A novel, flexible framework is proposed for parameterizing the heterogeneous nucleation of ice within clouds. It has empirically derived dependencies on the chemistry and surface area of multiple species of ice nucleus (IN) aerosols. Effects from variability in mean size, spectral width, and mass loading of aerosols are represented via their influences on surface area. The parameterization is intended for application in largescale atmospheric and cloud models that can predict 1) the supersaturation of water vapor, which requires a representation of vertical velocity on the cloud scale, and 2) concentrations of a variety of insoluble aerosol species.Observational data constraining the parameterization are principally from coincident field studies of IN activity and insoluble aerosol in the troposphere. The continuous flow diffusion chamber (CFDC) was deployed. Aerosol species are grouped by the parameterization into three basic types: dust and metallic compounds, inorganic black carbon, and insoluble organic aerosols.Further field observations inform the partitioning of measured IN concentrations among these basic groups of aerosol. The scarcity of heterogeneous nucleation, observed at humidities well below water saturation for warm subzero temperatures, is represented. Conventional and inside-out contact nucleation by IN is treated with a constant shift of their freezing temperatures.The empirical parameterization is described and compared with available field and laboratory observations and other schemes. Alternative schemes differ by up to five orders of magnitude in their freezing fractions (Ϫ30°C). New knowledge from future observational advances may be easily assimilated into the scheme's framework. The essence of this versatile framework is the use of data concerning atmospheric IN sampled directly from the troposphere.
An updated version of the spectral (bin) microphysics cloud model developed at the Hebrew University of Jerusalem [the Hebrew University Cloud Model (HUCM)] is described. The model microphysics is based on the solution of the equation system for size distribution functions of cloud hydrometeors of seven types (water drops, plate-, columnar-, and branch-like ice crystals, aggregates, graupel, and hail/frozen drops) as well as for the size distribution function of aerosol particles playing the role of cloud condensational nuclei (CCN). Each size distribution function contains 33 mass bins. The conditions allowing numerical reproduction of a narrow droplet spectrum up to the level of homogeneous freezing in deep convective clouds developed in smoky air are discussed and illustrated using as an example Rosenfeld and Woodley's case of deep Texas clouds. The effects of breakup on precipitation are illustrated by the use of a new collisional breakup scheme. Variation of the microphysical structure of a melting layer is illustrated by using the novel melting procedure. It is shown that an increase in the aerosol concentration leads to a decrease in precipitation from single clouds both under continental and maritime conditions. To provide similar precipitation, a cloud developed in smoky air should have a higher top height. The mechanisms are discussed through which aerosols decrease precipitation efficiency. It is shown that aerosols affect the vertical profile of the convective heating caused by latent heat release.
Most atmospheric motions of different spatial scales and precipitation are closely related to phase transitions in clouds. The continuously increasing resolution of large-scale and mesoscale atmospheric models makes it feasible to treat the evolution of individual clouds. The explicit treatment of clouds requires the simulation of cloud microphysics. Two main approaches describing cloud microphysical properties and processes have been developed in the past four and a half decades: bulk microphysics parameterization and spectral (bin) microphysics (SBM). The development and utilization of both represent an important step forward in cloud modeling. This study presents a detailed survey of the physical basis and the applications of both bulk microphysics parameterization and SBM. The results obtained from simulations of a wide range of atmospheric phenomena, from tropical cyclones through Arctic clouds using these two approaches are compared. Advantages and disadvantages, as well as lines of future development for these methods are discussed.
Landscapes influence precipitation via the water vapor and energy fluxes they generate. Biologically active landscapes also generate aerosols containing microorganisms, some being capable of catalyzing ice formation and crystal growth in clouds at temperatures near 0 °C. The resulting precipitation is beneficial for the growth of plants and microorganisms. Mounting evidence from observations and numerical simulations support the plausibility of a bioprecipitation feedback cycle involving vegetated landscapes and the microorganisms they host. Furthermore, the evolutionary history of ice nucleation-active bacteria such as Pseudomonas syringae supports that they have been part of this process on geological time scales since the emergence of land plants. Elucidation of bioprecipitation feedbacks involving landscapes and their microflora could contribute to appraising the impact that modified landscapes have on regional weather and biodiversity, and to avoiding inadvertent, negative consequences of landscape management.
Measured ice crystal concentrations in natural clouds at modest supercooling (temperature ;.2108C) are often orders of magnitude greater than the number concentration of primary ice nucleating particles. Therefore, it has long been proposed that a secondary ice production process must exist that is able to rapidly enhance the number concentration of the ice population following initial primary ice nucleation events. Secondary ice production is important for the prediction of ice crystal concentration and the subsequent evolution of some types of clouds, but the physical basis of the process is not understood and the production rates are not well constrained. In November 2015 an international workshop was held to discuss the current state of the science and future work to constrain and improve our understanding of secondary ice production processes. Examples and recommendations for in situ observations, remote sensing, laboratory investigations, and modeling approaches are presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.