Modeling Precipitation in the Ross Island Region, Antarctica Using Assimilated Observational Data

To observe weather parameters across the Ross Island region in Antarctica it is necessary to deploy automated observational units. To measure precipitation, we have deployed acoustic depth gauges (ADG) on board Antarctic Automatic Weather Station units (AWS). Unfortunately, the actual snow precipitation amount, implied from the depth measurements, tends to be ambiguous. In the long term, we hope to use data assimilation of these measurements to allow a sophisticated mesoscale model employing explicit ice simulation to define the spatial variability and amounts of precipitation implied by these measurements. In order to assimilate depth measurements, it will be necessary for the model to reasonably simulate the observed depth changes with model physics. In this study, we have been developing methodologies to simulate snow spray due to ground level winds, and the associated displacement of snow cover. We can then evaluate and develop the model to represent the ground truth measured directly by the ADGs. This talk will focus on the preliminary work of this data assimilation, as well as the beginning development of an algorithm that will model the snow spray and how it feeds directly into the University of Wisconsin Nonhydrostatic Modeling System (UW-NMS) models' explicit ice microphysics prediction scheme. Comparisons of the results with ADG measurements will be presented.