High-Resolution Observations of Mammatus in Tropical Anvils

Abstract Unprecedented high-resolution observations of mammatus from a profiling 94-GHz Doppler radar during the NASA Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL–FACE) are presented. Because of its high sensitivity and temporal and spatial resolution, the cloud radar used was able to resolve the fine structure of individual mammatus clouds and record significant vertical Doppler velocity perturbations (−6 to +1 m s−1). Strong perturbations of the Doppler velocity within the mammatus as it extends below the main cirrus cloud base are captured by the radar observations. Upward motions in the periphery of descending mammatus cores are documented. Areas of intense, small-scale turbulent mixing near the cirrus cloud base are identified using the Doppler spectrum width. Power spectra analysis of the mean Doppler velocity field supports the presence of gravity waves and the development of higher-frequency structures near the cirrus anvil base, where the mammatus clouds are observed. The observations provide strong evidence for dynamical forcing from coherent vertical motions 500 m above the cloud base contributing to the mammatus formation. The results are discussed in the context of suggested theories for mamma formation and morphology.

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MU Radar and Lidar Observations of Clear-Air Turbulence underneath Cirrus

Monthly Weather Review ◽

10.1175/2009mwr2927.1 ◽

2010 ◽

Vol 138 (2) ◽

pp. 438-452 ◽

Cited By ~ 18

Author(s):

Hubert Luce ◽

Takuji Nakamura ◽

Masayuki K. Yamamoto ◽

Mamoru Yamamoto ◽

Shoichiro Fukao

Keyword(s):

Convective Instability ◽

Radar Data ◽

Ice Crystals ◽

Shear Instability ◽

Cloud Base ◽

Doppler Spectrum ◽

Cirrus Cloud ◽

Air Turbulence ◽

Mu Radar ◽

Generation Mechanisms

Abstract Turbulence generation mechanisms prevalent in the atmosphere are mainly shear instabilities, breaking of internal buoyancy waves, and convective instabilities such as thermal convection due to heating of the ground. In the present work, clear-air turbulence underneath a cirrus cloud base is described owing to coincident observations from the VHF (46.5 MHz) middle and upper atmosphere (MU) radar, a Rayleigh–Mie–Raman (RMR) lidar, and a balloon radiosonde on 7–8 June 2006 (at Shigaraki, Japan; 34.85°N, 136.10°E). Time–height cross section of lidar backscatter ratio obtained at 2206 LT 7 June 2006 showed the presence of a cirrus layer between 8.0 and 12.5 km MSL. Downward-penetrating structures of ice crystals with horizontal and vertical extents of 1.0–4.0 km and 200–800 m, respectively, have been detected at the cirrus cloud base for about 35 min. At the same time, the MU radar data revealed clear-air turbulence layers developing downward from the cloud base in the environment of the protuberances detected by the RMR lidar. Their maximum depth was about 2.0 km for about 1.5 h. They were associated with oscillatory vertical wind perturbations of up to ±1.5 m s−1 and variances of Doppler spectrum of 0.2–1.5 m−2 s−2. Analysis of the data suggests that the turbulence and the downward penetration of cloudy air were possibly the consequence of a convective instability (rather than a dynamical shear instability) that was likely due to sublimation of ice crystals in the subcloud region. Downward clear-air motions measured by the MU radar were associated with the descending protuberances, and updrafts were observed between them. These observations suggest that the cloudy air might have been pushed down by the downdrafts of the convective instability and pushed up by the updrafts to form the observed protuberances at the cloud base. These structures may be virga or perhaps more likely mamma as reported by recent observations of cirrus mamma with similar instruments and by numerical simulations.

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Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra

10.5194/amt-2021-27 ◽

2021 ◽

Author(s):

Christopher R. Williams ◽

Karen L. Johnson ◽

Scott E. Giangrande ◽

Joseph C. Hardin ◽

Ruşen Öktem ◽

...

Keyword(s):

Power Spectra ◽

Department Of Energy ◽

Cloud Base ◽

Doppler Velocity ◽

Polarimetric Radar ◽

Ka Band ◽

Ice Particles ◽

Linear Depolarization Ratio ◽

Velocity Spectra ◽

Discrimination Method

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The insect-hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects versus cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra linear depolarization ratio (LDR) produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives this need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Comparison with a collocated ceilometer indicates that hydrometeor mask column bottoms are within +/-100 meters of simultaneous ceilometer cloud base heights. Forty-seven (47) summer-time days were processed with the insect-hydrometeor discrimination method using U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma (USA). All datasets and images are available on public repositories.

