Forecasting Lake Effect Snow in Lake Superior region
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This page first made public: Oct 24, 2008
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Description of the activity/assignment
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
Inversion layer height
topographic lift factor
wind shear evidence
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.
Determining whether students have met the goals
Download teaching materials and tips
- Power point about LES, Greg Byrd NWS (PowerPoint 2.3MB Oct22 08)