2. Data and Methodology
2.1 Freezing Rain Climatology
Changnon and Creech (2003) surveyed the various sources of data on freezing
rain and ice storms. They determined that daily and hourly surface observations are
available dating back to the 1920s and archived by the National Climatic Data Center
(NCDC). Specifically, the Integrated Surface Database (ISD) contains hourly surface
observations from more than 20,000 stations globally. Primary components of the ISD
include the Automated Surface Observing System (ASOS) network, synoptic reports,
METAR reports, surface airway observations, and military observations (Smith et al.
2011). In this study, hourly surface observations from the ISD were employed to: 1)
create long-term records of freezing rain occurrence at individual stations, and 2) analyze
the spatial and temporal variability of freezing rain.
For the purposes of our climatology, we define a freezing rain hour as a single
report of freezing rain (as indicated by the present weather identifier or the METAR
code). Observations must be issued either on the hour or no more than 15 min preceding
the new hour, and sequential reports of freezing rain must be separated by at least 45 min
to be considered as two discrete freezing rain hours. Moreover, we assume that a single
report represents 1 h of freezing rain ending at the nearest hour. For instance, if freezing
rain was included in a METAR report issued at 2251 UTC, we assume that freezing rain
was observed during the entire period between 2200 UTC and 2300 UTC. Although this
method is inherently prone to error, previous studies have used a similar approach when
calculating freezing rain frequencies (e.g., Bernstein 2000; Robbins and Cortinas 2002).
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A freezing rain event consists of all hourly freezing rain observations occurring
within 6 h of each other. If more than 6 h passes between sequential freezing rain
observations, the most recent observation marks the beginning of a new event. The 6-h
threshold implies that all instances of freezing rain during a single event are associated
with the same synoptic forcing. A significant freezing rain event requires at least 6 h (not
necessarily consecutive) of freezing rain in a 24-h period, with no more than 6 h between
sequential freezing rain observations. Previous studies have also adopted the 6-h
minimum threshold when identifying “severe” freezing rain episodes (e.g., Ressler et al.
2012). Lastly, the significant event ratio is defined as the number of significant freezing
rain events divided by the number of total freezing rain events.
Figure 2.1 illustrates the locations of all 225 stations in our climatology, along
with surface elevation shaded every 250 m. The climatology uses an extended domain
(32° to 48°N, 90° to 66°W) in order to adequately capture both synoptic-scale and
mesoscale variability of freezing rain across the eastern U.S. and southeastern Canada.
Because hourly observations were substantially limited before 1975, we only considered
the 1975–2010 period. We defined the cool-season as Oct–Apr and thus neglected any
freezing rain reports between May and September.
Qualifying stations were selected based on three strict quality control criteria.
First, a candidate station must have at least 28 cool-seasons of hourly observations (80%
of all 35 cool-seasons). Second, a candidate station must take at least 16 hourly
observations each day (66.7% of all hourly observations in a 24-h period). Third, a
candidate station must report present weather type(s) on an hourly basis. For stations that
met these criteria, we applied two additional constraints. We removed stations whose
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calculated freezing rain frequencies were markedly different from those of nearby
stations, as well as non-first-order stations located in close proximity to first-order
stations.
2.2 Ice Storm Climatology
Despite the relative abundance of freezing rain observations, historical records of
ice accretion are spatially and temporally limited. The Association of American Railroads
conducted direct ice load measurements for damaging ice-storm areas, but only during
the 1928–1937 period (Hay 1957). Ice thickness estimates have been documented in
NCDC’s Storm Data publication since 1959, but many early entries lack important
details and reports are subject to human errors and population biases (Changnon and
Creech 2003). Nevertheless, Storm Data offers the most complete long-term record of
icing events impacting each state. Moreover, Storm Data provides useful information
about regions, counties, and zones affected, event durations, precipitation types observed,
icing amounts, and damage estimates.
A given event in Storm Data qualified as an ice storm if one of the following
three criteria were met: 1) the event was listed as an “Ice Storm”, 2) the event featured
freezing rain resulting in significant ice accumulations (≥ 0.25 in/0.64 cm), or 3) the
event featured damage specifically attributed to ice accretion. Although NWS Weather
Forecast Offices (WFOs) in New York and New England typically adopt a stricter 0.50 in
(1.27 cm) minimum criterion when issuing an ice storm warning, the NWS general
definition for an ice storm uses the 0.25 in (0.64 cm) threshold (Call 2009). Furthermore,
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past events have demonstrated that ice accretions well below 0.50 in (1.27 cm) can still
cause tree damage and/or power outages.
Figure 2.2 highlights the 14 county warning areas (CWAs) included in the ice
storm climatology. This domain encompasses the New England states, New York,
Pennsylvania, New Jersey, Delaware, Maryland, northern Virginia, West Virginia, and
eastern Ohio. The southern boundary separates our domain from the region primarily
dominated by cold-air damming events (central North Carolina and southern Virginia).
Since Storm Data lacks sufficient detail about icing events prior to 1993, we limited our
climatology to cool-seasons (Oct–Apr) during the 1993–2010 period.
