Differences of Microphysical Processes in the Melting Layer Found for Rimed and Unrimed Snowflakes Using Cloud Radar Statistics

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.

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

10.5194/egusphere-egu2020-11342 ◽

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

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.&#160;&#160;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.&#160;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.&#160;

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Observations of Ice Microphysics through the Melting Layer

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-14-0363.1 ◽

2015 ◽

Vol 72 (8) ◽

pp. 2902-2928 ◽

Cited By ~ 21

Author(s):

Andrew J. Heymsfield ◽

Aaron Bansemer ◽

Michael R. Poellot ◽

Norm Wood

Keyword(s):

Particle Size ◽

Size Distributions ◽

Particle Size Distributions ◽

Small Particles ◽

Melting Layer ◽

Maximum Particle Size ◽

Maximum Particle ◽

Microphysical Processes ◽

Increasing Temperature

Abstract The detailed microphysical processes and properties within the melting layer (ML)—the continued growth of the aggregates by the collection of the small particles, the breakup of these aggregates, the effects of relative humidity on particle melting—are largely unresolved. This study focuses on addressing these questions for in-cloud heights from just above to just below the ML. Observations from four field programs employing in situ measurements from above to below the ML are used to characterize the microphysics through this region. With increasing temperatures from about −4° to +1°C, and for saturated conditions, slope and intercept parameters of exponential fits to the particle size distributions (PSD) fitted to the data continue to decrease downward, the maximum particle size (largest particle sampled for each 5-s PSD) increases, and melting proceeds from the smallest to the largest particles. With increasing temperature from about −4° to +2°C for highly subsaturated conditions, the PSD slope and intercept continue to decrease downward, the maximum particle size increases, and there is relatively little melting, but all particles experience sublimation.

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Microphysical and Thermodynamic Structure and Evolution of the Trailing Stratiform Regions of Mesoscale Convective Systems during BAMEX. Part II: Column Model Simulations

Monthly Weather Review ◽

10.1175/2008mwr2505.1 ◽

2009 ◽

Vol 137 (4) ◽

pp. 1186-1205 ◽

Cited By ~ 17

Author(s):

Joseph A. Grim ◽

Greg M. McFarquhar ◽

Robert M. Rauber ◽

Andrea M. Smith ◽

Brian F. Jewett

Keyword(s):

Mesoscale Convective Systems ◽

Sharp Change ◽

Melting Layer ◽

Thermodynamic Structure ◽

Column Model ◽

Convective Systems ◽

Stratiform Region ◽

Bow Echo ◽

Mesoscale Convective ◽

Microphysical Processes

Abstract This study employed a nondynamic microphysical column model to evaluate the degree to which the microphysical processes of sublimation, melting, and evaporation alone can explain the evolution of the relative humidity (RH) and latent cooling profiles within the trailing stratiform region of mesoscale convective systems observed during the Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX). Simulations revealed that observations of a sharp change in the profile of RH, from saturated air with respect to ice above the melting layer to subsaturated air with respect to water below, developed in response to the rapid increase in hydrometeor fall speeds from 1–2 m s−1 for ice to 2–11 m s−1 for rain. However, at certain times and locations, such as the first spiral descent on 29 June 2003 within the notch of lower reflectivity, the air may remain subsaturated for temperatures (T) < 0°C. Sufficiently strong downdrafts above the melting level, such as the 1–3 m s−1 downdrafts observed in the notch of lower reflectivity on 29 June, could enable this state of sustained subsaturation. Sensitivity tests, where the hydrometeor size distributions and upstream RH profiles were varied within the range of BAMEX observations, revealed that the sharp contrast in the RH field across the melting layer always developed. The simulations also revealed that latent cooling from sublimation and melting resulted in the strongest cooling at altitudes within and above the melting layer for locations where hydrometeors did not reach the ground, such as within the rear anvil region, and where sustained subsaturated air is present for T < 0°C, such as is observed within downdrafts. Within the enhanced stratiform rain region, the air is typically at or near saturation for T < 0°C, whereas it is typically subsaturated for T > 0°C; thus, evaporation and melting result in the primary cooling in this region. The implications of these results for the descent of the rear inflow jet across the trailing stratiform region are discussed.

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

10.5194/amt-2019-20 ◽

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.

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Lidar and radar measurements of the melting layer in the frame of the Convective and Orographically-induced Precipitation Study: observations of dark and bright band phenomena

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-30949-2011 ◽

2011 ◽

Vol 11 (11) ◽

pp. 30949-30987

Author(s):

P. Di Girolamo ◽

D. Summa ◽

R. Bhawar ◽

T. Di Iorio ◽

E. G. Norton ◽

...

Keyword(s):

Raman Lidar ◽

Layer Model ◽

Lidar System ◽

Melting Layer ◽

Cloud Radar ◽

Bright Band ◽

Radar Measurements ◽

Uhf Wind Profiler ◽

The University ◽

University Of Manchester

Abstract. During the Convective and Orographically-induced Precipitation Study (COPS), lidar dark and bright bands were observed by the University of BASILicata Raman lidar system (BASIL) during several intensive (IOPs) and special (SOPs) observation periods (among others, 23 July, 15 August, and 17 August 2007). Lidar data were supported by measurements from the University of Hamburg cloud radar MIRA 36 (36 GHz), the University of Hamburg dual-polarization micro rain radars (24.1 GHz) and the University of Manchester UHF wind profiler (1.29 GHz). Results from BASIL and the radars for 23 July 2007 are illustrated and discussed to support the comprehension of the microphysical and scattering processes responsible for the appearance of the lidar and radar dark and bright bands. Simulations of the lidar dark and bright band based on the application of concentric/eccentric sphere Lorentz-Mie codes and a melting layer model are also provided. Lidar and radar measurements and model results are also compared with measurements from a disdrometer on ground and a two-dimensional cloud (2DC) probe on-board the ATR42 SAFIRE.

