Assessing the Errors of Cloud Liquid Water and Precipitation Flux Retrievals in Marine Stratocumulus Based on Doppler Radar Parameters

2007 ◽  
Vol 8 (4) ◽  
pp. 665-677 ◽  
Author(s):  
Yefim L. Kogan ◽  
Zena N. Kogan ◽  
David B. Mechem
Keyword(s):  
Liquid Water ◽  
Doppler Radar ◽  
Radar Reflectivity ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Cloud Liquid Water ◽  
Eddy Simulation ◽  
Air Turbulence ◽  
Spectrum Width ◽  
Drop Size Distributions

Abstract The errors of formulations of cloud retrievals based on radar reflectivity, mean Doppler velocity, and Doppler spectrum width are evaluated under the controlled framework of the Observing System Simulation Experiments (OSSEs). Cloud radar parameters are obtained from drop size distributions generated by the high-resolution Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) large-eddy simulation (LES) model with explicit microphysics. It is shown that in drizzling stratocumulus the accuracy of cloud liquid water (Ql) retrieval can be substantially increased when information on Doppler velocity or Doppler spectrum width is included in addition to radar reflectivity. In the moderate drizzle case (drizzle rate R of about 1 mm day−1) the mean and standard deviation of errors is of the order of 10% for Ql values larger than 0.2 g m−3; in stratocumulus with heavy drizzle (R > 2 mm day−1) these values are approximately 20%–30%. Similarly, employing Doppler radar parameters significantly improves the accuracy of drizzle flux retrieval. The use of Doppler spectrum width σd instead of Doppler velocity yields about the same accuracy, thus demonstrating that both Doppler parameters have approximately the same potential for improving microphysical retrievals. It is noted that the error estimates herein represent the theoretical lower bound on retrieval errors, because the actual errors will inevitably increase, first and foremost, due to uncertainties in estimation contributions from air turbulence.

scholarly journals Mobile Ka-band Polarimetric Doppler Radar Observations of Wildfire Smoke Plumes

2021 ◽  
Author(s):  
Taylor B. Aydell ◽  
Craig B. Clements
Keyword(s):  
Radial Velocity ◽  
Doppler Radar ◽  
Radar Reflectivity ◽  
Doppler Spectrum ◽  
Fine Scale ◽  
Prescribed Burn ◽  
Ka Band ◽  
Wildfire Smoke ◽  
Smoke Plumes ◽  
Spectrum Width

AbstractRemote sensing techniques have been used to study and track wildfire smoke plume structure and evolution, however knowledge gaps remain due to the limited availability of observational datasets aimed at understanding fine-scale fire-atmosphere interactions and plume microphysics. While meteorological radars have been used to investigate the evolution of plume rise in time and space, highly resolved plume observations are limited. In this study, we present a new mobile millimeter-wave (Ka-band) Doppler radar system acquired to sample the fine-scale kinematics and microphysical properties of active wildfire smoke plumes from both wildfires and large prescribed fires. Four field deployments were conducted in the fall of 2019 during two wildfires in California and one prescribed burn in Utah. Radar parameters investigated in this study include reflectivity, radial velocity, Doppler spectrum width, Differential Reflectivity (ZDR), and copolarized correlation coefficients (ρHV). Observed radar reflectivity ranged between -15 and 20 dBZ in plume and radial velocity ranged 0 to 16 m s-1. Dual-polarimetric observations revealed that scattering sources within wildfire plumes are primarily nonspherical and oblate shaped targets as indicated by ZDR values measuring above 0 and ρHV values below 0.8 within the plume. Doppler spectrum width maxima were located near the updraft core region and were associated with radar reflectivity maxima.

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.

scholarly journals Can liquid cloud microphysical processes be used for vertically pointing cloud radar calibration?

2019 ◽  
Vol 12 (6) ◽  
pp. 3151-3171 ◽  
Author(s):  
Maximilian Maahn ◽  
Fabian Hoffmann ◽  
Matthew D. Shupe ◽  
Gijs de Boer ◽  
Sergey Y. Matrosov ◽  
...  
Keyword(s):  
Radar Data ◽  
Reference Points ◽  
Radar Reflectivity ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Liquid Water Path ◽  
Cloud Radar ◽  
Microphysical Processes ◽  
Radar Calibration ◽  
Sudden Decrease

Abstract. Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Thus far, no single robust method exists for assessing the calibration of past cloud radar data sets. Here, we investigate whether observations of microphysical processes in liquid clouds such as the transition of cloud droplets to drizzle drops can be used to calibrate cloud radars. Specifically, we study the relationships between the radar reflectivity factor and three variables not affected by absolute radar calibration: the skewness of the radar Doppler spectrum (γ), the radar mean Doppler velocity (W), and the liquid water path (LWP). For each relation, we evaluate the potential for radar calibration. For γ and W, we use box model simulations to determine typical radar reflectivity values for reference points. We apply the new methods to observations at the Atmospheric Radiation Measurement (ARM) sites North Slope of Alaska (NSA) and Oliktok Point (OLI) in 2016 using two 35 GHz Ka-band ARM Zenith Radars (KAZR). For periods with a sufficient number of liquid cloud observations, we find that liquid cloud processes are robust enough for cloud radar calibration, with the LWP-based method performing best. We estimate that, in 2016, the radar reflectivity at NSA was about 1±1 dB too low but stable. For OLI, we identify serious problems with maintaining an accurate calibration including a sudden decrease of 5 to 7 dB in June 2016.

