Paper on how dry air interacts with clouds in the cores of tropical cyclones published in Geophysical Research Letters – Hurricane Research Division3 min read
Hurricane Hunter aircraft measurements and numerical simulations from the Hurricane Weather Research and Forecast and new Hurricane Analysis and Forecast System models show that the air outside of the eyewall and rainbands entrained into the eyewall and rainbands meets an instability criterion, and therefore, sinks unstably as a convective downdraft. This is an important source for turbulent kinetic energy (TKE) in the eyewall and rainbands and is therefore important for intensity forecasts. This process should therefore be included in computer forecast models.
Figure 1: (a) Selected NOAA Hurricane Hunter flight legs through the eyewall and rainbands of Hurricane Michael (2018). (b) – (e): Relative humidity, water vapor mixing ratio (the percentage of the air that is made up of water vapor), equivalent potential temperature (a measure of the energy in the air), and wind speed, respectively, with distance (radius) from the TC center at ~ 750 hPa from one of the flight legs.
Turbulence is rapidly changing wind across small distances. It is important in tropical cyclones (TCs) because turbulence in the lowest 1-2 km of the atmosphere and in clouds affects TC intensity and structure by impacting how much warm, moist air that fuels the TC flows into it at low levels. The size of the turbulence is sometimes less than 100 meters across, or about the length of a football field.
We use computer models to forecast the weather, including tropical cyclones. These models forecast the weather on grids with the distance between points much larger than the size of the turbulence. This means that the models themselves cannot predict turbulence. Thus, turbulence is estimated in the models using what we call parameterization schemes.
An important measure of how much turbulence exists is turbulence kinetic energy (TKE), or the amount of energy in the turbulence. Turbulence at the edges of clouds can bring dry air from outside the clouds into them (what we call lateral entrainment). When precipitation falls from clouds, it cools. This cool air sinks in what we call downdrafts which can generate TKE. This study used Hurricane Hunter aircraft measurements in the eyewalls and rainbands of Hurricanes Rita (2005), Patricia (2015), Harvey (2017), and Michael (2018), and computer simulations of Patricia (2015) and Michael (2018) to look at how lateral entrainment causes the downdrafts and generates TKE. An example of flight-level data in Hurricane Michael (2018) is shown in Fig. 1, with black lines showing radial flight legs that penetrated the eyewall and cloud regions. An example of some data from one leg (panels b-e) is also shown; panels b-c show that the humidity, mixing ratio, and equivalent potential temperature are lower outside the rain areas (pink bars) than inside them. All the data used in this study are shown in Fig. 2, indicating that the lateral entrainment instability almost always occurs. We recommend including this process in parameterization schemes in numerical forecasts of TCs.
Figure 2: Difference in equivalent potential temperature (∆e) between the eyewall/rainbands and the moat (outside the eyewall/rainbands) regions versus the corresponding instability criterion ∆q/α for flight legs into Hurricanes Rita (2005), Patricia (2015), Harvey (2017), and Michael (2018). The inset panel is zoomed into the upper-right portion of the plot.
- Hurricane Hunter aircraft measurements show temperature and moisture variations (instability) at the edges of the TC eyewall and rainbands large enough to create TKE.
- Computer forecast models show that this instability is important in TC intensity predictions and should be included in parameterization schemes.
For more information, contact email@example.com. The study can be found at https://doi.org/10.1029/2022GL102494. This work is supported by NOAA/HFIP under the Grant NA18NWS4680057, NOAA/JTTI under the Grant NA22OAR4590177, and National Science Foundation under the Grants 2211307 and 2211308.
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