scholarly journals Simulation of X-Band Rainfall Observations from S-Band Radar Data

2006 ◽  
Vol 23 (9) ◽  
pp. 1195-1205 ◽  
Author(s):  
V. Chandrasekar ◽  
S. Lim ◽  
E. Gorgucci
Keyword(s):  
Doppler Radar ◽  
Theoretical Models ◽  
Radar Data ◽  
Shape Distribution ◽  
Microphysical Properties ◽  
Rain Medium ◽  
Microphysical Parameters ◽  
X Band ◽  
State Water ◽  
The Impact

Abstract To design X-band radar systems as well as evaluate algorithm development, it is useful to have simultaneous X-band observation with and without the impact of path attenuation. One way to develop that dataset is through theoretical models. This paper presents a methodology to generate realistic range profiles of radar variables at attenuating frequencies, such as X band, for rain medium. Fundamental microphysical properties of precipitation, namely, size and shape distribution information, are used to generate realistic profiles of X band starting with S-band observation. Conditioning the simulation from S band maintains the natural distribution of rainfall microphysical parameters. Data from the Colorado State University’s University of Chicago–Illinois State Water Survey (CHILL) radar and the National Center for Atmospheric Research S-band dual-polarization Doppler radar (S-POL) are used to simulate X-band radar variables. Three procedures to simulate the radar variables and sample applications are presented.

The Multiple-Vortex Structure of the El Reno, Oklahoma, Tornado on 31 May 2013

2018 ◽  
Vol 146 (8) ◽  
pp. 2483-2502 ◽  
Author(s):  
Howard B. Bluestein ◽  
Kyle J. Thiem ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Rapid Scan ◽  
X Band ◽  
Close Range ◽  
Formation And Evolution ◽  
Using Data ◽  
Secondary Vortices ◽  
The Right ◽  
Gust Front

Abstract This study documents the formation and evolution of secondary vortices associated within a large, violent tornado in Oklahoma based on data from a close-range, mobile, polarimetric, rapid-scan, X-band Doppler radar. Secondary vortices were tracked relative to the parent circulation using data collected every 2 s. It was found that most long-lived vortices (those that could be tracked for ≥15 s) formed within the radius of maximum wind (RMW), mainly in the left-rear quadrant (with respect to parent tornado motion), passing around the center of the parent tornado and dissipating closer to the center in the right-forward and left-forward quadrants. Some secondary vortices persisted for at least 1 min. When a Burgers–Rott vortex is fit to the Doppler radar data, and the vortex is assumed to be axisymmetric, the secondary vortices propagated slowly against the mean azimuthal flow; if the vortex is not assumed to be axisymmetric as a result of a strong rear-flank gust front on one side of it, then the secondary vortices moved along approximately with the wind.

scholarly journals Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model

2013 ◽  
Vol 2013 ◽  
pp. 1-18
Author(s):  
Edward Natenberg ◽  
Jidong Gao ◽  
Ming Xue ◽  
Frederick H. Carr
Keyword(s):  
Doppler Radar ◽  
Initial Conditions ◽  
Three Dimensional ◽  
Radar Data ◽  
Advanced Regional Prediction System ◽  
Regional Prediction ◽  
Upper Level ◽  
Using Data ◽  
Nwp Model ◽  
The Impact

A three-dimensional variational (3DVAR) assimilation technique developed for a convective-scale NWP model—advanced regional prediction system (ARPS)—is used to analyze the 8 May 2003, Moore/Midwest City, Oklahoma tornadic supercell thunderstorm. Previous studies on this case used only one or two radars that are very close to this storm. However, three other radars observed the upper-level part of the storm. Because these three radars are located far away from the targeted storm, they were overlooked by previous studies. High-frequency intermittent 3DVAR analyses are performed using the data from five radars that together provide a more complete picture of this storm. The analyses capture a well-defined mesocyclone in the midlevels and the wind circulation associated with a hook-shaped echo. The analyses produced through this technique are used as initial conditions for a 40-minute storm-scale forecast. The impact of multiple radars on a short-term NWP forecast is most evident when compared to forecasts using data from only one and two radars. The use of all radars provides the best forecast in which a strong low-level mesocyclone develops and tracks in close proximity to the actual tornado damage path.

