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An Analysis on the Impacts of Ice Cover on Two Eastern Great Lakes Lake Effect Snow Events
Honors Thesis
Presented to the College of Agriculture and Life Sciences, Department of Earth and Atmospheric Sciences of Cornell University
in Partial Fulfillment of the Requirements for the Research Honors Program
by
Brian A. Crandall May 2010
Stephen J. Colucci
2
ABSTRACT
Analysis of lake effect snow events is important due to the economic effects lake effect
events can have on a region, such as the replenishment of watersheds used in agricultural
purposes. It is generally accepted that a number of factors play a role in the persistence and
intensity of lake effect snow events, such as ice formation of the surface of the lake, but only
recently has that relationship begun to be thoroughly examined. This observational study focuses
on the impact of lake surface ice coverage on two lake effect storms that occurred downwind of
both Lake Erie and Lake Ontario: “Jack Russell”, which occurred from February 19-20 2008,
and “Jararaca”, which occurred from January 16-17, 2009. This study undertakes a graphical
analysis of the lake surface conditions at the time as well as a mathematical study of the heat
fluxes and total energy transfer interaction between the lakes and the atmosphere during the
duration of the two lake effect events. The analysis identifies that Lake Erie, which is mostly ice
covered, experiences a significant decrease in energy transfer as the event persists, while the
relatively ice-free Lake Ontario experiences no significant change in energy transfer for the
duration of the two storms. Graphical analysis indicates that the areas of heaviest and most
persistent snowfall were experiencing wind fetches off the lake that had traveled over lake
surface areas with minimal ice coverage and thickness, highlighting the influence of ice coverage
and thickness on the development of lake effect bands.
3
1. Introduction
The study of lake effect snow is important because of its short and long-term impacts. In the
short-term, severe lake effect events can cause persistent heavy snows that can impact
transportation infrastructure, cause widespread power outages, damage to buildings and human
injury (Peterson et al. 2008, Schmidlin 1993, Schmidlin and Kosarik 1999, GLRA 2002). In the
longer-term, lake effect snow is important for winter-weather recreation and replenishment of
watersheds that may be used in agricultural processes (Burnett et al. 2003).
The development of lake effect snow bands is affected by a number of environmental
factors, including the amount and thickness of ice cover on the lake surface. To investigate this
relationship further, two late-season lake effect snow events where ice was believed to be a
factor were selected: “Jack Russell”, which occurred over Lakes Erie and Ontario from February
19-20, 2008, and “Jararaca”, which occurred from January 16-17, 2009. This is important
because ice does not begin to form in any significant amount on the Great Lakes until December
and January, and maximum spatial coverage is reached usually in late February or early March
(Assel 1990, 1999).
Jararaca occurred at a time when Lake Erie was largely frozen over, and as a result the
Lake Ontario band was better developed than its Lake Erie counterpart. According to the
National Weather Service (NWS) Buffalo branch’s snow spotter datasets, while the Lake Erie
bands produced no more than 12” with the highest accumulations concentrated to the south and
west of Buffalo in southeastern Erie County, the better-developed Ontario bands produced
accumulations as high as 29” on the Tughill Plateau in northeastern Oswego County and
southeastern Jefferson County (Fig. 1). This particular storm is useful in determining the effect
4
of ice cover because of the differing conditions between Lake Erie and Lake Ontario; Jararaca
serves as a good example of an event where ice coverage inhibits lake effect development.
In comparison, Jack Russell provided a more complicated situation. Being late in the
season, the Lake Erie snow bands were forecast to be weak due to the lake being covered with
extensive amounts of ice at the time. Ontario was not as covered by ice and was expected to have
better-developed snow bands. While the expectations for Ontario were correct (NWS at Buffalo
archived snow spotter reports indicate a maximum accumulation of 49” of snow was recorded in
northeastern Oswego County), a recent warm spell had broken up some of the Erie surface ice,
allowing for the Erie bands to develop more than expected, with snow spotter reports of
accumulations as high as 14” on the eastern shores of Lake Erie near Buffalo (Fig. 2). The
unexpected melting of surface ice resulted in the forecast underestimating the Lake Erie bands.
This unusual event highlights the importance of closely and accurately monitoring the conditions
of ice coverage and thickness when there is potential for lake effect snow band development.
2. Literature Review
There have been a number of papers published on lake effect snow events in the Great Lakes
region (Braham 1983; Reinking et al. 1993, Ballentine 1998, Kristovich et al. 2000), but the
these events occurred under relatively ice-free conditions. At least two previous studies on lake
effect snow have noted the influence of ice on lake effect events (Niziol et al. 1995, Rauber and
Ralph 2004). Niziol et al. noted that significant ice coverage has the effect of limiting surface
and moisture flux exchanges. More specifically, the detailed effect of ice cover on individual
lake effect events has been the subject of a few recently-published papers (Kristovich and Laird
2002, Laird and Kristovich 2004, Cordeira and Laird 2007). In Laird and Kristovich (2004), out
5
of 640 lake effect events that the authors evaluated for ice coverage, 11 historically significant
Great Lakes lake effect snow events occurred with extensive ice coverage; their investigation
determined that 8 of the events occurred when the underlying lake had greater than or equal to 80
percent ice concentration, and that 3 events occurred when the underlying lake had greater than
or equal to 95 percent ice concentration over the entire lake. However, these events were each
treated as distinctly separate events and do not constitute a comparison. Kristovich and Laird
(2002) focused on Lake Michigan, and Cordeira and Laird (2007) examined only Lake Erie; a
comparison of the same storm affecting two of the Great Lakes, such as Lake Erie and Lake
Ontario when affected by the same storm, has not been undertaken.
Laird and Kristovich (1998) described a previously-derived mathematical formula (Garratt
1992) that determined surface lake fluxes using lake water temperatures and meteorological
observational data taken from upwind stations near the shore of Lake Michigan. Positive values
indicated heat transfer out of the lake and into the surrounding atmosphere. Bulk transfer
relationships were utilized by the authors since a vertical profile of observations was not present
at each measurement location. By doing so, temporal trends and estimated values of the flux over
the lake would be closely related, though they noted the exact values may not be quantitatively
equal. Laird and Kristovich chose this particular method of determining surface flux because it
gave reasonable values compared to past in situ observations of fluxes over Lake Michigan and
due to limited vertical extent of the wind and temperature observations.
In the case study undertaken by Cordeira and Laird (2007), the two lake effect events
examined occurred in February 2003 and January 2004, both late-season developments. Both
storms also maintained well-developed, persistent snow bands, resulting in snowfall
accumulations as high as 43.2 cm (17”) in the 2003 case and 63.5 cm (25”) in the 2004 case.