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High-Range Resolution Spectral Analysis of Precipitation Through Range Imaging of the Chung-Li VHF Radar

10.5194/amt-2017-156 ◽

2017 ◽

Author(s):

Shih-Chiao Tsai ◽

Jenn-Shyong Chen ◽

Yen-Hsyang Chu ◽

Ching-Lun Su ◽

Jui-Hsiang Chen

Keyword(s):

Weighting Function ◽

Power Doppler ◽

Power Spectra ◽

Doppler Frequency ◽

Doppler Velocity ◽

Small Scale ◽

Range Imaging ◽

Very High Frequency ◽

Vhf Radar ◽

Range Resolution

Abstract. Multi-frequency range imaging (RIM) has been implemented in the Chung-Li very-high-frequency (VHF) radar, located on the campus of National Central University, Taiwan, since 2008. RIM processes the echo signals with a group of closely spaced transmitting frequencies through appropriate inversion methods to obtain high-resolution distribution of echo power in the range direction. This is beneficial to the investigation of the small scale structure embedded in dynamic atmosphere. Five transmitting frequencies were employed in the radar experiment for observation of the precipitating atmosphere during the period between 21 and 23 Aug, 2013. Using the Capon and Fourier methods, the radar echoes were synthesized to retrieve the temporal signals at a smaller range step than the original range resolution defined by the pulse width, and such retrieved temporal signals were then processed in the Doppler frequency domain to identify the atmosphere and precipitation echoes. An analysis called conditional averaging was further executed for echo power, Doppler velocity, and spectral width to verify the potential capabilities of the retrieval processing in resolving small-scale precipitation and atmosphere structures. Point-by-point correction of range delay combined with compensation of range weighting function effect has been performed during the retrieval of temporal signals to improve the continuity of power spectra at gate boundaries, making the small-scale structures in the power spectra more natural and reasonable. We examined stratiform and convective precipitations and demonstrated their different structured characteristics by means of the Capon-processed results.

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Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-18-0111.1 ◽

2019 ◽

Vol 36 (6) ◽

pp. 921-940 ◽

Cited By ~ 5

Author(s):

M. Christian Schwartz ◽

Virendra P. Ghate ◽

Bruce. A. Albrecht ◽

Paquita Zuidema ◽

Maria P. Cadeddu ◽

...

Keyword(s):

High Performance ◽

Environmental Research ◽

High Spectral Resolution ◽

Cloud System ◽

Cloud Base ◽

Doppler Spectrum ◽

Doppler Velocity ◽

System Evolution ◽

Microphysical Properties ◽

Fuzzy Logic Technique

AbstractThe Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR’s High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved using the HCR reflectivity, HSRL backscatter, and the HCR Doppler spectrum width after it is corrected for the aircraft speed. These indicate that as the boundary layers deepen and cloud-top heights increase toward the equator, both the cloud and rain fractions decrease.

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The impact of inhomogeneous subgrid clumping on cosmic reionization

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/stz2986 ◽

2019 ◽

Vol 491 (2) ◽

pp. 1600-1621

Author(s):

Yi Mao ◽

Jun Koda ◽

Paul R Shapiro ◽

Ilian T Iliev ◽

Garrelt Mellema ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Power Spectra ◽

Coarse Grained ◽

Small Scale ◽

Sources And Sinks ◽

Coarse Grained Simulations ◽

Cent Error ◽

Spatially Varying ◽

The Impact

ABSTRACT Cosmic reionization was driven by the imbalance between early sources and sinks of ionizing radiation, both of which were dominated by small-scale structure and are thus usually treated in cosmological reionization simulations by subgrid modelling. The recombination rate of intergalactic hydrogen is customarily boosted by a subgrid clumping factor, 〈n2〉/〈n〉2, which corrects for unresolved fluctuations in gas density n on scales below the grid-spacing of coarse-grained simulations. We investigate in detail the impact of this inhomogeneous subgrid clumping on reionization and its observables, as follows: (1) Previous attempts generally underestimated the clumping factor because of insufficient mass resolution. We perform a high-resolution N-body simulation that resolves haloes down to the pre-reionization Jeans mass to derive the time-dependent, spatially varying local clumping factor and a fitting formula for its correlation with local overdensity. (2) We then perform a large-scale N-body and radiative transfer simulation that accounts for this inhomogeneous subgrid clumping by applying this clumping factor-overdensity correlation. Boosting recombination significantly slows the expansion of ionized regions, which delays completion of reionization and suppresses 21 cm power spectra on large scales in the later stages of reionization. (3) We also consider a simplified prescription in which the globally averaged, time-evolving clumping factor from the same high-resolution N-body simulation is applied uniformly to all cells in the reionization simulation, instead. Observables computed with this model agree fairly well with those from the inhomogeneous clumping model, e.g. predicting 21 cm power spectra to within 20 per cent error, suggesting it may be a useful approximation.

