Turbulence in clouds is known to enhance particle collision rates, as widely demonstrated for warm rain formation. A similar impact on ice growth processes is expected but a solid observational basis ...is missing. A statistical analysis of a 15‐month data set of cloud radar observations allows for the first time to quantify the impact of turbulence on ice aggregation and riming in Arctic low‐level mixed‐phase clouds. Increasing eddy dissipation rate (EDR), from below 10−4 to above 10−3 m2 s−3, yields larger ice aggregates, and higher particle concentration, likely caused by increasing fragmentation. In conditions more favorable to riming, higher EDR is associated with dramatically higher particle fall velocities (by up to 125%), under similar liquid water paths, indicative of markedly higher degrees of riming. Our findings thus reveal the key role of turbulence for cold precipitation formation, and highlight the need for an improved understanding of turbulence‐hydrometeor interactions in cold clouds.
Plain Language Summary
Liquid and frozen precipitation mainly forms by collision and subsequent aggregation of small particles. Collisions between cloud particles, such as droplets and ice crystals, are thought to be increased by turbulence. While this effect has been intensively studied for liquid‐only clouds, the impact of turbulence on ice‐ice collisional growth (aggregation) and ice‐liquid collisional growth (riming) is expected but has so far been poorly quantified. We study the effect of turbulence on aggregation and riming based on a long‐term remote‐sensing data set of low‐level clouds containing both ice and liquid particles, recorded at the Arctic site of Ny‐Ålesund, Svalbard. Cloud radar observations are used to retrieve the dissipation rate of turbulent kinetic energy (i.e., the eddy dissipation rate; EDR), which is the relevant quantity driving increases in collision rates, and to characterize ice particle properties. We find evidence that higher EDR regimes enhance the aggregation of particles, and are associated with signatures of increased ice particle concentration, possibly caused by the production of particle fragments upon collision. In temperature regimes more favorable to riming, turbulence dramatically enhances the particles' fall velocity, denoting higher degrees of riming. Our findings thus highlight a key role of turbulence for the formation of precipitable ice.
Key Points
Relation between turbulence and ice growth investigated based on long‐term remote sensing data set of Arctic low‐level mixed‐phase clouds
Higher eddy dissipation rate (EDR) correlates with larger ice aggregates, and possibly higher degrees of fragmentation
High EDR is an essential component needed for the formation of rimed particles
Recently published studies of triple‐frequency radar observations of snowfall have demonstrated that naturally occurring snowflakes exhibit scattering signatures that are in some cases consistent ...with spheroidal particle models and in others can only be explained by complex aggregates. Until recently, no in situ observations have been available to investigate links between microphysical snowfall properties and their scattering properties. In this study, we investigate for the first time relations between collocated ground‐based triple‐frequency observations with in situ measurements of snowfall at the ground. The three analyzed snowfall cases obtained during a recent field campaign in Finland cover light to moderate snowfall rates with transitions from heavily rimed snow to open‐structured, low‐density snowflakes. The observed triple‐frequency signatures agree well with the previously published findings from airborne radar observations. A rich spatiotemporal structure of triple‐frequency observations throughout the cloud is observed during the three cases, which often seems to be related to riming and aggregation zones within the cloud. The comparison of triple‐frequency signatures from the lowest altitudes with the ground‐based in situ measurements reveals that in the presence of large (>5 mm) snow aggregates, a bending away in the triple‐frequency space from the curve of classical spheroid scattering models is always observed. Rimed particles appear along an almost horizontal line in the triple‐frequency space, which was not observed before. Overall, the three case studies indicate a close connection of triple‐frequency signatures and snow particle structure, bulk snowfall density, and characteristic size of the particle size distribution.
