scholarly journals Constant Raindrop Fall Speed Profiles Derived from Doppler Radar Data Analyses for Steady Nonconvective Precipitation

2005 ◽  
Vol 62 (1) ◽  
pp. 220-230 ◽  
Author(s):  
Robert Nissen ◽  
Roland List ◽  
David Hudak ◽  
Greg M. McFarquhar ◽  
R. Paul Lawson ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Free Fall ◽  
Radar Data ◽  
Measuring System ◽  
Doppler Velocity ◽  
Light Rain ◽  
Fall Speed ◽  
Air Speed ◽  
Velocity Moments ◽  
Rain Rates

Abstract For nonconvective, steady light rain with rain rates <5 mm h−1 the mean Doppler velocity of raindrop spectra was found to be constant below the melting band, when the drop-free fall speed was adjusted for pressure. The Doppler radar–weighted raindrop diameters varied from case to case from 1.5 to 2.5 mm while rain rates changed from 1.2 to 2.9 mm h−1. Significant changes of advected velocity moments were observed over periods of 4 min. These findings were corroborated by three independent systems: a Doppler radar for establishing vertical air speed and mean terminal drop speeds [using extended Velocity Azimuth Display (EVAD) analyses], a Joss–Waldvogel disdrometer at the ground, and a Particle Measuring System (PMS) 2-DP probe flown on an aircraft. These measurements were supported by data from upper-air soundings. The reason why inferred raindrop spectra do not change with height is the negligible interaction rate between raindrops at low rain rates. At low rain rates, numerical box models of drop collisions strongly support this interpretation. It was found that increasing characteristic drop diameters are correlated with increasing rain rates.

A Variational Method for Filling in Missing Data in Doppler Velocity Fields

2021 ◽  
Author(s):  
VINCENT T. WOOD ◽  
ROBERT P. DAVIES-JONES ◽  
ALAN SHAPIRO
Keyword(s):  
Missing Data ◽  
Doppler Radar ◽  
Signal To Noise Ratio ◽  
Original Data ◽  
Radar Data ◽  
Velocity Fields ◽  
Doppler Velocity ◽  
Doppler Radar Data ◽  
Ground Clutter ◽  
Tornado Warnings

AbstractSingle-Doppler radar data are often missing in important regions of a severe storm due to low return power, low signal-to-noise ratio, ground clutter associated with normal and anomalous propagation, and missing radials associated with partial or total beam blockage. Missing data impact the ability of WSR-88D algorithms to detect severe weather. To aid the algorithms, we develop a variational technique that fills in Doppler velocity data voids smoothly by minimizing Doppler velocity gradients while not modifying good data. This method provides estimates of the analysed variable in data voids without creating extrema.Actual single-Doppler radar data of four tornadoes are used to demonstrate the variational algorithm. In two cases, data are missing in the original data, and in the other two, data are voided artificially. The filled-in data match the voided data well in smoothly varying Doppler velocity fields. Near singularities such as tornadic vortex signatures, the match is poor as anticipated. The algorithm does not create any velocity peaks in the former data voids, thus preventing false triggering of tornado warnings. Doppler circulation is used herein as a far-field tornado detection and advance-warning parameter. In almost all cases, the measured circulation is quite insensitive to the data that have been voided and then filled. The tornado threat is still apparent.

scholarly journals Improved rain-rate and drop-size retrievals from airborne and spaceborne Doppler radar

2017 ◽  
Author(s):  
Shannon L. Mason ◽  
J. Christine Chiu ◽  
Robin J. Hogan ◽  
Lin Tian
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Doppler Radar ◽  
Number Concentration ◽  
Doppler Velocity ◽  
Light Rain ◽  
Warm Rain ◽  
Rain Drop ◽  
Drop Number