scholarly journals A Doppler Radar Emulator with an Application to the Detectability of Tornadic Signatures

2007 ◽  
Vol 24 (12) ◽  
pp. 1973-1996 ◽  
Author(s):  
Ryan M. May ◽  
Michael I. Biggerstaff ◽  
Ming Xue
Keyword(s):  
Pulse Propagation ◽  
Doppler Radar ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Advanced Regional Prediction System ◽  
Adaptive Sensing ◽  
Regional Prediction ◽  
Sampling Intervals ◽  
Half Power ◽  
The Impact

Abstract A Doppler radar emulator was developed to simulate the expected mean returns from scanning radar, including pulse-to-pulse variability associated with changes in viewing angle and atmospheric structure. Based on the user’s configuration, the emulator samples the numerical simulation output to produce simulated returned power, equivalent radar reflectivity, Doppler velocity, and Doppler spectrum width. The emulator is used to evaluate the impact of azimuthal over- and undersampling, gate spacing, velocity and range aliasing, antenna beamwidth and sidelobes, nonstandard (anomalous) pulse propagation, and wavelength-dependent Rayleigh attenuation on features of interest. As an example, the emulator is used to evaluate the detection of the circulation associated with a tornado simulated within a supercell thunderstorm by the Advanced Regional Prediction System (ARPS). Several metrics for tornado intensity are examined, including peak Doppler velocity and axisymmetric vorticity, to determine the degradation of the tornadic signature as a function of range and azimuthal sampling intervals. For the case of a 2° half-power beamwidth radar, like those deployed in the first integrated project of the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA), the detection of the cyclonic shear associated with this simulated tornado will be difficult beyond the 10-km range, if standard metrics such as azimuthal gate-to-gate shear from a single radar are used for detection.

scholarly journals Can liquid cloud microphysical processes be used for vertically-pointing cloud radar calibration?

2019 ◽  
Author(s):  
Maximilian Maahn ◽  
Fabian Hoffmann ◽  
Matthew D. Shupe ◽  
Gijs de Boer ◽  
Sergey Y. Matrosov ◽  
...  
Keyword(s):  
Radar Data ◽  
Reference Points ◽  
Radar Reflectivity ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Liquid Water Path ◽  
Cloud Radar ◽  
Microphysical Processes ◽  
Radar Calibration ◽  
Sudden Decrease

Abstract. Cloud radars are unique instruments for observing cloud processes, but uncertainties in radar calibration have frequently limited data quality. Thus far, no single, robust method exists for assessing calibration of past cloud radar data sets. Here, we investigate whether observations of microphysical processes of liquid clouds such as the transition of cloud droplets to drizzle drops can be used to calibrate cloud radars. Specifically, we study the relationships between the radar reflectivity factor and three variables not affected by absolute radar calibration: the skewness of the radar Doppler spectrum (γ), the radar mean Doppler velocity (W), and the liquid water path (LWP). We identify reference points of these relationships and evaluate their potential for radar calibration. For γ and W, we use box model simulations to determine typical radar reflectivity values for these reference points. We apply the new methods to observations at the Atmospheric Radiation Measurement (ARM) sites North Slope of Alaska (NSA) and Oliktok Point (OLI) in 2016 using two 35 GHz Ka-band ARM Zenith Radars (KAZR). For periods with a sufficient number of liquid cloud observations, we find that the methods are robust enough for cloud radar calibration, with the LWP-based method performing best. We estimate that in 2016, the radar reflectivity at NSA was about 1 ± 1 dB too low, but stable. For OLI, we identify serious problems with maintaining an accurate calibration including a sudden decrease of 5 to 7 dB in June 2016.