Key Points
Triple‐frequency radar compared to ground‐based in situ snowfall measurements
Strong relation between PSD/snowfall density and triple‐frequency signatures
Triple‐frequency data also provide a very sensitive measure for riming
Low-level mixed-phase clouds (MPCs) are common in the Arctic. Both local and large-scale phenomena influence the properties and lifetime of MPCs. Arctic fjords are characterized by complex terrain ...and large variations in surface properties. Yet, not many studies have investigated the impact of local boundary layer dynamics and their relative importance on MPCs in the fjord environment. In this work, we used a combination of ground-based remote sensing instruments, surface meteorological observations, radiosoundings, and reanalysis data to study persistent low-level MPCs at Ny-Ålesund, Svalbard, for a 2.5-year period. Methods to identify the cloud regime, surface coupling, and regional and local wind patterns were developed. We found that persistent low-level MPCs were most common with westerly winds, and the westerly clouds had a higher mean liquid (42 g m−2) and ice water path (16 g m−2) compared to those with easterly winds. The increased height and rarity of persistent MPCs with easterly free-tropospheric winds suggest the island and its orography have an influence on the studied clouds. Seasonal variation in the liquid water path was found to be minimal, although the occurrence of persistent MPCs, their height, and their ice water path all showed notable seasonal dependency. Most of the studied MPCs were decoupled from the surface (63 %–82 % of the time). The coupled clouds had 41 % higher liquid water path than the fully decoupled ones. Local winds in the fjord were related to the frequency of surface coupling, and we propose that katabatic winds from the glaciers in the vicinity of the station may cause clouds to decouple. We concluded that while the regional to large-scale wind direction was important for the persistent MPC occurrence and properties, the local-scale phenomena (local wind patterns in the fjord and surface coupling) also had an influence. Moreover, this suggests that local boundary layer processes should be described in models in order to present low-level MPC properties accurately.
Vertically pointing radar observations combining multiple frequencies and Doppler measurements have been recently shown to contain valuable information about ice particle growth processes, such as ...aggregation and riming. In this study, we use a two‐months X, Ka, W‐Band Doppler radar dataset of midlatitude winter clouds to infer statistical growth signatures of ice and snow particles. The observational statistics are compared to forward‐simulated radar moments based on simulations of the campaign time period with a high‐resolution version of the ICON model and a two‐moment microphysical scheme. The statistical comparison shows very good agreement of the simulated vertical structure of radar reflectivity and surface precipitation rate. The dual‐wavelength ratios, which are closely related to the mean particle size, also show consistently a major increase at temperatures higher than –15 °C. However, at temperatures higher than –7 °C, ICON increasingly overestimates the mean particle size. The statistics of mean Doppler velocities also reveal that the model overestimates the terminal velocity of snow particles, especially at larger sizes. We discuss possible reasons for the identified discrepancies, such as an unrealistic temperature dependence of the sticking efficiency or the non‐saturation of terminal velocities at larger sizes caused by the implemented power law relations. Our study demonstrates examples of the importance of combining various radar techniques for identifying issues in simulated microphysical processes, which can otherwise be hidden due to compensating errors.
Numerical weather prediction model output is compared with multi‐frequency Doppler radar observations. The statistical comparison reveals discrepancies in the cloud structure that suggest the presence of some inaccuracies in the modelled ice properties. The study demonstrates the importance of combining various radar techniques (such as multi‐frequency and Doppler) for revealing these discrepancies which otherwise might remain hidden by the effect of compensating errors.
Computer simulations of the aggregation and riming of ice crystals are performed to investigate the geometry of rimed aggregate snowflakes. Due to the universality of the geometry of aggregates, the ...conversion to a graupel‐like particle is self‐similar and independent from specific properties of the aggregate, when formulated in properly normalized variables. Hence, the particle habit of the primary crystals, the size of the aggregate or the density of the rime mass, does not lead to a structural change in the transition to graupel. Therefore, this transition can be parameterized by a similarity approach using simulations of many individual rimed aggregates. These parameterizations can replace the classic fill‐in model used in many cloud models. The parameterizations are applied and tested in a one‐dimensional Lagrangian superparticle model to simulate the growth of aggregates in a liquid layer. We find that the similarity model for the geometry of rimed snowflakes leads to a more rapid growth by riming and, hence, an increased precipitation rate compared to the fill‐in model. The main reason for this is that the increase of the maximum dimension during the early stages of riming is properly taken into account by the similarity model, whereas it is neglected by the fill‐in model.
