Impact of aerosols on the microphysical processes within a seeder-feeder orographic cloud environment

Cloud nucleating aerosols have been found to modify the amount and spatial distribution of snowfall in mountainous areas where riming growth of snow crystals is known to contribute substantially to the total snow water equivalent precipitation. In the Park Range of Colorado, a 2km deep supercooled liquid water orographic cloud frequently enshrouds the mountaintop during snowfall events. This leads to a seeder-feeder growth regime in which snow falls through the orographic cloud and collects cloud water prior to surface deposition. The addition of higher concentrations of cloud condensation nuclei (CCN) modifies the cloud droplet spectrum toward smaller size droplets and suppresses riming growth. Without rime growth, the density of snow crystals remains low and horizontal trajectories carry them further downwind due to slower vertical fall speeds. This leads to a downwind shift in snowfall accumulation at high CCN concentrations.

The potential for significant modification of snowfall accumulation in the seeder-feeder environment depends upon the cloud liquid water content, mean cloud droplet size, snowfall rate, ice water content, environmental temperature and supersaturation, vapor deposition rate, the Bergeron process, and the size and lifetime of the orographic cloud. Changes in these microphysical processes can substantially alter the amount of riming growth of snow crystals and snowfall accumulation. Cloud resolving model simulations were performed (at 600m horizontal grid spacing) for several snowfall events over the Park Range. The chosen events were well simulated and occurred during intensive observations periods as part of two winter field campaigns in 2007 and 2010 based at Storm Peak Laboratory in Steamboat Springs, CO. For each event, sensitivity simulations were run with various initial CCN concentration vertical profiles that represent clean to very-polluted aerosol environments. Microphysical budget analyses were performed for these simulations in order to determine the relative importance of the various cloud properties and growth processes that contribute to precipitation production. Microphysics diagnostic tools were used to sample an array of grid points within the supercooled orographic cloud to establish trends relating the variability in the aerosol effects due to specific changes in the liquid and ice clouds. By determining the range of environmental conditions, droplet size thresholds, LWC, and snowfall rates that lead to minimum and maximum riming modification, we have been able to create a matrix of conditions that allow for a prediction of potential precipitation modification by CCN aerosols for a given orographic precipitation scenario.