Abstract. Satellite radar remote-sensing of rain is important for quantifying of the global hydrological cycle, atmospheric energy budget, and many microphysical cloud and precipitation processes; however, radar estimates of rain rate are sensitive to assumptions about the raindrop size distribution. The upcoming EarthCARE satellite will feature a 94-GHz Doppler radar alongside lidar and radiometer instruments, presenting opportunities for enhanced global retrievals of the rain drop size distribution. In this paper we demonstrate the capability to retrieve both rain rate and a parameter of the rain drop size distribution from an airborne 94-GHz Doppler radar using CAPTIVATE, the variational retrieval algorithm developed for EarthCARE radar–lidar synergy. For a range of rain regimes observed during the Tropical Composition, Cloud and Climate Coupling (TC4) field campaign in the eastern Pacific in 2007, we explore the contributions of Doppler velocity and path-integrated attenuation (PIA) to the retrievals, and evaluate the retrievals against independent measurements from a second, less attenuated, Doppler radar aboard the same aircraft. Retrieved drop number concentration varied over five orders of magnitude between light rain from melting ice, and warm rain from liquid clouds. Doppler velocity can be used to estimate rain rate over land, and retrievals of rain rate and drop number concentration are possible in profiles of light rain over land; in moderate warm rain, drop number concentration can be retrieved without Doppler velocity. These results suggest that EarthCARE rain retrievals facilitated by Doppler radar will make substantial improvements to the global understanding of the interaction of clouds and precipitation.

A Velocity Dealiasing Technique Using Rapidly Updated Analysis from a Four-Dimensional Variational Doppler Radar Data Assimilation System

2010 ◽  
Vol 27 (7) ◽  
pp. 1140-1152 ◽  
Author(s):  
Eunha Lim ◽  
Juanzhen Sun
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Radar Data ◽  
Objective Analysis ◽  
Doppler Velocity ◽  
Horizontal Shear ◽  
Data Assimilation System ◽  
Radar Data Assimilation ◽  
Assimilation System

Abstract A Doppler velocity dealiasing algorithm is developed within the storm-scale four-dimensional radar data assimilation system known as the Variational Doppler Radar Analysis System (VDRAS). The innovative aspect of the algorithm is that it dealiases Doppler velocity at each grid point independently by using three-dimensional wind fields obtained either from an objective analysis using conventional observations and mesoscale model output or from a rapidly updated analysis of VDRAS that assimilates radar data. This algorithm consists of three steps: preserving horizontal shear, global dealiasing using reference wind from the objective analysis or the VDRAS analysis, and local dealiasing. It is automated and intended to be used operationally for radar data assimilation using numerical weather prediction models. The algorithm was tested with 384 volumes of radar data observed from the Next Generation Weather Radar (NEXRAD) for a severe thunderstorm that occurred during 15 June 2002. It showed that the algorithm was effective in dealiasing large areas of aliased velocities when the wind from the objective analysis was used as the reference and that more accurate dealiasing was achieved by using the continuously cycled VDRAS analysis.

Assimilation of Doppler Radar Observations with a Regional 3DVAR System: Impact of Doppler Velocities on Forecasts of a Heavy Rainfall Case

2005 ◽  
Vol 44 (6) ◽  
pp. 768-788 ◽  
Author(s):  
Qingnong Xiao ◽  
Ying-Hwa Kuo ◽  
Juanzhen Sun ◽  
Wen-Chau Lee ◽  
Eunha Lim ◽  
...  
Keyword(s):  
Radial Velocity ◽  
Vertical Velocity ◽  
Short Range ◽  
Heavy Rainfall ◽  
Doppler Radar ◽  
Radar Data ◽  
Radial Velocities ◽  
Doppler Velocity ◽  
Rainfall Forecast ◽  
Background Fields

Abstract In this paper, the impact of Doppler radar radial velocity on the prediction of a heavy rainfall event is examined. The three-dimensional variational data assimilation (3DVAR) system for use with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is further developed to enable the assimilation of radial velocity observations. Doppler velocities from the Korean Jindo radar are assimilated into MM5 using the 3DVAR system for a heavy rainfall case that occurred on 10 June 2002. The results show that the assimilation of Doppler velocities has a positive impact on the short-range prediction of heavy rainfall. The dynamic balance between atmospheric wind and thermodynamic fields, based on the Richardson equation, is introduced to the 3DVAR system. Vertical velocity (w) increments are included in the 3DVAR system to enable the assimilation of the vertical velocity component of the Doppler radial velocity observation. The forecast of the hydrometeor variables of cloud water (qc) and rainwater (qr) is used in the 3DVAR background fields. The observation operator for Doppler radial velocity is developed and implemented within the 3DVAR system. A series of experiments, assimilating the Korean Jindo radar data for the 10 June 2002 heavy rainfall case, indicates that the scheme for Doppler velocity assimilation is stable and robust in a cycling mode making use of high-frequency radar data. The 3DVAR with assimilation of Doppler radial velocities is shown to improve the prediction of the rainband movement and intensity change. As a result, an improved skill for the short-range heavy rainfall forecast is obtained. The forecasts of other quantities, for example, winds, are also improved. Continuous assimilation with 3-h update cycles is important in producing an improved heavy rainfall forecast. Assimilation of Doppler radar radial velocities using the 3DVAR background fields from a cycling procedure produces skillful rainfall forecasts when verified against observations.