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SOME ISSUES IN CMB POLARIZATION OBSERVATION

Modern Physics Letters A ◽

10.1142/s0217732307025121 ◽

2007 ◽

Vol 22 (25n28) ◽

pp. 1901-1910

Author(s):

KIN-WANG NG

Keyword(s):

High Resolution ◽

Power Spectra ◽

High Sensitivity ◽

Unbiased Estimation ◽

Huge Amount ◽

High Resolution Data ◽

Polarization Observation ◽

Cmb Polarization ◽

Resolution Data

As a huge amount of high-resolution data made by future high-sensitivity CMB experiments comes along, it is timely to study some important issues such as asymmetric beam effects and the mixing and separation of the E-mode and B-mode polarization in order to make efficient and unbiased estimation of the CMB anisotropy power spectra.

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Cirrus Mammatus Properties Derived from an Extended Remote Sensing Dataset

Journal of the Atmospheric Sciences ◽

10.1175/jas3648.1 ◽

2006 ◽

Vol 63 (2) ◽

pp. 712-725 ◽

Cited By ~ 9

Author(s):

Likun Wang ◽

Kenneth Sassen

Keyword(s):

Remote Sensing ◽

Large Scale ◽

Doppler Radar ◽

Three Dimensional ◽

Remote Sensing Data ◽

Cloud Base ◽

Doppler Velocity ◽

Small Scale ◽

Length Scales ◽

Atmospheric Remote Sensing

Abstract The first quantitative and statistical evaluation of cirrus mammatus clouds based on wavelet analysis of remote sensing data is made by analyzing the University of Utah Facility for Atmospheric Remote Sensing (FARS) 10-yr high-cloud dataset. First, a case study of cirrus mammata combining a high-resolution lidar system and a W-band Doppler radar is presented, yielding an assessment of the thermodynamic environment and dynamic mechanisms. Then, 25 cirrus mammatus cases selected from the FARS lidar dataset are used to disclose their characteristic environmental conditions, and vertical and length scales. The results show that cirrus mammata occur in the transition zone from moist (cloudy) to dry air layers with weak wind shear, which suggests that cloud-induced thermal structures play a key role in their formation. Their maximum vertical and horizontal length scales vary from 0.3 to 1.1 km and 0.5 to 8.0 km, respectively. It is also found that small-scale structures develop between the large-scale protuberances. The spectral slopes of the lidar-returned power and mean radar Doppler velocity data extracted from the cirrus cloud-base region further indicate the presence of developed three-dimensional, locally isotropic, homogeneous turbulence generated by buoyancy. Finally, comparisons of anvil and cirrus mammata are made. Although both are generated in a similar environment, cirrus mammata generally do not form fallout fronts like their anvil counterparts, and so do not have their smooth and beautiful outlines.

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High-Resolution Raindrop Size Distribution Retrieval Based on the Doppler Spectrum in the Case of Slant Profiling Radar

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-13-00225.1 ◽

2015 ◽

Vol 32 (6) ◽

pp. 1191-1208 ◽

Cited By ~ 5

Author(s):

Christine Unal

Keyword(s):

High Resolution ◽

Size Distribution ◽

Horizontal Wind ◽

Doppler Spectrum ◽

Small Scale ◽

Velocity Spectrum ◽

Fall Velocity ◽

Light Rain ◽

Raindrop Size Distribution ◽

Raindrop Size

AbstractDoppler spectra from vertically profiling radars are usually considered to retrieve the raindrop size distribution (DSD). However, to exploit both fall velocity spectrum and polarimetric measurements, Doppler spectra acquired in slant profiling mode should be explored. Rain DSD samples are obtained from simultaneously measured vertical and slant profile Doppler spectra and evaluated. In particular, the effect of the horizontal wind and the averaging time are investigated.The Doppler spectrum provides a way to retrieve the DSD, the radial wind, and a spectral broadening factor by means of a nonlinear optimization technique. For slant profiling of light rain when the horizontal wind is strong, the DSD results can be affected. Such an effect is demonstrated on a study case of stratiform light rain. Adding a wind profiler mode to the radar simultaneously supplies the horizontal wind and Doppler spectra. Before the retrieval procedure, the Doppler spectra are shifted in velocity to remove the mean horizontal wind contribution. The DSD results are considerably improved.Generally, averaged Doppler spectra are input into this type of algorithm. Instead, high-resolution, low-averaged Doppler spectra are chosen in order to take into account the small-scale variability of the rainfall. Investigating the linear relations at fixed median volume diameter, measured reflectivity-retrieved rainfall rate, for a slant beam, the consistency of the integrated parameters is established for two averaging periods. Nevertheless, the corresponding DSD parameter distributions reveal differences attributed to the averaging of the Doppler spectra.The new aspects are to obtain the same retrieval quality as vertically profiling and highly averaged spectra in an automated way.

