
Kao-Shen Chung
Keyword(s):  
Data Assimilation ◽  
Radar Data ◽  
Convective Precipitation ◽  
Polarimetric Radar ◽  
Differential Phase ◽  
Observation Operator ◽  
Quantitative Precipitation Forecasts ◽  
Series Of Experiments ◽  
Differential Reflectivity ◽  
Radar Data Assimilation

Based on the preciousness and uniqueness of polarimetric radar observations collected near the landfall of Typhoon Soudelor (2015), this study investigates the sensitivities of very short-range quantitative precipitation forecasts (QPFs) for this typhoon to polarimetric radar data assimilation. A series of experiments assimilating various combinations of radar variables are carried out for the purpose of improving a 6 h deterministic forecast for the most intense period. The results of the control simulation expose three sources of the observation operator errors, including the raindrop shape-size relation, the limitations for ice-phase hydrometeors, and the melting ice model. Nevertheless, polarimetric radar data assimilation with the unadjusted observation operator can still improve the analyses, especially rainwater, and consequent QPFs for this typhoon case. The different impacts of assimilating reflectivity, differential reflectivity, and specific differential phase are only distinguishable at the lower levels of convective precipitation areas where specific differential phase is found most helpful. The positive effect of radar data assimilation on QPFs can last three hours in this study, and further improvement can be expected by optimizing the observation operator in the future

scholarly journals A Variational Approach for Retrieving Raindrop Size Distribution from Polarimetric Radar Measurements in the Presence of Attenuation

2013 ◽  
Vol 52 (1) ◽  
pp. 169-185 ◽  
Author(s):  
Qing Cao ◽  
Guifu Zhang ◽  
Ming Xue
Keyword(s):  
Variational Approach ◽  
Simulated Data ◽  
Real Data ◽  
Radar Data ◽  
Polarimetric Radar ◽  
University Of Oklahoma ◽  
Raindrop Size Distribution ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Differential Reflectivity

AbstractThis study presents a two-dimensional variational approach to retrieving raindrop size distributions (DSDs) from polarimetric radar data in the presence of attenuation. A two-parameter DSD model, the constrained-gamma model, is used to represent rain DSDs. Three polarimetric radar measurements—reflectivity ZH, differential reflectivity ZDR, and specific differential phase KDP—are optimally used to correct for the attenuation and retrieve DSDs by taking into account measurement error effects. Retrieval results with simulated data demonstrate that the proposed algorithm performs well. Applications to real data collected by the X-band Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radars and the C-band University of Oklahoma–Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) also demonstrate the efficacy of this approach.

scholarly journals Can a Unique Model Describe the Raindrop Shape–Size Relation? A Clue from Polarimetric Radar Measurements

2009 ◽  
Vol 26 (9) ◽  
pp. 1829-1842 ◽  
Author(s):  
Eugenio Gorgucci ◽  
V. Chandrasekar ◽  
Luca Baldini
Keyword(s):  
Axial Ratio ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Drop Shape ◽  
Climatic Regions ◽  
Unique Shape ◽  
Initial Drop ◽  
Radar Measurements ◽  
Differential Reflectivity ◽  
Size Relation

Abstract A method is proposed to retrieve raindrop shape–size relations from the radar measurements of reflectivity factor Zh, differential reflectivity Zdr, and specific differential phase Kdp at S band. This procedure is obtained using a domain defined by the two variables Kdp/Zh and Zdr where the drop size distribution (DSD) variability is collapsed onto a line and any variation is essentially due to the drop shape variability. To obtain information on the raindrop shape–size relation underlying a set of radar observations, this domain is studied in conjunction with another domain describing the relation between the drop axial ratio (or shape) and its equivolumetric diameter. Using an initial drop shape and choosing a set of DSDs described by a normalized gamma model, polarimetric radar measurements are produced by simulation. An averaged curve of Kdp/Zh versus Zdr is obtained and compared with the same curve obtained from the radar data. By changing the initial axial ratio relation, a procedure of minimization between the two curves is developed to derive the underlying drop shape–size relation governing the radar measurements under consideration. Three sets of radar data collected in different climatic regions are analyzed to evaluate whether there is a unique shape–size relation.

scholarly journals Polarimetric Radar Observations from a Waterspout-Producing Thunderstorm

2015 ◽  
Vol 30 (2) ◽  
pp. 329-348 ◽  
Author(s):  
Matthew S. Van Den Broeke ◽  
Cynthia A. Van Den Broeke
Keyword(s):  
Lake Michigan ◽  
Convective Cell ◽  
Great Lakes Region ◽  
Polarimetric Radar ◽  
Air Mass ◽  
Radar Observations ◽  
Potential Source ◽  
Western Lake ◽  
Low Levels ◽  
Differential Reflectivity

