Idealized Simulations Examining the Role of Terrain-Channeling on Convective Organization William Flamholtz, Brian Tang, and Lance Bosart University at Albany, SUNY 19th Northeast Regional Operational Workshop Wednesday, 7 November 2018 Research Funded by the Collaborative Science, Technology, and Applied Research (CSTAR) Program

Motivation Forecasting severe weather in the northeastern U.S. is challenging due to: Perturbations imparted on convective environments by complex terrain such as terrain-channeling of warm, moist air, and an increase of low-level shear in valley locations (Bosart et al. 2006, Katona et al. 2016, Tang et al. 2016). Many severe weather events occur in marginally favorable environments (Vaughan et al. 2017).

Motivation Forecasting severe weather in the northeastern U.S. is challenging due to: Perturbations imparted on convective environments by complex terrain such as terrain-channeling of warm, moist air, and an increase of low-level shear in valley locations (Bosart 2006, Katona et al. 2016, Tang et al. 2016). Many severe weather events occur in marginally favorable environments (Vaughan et al. 2017).

Terrain-Channeled Flow From Bosart et al. (2006)

Terrain-Channeled Flow South-southeasterly flow near the surface, veering to southwesterly aloft for the Valley location From Bosart et al. (2006)

Terrain-Channeled Flow South-southeasterly flow near the surface, veering to southwesterly aloft for the Valley location Southwesterly flow near the surface in the higher terrain yields a shorter hodograph From Bosart et al. (2006)

Low-Predictability Events Many low-predictability cases happen in high-CAPE, low-shear environments. From Vaughan et al. (2017)

Low-Predictability Events Many low-predictability cases happen in high-CAPE, low-shear environments. From Vaughan et al. (2017)

Hypothesis Terrain-channeling in valley locations perturbs the low-level flow such that the low- level wind shear increases. Higher amounts of low-level wind shear leads to an increase of convective organization due to a greater optimal state between cold pools and environmental shear (RKW-Theory). There’s a higher risk of severe wind in terrain-channeled locations.

Methodology Identified a high-impact, low-predictability event using methods of Vaughan et al. (2017).

Methodology Identified a high-impact, low-predictability event using methods of Vaughan et al. (2017). Conducted two parent simulations using the Weather and Research Forecast model (WRF): One simulation with realistic terrain One simulation with terrain removed

Methodology Identified a high-impact, low-predictability event using methods of Vaughan et al. (2017). Conducted two parent simulations using the Weather and Research Forecast model (WRF): One simulation with realistic terrain One simulation with terrain removed Extracted a wind profile from each simulation using the same location in the Hudson Valley: Preserved the 0-1km wind profile from each of the profiles. Averaged the wind profile from the two simulations above 1 km.

Methodology Identified a high-impact, low-predictability event using methods of Vaughan et al. (2017). Conducted two parent simulations using the Weather and Research Forecast model (WRF): One simulation with realistic terrain One simulation with terrain removed Extracted a wind profile from each simulation using the same location in the Hudson Valley: Preserved the 0-1km wind profile from each of the profiles. Averaged the wind profile from the two simulations above 1 km. Increased the wind shear of each wind profile by multiplying by a scale (S): Preserves the shape of each hodograph while increasing speed shear.

Methodology Identified a high-impact, low-predictability event using methods of Vaughan et al. (2017). Conducted two parent simulations using the Weather and Research Forecast model (WRF): One simulation with realistic terrain One simulation with terrain removed Extracted a wind profile from each simulation using the same location in the Hudson Valley: Preserved the 0-1km wind profile from each of the profiles. Averaged the wind profile from the two simulations above 1 km. Increased the wind shear of each wind profile by multiplying by a scale (S): Preserves the shape of each hodograph while increasing speed shear. Conducted six idealized simulations using the two wind profiles and four scaled profiles.

Case Study for Parent Simulations Characterized as a high-impact, low-predictability event using methods from Vaughan et al. (2017). Large swath of wind reports across NY and SW New England.

Observed Composite Reflectivity

Parent Simulations Model Configuration: WRF-ARW 3.9 core with High Resolution Rapid Refresh (HRRR)-like physics Three nested domains (27km, 9km, and 3km) Aerosol-aware Thompson microphysics Modified Mellor–Yamada Nakanishi Niino (MYNN) planetary boundary layer Initialized with 12-km hourly RAP+NAM soil moisture analysis 30-h simulations (0600 UTC 13 August 2016 – 1200 UTC 14 August 2016) Two simulations: one with terrain and one without terrain

Wind Profile Location

Input Soundings Channeled (C) Non-Channeled (NC)

Input Soundings Channeled (C) Non-Channeled (NC) Sounding Type MUCAPE (J kg^-1) CIN (J kg^-1) 0-1 km Shear (m s^-1) 0-1 km SRH (m^2 s^-2 0-6 km Shear (m s^-1) 0-6 km SRH (m^2 s^-2) C 4593.59 -72.94 8.64 96.10 13.38 162.68 NC 5.31 50.75 11.18 114.09

Scaling of Shear Profiles - Two parent wind profiles (S=1.0) were both scaled by S=1.25 and S=1.50. Scale factor increases speed shear while preserving the directional differences. Expand figures

Scaling of Shear Profiles - Two parent wind profiles (S=1.0) were both scaled by S=1.25 and S=1.50. C NC 0-1 km SRH (m^2/s^2) 0-1 km Shear (m/s) 0-6 km shear (m/s) 96.10, 149.89, 215.69 8.64, 11.61, 14.60 13.38, 16.92, 20.51 50.75, 79.56, 112.87 5.31, 7.63, 9.96 11.18, 14.78, 18.41 C NC

Idealized Model Setup Use graphics (use prior figures(i.e. profiles, warm bubble. Combine prior images.

