Microphysical Impacts to Landfalling Hurricanes
Simulating hurricanes in a regional numerical weather model typically means using grid sizes on the order of 1 kilometer. Getting accurate cloud behavior, then, can be very challenging, especially because particles like ice, snow, hail (called graupel when it is beginning to form), and rain droplets, which make up clouds, are less than 1 millimeter in size. It would take more computer power than is favorable for a computer model to resolve those itty, bitty particles while also resolving phenomenal storms, like hurricanes.
In order to conserve computing energy, we must use what are called “microphysical schemes”. This means that instead of literally simulating every single particle inside our models, then following each one as they evolve in time, we instead represent them mathematically by packing up (or “bulking”) similar particles with each other. However, this method is also limited, as the scientists who develop mathematical microphysical schemes must make certain assumptions about the average particle’s size, density, and distribution. Those assumptions certainly make our computers run faster, but they also add uncertainty into our models.
So, for the type of research that I do currently–improving computer models of hurricanes–this means that we don’t always know how modeled precipitation will depend on the various particles in all of the clouds that make up the storm’s system. In order to investigate such dependencies, my current research investigates the case study of Hurricane Florence (2018), which had a long-lasting period offshore of North Carolina before making landfall on 14 September. Not eager to leave the Carolinas, Florence caused large flooding, with a record of almost 36 inches in Elizabethtown.
To date, my Hurricane Florence simulations have been tested with three different microphysical schemes and produce a range of total rainfall between 30 and 50 inches. Of the three schemes, one distributes particles throughout the simulated hurricane’s outer rainbands, while the other two retain more precipitation within their stormiest inner cores. The scheme with greater particle distribution tends to bulk precipitation closer to the Carolina coastline (more flooding nearest the shore), while the other two microphysics schemes spread heavier precipitation further inland.
The contoured frequency by altitude diagram (CFAD) below shows that this scheme produces a greater mix of rain in the lower atmosphere, while concentrating ice and snow above the melting layer. This can be seen by the range of reflectivity (radar calculations) between about 25 and 50 dBZ below 4.5 km and between 10 and 35 dBZ above. This work is ongoing and will be presented in May 2020 at the AMS Tropical Meteorology conference in New Orleans, so stay tuned for updates!