Students learn how scientists assess wildfires using remote sensing, then use some of the same techniques to solve grade-level appropriate math problems.

This video introduces viewers to oceanic thermohaline circulation - the system of global ocean currents that cycle warm and cold water across the planet.

This interactive online visualization allows the user to view a variety of weather patterns including temperature, wind, and wave action over time.

This exercise is designed to present the realistic problems of forecasting weather. Lake effect snows are hard to forecast because they depend on information that isn't part of the regular set of information and involve some pretty specific things that integrate the location of the site with surrounding environment. Even places close by can get totally different forecasts. When you have a regional forecast, it doesn't really address lake effect snows, unless the forecaster really focuses. So the exercise aims to show the value of broad critical thinking in meteorology, and it is very dramatic, because the difference between 36 inches and whiteout and clear blue sky is undeniable. The exercise comes when students are 8 weeks into the class. The class is an AMS based class, which has already been described well in this workshop by Julie Snow from Slippery Rock. Our class is given in the fall semester and lake effect snow starts in October and is quite an issue in forecasts until April. The skills of a forecaster are tested, and you cannot use forecasts from nearby areas reliably. Finally, we live in a fantastic snow belt, so lake effect snow happens a lot. In a good year we get over 300 inches of snow, mostly at times that places nearby do not. You can drive to Houghton in the bright sun and be met by a wall of very active blizzard just a few miles out of town.

There are some excellent tutorials available from COMET, and outreach of the National Weather Service. I use one done by Greg Byrd, which is available online or in a power point format. There are a number of things that must be learned before forecasting. These include some fluid dynamics of plumes, latent heat, remote sensing, upper air mapping, and the use of models. We cannot cover all them completely. I try to introduce all these things and give people entry points into the juicy parts of these topics, but do not expect students to understand completely. One thing you can spend a long time on are the satellite images. Here is one, just to whet your interest: http://serc.carleton.edu/details/images/13586.html

I have the students make a list of the critical parameters they think might be needed for a successful lake effect forecast. This is a challenge to prepare, but the idea is to include things that are even marginally useful and to collect data to see what is most important. We get a list of parameters like this:


850 mb wind direction
850 mb temperature
Lake Superior surface temperature
fetch length
opposing bay?
Inversion layer height
topographic lift factor
wind shear evidence
upstream lake
upstream moisture factor
snow/ice cover issues


This list is pretty good, but deliberately not complete, and we encourage students to add other things they think might be important. The next step is to find where you can get this information. I have web data sources for most (see below), and some of them are interrelated. You can do this exercise for any site around Lake Superior or probably many other lakes as well. For specific sites, the fetch length, upstream lake and opposing bay information are obtainable directly from the wind direction if you have a good map (Google Earth). So a spreadsheet for parameters related to wind direction can be prepared in advance and these parameters can be immediately available from the wind direction. Nonetheless the issue of sources for all this stuff must be addressed in an effort that spans several hours. The use of models is needed to look into the future where possible.

Once students know what they are looking for and how to find it, the exercise starts its data collection. Every day or every 6 or 12 hours beginning when conditions get close to "LES favorable" students collect information on these LES predictors. They also make LES forecasts for each period and include that information in the spreadsheet. The next day the real snowfall data is added to the spreadsheet, and this can be used as validation data for the forecast. This data collection needs to be done for several weeks (November and December in my case, usually a good time for LES).

The data analysis is the most challenging part. Spreadsheet plots which test the sensitivity of various parameters singly and together are possible. There is a lot of sophistication possible if there is enough LES to analyze. Overall, results should be a good experience with imperfect data addressed to a real-time problem. Models and real data, remote sensing, and balloons are all integrated and there are quite obvious weaknesses.

On the final day of class student groups will compete by doing forecasting which employs the LES techniques. This might reflect the most recent snow event. A more important element of this submission will be their evaluation of LES prediction parameters. Not only do we consider the actual forecast, but we discuss which parameters were successful? Which are inconclusive? What suggestions for improved forecasts are possible from the experience? The format of this will be short presentations with time for discussion.

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Human-caused climate change represents one of the great environmental challenges of our time. As it is inextricably linked with issues of energy policy, a familiarity with the fundamentals of climate change is critical for those looking to careers in the energy field. To appreciate the societal, environmental, and economic implications of policies governing greenhouse gas emissions, one must understand the basic underlying science. METEO 469 serves to lay down the fundamental scientific principles behind climate change and global warming. A firm grounding in the science is then used as a launching point for exploring issues involving climate change impacts and mitigation.

