Monday, 23 January 2017
4E (Washington State Convention Center )
Steven Michael Naegele
, Pennsylvania State University/Significant Opportunities in Atmospheric Research and Science, University Park, PA; and T. Eidhammer
, G. Thompson, M. R. Kumjian
, and D. J. Stensrud
Northeast winter cyclones (“nor’easters”) can produce large amounts of snow that have the potential to economically cripple coastal cities. However, inaccurate forecasts of nor’easter snowbands can cause cities to prepare for an extreme snow event that never happens. One source of uncertainty in snowband forecasting is the treatment of microphysical processes in parameterization schemes used in numerical models, including the representation of riming of snow crystals. In the Thompson microphysics scheme, snow mass is converted to graupel when the riming rate exceeds the depositional growth rate, and the proportion of snow mass converted to graupel is a function of the ratio of those process rates. To test the sensitivity of accumulated snowfall and storm structure to this parameterization, simulations of the 26-27 January 2015 nor’easter and its associated snowbands were performed using the Weather Research and Forecasting model with two different treatments of riming efficiency in the Thompson microphysics scheme.
When the riming parameterization was altered to convert more snow mass to graupel at riming to depositional growth ratios larger than 1:1, more snow accumulated over the western and eastern ends of Long Island, New York by the end of the nor’easter event, even though observed snowfall was primarily in eastern Long Island. Though both simulations had lower reflectivity values in the main snowband and had slower snowband translation compared to dual-polarization radar and vertically-pointing radar, the simulation with more efficient riming conversion had a faster-moving snowband compared to the simulation with the original riming conversion and had up to 25% more snow in the eastern and western ends of Long Island. Thermodynamic profiles, moisture budgets and microphysical process rates for the simulations were examined to determine the physical reasons for the differences in snowband translation and accumulated snow coverage. The changes in simulated snow accumulation and radar reflectivity indicated that the parameterization of riming in Thompson microphysics can affect where heavy snowfall occurs within the domains of numerical models as well as the habit of the simulated frozen hydrometeors, thus affecting forecast accuracy of the snowbands associated with nor’easters.
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