Herein the authors introduce the Snowflake Video Imager (SVI), which is a new instrument for characterizing frozen precipitation. An SVI utilizes a video camera with sufficient frame rate, pixels, and shutter speed to record thousands of snowflake images. The camera housing and lighting produce little airflow distortion, so SVI data are quite representative of natural conditions, which is important for volumetric data products such as snowflake size distributions. Long-duration, unattended operation of an SVI is feasible because datalogging software provides data compression and the hardware can operate for months in harsh winter conditions. Details of SVI hardware and field operation are given. Snowflake size distributions (SSDs) from a storm near Boulder, Colorado, are computed. An SVI is an imaging system, so SVI data can be utilized to compute diverse data products for various applications. In this paper, the authors present visualizations of frozen particles (i.e., snowflake aggregates as well as individual crystals), which provide insight into the weather conditions such as temperature, humidity, and winds.

Based on theoretical analysis and laboratory data, we proposed a unified two-parameter wave spectral model as $\phi(n) = \frac{\beta g^2}{n^m n_0^{5-m}} {\rm exp} \left\{-\frac{m}{4}\left(\frac{n_0}{n}\right)^4\right\}$ with β and m as functions of the internal parameter, the significant slope η of the wave field which is defined as $\sect = \frac{(\overline{\zeta^2})^{\frac{}1{2}}}{\lambda_0},$ where $\overline{\zeta^2}$ is the mean squared surface elevation, and λ₀, n₀ are the wavelength and frequency of the waves at the spectral peak. This spectral model is independent of local wind. Because the spectral model depends only on internal parameters, it contains information about fluid-dynamical processes. For example, it maintains a variable bandwidth as a function of the significant slope which measures the nonlinearity of the wave field. And it also contains the exact total energy of the true spectrum. Comparisons of this spectral model with the JONSWAP model and field data show excellent agreements. Thus we established an alternative approach for spectral models. Future research efforts should concentrate on relating the internal parameters to the external environmental variables.

We present an analysis of ring-wave and scatterometer data from a water surface that was agitated by simulated rain. Water droplets of 2.8mm diameter impacted the water surface at almost terminal velocity, and the rain rates cover a wide range of conditions (5 to 200mm hr⁻¹). Both the ring-wave energy and backscattered power from the GHz scatterometer increase as R increases, but the growth rates slacken at higher rain intensities. Ring-wave frequency spectra and wavenumber spectra are well represented by log-Gaussian spectral models. The results can be used to guide development of microwave scattering models.