Figure 8 - uploaded by Stephen R. Guimond
Content may be subject to copyright.
Time series of (a) maximum horizontal windspeed for the LES (green line), coarse simulation with the same diffusion coefficients as the LES (blue line), coarse simulation with h = 20,000 m 2 s-1 and v = 400 m 2 s-1 (black line) and (b) maximum azimuthally averaged horizontal wind speed for the LES (red line) and the coarse simulation with h = 20,000 m 2 s-1 and v = 400 m 2 s-1 .
Source publication
An idealized numerical simulation of the hurricane intensification process at a grid spacing of 60 meters that covers a large region of the hurricane inner-core is presented and analyzed in this paper. While the initial, balanced vortex and properties of the environment (e.g. dry, no shear) are idealized, the simulations are driven by latent heatin...
Contexts in source publication
Context 1
... Ma = rv + 1/2for 2 is the AAM, r is the radius, u, v and w are the radial, tangential and vertical velocity, respectively, fo is the constant Coriolis frequency (5.0×10 -5 s -1 ) and is the density. The overbar and primes denote azimuthal mean and eddy terms, respectively. To focus on the impacts of the resolved dynamics in the intensification process, the strength of the sub-grid diffusion in (3) and (5) should adjust in the large eddy and coarse resolution simulations as a result of the differences in scale. If the diffusion coefficient chosen for the LES (200 m 2 s -1 ) is used in the coarse simulation, then the vortex becomes more intense because energy dissipation isn't an active player in the budget due to the discretization coefficient, ( ∆í µí±¡ ∆í µí±¥ 2 , ∆í µí±¡ ∆í µí± § 2 ). In order for the diffusion terms to play the same role in the coarse simulation, the coefficient must be set to ~ 20,000 m 2 s -1 in the horizontal and 400 m 2 s -1 in the vertical. To examine this effect, two coarse simulations were run: one with the larger diffusion coefficient values and one with the same values as the LES. Figure 8a shows the maximum horizontal wind speed for the LES and the two coarse simulations. After approximately 1 h, the maximum wind speed in the LES becomes much larger than the coarse simulations with values reaching above 120 m s -1 at 3.5 h for short time intervals. This result is similar to that documented in Rotunno et al. (2009) using the WRF ARW model. When examining the maximum azimuthally averaged wind speed (Fig. 8b), the large fluctuations in values are removed but the mean vortex intensity is still higher in the LES by up to ~ 30 % at 3.5 ...
Context 2
... Ma = rv + 1/2for 2 is the AAM, r is the radius, u, v and w are the radial, tangential and vertical velocity, respectively, fo is the constant Coriolis frequency (5.0×10 -5 s -1 ) and is the density. The overbar and primes denote azimuthal mean and eddy terms, respectively. To focus on the impacts of the resolved dynamics in the intensification process, the strength of the sub-grid diffusion in (3) and (5) should adjust in the large eddy and coarse resolution simulations as a result of the differences in scale. If the diffusion coefficient chosen for the LES (200 m 2 s -1 ) is used in the coarse simulation, then the vortex becomes more intense because energy dissipation isn't an active player in the budget due to the discretization coefficient, ( ∆í µí±¡ ∆í µí±¥ 2 , ∆í µí±¡ ∆í µí± § 2 ). In order for the diffusion terms to play the same role in the coarse simulation, the coefficient must be set to ~ 20,000 m 2 s -1 in the horizontal and 400 m 2 s -1 in the vertical. To examine this effect, two coarse simulations were run: one with the larger diffusion coefficient values and one with the same values as the LES. Figure 8a shows the maximum horizontal wind speed for the LES and the two coarse simulations. After approximately 1 h, the maximum wind speed in the LES becomes much larger than the coarse simulations with values reaching above 120 m s -1 at 3.5 h for short time intervals. This result is similar to that documented in Rotunno et al. (2009) using the WRF ARW model. When examining the maximum azimuthally averaged wind speed (Fig. 8b), the large fluctuations in values are removed but the mean vortex intensity is still higher in the LES by up to ~ 30 % at 3.5 ...