6
Their paper described synoptic conditions before and during the event according to data
collected by the National Climatic Data Center (NCDC), and also pulled temperature, dew point,
wind direction and wind speed data from nine stations in the vicinity of Lake Erie. Of these nine
stations, four were identified as upwind from the fetch and five were downwind from the fetch
near the eastern shores of the lake. Accessing data from the Great Lakes Environmental Research
Institute (GLERL), the authors determined the conditions of the ice coverage on Lake Erie
during the time periods of the two lake effect storms, and using the formula described in Laird
and Kristovich (2004), they examined on an hourly level the heat fluxes between the lake surface
and the air immediately above the surface. To determine the passage of fetch winds over
different ice concentrations of Lake Erie, the authors made use of the Air Resource Laboratory
(ARL) HYSPLIT trajectory model, plotting backwards the points of the highest accumulations
from each snow band as recorded by the National Weather Service (NWS). In their examination
of the Lake Erie heat fluxes, Cordeira and Laird found that the positive heat flux values tended to
decrease in magnitude with time, even when diurnal effects were taken into consideration. They
also noted that the area of highest snowfall accumulation from the Lake Erie snow bands were
downwind of fetch that passes over the parts of the lake that had minimal ice coverage and
thickness. While Laird and Cordeira (2007) examine Lake Erie in detail, they did not do a
comparison between two lakes, nor have any studies examined ice cover on Lake Ontario.
3. Data and Methodology
For this observational study, data were incorporated from archived station data, radar, and
satellite images for both of the lake effect events in order to try and understand the conditions at
the time and better evaluate the influence of the ice coverage and thickness. Considering Figures
1 and 2, the geographic distribution of the two events for the two lakes can be ascertained,
7
indicating the larger snowfall amounts for areas downwind of Lake Ontario and larger snowfalls
for areas within 25 km of each lakeshore.
In order to obtain relevant meteorological data for Lake Erie and Lake Ontario, multiple
surface stations were selected for locations downwind and upwind of each lake. For Lake Erie,
three upwind stations were used [KDTW (Detroit Metro Airport), CWAJ (Erieau, Ontario,
Canada), CYXU (London, Ontario, Canada)] and five downwind stations [KBUF (Greater
Buffalo International Airport, Buffalo, New York), KDKK (Chautauqua County/Dunkirk
Airport, Dunkirk, New York), KERI (Erie International Airport, Erie, Pennsylvania), KIAG
(Niagara Falls International Airport, Niagara Falls, New York) and KJHW (Chautauqua County
Airport, Jamestown, New York)] were also used (Fig. 3a). For Lake Ontario, four upwind
stations were used [CYYZ (Pearson International Airport, Toronto, Canada), CYPQ
(Peterborough, Ontario, Canada), CYHM (Hamilton, Ontario, Canada) and CYGK (Kingston,
Ontario, Canada), and four downwind stations [KART (Watertown International Airport,
Watertown, New York), KFZY (Oswego County Airport, Fulton, New York), KSYR (Hancock
International Airport, Syracuse, New York) and KROC (Greater Rochester International Airport,
Rochester, New York)] (Fig. 3). Relevant data included air temperature, dew point, wind
direction, wind speed, current weather conditions, sea level pressure and cloud cover.
Radar data were obtained from the NCDC’s NEXRAD radar archive. Data sets were ordered
directly from the website (http://www.ncdc.noaa.gov/oa/radar/radardata.html) and processed
using a java application called the “NCDC Weather and Climate Toolkit” which was also
downloaded from the website. For the purpose of this study, data were ordered starting at 18Z on
the day prior to the date the National Weather Service determined as the starting date of the
event, continuing for the whole duration of the event, up to the six hours immediately after the
8
event concluded. For Jack Russell, data were ordered from 18Z on February 18th, 2008
continuous through 06Z on February 21st, 2008, and for Jararaca data were ordered from 18Z on
January 15th, 2009 continuous through 06Z on January 18th, 2009. For consistency, all data were
ordered on Level-II Base Data in the REF format. Radar data for Lake Erie was taken from the
archives of the KBUF (Buffalo, New York) radar, and data for Lake Ontario was taken from the
KTYX (Fort Drum/Montague, New York) radar. KTYX consists of only a radar site and does
not maintain a fully-functional weather station (Brown et al. 2007). Once processed through the
NCDC toolkit, the radar images were exported along with the station data to the Grid Analysis
and Display System (GrADS) visualization tool.
Regarding the synoptic environment, surface charts and upper-air charts from the 850 mb
level that were produced by the National Centers for Environmental Protection (NCEP) were
obtained from the NCDC, and these were used to investigate the influence of synoptic-scale
factors on the lake effect snow bands. Surface analyses were obtained in 3-hour intervals and
850mb analyses were obtained in 12-hour intervals, the shortest intervals available between
successive analyses at each pressure level. For the actual ice coverage and thicknesses on the
lake, ice analysis charts created by the Canadian Ice Service (CIS) were obtained from the
National Ice Center (NIC) through the North American Ice Service (NAIS) partnership. The ice
charts are created using Moderate Resolution Imaging Spectroradiometer (MODIS) and
Geostationary Operational Environmental Satellite (GOES) image data. The ice charts are
produced on Sundays and Wednesdays. For the Jack Russell snow event, ice analyses were
retrieved for February 14th, February 18th and February 21st, 2008. For the Jararaca snow event,
ice analyses were retrieved for January 12th, January 15th, and January 19th, 2009.
9
NIC ice analyses are produced by manual interpretation of several different data sources,
including data obtained from direct nautical observation, remote sensing data (infrared, visible,
active and passive microwave), air reconnaissance data and model outputs (Fetterer and Fowler
2006). While the uncertainty of NIC ice analyses has never been thoroughly examined,
Partington et al. (2003) estimates the accuracy of ice concentrations to be within +/- 5-10% of
the actual value.
Fetch distances over the lake surface are important for determining the intensity of lake effect
snow bands (Kristovich and Laird 2004). To examine the relation of fetch trajectories, ice
thickness, and the amount of snowfall received downwind of the lake from a given event,
trajectories were obtained from the HYbrid Single-Particle Lagrangian Integrated Trajectory
(HYSPLIT) model developed by NOAA’s Air Resource Lab (ARL). The HYSPLIT model was
developed for use in modeling dispersion and deposition by taking an archived dataset and
determining and plotting forward and backward trajectories at a certain altitude (Draxler and
Rolph 2010). The HYSPLIT model was accessed at the ARL’s website
(http://www.arl.noaa.gov/ready.html). For the purposes of this study, the National Center for
Environmental Protection’s Global Data Assimilation System (GDAS) archived datasets was
utilized. The trajectories were initialized at a height of 500 meters, and are modeled backwards
six hours from the geographic coordinates of the communities that received the heaviest snow
accumulations from each lake as determined from NWS snow spotter data. In order to account
for atmospheric dynamic changes that would lead to fetch variation, the model inputs were set
such that for each hour backwards from initialization, the trajectory splits into two trajectories,
one using preset perturbation already programmed into HYSPLIT, and the initial trajectory that
10
remains unaltered. As this doubles the number of trajectories after each hour, the model
produces 32 separate endpoints for a six hour model run.
For each lake in each case under examination, a total energy transfer (TET) analysis was
conducted to better understand the energy transfer from the warm lake to the cooler air lying
directly above the surface, and its ability to modify the regional atmosphere and induce lake
effect development. Total energy transfer is the product of the ice-free lake surface area and total
heat flux, based on an approach used by Jeffries and Morris (2006) in which they measured the
total energy loss for Canada’s Great Slave Lake.
