New Study Looks at How Different Techniques to Model the Hurricane Boundary Layer Can Improve Forecasts

In a new study published in Atmosphere, hurricane scientists looked at how turbulent mixing in the boundary layer affects the intensity and structure of hurricanes in NOAA’s Hurricane Weather Research and Forecasting (HWRF) model. They found that turbulent mixing affects where thunderstorms in hurricanes occur, and how fast air flows towards the center of a storm.

Knowing what is happening in the atmosphere immediately above the ocean, an area called the boundary layer, is vital for predicting hurricane intensity. While hurricanes can measure hundreds of miles across, the strongest winds usually occur in gusts smaller than 100 yards across, what is known as the turbulent scale. The swirling flow associated with this small area is called turbulent mixing, which is especially important in the boundary layer where it can transport heat and moisture from the ocean below.

However, turbulent-scale features are too small for the HWRF and other models to capture; instead, scientists use parameterization to estimate the strength of turbulent mixing. Parameterization is a method used to represent the small-scale processes that can’t be resolved by models. This study reviewed the impact of planetary boundary layer parameterization schemes that have been used in the operational version of HWRF since 2011.

“The horizontal grid spacing of a hurricane forecast model is usually larger than 1 km, but the scales of turbulent eddies can be as small as 10 m,” said Jun Zhang, a hurricane scientist with the Cooperative Institute for Marine and Atmospheric Studies at the University of Miami.

In this study, the HWRF model was run multiple times using five types of parameterization to determine which forecasts were closest to the observations obtained from NOAA’s Hurricane Hunter aircraft. Scientists then looked at how and why different boundary layer parameterization schemes produced different forecasts in the HWRF model.

Image showing differences in the hurricane structure in the region closest to the storm center due to changes in the vertical eddy diffusivity. RMW represents the radius of maximum wind speed, or the eyewall. The light blue arrows show the radial flow. The dark blue arrows show the updrafts and convection. The region below the green line is the boundary layer. Dry and cool biases were identified based on model evaluation against observations. These biases need to be corrected in future model physics upgrades.

Turbulent mixing is controlled by a parameter called the vertical eddy diffusivity. According to Zhang, the vertical eddy diffusivity is a parameter in the forecast model that describes the strength of vertical mixing by the small-scale rotating flow in the atmosphere.

“This study shows the tremendous value in using observations from the unique platform of hurricane hunter aircraft to improve the representation of fundamental physical processes in hurricane models,” said AOML hurricane scientist Robert Rogers.

“This parameter is very important for hurricane intensity forecast,” Zhang said. 

When vertical eddy diffusivity is high, more turbulent mixing occurs. When it is small, less turbulent mixing occurs, and the strongest winds in the model are closer to the center of the storm.

Scientists also determined that turbulent mixing affects where thunderstorms are located in hurricanes. When vertical eddy diffusivity is small, strong thunderstorms in a hurricane tend to be located closer to the center of the storm and further inside the eyewall where the fastest winds occur.

Turbulent mixing can also impact how fast air flows towards the center of a hurricane near the surface, otherwise known as the radial flow, as well as how tall the boundary layer is. This inflow feeds energy from the ocean into the hurricane’s core. When the vertical eddy diffusivity is small, the radial inflow is strong, and the boundary layer is shallow.

These findings emphasize the importance of model physics on hurricane intensity and structure forecasts and will guide model developers to further improve hurricane forecast models. Such improvements have the potential to save lives, reduce property damage, and increase the public’s confidence in NOAA’s official hurricane forecasts and warnings.