Context 3
... highlighting the radius-height structure of the primary and secondary circulations of the simulations as well as the individual terms in (5) have been produced and analyzed. For brevity, only those figures that provide insight into the role of asymmetric dynamics are presented and discussed here. Figure 9 shows the net time tendency term [LHS of (5)], net symmetric flux convergence term [sum of first two terms on RHS of (5)], net asymmetric flux convergence term [sum of third and fourth terms on RHS of (5)] and sub- grid scale diffusion term [last term on RHS of (5)] averaged over height (0 -3 km) and time (2.5 -3.5 h). This time period was chosen due to the significant intensification occurring in the storm (Figs. 8a and 8b) and the height interval was chosen to focus on the low-level dynamics. The coarse simulation with larger diffusion coefficients (Fig. 9a) shows that the time tendency is dominated by the sub-grid scale diffusion with large increases radially inward of ~ 15 km. The net symmetric term also contributes substantially to the time tendency as a result of the heat forcing with peak values slightly inside the RMW at ~ 18 km. The net asymmetric term is slightly negative at most radii and doesn't make much of a contribution to the time tendency. From a physics point of view, the symmetric response to the heating is intensifying and contracting the hurricane, while diffusion is mixing/smoothing the large gradients in AAM, which moves momentum in the downgradient direction (from the eyewall to the ...
Context 4
... the standard downgradient diffusion [Laplacian operator in (3) and (6)] used to model the effects of sub-grid turbulence in the coarse simulation a good approximation of the LES? While the overall trend of spreading AAM from the eyewall to the eye is captured by the Laplacian diffusion, it is clear that complicated, small-scale details in the LES can have important consequences for the mean hurricane. After all, the azimuthal mean wind speed is up to ~ 30 % stronger in the LES for short time integrations of 3.5 h (Fig. 8b). Note that the time tendency of AAM is negative from ~ 18 -25 km radius in the coarse simulation with large diffusion (Fig. 9a) and positive in the same region in the LES (Fig. 9c), which could explain some of the differences in mean intensity. A flow dependent eddy viscosity should improve the modeling of the LES effects. However, the first order turbulence closure assumes that the AAM transport is purely downgradient, which may not be the case in the ...
Context 5
... Ma = rv + 1/2for 2 is the AAM, r is the radius, u, v and w are the radial, tangential and vertical velocity, respectively, fo is the constant Coriolis frequency (5.0×10 -5 s -1 ) and is the density. The overbar and primes denote azimuthal mean and eddy terms, respectively. To focus on the impacts of the resolved dynamics in the intensification process, the strength of the sub-grid diffusion in (3) and (5) should adjust in the large eddy and coarse resolution simulations as a result of the differences in scale. If the diffusion coefficient chosen for the LES (200 m 2 s -1 ) is used in the coarse simulation, then the vortex becomes more intense because energy dissipation isn't an active player in the budget due to the discretization coefficient, ( ∆í µí±¡ ∆í µí±¥ 2 , ∆í µí±¡ ∆í µí± § 2 ). In order for the diffusion terms to play the same role in the coarse simulation, the coefficient must be set to ~ 20,000 m 2 s -1 in the horizontal and 400 m 2 s -1 in the vertical. To examine this effect, two coarse simulations were run: one with the larger diffusion coefficient values and one with the same values as the LES. Figure 8a shows the maximum horizontal wind speed for the LES and the two coarse simulations. After approximately 1 h, the maximum wind speed in the LES becomes much larger than the coarse simulations with values reaching above 120 m s -1 at 3.5 h for short time intervals. This result is similar to that documented in Rotunno et al. (2009) using the WRF ARW model. When examining the maximum azimuthally averaged wind speed (Fig. 8b), the large fluctuations in values are removed but the mean vortex intensity is still higher in the LES by up to ~ 30 % at 3.5 ...