Investigation on Spin-Stabilized Projectile Trajectory Observability Based on Flight Stability

2014 ◽  
Vol 530-531 ◽  
pp. 175-180 ◽  
Author(s):  
Mostafa Khalil ◽  
Xiao Ting Rui ◽  
Qi Cheng Zha ◽  
Hossam Hendy
Keyword(s):  
Doppler Radar ◽  
Numerical Study ◽  
Radar Data ◽  
Angular Motion ◽  
Impact Point ◽  
3D Tracking ◽  
Flight Stability ◽  
Doppler Radar Data ◽  
Six Degree Of Freedom ◽  
The Impact

To accurately estimate the projectile ballistic trajectory, where the real impact point can not be identified in case of indirect firing, a 3D tracking radar with Doppler is used during the first portion of projectile trajectory to estimate the projectile attitude and angular motion during flight, and hence; compute the impact point using a nonlinear six-degree-of-freedom 6-DOF trajectory model. A numerical study is done to investigate the effect of the flight stability of a 105mm artillery projectile on the length of Doppler radar data needed to accurately estimate the projectile impact point. A discrete time transfer matrix method DTTM-4DOF is used to estimate the in-flight projectile angular motion using Doppler radar measurements. Simulated Doppler radar data are generated using the 6-DOF model including the projectile initial disturbance problem.

Improved Prediction of Landfalling Tropical Cyclone in China Based on Assimilation of Radar Radial Winds with New Super-Observation Processing

2020 ◽  
Vol 35 (6) ◽  
pp. 2523-2539
Author(s):  
Jianing Feng ◽  
Yihong Duan ◽  
Qilin Wan ◽  
Hao Hu ◽  
Zhaoxia Pu
Keyword(s):  
Data Assimilation ◽  
Inner Core ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Numerical Weather Prediction Model ◽  
Previous Method ◽  
Horizontal Wind ◽  
The Impact

AbstractThis work explores the impact of assimilating radial winds from the Chinese coastal Doppler radar on track, intensity, and quantitative precipitation forecasts (QPF) of landfalling tropical cyclones (TCs) in a numerical weather prediction model, focusing mainly on two aspects: 1) developing a new coastal radar super-observation (SO) processing method, namely, an evenly spaced thinning method (ESTM) that is fit for landfalling TCs, and 2) evaluating the performance of the radar radial wind data assimilation in QPFs of landfalling TCs with multiple TC cases. Compared to a previous method of generating SOs (i.e., the radially spaced thinning method), in which the density of SOs is equal within the radial space of a radar scanning volume, the SOs created by ESTM are almost evenly distributed in the horizontal grids of the model background, resulting in more observations located in the TC inner-core region being involved in SOs. The use of SOs from ESTM leads to more cyclonic wind innovation, and larger analysis increments of height and horizontal wind in the lower level in an ensemble Kalman filter data assimilation experiment with TC Mujigae (2015). Overall, forecasts of a TC’s landfalling position, intensity, and QPF are improved by radar data assimilation for all cases, including Mujigae and the other eight TCs that made landfall on the Chinese mainland in 2017. Specifically, through assimilation, TC landing position error and intensity error are reduced by 33% and 25%, respectively. The mean equitable threat score of extreme rainfall [>80 mm (3 h)−1] forecasts is doubled on average over all cases.

scholarly journals Multiple-Radar Data Assimilation and Short-Range Quantitative Precipitation Forecasting of a Squall Line Observed during IHOP_2002

2007 ◽  
Vol 135 (10) ◽  
pp. 3381-3404 ◽  
Author(s):  
Qingnong Xiao ◽  
Juanzhen Sun
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Doppler Radar ◽  
Radar Data ◽  
Squall Line ◽  
Convective System ◽  
Precipitation Forecasting ◽  
Doppler Radar Data ◽  
The Impact ◽  
Radar Data Assimilation

Abstract The impact of multiple–Doppler radar data assimilation on quantitative precipitation forecasting (QPF) is examined in this study. The newly developed Weather Research and Forecasting (WRF) model Advanced Research WRF (ARW) and its three-dimensional variational data assimilation system (WRF 3DVAR) are used. In this study, multiple–Doppler radar data assimilation is applied in WRF 3DVAR cycling mode to initialize a squall-line convective system on 13 June 2002 during the International H2O Project (IHOP_2002) and the ARW QPF skills are evaluated for the case. Numerical experiments demonstrate that WRF 3DVAR can successfully assimilate Doppler radial velocity and reflectivity from multiple radar sites and extract useful information from the radar data to initiate the squall-line convective system. Assimilation of both radial velocity and reflectivity results in sound analyses that show adjustments in both the dynamical and thermodynamical fields that are consistent with the WRF 3DVAR balance constraint and background error correlation. The cycling of the Doppler radar data from the 12 radar sites at 2100 UTC 12 June and 0000 UTC 13 June produces a more detailed mesoscale structure of the squall-line convection in the model initial conditions at 0000 UTC 13 June. Evaluations of the ARW QPF skills with initialization via Doppler radar data assimilation demonstrate that the more radar data in the temporal and spatial dimensions are assimilated, the more positive is the impact on the QPF skill. Assimilation of both radial velocity and reflectivity has more positive impact on the QPF skill than does assimilation of either radial velocity or reflectivity only. The improvement of the QPF skill with multiple-radar data assimilation is more clearly observed in heavy rainfall than in light rainfall. In addition to the improvement of the QPF skill, the simulated structure of the squall line is also enhanced by the multiple–Doppler radar data assimilation in the WRF 3DVAR cycling experiment. The vertical airflow pattern shows typical characteristics of squall-line convection. The cold pool and its related squall-line convection triggering process are better initiated in the WRF 3DVAR analysis and simulated in the ARW forecast when multiple–Doppler radar data are assimilated.

