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Influences of Large-Scale Moist Convection on Turbulence in Clear Air (CAT). Outline: Observations and High Resolution Simulations of a Cold-Season Case Midlatitude cold front/upper trough case (9-10 March 2006) Observations and High Resolution Simulations of a Warm-Season Case

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Influences of Large-Scale Moist Convection on Turbulence in Clear Air (CAT)


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influences of large scale moist convection on turbulence in clear air cat

Influences of Large-Scale Moist Convection on Turbulence inClear Air (CAT)

  • Outline:
  • Observations and High Resolution Simulations of a Cold-Season Case
  • Midlatitude cold front/upper trough case (9-10 March 2006)
  • Observations and High Resolution Simulations of a Warm-Season Case
  • Central U.S. MCS case (16-17 June 2005)
  • 3) Discussion of Common Roles of Organized Deep Convection

Stan Trier

NCAR, Boulder

Collaborators:

Bob Sharman (NCAR), Todd Lane (Univ of Melbourne), Rob Fovell (UCLA)

Workshop on Aviation Turbulence, 28 August 2013, NCAR, Boulder, CO

slide2

CAT Outbreak within a Midlatitude Cyclone (9-10 March 2006)

Over 200 reports of moderate or

greater turbulence from 1500 UTC

9 March to 0300 UTC 10 March

Reference:

Trier, S.B., R.D. Sharman, and T.P. Lane 2012: Influences

of moist convection on a cold-season outbreak of clear-air

turbulence (CAT), Mon. Wea. Rev., 140, 2477-2496.

slide3

Location of Turbulence Relative to Large-Scale Flow Features

0000 UTC RUC Analysis and 2300-0100 UTC Time-Space Corrected Turbulence Reports

2 PVU

A

B

C

D

West – East Distance (km)

slide4

Experimental Design

  • ARW-WRF Simulations with 4 interactive nests (with D = 30, 10, 3.333, and 0.667-km)

- D3 and D4 have fully explicit convection (no cumulus parameterization)

  • Simulations:
  • CRTL (full physics, uses D1, D2, D3)
  • NOMP (cloud microphysics deactivated, uses D1, D2, D3)
  • HRES (like CTRL, but D = 0.667 nest D4 activated between 2300 and 0100 UTC)
slide5

24-h Forecast (CTRL) over Domain 3 at 0000 UTC 10 March

  • model derived reflectivity
  • surface winds
  • surface q (2-K contour intervals)

Observations over Region at 0000 UTC 10 March

  • NOWRAD reflectivity
  • surface winds
  • surface q (2-K contour intervals)
slide6

Line-Averaged Cross Section of Cloud (colorfill), q, Winds, TKE (green), Nm (red)

Layer of reported

turbulence

CTRL 24-h Forecast (0000 UTC 10 March 2006)

slide7

Wintertime Clear-Air Turbulence (CAT) Associated with Deep Convection

Breaking Gravity Waves Above Storms

Kelvin-Helmholtz Instability

Potential Temperature, Vertical Velocity and Total Cloud Condensate

Turbulence mechanisms at

different locations on the

fine-scale grid (D = 667 m)

Horizontal Distance (km)

slide8

Radial (Transverse) Cirrus Bands in MCS Anvils

A recent example (13 August 2013)

1632 UTC 13 Aug 2013

Moderate Turbulence

Moderate Turbulence

1656 UTC 13 Aug 2013

Moderate Turbulence

slide9

Radial (Transverse) Cirrus Bands in MCS Anvils

A recent example (13 August 2013)

1632 UTC 13 Aug 2013

Moderate Turbulence

Moderate Turbulence

1656 UTC 13 Aug 2013

Moderate Turbulence

slide10

16 – 17 June 2005 Case Study

0905 UTC 16 June

43 N

40 N

37 N

0745 UTC 17 June

40 N

37 N

slide11

Simulation of Radial Outflow Bands in 17 June 2005 MCS

0800 UTC Simulated Reflectivity and 12.5-km MSL Winds

  • Simulations with ARW-WRF V2.2
  • Explicit Deep Convection
  • Initial and Boundary Conditions from
  • D = 13 km 3-hourly RUC Analyses
  • Large Single Domain Run with D = 3 km
  • Simulation with D2 nest of D = 600 m
  • started at t = 7h of Large Domain Run

Model Parameterizations

- Thompson Bulk Microphysics

- Noah LSM

- PBL Scheme (MYJ)

- Dudhia Longwave Radiation

- RRTM Shortwave Radiation

slide12

Turbulence

UA

776

Observations and WRF-Simulations of the 17 June 2005 MCS Case

Simulated Cloud Top Temperature (0950 UTC, t = 5.8 h )

Observed Turbulence @ 37 Kft (0936-0957 UTC) L=light, M=Moderate

IR Satellite at 0950 UTC 17 June 2005

Trier and Sharman (2009, Mon. Wea. Rev.) Observations and MCS-Scale Simulations

Trier et al. (2010, J. Atmos. Sci.) High-Resolution Simulation and Analysis of Radial Bands

slide13

2

4-hour Loop of Brightness Temperature, 12-km Moist Static Instability N < 0

and 11.5-13-km Vertical Shear from 07-11 UTC 17 June with Dt = 10 min

m

North

East

Tb

  • Anvil bands originate within zones of moist static instability
  • Bands are aligned along the anvil vertical shear vector
  • Similar to horizontal convective rolls in boundary layer arising from thermal instability
slide14

0930 UTC Brightness Temperature and Moist Static Stability

Control Simulation (Full Physics)

No Cloud-Radiative Feedback Simulation

Tb

slide15

150-km Line Average

Simulated TKE typically occurs

where Ri number is reduced

m

At typical commercial aircraft

cruising altitudes (z = 10-12 km)

~

m

e

e

Stability Budget

Equation

Differential

Horizontal

Advection

Differential

Vertical

Advection

Tendency

Subgrid Source

Term

slide16

Red = Upward Motion

Blue = Downward Motion

slide17

17 June 2005 Turbulence Measurements Near Transverse (Radial) MCS Outflow Bands

radial bands

Turbulence intensities from in situ EDR:

Green = Smooth

Yellow = Light

Orange = Moderate

Red = Severe

slide20

Summary

  • Near-cloud turbulence (NCT) can result from many different mechanisms
  • - Many types of convective weather involved (isolated cells, MCSs, midlatitude cyclones)
  • - Turbulence forecasting systems need to account for this non-traditional CAT
  • Mesoscale circulations play an important role in producing NCT
  • - Large-scale upper-level anticyclonic outflows enhance vertical shear supporting NCT
  • - Many important effects of vertical shear
  • Provides large-scale thermodynamic destabilization and organizes radial bands
  • Promotes Kelvin-Helmholtz instability
  • Gravity Waves play a role in many NCT situtations
  • - Directly through wave breaking
  • - Indirectly through local reductions in Ri where other instabilities are favored
  • - Indirectly through their vertical motions, which perturb already unstable flow