Context 6
... Ma = rv + 1/2for 2 is the AAM, r is the radius, u, v and w are the radial, tangential and vertical velocity, respectively, fo is the constant Coriolis frequency (5.0×10 -5 s -1 ) and is the density. The overbar and primes denote azimuthal mean and eddy terms, respectively. To focus on the impacts of the resolved dynamics in the intensification process, the strength of the sub-grid diffusion in (3) and (5) should adjust in the large eddy and coarse resolution simulations as a result of the differences in scale. If the diffusion coefficient chosen for the LES (200 m 2 s -1 ) is used in the coarse simulation, then the vortex becomes more intense because energy dissipation isn't an active player in the budget due to the discretization coefficient, ( ∆í µí±¡ ∆í µí±¥ 2 , ∆í µí±¡ ∆í µí± § 2 ). In order for the diffusion terms to play the same role in the coarse simulation, the coefficient must be set to ~ 20,000 m 2 s -1 in the horizontal and 400 m 2 s -1 in the vertical. To examine this effect, two coarse simulations were run: one with the larger diffusion coefficient values and one with the same values as the LES. Figure 8a shows the maximum horizontal wind speed for the LES and the two coarse simulations. After approximately 1 h, the maximum wind speed in the LES becomes much larger than the coarse simulations with values reaching above 120 m s -1 at 3.5 h for short time intervals. This result is similar to that documented in Rotunno et al. (2009) using the WRF ARW model. When examining the maximum azimuthally averaged wind speed (Fig. 8b), the large fluctuations in values are removed but the mean vortex intensity is still higher in the LES by up to ~ 30 % at 3.5 ...
Context 7
... highlighting the radius-height structure of the primary and secondary circulations of the simulations as well as the individual terms in (5) have been produced and analyzed. For brevity, only those figures that provide insight into the role of asymmetric dynamics are presented and discussed here. Figure 9 shows the net time tendency term [LHS of (5)], net symmetric flux convergence term [sum of first two terms on RHS of (5)], net asymmetric flux convergence term [sum of third and fourth terms on RHS of (5)] and sub- grid scale diffusion term [last term on RHS of (5)] averaged over height (0 -3 km) and time (2.5 -3.5 h). This time period was chosen due to the significant intensification occurring in the storm (Figs. 8a and 8b) and the height interval was chosen to focus on the low-level dynamics. The coarse simulation with larger diffusion coefficients (Fig. 9a) shows that the time tendency is dominated by the sub-grid scale diffusion with large increases radially inward of ~ 15 km. The net symmetric term also contributes substantially to the time tendency as a result of the heat forcing with peak values slightly inside the RMW at ~ 18 km. The net asymmetric term is slightly negative at most radii and doesn't make much of a contribution to the time tendency. From a physics point of view, the symmetric response to the heating is intensifying and contracting the hurricane, while diffusion is mixing/smoothing the large gradients in AAM, which moves momentum in the downgradient direction (from the eyewall to the ...
Context 8
... the standard downgradient diffusion [Laplacian operator in (3) and (6)] used to model the effects of sub-grid turbulence in the coarse simulation a good approximation of the LES? While the overall trend of spreading AAM from the eyewall to the eye is captured by the Laplacian diffusion, it is clear that complicated, small-scale details in the LES can have important consequences for the mean hurricane. After all, the azimuthal mean wind speed is up to ~ 30 % stronger in the LES for short time integrations of 3.5 h (Fig. 8b). Note that the time tendency of AAM is negative from ~ 18 -25 km radius in the coarse simulation with large diffusion (Fig. 9a) and positive in the same region in the LES (Fig. 9c), which could explain some of the differences in mean intensity. A flow dependent eddy viscosity should improve the modeling of the LES effects. However, the first order turbulence closure assumes that the AAM transport is purely downgradient, which may not be the case in the ...