TET is imperative to our understanding of lake effect development because of its ability to
modify the stability of the boundary layer of air directly above the lake surface. This
modification of air generates CAPE, and it is the formation and release of CAPE that drives lake
effect snow production (Markowski and Richardson 2010). TET is calculated for the ice-free
open surface area, and frozen-over areas are assumed to have a TET of 0 W/m2, meaning no
energy transfer. The one major drawback of this method of estimating TET is that it inaccurately
assumes that there is no heat transfer through ice-covered areas, when in reality the energy
transfer is greatly reduced but still present (Jeffries and Morris 2006). However, given the lack of
sufficient data on ice thickness, this method was chosen to examine TET by Cordeira and Laird
(2008) on an hourly interval based on a lake-wide average of individually calculated heat fluxes
from each of the stations upwind and downwind of each lake. Stations are subdivided into Lake
Erie and Lake Ontario heat flux datasets, with lakeshore and lake-vicinity subsets taken into
consideration during analysis. The heat fluxes are then averaged over all stations; Jeffries and
Morris (2006) established this heat flux figure as the open-water value, so TET can be
determined as a figure in the hypothetical case where the lake has no ice whatsoever, and more
11
realistically where surface ice inhibits heat transfer, reducing the applicable surface area from
which TET is partially calculated.
In order to calculate the sensible and latent heat fluxes used in the calculation of TET, a
previously derived bulk formulation formula was used (Kristovich and Laird 1998, Garratt 1992,
Stull 1988). Although there are several methods of bulk formulation that may be applied to
determine energy fluxes, Laird (personal communication) used this approach because of its use
of routinely collected observations from lakeshore stations. The formulas used to determine the
sensible and latent heat flux are as follows:
�� � ������� �� (1)
�� � ����� �� � ����� �� (2)
where �� is the sensible heat in W/���, �� and��� are non-dimensional bulk transfer
coefficients of heat and moisture respectively, (roughly constant at a value of 1.5 * ���� ), �� is
specific heat at constant pressure for dry air (1004.5 J/kg*K), ��is air density (roughly constant to
1.25 kg/��� ), �� is the latent heat of vaporization (roughly equal to 2500 J/g), u is the mean
wind speed, �� and ���are respectively the temperature and specific humidity at or very near the
lake surface water, and T and q are the overhead air temperature and specific humidity
respectively. Therefore, the formula for determining total heat flux is as follows:
�� ���� ���� (3)
The mean wind speed u and temperature T are taken directly from hourly station
observations, converted into the proper units. ���being at or very near the lake surface is assumed
to be equal to 1 for the purposes of this study, and lake water temperature, following a previous
12
example in Cordeira and Laird (2008), is set equal to 0 C for partially frozen over lake-surface
areas. This was assumed to be adequate due to the significant ice concentrations at the lake
surface and the lack of available water measurements for the Great Lakes during the winter
months (Cordeira and Laird, 2008). Specific humidity can be calculated from relative humidity
observed at weather stations by determining the mixing ratio when saturated with water vapor,
and by performing the following operations:
� ! �� "#�
$%$&'()* +&
$&, -�# � -
��./ (4)
� � � 0&12$��
-3�0&12$�� (5)
In these equations, 45 is a constant value equal to 6.11mb, p is the pressure at the station at a
given observation time,�67 is a dry air constant equal to 287 J/kg*K, 6 is a saturated air
constant equal to 461 J/kg*K, �5 is 0 C (imputed as 273.15 K), and T and RH are the respective
temperature and relative humidity at a given station and time.
These calculations were performed on hourly intervals for each station during each lake
effect event being examined. The results were then plotted as a function of time to identify any
apparent trends or features in the Total Energy Transfer values.
4. Case 1: 16-17 January 2009 “Jararaca”
a. Regional conditions overview
Arctic air following the passage of a frontal boundary was firmly in place over the
eastern Great Lakes region at 1200 UTC on 15 January 2009. Surface temperatures throughout
the region were in the 12 to -12 Fahrenheit range (-12 to -25 Celsius) range (Fig. 4d) with winds
near the surface being light and variable, and that was the case for 850 hPa winds as well (Fig.
13
4a). Water temperatures at this time were at or near 0 degrees Celsius, with significant ice
coverage reported over Lake Erie by the National Ice Center. By the 16th, winds shifted to 5 to
10 m/sec out of the southwest and conditions in the region began to favor lake effect
development as lapse rates were near the dry adiabatic lapse rate of 9.8 degrees Celsius/km
(Fig.5). Around 2000 UTC on 15 January, poorly organized lake effect snow showers began to
form downwind of Lake Erie along the shoreline of Chautauqua County, and eventually, two
distinct lake effect band developed, a moderately strong band over southern Erie County, with a
less intense band developing over the shores of Chautauqua County. The southern band
remained fairly constant in direction in part due to winds out of the WSW at 260 degrees, while
the northern band oscillated slightly north into central Erie County by 0000 UTC on the 17th
(Fig. 6). The southern band became disorganized and shifted into southern Erie County by 0000
UTC on the 17th, and both bands steadily weakened near daybreak as winds shifted to the
northwest and then to the north, the bands remaining distinctly separate of one another until they
fully dissipated around 1000 UTC on the 17th.
Lake effect bands off of Lake Ontario began to develop in earnest around 1500 UTC on
16 January, and rapidly intensified over the next few hours due to a lack of surface ice over the
open waters of Lake Ontario, with the most intense portion of the band centered over northern
Oswego County (Fig. 7), shifting slightly southwards into central Oswego County after 0000
UTC on the 17th. The band weakened during the overnight hours and then re-intensified after
0900 UTC, shifting back north to the Oswego-Jefferson County line. The band continued to
move north as the day progressed, moving into central Jefferson County near Watertown before
weakening due to northerly shifting winds and fully dissipating around 2200 UTC on the 17th.
b. Ice coverage and trajectories
14
A detailed analysis of the lake surface ice conditions is necessary to understand the
interactions between ice coverage and any possible influence it may have on mesoscale weather
systems. Looking at the case of Jararaca, ice rapidly built up on Lake Erie during the days prior
to and including the formation of the snow bands. NIC ice charts analysis suggest thin (thickness
less than 30 cm) but widespread (9-10/10) ice over the western half of lake Erie and along the
northern and southern shores of the lake, leaving the central and eastern shores of the lake with
less than 1/10 ice coverage (Fig. 8a). Due to the cold air temperatures over the region, ice
continued to build up on the lake, and by the 15th the only portion of the lake that was ice-free
was a small area over the east-central part of the lake. Fast ice, thin widespread and medium
thickness (30 to 71 cm) widespread ice dominated most of the lake surface (Fig. 8b). By the 19th,
charts indicate that the lake nearly completely frozen over with thin and medium ice, and even
some thick (thickness greater than 71 cm) ice over the far western part of Lake Erie (Fig. 8c).
