PBL Variability and Forecast Sensitivity Tammy M. Weckwerth - - PowerPoint PPT Presentation

PBL Variability and Forecast Sensitivity

Tammy M. Weckwerth NCAR/Earth Observing Laboratory

Workshop on Tropospheric Profiling Technologies, NCAR, Boulder, CO, 12-14 April 2011

• Convection initiation and evolution
• Elevated convection initiation
• Storm morphology
• Analyses and nowcasting techniques

Surface-Based Convection Initiation

Wilson et al. (1997)

Surface Horizontal Mass Convergence

Banacos and Schultz (2005)

• a. SHMC max with

tropospheric circulation and deep convection

• b. SHMC max with

shallow convection due to subsidence or capping inversion

• c. SHMC max near

change in CBL depth

• d. HMC above CBL

Convergence field is important

Shear Balance

From Weisman after Rotunno et al. (1988)

No shear; gust front moves away from storm Shear balances gust front and produces

• ptimal situation for

long-lived systems

Steering Level Winds

• Vertical, deep

updrafts

• Boundary motion

~ storm motion

• Supported by

Moncrieff and Miller (1976) and Weisman and Klemp (1986)

Wilson and Megenhardt (1997)

Full wind profiles important

Boundaries Modify Local Stability

Wilson et al. (1997)

CI Along Dryline

Ziegler and Rasmussen (1998)

• Intense, deep

mesoscale lifting - CI

• Require w ht

> LFC Need depth and amount of moisture to forecast CI

Cold Front and Dryline CI

Murphey et al. (2006) NW SE Cool, moist, N flow Cool, moist, S flow

• Cool, moist

air capped by inversion

• CI where q

bulges, no cap

Warm, dry, SW flow CI

• CI not

continuous along DL

Dryline CI

Murphey et al. (2006)

• Leandre II wv DIAL showed

moisture variations

• Caused by misocyclones
• Near Wmax and CI

High-resolution 3D structure

• f q, T, winds important

8 km

CI – 24 May 2002

Wakimoto et al. (2006)

• No CI at triple point!

Cold, dry Warm, moist W E CI CI

• CI east of TP
• Deeper moist air E
• Deeper CBL (aerosol plume)
• Less stable (θv vertical

gradient reduced)

• Wave or solenoidal DL

circulation? Detailed 3D structure essential to improved understanding

CI by SBF and Rolls

Atkins et al. (1995)

• Rolls lifted up at

SBF intersections

• Deeper, stronger

updrafts and clouds at intersection points – increased likelihood of CI

• Simulated by Rao

et al. (1999) and Dailey and Fovell (1999) Need 3D structure

• f kinematics and

thermodynamics

T and q Sensitivity to Thunderstorm Occurrences

Lin et al. (2011)

• 4 years of warm

season

• Non-synoptically

forced systems in Taiwan

• Warmer (1 °C) and

moister (1-3 °C) on thunderstorm days compared to non- thunderstorm days

CI

Thunderstorm days Non- Thunderstorm days

T T Td Td

T and q Sensitivity to CI

Crook (1996)

• CI related to surface

temperature dropoff

Integrated rain water

• Storm strength

related to surface moisture dropoff

• CBL variations of 1 °C

and 1 g kg-1 are important for CI

Integrated rainwater

CI Storm strength

• Moisture

variations of 1.5 g kg-1 observed between roll updrafts and downdrafts

• Representative-

ness of soundings?

Weckwerth et al. (1996)

Observed Moisture Variability

CI and AERI Stability Indices

• Multiple severe

storms around AERIs

• CAPE increased and

CIN decreased with CI: erosion of cap

• Valuable info but not

sufficient

Feltz and Mecikalski (2002) x Lamont x Purcell Vici x x x x x x

Sounding Susceptible to Elevated Convection Sounding Susceptible to Surface- Based Convection DVN (0000 UTC 9/12/2000) GRB (0000 UTC 9/12/2000)

From Trier et al. 2002, abstract 130, Reading QPF meeting

A key factor in nocturnal convection is the depth

• f the moist inflow, which can be aloft

Sounding Susceptible to Elevated Convection Sounding Susceptible to PBL- Based Convection

Courtesy Jim Wilson (NCAR)

Elevated Convection Initiation

Elevated Convection Initiation

• Stable surface layer
• Height of max CAPE:

0.6-1.3 km

Marsham et al. (2011)

Need high-res 3D observations

• f wind and stability
• No surface boundary
• Further CI due to bore
• Morning CI due to

gust front

• Elevated CI

transitioning to sfc CI – important for generation of long- lived MCSs (e.g., Carbone et al. 2002)

Storm Morphology Affected by Changes in Shear

Richardson et al. (2007)

• 1.5 km ARPS grid

spacing

• 4-hr simulation

No change in shear produces cellular convection Changing shear: Quasi- linear convection with a bow echo

Storm Morphology Affected by Changes in Inversion Layer

Ziegler et al. (2010)

• 1 km grid spacing
• Time-varying inflow

lateral BC prescribed from meso analysis with increasing stability - accurate

• Homogeneous

simulation produces MCS – not accurate

Lagrangian Analysis

• Assimilate

multiple datasets using 3D radar wind field

• Output 3D

fields of q, θ and θv

• Study

boundary structures and CI

Ziegler et al. (2007a; 2007b)

VDRAS

• Variational Doppler Radar

Analysis System

• 4DVAR based on cloud-scale

model

• Assimilates Z, Vr + sfc
• bservations
• Produces 1-3 km T, q and wind

fields

• Excellent tool for nowcasting

Sun and Crook (1997, 1998)

• Extrapolates radar echoes
• Produces 0-1 hr time and

place specific forecast

• Expert system utilizes fuzzy

logic

• Ingest multiple data sets
• Ingest NWP output
• 4-D Variational Doppler

Radar Analysis System (VDRAS)

• Forecast storm initiation,

growth and dissipation

• Algorithms derive forecast

parameters based on the characteristics of the boundary layer, storms and clouds.

NCAR Autonowcaster System

Mueller et al. (2003)

Example of Auto-Nowcaster Initiation Forecast

1 hour forecast Verification

Initiation nowcasts extrapolation nowcasts

Courtesy Jim Wilson (NCAR)

Closing Remarks

• Important to continuously sample small-scale

variations of temperature, moisture and wind

• Satellite imagery and scanning radars provide

the big picture

• Integration of data sets is required to improve

understanding of mesoscale dynamics and improve forecasting skill

• High-resolution data assimilation of multiple

datasets essential to provide 3D, time-varying temperature, moisture and wind fields

Thank you for your attention.