Clarifying remotely-retrieved precipitation of shallow marine clouds from the NSF/NCAR Gulfstream V

2021 ◽  
Author(s):  
Mampi Sarkar ◽  
Paquita Zuidema ◽  
Virendra Ghate
Keyword(s):  
Doppler Radar ◽  
Rain Attenuation ◽  
Doppler Velocity ◽  
Distribution Width ◽  
Raindrop Size Distribution ◽  
Remote Measurements ◽  
Raindrop Size ◽  
Rain Rates ◽  
The Impact

AbstractPrecipitation is a key process within the shallow cloud lifecycle. The Cloud System Evolution in the Trades (CSET) campaign included the first deployment of a 94 GHz Doppler radar and 532 nm lidar. Despite a larger sampling volume, initial mean radar/lidar retrieved rain rates (Schwartz et al. 2019) based on the upward-pointing remote sensor datasets are systematically less than those measured by in-situ precipitation probes in the cumulus regime. Subsequent retrieval improvements produce rainrates that compare better to in-situ values, but still underestimate. Retrieved shallow cumulus drop sizes can remain too small and too few, with an overestimated shape parameter narrowing the raindrop size distribution too much. Three potential causes for the discrepancy are explored: the gamma functional fit to the dropsize distribution, attenuation by rain and cloud water, and an underaccounting of Mie dampening of the reflectivity. A truncated exponential fit may represent the dropsizes below a showering cumulus cloud more realistically, although further work would be needed to fully evaluate the impact of a different dropsize representation upon the retrieval. The rain attenuation is within the measurement uncertainty of the radar. Mie dampening of the reflectivity is shown to be significant, in contrast to previous stratocumulus campaigns with lighter rain rates, and may be difficult to constrain well with the remote measurements. An alternative approach combines an a priori determination of the dropsize distribution width based on the in-situ data with the mean radar Doppler velocity and reflectivity. This can produce realistic retrievals, although a more comprehensive assessment is needed to better characterize the retrieval errors.

scholarly journals Use of Cloud Radar Doppler Spectra to Evaluate Stratocumulus Drizzle Size Distributions in Large-Eddy Simulations with Size-Resolved Microphysics

2017 ◽  
Vol 56 (12) ◽  
pp. 3263-3283 ◽  
Author(s):  
J. Rémillard ◽  
A. M. Fridlind ◽  
A. S. Ackerman ◽  
G. Tselioudis ◽  
P. Kollias ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Cloud Base ◽  
Doppler Velocity ◽  
Sharp Reduction ◽  
Cloud Radar ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Formation And Evolution ◽  
Bin Microphysics

AbstractA case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated with an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.

Finescale Vertical Structure of a Cold Front as Revealed by an Airborne Doppler Radar

2006 ◽  
Vol 134 (1) ◽  
pp. 251-271 ◽  
Author(s):  
Bart Geerts ◽  
Rick Damiani ◽  
Samuel Haimov
Keyword(s):  
Vertical Structure ◽  
Doppler Radar ◽  
Cold Front ◽  
Vertical Plane ◽  
Radar Data ◽  
Doppler Velocity ◽  
Density Current ◽  
Convective Boundary ◽  
Flight Level ◽  
Airborne Doppler Radar

