Bomb Cyclones - They're Explosive!

Jacqui Jenkins-Degan, Marine Technology Program, Cape Fear Community College

Summary

Storms can have devastating impacts on coastal communities. Typically, tropical storms like hurricanes get the most attention, but there are other types of storms that occur at more northern latitudes that can be just as destructive. For example, in January of 2018, Winter Storm Grayson caused more than 300,000 power outages and $1.1 billion in damage, and resulted in 22 confirmed casualties along the eastern seaboard. In this module, students will learn how barometric pressure changes during a storm, analyze the effect of storms on oceanographic variables, classify a storm as a bomb cyclone, and compare a bomb cyclone to a hurricane. Ultimately students will use their quantitative reasoning skills to manipulate and visualize data during storms in the northeastern United States.

Strengths of Module

At the end of this module students will be comfortable with manipulating data and creating graphs in Excel, understanding correlative relationships using R-squared values, determining how to classify a storm as a bomb cyclone, analyzing how to calculate the rate of change of barometric pressure over time using linear regression and the equation of a line, and comparing hurricanes to bomb cyclones.

What does success look like

By the end of the module, students will be able to:

  • correlate barometric pressure data to other oceanographic variables and analyze how they change during bomb cyclones
  • analyze a past winter storm to determine if it is a bomb cyclone and when exactly it occurred
  • compare a hurricane to a bomb cyclone
  • manipulate data from the Ocean Observatories Initiative (OOI) suite of buoys and other data sources
  • demonstrate basic graphing methods in Excel

Context for Use

This module can be used in an introductory Oceanography course at the undergraduate level in various class sizes. Instructors could cover these activities in a single class period if used as a demonstration or they can be broken up into multiple lab/lecture periods. If students have experience graphing in Excel, it is possible to complete Activities A through C in one 50 minute class period. Activities D and E would require more time and may be more appropriate for a lab period or as a homework assignment.

Description and Teaching Materials

Why this Matters:

Students will develop their quantitative skills in the context of a real-world atmospheric phenomenon and learn about the implications of extra-tropical cyclones at northern latitudes.

Quick outline/overview of the activities in this module

  • Pre-module work: QR/Statistical review of correlation and regression; overview of Excel graphing
  • Activity A:
    • Graph change of oceanographic variables (precipitation, wind speed, wave height, sea surface temperature, and barometric pressure) during a storm as it passes the Coastal Pioneer Array of the Ocean Observatories Initiatives suite of buoys.
  • Activity B:
    • Explore how a change in barometric pressure correlates with oceanographic variables (precipitation, wind speed, wave height, sea surface temperature).
  • Activity C:
    • Determine how to classify a storm as a bomb cyclone
    • Determine whether the storm from Activity A is a bomb cyclone
  • Activity D:
    • Determine when a bomb cyclone occurred from a large dataset
  • Activity E:
    • Compare a hurricane to a bomb cyclone

Teaching Materials:

  • Instructor Manual (Microsoft Word 2007 (.docx) 22kB Jul6 21)
  • Instructor PowerPoint (PowerPoint 2007 (.pptx) 5.8MB Jul10 21)
  • Student Handout (Microsoft Word 2007 (.docx) 74kB Jul6 21)
  • All Datasets (Excel 2007 (.xlsx) 5.6MB Jul10 21)
  • (Instructors Only)
  • (Instructors Only)

Teaching Notes and Tips

The module has been designed to expose students to regularly-studied oceanographic parameters and how they change during storms. Bomb cyclones have been in the news and students are usually curious about how they are different from other storms, particularly hurricanes. Students will also be exposed to real-time data platforms including the Ocean Observatories Initiative (OOI) arrays and the National Data Buoy Center. Instructors should be mindful of the following common misconceptions:

  • Bomb cyclones are a completely new type of storm.
  • Bomb cyclones are not as destructive as hurricanes.

Workflow of this module:

  1. Assign pre-class readings reviewing correlation, regression, and rate of change.
  2. Give students their handout when they arrive to class.
  3. Instructor gives brief PowerPoint presentation with background material. Discussion of the readings can be integrated into this presentation or done before.
  4. Students work through the module activities.
  5. Instructor and students discuss how bomb cyclones compare to other types of coastal storms.

Notes on the student handout:

Depending on how instructors would like students to record their process and answer questions, the student handout may be reformatted. A student handout key is available to instructors.

Measures of Student Success

In Activity A, after the PowerPoint presentation and a discussion of the readings, students will make predictions on what happens to oceanographic variables (precipitation, wind speed, wave height, sea surface temperature, and barometric pressure) during a storm. Students will then create graphs to determine the change of oceanographic variables during a winter storm from a provided OOI dataset. Prior knowledge will help guide student predictions. Student graphs will demonstrate their ability to use basic graphing in Excel.

In Activity B, students will calculate correlation coefficients to determine if barometric pressure can be a useful predictor of oceanographic variables. Prior knowledge will help guide student predictions. Student graphs will demonstrate their ability to use basic graphing in Excel. Students will show their understanding of correlations by interpreting patterns and trends in graphs, as well as by using linear regression analysis and R2 values.

In Activity C, students learn how to classify a storm as a Bomb Cyclone. Students choose a subset of the provided dataset to calculate the rate of change of barometric pressure over a 24-hour period. Students will create a scatterplot and calculate the slope of the trendline. Student graphs will demonstrate their ability to use basic graphing in Excel. Students will show how linear regression analysis can provide evidence to support storm analyses and classifications.

In Activity D, students will be given more choice in how to analyze the data. Students will be given a larger dataset from a known Bomb Cyclone, Winter Storm Grayson, and will choose the 24-hour time frame used to classify it as a Bomb Cyclone. Students will have the opportunity to choose multiple time frames to analyze. Student graphs will demonstrate their ability to use basic graphing in Excel. Students will show how linear regression analysis can provide evidence to support storm analyses and classifications.

In Activity E, students are asked to compare a Hurricane and a Bomb Cyclone. Students will make predictions on how oceanographic variables compare and contrast between the two types of storms. Students will graph the variables for both storms, and compare the data to their predictions. Student graphs will demonstrate their ability to use basic graphing in Excel. Students will use outside sources to answer questions about the two types of storms.

References and Resources

The Oceans Observatory Network (2020) Coastal Pioneer Array: https://oceanobservatories.org/array/coastal-pioneer-array/

Sanders, F., & Gyakum, J. R. (1980). Synoptic-Dynamic Climatology of the "Bomb". Monthly Weather Review, 108(10), 1589-1606.