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Do Hurricanes Cool the Ocean?

Time Required Average (6-10 days)
Prerequisites Familiarity with computers and web browsers helps
Material Availability Readily available
Cost Very Low (under $20)
Safety No issues


If you've ever so much as watched a news clip about a hurricane, you probably know that hurricanes draw their power from warm ocean waters. If that is true, does it mean that hurricanes actually cool the ocean down when they pass through? Can the amount of cooling be measured? Is it proportional to the strength of the hurricane? Find out using data that you can collect yourself using online archives. This project shows you how.


If hurricanes get their power from warm ocean waters, does this mean that after a hurricane passes the ocean surface will be cooler? If so, is the amount of cooling proportional to the strength of the hurricane? The goal of this project is to test both hypotheses using historical hurricane and sea surface temperature data.

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  • Background references on hurricane formation selected from the an NSDL/NSTA web seminar on hurricanes:
    Van Gundy, S. and R. Payo, 2006. "NSDL/NSTA Web Seminars: Hurricanes," National Science Digital Library/National Science Teacher's Association [accessed May 17, 2006] http://ia.usu.edu/viewproject.php?project=ia:2582.

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General citation information is provided here. Be sure to check the formatting, including capitalization, for the method you are using and update your citation, as needed.

MLA Style

Science Buddies Staff. "Do Hurricanes Cool the Ocean?" Science Buddies, 28 Apr. 2018, https://www.sciencebuddies.org/science-fair-projects/project-ideas/OceanSci_p006/ocean-sciences/do-hurricanes-cool-the-ocean. Accessed 20 May 2018.

APA Style

Science Buddies Staff. (2018, April 28). Do Hurricanes Cool the Ocean? Retrieved from https://www.sciencebuddies.org/science-fair-projects/project-ideas/OceanSci_p006/ocean-sciences/do-hurricanes-cool-the-ocean

Last edit date: 2018-04-28


The dramatic image is from a computer model of Hurricane Katrina, developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL, 2005). The sea surface temperature in the Gulf of Mexico is color-coded (see legend at bottom left). The model's track for the hurricane (white line) and the actual observed positions of the hurricane (magenta dots) are shown. The model predicts a strong cooling effect associated with the hurricane's path. (For a higher-resolution version of this image, and an animation of the model, see the Bibliography (GFDL, 2005)).

GFDL model of Hurrican Katrina showing cooling wake in the Gulf of Mexico.
GFDL model of Hurricane Katrina showing a cooling wake trailing the path of the hurricane.

In this project you will use your web browser to collect data on hurricane strength and sea surface temperature. The goal is to see if there is a consistent cooling effect after a hurricane passes. If you find such an effect, is the amount of cooling proportional to the strength of the hurricane? Each hurricane will be one data point on your graph, so you will need to collect data from many, many hurricanes to make a reliable graph.

In this project you will be analyzing two kinds of archived data:

  1. hurricane track data, and
  2. meteorological data from monitoring buoys.

The Experimental Procedure section has instructions on how to access the archived data. The hurricane track data will show you the location of the storm (best-track analysis, with positions given every six hours), and two measures of the hurricane strength: central pressure and wind speed. The meteorological data will be using for this project is the sea surface temperature, recorded hourly from monitoring buoys. Note that the monitoring buoys also collect other interesting information (wind speed and direction, barometric pressure, and wave height information) which you may also wish to analyze (see the Variations section for some ideas to get you started).

A hurricane lasts for many days, it constantly moves, and its strength usually fluctuates during its lifetime. We have to start somewhere, though, so the method we will use is to look for the peak intensity of the hurricane, and take all of the measurements relative to that time and location. In the procedure, we have (arbitrarily) picked 3 days before the hurricane and 1 day after as the two endpoints for measuring temperature changes. When you do your background research, you should learn as much as you can about how fast hurricanes travel and how big they are. Is three days earlier enough time, or might the hurricane already have an influence on water temperature at this point? Use the information you gather from your background research to pick your own time window.

Before you start collecting data, you should do background research on how hurricanes form and grow. The next two sections will help you get started with your background research.

Terms and Concepts

To do this project, you should do research that enables you to understand the following terms and concepts:

  • air pressure,
  • air density,
  • Hadley cells,
  • Saffir-Simpson scale for hurricane strength.


