ALBERT

Description: 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 large-scale 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 (−30°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.

Description: Toward the end of the Cirrus Regional Study of Tropical Anvils and Cirrus Layer–Florida Area Cirrus Experiment (CRYSTAL–FACE) field campaign held during July 2002, high concentrations of Saharan dust, which can serve as cloud condensation nuclei (CCN), giant CCN (GCCN), and ice-forming nuclei (IFN) were observed over the peninsula of Florida. To investigate the impacts of enhanced aerosol concentrations on the characteristics of convective storms and their subsequent anvil development, sensitivity tests are conducted using the Regional Atmospheric Modeling System (RAMS) model, in which the initialization profiles of CCN, GCCN, and IFN concentrations are varied. These variations are found to have significant effects on the storm dynamics and microphysical processes, as well as on the surface precipitation. Updrafts are consistently stronger as the aerosol concentrations are increased. The anvils cover a smaller area but are better organized and have larger condensate mixing ratio maxima in the cases with greater aerosol concentrations. Cloud water mass tends to increase with increasing aerosol concentrations, with enhanced GCCN concentrations having the most significant influence. Increasing either the GCCN or IFN concentrations produces the most rainfall at the surface whereas enhanced CCN concentrations reduce surface rainfall. Higher IFN concentrations produce ice at warmer temperatures and deeper anvils, but simultaneously increasing the concentrations of CCN and GCCN leads to more supercooled liquid water available for freezing and greater ice mixing ratios. Graupel mixing ratios decrease and hail mixing ratios increase with increasing aerosol concentrations. Higher concentrations of GCCN and IFN result in greater accumulated surface precipitation initially. By the end of the simulation period, however, the accumulated precipitation is the greatest for the case in which the aerosol concentrations are lowest. Such changes in the dynamical and microphysical characteristics of convective storms as a result of the variations in aerosol concentrations have potential climate consequences, both through cloud radiative effects and the hydrological cycle. The impacts of varying CCN, GCCN, and IFN concentrations on the anvils will be discussed more fully in Part II.

Description: Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate and regional models have generally proven unsuccessful at simulating Arctic cloudiness, particularly during the colder months. Specifically, models tend to underpredict the amount of liquid water in mixed-phase clouds. The Mixed-Phase Arctic Cloud Experiments (M-PACE), conducted from late September through October 2004 in the vicinity of the Department of Energy's Atmospheric Radiation Measurement (ARM) North Slope of Alaska field site, focused on characterizing low-level Arctic stratus clouds. Ice nuclei (IN) measurements were made using a continuous-flow ice thermal diffusion chamber aboard the University of North Dakota's Citation II aircraft. These measurements indicated IN concentrations that were significantly lower than those used in many models. Using the Regional Atmospheric Modeling System (RAMS), we show that these low IN concentrations, as well as inadequate parameterizations of the depletion of IN through nucleation scavenging, may be partially responsible for the poor model predictions. Moreover, we show that this can lead to errors in the modeled surface radiative energy budget of 10–100 Wm−2. Finally, using the measured IN concentrations as input to RAMS and comparing to a mixed-phase cloud observed during M-PACE, we show excellent agreement between modeled and observed liquid water content and net infrared surface flux.