Observed and Simulated Multi-bands in Northeast U.S. Winter

Report
Observed and Simulated Multi-bands
in Northeast U.S. Winter Storms
SARA A. GANETIS1, BRIAN A. COLLE1, SANDRA E. YUTER2, AND NICOLE CORBIN2
1 School
of Marine and Atmospheric Sciences,
Stony Brook University, Stony Brook, New York
2 Department
of Marine, Earth and Atmospheric Sciences,
North Carolina State University, Raleigh, North Carolina
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Previous Work on Snowbands
Lift
Moisture
Novak et al. 2004
•
Instability
Novak et al. 2010
Climatology of banded structures in
•
Northeast U.S. extratropical cyclones for 5
•
years (1996-2001) that identified 88 cases,
75 banded, 48 single bands & 13 nonbanded
Single Band
Single Band
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75 cases, 30 single-banded cases for 2002-08
Band-relative composites using 3-hourly 32km (NARR) data and hourly 20-km RUC data
Nonbanded
Nonbanded
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2
Previous Work on Microphysics within East Coast Storms
Stark et al. (2013)
• Case studies examining microphysical
evolution of snowbands
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Previous Work on Utilization of Mesoscale Models
Novak et al. 2009
•
Confirmed the capability of a mesoscale model in simulating single-banded storms
Observation
4-km MM5
Simulation
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What about Multi-bands?
26-27 Dec 2010 OKX 0.5° Reflectivity
Reflectivity [dBZ]
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Previous Work on Multi-bands
Fewer studies have focused on or
discussed smaller-scale
multi-bands found in the comma head of
cool season (Oct – Mar) extratropical
cyclones and include
• observational studies
•
e.g. Uccellini and Koch 1987; Shields et al.
1991; Nicosia and Grumm 1999
• theoretical and/or idealized studies
•
e.g. Xu 1992; Pizzamei et al. 2005;
Morcrette and Browning 2006
Cross-section of vertical velocity for a saturated
region in the presence of negative moist
geostrophic potential vorticity (Xu 1992).
VT
Stable
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Unstable
12 November 2014
Novak et al. 2006
6
Science Questions
What are the frequency of occurrence and characteristics
of observed banded precipitation structures in Northeast
U.S. winter storms and are they in agreement with those of
previous studies?
•
How often do multi-bands transition into a single band
and vice-versa?
How do environmental parameters differ among the
different banded precipitation structures and how could the
differences be used to enhance conceptual knowledge?
•
Do multi-bands always form in an environment of
instability?
Can a mesoscale model run down to 1.33-km grid spacing
simulate the different observed precipitation structures?
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Dataset Creation Methodology
• Coastal Northeast U.S. cool season (Oct – Mar) snow storms
from 1997-2014
• Goal  Using stitched radar data (NCState) from DIX, OKX, BOX:
Classify events or time periods during which different banded
precipitation structures were observed within cases
123 Cyclone Dates
Reporting ≥ 1” snow
in 24 h
Source: US Census Bureau
71 Cyclone Dates
w/ Radar Data from
KDIX, KOKX, KBOX
Terrain Height [m]
50 Cyclone cases with
radar data available for
entire duration of storm
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Classification Methodology
Band Type
Band Description
Single band
Linear structure 20–100 km
in width, >250 km in length,
with an intensity >30 dBZ
maintained for at least 2 h
Multi-bands
>3 finescale (5–20-km width)
bands with periodic spacing
and similar spatial
orientation, with intensities
>5 dBZ over the background
reflectivity maintained for at
least 1 h
Both single
band and
multi-bands
Both above single band and
multi-bands criteria are met
within 250 km
Nonbanded
None of the above criteria
are met and this may also be
classified as "cellular" where
reflectivity features >30 dBZ
are not ellipsoidal in shape to
be classified as multibands