  • How do hurricanes form?
  • In what part of the hurricane is the air pressure lowest?
  • Why are warm water temperatures important for hurricane formation?


  • There are many websites where you can find background information on hurricanes. You'll want to learn about how hurricanes form, which means learning about global wind patterns, and areas of high and low air pressure, among other things. The following web sites are good places to start:
  • NOAA's Geophysical Fluid Dynamics Laboratory has a webpage with computer modeling results for hurricanes:
    GFDL, n.d. "Hurricane Visualizations," Geophysical Fluid Dynamics Laboratory, NOAA. Retrieved April 11, 2018, from https://www.gfdl.noaa.gov/visualizations-hurricanes/.
  • Test your knowledge of hurricane formation with this interactive applet (requires Java). You can drag a hurricane around to areas with different water temperature and see what happens to it!
    Whittaker, T. and S. Ackerman, 2005. "Hurricane Applet," Weatherwise, University of Wisconsin. Retrieved May 17, 2006, from http://profhorn.aos.wisc.edu/wxwise/hurr/hurr.html.
  • This is one of many online sources of historical hurricane data. We chose this website because the track maps include index information at selected data points so that you can easily correlate position and date (the one drawback is that the background color of the maps is black):
    Unisys, 2004. "Atlantic Tropical Storm Tracking by Year," Unisys Weather. Retrieved May 17, 2006, from http://weather.unisys.com/hurricane/atlantic/.
  • The National Data Buoy Center has current and historical meteorological data from a network of continuous monitoring buoys:
    NDBC, 2006. "National Data Buoy Center," NDBC, National Oceanic and Atmospheric Administration. Retrieved May 17, 2006, from http://www.ndbc.noaa.gov/.
  • For calculating distances on your hurricane track map, try this longitude and latitude distance calculator:
    CSGNetwork.com, 2006. "Length of a Degree of Latitude and Longitude," CSGNetwork.com. Retrieved May 17, 2006, from http://www.csgnetwork.com/degreelenllavcalc.html.

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Materials and Equipment

To do this experiment you will need the following materials and equipment:

  • computer with Internet access and printer.

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Experimental Procedure

  1. Do your background research so that you are knowledgeable about the terms, concepts, and questions.
  2. To illustrate the steps involved in the analysis, we will work through a single example. You will need to repeat the data collection (steps 3 and 4) for many more hurricanes in order to test the hypothesis. You should collect data for no less than 40 hurricanes (even more is better). Not every storm will have a data buoy nearby. To see how close the buoy is, you can use an online calculator to convert degrees of latitude and longitude to other distance scales (CSGNetwork.com, 2004). If reliable sea surface temperature data is not available for a particular storm, don't use it in your data set.
  3. Accessing Archived Hurricane Data

    The Unisys weather website is a good source for historical hurricane data. You can obtain the data in both map and tabular formats. In this example, we will be looking at data from Hurricane Katrina in 2005.
    1. Go to Atlantic Tropical Storm Tracking by Year (Unisys, 2004), and click on the year of interest.
    2. At the top of the page you will see a map with all of the hurricane and tropical storm tracks for the selected year. These maps have overlapping storm tracks and no date information, so we won't be using them for the analysis. They do give you a visual impression of the number of storms that occurred during a given a year.
    3. Scroll down the page to the "Individual Storm Summary" section. You will see a summary table showing the number and name of each storm, along with a line of data about the maximum strength of each storm. From this table you can quickly see how many hurricanes occurred during the selected year.
      Individual Storm Summary table, 2005 (partial)

    4. Scroll down further to the "Saffir-Simpson Scale" section. This section describes the Saffir-Simspon hurricane strength scale, and also explains the color code used for showing hurricane strength in the maps.
      Saffir-Simpson Scale table

    5. Scroll down further to the "Individual Storm Details" section. For each storm there is a thumbnail map of the storm's path, and a link to the tabular data for the storm.
      Individual storm details: Hurricane Katrina

    6. Click on the map for an enlarged view of the hurricane track. Print the map. The data points are numbered sequentially. Each tick mark on the map represents six hours of elapsed time. In the next step, you'll print a data table that matches up with these index numbers.