Ku-Band High-Speed Scanning Doppler Radar for Volcanic Eruption Monitoring

2019 ◽  
Vol 14 (4) ◽  
pp. 630-640
Author(s):  
Masayuki Maki ◽  
Shinobu Takahashi ◽  
Sumiya Okada ◽  
Katsuyuki Imai ◽  
Hiroshi Yamaguchi ◽  
...  
Keyword(s):  
Volcanic Eruption ◽  
High Speed ◽  
Doppler Radar ◽  
Volcanic Eruptions ◽  
Radio Station ◽  
Japan Meteorological Agency ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Eruption Column ◽  
Ku Band

This paper presents the major specifications and characteristics of the Ku-band high-speed scanning Doppler radar for volcano observation (KuRAD) introduced to Kagoshima University in March 2017 as well as the results of a test observation at Sakurajima. KuRAD is a Doppler radar for research with a wavelength of approximately 2 cm and uses a 45 cm diameter Luneberg lens antenna as a transmitting and receiving antenna to observe the development of a volcanic eruption column immediately following eruption at a maximum rotation speed of 40 rpm. The maximum transmitter power is 9.6 W and the maximum observational range is 20 km. Observed data includes radar reflectivity factor, Doppler velocity, and Doppler spectrum width. Another feature of KuRAD is an obtained radio station license for observation of a total of seven active volcanos in Kyushu. To assess the basic performance of KuRAD, we carried out test observations of volcanic eruptions at Sakurajima, Kagoshima Prefecture, Japan and collected a total of 87 eruptions (20 of which are explosive eruptions and 7 of which had 3,000 m or higher eruptive smoke from vents). From the eruption data of Showa vent on May 2, 2017, it was confirmed that KuRAD could monitor the three-dimensional internal structure of a volcanic eruption column immediately following eruption. Eruption data from Minamidake of Sakurajima on March 5, 2018, showed that KuRAD successfully observed the eruptive smoke reaching a height of 4,000 m, although the eruptive smoke was covered with clouds and could not be detected by optical instruments of the Japan Meteorological Agency.

Numerical Evaluation of Observation Algorithm for Sea Surface Remote Sensing by Doppler Radar

2011 ◽  
Author(s):  
Takero Yoshida ◽  
Chang-Kyu Rheem
Keyword(s):  
Remote Sensing ◽  
Fourier Transform ◽  
Microwave Irradiation ◽  
Frequency Analysis ◽  
Doppler Radar ◽  
Sea Surface ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
Regular Wave ◽  
The Fourier Transform

Algorithms of sea surface remote sensing are based on changes of Doppler shifts, which are measured by a Doppler radar. Microwave irradiation width on the sea surface and time taken to collect data for frequency analysis influence Doppler spectra. In order to evaluate the influences of these parameters in observing algorithms, a simulation of microwave backscattering from numerical sea surface was done in time domain to obtain Doppler spectra. Doppler spectra have been simulated in the case of various numerical regular waves. In the case of the microwave irradiation width is larger than the wavelength of the numerical regular wave or the Fourier transform time for the frequency analysis is longer than the period of the numerical regular wave, the peak value of Doppler spectra shows the phase velocity of the Bragg resonance wave. The results show the principle of measuring sea surface current. In the case of the microwave irradiation width is smaller than the wavelength of the numerical regular wave or the Fourier transform time is shorter than the period of the numerical regular wave, Doppler spectra vary with the orbital motions of the regular wave. As the result, when the sea surface wavelength is five times or more as long as the microwave irradiation width, the time fluctuations of Doppler velocity which shows a mean value of Doppler spectrum are good agreement with the orbital motions of the numerical regular wave. Also in such condition, the wave height of the sea surface waves can be observed accurately by analyzing the changes of Doppler velocity.

scholarly journals Fidelity of Analytic Drop Size Distributions in Drizzling Stratiform Clouds Based on Large-Eddy Simulations

2009 ◽  
Vol 66 (8) ◽  
pp. 2335-2348 ◽  
Author(s):  
Yefim L. Kogan ◽  
Zena N. Kogan ◽  
David B. Mechem
Keyword(s):  
Gamma Distribution ◽  
Drop Size ◽  
Accurate Estimate ◽  
Radar Reflectivity ◽  
Size Distributions ◽  
Eddy Simulation ◽  
Analytical Functions ◽  
Large Eddy ◽  
Stratiform Clouds ◽  
Drop Size Distributions

Abstract Cloud microphysical parameterizations and retrievals rely heavily on knowledge of the shape of drop size distributions (DSDs). Many investigations assume that DSDs in the entire or partial drop size range may be approximated by known analytical functions. The most frequently employed approximations of function are of the type of gamma, lognormal, Khrgian–Mazin, and Marshall–Palmer. At present, little is known about the accuracy of these approximations. The authors employ a DSD dataset generated by the Cooperative Institute for Mesoscale Meteorological Studies Large-Eddy Simulation (CIMMS LES) explicit microphysics model for stratocumulus cases observed during the Atlantic Stratocumulus Transition Experiment (ASTEX) field project. The fidelity of analytic lognormal- and gamma-type DSD functions is evaluated according to how well they represent the higher-order moments of the drop spectra, such as precipitation flux and radar reflectivity. It is concluded that for boundary layer marine drizzling stratocumuli, a DSD based on the two-mode gamma distribution provides a more accurate estimate of precipitation flux and radar reflectivity than the DSD based on the lognormal distribution. The gamma distribution also provides a more accurate radar reflectivity field in two- and three-moment bulk microphysical models compared to the conventional Z–R relationship.

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