Abstract A family of four waterspouts was produced by a convective cell over western Lake Michigan on 12 September 2013. This storm initiated along a boundary north of a mesolow in a low-level cold-air advection regime, and developed supercell characteristics once the second waterspout was in progress. Polarimetric characteristics of the storm, and of the development of supercell character, are presented. These observations represent the first documented polarimetric radar observations of waterspout-producing convection in the Great Lakes region. Unusually high differential reflectivity values accompanied this storm and its initiating boundary. The high values along the boundary are partially explained by a high density of dragonflies. High differential reflectivity values were present through much of the storm of interest despite very low aerosol concentration at low levels in the lake-influenced air mass. Finally, this case illustrates the importance of environmental awareness on waterspout-favorable days, especially when boundaries are nearby to serve as a potential source of enhanced environmental vertical vorticity.

scholarly journals Toward Completing the Raindrop Size Spectrum: Case Studies Involving 2D-Video Disdrometer, Droplet Spectrometer, and Polarimetric Radar Measurements

2017 ◽  
Vol 56 (4) ◽  
pp. 877-896 ◽  
Author(s):  
Merhala Thurai ◽  
Patrick Gatlin ◽  
V. N. Bringi ◽  
Walter Petersen ◽  
Patrick Kennedy ◽  
...  
Keyword(s):  
Radar Data ◽  
Size Spectrum ◽  
Polarimetric Radar ◽  
Dual Frequency ◽  
Low Profile ◽  
Precipitation Measurement ◽  
Raindrop Size ◽  
Drop Size Distributions ◽  
Differential Reflectivity ◽  
Global Precipitation

AbstractAnalysis of drop size distributions (DSD) measured by collocated Meteorological Particle Spectrometer (MPS) and a third-generation, low-profile, 2D-video disdrometer (2DVD) are presented. Two events from two different regions (Greeley, Colorado, and Huntsville, Alabama) are analyzed. While the MPS, with its 50-μm resolution, enabled measurements of small drops, typically for drop diameters below about 1.1 mm, the 2DVD provided accurate measurements for drop diameters above 0.7 mm. Drop concentrations in the 0.7–1.1-mm overlap region were found to be in excellent agreement between the two instruments. Examination of the combined spectra clearly reveals a drizzle mode and a precipitation mode. The combined spectra were analyzed in terms of the DSD parameters, namely, the normalized intercept parameter NW, the mass-weighted mean diameter Dm, and the standard deviation of mass spectrum σM. The inclusion of small drops significantly affected the NW and the ratio σM/Dm toward higher values relative to using the 2DVD-based spectra alone. For each of the two events, polarimetric radar data were used to characterize the variation of radar-measured reflectivity Zh and differential reflectivity Zdr with Dm from the combined spectra. In the Greeley event, this variation at S band was well captured for small values of Dm (<0.5 mm) where measured Zdr tended to 0 dB but Zh showed a noticeable decrease with decreasing Dm. For the Huntsville event, an overpass of the Global Precipitation Measurement mission Core Observatory satellite enabled comparison of satellite-based dual-frequency radar retrievals of Dm with ground-based DSD measurements. Small differences were found between the satellite-based radar retrievals and disdrometers.

scholarly journals Polarimetric Radar Characteristics of Melting Hail. Part III: Validation of the Algorithm for Hail Size Discrimination

2016 ◽  
Vol 55 (4) ◽  
pp. 829-848 ◽  
Author(s):  
Kiel L. Ortega ◽  
John M. Krause ◽  
Alexander V. Ryzhkov
Keyword(s):  
Radar Data ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Polarimetric Radar ◽  
Size Discrimination ◽  
Critical Success ◽  
Single Polarization ◽  
Differential Reflectivity

AbstractThis study is the third part of a paper series investigating the polarimetric radar properties of melting hail and application of those properties for operational polarimetric hail detection and determination of its size. The results of theoretical simulations in Part I were used to develop a hail size discrimination algorithm (HSDA) described in Part II. The HSDA uses radar reflectivity Z, differential reflectivity ZDR, and cross-correlation coefficient ρhv along with melting-level height within a fuzzy-logic scheme to distinguish among three hail size classes: small hail (with diameter D < 2.5 cm), large hail (2.5 < D < 5.0 cm), and giant hail (D > 5.0 cm). The HSDA validation is performed using radar data collected by numerous WSR-88D sites and more than 3000 surface hail reports obtained from the Severe Hazards Analysis and Verification Experiment (SHAVE). The original HSDA version was modified in the process of validation, and the modified algorithm demonstrates probability of detection of 0.594, false-alarm ratio of 0.136, and resulting critical success index (CSI) equal to 0.543. The HSDA outperformed the current operational single-polarization hail detection algorithm, which only provides a single hail size estimate per storm and is characterized by CSI equal to 0.324. It is shown that HSDA is particularly sensitive to the quality of ZDR measurements, which might be affected by possible radar miscalibration and anomalously high differential attenuation.

