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.

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.

Understanding the Importance of Microphysics and Macrophysics for Warm Rain in Marine Low Clouds. Part I: Satellite Observations

2009 ◽  
Vol 66 (10) ◽  
pp. 2953-2972 ◽  
Author(s):  
Terence L. Kubar ◽  
Dennis L. Hartmann ◽  
Robert Wood
Keyword(s):  
Gulf Of Mexico ◽  
Radar Data ◽  
Droplet Radius ◽  
Liquid Water Path ◽  
Cloud Radar ◽  
Warm Rain ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Tops ◽  
The Tropics

Abstract The importance of macrophysical variables [cloud thickness, liquid water path (LWP)] and microphysical variables (effective radius re, effective droplet concentration Neff) on warm drizzle intensity and frequency across the tropics and subtropics is studied. In this first part of a two-part study, Moderate Resolution Imaging Spectroradiometer (MODIS) optical and CloudSat cloud radar data are used to understand warm rain in marine clouds. Part II uses simple heuristic models. Cloud-top height and LWP substantially increase as drizzle intensity increases. Droplet radius estimated from MODIS also increases with cloud radar reflectivity (dBZ) but levels off as dBZ > 0, except where the influence of continental pollution is present, in which case a monotonic increase of re with drizzle intensity occurs. Off the Asian coast and over the Gulf of Mexico, re values are smaller (by several μm) and Neff values are larger compared to more remote marine regions. For heavy drizzle intensity, both re and Neff values off the Asian coast and over the Gulf of Mexico approach re and Neff values in more remote marine regions. Drizzle frequency, defined as profiles in which maximum dBZ > −15, increases dramatically and nearly uniformly when cloud tops grow from 1 to 2 km. Drizzle frequencies exceed 90% in all regions when LWPs exceed 250 g m−2 and Neff values are below 50 cm−3, even in regions where drizzle occurs infrequently on the whole. The fact that the relationship among drizzle frequency, LWP, and Neff is essentially the same for all regions suggests a near universality among tropical and subtropical regions.

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.

Assessment of the impact of INP and CCN perturbations on mixed-phase cloud microphysics using a spectral-bin model and reference observations

2020 ◽  
Author(s):  
Junghwa Lee ◽  
Patric Seifert ◽  
Tempei Hashino ◽  
Roland Schrödner ◽  
Michael Weger ◽  
...  
Keyword(s):  
Weather Prediction ◽  
Cloud Microphysics ◽  
Mixed Phase ◽  
Doppler Spectrum ◽  
Small Scale ◽  
Prediction System ◽  
Cloud Radar ◽  
Microphysical Processes ◽  
Mixed Phase Clouds ◽  
The Impact

<p>Ice- and mixed-phase clouds largely contribute to global precipitation due to their high spatiotemporal coverage. It has been highlighted that aerosol-cloud interaction is a critical factor. However, our current understanding of the complexity of their microphysical properties is still rather limited.  </p><p>In this talk, we will discuss the impact of perturbations of the cloud condensation nuclei (CCN) and ice-nucleating particle (INP) on the structure and composition of mixed-phase clouds. The main methods are ground-based observations (i.e., Ka-band polarimetric cloud radar) as well as the spectral-bin microphysical methodology called AMPS (Advanced Microphysics Prediction System). Until now, significant efforts have been underway to improve microphysical processes in AMPS, such as the schemes for immersion freezing and habit prediction. Despite these endeavors, it is still challenging using modeling alone to resolve such complexity of microphysical processes due to many parameterizations and assumptions. In particular, the ice habit prediction system in AMPS is sensitive to the 3-D Eulerian advection scheme. Meanwhile, the Doppler-spectra derived from polarimetric cloud radar enables us to retrieve the hydrometeor habit of the significant signal peak in the Doppler spectrum of mixed-phase clouds. The synergy between the above mentioned advanced modeling approach and state-of-the-art observation techniques are in our study used to evaluate the effects of the CCN and INP perturbations on mixed-phase clouds. </p><p>The steps are as follows. First of all, we will present the evaluation of a case study of a mixed-phase cloud by observation data. In the course of the work, AMPS is coupled with the German weather prediction system COSMO (Consortium for Small-scale Modeling) model. We choose an observation dataset from the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) field campaign in Cabauw, Netherlands, which was conducted during fall 2014. Also, we use the radar forward operator CR-SIM (Cloud Resolving Model Radar Simulator) that translates the dataset of simulation output into radar variables. Therefore, we will present direct comparisons between ground-based observation and modeling datasets. In the next step, AMPS is coupled with a simple 1-D dynamic core KiD (Kinematic Driver for microphysics intercomparison), so-called KiD-AMPS. In doing so, we will discuss the comparison with other schemes (i.e., Morrison 2-moment). Finally, in the frame of KiD-AMPS, we will debate the impact of the CCN and INP perturbations on mixed-phase clouds. </p>

