On the forward modeling of radar Doppler spectrum width from LES: Implications for model evaluation.

Large-eddy simulations of an observed single-layer Arctic mixed-phase cloud are analyzed to study the value of forward modeling of profiling millimeter-wave cloud radar Doppler spectral width for model evaluation. Individual broadening terms and their uncertainties are quantified for the observed spectral width and compared to modeled broadening terms. Modeled turbulent broadening is narrower than the observed values when the turbulent kinetic energy dissipation rate from the subgrid-scale model is used in the forward model. The total dissipation rates, estimated with the subgrid-scale dissipation rates and the numerical dissipation rates, agree much better with both the retrieved dissipation rates and those inferred from the power spectra of the simulated vertical air velocity. The comparison of the microphysical broadening provides another evaluative measure of the ice properties in the simulation. To accurately retrieve dissipation rates as well as each broadening term from the observations, we suggest a few modifications to previously presented techniques. First, we show that the inertial subrange spectra filtered with the radar sampling volume is a better underlying model than the unfiltered -5/3 law for the retrieval of the dissipation rate from the power spectra of the mean Doppler velocity. Second, we demonstrate that it is important to filter out turbulence and remove the layer-mean reflectivity-weighted mean fall speed from the observed mean Doppler velocity to avoid overestimation of shear broadening. Finally, we provide a method to quantify the uncertainty in the retrieved dissipation rates, which eventually propagates to the uncertainty in the microphysical broadening.

Seasonal and spatial variations of magnetic susceptibility and potentially toxic elements (PTEs) in road dusts of Thessaloniki city, Greece: A one-year monitoring period.

A one-year sampling campaign of road dusts was carried out at 10 distinct sites in the broader area of the city of Thessaloniki, Greece and concentrations of heavy metals (HMs) along with magnetic susceptibility were evaluated. The concentrations of HMs in road dusts were higher than their local background values, while magnetic parameters indicated a significant anthropogenic load. Principal component analysis (PCA) identified non-exhaust vehicular emissions, oil/fuel combustion and industrial activities as major sources of heavy metals accounted for approximately 73% of the total variance. A significant seasonal variability for Cr, Cu, Mn, and χlf was observed with constantly higher values during summer. Moreover, variations among urban and industrial sites were more pronounced for Cr, Cu, Zn, and χlf, while they displayed insignificant variations across all urban sites. On the contrary, concentration peaks in the urban cluster were observed for Cd, Mn, and Ni coinciding with the port area. Based on multiple pollution indices, a severe polluted area was revealed, while potential ecological risk index (RI) indicated a high potential ecological risk with Cd being regarded as the pollutant of high concern. The health risk assessment model indicated ingestion as the major exposure pathway. For both adults and children, Cr and Pb had the highest risk values, mainly recorded in the urban cluster underscoring the need of potential measures to reduce road dust in urban environments.

Use of cloud radar Doppler spectra to evaluate stratocumulus drizzle size distributions in large-eddy simulations with size-resolved microphysics.

A case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated with an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 µm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.