Plain Language Summary
We have simulated the growth of snowflakes by using a computer model. In a first step, snowflakes grow by collisions with small ice crystals and between each other. The resulting snowflakes have a fractal geometry. In a second step, we let them collide with small spheres that mimic the cloud droplets in a cloud that contains ice as well as liquid. The collision with the cloud droplets makes the snowflakes more and more spherical, but they never become perfect spheres. We are interested in this change in the shape of the snowflakes during these different growth stages. The geometry of the snowflakes can be described by the relationship between their mass, their diameter, and their projected area. We suggest some simple mathematical formulas to calculate these geometrical properties for a given mass. Knowing the geometry, we can then estimate the fall speed of the snowflakes. Then we use yet another model to simulate the interaction of many snowflakes under typical conditions in the atmosphere. We show that the assumed geometry of the snowflakes is important for the amount of precipitation that reaches the ground.
Key Points
Simulations of individual particles grown by aggregation and riming are presented
New parameterization for geometry and terminal fall velocity of rimed snowflake aggregates are derived
Size growth during riming has a significant impact on the precipitation rate
Abstract
Riming is an efficient process of converting liquid cloud water into ice and plays an important role in the formation of precipitation in cold clouds. Due to the rapid increase in ice ...particle mass, riming enhances the particle’s terminal velocity, which can be detected by ground-based vertically pointing cloud radars if the effect of vertical air motions can be sufficiently mitigated. In our study, we first revisit a previously published approach to relate the radar mean Doppler velocity (MDV) to rime mass fraction (FR) using a large ground-based in situ dataset. This relation is then applied to multiyear datasets of cloud radar observations collected at four European sites covering polluted central European, clean maritime, and Arctic climatic conditions. We find that riming occurs in 1%–8% of the nonconvective ice containing clouds with median FR between 0.5 and 0.6. Both the frequency of riming and FR reveal relatively small variations for different seasons. In contrast to previous studies, which suggested enhanced riming for clean environments, our statistics indicate the opposite; however, the differences between the locations are overall small. We find a very strong relation between the frequency of riming and temperature. While riming is rare at temperatures lower than −12°C, it strongly increases toward 0°C. Previous studies found a very similar temperature dependence for the amount and droplet size of supercooled liquid water, which might be closely connected to the riming signature found in this study. In contrast to riming frequency, we find almost no temperature dependence for FR.
This study analyzes the effect of snow particle orientation on polarization differences (PDs) observed with a ground‐based radiometer at 150 GHz on the basis of a 1 year time series of snowfall ...observations. The observations performed on Mount Zugspitze (German Alps) at 2650 meters above sea level reveal that brightness temperature (TB) differences between vertical and horizontal polarizations reach up to −10 K at an elevation angle of 34.8° during snowfall. The analysis of 458 h of snowfall data shows that PDs can be explained by the occurrence of oriented snow particles and supports the potential role of polarization measurements for improved retrievals of snowfall microphysical parameters. The dependence of measured PD and TB on integrated K band radar reflectivity (at 24.1 GHz) and independently derived cloud liquid water path (LWP) has been analyzed. The higher snow water path (SWP) indicated by high values of integrated reflectivity enhances both TB and PD because of the scattering of snow particles. TBs are also found to increase during snowfall when supercooled liquid water is present. The increase of LWP enhances the TB but damps the PD resulting from oriented snow particles. To evaluate the effects of SWP and LWP on PD and TB, radiative transfer simulations assuming horizontally aligned snow oblates using a radiative transfer model have been carried out. PD and TB observations can be captured well by the model given realistic assumptions on mass size relationship and aspect ratio of the oriented snow oblates.
