Big hail near Dallas, April 11

A major hail event occurred in the north suburbs of Dallas on Monday, April 11.  Some media I thought worth saving are captured below.  [Reminders: more than anything, this is archive of images and links that I might use in future classes.  I may add more later, or delete some of these.  If you have any sources that you think complete or improve on this set, please do share.]

Let’s start with the geography of the event:

The Severe Thunderstorm Warning that included Wylie, focus of some of the videos below:

 

Videos

Slow-motion video of baseball or softball hail crashing into a pool:

Additional good ones:

 

Photos

I don’t know how big this person’s hand is, but does it really matter?

Additional good ones:

Meteorology

  • The focusing mechanism for convection: a surface low, frontal boundary and dryline.  The WPC’s surface analysis at 1800 UTC:
    namussfc2016041118
  • The full complement of upper air charts for 1200 UTC (11th) and 0000 UTC (12th) is available via the Storm Prediction Center’s archive.
  • A 9-h forecast sounding from the 4km NAM for 2100 UTC (model initialized at 1200 UTC).  Over 3000 J/kg of CAPE, no matter how you calculate it!
    nam4km_2016041112_009_32.91--96.14
  • And if model soundings aren’t your thing, the observed, pre-event FWD sounding at 1800 UTC.  But note that in this case, there’s a 2500 J/kg difference between surface-based and mixed-layer CAPE; the high surface dewpoint may be anomalous.
    FWD
  • A regional radar loop that honestly isn’t that breathtaking, but illustrates the isolated supercell nature of this hail producer.
    dfw_hail
  • At one point, about 2200 UTC, the storm had a textbook high-precipitation supercell look.  Upper left and color bar: reflectivity at the lowest elevation angle.  Lower left: storm-relative velocity.  Upper-right: VIL (the scale maxes out at 80 kg/m2, but I found a value of 121!!!).  Lower right: radar-estimated maximum hail size, with one pixel indicating 2.98-inch size.  Probably one too many significant figures there, but I digress.
    kfws_20160411_2202

Images and data from November 16

The rare November tornadoes in western Kansas provided some breathtaking photography and great meteorology.  As I’ve said before, one purpose of this “blog” is to keep some of that information together for posterity’s sake and for future classes.  If there’s anything you think would make a nice addition, send it on.

NWS survey photos and damage tracks:  http://www.weather.gov/ddc/TornadoOutbreak2015Nov16

Recap from US Tornadoes website, emphasizing the rarity of a November tornado event in the Plains

USA Today’s story has a superb collection of Twitter-linked photos from the day

Springtime in November” brief summary from Jeff Masters, including a couple of links

Story from the Hays Post, of people complaining about the lack of sirens even when they were being warned via text message (sighhhhh)

Sorry about the sounding diagrams below — they display correctly at full resolution, but they have a transparent background so the thumbnails look garbled.

DDC

DNR

500_151117_00

namussfc2015111621

Throwing out the record books?

I’ve tweeted about that phrase a lot this week.  “It’s a rivalry game, so throw out the record books!” and all its variations, in most cases, couldn’t be further from the truth.

Records of the favored team in rivalry games since 1995 are shown below; lines and results are from Odds Shark.

  • Alabama/Auburn 15-4
  • Baylor/TCU 6-3
  • Clemson/South Carolina 15-4
  • Florida/Florida State 16-3
  • Georgia/Georgia Tech 12-7
  • Indiana/Purdue 17-2
  • Michigan/Ohio State 15-4
  • Michigan State/Penn State 11-4
  • Minnesota/Wisconsin 17-2
  • Notre Dame/USC 14-6
  • Oklahoma/Oklahoma State 13-6
  • UCLA/USC 13-6

All games are alphabetical, just so no one gets peeved.  🙂  The favored teams have the worst results in Baylor/TCU, which may be because they’ve only played 9 times in those 20 years.  For all the others, it is overwhelmingly true — on average 75 percent of the time — that the favored team wins.

(Disclaimer: results from this year are not included, since I just decided to do the post today.  I’ll update it between now and next year.)

The “All-Star Soundings”

One of the highlights of my undergraduate synoptic meteorology course at Oklahoma was the first three weeks — the “all-star soundings,” our individual presentations of notable weather events which had classic signatures on the Skew-T diagram.  Dr. Kenneth Crawford was one of the best teachers I ever had, and I loved this part of his course so much that I’ve kept the name and tried to carry on the tradition.

This post is simply a way for me to keep track of all the events I’ve collected on my “all-star” list.  I’ll come back and add more as I find them, as people suggest them, etc.  Don’t hesitate to submit your own: by sharing this list publicly I want to make it more of a community effort.  Ideally, while the events from pre-2005-ish are good, there is much more data available online for those that are more recent; I’m most interested in those.

As of right now, the entries don’t have a common format–I’ll change that later.  I might even add links.  They are sorted only by date and season, the way it was when I was a student.  Old habits die hard.

