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 Variational Retrieval of Rain Microphysics and Related Parameters from Polarimetric Radar Data with a Parameterized Operator

2019 ◽  
Vol 36 (12) ◽  
pp. 2483-2500 ◽  
Author(s):  
Vivek N. Mahale ◽  
Guifu Zhang ◽  
Ming Xue ◽  
Jidong Gao ◽  
Heather D. Reeves
Keyword(s):  
Weather Prediction ◽  
Radar Data ◽  
Optimal Interpolation ◽  
Physical Parameters ◽  
Polarimetric Radar ◽  
Polarimetric Observation ◽  
Convective Scale ◽  
The Cost ◽  
Differential Reflectivity ◽  
Mass Volume

Abstract A variational retrieval of rain microphysics from polarimetric radar data (PRD) has been developed through the use of S-band parameterized polarimetric observation operators. Polarimetric observations allow for the optimal retrieval of cloud and precipitation microphysics for weather quantification and data assimilation for convective-scale numerical weather prediction (NWP) by linking PRD to physical parameters. Rain polarimetric observation operators for reflectivity ZH, differential reflectivity ZDR, and specific differential phase KDP were derived for S-band PRD using T-matrix scattering amplitudes. These observation operators link the PRD to the physical parameters of water content W and mass-/volume-weighted diameter Dm for rain, which can be used to calculate other microphysical information. The S-band observation operators were tested using a 1D variational retrieval that uses the (nonlinear) Gauss–Newton method to iteratively minimize the cost function to find an optimal estimate of Dm and W separately for each azimuth of radar data, which can be applied to a plan position indicator (PPI) radar scan (i.e., a single elevation). Experiments on two-dimensional video disdrometer (2DVD) data demonstrated the advantages of including ΦDP observations and using the nonlinear solution rather than the (linear) optimal interpolation (OI) solution. PRD collected by the Norman, Oklahoma (KOUN) WSR-88D on 15 June 2011 were used to successfully test the retrieval method on radar data. The successful variational retrieval from the 2DVD and the radar data demonstrate the utility of the proposed method.

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 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 From model to radar variables: a new forward polarimetric radar operator for COSMO

2018 ◽  
Vol 11 (7) ◽  
pp. 3883-3916 ◽  
Author(s):  
Daniel Wolfensberger ◽  
Alexis Berne
Keyword(s):  
Phase Shift ◽  
Solid Phase ◽  
Weather Prediction ◽  
Doppler Spectrum ◽  
Polarimetric Radar ◽  
Dual Frequency ◽  
Differential Phase Shift ◽  
Radar Observations ◽  
Differential Phase ◽  
Differential Reflectivity

Abstract. In this work, a new forward polarimetric radar operator for the COSMO numerical weather prediction (NWP) model is proposed. This operator is able to simulate measurements of radar reflectivity at horizontal polarization, differential reflectivity as well as specific differential phase shift and Doppler variables for ground based or spaceborne radar scans from atmospheric conditions simulated by COSMO. The operator includes a new Doppler scheme, which allows estimation of the full Doppler spectrum, as well a melting scheme which allows representing the very specific polarimetric signature of melting hydrometeors. In addition, the operator is adapted to both the operational one-moment microphysical scheme of COSMO and its more advanced two-moment scheme. The parameters of the relationships between the microphysical and scattering properties of the various hydrometeors are derived either from the literature or, in the case of graupel and aggregates, from observations collected in Switzerland. The operator is evaluated by comparing the simulated fields of radar observables with observations from the Swiss operational radar network, from a high resolution X-band research radar and from the dual-frequency precipitation radar of the Global Precipitation Measurement satellite (GPM-DPR). This evaluation shows that the operator is able to simulate an accurate Doppler spectrum and accurate radial velocities as well as realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the simulated differential reflectivity and specific differential phase shift upon propagation tend to be underestimated. This radar operator makes it possible to compare directly radar observations from various sources with COSMO simulations and as such is a valuable tool to evaluate and test the microphysical parameterizations of the model.

scholarly journals Polarimetric Tornadic Debris Signature Variability and Debris Fallout Signatures