For each ice storm, we noted the counties and CWAs affected, icing amount, and
damage. Once all individual ice storms were identified, we evaluated the geographical
and temporal variability of ice storms, then classified events by spatial coverage and
applicable synoptic-scale features. Based on the number of counties and CWAs impacted,
ice storms were defined as local, regional, subsynoptic, or synoptic (refer to Table I for
complete descriptions). Additionally, ice storms were categorized according to seven
archetypical synoptic weather patterns commonly associated with freezing rain (Rauber
et al. 2001b). Type A events occur behind an arctic front, usually within the southwestern
or southeastern quadrants of an anticyclone (Fig. 2.3a). Type B and C events are
generally associated with a surface cyclone and occur on the cold side of a
warm/stationary front or within the occluded region of the cyclone (Figs. 2.3b and 2.3c).
Type D events occur in the western quadrant of an anticyclone (Fig. 2.3d). Type E, F, and
G events occur under cold-air damming conditions along and east of the Appalachians
(Figs. 2.3e, 2.3f, and 2.3g). However, while Type E and F events are typically associated
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with a surface trough or cyclone along the Atlantic coast and a dominant anticyclone
north of the damming region, Type G events are strictly associated with a surface cyclone
approaching the Appalachians or Great Lakes from the west or southwest. Due to the
fundamental similarities between Types B and C, and E and F, we grouped these patterns
together as Type BC and Type EF.
2.3 Composite Analysis
After partitioning ice storms by the five synoptic weather patterns (A, BC, D, EF,
and G), we composited events based on the two most prevalent patterns in each CWA.
Synoptic composite maps and composite cross sections were created from 2.5° National
Centers for Environmental Prediction–National Center for Atmospheric Research
(NCEP–NCAR) reanalysis data (Kalnay et al. 1996) and 0.5° Climate Forecast System
Reanalysis (CFSR) data (Saha et al. 2010), respectively. The synoptic composites
demonstrate how large-scale circulations, thermal boundaries, and moisture transport
establish environments conducive to ice storms. We also applied the Q-vector form of the
QG omega equation (Eq. 2.1) and the definition of the Q-vector (Eq. 2.2), ignoring the
𝑅
− 𝑝 term, from Sanders and Hoskins (1990) to investigate the associated QG forcing:
2
(𝜎𝛻𝑝2 + 𝑓02
𝜕
⃗ (2.1)
⃗ 𝑝•𝑄
) 𝜔 = −2∇
𝜕𝑝2
⃗𝑔
𝜕𝑉
• ⃗∇𝑝 𝑇
𝑄
𝜕𝑥
⃗ =
𝑄
= ( 1 ) (2.2)
𝑄
⃗
𝜕𝑉𝑔
2
⃗ 𝑝𝑇
•∇
( 𝜕𝑦
)
When considered together, the Q-vector analysis and composite cross sections
convey important synoptic–mesoscale linkages that influence the evolution and
persistence of ice storms. Analyses were performed at t−48, t−24, and t0, where t0 represents
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the synoptic time (0000, 0600, 1200, 1800 UTC) nearest the midpoint of each event, and
the subscript denotes the number of hours preceding t0. In this paper, we will present and
discuss the results of our composite analysis for ice storms impacting the Albany, NY
(ALY), CWA.
2.4 Case Studies
Based on the composite analysis of ALY events, we conducted case studies of ice
storms that fit the two most prevalent synoptic weather patterns (Type G and Type BC).
Two such cases include the 3–4 Jan 1999 (Type G) and 11–12 Dec 2008 (Type BC) ice
storms, both of which featured prolonged freezing rain, significant ice accretions, and
power outages over relatively large geographic areas. We adopted a multiscale
perspective to examine the synoptic-scale evolution of each ice storm and discuss the
physical mechanisms that extended the duration of freezing rain. Upper-air and surface
maps were created with 0.5° CFSR data and serve to highlight critical dynamical
processes. Radiosonde data were obtained from the University of Wyoming
(http://weather.uwyo.edu/upperair/sounding.html) and used to describe the local
thermodynamic environment associated with freezing rain. Finally, parcel trajectories
were calculated from the National Oceanic and Atmospheric Administration’s (NOAA)
Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model (Draxler and
Hess 1998) and indicate the primary source regions for air parcels entering each ice storm
area.
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Figure 2.1: Surface map showing the location of all 225 stations (red dots) in the
freezing rain climatology. The elevation (meters above sea level) is shaded every 250 m.
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Figure 2.2: Map highlighting the 14 CWAs included in the ice storm climatology.
Size
Local
Regional
Subsynoptic
Synoptic
Counties Affected
≤3
4–12
13–48
> 48
AND
AND
AND
OR
CWAs Affected
≤3
≤6
≤6
>6
Table I: Classification scheme for categorizing ice storms by spatial coverage.
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Figure 2.3: Archetypical surface synoptic weather patterns associated with freezing
precipitation east of the Rocky Mountains. Caption and figure reproduced from Fig. 2 in
Rauber et al. (2001b).
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