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Single band
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Classification Methodology
Band Type
Band Description
Single band
Linear structure 20–100 km
in width, >250 km in length,
with an intensity >30 dBZ
maintained for at least 2 h
Multi-bands
>3 finescale (5–20-km width)
bands with periodic spacing
and similar spatial
orientation, with intensities
>5 dBZ over the background
reflectivity maintained for at
least 1 h
Both single
band and
multi-bands
Both above single band and
multi-bands criteria are met
within 250 km
Nonbanded
None of the above criteria
are met and this may also be
classified as "cellular" where
reflectivity features >30 dBZ
are not ellipsoidal in shape to
be classified as multibands
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Multi-bands
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Classification Methodology
Band Type
Band Description
Single band
Linear structure 20–100 km
in width, >250 km in length,
with an intensity >30 dBZ
maintained for at least 2 h
Multi-bands
>3 finescale (5–20-km width)
bands with periodic spacing
and similar spatial
orientation, with intensities
>5 dBZ over the background
reflectivity maintained for at
least 1 h
Both single
band and
multi-bands
Both above single band and
multi-bands criteria are met
within 250 km
Nonbanded
None of the above criteria
are met and this may also be
classified as "cellular" where
reflectivity features >30 dBZ
are not ellipsoidal in shape to
be classified as multibands
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Both Single & Multi-bands
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Classification Methodology
Band Type
Band Description
Single band
Linear structure 20–100 km
in width, >250 km in length,
with an intensity >30 dBZ
maintained for at least 2 h
Multi-bands
>3 finescale (5–20-km width)
bands with periodic spacing
and similar spatial
orientation, with intensities
>5 dBZ over the background
reflectivity maintained for at
least 1 h
Both single
band and
multi-bands
Both above single band and
multi-bands criteria are met
within 250 km
Nonbanded
None of the above criteria
are met and this may also be
classified as "cellular" where
reflectivity features >30 dBZ
are not ellipsoidal in shape to
be classified as multibands
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Non-banded
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Preliminary Event Results
Spatial Distribution
68 Events
•
•
•
•
12 Single bands (18%)
22 Multi-bands (32%)
14 Both single bands and
multi-bands (21%)
20 non-banded (29%)
Comparison to previous studies
•
Less events over a longer time period
compared to Novak et al. 2004
•
162 events, 48 exhibited single bands
Multi-band Transitions within 13 cases
•
•
•
•
•
•
•
Both  Multi: 4
Multi  Both  Multi: 2
Multi  Both: 2
Single  Both: 2
Multi  Both  Single: 1
Multi  Single  Both: 1
Single  Both  Single: 1
Terrain Height [m]
Lift
Moisture
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Instability
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Composite Methodology
•
•
3-hourly NARR Data (1997-2014)
One NARR file per event, but cyclone can be
sampled more than once
Multi-bands Both Single & Multi-bands
N-3
Multi-bands
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N0
N+3
Both Single & Multi-bands
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Composite Results: 300 mb
Single Band
Both Single &
Multi-bands
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Multi-bands
Wind Speed [kt]
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Non-banded
15
Composite Results: 700 mb
Single Band
Both Single &
Multi-bands
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Multi-bands
Relative Humidity
[%]
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Non-banded
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Composite Results: Forcing for Lift
Single Band
Hypothesis:
There is low-to-midlevel frontogenesis
inducing an
ageostrophic
vertical circulation
that provides forcing
for lift for both single
bands and
