The Superstorm of 1993


The Superstorm of 1993
The Superstorm of 1993
Although the Nor’easter of March 12-15, 1993 was not the biggest snow producer or
coldest storm in history, it has gone down as one of the largest and most destructive winter
storms in US history. Its beginnings quiet and its end only five short days later, the storm affected
fully half of the United States’ population and caused over 500 deaths and three billion dollars in
damage. Since it represents the closest version to “perfection” an extra-tropical (mid latitude)
cyclone can achieve and historical data is limited on other storms of the same type from earlier
years (especially in terms of satellite data), the ‘93 Superstorm represents a goldmine of
meteorological data and forms the basis for most current research into extra-tropical cyclones.
For this lab, you will combine information already presented in class with meteorological map
reading and satellite imagery to analyze the Storm of the Century.
Internet Sources
For most of this lab, the Weather World 2010 Project will be used as the primary source
for satellite and surface data. This project is an outreach of the University of Illinois (known for
its strong meteorology department) and contains archived data about many of the greatest
meteorological events of the late 20th century including hurricanes and tornado outbreaks. To
begin, go to the main page for the Superstorm of 1993 at
General Instructions
Part 1:
General Information
Using the Introduction and Storm History sections of the
WW2010 archive, record the requested data on your lab sheet. Note
that the included links and a few independent web searches of other
sources will be needed to obtain some of the data since it is not directly
related to SS93 (SuperStorm of 1993).
Part 2: Surface Data/Station Models
The second part of this lab focuses on reading meteorological
surface data. Since so much incoming data is used in each and every
weather report, scientists reduce it to a series of related symbols which
are then plotted on a map for analysis. Called station models, these
symbols can be easily interpreted and used to formulate weather
Part 2:
Surface Data/Station Models (cont.)
When you have advanced to the screen that starts with “surface Images,” look at the small
map below the title. Although they are too small to read, each set of symbols on the map
represent a separate set of weather data observed at the site where the symbols are located. In
addition, the light blue lines are isobars which you have already been introduced to. Click on
“surface observations” and review how station models are constructed if you need a refresher.
Now, pick a city along the East Coast that was obviously affected by the passing
superstorm and consistently shows station models throughout the Nor’easter event. You might
need an atlas/map to name the city. Redraw five separate station models for the same location on
your lab sheet that are as evenly spread out through the event as possible. The goal is to produce
an overall impression of how the weather at the station you chose was affected by the storm
before and after it passed. The best locations to choose for this will be along the coast from
Georgia to New England.
Finally, remember the images are shown in Zulu time and must be translated into local
time for accurate analysis. It is also important to note that along the bottom of the surface
analysis maps, the surface pressure interval is given along with the highest and lowest pressures
on the map (although the key does not tell you exactly where that pressure reading was
Part 3:
Satellite Imagery
United States meteorological satellites basically provide three types of imagery. Using
devices already introduced earlier in the course, these satellites provide visible light, infrared and
water vapor images. Not surprisingly, each resolves different types of information better than the
others so all three are vital components of weather prediction and forecasting. You will also note
that the infrared images have been colorized for better viewing. However, unlike the usual color
scheme you might expect where reds and yellows are the warmest locations and blues are the
coolest, remember the reverse is true in weather imagery. As you know, the higher into the
atmosphere a cloud is forced to rise, the colder its top becomes. Since a satellite will pick up only
the tops of the clouds, meteorologists use their approximate temperature to determine their
vertical development. Thunderstorms are immensely high clouds capable of reaching to the top of
the troposphere, their tops tend to stand out among the warmer air around them making them
easy to identify (as you will see). If you have not done so already, read the GOES Meteorology
section of the AGS 371 Remote Sensing Lab before completing this section in order to familiarize
yourself with how the GOES satellites operate and what services they can provide. This
information can be found at
Go back to the storm history page and look beneath the color image to locate a table titled
“Satellite Images.” This table will be your major jump point to the satellite databases. For some
questions, multiple images may be needed.
The Superstorm of 1993
Lab Sheet
Part 1: General Information
In what geographic area did the SS93 first appear at the surface?
