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.
Large-eddy simulations (LES) with the newThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. R. Heinze et al.at building confidence in the model's ability to simulate small-to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small-to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.
Atmospheric reanalyses covering the European region are mainly available as part of relatively coarse global reanalyses. The aim of this article is to present the development and evaluation of a next generation regional reanalysis for the European CORDEX EUR-11 domain with a horizontal grid spacing of approximately 6 km. In this context, a reanalysis is understood to be an assimilation of heterogeneous observations with a physical model such as a numerical weather prediction (NWP) model. The reanalysis system presented here is based on the NWP model COSMO by the German Meteorological Service (Deutscher Wetterdienst) using a continuous nudging scheme. In order to assess the added value of data assimilation, a dynamical downscaling experiment has been conducted, i.e. an identical model set-up but without data assimilation. Both systems have been evaluated for a 1 year test period, employing standard measures such as analysis increments, biases, or log-odds ratios, as well as tests for distributional characteristics. An important aspect is the evaluation from different perspectives and with independent measurements such as satellite infrared brightness temperatures using forward operators, integrated water vapour from GPS stations, and ceilometer cloud cover. It can be shown that the reanalysis better resolves local extreme events; this is basically an effect of the higher spatio-temporal resolution, as known from dynamical downscaling approaches. However, an important criterion for regional reanalyses is the coherence with independent observations of high temporal and spatial resolution, resulting in significant improvement over dynamical downscaling. The system is intended to become operational within a year, continuously reprocessing and evaluating longer time periods. The reanalysis data are planned to become available to the research community within a year.
[1] Backscattering and extinction properties of various snow particle models are studied for three typical cloud radar frequency ranges, namely K u band, K a band, and W band, both in terms of their individual scattering properties as well as averaged over size distributions. Models studied include soft spheres, randomly oriented pristine nonspherical particles and complex aggregates, as well as horizontally aligned spheroids. It is shown that the concurrent use of K u /K a band and K a /W band dual wavelength ratios (DWR) allows for a separation of different snow particle habits. It is further shown that triple-frequency approaches constrain the slope parameter of exponential size distributions more tightly than conventional single DWR approaches can. Uncertainties introduced by unknown mass-size relations for different snow particle habits remain a challenge when mass-related quantities are to be derived. Attenuation by snow, especially at W band, is found to potentially alter these results, albeit moderately, without affecting the general conclusions. Sensitivity studies performed with respect to cutoffs in the simulated size distribution highlight potential benefits of including larger particles in future scattering databases.Citation: Kneifel, S., M. S. Kulie, and R. Bennartz (2011), A triple-frequency approach to retrieve microphysical snowfall parameters,
Abstract. A new comprehensive cloud–precipitation–meteorological observatory has been established at Princess Elisabeth base, located in the escarpment zone of Dronning Maud Land (DML), East Antarctica. The observatory consists of a set of ground-based remote-sensing instruments (ceilometer, infrared pyrometer and vertically profiling precipitation radar) combined with automatic weather station measurements of near-surface meteorology, radiative fluxes, and snow height. In this paper, the observatory is presented and the potential for studying the evolution of clouds and precipitating systems is illustrated by case studies. It is shown that the synergetic use of the set of instruments allows for distinguishing ice, liquid-containing clouds and precipitating clouds, including some information on their vertical extent. In addition, wind-driven blowing snow events can be distinguished from deeper precipitating systems. Cloud properties largely affect the surface radiative fluxes, with liquid-containing clouds dominating the radiative impact. A statistical analysis of all measurements (in total 14 months mainly during summer–beginning of winter) indicates that these liquid-containing clouds occur during as much as 20% of the cloudy periods. The cloud occurrence shows a strong bimodal distribution with clear-sky conditions 51% of the time and complete overcast conditions 35% of the time. Snowfall occurred during 17% of the cloudy periods with a predominance of light precipitation and only rare events with snowfall >1 mm h−1 water equivalent (w.e.). Three of such intense snowfall events occurred during 2011 contributing to anomalously large annual surface mass balance (SMB). Large accumulation events (>10 mm w.e. day−1) during the radar-measurement period of 26 months were always associated with snowfall, but at the same time other snowfall events did not always lead to accumulation. The multiyear deployment of a precipitation radar in Antarctica allows for assessing the contribution of the snowfall to the local SMB and comparing it to the other SMB components. During 2012, snowfall rate was 110 ± 20 mm w.e. yr−1, from which surface and drifting snow sublimation removed together 23%. Given the measured yearly SMB of 52 ± 3 mm w.e., the residual term of 33 ± 21 mm w.e. yr−1 was attributed to the wind-driven snow erosion. In general, this promising set of robust instrumentation allows for improved insight into cloud and precipitation processes in Antarctica and can be easily deployed at other Antarctic stations.
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