observed and simulated multi-bands in northeast u.s. winter storms s ara a. g anetis 1, b rian a. c...
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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
Moisture Instability
Lift
Single Band
Single Band Nonbanded
Nonbanded
Novak et al. 2004• 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
Novak et al. 2010• 75 cases, 30 single-banded cases for 2002-08• Band-relative composites using 3-hourly 32-
km (NARR) data and hourly 20-km RUC data
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Previous Work on Microphysics within East Coast Storms
Stark et al. (2013)• Case studies examining microphysical evolution of snowbands
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Novak et al. 2009• Confirmed the capability of a mesoscale model in simulating single-banded storms
Observation
4-km MM5 Simulation
Previous Work on Utilization of Mesoscale Models
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What about Multi-bands?
Reflectivity [dBZ]
26-27 Dec 2010 OKX 0.5° Reflectivity
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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
Previous Work on Multi-bands
Novak et al. 2006
Cross-section of vertical velocity for a saturated region in the presence of negative moist geostrophic potential vorticity (Xu 1992).
Stable Unstable
VT
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Science QuestionsWhat 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
123 Cyclone DatesReporting ≥ 1” snow
in 24 h
71 Cyclone Dates w/ Radar Data from KDIX, KOKX, KBOX
Source: US Census Bureau
• 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
50 Cyclone cases with radar data available for entire duration of storm
Terrain Height [m]
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Band Description
Band Type
Single bandLinear 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
Classification Methodology
Single band
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Classification Methodology Band Description
Band Type
Single bandLinear 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
Multi-bands
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Classification Methodology Band Description
Band Type
Single bandLinear 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
Both Single & Multi-bands
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Classification Methodology Band Description
Band Type
Single bandLinear 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
Non-banded
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Preliminary Event Results
Terrain Height [m]
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
Spatial Distribution
Moisture Instability
Lift
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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
N-3 N0 N+3Multi-bands Both Single & Multi-bands
Multi-bands Both Single & Multi-bands
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Composite Results: 300 mbSingle Band Multi-bands
Both Single & Multi-bands
Non-bandedWind Speed [kt]
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Composite Results: 700 mbSingle Band Multi-bands
Both Single & Multi-bands
Non-bandedRelative Humidity
[%]
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Composite Results: Forcing for LiftSingle Band Multi-bands
Both Single & Multi-bands
Non-bandedFrontogenesis
[K (100 km 3 h)-1]
-5 -2 -1 1 2 5
Hypothesis:There is low-to-mid-level frontogenesis inducing an ageostrophic vertical circulation that provides forcing for lift for both single bands and multi-bands
850 mb Frontogenesis
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Composite Results: InstabilitySingle Band Multi-bands
Both Single & Multi-bands
Non-banded
Hypothesis:There is larger instability in the low-to-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
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
36 km
12 km
4 km
1.33
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Mesoscale Model Results: 0000 UTC 27 Dec 2010 Simulated Reflectivity
OKX 0.5°
Reflectivity [dBZ]
MYJ PBL / Thom MP MYJ PBL / WSM6 MP
YSU PBL / Thom MP YSU PBL / WSM6 MP1-km AGL Stitched
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Mesoscale Model Results: 0000 UTC 27 Dec 2010 OKX Sounding
MYJ PBL / Thom MP
MYJ PBL / WSM6 MP
YSU PBL / Thom MP
YSU PBL / WSM6 MP
OKX Sounding
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Mesoscale Model Results: 850 mb Geopotential Height26/1800 27/0000
27/0300 27/0600
MYJ PBL / Thom MP
MYJ PBL / WSM6 MP
YSU PBL / Thom MP
YSU PBL / WSM6 MP
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Mesoscale Model Results: Dec 2010 Simulated Reflectivity
00 UTC 27 Dec 2010
Reflectivity [dBZ]
OK
X 0
.5°
Ref
lect
ivit
y
WR
F 1
.33
-km
Do
ma
in 5
00
-m A
GL
S
imu
late
d R
efl
ec
tiv
ity
FH 18 Valid 00 UTC 27 Dec 2010
FH 19 Valid 01 UTC 27 Dec 2010
FH 21 Valid 03 UTC 27 Dec 2010
01 UTC 27 Dec 2010 03 UTC 27 Dec 2010
B
B’
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FH 18 Valid 00 UTC 27 Dec
FH 19 Valid 01 UTC 27 Dec
FH 21 Valid 03 UTC 27 Dec
BB’
BB’
BB’
Reflectivity [dBZ]
-70 -30 0 30 70
Frontogenesis [K (100 km h)-1]
Simulated Reflectivity, θes, Circulation Vectors
Frontogenesis, θe, Circulation Vectors
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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 [email protected]
http://flurry.somas.stonybrook.edu/band_study/