Context 9
... Ma = rv + 1/2for 2 is the AAM, r is the radius, u, v and w are the radial, tangential and vertical velocity, respectively, fo is the constant Coriolis frequency (5.0×10 -5 s -1 ) and is the density. The overbar and primes denote azimuthal mean and eddy terms, respectively. To focus on the impacts of the resolved dynamics in the intensification process, the strength of the sub-grid diffusion in (3) and (5) should adjust in the large eddy and coarse resolution simulations as a result of the differences in scale. If the diffusion coefficient chosen for the LES (200 m 2 s -1 ) is used in the coarse simulation, then the vortex becomes more intense because energy dissipation isn't an active player in the budget due to the discretization coefficient, ( ∆í µí±¡ ∆í µí±¥ 2 , ∆í µí±¡ ∆í µí± § 2 ). In order for the diffusion terms to play the same role in the coarse simulation, the coefficient must be set to ~ 20,000 m 2 s -1 in the horizontal and 400 m 2 s -1 in the vertical. To examine this effect, two coarse simulations were run: one with the larger diffusion coefficient values and one with the same values as the LES. Figure 8a shows the maximum horizontal wind speed for the LES and the two coarse simulations. After approximately 1 h, the maximum wind speed in the LES becomes much larger than the coarse simulations with values reaching above 120 m s -1 at 3.5 h for short time intervals. This result is similar to that documented in Rotunno et al. (2009) using the WRF ARW model. When examining the maximum azimuthally averaged wind speed (Fig. 8b), the large fluctuations in values are removed but the mean vortex intensity is still higher in the LES by up to ~ 30 % at 3.5 ...
Context 10
... Ma = rv + 1/2for 2 is the AAM, r is the radius, u, v and w are the radial, tangential and vertical velocity, respectively, fo is the constant Coriolis frequency (5.0×10 -5 s -1 ) and is the density. The overbar and primes denote azimuthal mean and eddy terms, respectively. To focus on the impacts of the resolved dynamics in the intensification process, the strength of the sub-grid diffusion in (3) and (5) should adjust in the large eddy and coarse resolution simulations as a result of the differences in scale. If the diffusion coefficient chosen for the LES (200 m 2 s -1 ) is used in the coarse simulation, then the vortex becomes more intense because energy dissipation isn't an active player in the budget due to the discretization coefficient, ( ∆í µí±¡ ∆í µí±¥ 2 , ∆í µí±¡ ∆í µí± § 2 ). In order for the diffusion terms to play the same role in the coarse simulation, the coefficient must be set to ~ 20,000 m 2 s -1 in the horizontal and 400 m 2 s -1 in the vertical. To examine this effect, two coarse simulations were run: one with the larger diffusion coefficient values and one with the same values as the LES. Figure 8a shows the maximum horizontal wind speed for the LES and the two coarse simulations. After approximately 1 h, the maximum wind speed in the LES becomes much larger than the coarse simulations with values reaching above 120 m s -1 at 3.5 h for short time intervals. This result is similar to that documented in Rotunno et al. (2009) using the WRF ARW model. When examining the maximum azimuthally averaged wind speed (Fig. 8b), the large fluctuations in values are removed but the mean vortex intensity is still higher in the LES by up to ~ 30 % at 3.5 ...
Context 11
... highlighting the radius-height structure of the primary and secondary circulations of the simulations as well as the individual terms in (5) have been produced and analyzed. For brevity, only those figures that provide insight into the role of asymmetric dynamics are presented and discussed here. Figure 9 shows the net time tendency term [LHS of (5)], net symmetric flux convergence term [sum of first two terms on RHS of (5)], net asymmetric flux convergence term [sum of third and fourth terms on RHS of (5)] and sub- grid scale diffusion term [last term on RHS of (5)] averaged over height (0 -3 km) and time (2.5 -3.5 h). This time period was chosen due to the significant intensification occurring in the storm (Figs. 8a and 8b) and the height interval was chosen to focus on the low-level dynamics. The coarse simulation with larger diffusion coefficients (Fig. 9a) shows that the time tendency is dominated by the sub-grid scale diffusion with large increases radially inward of ~ 15 km. The net symmetric term also contributes substantially to the time tendency as a result of the heat forcing with peak values slightly inside the RMW at ~ 18 km. The net asymmetric term is slightly negative at most radii and doesn't make much of a contribution to the time tendency. From a physics point of view, the symmetric response to the heating is intensifying and contracting the hurricane, while diffusion is mixing/smoothing the large gradients in AAM, which moves momentum in the downgradient direction (from the eyewall to the ...