scholarly journals Potential of Higher-Order Moments and Slopes of the Radar Doppler Spectrum for Retrieving Microphysical and Kinematic Properties of Arctic Ice Clouds

2017 ◽  
Vol 56 (2) ◽  
pp. 263-282 ◽  
Author(s):  
Maximilian Maahn ◽  
Ulrich Löhnert
Keyword(s):  
Higher Order ◽  
Doppler Spectrum ◽  
Doppler Velocity ◽  
State Variables ◽  
Higher Order Moments ◽  
Radar Observations ◽  
Additional Information ◽  
Cloud Radar ◽  
Mass Size ◽  
Size Relation

AbstractRetrievals of ice-cloud properties from cloud-radar observations are challenging because the retrieval methods are typically underdetermined. Here, the authors investigate whether additional information can be obtained from higher-order moments and the slopes of the radar Doppler spectrum such as skewness and kurtosis as well as the slopes of the Doppler peak. To estimate quantitatively the additional information content, a generalized Bayesian retrieval framework that is based on optimal estimation is developed. Real and synthetic cloud-radar observations of the Indirect and Semi-Direct Aerosol Campaign (ISDAC) dataset obtained around Barrow, Alaska, are used in this study. The state vector consists of the microphysical (particle-size distribution, mass–size relation, and cross section–area relation) and kinematic (vertical wind and turbulence) quantities required to forward model the moments and slopes of the radar Doppler spectrum. It is found that, for a single radar frequency, more information can be retrieved when including higher-order moments and slopes than when using only reflectivity and mean Doppler velocity but two radar frequencies. When using all moments and slopes with two or even three frequencies, the uncertainties of all state variables, including the mass–size relation, can be considerably reduced with respect to the prior knowledge.

Finescale Vertical Structure and Evolution of a Preconvective Dryline on 19 June 2002

2007 ◽  
Vol 135 (6) ◽  
pp. 2111-2134 ◽  
Author(s):  
Benjamin D. Sipprell ◽  
Bart Geerts
Keyword(s):  
Vertical Structure ◽  
Radar Data ◽  
Doppler Velocity ◽  
Convective Boundary ◽  
Convective Initiation ◽  
Depth Difference ◽  
Cloud Radar ◽  
Later Phase ◽  
Total Elimination ◽  
Vertical Transect