This class is designed to expose you to the cycles of disasters, the roots of emergency planning in the U.S., how to understand and map vulnerabilities, and expose you to the disaster planning in different contexts, including in developing countries.

This is lesson five of a 9-lesson module. Activity explores the effects of climate change on different parts of the Earth system and on human well-being: polar regions, coral reefs, disease vectors, extreme weather, and biodiversity.

In this lesson, students analyze and synthesize data about how drought is measured, how scientists expect drought to change in the future, and how we can mitigate the impacts of drought in our communities.

In this lesson, students build an understanding of drought in Colorado through exploring case studies, authentic data, and online resources. After completing this lesson, students will be able to understand the basic causes and impacts of droughts, analyze a case study and current drought data in Colorado, and summarize the main preparedness steps and response strategies for drought events.

In this lesson, students analyze and synthesize data, and design local flood preparation strategies to answer the question, "What can we learn from past flood events to prepare for future floods?"

In this hazard lesson, students build an understanding of flooding in Colorado by exploring case studies, authentic data, and online resources. After completing this lesson, students will be able to understand the basic causes and impacts of floods, analyze case study and current flood data in Colorado, and summarize the main preparedness steps and response strategies for flood events.

In this lesson, students analyze and synthesize data, and design local wildfire preparation strategies to answer the question "What can we learn from past wildfires to prepare for future wildfires?"

In this lesson, students investigate wildfires in Colorado by analyzing wildfire data and information to create a local news story that educates community members about wildfire risk. In Part 1, students watch and discuss a short documentary about wildfires. In Part 2, students analyze wildfire data to build understanding of the causes, impacts, locations, and frequency of wildfires. In Part 3, students create a local news story for their community.

In this interactive game, students solve challenges that their community faces during the course of an extreme drought event by using available individual and community resources. Students work in three resilience teams to determine the strategies that they will invest in as a community as the drought situation evolves.

In this interactive game, students solve the challenges that their community faces during the course of an extreme flooding event by using available individual and community resources. Students work in three zone response teams to determine the responses they will take in each round as the flood situation evolves.

In this interactive game, students solve the challenges that their community faces during the course of a wildfire event by using available individual and community resources. Students work in three zone response teams to determine the responses they will take in each round as the wildfire situation evolves.

Students will be required to answer a series of simple questions for this assignment based on material covered in lecture. This assignment also allows students the experience of searching a website for more specific information about hurricane statistics that are not covered in lecture. Hurricane Katrina will be discussed in lecture. Students will see where Katrina falls relative to other major hurricanes while answering the questions.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

In this problem-based learning module, students research and report on Hurricane Katrina, using an earth systems science analysis approach.

In this activity, students learn how people prepared for and then dealt during a hurricane by analyzing news headlines about Hurricane Florence (2018). Then they analyze data about the amount of damage that different categories of hurricanes cause, learning that even low category storms are able to cause damage.

This homework assignment is given in the first two weeks of class. Students receive one or two lectures that cover the topics of atmospheric layers, temperature and pressure profiles, concepts of atmospheric mass and pressure and measuring (i.e. dropsonde) instrumentation. At the beginning of each lecture I briefly show them the tropical update from the NOAA National Hurricane Center web site; if there is an active storm, I show where I go to get more info, such as the projected storm track and storm history (for example, from Intellicast Hurricane Tracking). Then, for this assignment, I reintroduce them to these hurricane information web sites and demonstrate how to find the historical data on tropical storms (such as from the Unisys Hurricane Data Archive), and how to copy and paste text data into word and/or excel, as a tab- or space-delimited file. I point out some problem areas with this data-grabbing method, such as headers that get lost from their associated data column or date information that may not format as dates.
I then hand out the assignment, which asks them to:

Find data on a current or recent (this year) tropical system, provide the name and year of the storm and the reference web site, and plot the wind speed and pressure variables against time. Students should label the axes and give a descriptive title to the chart.
Describe what they notice in the graphed data and if it seems believable (this allows students to decide if they have done the task correctly by using their understanding of the data).
Predict what will happen if the storm a) intensifies or b) weakens.
I then provide another data set (of any long-duration tropical storm that formed, weakened and later re-intensified) and ask them to go through the same process of plotting and interpretation.
I tell them that some future climate predictions are for more storms with lower central pressures and ask which of the two charts best represents that future scenario, and why.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)