scholarly journals Impact of the Dual-Polarization Doppler Radar Data on Two Convective Storms with a Warm-Rain Radar Forward Operator

2012 ◽  
Vol 140 (7) ◽  
pp. 2147-2167 ◽  
Author(s):  
Xuanli Li ◽  
John R. Mecikalski
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Radar Data ◽  
Dual Polarization ◽  
Convective Storms ◽  
Warm Rain ◽  
Mesoscale Convective ◽  
Differential Reflectivity ◽  
The Impact

Abstract The dual-polarization (dual pol) Doppler radar can transmit/receive both horizontally and vertically polarized power returns. The dual-pol radar measurements have been shown to provide a more accurate precipitation estimate compared to traditional radars. In this study, the horizontal reflectivity ZH, differential reflectivity ZDR, specific differential phase KDP, and radial velocity VR collected by the C-band Advanced Radar for Meteorological and Operational Research (ARMOR) are assimilated for two convective storms. A warm-rain scheme is constructed to assimilate ZH, ZDR, and KDP data using the three-dimensional variational data assimilation (3DVAR) system with the Advanced Research Weather Research and Forecasting Model (ARW-WRF). The main goals of this study are first to demonstrate and compare the impact of various dual-pol variables in initialization of real case convective storms and second to test how the dual-pol fields may be better used with a 3DVAR system. The results show that the ZH, ZDR, KDP, and VR data substantially improve the initial condition for two mesoscale convective storms. Significant positive impacts on short-term forecast are obtained for both storms. Additionally, KDP and ZDR data assimilation is shown to be superior to ZH and ZDR and ZH-only data assimilation when the warm-rain microphysics is adopted. With the ongoing upgrade of the current Weather Surveillance Radar-1988 Doppler (WSR-88D) network to include dual-pol capabilities (started in early 2011), the findings from this study can be a helpful reference for utilizing the dual-pol radar data in numerical simulations of severe weather and related quantitative precipitation forecasts.

scholarly journals Retrieval of Reflectivity in a Networked Radar Environment

2008 ◽  
Vol 25 (10) ◽  
pp. 1755-1767 ◽  
Author(s):  
V. Chandrasekar ◽  
S. Lim
Keyword(s):  
Electromagnetic Waves ◽  
State University ◽  
Colorado State University ◽  
Adaptive Sensing ◽  
Specific Attenuation ◽  
Rain Medium ◽  
X Band ◽  
State Water ◽  
Networked Radar ◽  
Using Data

Abstract A system for reflectivity and attenuation retrieval for rain medium in a networked radar environment is described. Electromagnetic waves backscattered from a common volume in networked radar systems are attenuated differently along the different paths. A solution for the specific attenuation distribution is proposed by solving the integral equation for reflectivity and attenuation. The set of governing integral equations describing the backscatter and propagation of common resolution volume are solved simultaneously with constraints on total path attenuation. The proposed algorithm is evaluated based on simulated X-band radar observations synthesized from S-band measurements collected by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar. Retrieved reflectivity and specific attenuation using the proposed method show good agreement with simulated reflectivity and specific attenuation. Preliminary demonstration of the network-based retrieval using data from the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) IP-1 radar network are also presented.

Automatic detection of volcanic eruptions in Doppler radar observations using a neural network approach

2020 ◽  
Author(s):  
Matthias Hort ◽  
Daniel Uhle ◽  
Fabio Venegas ◽  
Lea Scharff ◽  
Jan Walda ◽  
...  
Keyword(s):  
Neural Network ◽  
Doppler Radar ◽  
Volcanic Eruptions ◽  
Radar Data ◽  
Visual Observation ◽  
Data Sets ◽  
Network Approach ◽  
Neural Network Approach ◽  
Data Set ◽  
The Impact

