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This study explores the potential of using Doppler (power) spectra from vertically pointing C-band radar birdbath scans to investigate precipitating clouds above the radar. First, the new birdbath scan strategy for the network of dual-polarization C-band radars operated by the German Meteorological Service (Deutscher Wetterdienst, DWD) is outlined, and a novel spectral postprocessing and analysis method is presented. The postprocessing algorithm isolates the weather signal from non-meteorological contributions in the radar output based on polarimetric attributes, identifies the statistically significant precipitation modes contained in each Doppler spectrum, and calculates characteristics of every precipitation mode as well as multimodal properties that describe the relation among different modes when more than a single mode is identified. To achieve a high degree of automation and flexibility, the postprocessing chain combines classical signal processing with clustering algorithms. Uncertainties in the calculated modal and multimodal properties are estimated from the small variations associated with smoothing the measured radar signal. The analysis of five birdbath scans recorded at different radar sites and for various precipitation conditions delivers reliable profiles of the derived modal and multimodal properties for two snowfall cases and for stratiform precipitation above and below the melting layer. To help identify the dominant precipitation growth mechanism, Doppler spectra from DWD's birdbath scans can be used to retrieve the typical degree of riming for individual snow modes. Here, the automatically identified snow modes span a wide range of riming conditions with estimated rime mass fractions (RMFs) of up to RMF>0.5. The evaluation of Doppler spectra inside the melting layer and for an intense frontal shower, with observed radar reflectivities of up to about 40 dBZ, occasionally shows erroneously identified precipitation modes and spurious results for the calculated higher-order Doppler moments of skewness and kurtosis. Nonetheless, the Doppler spectra from DWD's operational C-band radar birdbath scan provide a detailed view into the precipitating clouds and allow for calculating a high-resolution profile of radar reflectivity, mean Doppler velocity, and spectral width even in intense frontal precipitation. [ABSTRACT FROM AUTHOR]

Clouds in the mixed-phase temperature regime impose a large uncertainty onto climate prediction models, in part due to incomplete knowledge of the degree of glaciation affecting cloud radiative properties. To achieve a better representation of these clouds, it is crucial to improve the understanding of ice nucleation and growth as well as microphysical properties determining the cloud phase. In this case study, we provide a rare data set of aircraft in situ measurements in a strong midlatitude convective system extending from the boundary layer to the tropopause and aim to extend the sparse database of such measurements. Data were obtained with the research aircraft HALO and cloud properties were probed with the Cloud and Aerosol Spectrometer (CAS-DPOL) and the Cloud Imaging Probe grayscale (CIPg) during the CIRRUS-HL mission above Southern Germany in July 2021. Microphysical properties of the convective cloud system were measured along a 58-minute stepwise descent between the ground weather stations of Hohenpeissenberg and Munich at temperatures of -35 °C, -23 °C, -13 °C, -7 °C, and -1 °C. A phase identification (liquid/ice) of particles with diameters > 50 µm was achieved using the particle images of the CIPg. Based on recent work, clouds were categorized into four groups with different microphysical properties: Mostly Liquid, Coexistence, Secondary Ice, and Large Ice. High concentrations of large ice crystals were observed in upper layers at temperatures between -35 °C and -13 °C, confirming the importance of the Wegener-Bergeron-Findeisen process for mid-latitude convection. Exceptionally high vertical motions for mid-latitudes of up to +/- 4 ms-1 encountered in the convection promote various freezing and ice growth processes, which in this system led to high ice water contents of up to ~ 1.2 gm-3 and to instrument icing. In contrast, low-level clouds near -1 °C encountered at lower vertical velocities were predominantly composed of liquid droplets and contained precipitated large ice in low concentrations. We find that mechanisms initiating ice nucleation and growth strongly depend on temperature, relative humidity, and vertical velocity and variate within the cloud system. Our measurements represent a unique in-flight data set on microphysical cloud properties of a strong midlatitude convective event and invite for detailed cloud model evaluations and radar intercomparisons with focus on the mixed-phase temperature regime. [ABSTRACT FROM AUTHOR]

Cloud and precipitation processes are still a main source of uncertainties in numerical weather prediction and climate change projections. The Priority Programme "Polarimetric Radar Observations meet Atmospheric Modelling (PROM)", funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis that many uncertainties relate to the lack of observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Such observations can, however, at present be provided by the recently installed dual-polarization C-band weather radar network of the German national meteorological service in synergy with cloud radars and other instruments at German supersites and similar national networks increasingly available worldwide. While polarimetric radars potentially provide valuable in-cloud information on hydrometeor type, quantity, and microphysical cloud and precipitation processes, and atmospheric models employ increasingly complex microphysical modules, considerable knowledge gaps still exist in the interpretation of the observations and in the optimal microphysics model process formulations. PROM is a coordinated interdisciplinary effort to increase the use of polarimetric radar observations in data assimilation, which requires a thorough evaluation and improvement of parameterizations of moist processes in atmospheric models. As an overview article of the inter-journal special issue "Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes", this article outlines the knowledge achieved in PROM during the past 2 years and gives perspectives for the next 4 years. [ABSTRACT FROM AUTHOR]

The snowflake microstructure determines the microwave scattering properties of individual snowflakes and has a strong impact on snowfall radar signatures. In this study, individual snowflakes are represented by collections of randomly distributed ice spheres where the size and number of the constituent ice spheres are specified by the snowflake mass and surface-area-to-volume ratio (SAV) and the bounding volume of each ice sphere collection is given by the snowflake maximum dimension. Radar backscatter cross sections for the ice sphere collections are calculated at X-, Ku-, Ka-, and W-band frequencies and then used to model triple-frequency radar signatures for exponential snowflake size distributions (SSDs). Additionally, snowflake complexity values obtained from high-resolution multi-view snowflake images are used as an indicator of snowflake SAV to derive snowfall triple-frequency radar signatures. The modeled snowfall triple-frequency radar signatures cover a wide range of triple-frequency signatures that were previously determined from radar reflectivity measurements and illustrate characteristic differences related to snow type, quantified through snowflake SAV, and snowflake size. The results show high sensitivity to snowflake SAV and SSD maximum size but are generally less affected by uncertainties in the parameterization of snowflake mass, indicating the importance of snowflake SAV for the interpretation of snowfall triple-frequency radar signatures. [ABSTRACT FROM AUTHOR]

Quantifying snow grain size is crucial to analyze radiative transfer and mechanical interactions in the snow cover. We present a nondestructive method for fast measurements of snow optically equivalent diameter (OED). The method consists of diffuse near-infrared reflectance measurements by a compact integrating sphere setup to derive OED. This principle is realized in the handheld InfraSnow instrument. The correlation between snow OED and reflectance is calculated by applying Monte Carlo ray tracing to a 3-D implementation of the measurement geometry. Including the geometrical boundary conditions is essential to obtain a good agreement between modeled and measured InfraSnow reflectance values. In addition to InfraSnow reflectance, snow density is required as second input parameter to the OED analysis. Our InfraSnow OED measurements agree with reference OED measurements by micro computed tomography (micro-CT) within 25% for seven of the ten tested snow blocks. Furthermore, the relative differences between both measurement methods are close to the estimated uncertainties of the InfraSnow methodology. If density is measured by micro-CT and then used as InfraSnow model input to derive OED, an average agreement with the reference micro-CT OED values within 13% is found. If density is measured by a permittivity sensor, the average agreement is within 20%. [ABSTRACT FROM PUBLISHER]