University of Wisconsin–Madison

A COURSE BLOG WITH STUDENT ANALYSES OF WEATHER EVENTS

PROFESSOR STEVE ACKERMAN & TIM WAGNER 

ATMOSPHERIC AND OCEANIC 441

Background:

Sometimes we gave students an explicit assignment, and other times we let students find an interesting topic to present. Either way, students wrote their blogs with a detailed rubric in hand.

We controlled when the blog became visible to the entire class. Students would post a draft (though not publicly) by a certain date, and we would go online and make comments about the current posting as well as make suggestions for students to consider in their revisions. Students would then address those suggestions before the publication date.

After the blog was published, students from the class could see each others’ work, and the professor and TA could point to good examples during subsequent class sessions.

To see student blog entries:

The class blog with students’ entries is available online—http://profhorn.aos.wisc.edu/blog1/

 

AOS 441: Mountain Wave Case Studies

***Due before Friday Class***

The object of this exercise is to reinforce what you learned about McIDAS-V and interpreting features in water vapor images. You will do a blog to demonstrate your knowledge of interpreting imagery from a GOES satellite. You will do one of three case studies:

• Feb 4 2003 – Virginia region (GOES 12)

• March 6 2004 – Colorado region (GOES 12)

• March 9 2009 – Nevada region (GOES 11, 12, or 13)

Include an appropriate title and any authors involved in the study.

Use McIDAS-V to analyze satellite data for your case study. Using at least 2 GOES channels, locate and discuss the mountain wave feature.

Explain how you estimated the size of the feature and any potential deficiencies in your methodology. In your short write-up include:

• A GOES water vapor image that highlights the cloud feature you’re analyzing, including an animation. Include a brief description of the scene you are viewing.

• Include a legend that relates gray shade (or color scheme) to brightness temperature.

• Include ancillary data that you used to describe and explain the wave feature.

In your blog, also:

• Describe the approximate brightness temperature difference in the banded regions (dark and light areas) in the water vapor imagery.

• Estimate the approximate size, wavelength, and propagation of the wave. Compare the wind speed with the wavelength of the wave structure. (The forecasting rule of thumb is the wind direction is along the wave pattern. The velocity of the winds in a mountain wave can be estimated by: V=6 w + 12; where w is the wavelength in miles of the waves, and V is the wind velocity [in mph]).

• Explain how the banded structures in water vapor imagery are generated.

• Remember to include the four ‘W’s in your blog (When, Where, Wavelength and Wresolution)