Cool Season Soundings

  • IAD 12 UTC 03/13/1993 – “Storm of the Century”
  • HAT 12 UTC 03/13/1993 – “Storm of the Century”
  • BNA 12 UTC 03/13/1993 – “Storm of the Century”
  • INL 12 UTC 02/02/1996 – Arctic Air Outbreak
  • LCH 00Z 01/13/1997 – Ice Storm
  • WMW 00 UTC 01/06/1998 – Ice Storm
  • Buffalo – Lake Effect Snow Christmas 2001
  • CRP 12 UTC 12/25/2004 White Christmas in South Texas
  • JAN 15 UTC 12/11/2008 – Deep South Snow/Heavy Rain
  • OKX 00 UTC 12/27/2010 – NY Blizzard with Thundersnow
  • DNR 12 UTC 12/22/2011 – Upslope Snow
  • January 2014 – the “Polar Vortex” Cold Air Outbreak
  • February 2014 Southeast Ice Storm
  • Buffalo Record Lake Effect Snow – November 2014

Warm Season Soundings

  • CKL 12 UTC 03/27/1994 – Palm Sunday Tornado Outbreak
  • TOP 00 UTC 04/11/2001 – Hailstorm
  • LIX 06 UTC 08/29/2005 – Hurricane Katrina
  • JAX 00 UTC 08/22/2008 – Tropical Storm Fay
  • LCH 12 UTC 09/13/2008 – Hurricane Ike
  • JAN 18 UTC 04/24/2010 – Yazoo City, MS Tornado
  • BMX 18 UTC 04/27/2011 – April Tornado Outbreak
  • SGF 00 UTC 05/23/2011 – Joplin Tornado
  • ILN 00 UTC 05/26/2011 – Indiana Tornadoes
  • ILX 00 UTC 07/12/2011 – Derecho
  • Hurricane Irene – August 2011
  • High Risk / Ohio Valley Tornado Outbreak – March 2012
  • OUN 00 UTC 08/04/12 – Plains Heat Wave
  • Wildfire in Arizona – June 2013
  • Colorado Record Flooding – September 2013
  • Detroit Flooding August 2014
  • Calbuco Eruption, Chile – April 2015
  • CRP 12 UTC 10/30/2015 – Record TX Rainfall

I’m overwhelmed.

I just can’t figure out how to keep up with all the “social media” accounts I have. At least not all of them at the same time. Maybe this think-out-loud post, or some of your comments, will help.

As with most people, I’ve used Facebook to stay connected with family and friends, but I haven’t posted there much lately at all. I’m not losing touch with anyone (any more than I already have!) — instead I’ve been sharing more of my quick thoughts, ramblings, and science link finds on Twitter. That’s where most of my science- and teaching friends and colleagues are, where our dialogue is, where the community is. It means that my own  feed is a mosh of weather, education, political ramblings and sports quips, but it works. I could separate those into multiple accounts like some of my friends do, but so far I have refused because I am one person. A very complicated person, but one with lots of interests, from Alabama to Z-R relationships.

This summer I joined Instagram for its intended purpose, photo sharing. That site has become my happy place — a no-spin, no-bad-news zone. Come over and sit a spell.

When I don’t want to be bothered by anyone I know, there’s Tumblr, which for me is more for kitten animations and funny pictures and such. That leaves us with this blog, which in my mind has an identity crisis. I don’t know what I want to put here. And more so a time crisis, which is the essence of this rambling — I just simply don’t know how to juggle all of these. I already have way too many emails to answer and text messages to read and write. And course materials and websites (with blogs, ugh!) to maintain. And a couple personal websites I run. It always seems, however, that when I focus on one or two, the others take a hit in activity. How do you all do it?? How do you keep up track of all your platforms and media at the same time without becoming paralyzed by it all??

My favorite media from April 9

In addition to just serving as a “blog,” I want to use this space to curate some of the images, videos, and links used in class for specific weather events.

The tornadoes of April 9 in Illinois (and elsewhere) are a good starting point.  Don’t hesitate to offer additions or corrections.  Each list like this will probably be updated at random times in the future.  Almost all these will be linked from source–I’ll provide acknowledgments for any that aren’t.

Videos

Photos

Data, other items, etc.

 

I love cumulative exams.

In a recent Faculty Focus post, Maryellen Weimer argues in favor of cumulative or comprehensive exams, which most of my students aren’t particularly fond of.  [grin]  Put very simply, she says “Students don’t like cumulative exams for the very reason we should be using them: they force regular, repeated encounters with the content.

This post is a reminder to me to include more of my old test questions.  They are ideal for in-class discussion, formative and summative assessment of student understanding for a course unit, and even to help me identify vague or confusing questions.  (There have been a couple of those lately–so I’ve resolved to punt them off the exam and use them in class next semester so I can figure out how to fix them.)

I also love the ideas to bring up older course material as a way to instill better cumulative/comprehensive study habits.  Almost all the courses I teach have at least some long-term scaffolding to them (shouldn’t we be designing our courses that way???), and I need to do a better job of cultivating these skills in my students.  This was spring break week on my campus, and Monday I think I’ll open with a pop quiz based on her last item:  “Your friend Leo wasn’t in class last week.  He texts, asking what happened in class.  Text Leo a short answer and don’t tell him ‘nothing’.”