2015 ◽  
Vol 54 (12) ◽  
pp. 2389-2405 ◽  
Author(s):  
Matthew S. Van Den Broeke
Keyword(s):  
Land Cover ◽  
Correlation Coefficient ◽  
Cross Correlation ◽  
Extreme Values ◽  
Life Cycles ◽  
Areal Extent ◽  
Polarimetric Radar ◽  
Horizontal Polarization ◽  
Differential Reflectivity ◽  
Relative Flow

AbstractValues of polarimetric radar variables may vary substantially between and through tornadic debris signature (TDS) events. Tornadoes with higher intensity ratings are associated with higher average and extreme values of reflectivity factor at horizontal polarization ZHH and lower values of copolar cross-correlation coefficient ρhv. Although values of these variables often fluctuate through reported tornado life cycles, ZHH repeatably decreases and ρhv repeatably increases across the volume scan immediately following reported tornado demise. Land cover has a relatively small effect on values of the polarimetric variables within TDSs, although near-radar urban TDSs may exhibit relatively high ZHH values. TDS areal extent is typically larger aloft than near the surface, although this trend may reverse in the most intense tornadoes. Maximum altitude to which a TDS is visible is more strongly a function of tornado intensity than of land cover or ambient shear and instability. Debris often disappears once lofted but may also be observed to spread out downstream with the storm-relative flow or to fall out along the parent storm’s northwest flank in a debris fallout signature (DFS). DFS characteristics, although variable, most commonly include ZHH values of 30–35 dBZ, ρhv values of 0.60–0.80, and values of differential reflectivity ZDR that are repeatably near 0 dB.

scholarly journals Asymmetric Radar Echo Patterns from Insects

2015 ◽  
Vol 32 (4) ◽  
pp. 659-674 ◽  
Author(s):  
Valery M. Melnikov ◽  
Michael J. Istok ◽  
John K. Westbrook
Keyword(s):  
Correlation Coefficient ◽  
Critical Role ◽  
Radar Data ◽  
Model Output ◽  
Differential Phase ◽  
Radar Echoes ◽  
Polarized Waves ◽  
Radar Echo ◽  
Differential Reflectivity

AbstractRadar echoes from insects, birds, and bats in the atmosphere exhibit both symmetry and asymmetry in polarimetric patterns. Symmetry refers to similar magnitudes of polarimetric variables at opposite azimuths, and asymmetry relegates to differences in these magnitudes. Asymmetry can be due to different species observed at different azimuths. It is shown in this study that when both polarized waves are transmitted simultaneously, asymmetric patterns can also be caused by insects of the same species that are oriented in the same direction. A model for scattering of simultaneously transmitted horizontally and vertically polarized radar waves by insects is developed. The model reproduces the main features of asymmetric patterns in differential reflectivity: the copolar correlation coefficient and the differential phase. The radar differential phase on transmit between horizontally and vertically polarized waves plays a critical role in the formations of the asymmetric patterns. The width-to-length ratios of insects’ bodies and their orientation angles are retrieved from matching the model output with radar data.

scholarly journals Autocorrelation and Cross-Correlation Estimators of Polarimetric Variables

2007 ◽  
Vol 24 (8) ◽  
pp. 1337-1350 ◽  
Author(s):  
Valery M. Melnikov ◽  
Dusan S. Zrnić
Keyword(s):  
Correlation Coefficient ◽  
Cross Correlation ◽  
Radar Data ◽  
Lower Sensitivity ◽  
Noise Levels ◽  
Low Snr ◽  
Interference Signals ◽  
Cross Correlations ◽  
Differential Reflectivity ◽  
Thermal Radiations

Abstract Herein are proposed novel estimators of differential reflectivity ZDR and correlation coefficient ρhv between horizontally and vertically polarized echoes. The estimators use autocorrelations and cross correlations of the returned signals to avoid bias by omnipresent but varying white noise. These estimators are considered for implementation on the future polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) network. On the current network the reflectivity factor is measured at signal-to-noise ratios (SNRs) as low as 2 dB and the same threshold is expected to hold for the polarimetric variables. At such low SNR and all the way up to SNR = 15 dB, the conventional estimators of differential reflectivity and the copolar correlation coefficient are prone to errors due to uncertainties in noise levels caused by instability of radar devices, thermal radiations of precipitation and the ground, and wideband radiation of electrically active clouds. Noise variations at SNR less than 15 dB can bias the estimates beyond apparatus accuracy. For brevity the authors refer to the estimators of ZDR and ρhv free from noise bias as the “1-lag estimators” because these are derived from 1-lag correlations. The estimators are quite robust and the only weak assumption for validity is that spectral widths of signals from vertically and horizontally polarized returns are equal. This assumption is verified on radar data. Radar observations demonstrate the validity of these estimator and lower sensitivity to interference signals than the conventional algorithms.