Abstract In the afternoon of 24 May 2002, a well-defined and frontogenetic cold front moved through the Texas panhandle. Detailed observations from a series of platforms were collected near the triple point between this cold front and a dryline boundary. This paper primarily uses reflectivity and Doppler velocity data from an airborne 95-GHz radar, as well as flight-level thermodynamic data, to describe the vertical structure of the cold front as it intersected with the dryline. The prefrontal convective boundary layer was weakly capped, weakly sheared, and about 2.5 times deeper than the cold-frontal density current. The radar data depict the cold front as a fine example of an atmospheric density current at unprecedented detail (∼40 m). The echo structure and dual-Doppler-inferred airflow in the vertical plane reveal typical features such as a nose, a head, a rear-inflow current, and a broad current of rising prefrontal air that feeds the accelerating front-to-rear current over the head. The 2D cross-frontal structure, including the frontal slope, is highly variable in time or alongfront distance. Along this slope horizontal vorticity, averaging ∼0.05 s−1, is generated baroclinically, and the associated strong cross-front shear triggers Kelvin–Helmholtz (KH) billows at the density interface. Some KH billows occupy much of the depth of the density current, possibly even temporarily cutting off the head from its trailing body.

scholarly journals Doppler Radar Observations of Anticyclonic Tornadoes in Cyclonically Rotating, Right-Moving Supercells

2016 ◽  
Vol 144 (4) ◽  
pp. 1591-1616 ◽  
Author(s):  
Howard B. Bluestein ◽  
Michael M. French ◽  
Jeffrey C. Snyder ◽  
Jana B. Houser
Keyword(s):  
Case Studies ◽  
Doppler Radar ◽  
Environmental Parameters ◽  
Radar Data ◽  
Doppler Velocity ◽  
Weighted Mean ◽  
Radar Observations ◽  
Azimuthal Shear ◽  
The Right ◽  
Gust Front

Abstract Supercells dominated by mesocyclones, which tend to propagate to the right of the tropospheric pressure-weighted mean wind, on rare occasions produce anticyclonic tornadoes at the trailing end of the rear-flank gust front. More frequently, mesoanticyclones are found at this location, most of which do not spawn any tornadoes. In this paper, four cases are discussed in which the formation of anticyclonic tornadoes was documented in the plains by mobile or fixed-site Doppler radars. These brief case studies include the analysis of Doppler radar data for tornadoes at the following dates and locations: 1) 24 April 2006, near El Reno, Oklahoma; 2) 23 May 2008, near Ellis, Kansas; 3) 18 March 2012, near Willow, Oklahoma; and 4) 31 May 2013, near El Reno, Oklahoma. Three of these tornadoes were also documented photographically. In all of these cases, a strong mesocyclone (i.e., vortex signature characterized by azimuthal shear in excess of ~5 × 10−3 s−1 or a 20 m s−1 change in Doppler velocity over 5 km) or tornado was observed ~10 km away from the anticyclonic tornado. In three of these cases, the evolution of the tornadic vortex signature in time and height is described. Other features common to all cases are noted and possible mechanisms for anticyclonic tornadogenesis are identified. In addition, a set of estimated environmental parameters for these and other similar cases are discussed.

scholarly journals Single-Doppler Velocity Retrieval of the Wind Field in a Tornadic Supercell Using Mobile, Phased-Array, Doppler Radar Data

2018 ◽  
Vol 35 (8) ◽  
pp. 1649-1663 ◽  
Author(s):  
Yu-Chieng Liou ◽  
Howard B. Bluestein ◽  
Michael M. French ◽  
Zachary B. Wienhoff
Keyword(s):  
Temporal Resolution ◽  
Wind Field ◽  
Phased Array ◽  
Doppler Radar ◽  
Radar Data ◽  
Moving Frame ◽  
Doppler Velocity ◽  
High Temporal Resolution ◽  
Wind Component ◽  
Using Data