Idealized Model Setup

Idealized Model Setup Channeled (C)

Idealized Model Setup Channeled (C) Use graphics (use prior figures(i.e. profiles, warm bubble. Combine prior images.

Idealized Model Setup Non-Channeled (NC)

Idealized Model Setup Non-Channeled (NC)

Idealized Model Setup dx, dy =1 km 500 km x 300 km f=0 Channeled (C) Non-Channeled (NC)

Radar Reflectivity C, S=1.0 C, S=1.25 C, S=1.5 NC, S=1.0 NC, S=1.25

Radar Reflectivity C, S=1.0 C, S=1.25 C, S=1.5 NC, S=1.0 NC, S=1.25

Radar Reflectivity C, S=1.0 C, S=1.25 C, S=1.5 NC, S=1.0 NC, S=1.25

Radar Reflectivity cold pool races well ahead of convection in both low-shear simulations, and all NC cases. C, S=1.5 simulation develops a QLCS structure. C simulations have larger areas of higher reflectivity the than NC simulations Cold pool undercuts both low-shear, NT cases. Place words on figures, avoid text on bottom, make refl-low level vert vort plot

Perturbation 2-Meter Temperature C, S=1.0 C, S=1.25 C, S=1.5 NC, S=1.0 NC, S=1.25 NC, S=1.5

Perturbation 2-Meter Temperature C, S=1.0 C, S=1.25 C, S=1.5 NC, S=1.0 NC, S=1.25 NC, S=1.5

Perturbation 2-Meter Temperature All NC cold pools travel faster than terrain-channeled cold pools C cold pools are stronger, regardless of S.

Scale factor (S) = 1.0

Scale factor (S) = 1.0

Scale factor (S) = 1.0

Scale factor (S) = 1.0 S=1.0, UHI=NST, VVEL=NST, 2mT=NST, 10mW=NST, VVORT=NST Oscillating mode for VVEL, pulsing convevtion, Same with UHEL Remove 2m temp, vertical vorticity. Step by step with each figure

Scale factor (S) = 1.0

Scale factor (S) = 1.0

Scale factor (S) = 1.0

Scale factor (S) = 1.0 No significant differences between the C and NC simulation when S=1.0

Scale factor (S) = 1.0 No significant differences between the C and NC simulation when S=1.0 Suggests that low-level shear perturbation due to terrain-channeling may not play a significant role in storm severity in high-CAPE, low-shear environments.

Scale factor (S) = 1.25

Scale factor (S) = 1.25 Most indices in the simulations with S = 1.25 remain are similar the S = 1.0 simulations. S=1.0, UHI=NST, VVEL=NST, 2mT=NST, 10mW=NST, VVORT=NST Oscillating mode for VVEL, pulsing convevtion, Same with UHEL Remove 2m temp, vertical vorticity. Step by step with each figure

Scale factor (S) = 1.5 S=1.0, UHI=NST, VVEL=NST, 2mT=NST, 10mW=NST, VVORT=NST Oscillating mode for VVEL, pulsing convevtion, Same with UHEL Remove 2m temp, vertical vorticity. Step by step with each figure

Scale factor (S) = 1.5 C simulation has statistically higher values for all indices S=1.0, UHI=NST, VVEL=NST, 2mT=NST, 10mW=NST, VVORT=NST Oscillating mode for VVEL, pulsing convevtion, Same with UHEL Remove 2m temp, vertical vorticity. Step by step with each figure

Scale factor (S) = 1.5 C simulation has statistically higher values for all indices When shear is increased, the C simulation produces more significant convection. S=1.0, UHI=NST, VVEL=NST, 2mT=NST, 10mW=NST, VVORT=NST Oscillating mode for VVEL, pulsing convevtion, Same with UHEL Remove 2m temp, vertical vorticity. Step by step with each figure

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5):

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5): C simulation has statistically stronger convection.

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5): C simulation has statistically stronger convection. Cold-pool strength is stronger in the C simulation.

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5): C simulation has statistically stronger convection. Cold-pool strength is stronger in the C simulation. C simulation has a statistically significant higher maximum 10-meter wind speeds.

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5): C simulation has statistically stronger convection. Cold-pool strength is stronger in the C simulation. C simulation has a statistically significant higher maximum 10-meter wind speeds. Suggests that severe wind may be more likely in terrain-channeled locations.

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5): C simulation has statistically stronger convection. Cold-pool strength is stronger in the C simulation. C simulation has a statistically significant higher maximum 10-meter wind speeds. Suggests that severe wind may be more likely in terrain-channeled locations. Future Work:

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5): C simulation has statistically stronger convection. Cold-pool strength is stronger in the C simulation. C simulation has a statistically significant higher maximum 10-meter wind speeds. Suggests that severe wind may be more likely in terrain-channeled locations. Future Work: Examine different thermodynamic environments together with C and NC wind profiles.

Conclusions: There wasn’t a statistically significant difference between the C and NC simulations with S = 1 and 1.25 Low-level shear perturbations caused by terrain channeling in high-CAPE, low-shear environments may not be important Other terrain factors and stochastic factors associated with the convection itself may be more important Significant differences occur when shear is increased (S=1.5): C simulation has statistically stronger convection. Cold-pool strength is stronger in the C simulation. C simulation has a statistically significant higher maximum 10-meter wind speeds. Suggests that severe wind may be more likely in terrain-channeled locations Future Work: Examine different thermodynamic environments together with C and NC wind profiles. Construct an idealized simulation that has a channel across the center of the domain to emulate a more realistic progression of convection that’s moving across a valley.