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

Li, Haoran; Tiira, Jussi; Lerber, Annakaisa von; Moisseev, Dmitri

doi:10.5194/acp-2020-16

Cited by 4 publications

(18 citation statements)

References 47 publications

(85 reference statements)

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“…The C‐band LDR observations show a slightly descending trend as can be identified between 21:50 and 22:35 UTC. The local sagging of C‐band LDR in the ML (Kumjian et al., 2016) coincides with two fall streaks at around 22:25 UTC and 22:35 UTC, which can be explained by the locally enhanced aggregation and precipitation rate (Carlin & Ryzhkov, 2019; Li et al., 2020). In contrast, W‐band LDR shows less variation in the ML at these times.…”

Section: Observationsmentioning

confidence: 98%

“…Even though detailed observations of the ML are performed using aircraft penetrations, they are limited to measurement campaigns and do not provide continuous records. Ground‐based radars have been widely employed for ML studies (e.g., Fabry & Zawadzki, 1995; Griffin et al., 2020; Kumjian et al., 2016; Li et al., 2020; Russchenberg & Ligthart, 1996; Trömel et al., 2019). However, radar interpretations of the ML are still challenging largely due to the uncertainties in microphysical processes that take place in the ML (Heymsfield et al., 2015) and how snowflake melting modifies particle physical (Leinonen & von Lerber, 2018) and scattering properties (Ori & Kneifel, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Two Layers of Melting Ice Particles Within a Single Radar Bright Band: Interpretation and Implications

Moisseev

2020

Geophysical Research Letters

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Dual‐frequency dual‐polarization radar observations of the melting of two ice populations in a stratiform rainfall event are presented. The observed phenomenon occurs as a two‐layer linear depolarization ratio (LDR) signature in a single radar bright band. Doppler spectra observations show that the upper LDR layer is caused by the melting of ice needles, potentially generated by the rime‐splintering process, while the lower one is mainly due to the melting of background ice particles formed at the cloud top. The melting signal of small needles acts as a unique benchmark for detecting the onset of melting and is used to verify the current methods for the identification of melting layer boundaries. The radar‐derived characteristics of the melting layer are found to be dependent on the radar variable and frequency used. The implications of the presented findings for radar‐based studies of precipitation properties in and above the melting layer are also discussed.

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Section: Observationsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Two Layers of Melting Ice Particles Within a Single Radar Bright Band: Interpretation and Implications

Moisseev

2020

Geophysical Research Letters

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“…Riming is an important snow growth process and has an impact on the physical properties of ice particles (Barthazy & Schefold, 2006; Erfani & Mitchell, 2016; Grazioli et al., 2015; Li et al., 2018; Moisseev et al., 2017). Riming can also impact the microphysical properties of the melting layer (Li & Moisseev, 2020; Li et al., 2020; Mroz et al., 2020) and rainfall below the melting layer (Lin et al., 2020; Sarma et al., 2016). Furthermore, riming is affected by anthropogenic aerosols (Borys et al., 2003; Jackson et al., 2012), which is also supported by the ECHAM4 general circulation model simulations (Lohmann, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the rime mass fraction (FR) was introduced and predicted in the predicted particle properties (P3) microphysical scheme, which can continuously quantify the degree of riming (Morrison & Grabowski, 2008; Morrison & Milbrandt, 2014). Previous studies have used FR to quantify the riming degree using ground‐based observations (Kneifel & Moisseev, 2020; Li et al., 2018, 2020; Moisseev et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Assessing the Effect of Riming on Snow Microphysics: The First Observational Study in East China