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High-range resolution spectral analysis of precipitation through range imaging of the Chung-Li VHF radar

Atmospheric Measurement Techniques ◽

10.5194/amt-11-581-2018 ◽

2018 ◽

Vol 11 (1) ◽

pp. 581-592

Author(s):

Shih-Chiao Tsai ◽

Jenn-Shyong Chen ◽

Yen-Hsyang Chu ◽

Ching-Lun Su ◽

Jui-Hsiang Chen

Keyword(s):

Spectral Analysis ◽

Weighting Function ◽

Power Doppler ◽

Power Spectra ◽

Convective Precipitation ◽

Doppler Velocity ◽

Small Scale ◽

Range Imaging ◽

Vhf Radar ◽

Range Resolution

Abstract. Multi-frequency range imaging (RIM) has been operated in the Chung-Li very high-frequency (VHF) radar, located on the campus of National Central University, Taiwan, since 2008. RIM processes the echo signals with a group of closely spaced transmitting frequencies through appropriate inversion methods to obtain high-resolution distribution of echo power in the range direction. This is beneficial to the investigation of the small-scale structure embedded in dynamic atmosphere. Five transmitting frequencies were employed in the radar experiment for observation of the precipitating atmosphere during the period between 21 and 23 August 2013. Using the Capon and Fourier methods, the radar echoes were synthesized to retrieve the temporal signals at a smaller range step than the original range resolution defined by the pulse width, and such retrieved temporal signals were then processed in the Doppler frequency domain to identify the atmosphere and precipitation echoes. An analysis called conditional averaging was further executed for echo power, Doppler velocity, and spectral width to verify the potential capabilities of the retrieval processing in resolving small-scale precipitation and atmosphere structures. Point-by-point correction of range delay combined with compensation of range-weighting function effect has been performed during the retrieval of temporal signals to improve the continuity of power spectra at gate boundaries, making the small-scale structures in the power spectra more natural and reasonable. We examined stratiform and convective precipitation and demonstrated their different structured characteristics by means of the Capon-processed results. The new element in this study is the implementation of RIM on spectral analysis, especially for precipitation echoes.

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Identifying insects, clouds, and precipitation using vertically pointing polarimetric radar Doppler velocity spectra

Atmospheric Measurement Techniques ◽

10.5194/amt-14-4425-2021 ◽

2021 ◽

Vol 14 (6) ◽

pp. 4425-4444

Author(s):

Christopher R. Williams ◽

Karen L. Johnson ◽

Scott E. Giangrande ◽

Joseph C. Hardin ◽

Ruşen Öktem ◽

...

Keyword(s):

Power Spectra ◽

Department Of Energy ◽

Cloud Base ◽

Doppler Velocity ◽

Polarimetric Radar ◽

Ka Band ◽

Ice Particles ◽

Linear Depolarization Ratio ◽

Velocity Spectra ◽

Discrimination Method

Abstract. This study presents a method to identify and distinguish insects, clouds, and precipitation in 35 GHz (Ka-band) vertically pointing polarimetric radar Doppler velocity power spectra and then produce masks indicating the occurrence of hydrometeors (i.e., clouds or precipitation) and insects at each range gate. The polarimetric radar used in this study transmits a linear polarized wave and receives signals in collinear (CoPol) and cross-linear (XPol) polarized channels. The measured CoPol and XPol Doppler velocity spectra are used to calculate linear depolarization ratio (LDR) spectra. The insect–hydrometeor discrimination method uses CoPol and XPol spectral information in two separate algorithms with their spectral results merged and then filtered into single value products at each range gate. The first algorithm discriminates between insects and clouds in the CoPol Doppler velocity power spectra based on the spectra texture, or spectra roughness, which varies due to the scattering characteristics of insects vs. cloud particles. The second algorithm distinguishes insects from raindrops and ice particles by exploiting the larger Doppler velocity spectra LDR produced by asymmetric insects. Since XPol power return is always less than CoPol power return for the same target (i.e., insect or hydrometeor), fewer insects and hydrometeors are detected in the LDR algorithm than the CoPol algorithm, which drives the need for a CoPol based algorithm. After performing both CoPol and LDR detection algorithms, regions of insect and hydrometeor scattering from both algorithms are combined in the Doppler velocity spectra domain and then filtered to produce a binary hydrometeor mask indicating the occurrence of cloud, raindrops, or ice particles at each range gate. Forty-seven summertime days were processed with the insect–hydrometeor discrimination method using US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar observations in northern Oklahoma, USA. For these 47 d, over 70 % of the hydrometeor mask column bottoms were within ±100 m of simultaneous ceilometer cloud base heights. All datasets and images are available to the public on the DOE ARM repository.

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