AbstractA three-dimensional data assimilation (3DVar) least squares–type single-Doppler velocity retrieval (SDVR) algorithm is utilized to retrieve the wind field of a tornadic supercell using data collected by a mobile, phased-array, Doppler radar [Mobile Weather Radar (MWR) 05XP] with very high temporal resolution (6 s). It is found that the cyclonic circulation in the hook-echo region can be successfully recovered by the SDVR algorithm. The quality of the SDVR analyses is evaluated by dual-Doppler syntheses using data collected by two mobile Doppler radars [Doppler on Wheels 6 and 7 (DOW6 and DOW7, respectively)]. A comparison between the SDVR analyses and dual-Doppler syntheses confirms the conclusion reached by an earlier theoretical analysis that because of the temporally discrete nature of the radar data, the wind speed retrieved by single-Doppler radar is always underestimated, and this underestimate occurs more significantly for the azimuthal (crossbeam) wind component than for the radial (along beam) component. However, the underestimate can be mitigated by increasing the radar data temporal resolution. When the radar data are collected at a sufficiently high rate, the azimuthal wind component may be overestimated. Even with data from a rapid scan, phased-array, Doppler radar, our study indicates that it is still necessary to calculate the SDVR in an optimal moving frame of reference. Finally, the SDVR algorithm’s robustness is demonstrated. Even with a temporal resolution (2 min) much lower than that of the phased-array radar, the cyclonic flow structure in the hook-echo region can still be retrieved through SDVR using data observed by DOW6 or DOW7, although a difference in the retrieved fields does exist. A further analysis indicates that this difference is caused by the location of the radars.

scholarly journals The Accuracy of Radar Estimates of Ice Terminal Fall Speed from Vertically Pointing Doppler Radar Measurements

2011 ◽  
Vol 50 (10) ◽  
pp. 2120-2138 ◽  
Author(s):  
Alain Protat ◽  
Christopher R. Williams
Keyword(s):  
Statistical Methods ◽  
Doppler Radar ◽  
Doppler Velocity ◽  
Air Velocity ◽  
Ice Clouds ◽  
Microphysical Properties ◽  
Radar Measurements ◽  
The Mean ◽  
Fall Speed ◽  
Two Parameters

AbstractDoppler radar measurements at different frequencies (50 and 2835 MHz) are used to characterize the terminal fall speed of hydrometeors and the vertical air motion in tropical ice clouds and to evaluate statistical methods for retrieving these two parameters using a single vertically pointing cloud radar. For the observed vertical air motions, it is found that the mean vertical air velocity in ice clouds is small on average, as is assumed in terminal fall speed retrieval methods. The mean vertical air motions are slightly negative (downdraft) between the melting layer (5-km height) and 6.3-km height, and positive (updraft) above this altitude, with two peaks of 6 and 7 cm s−1 at 7.7- and 9.7-km height. For the retrieved hydrometeor terminal fall speeds, it is found that the variability of terminal fall speeds within narrow reflectivity ranges is typically within the acceptable uncertainties for using terminal fall speeds in ice cloud microphysical retrievals. This study also evaluates the performance of previously published statistical methods of separating terminal fall speed and vertical air velocity from vertically pointing Doppler radar measurements using the 50-/2835-MHz radar retrievals as a reference. It is found that the variability of the terminal fall speed–radar reflectivity relationship (Vt–Ze) is large in ice clouds and cannot be parameterized accurately with a single relationship. A well-defined linear relationship is found between the two coefficients of a power-law Vt–Ze relationship, but a more accurate microphysical retrieval is obtained using Doppler velocity measurements to better constrain the Vt–Ze relationship for each cloud. When comparing the different statistical methods to the reference, the distribution of terminal fall speed residual is wide, with most residuals being in the ±30–40 cm s−1 range about the mean. The typical mean residual ranged from 15 to 20 cm s−1, with different methods having mean residuals of <10 cm s−1 at some heights, but not at the same heights for all methods. The so-called Vt–Ze technique was the most accurate above 9-km height, and the running-mean technique outperformed the other techniques below 9-km height. Sensitivity tests of the running-mean technique indicate that the 20-min average is the best trade-off for the type of ice clouds considered in this analysis. A new technique is proposed that incorporates simple averages of Doppler velocity for each (Ze, H) couple in a given cloud. This technique, referred to as DOP–Ze–H, was found to outperform the three other methods at most heights, with a mean terminal fall residual of <10 cm s−1 at all heights. This error magnitude is compatible with the use of such retrieved terminal fall speeds for the retrieval of microphysical properties.

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