Understanding the growth of ice particles is critical for predicting the evolution of atmospheric cold clouds. Ice particles are important producers of precipitation of all types (rain, snow, graupel and hail) and have important consequences for the prediction of the radiative budget of the planet. The cirrus clouds that reside in the upper reaches of the troposphere, for instance, cover significant portions of the globe and importantly affect the amount of radiation reaching the surface. The computer models used to forecast clouds and precipitation, and those that simulate the climate require methods to predict the growth of ice. Unfortunately, methods used in computer forecast models for calculating how ice particles grow from water vapor do not allow particle shape to change in time. Ice particles attain different shapes, in part, because the efficiency with which water vapor molecules attach themselves to the ice particle varies over the ice surface. For instance, a pristine hexagonal plate crystal is thin because relatively few water vapor molecules attach to the hexagonal face of the crystal whereas a relatively large number of water vapor molecules attach themselves to the edges. The efficiency with which molecules attach to the hexagonal face is, therefore, low while the efficiency for attachment to the edge of the crystal is high. Calculating these growth efficiencies depends on the amount of water vapor (supersaturation) in the atmosphere, and a "characteristic supersaturation" determines the growth efficiencies. These growth efficiencies are required if the shapes of ice crystals are to change with time in a cloud model, and this process has been missing from computer models. Moreover, data on the growth efficiencies is also needed as input to the computer models. While growth efficiency data exist for temperatures greater than about -30C few data sets exist for temperatures below -30C.

Research conducted under this grant produced a new theoretical method for predicting changes in crystal shapes with time, and a new laboratory device was designed, constructed and used to derive information on the crystal growth efficiency. The laboratory device is unique in that charged ice crystals are levitated electrodynamically during growth. By levitating the crystals we avoid artificial supporting mechanisms that can bias crystal growth measurements. The laboratory-generated data are used to derive the growth efficiencies, and the characteristic supersaturations upon which they depend. These quantities are needed for ice crystal growth calculations. Between temperatures of -31 and -42C we find a range of growth efficiencies varying from high values (near 1) to low values of 0.001, meaning less than 1 molecule in 1000 will attach to the growing crystal. The characteristic supersaturations derived from our growth mesurements can predict these growth efficiencies. These data are used as input to our ice growth method. Our new method for evolving ice particle shapes and predicting growth efficiencies is simple enough that it can be used in computer cloud models. Computer simulations using the new ice growth method have helped to shed light on the evolution of both cirrus clouds and cold, snow producing stratus clouds. Cirrus clouds are radiatively important since the ice crystals that make up those clouds can reflect a significant amount of solar radiation. That solar reflection, however, depends on the number of ice particles in cirrus. Predicting the concentration of ice particles in cirrus is difficult as it depends on the growth efficiency of the ice particles. Our new ice growth method, because it predicts the efficiency of growth, has helped to shed light on the processes controlling ice nucleation in cirrus. Cold stratus clouds are also an important cloud type: They can generate slow and persistent snowfall in mid-latitudes, and have been implicated as important clouds for Arctic climate. Our new ice growth method has shown success in predicting the evolution of dendritic snowflakes and snow precipitation in cold stratus clouds. Moreover, the new ice growth method has provided insight into why these cold, snow producing stratus clouds tend to persist in the Arctic instead of dissipating quickly due to precipitation.

Last Modified: 10/10/2018
Modified by: Jerry Harrington