In general, lake ice on Lake Ontario is less extensive than for Lake Erie (Assel 1990), and
the situation during the Jararaca event was no different. NIC ice charts indicate a gradual
increase in the amount of ice on the lake just prior to and leading up to the occurrence of the lake
effect event. On the 12th of January 2009, ice concentrations were generally limited to thin
(thickness less than 30 cm), widespread (9-10/10) ice and fast ice (ice adhered to the shoreline)
of medium thickness (thickness between 30 and 71 cm) located over the northeastern part of the
lake, with smaller areas of thin, not as widespread (4-6/10 or 1-3/10) ice located along the coast
in the southeastern and north-central shores of the lake and the south-central shoreline near
Rochester, New York (Fig. 9a). As the week progressed to the 15th, the ice coverage in the
northeast generally spread outwards into the lake and along the northeastern shores, indicating
sufficient cold air temperatures to promote lake surface ice development and verifying the NCEP
15
charts during this period (Fig. 9b). By January 19th, two days after the lake effect snow bands
ceased, ice coverage had increased to 4-8/10 coverage along all parts of the Ontario lakeshore,
although ice coverage remained thin (Fig. 9c).
An examination of HYSPLIT trajectories proves very useful in analyzing wind fetch
during the time of the lake effect event. Looking at the time period that Jararaca first began to
develop, and plotting retroactively to determine wind fetches over the previous 6 hours, it can be
determined if the fetch passed over open or ice-covered areas of the lake surface. According to
Gerbush (2008), the largest energy transfers occur with open water and decrease with the
formation of ice on the water surface, rapidly declining as ice thickness increases. Since energy
transfer is essential for the development of strong lake effect bands (Markowski and Richardson
2010), the more open water a fetch passes over, the better condition are for lake-effect
development. Overlaying the fetches on the ice charts (Fig. 10) for Jararaca shows that for Lake
Erie measuring back from the area of highest precipitation, the wind fetch passes directly over
the only notably large patch of open water on the lake surface. Although the lake is over 90%
frozen over, all of the fetches (and presumably the actual fetch itself) when computed back from
the area of highest snow band accumulation, pass over the only large open surface water on the
lake. An examination of Lake Ontario shows that although the general wind fetch is from the
northwest where the ice coverage is, most of the fetch perturbations spend a great deal of time
over open water; a few spend the entire previous six hours over open water. Therefore, it is likely
that the wind fetch spent a majority of time over open water, beneficial for development.
c. Discussion of heat fluxes and TET
16
While graphical analysis has its utility in analyzing the impacts of ice cover on lake effect
events, a mathematical analysis is essential to verify findings. This can be conducted by
analyzing the actual numerical values of the heat flux between the lake surface water and the air
immediately aloft over the lake. As the lakes tend to transfer heat from the water to the air during
the fall and winter (Niziol 1995), a positive heat flux value as determined by the previously
mentioned formulae indicates a flow of heat from the lake into the atmospheric boundary layer.
In reviewing data for the combined average of stations on or near Lake Erie, the general trend
was a decrease in the heat flux transfer with time from values around 200 W/m2 to values around
125 W/m2 (Fig. 11), meaning less heat energy flowing from the lake into the air as the event
progressed. Analysis of the graph with regards to time of the day does not indicate any notable
diurnal effect, although the values do fluctuate during the time period. The highest values of
nearly 300 W/m2 occur around the same time as period of most significant development for the
Lake Erie snow bands. An analysis in this case and all the other cases comparing lakeshore
stations versus inland stations does not turn out any significant difference between the heat flux
values of the two subsets of stations. The average heat flux value is approximately 211 W/m2,
and given a lake surface area of 25744 km2, this means the theoretical maximum TET for this
time is about 5432 GW. However, as the lake is 90% frozen over, this value is reduced to a
minimum of 543 GW. Regarding the methodology reviewed in section 2, this value is lower than
the actual value since some heat transfer does occur through ice-covered surfaces, but is a good
estimate of the TET given the available information.
In comparison, analysis of Lake Ontario shows no discernable pattern from the beginning of
the event to its chronological conclusion, beginning at around 100 W/m2 and finishing around
125 W/m2 (Fig. 11). However, there is a large rise during the daytime hours on the 16th, which is
17
also when the most rapid development of the Ontario snow bands took place; values during this
period were recorded as high as 250 W/m2, and a second smaller rise coincides with a re-
strengthening of the bands as they shifted northwards the night of the 16th into the 17th. Given the
average heat flux value to be around 155 W/m2, the theoretical maximum TET value for when
the 19500 km2 lake is completely lacking ice is about 3023 GW, and the more realistic figure
taking into account approximately 25% ice coverage is 2267 GW, more energy than what is
transferred from the largely frozen Lake Erie.
5. Case 2: 19-20 February 2008 “Jack Russell”
a. Regional conditions overview
Between 0500 and 0700 UTC on 18 February 2008, a strong frontal boundary associated
with a 983mb low and ahead of an arctic air mass pushed through the eastern Great Lakes region
(Fig. 12a). At this time, surface air temperatures in the region went from unseasonably warm
temperatures between 5-10 degrees Celsius to temperatures rapidly dropping into the 0 to -5
degrees Celsius range during the overnight hours (Fig. 12b), indicating strong cold air advection
for the time period of 0700 UTC-1200 UTC February 18 2008. Following the passage of the
frontal boundary, surface winds shifted from out of the southwest at 5 to 10 m/sec to more out of
the west at 10 to 15 m/sec, holding roughly constant for the next 48 hours at that wind direction
with little variance in speed (Fig. 12c). At the 850 hPa level, winds shifted from out of the SSW
at 25 to 30 m/s at 1200 UTC on the 18th to a more westerly direction by 1200 UTC on the 19th,
and shifted slightly northwesterly direction by 1200 UTC on the 20th, with wind speeds on the
19th and 20th holding fairly steady at 20 to 25 m/s (Fig 12d-f) . 850 hPa temperatures in the
region declined from -5 to 0 degrees Celsius at 1200 UTC on the 18th to -15 to -20 Celsius at
1200 UTC on the 19th. Light to moderate rainfall accompanied the initial frontal passage, with
18
disorganized light snows reported by 1800 UTC. As surface winds shifted to the west and
temperatures continued to drop to near -10 degrees Celsius throughout much of the region, Lake
Effect (LE) snowfall formed downwind of Lake Erie and Lake Ontario around 0900 UTC and
1200 UTC respectively. Lapse rates during this time were close to the dry adiabatic lapse rate
(9.8 degrees Celsius/km; Fig. 13), indicating near absolute or absolute instability throughout the
region, which strongly supports lake effect development (Markowski and Richardson 2010).