Key Points
Polarization difference observed with ground‐based radiometry during snowfall
Snow/liquid water effects on polarization difference and brightness temperature
Polarization difference explained by oriented snow particles
This paper investigates the influence of snow microphysical parameters on the enhancement of ground‐based passive microwave brightness temperature (TB) measurements. In addition to multispectral ...passive microwave observations between 20 and 150 GHz, a 35 GHz cloud radar and a 2‐D video disdrometer for in situ measurements of snowfall were deployed as part of the “towards an optimal estimation‐based snowfall characterization algorithm” campaign in the winter season of 2008–2009 at an Alpine environment located at 2650 m mean sea level. These observations are combined with nearby radiosonde ascents and surface standard meteorological measurements to reconstruct the atmospheric state (i.e., fields of temperature, humidity, snow, and liquid water contents) and are subsequently used as input for a microwave radiative transfer (RT) model. We investigate the sensitivity of the missing information about snow shape and snow particle size distribution (SSD) on the microwave TB measurements using the disdrometer data as a rough constraint. For an extended case study, we found that TBs at 90 and 150 GHz are significantly enhanced because of scattering of surface radiation at snow crystals and that this enhancement is clearly correlated with the radar derived snow water path (SWP < 0.2 kg m−2). RT simulations highlight the strong influence of the vertical distribution of cloud liquid water (liquid water path LWP < 0.1 kg m−2) on the TB, which in extreme cases, can fully obscure the snow scattering signal. TB variations of the same magnitude can also be caused by typical variations in SSD parameters and particle shape similar to results obtained by space‐borne studies. Ground‐based stations with their infrastructural capabilities in combining active and passive microwave observations have the potential to disentangle the influences of different snow shape, SSD, and SWP in snow retrievals, thus supporting current and future satellite missions.
A retrieval for characteristic raindrop size and width of the drop size distribution (DSD) based on triple‐frequency vertical Doppler radar measurements is developed. The algorithm exploits a ...statistical relation that maps measurements of the differential Doppler velocities at X and Ka and at Ka and W bands into the two aforementioned DSD moments. The statistical mapping has been founded on 7,900 hr of disdrometer‐observed DSDs and their simulated Doppler velocities. Additionally, a retrieval of
Dm based only on
DDVX−W measurements is also presented, and its performance is compared to the analogous algorithm exploiting
DDVKa−W data. The retrievals are tested using triple‐frequency radar data collected during a recent field campaign held at the Juelich Observatory for Cloud Evolution (JOYCE, Germany) where in situ measurements of the DSD were carried out only few meters away from the vertically pointing radars. The triple‐frequency retrieval is able to obtain
Dm with an uncertainty below 25% for
Dm ranging from 0.7 to 2.4 mm. Compared to previously published dual‐frequency retrievals, the third frequency does not improve the retrieval for small
Dm (
<1.4 mm). However, it significantly surpasses the
DDVKa−W algorithm for larger
Dm (20% versus 50% bias at 2.25 mm). Also compared to
DDVX−W method, the triple‐frequency retrieval is found to provide an improvement of 15% in terms of bias for
Dm=2.25 mm. The triple‐frequency retrieval of
σm performs with an uncertainty of 20–50% for
0.2<σm<1.3 mm, with the best performance for
0.25<σm<0.8 mm.
Key Points
A triple‐frequency Doppler retrieval for the shape and size of the drop size distribution is developed using 7,900 hr of disdrometer data
The triple‐frequency Doppler algorithm outperforms the dual‐frequency Doppler methodologies in retrieving large characteristic DSD sizes
The uncertainty of the triple‐frequency methodology for retrieving the characteristic DSD size does not exceed 25% for
0.75<Dm<2.4 mm
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