Transcript Cold Fronts and their relationship to density currents: A

Cold Fronts and their relationship to
density currents: A case study and
idealised modelling experiments
Victoria Sinclair
University of HelsinkI
David Schultz
University of Helsinki, FMI,
University of Manchester, UK
Overview
• Previous work and some theory concerning cold
fronts and density currents
• A Case Study
– Observations
– AROME simulation
• Idealised Modeling Experiments
– 2D density current and 3D cold front
– Quantify governing dynamics
Can cold fronts be considered
density currents?
 Plenty of papers state
that a cold front
resembles a density
current in appearance
Tower observations of a
cold front, Colorado
Shapiro et al. 1985
 Visual similarity does
not equal dynamical
similarity
Density Current theory
Du
1 p
 fv 
Dt
 x
Dv
1 p
  fu 
Dt
 y
• Coriolis force can be neglected
 gh 
ck

  
• Density currents have a lowlevel feeder flow behind the
leading edge: the wind speeds
behind the front (u) are greater
than the speed that the gravity
current moves at (c)
X
X
u c  0
0.5
• Equations exists which predict
the speed of movement as a
function of density difference
and the depth
Fronts Theory
Du
1 p
 fv 
Dt
 x
Dv
1 p
  fu 
Dt
 y
X
X
• Fronts are often assumed
to be balanced, at least in
the cross front direction
• Acceleration term is
assumed to be small.
• No formula to predict the speed that fronts
move at
• Uncertainty remains as to what factors
control the speed that cold fronts move at
Questions
• What controls the speed that cold fronts move
at?
– Why do some cold fronts propagate – i.e. move faster
than the normal component of the wind?
– Why do some cold fronts move slower than the
normal wind, and hence share a feature with gravity
currents?
• When do cold fronts collapse to resemble
density currents?
• Are collapsed cold fronts dynamically similar to
density currents?
Motivation
• Cold fronts that evolve into gravity current
type features can produce hazardous
weather
• The scale of a collapsed front means that
even high resolution NWP models will not
capture the structure and evolution well
Case Study: synoptic evolution
12 UTC 29 Oct
00 UTC 30 Oct
00 UTC 31 Oct
• Developed as a frontal wave on pre-existing front
• Mature front and is far from the parent low
• Simulated event with AROME 33h1, 2.5km
Shallow frontal zone 00:11 UTC
7 m/s
6 m/s
Image provided by Matti Leskinen
• Radial wind speeds
from Kumpula
Radar
• Cold air is confined
to a shallow layer
• Resembles a
density current
Temperature at Kivenlahti
Observations
black:
5m
red:
26 m
blue:
48 m
magenta: 93 m
grey:
green:
brown:
orange:
141 m
218 m
266 m
296 m
AROME
black:
2m
blue:
38 m
magenta: 112 m
green: 200 m
orange: 300 m
Temperature at Kuopio
Observations
black:
5m
red:
26 m
blue:
48 m
magenta: 93 m
grey:
green:
brown:
orange:
141 m
218 m
266 m
296 m
AROME
black:
2m
blue:
38 m
magenta: 112 m
green: 200 m
orange: 300 m
Heat Fluxes
SMEAR III
SMEAR II
BLACK: observed. GREY: AROME
Data provided by Annika Nordbo and Ivan Mammarella
AROME Potential Temperature 900hPa
Location of Cold Front from
AROME
B
Averaged speed of front
between 22:00 UTC and
02:00 UTC
B
C
Section B = 5.03 ms-1
A
Section C = 5.47 ms-1
Section A = 6.92 ms-1
Front is located objectively
Black: 18:00 UTC Blue: 00:00 UTC
Red: 20:00 UTC
Purple: 02:00 UTC
Green: 22:00 UTC Cyan: 04:00 UTC
Hewson (1998)
Jenker et al (2010)
Wind Speeds from AROME
920 hPa
u – c > 0 especially in south
990 hPa
u–c≈0
• Wind speeds decrease behind the front
• Unconvincing evidence of a “feeder flow”
Ascent, potential temperature
Simulated Radar reflectivity
22 UTC, B
00 UTC, B
22 UTC, A
00 UTC, A
Case Study Conclusions
• Shallow and narrow front
– stable mid-troposphere
– Stable BL may have prevented frontolysis by turbulent
mixing
• Dynamics differ to density current dynamics
– No clear feeder flow
• Prefrontal boundary layer appears to affect
structure
Idealised Modelling with WRF
Idealized Experiment
• WRF-ARW
– Weather Research and Forecasting –
Advance Research WRF. V3.1
– Non-Hydrostatic, range of physics options
– Supported by NCAR
• First simulated a 2D density current at
high resolution (100m grid spacing)
• Calculate force balance.
Density Current
5 – 10 minutes : 20.5 ms-1
10 – 15 minutes: 15.3 ms-1
Force Balance
lowest model level (995 hPa)
Blue: Potential temperature
Purple: Coriolis
Red: Pressure Gradient Force
Black: Acceleration
Simulate a Cold Front
• Model a full 3D baroclinic life cycle
• Include two nested domains over the cold
front
– horizontal grid spacing is 100km : 20km : 4km
– All nests have 64 levels, model top at 100hPa
• Initial experiment has no moisture and no
physical parameterizations
Potential temperature and surface
pressure. Day 4.5. Parent domain
Potential Temperature and wind
vectors. 20 km domain
Potential temperature and vertical motion
Force balance
LEVEL 1 ~ 975 h Pa
LEVEL 7 ~ 805 h Pa
Blue: Potential temperature
Purple: Coriolis
Red: Pressure Gradient Force
Black: Acceleration
Force Balance 5 hrs later
LEVEL 1 ~ 975 h Pa
LEVEL 7 ~ 805 h Pa
Blue: Potential temperature
Purple: Coriolis
Red: Pressure Gradient Force
Black: Acceleration
Conclusions
• Idealised cold front does not visually resemble a
density current, but does have many interesting
features
• The force balance shows a three way balance
near the cold front
• HYPOTHESIS
– friction and turbulence will change force balance
– Trailing part of cold front will be visually more similar
to density currents
Future work
• Higher resolution (1km) simulation of cold
front, include boundary layer scheme
• Different baroclinic life cycles
• Simulate 3D density current at comparable
resolution to cold front case
Thank you
You can look at more animations
on my webpages
www.atm.helsinki.fi/~vsinclai
Force Balance: 5 hrs later
Force Balance across cold front