We generated a large number 105,000 of aggregates composed of various monomer types and sizes using an aggregation model. Combined with hydrodynamic theory, we derived ice particle properties such as ...mass, projected area, and terminal velocity as a function of monomer number and size. This particle ensemble allows us to study the relation of particle properties with a high level of detail which is often not provided by in situ measurements. The ice particle properties change rather smoothly with monomer number. We find very little differences in all particle properties between monomers and aggregates at sizes below 1 mm which is in contrast to many microphysics schemes. The impact of the monomer type on the particle properties decreases with increasing monomer number. Whether, for example, the terminal velocity of an aggregate is larger or smaller than an equal‐size monomer depends mostly on the monomer type. We fitted commonly used power laws as well as Atlas‐type relations, which represent the saturation of the terminal velocity at large sizes (terminal velocity asymptotically approaching a limiting value) to the data set and tested the impact of incorporating different levels of complexity with idealized simulations using a 1D Lagrangian super particle model. These simulations indicate that it is sufficient to represent the monomer number dependency of ice particle properties with only two categories (monomers and aggregates). The incorporation of the saturation velocity at larger sizes is found to be important to avoid an overestimation of self‐aggregation of larger snowflakes.
Plain Language Summary
We have simulated and analyzed the properties, such as mass, area, and terminal fall velocity of snowflakes using a computer model. The snowflakes in the atmosphere form by collisions of ice crystals present in many different shapes. In the computer model, ice crystal shapes typically found in the atmosphere are stuck together to create three‐dimensional snowflakes. The properties of the snowflakes depend on the shape and the number of ice crystals that are stuck together. While in weather and climate models, the properties of ice crystals and snowflakes are often assumed to be very different even if they are of the same size, we find very little differences in their properties. Many weather and climate models assume that snowflakes have a higher fall velocity the larger they are, although field observations have shown that particles larger than a few millimeters all fall with similar velocity. We fitted new parameterizations of the particle velocities which can remove this deficiency in the models. Finally, we used another model and showed that it might be sufficient to divide the properties of the ice particles in only two categories. However, it is important to consider the almost constant velocity of the large snowflakes.
Key Points
We simulated aggregates to study the impact of monomer number and type onice particle properties
Ice particle properties show a smooth transition from monomers to aggregates
The saturation of terminal velocity needs to be taken into account when simulating snow aggregation
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.
The intensity and phase of precipitation at the ground surface can have important implications not only for meteorological and hydrological situations but also in terms of hazards and risks. In the ...field, Thies disdrometers are sometimes used to monitor the quantity and nature of precipitation with high temporal resolution and very low maintenance and thus provide valuable information for the management of meteorological and hydrological risks. Here, we evaluate the Thies disdrometer with respect to precipitation detection, as well as the estimation of precipitation intensity and phase at a pre-alpine site in Switzerland (1060 m a.s.l.), using a weighing precipitation gauge (OTT pluviometer) and a two-dimensional video disdrometer (2DVD) as a reference. We show that the Thies disdrometer is well suited to detect even light precipitation, reaching a hit rate of around 95 %. However, the instrument tends to systematically underestimate rainfall intensities by 16.5 %, which can be related to a systematic underestimation of the number of raindrops with diameters between 0.5 and 3.5 mm. During snowfall episodes, a similar underestimation is observed in the particle size distribution (PSD), which is, however, not reflected in intensity estimates, probably due to a compensation by snow density assumptions. To improve intensity estimates, we test PSD adjustments (to the 2DVD) and direct adjustments of the resulting intensity estimates (to the OTT pluviometer), the latter of which are able to successfully reduce the systematic deviations during rainfall in the validation period. For snowfall, the combination of the 2DVD and the OTT pluviometer seems promising as it allows for improvement of snow density estimates, which poses a challenge to all optical precipitation measurements. Finally, we show that the Thies disdrometer and the 2DVD agree well insofar as the distinction between rain and snowfall is concerned, such that an important prerequisite for the proposed correction methods is fulfilled. Uncertainties mainly persist during mixed-phase precipitation or low precipitation intensities, where the assignment of precipitation phase is technically challenging, but less relevant for practical applications. We conclude that the Thies disdrometer is suitable not only to estimate precipitation intensity but also to distinguish between rain and snowfall. The Thies disdrometer therefore seems promising for the improvement of precipitation monitoring and the nowcasting of discharge in pre-alpine areas, where considerable uncertainties with respect to these quantities are still posing a challenge to decision-making.
In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the ...examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81∘ N.
Excellent agreement (difference less than 1 %) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45 % and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73∘ N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.
Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)(3) project was established in 2016 (www.ac3-tr.de/). It comprises modeling and ...data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric-ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
We have developed an algorithm that retrieves the size, number concentration and density of falling snow from multifrequency radar observations. This work builds on previous studies that have ...indicated that three-frequency radars can provide information on snow density, potentially improving the accuracy of snow parameter estimates. The algorithm is based on a Bayesian framework, using lookup tables mapping the measurement space to the state space, which allows fast and robust retrieval. In the forward model, we calculate the radar reflectivities using recently published snow scattering databases. We demonstrate the algorithm using multifrequency airborne radar observations from the OLYMPEX–RADEX field campaign, comparing the retrieval results to hydrometeor identification using ground-based polarimetric radar and also to collocated in situ observations made using another aircraft. Using these data, we examine how the availability of multiple frequencies affects the retrieval accuracy, and we test the sensitivity of the algorithm to the prior assumptions. The results suggest that multifrequency radars are substantially better than single-frequency radars at retrieving snow microphysical properties. Meanwhile, triple-frequency radars can retrieve wider ranges of snow density than dual-frequency radars and better locate regions of high-density snow such as graupel, although these benefits are relatively modest compared to the difference in retrieval performance between dual- and single-frequency radars. We also examine the sensitivity of the retrieval results to the fixed a priori assumptions in the algorithm, showing that the multifrequency method can reliably retrieve snowflake size, while the retrieved number concentration and density are affected significantly by the assumptions.
In this study measurements collected during winters 2013/2014 and 2014/2015 at the University of Helsinki measurement station in Hyytiala are used to investigate connections between ensemble mean ...snow density, particle fall velocity and parameters of the particle size distribution (PSD). The density of snow is derived from measurements of particle fall velocity and PSD, provided by a particle video imager, and weighing gauge measurements of precipitation rate. Validity of the retrieved density values is checked against snow depth measurements. A relation retrieved for the ensemble mean snow density and median volume diameter is in general agreement with previous studies, but it is observed to vary significantly from one winter to the other. From these observations, characteristic mass- dimensional relations of snow are retrieved. For snow rates more than 0.2mm/h, a correlation between the intercept parameter of normalized gamma PSD and median volume diameter was observed.
Radar-based snowfall intensity retrieval is investigated at
centimeter and millimeter wavelengths using co-located
ground-based multi-frequency radar and video-disdrometer observations. Using data ...from four snowfall events, recorded
during the Biogenic Aerosols Effects on Clouds and Climate (BAECC) campaign in Finland, measurements of
liquid-water-equivalent snowfall rate S are correlated to radar equivalent reflectivity factors Ze,
measured by the Atmospheric Radiation Measurement (ARM) cloud radars operating at X, Ka and W frequency bands. From these
combined observations, power-law Ze–S relationships are derived for all three frequencies considering
the influence of riming. Using microwave radiometer observations of liquid water path, the measured precipitation is
divided into lightly, moderately and
heavily rimed snow. Interestingly lightly rimed snow events show a spectrally distinct
signature of Ze–S with respect to moderately or heavily rimed snow cases. In order to understand the
connection between snowflake microphysical and multi-frequency backscattering properties, numerical simulations are
performed by using the particle size distribution provided by the in situ video disdrometer and retrieved ice particle
masses. The latter are carried out by using both the T-matrix method (TMM) applied to soft-spheroid particle models
with different aspect ratios and exploiting a pre-computed discrete dipole approximation (DDA) database for rimed
aggregates. Based on the presented results, it is concluded that the soft-spheroid approximation can be adopted to
explain the observed multi-frequency Ze–S relations if a proper spheroid aspect ratio is selected. The
latter may depend on the degree of riming in snowfall. A further analysis of the backscattering simulations reveals that
TMM cross sections are higher than the DDA ones for small ice particles, but lower for larger particles. The differences of computed cross sections for larger and smaller particles are compensating for each other. This may explain why the soft-spheroid approximation is satisfactory for radar reflectivity simulations under study.
Abstract Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC) 3 project was established in 2016 ( www.ac3-tr.de/ ). It comprises ...modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric–ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
The attenuation of spheroidal melting hydrometeors is simulated in C-, Ku- and Ka-band utilizing a microphysical melting layer model. The scattering properties are obtained with Mie scattering ...solution. In C-band the polarimetric radar parameters are computed utilizing a method based on volume integral equation. Polarization difference is detectable, but reflectivity values are regularly smaller than those calculated with Mie solution. This is dependent on the process of formatting the particle structure according to the change in liquid water mass fraction.
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