Water temperatures at this time were at or near 0 degrees Celsius. Development of the Erie band
was relegated largely to the south shore of the lake and to the eastern half well to the east of
station CWAJ, and affected areas along the southern shore of the lake in Chautauqua and Erie
County before shifting more to the northeast and into east-central Erie County (Fig. 14). The
Lake Ontario band, which was stronger, shifted to the south slightly into northern Oswego
County and then slightly northwards to along the Oswego-Jefferson County line (Fig. 15). By
0300Z on the 20th, winds had begun to slow considerably and LE snow bands began to dissipate,
with all activity ceasing off both lakes by 0900 UTC on the 20th.
b. Ice coverage and trajectories
The evolution of ice coverage on the lake surface is critical to understanding the
formation of the lake effect bands, particularly the unexpectedly strong Lake Erie bands as
reported by the NWS. February 14th 2008 NIC ice charts show that with the exclusion of a small
patch of southeastern Lake Erie comprising no more than 10% of the lake, the entirety of the lake
was covered with at least 1/10 ice per unit of surface area (an area with less than 1/10 coverage is
considered open water). Widespread (9-10/10 coverage) ice of thin (thickness less than 30 cm)
thickness was predominant on the lake, and moderate (thickness between 30 and 71 cm) to thick
(thickness greater than 71 cm) open water ices and fast ices were recorded towards the western
19
half of Lake Erie (Fig. 16a). The ice analysis chart produced by the NIC for the 18th of February
indicates that some ice has melted along the southern shore but has thickened in other areas of
the lake; with the exception of the southern shore of the lake and small portions of the far
western and north shore of Lake Erie (comprising no more than 20% of the lake surface), the
lake had at least 1-3/10ths ice coverage, with widespread coverage of 9-10/10 over approximately
two-thirds of the lake (Fig. 16b). With respect to the thickness of this ice, most of the ice was of
thin to medium thickness, with isolated thick fast ice in a couple of the bays along the northwest
shore of Lake Erie (no more than 1-2% of the total lake area). Ice Analysis charts updated for
February 21st suggest that the ice coverage of the lake had now increased to about 95% of the
lake surface, the only unfrozen area being a small, previously-frozen strip of open water along
the northwest shore of Lake Erie (Fig. 16c). The large majority of the surface of Lake Erie was
covered in ice at least 7/10 of the surface area, with over three-quarters of the lake under 9-10/10
coverage by a thin degree of thickness. The only areas that were recorded as medium thickness
were small portion of the western half of the lake, and the only thick areas were small regions of
fast ice along the western inlets. Overall, medium and thick ice depth did not constitute more
than 10% of the lake surface. Therefore, it would seem that while total lake surface ice coverage
increased with time, the average thickness of the ice seems to have decreased.
Looking at Lake Ontario, during the time period prior to and including Jack Russell, ice
coverage changes from the charts produced on the 14th to the charts produced on the 18th indicate
that ice coverage decreased in coverage and thickness, receding back to the northeastern corner
of the lake and becoming less widespread in coverage that region, retaining a thin degree of
thickness during the time period (Fig. 17a, 17b). From the 18th to the 21st of February, ice
coverage on Lake Ontario increased only slightly, by becoming slightly more widespread along
20
the northeast shore. This ice also decreased slightly in thickness as time progressed, going from
mostly thin to almost entirely thin ice (Fig. 17c). The slight increase in area but slight decrease in
thickness seem to suggest that total ice volume change for Lake Ontario during this time period
is negligible.
Regarding the trajectories, the HYSPLIT model of the wind fetch and its perturbations as
measured from six hours prior to the development of convection indicates that for areas impacted
with the most significant amount of precipitation, the wind fetch was likely parallel to the
southern shore of Lake Erie (Fig. 18) which, when compared to the ice charts chronologically
closest to the beginning of the Jararaca event, shows it also happened to be the only area that had
open lake surface water at that time. Examination of the Lake Ontario part of the event shows
that the wind fetch perturbations move northeastward and most of the perturbations fully avoid
the only concentrated ice area over the northeastern shores of the lake (Fig. 18), remaining over
open lake surface water. Therefore, the actual fetch most likely stayed over open waters.
c. Discussion of heat fluxes and TET
Reviewing the heat energy transfers for Lakes Erie and Ontario during the Jack Russell
event reveals some distinct characteristics to the values with respect to time. For Lake Erie, there
is a general trend downwards for the duration of the event; early on, heat flux values are near 105
W/m2 in value (Fig. 19), but rapidly increase about the same time the Lake Erie snow bands
begin to develop in earnest, reaching a maximum of about 180 W/m2 before trending steadily
downwards for the rest of the event, reaching a relative minimum near the end with values near
75 W/m2. This is similar to the general trend noted for the Jararaca event over Lake Erie,
although the values for Jack Russell are in general lower in magnitude. Lake Ontario exhibits no
21
distinct pattern to its values during the course of the Jack Russell, with values starting near 60
W/m2, dropping to a minimum below 40 W/m2, and then climbing upwards and holding roughly
steady to a maximum near 140 W/m2, afterwards fluctuating erratically through the rest of the
time period, with the last value around 80 W/m2. This is similar to Lake Ontario’s Jararaca
counterpart, and in that values for the Jack Russell event tend to be lower in magnitude. For
neither of the lakes is a diurnal pattern recognized within the values for Jack Russell.
Analysis of TET, given an average heat flux of about 94 W/m2 for Lake Erie and 103
W/m2 for Lake Ontario, returns open-water theoretical maximums of 2420 GW and 2009 GW
respectively, and taking into account Lake Erie experiencing 80% ice coverage and Lake Ontario
maintaining 15% ice coverage at the time of the vent, the actual values are closer to 484 GW for
Lake Erie and 1708 GW for Lake Ontario.
6. Discussion and Summary
General meteorological intuition suggests ice cover has a major impact on lake effect
development, but a thorough examination of that relationship has only begun to take place in
recent years (Gerbush et al. 2008, Cordeira and Laird 2007). A variety of mathematical and
graphical analyses can be used with recorded observations and data to illustrate the importance
of this relationship on the development of lake effect snow bands.
The evidence from the graphical analysis is clear. Looking at the levels of ice coverage and
thickness in comparison to the wind fetches for the areas of highest accumulations shows that the
wind fetches were limited in their passage over icy lake surfaces, especially areas of moderate or
thick ice. According to Gerbush et al. (2008), sensible heat values in an area of ice coverage less
than 70% and containing only thin thicknesses maintains values roughly similar to open-water
22
values for sensible heat fluxes. However, ice concentrations or larger thicknesses will reduce the
sensible heat flux rapidly, with heat flux values at 90% (9/10) coverage only 23-58% of their
open-water equivalents. Therefore, the graph overlays make sense, because if significant
amounts of energy are needed to promote snow band development, and the most energy comes
through water/air boundaries of relatively low ice concentration, then a significant snow band
needs open or partially open surface water to develop, with thin ice if any at all. The impact of
widespread ice versus open surface is particularly influential during the Jararaca event on Lake
Erie, where the most intense snow bands developed from fetches that passed over a small open-
water patch just prior to coming ashore. An average of the sensible heat flux during the time
period equals approximately 181 W/m2. Applying the values obtained by Gerbush et al. (2008),
this is the open-water surface flux; a reduction of 23-58% of this value as would be expected in
9/10 or greater ice coverage turns out values in the range of 42 W/m2 to 105 W/m2, heat flux
magnitudes which contribute far less convective energy towards snow band development.
Applying it to the aforementioned situation, the small patch where heat flux values were much
higher was apparently enough to supply enough additional transferred heat energy that it enabled
the snow bands to strengthen and produce larger accumulations inland.