<p>Immediate detection of volcanic eruptions is essential when trying to mitigate the impact on the health of people living in the vicinity of a volcano or the impact on infrastructure and aviation. Eruption detection is most often done by either visual observation or the analysis of acoustic data. While visual observation is often difficult due to environmental conditions, infrasound data usually provide the onset of an event. Doppler radar data, admittedly not available for a lot of volcanoes, however, provide information on the dynamics of the eruption and the amount of material released. Eruptions can be easily detected in the data by visual analysis and here we present a neural network approach for the automatic detection of eruptions in Doppler radar data. We use data recorded at Colima volcano in Mexico in 2014/2015 and a data set recorded at Turrialba volcano between 2017 and 2019. In a first step we picked eruptions, rain and typical noise in both data sets, which were the used for training two networks (training data set) and testing the performance of the network using a separate test data set. The accuracy for classifying the different type of signals was between 95 and 98% for both data sets, which we consider quite successful. In case of the Turriabla data set eruptions were picked based on observations of OVSICORI data. When classifying the complete data set we have from Turriabla using the trained network, an additional 40 eruptions were found, which were not in the OVSICORI catalogue.</p><p>In most cases data from the instruments are transmitted to an observatory by radio, so the amount of data available is an issue. We therefore tested by what amount the data could be reduced to still be able to successfully detect an eruption. We also kept the network as small as possible to ideally run it on a small computer (e.g. a Rasberry Pi architecture) for eruption detection on site, so only the information that an eruption is detected needs to be transmitted.</p>

scholarly journals Evaluation of Operational and Experimental Precipitation Algorithms and Microphysical Insights during IPHEx

2018 ◽  
Vol 19 (1) ◽  
pp. 113-125 ◽  
Author(s):  
Jessica M. Erlingis ◽  
Jonathan J. Gourley ◽  
Pierre-Emmanuel Kirstetter ◽  
Emmanouil N. Anagnostou ◽  
John Kalogiros ◽  
...  
Keyword(s):  
Radar Data ◽  
Great Smoky Mountains ◽  
Rain Gauges ◽  
Microphysical Parameters ◽  
X Band ◽  
Smoky Mountains ◽  
Precipitation Estimates ◽  
Intensive Observation ◽  
Microphysical Processes ◽  
Observation Period

Abstract During May and June 2014, NOAA X-Pol (NOXP), the National Severe Storms Laboratory’s dual-polarized X-band mobile radar, was deployed to the Pigeon River basin in the Great Smoky Mountains of North Carolina as part of the NASA Integrated Precipitation and Hydrology Experiment. Rain gauges and disdrometers were positioned within the basin to verify precipitation estimates from various radar and satellite precipitation algorithms. First, the performance of the Self-Consistent Optimal Parameterization–Microphysics Estimation (SCOP-ME) algorithm for NOXP was examined using ground instrumentation as validation and was found to perform similarly to or slightly outperform other precipitation algorithms over the course of the intensive observation period (IOP). Radar data were also used to examine ridge–valley differences in radar and microphysical parameters for a case of stratiform precipitation passing over the mountains. Inferred coalescence microphysical processes were found to dominate within the upslope region, while a combination of processes were present as the system propagated over the valley. This suggests that enhanced updrafts aided by orographic lift sustain convection over the upslope regions, leading to larger median drop diameters.

scholarly journals Wideband Reception and Processing for Dual-Polarization Radars with Dual Transmitters

2007 ◽  
Vol 24 (1) ◽  
pp. 95-101 ◽  
Author(s):  
Sutanay Choudhury ◽  
V. Chandrasekar
Keyword(s):  
Doppler Radar ◽  
Negative Impact ◽  
Spectral Width ◽  
Parameter Estimates ◽  
Dual Polarization ◽  
Mean Velocity ◽  
Colorado State University ◽  
State Water ◽  
Differential Reflectivity ◽  
The Impact

Abstract Oversampling pulsed Doppler radar returns at a rate larger than the pulse bandwidth, whitening the range samples, and subsequent averaging has been pursued as a potential way to decrease the measured standard deviation of signal parameter estimates. It has been shown that the application of oversampling, whitening, and subsequent averaging improves the quality of reflectivity, mean velocity, and spectral width estimates in agreement with theory. Application of this procedure to a dual-polarization radar with dual transmitters is evaluated in this paper. Oversampled data collected from the Colorado State University (CSU)-University of Chicago–Illinois State Water Survey (CHILL) radar using a wideband receiver are analyzed to evaluate the performance of dual-polarization parameter estimators, such as differential reflectivity and differential phase. The negative impact of relative phase characteristics of the transmitted pulses in two polarizations on the copolar correlation, and subsequently on polarimetric parameter estimation, is analyzed. CSU-CHILL radar’s transmitted pulse sampling capability is used to evaluate the impact of the transmitted waveform’s mismatch on whitening and estimation.

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