The Superstorm of 1993
Transcription
The Superstorm of 1993
Name_____________________________Date__________________Period_________________ The Superstorm of 1993 Background 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 http://ww2010.atmos.uiuc.edu/(Gh)/arch/cases/930312/home.rxml 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 forecasts. 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 measured). 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 http://geochief.org/Course_Materials/Remote_Sensing/sensing2.htm 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. Name_____________________________Date__________________Period_________________ The Superstorm of 1993 Lab Sheet Part 1: General Information 1. In what geographic area did the SS93 first appear at the surface? 2. Using Figure 1.2, what Florida city represented “ground zero” when the center of the cyclone made landfall? 3. 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 www.nhc.noaa.gov for starters.) 4. 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 differences. Event 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 http://weather.unisys.com/surface/meteogram/ 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________________________ Date/ZTime 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 model...it 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 it...” Part 2: (Continued) 1. 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________ 2. 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? 3. 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?) Date/ Time V* *V = W ind Vector Explanation: 4. 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). 5. 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?) 6. 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 1. 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 question...in 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 information. Now, here’s an example of what such a station model might look like...