      Storm track map for Hurricane Katrina

    7. Use your browser's "back" button to return to the individual storm details. Click on the "Details" button or the "Tracking Information" link for a table of tracking data for the storm. Print the data table. Add a column at the right for "sea surface temperature." In step 4, you'll fill in this value for the time point when the storm was at its maximum strength.

      Table of tracking data for Hurricane Katrina

    8. Here is an explanation of each of the data columns in the table:
      • ADV: the numbers on the map correspond to the "ADV" column in the data table. This number is a count of the 6-hour intervals at which the measurements were recorded.
      • LAT: latitude of the hurricane center.
      • LON: longitude of the hurricane center (negative numbers correspond to degrees west of 0°).
      • TIME: date and time of the measurements, in the format "mm/dd/hhZ". The "Z" stands for "Zulu," which is one of many ways to refer to Coordinated Universal Time or UTC (also known as Greenwich Mean Time, or GMT). The hours are in 24-hour format, so "00" means midnight.
      • WIND: in knots (nautical miles per hour; 1 nautical mile equals 1.15 miles).
      • PR: air pressure at hurricane center, in millibars (mb).
      • STAT: status of the storm on Saffir-Simpson scale.
    9. Scan down the WIND and PR columns to find the entry where the hurricane was at its maximum strength. In this example, Katrina reached its maximum strength (lowest pressure, highest wind) at row 21. The wind speed was 150 kt, and the pressure was 902 mb, on August 28 at 18 hours UTC. Find this position on the map.
  4. Accessing Archived Meteorological Data from Buoys

    The next step is to find the sea surface temperature at the location where the storm reached its peak. The National Oceanic and Atmospheric Administration (NOAA) maintains a network of moored buoys with sensors that continuously monitor ocean conditions. The data records, with hourly readings, are archived and available online at the National Data Buoy Center (NDBC, 2006). For this project, you will be accessing sea surface temperature data from the buoys. The monitoring buoys also collect other interesting information (wind speed and direction, barometric pressure, and wave height information) which you may also wish to analyze (see the Variations section, for some ideas to get you started). Here are detailed instructions for locating buoys near the hurricane track and accessing archived data from them. (You'll find it's much easier to do it than it is to describe it!)
    1. With your hurricane track map handy, go to National Data Buoy Center. You'll see a map, similar to the one shown. Click on the link that takes you to classic, recent maps, circled in red on the map.

      National Data Buoy Center world map.

    2. You should then see a map like the one shown. Each of the rectangles links to a higher-resolution map of the indicated area, showing data buoy locations. Since this project is focused on Atlantic hurricanes, you will be using data buoys from the regions highlighted by the red oval.

      National Data Buoy Center western Gulf of Mexico map.

    3. Click on the rectangle over the northwestern portion of the Gulf of Mexico. You'll see a map like the one shown. The legend (lower left) identifies the types of the data buoys. Not all of the buoys will have sea surface temperature information. To start with, look for the blue squares, which indicate NDBC moored buoys.

      National Data Buoy Center western Gulf of Mexico map.

    4. Just like your hurricane track map, the data buoy regional maps are marked with latitude and longitude grid squares at 5-degree intervals. Using the grid squares as a reference, locate the data buoy that is closest to the hurricane track. In the map, buoy 42001 is close to Hurricane Katrina's location on August 21, 2005. Click on the the number 42001, which will connect you to the webpage for that buoy.
    5. At the top of the page, you'll find information about the data buoy, including the owner, the type of buoy, the instrumentation onboard ("payload") and the buoy's latitude and longitude. Use the latitude and longitude data to mark the buoy location on your hurricane track map. (For your display board, you can mark the data buoy locations with pushpins and labels.)

      Location information for data buoy 42001.

    6. Scroll down to the bottom of the data buoy page and find the link for "Historical Data & Climatic Summaries". [Note: there are two additional links that you may find useful. "Description of Measurements" tells you what the measurements the data buoy takes and the units that the data are reported in. "Data Inventory" tells you what data is available for past time periods.]

      Historical and climatic data link for a data buoy.

    7. Click on the link for Historical & Climatic Summaries. Under "Standard meteorological data," click on the year of interest (2005, in our case). (The "data descriptions" link takes you to the "Description of Measurements" page, mentioned in step 4e.)

      Accessing historical meterology data from a data buoy.