scholarly journals Development of an Operational Convective Nowcasting Algorithm Using Raindrop Size Sorting Information from Polarimetric Radar Data

2018 ◽  
Vol 33 (5) ◽  
pp. 1477-1495 ◽  
Author(s):  
Darrel M. Kingfield ◽  
Joseph C. Picca
Keyword(s):  
Model Simulation ◽  
Algorithm Design ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Horizontal Polarization ◽  
Spatiotemporal Resolution ◽  
Raindrop Size Distribution ◽  
Size Sorting ◽  
Raindrop Size ◽  
Differential Reflectivity

Abstract Raindrop size sorting is a ubiquitous microphysical occurrence in precipitating systems. Owing to the greater terminal fall speed of larger particles, a raindrop’s fall trajectory can be sensitive to its size, and strong air currents (e.g., a convective updraft) can enhance this sensitivity. Indeed, observational and numerical model simulation studies have confirmed these effects on raindrop size distributions near convective updrafts. One striking example is the lofting of liquid drops and partially frozen hydrometeors above the environmental 0°C level, resulting in a small columnar region of positive differential reflectivity ZDR in polarimetric radar data, known as the ZDR column. This signature can serve as a proxy for updraft location and strength, offering operational forecasters a tool for monitoring convective trends. Beneath the 0°C level, where WSR-88D spatiotemporal resolution is highest, anomalously high ZDR collocated with lower reflectivity factor at horizontal polarization ZH is often observed within and beneath convective updrafts. Here, size sorting creates a deficit in small drops, while relatively large drops and melting hydrometeors are present in low concentrations. As such, this unique raindrop size distribution and its related polarimetric signature can indicate updraft location sooner and more frequently than the detection of a ZDR column. This paper introduces a novel algorithm that capitalizes on the improved radar coverage at lower levels and automates the detection of this size sorting signature. At the algorithm core, unique ZH–ZDR relationships are created for each radar elevation scan, and positive ZDR outliers (often indicative of size sorting) are identified. Algorithm design, examples, performance, strengths and limitations, and future development are discussed.

scholarly journals Retrieval of lower-order moments of the drop size distribution using CSU-CHILL X-band polarimetric radar: a case study

2020 ◽  
Vol 13 (9) ◽  
pp. 4727-4750
Author(s):  
Viswanathan Bringi ◽  
Kumar Vijay Mishra ◽  
Merhala Thurai ◽  
Patrick C. Kennedy ◽  
Timothy H. Raupach
Keyword(s):  
Size Distribution ◽  
Lower Order ◽  
Drop Size ◽  
Radar Data ◽  
Drop Size Distribution ◽  
Polarimetric Radar ◽  
X Band ◽  
Double Moment ◽  
Differential Reflectivity

Abstract. The lower-order moments of the drop size distribution (DSD) have generally been considered difficult to retrieve accurately from polarimetric radar data because these data are related to higher-order moments. For example, the 4.6th moment is associated with a specific differential phase and the 6th moment with reflectivity and ratio of high-order moments with differential reflectivity. Thus, conventionally, the emphasis has been to estimate rain rate (3.67th moment) or parameters of the exponential or gamma distribution for the DSD. Many double-moment “bulk” microphysical schemes predict the total number concentration (the 0th moment of the DSD, or M0) and the mixing ratio (or equivalently, the 3rd moment M3). Thus, it is difficult to compare the model outputs directly with polarimetric radar observations or, given the model outputs, forward model the radar observables. This article describes the use of double-moment normalization of DSDs and the resulting stable intrinsic shape that can be fitted by the generalized gamma (G-G) distribution. The two reference moments are M3 and M6, which are shown to be retrievable using the X-band radar reflectivity, differential reflectivity, and specific attenuation (from the iterative correction of measured reflectivity Zh using the total Φdp constraint, i.e., the iterative ZPHI method). Along with the climatological shape parameters of the G-G fit to the scaled/normalized DSDs, the lower-order moments are then retrieved more accurately than possible hitherto. The importance of measuring the complete DSD from 0.1 mm onwards is emphasized using, in our case, an optical array probe with 50 µm resolution collocated with a two-dimensional video disdrometer with about 170 µm resolution. This avoids small drop truncation and hence the accurate calculation of lower-order moments. A case study of a complex multi-cell storm which traversed an instrumented site near the CSU-CHILL radar is described for which the moments were retrieved from radar and compared with directly computed moments from the complete spectrum measurements using the aforementioned two disdrometers. Our detailed validation analysis of the radar-retrieved moments showed relative bias of the moments M0 through M2 was <15 % in magnitude, with Pearson’s correlation coefficient >0.9. Both radar measurement and parameterization errors were estimated rigorously. We show that the temporal variation of the radar-retrieved mass-weighted mean diameter with M0 resulted in coherent “time tracks” that can potentially lead to studies of precipitation evolution that have not been possible so far.

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