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Towards the connection between snow microphysics and melting layer: Insights from multi-frequency and dual-polarization radar observations during BAECC

10.5194/acp-2020-16 ◽

2020 ◽

Author(s):

Haoran Li ◽

Jussi Tiira ◽

Annakaisa von Lerber ◽

Dmitri Moisseev

Keyword(s):

Doppler Radar ◽

Strong Dependence ◽

Precipitation Intensity ◽

Dual Polarization ◽

Radar Observations ◽

Melting Layer ◽

Microphysical Properties ◽

Microphysical Processes ◽

Biogenic Aerosols ◽

The Impact

Abstract. In stratiform rainfall, the melting layer is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the melting layer and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured melting layer properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide an additional constraint on the retrieval of ice cloud microphysical properties, we have investigated this link. This study is divided into two parts. Firstly, surface-based snowfall measurements are used to devise a method for classifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. In the second part, this classification is used in combination with multi-frequency and dual-polarization radar observations to investigate the impact of precipitation intensity, aggregation, riming, and dendritic growth on melting layer properties. The radar-observed melting layer characteristics show strong dependence on precipitation intensity as well as detectable differences between unrimed and rimed snow. This study is based on the data collected during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) experiment, that took place in 2014 in Hyytiala, Finland.

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Towards the connection between snow microphysics and melting layer: insights from multifrequency and dual-polarization radar observations during BAECC

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-9547-2020 ◽

2020 ◽

Vol 20 (15) ◽

pp. 9547-9562 ◽

Cited By ~ 1

Author(s):

Haoran Li ◽

Jussi Tiira ◽

Annakaisa von Lerber ◽

Dmitri Moisseev

Keyword(s):

Doppler Radar ◽

Precipitation Intensity ◽

Dual Polarization ◽

Radar Observations ◽

Melting Layer ◽

Bright Band ◽

Radar Signatures ◽

Microphysical Processes ◽

The Impact ◽

Precipitation Formation

Abstract. In stratiform rainfall, the melting layer (ML) is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the ML and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured ML properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide new insights into radar signatures of snow growth processes, we have investigated this link. This study is divided into two parts. Firstly, surface-based snowfall measurements are used to develop a new method for identifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. Secondly, this classification is used in combination with multifrequency and dual-polarization radar observations collected during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) experiment in 2014 to investigate the impact of precipitation intensity, aggregation, riming and dendritic growth on the ML properties. The results show that the radar-observed ML properties are highly related to the precipitation intensity. The previously reported bright band “sagging” is mainly connected to the increase in precipitation intensity. Ice particle riming plays a secondary role. In moderate to heavy rainfall, riming may cause additional bright band sagging, while in light precipitation the sagging is associated with unrimed snow. The correlation between ML properties and dual-polarization radar signatures in the snow region above appears to be arising through the connection of the radar signatures and ML properties to the precipitation intensity. In addition to advancing our knowledge of the link between ML properties and snow processes, the presented analysis demonstrates how multifrequency Doppler radar observations can be used to get a more detailed view of cloud processes and establish a link to precipitation formation.

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An adaptive echo attenuation correction method for airborne Ka-band precipitation cloud radar based on melting layer

10.5194/amt-2021-221 ◽

2021 ◽

Author(s):

Dongfei Zuo ◽

Deping Ding ◽

Yichen Chen ◽

Ling Yang ◽

Delong Zhao ◽

...

Keyword(s):

Correlation Coefficient ◽

Attenuation Correction ◽

Relative Error ◽

Water Film ◽

Liquid Water Content ◽

Correction Method ◽

Ka Band ◽

Melting Layer ◽

Mean Relative Error ◽

Cloud Radar

Abstract. In this study, an airborne Ka-band Precipitation Cloud Radar (KPR) is used to carry out a cloud observation experiment.By analyzing the attenuation of the snow echo, it is found that during the snowfall, due to the low liquid water content, the KPR attenuation is small on the detection path, and after preliminary comparative analysis, the maximum attenuation correction value is 0.5 dBZ. According to the echo attenuation analysis of mixed precipitation, the melting layer is found to be the key factor affecting the attenuation correction. This study hereby proposes an adaptive echo attenuation correction method based on the melting layer (AEC), and uses the ground-based S-band radar to extract the echo on the aircraft trajectory to verify the correction results. The results show that the echo attenuation correction value above the melting layer is related to the flight position. The aircraft above the melting layer is dominated by ice particles, with small attenuation correction value, the maximum correction amount of 0.13 dBZ; when the aircraft is at and just below the melting layer, a water film is prone to be on the antenna, which leads to serious attenuation of the KPR detection path, with the attenuation correction value 1~2 dBZ. For the precipitation echo below the melting layer, due to the abundant rain and water vapor content, the KPR attenuation is significant with maximum correction value of about 5 dBZ. Compared with the S-band radar, before attenuation correction, the total mean relative error is 15 %, and the correlation coefficient is 0.82; after correction, the total mean relative error is 6 %, and the correlation coefficient is 0.90, indicating the significant improvement of the KPR data quality.

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