Abstract High-resolution airborne cloud radar data and other International H2O Project datasets are used to describe the vertical structure of an unusual prefrontal dryline. This dryline, observed in northwestern Kansas on 19 June 2002, first progressed eastward and tilted toward the west, and later became more stationary and reversed its tilt, toward the moist side. The convective boundary layer (CBL) depth difference also reversed: only in the later phase did the dry-side CBL become deeper than on the moist side. Echo and single/dual-Doppler velocity data in a vertical transect across the dryline suggest a solenoidal circulation dynamically consistent with the observed horizontal buoyancy gradient. Both this gradient and the solenoidal circulation reversed in the later phase. Simultaneously, confluence toward the dryline increased, resulting in an increasing moisture gradient as well as a deepening CBL in the dryline convergence zone. It is speculated that the baroclinically generated horizontal vorticity contributed to this CBL deepening, as the sign of this vorticity was opposite to that of the low-level wind shear on the opposite side of the dryline in both phases. Deep-convective initiation appears to have resulted from this local CBL deepening, leading to a total elimination of convective inhibition near the dryline.

scholarly journals The NCAR Airborne 94-GHz Cloud Radar: Calibration and Data Processing

Data ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 66
Author(s):  
Ulrike Romatschke ◽  
Michael Dixon ◽  
Peisang Tsai ◽  
Eric Loew ◽  
Jothiram Vivekanandan ◽  
...  
Keyword(s):  
Radar Data ◽  
Reanalysis Data ◽  
Time Range ◽  
Cloud Radar ◽  
Elevation Data ◽  
Radar Echo ◽  
Western Caribbean ◽  
Radar Calibration ◽  
Terrain Elevation ◽  
Gain Errors

The 94-GHz airborne HIAPER Cloud Radar (HCR) has been deployed in three major field campaigns, sampling clouds over the Pacific between California and Hawaii (2015), over the cold waters of the Southern Ocean (2018), and characterizing tropical convection in the Western Caribbean and Pacific waters off Panama and Costa Rica (2019). An extensive set of quality assurance and quality control procedures were developed and applied to all collected data. Engineering measurements yielded calibration characteristics for the antenna, reflector, and radome, which were applied during flight, to produce the radar moments in real-time. Temperature changes in the instrument during flight affect the receiver gains, leading to some bias. Post project, we estimate the temperature-induced gain errors and apply gain corrections to improve the quality of the data. The reflectivity calibration is monitored by comparing sea surface cross-section measurements against theoretically calculated model values. These comparisons indicate that the HCR is calibrated to within 1–2 dB of the theory. A radar echo classification algorithm was developed to identify “cloud echo” and distinguish it from artifacts. Model reanalysis data and digital terrain elevation data were interpolated to the time-range grid of the radar data, to provide an environmental reference.

scholarly journals A Quality Control Concept for Radar Reflectivity, Polarimetric Parameters, and Doppler Velocity

2006 ◽  
Vol 23 (7) ◽  
pp. 865-887 ◽  
Author(s):  
Katja Friedrich ◽  
Martin Hagen ◽  
Thomas Einfalt
Keyword(s):  
Quality Control ◽  
Quality Index ◽  
Prediction Models ◽  
Weather Prediction ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Doppler Velocity ◽  
Control Procedure ◽  
End User ◽  
Weather Situation

Abstract Over the last few years the use of weather radar data has become a fundamental part of various applications like rain-rate estimation, nowcasting of severe weather events, and assimilation into numerical weather prediction models. The increasing demand for radar data necessitates an automated, flexible, and modular quality control. In this paper a quality control procedure is developed for radar reflectivity factors, polarimetric parameters, and Doppler velocity. It consists of several modules that can be extended, modified, and omitted depending on the user requirement, weather situation, and radar characteristics. Data quality is quantified on a pixel-by-pixel basis and encoded into a quality-index field that can be easily interpreted by a nontrained end user or an automated scheme that generates radar products. The quality-index algorithms detect and quantify the influence of beam broadening, the height of the first radar echo, ground clutter contamination, return from non-weather-related objects, and attenuation of electromagnetic energy by hydrometeors on the quality of the radar measurement. The quality-index field is transferred together with the radar data to the end user who chooses the amount of data and the level of quality used for further processing. The calculation of quality-index fields is based on data measured by the polarimetric C-band Doppler radar (POLDIRAD) located in the Alpine foreland in southern Germany.

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.

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