Of special note are the values of the heat fluxes for the two lakes. Lake Erie observed general
decreases overtime during both lake effect events, while Lake Ontario exhibited no clear pattern
in heat flux values over time. In trying to come up with valid explanations, one possibility stands
out in particular: the physical differences between Lake Ontario and Lake Erie. Lake Ontario is a
deeper lake, and with the extra stored heat capacity that comes with being a deeper lake, is is not
as prone to freezing over like Erie (Assel 1999). Some of the air temperatures recorded during
these events are as low as -25 C, more than sufficient for ice formation. Lake Erie freezes over
23
more easily, and the surface ice already in place grows thicker in the cold temperatures. If ice
inhibits heat fluxes, the effect is quite apparent for Lake Erie, because as the lake effect events
progress, the cold temperatures cause heat fluxes to decrease and lake effect development is
inhibited. Although air temperatures are cold over both lakes, ice does not form easily on the
deeper lake, with the exception of the much shallower coastal areas like the Thousand Islands in
the northeastern segment of the lake. Therefore, it is difficult for ice to form on open waters
where the fetch is more significant. There are no notable downward trends in heat flux because
ice is unable to accumulate significantly on the lake; lake effect snows off Lake Ontario are, in
general, not significantly impacted by ice, so heat fluxes and therefore TET remain roughly
constant throughout the event until other impacting conditions become unfavorable for the
continuation of LES. Lake effect accumulations are therefore higher from Ontario events
because of the more constant feed of energy. Although the lack of diurnal effects may make the
data appear suspicious, analysis of satellite images (Fig. 20) and archived station data suggests
that much of the overnight period in the affected areas were mostly cloudy to overcast, offering a
plausible explanation on the lack of a strong diurnal influence on the data.
The two cases that are examined in this study emphasize the importance of taking into
account ice concentration and thickness data when making meteorological predictions on lake
effect snow events, in order to ensure good accuracy when producing a forecast. While the
passage of fetch over open-water is more important for lake-effect development than the
thicknesses of ice outside of the fetch area, the ice charts show that coverage and thickness can
change rapidly, and this is illustrated in the difficulty the NWS experienced with forecasting the
Jack Russell event. Since the impacts of lake effect events can have repercussions throughout the
region, and ice has been shown to have a major direct impact on snow band development,
24
extensive and up-to-date ice data is essential in determining the strength of lake effect snow
bands off the eastern Great Lakes, and thoughtful consideration should be used when assessing
the meaning of the collected ice data.
Acknowledgements. The author has deepest gratitude for Stephen Colucci for his guidance and
input, Brian Belcher for his technical assistance, and Neil Laird of Hobart and William Smith
Colleges (HWS) for his continued correspondence. The author gratefully acknowledges the
NOAA/Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and
dispersion model and/or READY website (http://www.arl.noaa.gov.ready.html) used in this
publication.
25
References
Assel, R.A., 1990: An ice-cover climatology for Lake Erie and Lake Superior for the winter
seasons 1897-98 to 1982-83. International Journal of Climatology, 10, 731-748.
Assel, R.A., 1999: Great lakes ice cover: Potential Climate Change Effects on Great Lakes
Hydrodynamics and Water Quality. D. C. L. Lan and W. M. Schertzer, Eds. American Society of
Civil Engineers, 1-21.
Ballentine, R.J., A.J. Stamm, E.E. Chermack, G. P. Byrd and D. Schleede, 1998: Mesoscale
model simulation of the 4-5 January 1995 lake-effect snowstorm. Weather Forecasting, 13, 893-
920.
Braham, R.R., Jr., 1983: The Midwest snowstorm of 8-11 December 1977. Monthly Weather
Review, 104, 860-867.
Brown, R.A., T.A. Niziol, N.R. Donaldson, P.I. Joe, V.T. Wood, 2007: Improved detection
Using Negative elevation Angles for Mountaintop WSR-88Ds. Part III: Simulations of shallow
Convective activity Over and Around Lake Ontario. Weather and Forecasting, 22, 839-852.
Burnett, A.W., M.E. Kirby, H.T. Mullins and W.P. Patterson, 2003: Increasing Great Lake-effect
snowfall during the twentieth century: a regional response to global warming? Journal of
Climate, 16: 3535-3542.
Cordeira, J.M., and N.F. Laird, 2007: The Influence of Ice Cover on Two Lake-Effect Snow
Events over Lake Erie. Monthly Weather Review, 135, 2747-2763.
26
Draxler, R.R. and G.D. Rolph, cited 2010. HYSPLIT (HYbrid Single-Particle Lagrangian
Integrated Trajectory) Model access via NOAA ARL READY Website
(http://ready.arl.noaa.gov/HYSPLIT.php). NOAA Air Resources Laboratory, Silver Spring, MD.
Draxler, R.R. amd G.D. Hess, 1998: An overview of the Hysplit_4 modeling system for
trajectories, dispersion and deposition. Australian Meteorology Magazine, 47, 295-308.
Garratt, J.R., 1992: The Atmospheric Boundary Layer. Cambridge University Press, 316 pp.
Gerbush, M.R., D.A.R. Kristovich, and N.F. Laird, 2008: Mesoscale boundary layer and heat
fluxes variations over ice-covered Lake Erie. Journal of Applied Meteorology and Climatology,
47, 668-682.
GLRA, 2002: Climate Change & Winter Tourism in the Great Lakes Region: The Potential
Impacts & What We Can Do. Workshop, November 8, 2002, [Available online at
http://www.geo.msu.edu/glra/workshop/05winterwkshop/wkshp.day.htm.]
Fetterer, F. and C. Fowler, 2006: National Ice center Arctic sea ice charts and climatologies in
gridded format. National Snow and Ice Data Center, Boulder, CO, digital media. [Available at
http://nsidc.org/data/docs/noaa/g02172_nic_charts_climo_grid/index.html.]
Jeffries, M.O. and K. Morris, 2006: Instantaneous daytime conductive heat flow through snow
on lake ice in Alaska. Hydrological Processes, 20, 803-815.
Kristovich, D.A.R., and N.F. Laird., 1998. Observations of widespread lake-effect cloudiness:
Influences of lake surface temperature and upwind conditions. Weather Forecasting, 13, 811-
821.
27
Kristovich, D.A.R., and Coauthors, 2000: The Lake-Induced Convection Experiment and the
Snowband Dynamics Project Bulletin of the American Meteorological Society, 81, 519-542.
Laird, N. F., and D.A.R. Kristovich, 2002: Variations of sensible and latent heat fluxes from a
Great Lakes buoy and associated synoptic weather patterns. Journal of Hydrometeorology, 3, 3-
12.
Laird, N.F., and D.A.R. Kristovich, 2004: Comparison of observations with idealized model
results for a method to resolve winter lake-effect mesoscale morphology. Monthly Weather
Review, 132, 1093-1103.
Markowski, P. and Y. Richardson, 2010: Mesoscale Meteorology in Midlatitudes. Wiley-
Blackwell Publishers, 430 pp.
Niziol, T.A., W.R. Snyder, and J.S. Waldstreicher, 1995: Winter weather forecasting throughout
the eastern United States. Part IV: Lake effect snow. Weather Forecasting, 10, 61-77.
Partington, K., T. Flynn, D. Lamb, C. Bertoia, and K. Dedrick, 2003: Late twentieth-century
Northern Hemisphere sea ice record from U.S. National Ice Center ice charts. Journal of
Geophysical Research, 108, 3343, doi:10.1029/2002JC001623.
