Ice-Phase Precipitation

Abstract

Ice-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed.

Cloud Condensation Nuclei Activity and Hygroscopicity of Fresh and Aged Biomass Burning Particles

“…Aerosol and cloud interactions directly influence the cloud microphysical process, thus leading to changes of spatio-temporal distribution of precipitation, rather than on the globally-averaged amount of precipitation . Gultepe and Isaac (1999) and Gultepe et al (2017) stated that no unique relationship exists between aerosols and cloud particles unless variability is considered, and their influence for precipitation is quite uncertain.…”

A Comparative Study of Bin and Bulk Cloud Microphysics Schemes in Simulating a Heavy Precipitation Case

“…This study shows that a more appropriate representation of microphysical processes in bin microphysics scheme than in bulk microphysics schemes can contribute to more accurate prediction in this real precipitation case. Therefore, certain oversimplified assumptions in treating microphysical processes of traditional bulk microphysics schemes (e.g., ignoring the terminal velocities of cloud droplets and ice crystals and the collision between cloud droplets and ice crystals) need to be revised and constrained by detailed observations [48] to improve the performance of bulk microphysics schemes. This can help better understanding and prediction of precipitation.…”

“…There are relatively less studies that report reliable observational statistics on the hydrometeor number concentration. Because the hydrometeor number concentration is used to estimate a representative size of particles that is essential for calculating microphysical processes, these large uncertainties in predicting hydrometeor number concentration should be improved in future studies (e.g., [48]). It was discussed in Figures 6 and 7 that the bin microphysics scheme exhibits a larger latent heat release by deposition and riming compared to the examined bulk microphysics schemes and that this increased latent heat release enhances vertical motion.…”

Comparisons of bin and bulk microphysics schemes in simulations of topographic winter precipitation with radar and radiometer measurements

“…It manifests as a bimodal distribution for large aggregates, which is artificial and not supported by observations or theory (e.g. Sekhon and Srivastava, ; Hallet and Mossop, ; Srivastava and Coen, ; Woods et al ., ; Gultepe et al ., ). Its likely cause is the parametrization of particle breakup in the bin scheme, which will be examined later through a sensitivity test (EnBr).…”