multi-bands
Both Single &
Multi-bands
Multi-bands
Frontogenesis
[K (100 km 3 h)-1]
-5 -2 -1 1 2
Non-banded
5
850 mb
Frontogenesis
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Composite Results: Instability
Single Band
Multi-bands
Both Single &
Multi-bands
Non-banded
Hypothesis:
There is larger
instability in the lowto-midlevel
environment for
multi-bands
950-925



≤0


>0

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Mesoscale Modeling Methodology
•
26-27 Dec 2010 Case
•
•
Both single and multi-bands 26/1700 - 27/0800
Weather Research and Forecasting (WRF)
mesoscale model v. 3.6.1
•
•
•
•
•
•
•
30-h Simulation 0600 UTC 26 – 1200 UTC 27
Initial and boundary conditions from 6-hourly 0.5° GFS
1/12th degree SST data from NCEP
4 one-way nested domains (36, 12, 4, 1.33 km)
40 vertical levels with model top set to 50 hPa
5-layer thermal diffusion surface layer scheme (Dudhia
1996)
Kain-Fritsch cumulus parameterization (Kain 2004)
•
•
applied to 36 and 12 km domains only
explicitly resolves updrafts and downdrafts
Planetary Boundary Layer
Parameterization Scheme
1.33
4 km
12 km
36 km
Microphysics Parameterization Scheme
MYJ (Janjic 1994)-- 1.5-order scheme with
local mixing and used in operational NAM
Thompson (Thompson et al. 2008)--predicts graupel
and also predicts the number concentration of ice in
addition to the mass concentration, despite being a
single-moment scheme
YSU (Hong et al. 2006)– Diagnostic non-local
closure scheme
WSM6 (Hong and Lim 2006)– single moment that also
predicts the mass concentration of graupel
 Resultant dataset: 4 simulations run down to 1.33-km grid spacing of 26-27 Dec 2010 multi-bands
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Mesoscale Model Results:
0000 UTC 27 Dec 2010 Simulated Reflectivity
OKX 0.5°
MYJ PBL / Thom MP
MYJ PBL / WSM6 MP
YSU PBL / Thom MP
YSU PBL / WSM6 MP
1-km AGL Stitched
Reflectivity [dBZ]
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Mesoscale Model Results:
0000 UTC 27 Dec 2010 OKX Sounding
OKX Sounding
MYJ PBL / Thom MP
MYJ PBL / WSM6 MP
YSU PBL / Thom MP
YSU PBL / WSM6 MP
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Mesoscale Model Results: 850 mb Geopotential Height
26/1800
27/0000
MYJ PBL / Thom MP
27/0300
27/0600
MYJ PBL / WSM6 MP
YSU PBL / Thom MP
YSU PBL / WSM6 MP
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Mesoscale Model Results: Dec 2010 Simulated Reflectivity
01 UTC 27 Dec 2010
03 UTC 27 Dec 2010
WRF 1.33-km Domain 500-m AGL
Simulated Reflectivity
OKX 0.5° Reflectivity
00 UTC 27 Dec 2010
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FH 18 Valid
00 UTC 27 Dec 2010
FH 19 Valid
01 UTC 27 Dec 2010
FH 21 Valid
03 UTC 27 Dec 2010
B
B’
Reflectivity [dBZ]
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B
B’
FH 18 Valid
00 UTC 27 Dec
B
B’
B
FH 19 Valid
01 UTC 27 Dec
B’
FH 21 Valid
03 UTC 27 Dec
Simulated Reflectivity, θes, Circulation Vectors
Reflectivity [dBZ]
Frontogenesis, θe, Circulation Vectors
Frontogenesis [K (100 km h)-1]
-70
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-30
0
30
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70
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Summary & Ongoing Work
 Multi-bands are found in 53% of 50 cyclones exhibiting ≥ 1”/h snowfall
amounts between 1997-2014 in the Northeast coastal region and are an
important part of the precipitation structure evolution
 Multi-bands occur during a less developed period of the baroclinic wave with
weaker frontogenesis than single band times, but more instability.
 The MYJ PBL & Thompson microphysics schemes provided the most
representative simulation of multi-bands for 26-27 Dec 2010 case
 Is this configuration true for a larger variety of similar cases? What about varying
IC/BCs?
 A high-resolution gridded dataset is necessary to quantify the evolution of
stability, moisture and lift attributed to the evolution of the banded
precipitation structures in these coastal cyclones
Thank you!
[email protected]
http://flurry.somas.stonybrook.edu/band_study/
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