Peterson T. C., M. McGuirk, T. G. Houston, A. H. Horvitz, and M. F. Wehner, 2008: Climate
variability and change with implications for transportation. National Climatic Data Center, 90
pp. [Available online at http://onlinepubs.trb.org/onlinepubs/sr/sr290Many.pdf.]
Rauber, R. M., and F. M. Ralph, 2004: An implementation plan for cool season quantitative
precipitation forecasting. United States Weather Research Program, 54 pp. [Available online at
http://box.mmm.ucar.edu/uswrp/implementation/CSQPF.pdf.]
28
Reinking, R.F., and Coauthors, 1993: The Lake Ontario Winter Storms (LOWS) project. Bulletin
of the American Meteorological Society, 74, 1828-1849.
Rolph, G.D., cited 2010. Real-time Environmental Applications and Display sYstem (READY)
Website (http://ready.arl.noaa.gov). NOAA Air Resources Laboratory, Silver Spring, MD.
Schmidlin T. W., 1993: Impacts of severe winter weather during December 1989 in the Lake
Erie snowbelt. Journal of Climate, 6, 759–767.
Schmidlin T. W., and J. Kosarik, 1999: A record Ohio snowfall during 9–14 November 1996.
Bulletin of the American Meteorological Society, 80, 1107–1116.
Stull, R.B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic
Publishers, 666 pp.
29
Figure Captions
Figure 1. NWS Buffalo’s graphical analysis of total accumulations from lake effect snow storm
“Jararaca”. Reported maximums were 12’’ in Perrysburg, NY for the Lake Erie snow bands, and
29” in Pulaski, NY for the Lake Ontario snow bands. [Image available at
http://www.erh.noaa.gov/buf/lakeffect/lake0809/j/stormsumj.html.]
Figure 2. NWS Buffalo’s graphical analysis of total accumulations from lake effect snow storm
“Jack Russell”. Reported maximums were 14’’ in Elma, NY for the Lake Erie snow bands, and
49” in Pulaski, NY for the Lake Ontario snow bands. [Image available at
http://www.erh.noaa.gov/buf/lakeffect/lake0708/j/stormsumj.html.]
Figure 3a. Location of Stations used in Lake Erie and Lake Ontario analyses, with station names.
Map produced using GrADS.
Figure 3b. Map of upstate New York Counties bordering Lake Erie and Lake Ontario. [Image
cropped from original available at http://www.nysl.nysed.gov/genealogy/counties.htm.
Figure 4. 850-hPa (850mb) analyses for 1200 UTC on (a) 15 Jan 2009, (b) 16 Jan 2009, and (c)
17 Jan 2009. Surface analyses for 1200 UTC on (d) 15 Jan 2009, (e) 16 Jan 2009, and (f) 17 Jan
2009. Temperatures on surface analyses are given in Fahrenheit, 850-hPa temperatures are given
in Celsius. Analyses were made available from NCEP.
Figure 5. Archived Upper-air sounding for KBUF (Buffalo, New York), 0000UTC (0000Z) on
January 16, 2009. Lapse rate in the between 1000mb and 850mb is approximately 9.8 degrees
Celsius/kilometer, roughly the dry adiabatic lapse rate. Image obtained from the University of
Wyoming,
30
Figure 6. GrADs-processed image of NERAD Level-II Radar from KBUF (Buffalo, NY), 2304Z
(UTC) on 16 January 2009. Well-defined bands in place over Lake Ontario and northern Lake
Erie, with scattered snow over the southern shores of Lake Erie.
Figure 7. GrADs-processed image of NERAD Level-II Radar from KTYX (Montague/Fort
Drum, NY), 2303Z (UTC) on 16 January 2009. A strong, clearly defined band is situated in
northern Oswego County near KFZY (Fulton, NY).
Figure 8. National ice chart images of Lake Erie nearest to the time of occurrence of lake effect
event Jararaca, (A) Jan 12 2009, (B) Jan 15 2009, (C) Jan 19 2009. The original image’s ice
analysis (egg) code has been modified to a standard written legend.
Figure 9. National ice chart images of Lake Ontario nearest to the time of occurrence of lake
effect event Jararaca, (A) Jan 12 2009, (B) Jan 15 2009, (C) Jan 19 2009. The original image’s
ice analysis (egg) code has been modified to a standard written legend.
Figure 10. Overlays of ice coverage charts closest to the initial formation of Jararaca’s lake effect
bands on Lake Erie (above) and Lake Ontario (bottom). HYSPLIT trajectory models are overlaid
to display the general course of the wind fetches with respect to the ice coverage on the lakes.
Figure 11. Time series of lake-area-average combined sensible and latent heat flux for Lake Erie
and Lake Ontario during the Jararaca event.
Figure 12. GrADs-processed image of NERAD Level-II Radar from KBUF (Buffalo, NY),
2342Z (UTC) on 19 February 2008. Disorganized showers over the southern part of Erie County
with a well-defined stronger band over KBUF. Multiple bands in place over Lake Ontario.
31
Figure 13. Archived Upper-air sounding for KBUF (Buffalo, New York), 0000UTC (0000Z) on
February 19, 2008. Lapse rate in the between 1000mb and 850mb is approximately 9.8 degrees
Celsius/kilometer, roughly the dry adiabatic lapse rate. Image obtained from the University of
Wyoming,
Figure 14. GrADs-processed image of NERAD Level-II Radar from KTYX (Montague/Fort
Drum, NY), 2346Z (UTC) on 19 February 2008. A very-well organized band lies over northern
Oswego and Southern Jefferson County. Reflectivity indicates moderate to heavy snowfall rates
in this region.
Figure 15. Surface analyses for 1200 UTC on (a) 18 Feb 2008, (b) 19 Feb 2008, and (c) 20 Feb
2008. 850 hPa (850mb) analyses for 1200 UTC on (d) 18 Feb 2008, (e) 19 Feb 2008, and (f) 20
Feb 2008. Temperatures on surface analyses are given in Fahrenheit, 850-hPa temperatures are
given in Celsius. Analyses were made available from NCEP.
Figure 16. National ice chart images of Lake Erie nearest to the time of occurrence of lake effect
event Jack Russell, (A) Feb 14 2008, (B) Feb 18 2008, (C) Feb 21 2008. The original image’s
ice analysis (egg) code has been modified to a standard written legend.
Figure 17. National ice chart images of Lake Ontario nearest to the time of occurrence of lake
effect event Jack Russell, (A) Feb 14 2008, (B) Feb 18 2008, (C) Feb 21 2008. The original
image’s ice analysis (egg) code has been modified to a standard written legend.
Figure 18. Overlays of ice coverage charts closest to the initial formation of Jack Russell’s lake
effect bands on Lake Erie (above) and Lake Ontario (bottom). HYSPLIT trajectory models are
overlaid to display the general course of the wind fetches with respect to the ice coverage on the
lakes.
32
Figure 19. Time series of lake-area-average combined sensible and latent heat flux for Lake Erie
and Lake Ontario during the Jack Russell event.
Figure 20. Satellite images obtained from the MODIS archived for January 16, 2009 (left) and
February 19, 2008 (left). Cloud cover obscures most of the Great Lakes region in the two cases.