et al. 2021

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Through the collision and freezing of supercooled droplets on the surface of snow particles, riming can change the density, fall velocity and aspect ratio of snow particles. Riming plays an important role in the formation of precipitation in cold clouds. To our knowledge, the impact of riming on snow microphysics is yet well understood, and there is a lack of observations obtained in China addressing this issue. For the first time in East China, the connection between riming and snow microphysical properties was investigated quantitatively during snow events in two winters. To quantify the degree of riming, the rime mass fraction (FR) is derived using the combination of a 2‐D video disdrometer (2DVD) and a weighing gauge. FR is added to the density‐diameter and fall velocity‐diameter relations, and a quantitative relation between riming and shapes of snowflakes is established based on the in situ observation of the 2DVD. The results show that riming can well explain the variability in the density and fall velocity of snowflakes. The changes in the shape of snowflakes can be divided into two distinct stages with increasing riming: in the initial stage (FR < 0.5), the aspect ratio increases very slowly, while in the later stage (FR > 0.5), the aspect ratio increases rapidly. Direct observations of the continuous changes in the shapes of snowflakes with riming are in good agreement with the retrieval results of radar.

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“…Whilst several studies have looked at the microphysical processes occurring within the melting layer (Drummond et al, 1996) and at the link between microphysical processes in snow above the freezing level and within the melting layer (Zawadzki et al (2005); Li et al (2020) and references therein), less attention has been paid to the analysis of quantitative relationships between ice microphysics just above the freezing level and rain microphysics just below the melting layer. This investigation can contribute to a holistic understanding of the chain of processes occurring in the cloud that lead to precipitation at the ground, which is key for model development but which may also help in better constraining full-column remote sensing retrievals, e.g.…”

Section: Introductionmentioning

confidence: 99%

Linking rain into ice microphysics across the melting layer in stratiform rain: a closure study

Mróz¹,

Battaglia²,

Kneifel³

et al. 2020

Preprint

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Abstract. This study investigates the link between rain and ice microphysics across the melting layer in stratiform rain systems using measurements from vertically pointing multi-frequency Doppler radars. A novel methodology to examine the variability of the precipitation rate and the mass-weighted melted diameter (Dm)across the melting region is proposed and applied to a 6 h-long case study, observed during the TRIPEx-pol field campaign at the Julich Observatory for Cloud Evolution Core Facility and covering a gamut of ice microphysical processes. The methodology is based on an optimal estimation (OE) retrieval of particle size distributions (PSD) and dynamics (turbulence and vertical motions) from observed multi-frequency radar Doppler spectra applied both above and below the melting layer. The retrieval is first applied in the rain region; based on a one-to-one conversion of raindrops into snowflakes, the retrieved Drop Size Distributions (DSD) are propagated upward to provide a first guess for the snow PSDs. These ice PSDs are then used to constrain the OE snow retrieval where Doppler spectra are simulated based on different snow models, which consistently compute fall-speeds and electromagnetic properties. The results corresponding to the best matching models are then used to compute snow fluxes and Dm, which can be directly compared to the corresponding rain quantities. For the case study, the total accumulation of rain (2.65 mm) and the melted equivalent accumulation of snow (2.60 mm) show only a 2 % difference. The analysis suggests that the mass flux through the melting zone is well preserved except the periods of intense aggregation and intense riming where the precipitation rates were respectively larger and lower in ice than in the rain below. Moreover, it is shown that, the mean mass weighted diameter of ice is strongly related to the characteristic size of the underlying rain. With a simple scaling, Dmice = 1.21Dmrain, the characteristic size of snow can be predicted with a root-mean-square-error of 0.12 mm. This formula leads to slight underestimation of the ice size during aggregation, potentially due to the breakup of melting snowflakes, and to overestimation during riming where the additional particle growth within the melting layer cannot be unambiguously attributed to one process. The proposed methodology can be applied to long-term observations to advance our knowledge of the processes occurring across the melting region; this can then be used to improve assumptions underpinning space-borne radar precipitation retrievals.

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

Cited by 4 publications

References 47 publications

Two Layers of Melting Ice Particles Within a Single Radar Bright Band: Interpretation and Implications

Two Layers of Melting Ice Particles Within a Single Radar Bright Band: Interpretation and Implications

Assessing the Effect of Riming on Snow Microphysics: The First Observational Study in East China

Linking rain into ice microphysics across the melting layer in stratiform rain: a closure study

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