scholarly journals Rain microstructure retrievals using 2-D video disdrometer and C-band polarimetric radar

2009 ◽  
Vol 20 ◽  
pp. 13-18 ◽  
Author(s):  
M. Thurai ◽  
V. N. Bringi ◽  
W. A. Petersen
Keyword(s):  
Correlation Coefficient ◽  
Radar Data ◽  
Correction Method ◽  
Heavy Rainfall Event ◽  
Polarimetric Radar ◽  
Individual Drop ◽  
The Individual ◽  
Reflectivity Data ◽  
Differential Reflectivity ◽  
Polar Correlation

Abstract. Measurements using the 2-D video disdrometer (2DVD) taken during a heavy rainfall event in Huntsville, Alabama, are analysed. The 2DVD images were processed to derive the rain microstructure parameters for each individual drop, which in turn were used as input to the T-matrix method to compute the forward and back scatter amplitudes of each drop at C-band. The polarimetric radar variables were then calculated from the individual drop contribution over a finite time period, e.g., 1 min. The calculated co-polar reflectivity, differential reflectivity, specific differential propagation phase and the co-polar correlation coefficient were compared with measurements from a C-band polarimetric radar located 15 km away. An attenuation-correction method based on the specific differential propagation phase was applied to the co-polar and differential reflectivity data from the C-band radar, after ensuring accurate radar calibration. Time series comparisons of the parameters derived from the 2DVD and C-band radar data show very good agreement for all four quantities, the agreement being sometimes better than the computations using the 1-min drop size distribution and bulk assumptions on rain microstructure (such as mean shapes and model-based assumptions for drop orientation). The agreement is particularly improved in the case of co-polar correlation coefficient since this parameter is very sensitive to variation of shapes as well as orientation angles. The calculations mark the first attempt at utilizing experimentally derived "drop- by-drop" rain microstructure information to compute the radar polarimetric parameters and to demonstrate the value of utilizing the 2-D video disdrometer for studying rain microstructure under various precipitation conditions. Histograms of drop orientation angles as well as the most probable drop shapes and the corresponding variations were also derived and compared with prior results from the 80 m fall "artificial rain" experiment.

X-Band Polarimetric Observations of Cross Coupling in the Ice Phase of Convective Storms in Taiwan

2014 ◽  
Vol 53 (6) ◽  
pp. 1678-1695 ◽  
Author(s):  
J. C. Hubbert ◽  
S. M. Ellis ◽  
W.-Y. Chang ◽  
Y.-C. Liou
Keyword(s):  
Electric Fields ◽  
Cross Coupling ◽  
Radar Data ◽  
Ice Crystals ◽  
Polarimetric Radar ◽  
Differential Phase ◽  
X Band ◽  
Linear Depolarization Ratio ◽  
Differential Reflectivity ◽  
Ice Phase

AbstractIn this paper, experimental X-band polarimetric radar data from simultaneous transmission of horizontal (H) and vertical (V) polarizations (SHV) are shown, modeled, and microphysically interpreted. Both range–height indicator data and vertical-pointing X-band data from the Taiwan Experimental Atmospheric Mobile-Radar (TEAM-R) are presented. Some of the given X-band data are biased, which is very likely caused by cross coupling of the H and V transmitted waves as a result of aligned, canted ice crystals. Modeled SHV data are used to explain the observed polarimetric signatures. Coincident data from the National Center for Atmospheric Research S-band polarimetric radar (S-Pol) are presented to augment and support the X-band polarimetric observations and interpretations. The polarimetric S-Pol data are obtained via fast-alternating transmission of horizontal and vertical polarizations (FHV), and thus the S-band data are not contaminated by the cross coupling (except the linear depolarization ratio LDR) observed in the X-band data. The radar data reveal that there are regions in the ice phase where electric fields are apparently aligning ice crystals near vertically and thus causing negative specific differential phase Kdp. The vertical-pointing data also indicate the presence of preferentially aligned ice crystals that cause differential reflectivity Zdr and differential phase ϕdp to be strong functions of azimuth angle.

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