    8. Almost there! Now use "Method 2" to access the data. The instructions are self-explanatory.

      Instructions for downloading data buoy file.

    9. At last, here it is: a year's worth of hourly records, 365×24=8,760 lines! (It may take awhile to load. If it takes too long, you may want to try downloading the compressed files (Method 1). You'll need to uncompress the files on your computer to access the data.) The illustration shows only the first 25 hours of data, to make a few points about what you'll find.

      Sample data table from data buoy 42001.

    10. The top line is a "header" identifying the data in each column. For detailed information on the data, use one of the "descriptions" links (see step 4e or 4f). In addition to the date and time information, you'll be using the "WTMP" column (third column from the right), which reports the water temperature in °C. The date information is in the first three columns (self-explanatory). The time information is in 24-hour format, and like the hurricane tracking data, is in Coordinated Universal Time (UTC, columns four and five, highlighted in red). Any data field that is "9-filled" (e.g., the right-most columns highlighted in blue) is invalid. In this case, it means that the data buoy is not equipped to collect this information. In other cases, it can indicate that a sensor is not functioning properly.
    11. You don't need to save the entire data file, just the time period around the hurricane of interest. You should decide for yourself (using information from your background research) what time window to use for the sea surface temperature measurements. (Since a little extra data won't hurt, you may want to collect some extra "baseline" data at each end, in case you want to analyze multiple time windows.) You can copy-and-paste the parts you need to make your own data table. Use a plain text editor (e.g., Notepad) for this. Copy-and-paste the data header line. Then scroll down and find the dates of interest and copy-and-paste the data into the same file. You should also add a line or two at the top of the table to identify the data buoy and its location. In our example, we have decided to use a single data point for each day, taken at 18:00, UTC. We did this by first copying the entire date range, and then deleting the lines we didn't need.

    Daily data (1800h) for buoy 42001 for 3 days before and 1 day after Hurricane Katrina passed.

  5. Analyzing and Graphing the Data

    Now it's time to put it all together. Devise a measure of temperature change to apply to the data for each hurricane. For example, you could subtract the temperature at the end of the chosen time window from the temperature at the beginning of the chosen time window. For a more advanced project, you might want to get fancier and try to analyze the rate of temperature change before the hurricane arrived compared to the rate of temperature change as the hurricane passed through.
  6. Run your temperature calculation for each hurricane, and add the temperature change information to the hurricane's data table (the one you printed in step 3).
  7. Examine the results. Is the temperature change consistent for all (or most) hurricanes?
  8. Is the temperature change proportional to hurricane strength? Make a graph of temperature change (y-axis) vs. hurricane strength (x-axis, use either minimum pressure or maximum wind speed). What does the graph look like? Does it support the hypothesis? Explain why or why not.

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  • More advanced students can do further analysis to examine the statistical significance of the correlation using the linear regression technique. For comparison, you might want to also look at the correlation between central pressure and wind speed (should be strongly correlated). See the Science Buddies project Which Team Batting Statistic Predicts Run Production Best? for an example of statistical correlation analysis using a spreadsheet program.
  • It is important to remember that correlation between two variables does not imply causality. In other words, finding a correlation shows that there is a relationship between the variables, but does not show that warmer seas cause stronger hurricanes. Finding a correlation between two variables is often the first step in explaining a causal relationship, but correlation alone is not proof of a causal relationship. Consider the possibility that cloud cover from the hurricane is responsible for any decrease in water temperature, because it blocks sunlight that would otherwise be warming the water. Can you think of a way to distinguish between this hypothesis and the original one?
  • In addition to water temperature, the data buoys also collect information on wave height, air pressure, wind direction, and wind speed. Many other projects are possible using this data. For example: how far away from the hurricane center is wave height affected? How does this vary with the strength of the storm (minimum pressure at the center)? How does the wind direction change as the hurricane passes through?
  • One problem with the buoy data used in this project is that there are relatively few buoys. This means that the temperature data is often collected at a point distant from the hurricane. You may want to measure the distance. More advanced students can use high-resolution satellite data for sea surface temperature measurement. The data set begins in 2002, and is available from https://oceancolor.gsfc.nasa.gov/. You will have to learn how to access the data from the instructions on the page.
  • As the hurricane travels, does it have the same cooling effect throughout its path? Use data from buoys near other locations on the hurricane's track to investigate.

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