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Abstract. It is a challenge to obtain accurate measurements of the microphysical properties of delicate, structurally complex, frozen, and semi-frozen hydrometeors. We present a new technique for the real-time measurement of the density of freshly fallen individual snowflakes. A new thermal-imaging instrument, the Differential Emissivity Imaging Disdrometer (DEID), has been shown through laboratory and field experiments to be capable of providing accurate estimates of individual snowflake and bulk snow hydrometeor density (which can be interpreted as the snow-to-liquid ratio or SLR). The method exploits the rate of heat transfer during the melting of a hydrometeor on a heated metal plate, which is a function of the temperature difference between the hotplate surface and the top of the hydrometeor. The product of the melting speed and melting time yields an effective particle thickness normal to the hotplate surface, which can then be used in combination with the particle mass and area on the plate to determine a particle density. Uncertainties in estimates of particle density are approximately 4 % based on calibrations with laboratory-produced particles made from water and frozen solutions of salt and water and field comparisons with both high-resolution imagery of falling snow and traditional snowpack density measurements obtained at 12 h intervals. For 17 storms, individual particle densities vary from 19 to 495 kg m−3, and storm mean snow densities vary from 40 to 100 kg m−3. We observe probability distribution functions for hydrometeor density that are nearly Gaussian with kurtosis of ≈ 3 and skewness of ≈ 0.01. 

We use a novel experimental setup to obtain the vertical velocity and acceleration statistics of snowflakes settling in atmospheric surface-layer turbulence, for Taylor microscale Reynolds numbers (Reλ) between 400 and 67 000, Stokes numbers (St) between 0.12 and 3.50, and a broad range of snowflake habits. Despite the complexity of snowflake structures and the non-uniform nature of the turbulence, we find that mean snowflake acceleration distributions can be uniquely determined from the value of St. Ensemble-averaged snowflake root mean square (rms) accelerations scale nearly linearly with St. Normalized by the rms value, the acceleration distribution is nearly exponential, with a scaling factor for the (exponent) of −3/2 that is independent of Reλ and St; kurtosis scales with Reλ, albeit weakly compared to fluid tracers in turbulence; gravitational drift with sweeping is observed for St < 1. Surprisingly, the same exponential distribution describes a pseudo-acceleration calculated from fluctuations of snowflake terminal fall speed in still air. This equivalence suggests an underlying connection between how turbulence determines the trajectories of particles and the microphysics determining the evolution of their shapes and sizes. 

Recent works on wall-bounded flows have corroborated the coexistence of wall-attached eddies, whose statistical features are predicted through Townsend's attached-eddy hypothesis (AEH), and very-large-scale motions (VLSMs). Furthermore, it has been shown that the presence of wall-attached eddies within the logarithmic layer is linked to the appearance of an inverse-power-law region in the streamwise velocity energy spectra, upon significant separation between outer and viscous scales. In this work, a near-neutral atmospheric surface layer is probed with wind light detection and ranging to investigate the contributions to the streamwise velocity energy associated with wall-attached eddies and VLSMs for a very-high-Reynolds-number boundary layer. Energy and linear coherence spectra (LCS) of the streamwise velocity are interrogated to identify the spectral boundaries associated with eddies of different typologies. Inspired by the AEH, an analytical model for the LCS associated with wall-attached eddies is formulated. The experimental results show that the identification of the wall-attached-eddy energy contribution through the analysis of the energy spectra leads to an underestimate of the associated spectral range, maximum height attained and turbulence intensity. This feature is due to the overlap of the energy associated with VLSMs obscuring the inverse-power-law region. The LCS analysis estimates wall-attached eddies with a streamwise/wall-normal ratio of about 14.3 attaining a height of about 30 % of the outer scale of turbulence. 