On scaffolding and learning outcomes

About 10 minutes into the first class meeting…..”I expect all of you to come to class prepared…”

Yawn.  *clicks back to Facebook tab*

Prepared to do what?  Listen to a lecture for an hour every day?  How do I need to prepare for that beyond making sure my laptop battery is fully charged?

Or perhaps, we should ask (and expect) our students to show up prepared for an active class period full of questions, problems, what-ifs, discussions, and ultimately some answers.  So how do we do that?  I try my best to follow Robert Talbert’s guide to creating learning objectives.  Seriously, that little blog post may be one of the best explications of how to design effective, active classrooms that’s ever been produced

To provide an example, I’ll return to the “difference between HP and LP supercells” outcomes I wrote about last fall.  In a course unit on supercell archetypes where we want students to “know the difference between LP and HP supercells,” we might come up with these:

“At the end of this section, students will be able to:

– state the physical differences between LP, classic, and HP supercells;

– recognize the different overall structure between the conceptual models of the three types;

– identify which types are more/less likely to produce tornadoes, strong “straight-line” winds, and large hail;

– describe how environmental wind shear plays a role in modulating supercell type;

– describe how atmospheric water vapor and/or cloud base height play a role in modulating supercell type;

– sketch and label archetypal models of LP, classic, and HP supercells, including cloud and precipitation extent, updraft location relative to precipitation, surface outflows, and the most likely location of a tornado;

– differentiate between supercell modes using radar data; and

– differentiate between supercell modes in photographs and/or videos.”

Wow.  That’s a lot to accomplish…probably multiple classes!  I think these are listed roughly in order of increasing difficulty–which is the point–and it would be very easy for me to just sit back and put together 80 or 90 slides that cover everything, and then test students on what I think is important.  But I’d rather have them do some Preparation H (homework!) and come to class armed with some basic vocabulary and knowledge.  That way, we can get further down the list and spend our class time really diving into and interpreting the radar data, pretty pictures, and complex videos.

So here’s my approach.  Before the class period(s) on supercell types, students are expected to be able to perform the first three, maybe four, tasks on that list.  Yes, I expect them do be able to do these things before coming to class.  The activities for this unit would probably involve reading (Ahrens Extreme Weather and Climate pp. 311-5), looking at additional material (this nice and quick summary by Zach Roberts), and answering short questions online before class (the Just-in-Time method; my example questions for both days of this unit are at the bottom of the post).  If students have done the requested assignment, and spent time digesting it and trying to understand it, they should be able to answer these questions easily and will be well prepared for two productive and fun class periods.

Class time would begin with a follow-up on anything that students identify as still unclear, and a review of their answers to the pre-class questions.  This typically only requires 10-15 minutes; after that, we move on.  For the students who didn’t answer the questions, and didn’t show up prepared, they are going to be seriously lost for the rest of class.  It is imperative that students realize their success in class depends on coming to class prepared.

It’s then on me to select the right kind of in-class activities to achieve the last 4-5 objectives in the list.  Just a few ideas:

  • I might draw three different vertical shear profiles on the board, and ask students to discuss and then draw in what the Cb would look like — barely tilted in weak shear, somewhat tilted in moderate shear, and very tilted in strong shear.
  • Provide a printed color copy of reflectivity and velocity data for a classic supercell, to let students draw on and place the mesocyclone relative to the precipitation.  (And then identify and label the “hook echo.”)
  • Giving the customary supecell schematic with most (or all) of the labels missing, and ask students to label pertinent features.
  • Display Figure 7 from Rasmussen and Straka 1998, and ask students to identify which bar graphs correspond to LP, CL, or HP storms.
  • Or others, depending on how students respond to the pre-class questions.

This set of learning outcomes, arranged in approximate order of difficulty, is precisely what I would give students as a “study guide” for these class meetings.  Exams would include questions that test a range of these outcomes.  The ‘A’ students will successfully use photos and videos and radar, the most complex tasks we do; the ‘B’ students will be able to relate supercell types to environment and to label their models; the ‘C’ students may only know the LP/CL/HP differences and the tornado risk from each.

I’ll close with Talbert’s last sentence, which is a superb summary of this process:  “This is far from a perfect system, but it’s a reliable way to align learning objectives with the actions you want students to perform and the means you want to use to assess them, and it gives students a key ingredient for self-regulated learning: A clear set of criteria that will tell them what they need to know and how to measure whether or not they know it.”

– – – – –

Students submit answers to these questions online before the first day:

1. The textbook omits large hail from the list of hazards for one of the three supercell types.  Which type is less likely to produce large hail?

2. Name two differences you see between the HP and LP photographs in the online reading.

3. Radars can be helpful in determining supercell type (LP/classic/HP).  Why do you think that’s the case?

4. Name one thing about either reading that was unclear, confusing, or that you would like clarification on.

Before the second day:

1. The author of this video has declared this storm to be an LP supercell.  Do you agree?  Why?  How would you compare it to the photo and schematic you’ve already seen?

https://www.youtube.com/watch?v=BF8XManeSn0

2. Name one thing that was unclear about yesterday’s discussion that is still unclear, confusing, or that you would like more clarification on.

My meandering thoughts