Context 12
... the standard downgradient diffusion [Laplacian operator in (3) and (6)] used to model the effects of sub-grid turbulence in the coarse simulation a good approximation of the LES? While the overall trend of spreading AAM from the eyewall to the eye is captured by the Laplacian diffusion, it is clear that complicated, small-scale details in the LES can have important consequences for the mean hurricane. After all, the azimuthal mean wind speed is up to ~ 30 % stronger in the LES for short time integrations of 3.5 h (Fig. 8b). Note that the time tendency of AAM is negative from ~ 18 -25 km radius in the coarse simulation with large diffusion (Fig. 9a) and positive in the same region in the LES (Fig. 9c), which could explain some of the differences in mean intensity. A flow dependent eddy viscosity should improve the modeling of the LES effects. However, the first order turbulence closure assumes that the AAM transport is purely downgradient, which may not be the case in the ...
Similar publications
The structure of vortex Rossby waves (VRWs) and their role in the development of a secondary eyewall in Hurricane Matthew (2016) is examined from observations taken during the NOAA Sensing Hazards with Operational Unmanned Technology (SHOUT) field experiment. Radar measurements from ground-based and airborne systems, with a focus on the NASA High-A...
Citations
... While valuable sources of information, these data cannot provide the localized structure of the HBL at high resolution and require gathering data over many hours and many storms to compile a complete, averaged picture of this layer. However, new algorithms and processing of data from the Imaging Wind and Rain Airborne Profiler (IWRAP) airborne Doppler radar can provide the 3-D wind vector over the HBL at a grid spacing that is fully capable of resolving large turbulent eddies [7], [9]. ...
... The IWRAP 3-D winds have been thoroughly validated and compared very well with in situ flight-level data [7], G18. Guimond et al. [9] designed an IWRAP 3-D winds simulator using a large eddy simulation of a hurricane and found from spectral analysis that the 3-D winds are fully resolved at 4-5 x, where x is the retrieval grid spacing. This means that with a grid spacing of 125 m, the IWRAP 3-D winds can capture the full essence of turbulent eddies with scales of ∼600 m. ...
New radar remote sensing measurements of the turbulent hurricane boundary layer (HBL) are examined through analysis of airborne (Imaging Wind and Rain Airborne Profiler; IWRAP) and spaceborne (synthetic aperture radar; SAR) data from Hurricanes Dorian (2019) and Rita (2005). These two systems provide a wide range of storm intensities and intensity trends to examine the turbulent HBL. The central objective of the work is to document the characteristics of coherent turbulent structures (CTSs) found in the eyewall region of the HBL. Examination of the IWRAP data in Dorian shows that the peak, localized wind speeds are found inside the CTSs near the eye-eyewall interface. The peak winds are typically located at lower levels (0.15 - 0.50 km), but sometimes are found at higher levels (1.0 - 1.5 km) when the CTSs are stretched vertically. A SAR overpass of Dorian’s eyewall showed ocean surface backscatter perturbations at the eye-eyewall interface that have connections to the CTSs identified in IWRAP data. Wavelet analysis, including detailed significance testing, was performed on the IWRAP and SAR data to study the CTS wavelengths and power characteristics. Both datasets showed a multi-scale structure in the wavelet power spectrum with peaks at ~ 10 km (eyewall), ~ 4 - 5 km (merger of small-scale eddies) and ~ 2 km (native scale of the CTSs). The ~ 2 km native scale of the CTSs is robust across intensity trends (rapid intensification, weakening and steady-state), storm cases and region of the storm. This information is useful for turbulence parameterization schemes used in numerical models that require the specification of a turbulent length scale.
