Towards the connection between snow microphysics and melting layer : insights from multifrequency and dual-polarization radar observations during BAECC

In stratiform rainfall, the melting layer (ML) is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the ML and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured ML properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide new insights into radar signatures of snow growth processes, we have investigated this link This study is divided into two parts. Firstly, surface-based snowfall measurements are used to develop a new method for identifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. Secondly, this classification is used in combination with multifrequency and dual-polarization radar observations collected during the Biogenic Aerosols - Effects on Clouds and Climate (BAECC) experiment in 2014 to investigate the impact of precipitation intensity, aggregation, riming and dendritic growth on the ML properties. The results show that the radar-observed ML properties are highly related to the precipitation intensity. The previously reported bright band "sagging" is mainly connected to the increase in precipitation intensity. Ice particle riming plays a secondary role. In moderate to heavy rainfall, riming may cause additional bright band sagging, while in light precipitation the sagging is associated with unrimed snow. The correlation between ML properties and dual-polarization radar signatures in the snow region above appears to be arising through the connection of the radar signatures and ML properties to the precipitation intensity. In addition to advancing our knowledge of the link between ML properties and snow processes, the presented analysis demonstrates how multifrequency Doppler radar observations can be used to get a more detailed view of cloud processes and establish a link to precipitation formation.Peer reviewe

Comprehensive T-Matrix Reference Database: A 2007-2009 Update

The T-matrix method is among the most versatile, efficient, and widely used theoretical techniques for the numerically exact computation of electromagnetic scattering by homogeneous and composite particles, clusters of particles, discrete random media, and particles in the vicinity of an interface separating two half-spaces with different refractive indices. This paper presents an update to the comprehensive database of T-matrix publications compiled by us previously and includes the publications that appeared since 2007. It also lists several earlier publications not included in the original database

Global Scale Impacts

Global scale impacts modify the physical or thermal state of a substantial fraction of a target asteroid. Specific effects include accretion, family formation, reshaping, mixing and layering, shock and frictional heating, fragmentation, material compaction, dilatation, stripping of mantle and crust, and seismic degradation. Deciphering the complicated record of global scale impacts, in asteroids and meteorites, will lead us to understand the original planet-forming process and its resultant populations, and their evolution in time as collisions became faster and fewer. We provide a brief overview of these ideas, and an introduction to models.Comment: A chapter for Asteroids IV, a new volume in the Space Science Series, University of Arizona Press (Patrick Michel, Francesca E. DeMeo, William F. Bottke, Eds.

Simulation and sensitivity analysis for cloud and precipitation measurements via spaceborne millimeter-wave radar

This study presents a simulation framework for cloud and precipitation measurements via spaceborne millimeter-wave radar composed of eight submodules. To demonstrate the influence of the assumed physical parameters and to improve the microphysical modeling of the hydrometeors, we first conducted a sensitivity analysis. The results indicated that the radar reflectivity was highly sensitive to the particle size distribution (PSD) parameter of the median volume diameter and particle density parameter, which can cause reflectivity variations of several to more than 10 dB. The variation in the prefactor of the mass–power relations that related to the riming degree may result in an uncertainty of approximately 30 %–45 %. The particle shape and orientation also had a significant impact on the radar reflectivity. The spherical assumption may result in an average overestimation of the reflectivity by approximately 4 %–14 %, dependent on the particle type, shape, and orientation. Typical weather cases were simulated using improved physical modeling, accounting for the particle shapes, typical PSD parameters corresponding to the cloud precipitation types, mass–power relations for snow and graupel, and melting modeling. We present and validate the simulation results for a cold-front stratiform cloud and a deep convective process with observations from a W-band cloud profiling radar (CPR) on the CloudSat satellite. The simulated bright band features, echo structure, and intensity showed a good agreement with the CloudSat observations; the average relative error of radar reflectivity in the vertical profile was within 20 %. Our results quantify the uncertainty in the millimeter-wave radar echo simulation that may be caused by the physical model parameters and provide a scientific basis for optimal forward modeling. They also provide suggestions for prior physical parameter constraints for the retrieval of the microphysical properties of clouds and precipitation.</p