Data from the Idealized Planar-Array experiment for Quantifying Spatial heterogeneity are used to perform a control volume analysis (400 × 400 × × 2 m^3) on the total derivative of the temperature tendency equation. Analysis of the heat-flux imbalance, which is defined as the ratio of the sum of advective, dispersive, and turbulence-flux terms to the turbulence-flux term, are presented. Results are divided amongst free-convective and forced-convective days, as well as high-wind-speed and quiescent nocturnal periods. Findings show that the median flux imbalance is greater on forced-convective days (a 168% turbulence-flux overestimation, or relative importance of the advection to dispersive flux to the turbulence flux) when compared to free-convective periods (79% turbulence-flux overestimation). During nocturnal periods, a median turbulence-flux underestimation of 146% exists for quiescent nights and a 43% underestimation of the flux for high-wind-speed nights. These results support the existing literature, suggesting that mean air-temperature heterogeneities lead to strong bulk advection and dispersive fluxes. A discussion of the impact of the flux imbalance on the surface energy balance and numerical-weather-prediction modelling is presented. 

A microscale wildfire model, QES-Fire, that dynamically couples the fire front to microscale winds was developed using a simplified physics rate of spread (ROS) model, a kinematic plume-rise model and a mass-consistent wind solver. The model is three-dimensional and couples fire heat fluxes to the wind field while being more computationally efficient than other coupled models. The plume-rise model calculates a potential velocity field scaled by the ROS model’s fire heat flux. Distinct plumes are merged using a multiscale plume-merging methodology that can efficiently represent complex fire fronts. The plume velocity is then superimposed on the ambient winds and the wind solver enforces conservation of mass on the combined field, which is then fed into the ROS model and iterated on until convergence. QES-Fire’s ability to represent plume rise is evaluated by comparing its results with those from an atmospheric large-eddy simulation (LES) model. Additionally, the model is compared with data from the FireFlux II field experiment. QES-Fire agrees well with both the LES and field experiment data, with domain-integrated buoyancy fluxes differing by less than 17% between LES and QES-Fire and less than a 10% difference in the ROS between QES-Fire and FireFlux II data. 

Abstract. The Differential Emissivity Imaging Disdrometer (DEID) is a new evaporation-based optical and thermal instrument designed to measure the mass, size, density and type of individual hydrometeors as well as their bulk properties. Hydrometeor spatial dimensions are measured on a heated metal plate using an infrared camera by exploiting the much higher thermal emissivity of water compared with metal. As a melted hydrometeor evaporates, its mass can be directly related to the loss of heat from the hotplate assuming energy conservation across the hydrometeor. The heat loss required to evaporate a hydrometeor is found to be independent of environmental conditions including ambient wind velocity, moisture level and temperature. The difference in heat loss for snow vs. rain for a given mass offers a method for discriminating precipitation phase. The DEID measures hydrometeors at sampling frequencies of up to 1 Hz with masses and effective diameters greater than 1 µg and 200 µm, respectively, determined by the size of the hotplate and the thermal camera specifications. Measurable snow water equivalent (SWE) precipitation rates range from 0.001 to 200 mm h−1, as validated against a standard weighing bucket. Preliminary field experiment measurements of snow and rain from the winters of 2019 and 2020 provided continuous automated measurements of precipitation rate, snow density and visibility. Measured hydrometeor size distributions agree well with canonical results described in the literature. 

Abstract. A new precipitation sensor, the Differential Emissivity Imaging Disdrometer (DEID), is used to provide the first continuous measurements of the mass, diameter, and density of individual hydrometeors. The DEID consists of an infrared camera pointed at a heated aluminum plate. It exploits the contrasting thermal emissivity of water and metal to determine individual particle mass by assuming that energy is conserved during the transfer of heat from the plate to the particle during evaporation. Particle density is determined from a combination of particle mass and morphology. A Multi-Angle Snowflake Camera (MASC) was deployed alongside the DEID to provide refined imagery of particle size and shape. Broad consistency is found between derived mass–diameter and density–diameter relationships and those obtained in prior studies. However, DEID measurements show a generally weaker dependence with size for hydrometeor density and a stronger dependence for aggregate snowflake mass.