Using Figure 1.2, what Florida city represented “ground zero” when the center of the
cyclone made landfall?
Franklin County, Florida recorded the highest wind speeds of anywhere in the Gulf States.
Had the storm been a hurricane, what classification would it have received? (You will
need to look up the classification system for hurricanes. Try for
During the storm, Philadelphia observed a record low barometric pressure. Find the
minimum recorded pressure for the following listed events as a comparison and note the
Minimum Pressure (mb)
SS93 (Philadelphia)
Lowest Phila. reading in past
24 hours*
Hurricane Andrew** (1992)
Hurricane Floyd** (1999)
Blizzard of ‘96
Hurricane Wilma** (2005)
*Go to and find the meteogram for Philadelphia
(KPHL). Then use the online information to determine the barometer reading.
**The Tropical Prediction Center (National Hurricane Center) keeps detailed archives for every
hurricane/tropical storm in their Seasons Archive section which can be accessed from the main
NHC page.
Part 2: Surface Data/Station Models
Station Models
Selected City________________________
Station Model
Analysis of two important trends or information directly
related to SS93*
* Y our task here is to examine the impact of the SS93 on local conditions, not explain what is in the is assumed you already know
how to read them. For instance, do not report “...the winds were coming from the NE...” Instead, report “...the winds showed a noticeable
shift to the N E from the past model as the center of the low pressure approached the region and a C C W spin started to be created around
Part 2: (Continued)
Using the available surface data plots, determine the greatest national pressure gradient in
the United States throughout the storm’s lifespan. In other words, a normal national
pressure gradient on any given day is about 15-20mb from the highest high to the lowest
low. Look at what impact the SS93 had on the gradient!
Date/Time_________________ Highest Pressure___________Lowest Pressure________
At what local date and time (you must convert Z time...use EST) did the storm reach its
greatest strength and where was its center located at that time?
Choose 12 evenly spaced (approximate) times throughout the storm’s life and record the
wind direction as recorded in Philadelphia. Using what you have already learned about
pressure and wind, explain what the significance of the wind direction has on determining
the actual location of the storm for someone who might be caught outdoors throughout the
storm’s duration. (In other words, if you were outside but understood the nature of winds,
how could you “track” the storm?)
*V = W ind Vector
Locate Orlando, Florida using the computer
or an atlas. Your goal is to determine at
what date/time the strong cold front that
dropped south from the storm center passed
the area. How do you do that?
There are actually a few important
indicators. The first is that isobars often
“kink” towards higher pressure where a
front crosses them. Bearing that in mind,
look at the diagram at the right and fill in the
wind directions for the included station
models using what you already know about PGF, CE, etc. You should notice a trend in wind
direction that can help you locate the front (I have spoken about it before).
Remember that you are looking for a cold front. What temperature and precipitation
patterns should be present to help identify the front’s location? (Do NOT simply say “cold
temperatures”...that is not enough. How can you find the actual front?)
At what date and time did the SS93's destructive cold front pass through central Florida?
Support your answer with specific data from any sources used (there are multiple strategies
and sources of data that can be used to answer this question.)
Part 3: Satellite Imagery
Choose a date/time (use daylight hours so visible imagery will be available) where images
exist for all three types of sensors and examine each photo. Since this data is being received
from satellites, it will periodically contain data errors so discount these photos as well if the
errors are large enough to obscure the storm. For each type of information below, indicate
which type of photo would be the most useful for examining that particular data. This is not
simply an opinion certain cases especially, one type of image or another is much
more useful than the others. There may be multiple answers for certain types of desired data.
Desired Data
Overall Storm Structure
Cloud Types and Organization
Storm Intensity
Location of Jet Stream
Center of the Storm
Front Boundaries
Best Image Type/Explanation
Station Model Refresher
Below is a diagram illustrating all of the possible information contained in a station model.
Although all of this information is rarely available a the same time, it must nevertheless be accounted
for. In addition, the possible symbols used for current weather conditions, clouds, etc. are quite
numerous and have been included on the back of this page for your use.
Here is a “worst case scenario” station model that shows where to put all possible weather
Now, here’s an example of what such a station model might look like...