33
Figure 1. NWS Buffalo’s graphical analysis of total accumulations from lake effect snow storm “Jararaca”. Reported maximums were 12’’ in Perrysburg, NY for the Lake Erie snow bands, and 29” in Pulaski, NY for the Lake Ontario snow bands. [Image available at http://www.erh.noaa.gov/buf/lakeffect/lake0809/j/stormsumj.html.]
Figure 2. NWS Buffalo’s graphical analysis of total accumulations from lake effect snow storm “Jack Russell”. Reported maximums were 14’’ in Elma, NY for the Lake Erie snow bands, and 49” in Pulaski, NY for the Lake Ontario snow bands. [Image available at http://www.erh.noaa.gov/buf/lakeffect/lake0708/j/stormsumj.html.]
Figure 3a. Location of Stations used in Lake Erie and Lake Ontario analyses, with station names.Map produced using GrADS.
Figure 3b. Map of upstate New York Counties bordering Lake Erie and Lake Ontario. [Image cropped from original available at
34
. Location of Stations used in Lake Erie and Lake Ontario analyses, with station names.
Map of upstate New York Counties bordering Lake Erie and Lake Ontario. [Image cropped from original available at http://www.nysl.nysed.gov/genealogy/counties.htm
. Location of Stations used in Lake Erie and Lake Ontario analyses, with station names.
Map of upstate New York Counties bordering Lake Erie and Lake Ontario. [Image http://www.nysl.nysed.gov/genealogy/counties.htm.]
35
Figure 4. 850-hPa (850mb) analyses for 1200 UTC on (a) 15 Jan 2009, (b) 16 Jan 2009, and (c) 17 Jan 2009. Surface analyses for 1200 UTC on (d) 15 Jan 2009, (e) 16 Jan 2009, and (f) 17 Jan 2009. Temperatures on surface analyses are given in Fahrenheit, 850-hPa temperatures are given in Celsius. Analyses were made available from NCEP.
36
Figure 5. Archived Upper-air sounding for KBUF (Buffalo, New York), 0000UTC (0000Z) on January 16, 2009. Lapse rate in the between 1000mb and 850mb is approximately 9.8 degrees Celsius/kilometer, roughly the dry adiabatic lapse rate. Image obtained from the University of Wyoming,
Figure 6. GrADs-processed image of NERAD Level(UTC) on 16 January 2009. WellErie, with scattered snow over the southern shores of Lake
Figure 7. GrADs-processed image of NERAD LevelDrum, NY), 2303Z (UTC) on 16 January 2009. A strong, clearly defined band is situated in northern Oswego County near KFZY (Fulton, NY)
37
processed image of NERAD Level-II Radar from KBUF (Buffalo, NY)(UTC) on 16 January 2009. Well-defined bands in place over Lake Ontario and northern Lake Erie, with scattered snow over the southern shores of Lake Erie.
processed image of NERAD Level-II Radar from KTYX (Montague/Fort Drum, NY), 2303Z (UTC) on 16 January 2009. A strong, clearly defined band is situated in northern Oswego County near KFZY (Fulton, NY)
(Buffalo, NY), 2304Z defined bands in place over Lake Ontario and northern Lake
II Radar from KTYX (Montague/Fort Drum, NY), 2303Z (UTC) on 16 January 2009. A strong, clearly defined band is situated in
38
Figure 8. National ice chart images of Lake Erie nearest to the time of occurrence of lake effect event Jararaca, (A) Jan 12 2009, (B) Jan 15 2009, (C) Jan 19 2009. The original image’s ice analysis (egg) code has been modified to a standard written legend.
39
Figure 9. National ice chart images of Lake Ontario nearest to the time of occurrence of lake effect event Jararaca, (A) Jan 12 2009, (B) Jan 15 2009, (C) Jan 19 2009. The original image’s ice analysis (egg) code has been modified to a standard written legend.
40
Figure 10. Overlays of ice coverage charts closest to the initial formation of Jararaca’s lake effect bands on Lake Erie (above) and Lake Ontario (bottom). HYSPLIT trajectory models are overlaid to display the general course of the wind fetches with respect to the ice coverage on the lakes.
41
Figure 11. Time series of lake-area-average combined sensible and latent heat flux for Lake Erie and Lake Ontario during the Jararaca event.
42
Figure 12. Surface analyses for 1200 UTC on (a) 18 Feb 2008, (b) 19 Feb 2008, and (c) 20 Feb 2008. 850 hPa (850mb) analyses for 1200 UTC on (d) 18 Feb 2008, (e) 19 Feb 2008, and (f) 20 Feb 2008. Temperatures on surface analyses are given in Fahrenheit, 850-hPa temperatures are given in Celsius. Analyses were made available from NCEP.
43
Figure 13. Archived Upper-air sounding for KBUF (Buffalo, New York), 1200UTC (1200Z) on February 19, 2008. Lapse rate in the between 1000mb and 850mb is approximately 9.8 degrees Celsius/kilometer, roughly the dry adiabatic lapse rate. Image obtained from the University of Wyoming,
Figure 14. GrADs-processed image of NE2342Z (UTC) on 19 February 2008. Disorganized showers over the southern part of Erie County with a well-defined stronger band over KBUF. Multiple bands i
Figure 15. GrADs-processed image of NERAD LevelDrum, NY), 2346Z (UTC) on 19 February 2008. A veryOswego and Southern Jefferson County. Reflectivity indiin this region.
44
processed image of NEXRAD Level-II Radar from KBUF (Buffalo, NY), 2342Z (UTC) on 19 February 2008. Disorganized showers over the southern part of Erie County
defined stronger band over KBUF. Multiple bands in place over Lake Ontario.
processed image of NERAD Level-II Radar from KTYX (Montague/Fort Drum, NY), 2346Z (UTC) on 19 February 2008. A very-well organized band lies over northern Oswego and Southern Jefferson County. Reflectivity indicates moderate to heavy snowfall rates
II Radar from KBUF (Buffalo, NY), 2342Z (UTC) on 19 February 2008. Disorganized showers over the southern part of Erie County
n place over Lake Ontario.
II Radar from KTYX (Montague/Fort well organized band lies over northern cates moderate to heavy snowfall rates
45
Figure 16. National ice chart images of Lake Erie nearest to the time of occurrence of lake effect event Jack Russell, (A) Feb 14 2008, (B) Feb 18 2008, (C) Feb 21 2008. The original image’s ice analysis (egg) code has been modified to a standard written legend.
46
Figure 17. National ice chart images of Lake Ontario nearest to the time of occurrence of lake effect event Jack Russell, (A) Feb 14 2008, (B) Feb 18 2008, (C) Feb 21 2008. The original image’s ice analysis (egg) code has been modified to a standard written legend.
47
Figure 18. Overlays of ice coverage charts closest to the initial formation of Jack Russell’s lake effect bands on Lake Erie (above) and Lake Ontario (bottom). HYSPLIT trajectory models are overlaid to display the general course of the wind fetches with respect to the ice coverage on the lakes.
48
Figure 19. Time series of lake-area-average combined sensible and latent heat flux for Lake Erie and Lake Ontario during the Jack Russell event.
49
Figure 20. Satellite images obtained from the MODIS archived for January 16, 2009 (left) and February 19, 2008 (left). Cloud cover obscures most of the Great Lakes region in the two cases.