Wednesday, June 25, 2014

An Essay: Applying Classroom Theories to Real Weather Experiences

Most of us who have been through a course or two in meteorology know that it requires more than just looking outside your window and seeing what the current weather is.  I remember my days as an undergraduate student sitting in a cozy classroom surrounded by di-fax maps along the “map wall” during my meteorology classes and wondering how in heck are all of these topics relevant to weather forecasting especially in severe weather.  I was a little green back then.  I attended Millersville University which is about 60 miles outside of Philadelphia where the terrain, road network and the abundance of trees made it less than ideal for storm chasing, although it did not discourage the hardcore students from going out.  Their adventures usually ended up in wild goose chases.

Image taken from e-education page from PSU.
Fast forward to my graduate school days, where I attended Texas Tech University for my master’s degree.  Although I lived in a great area where supercell thunderstorms were plentiful, I was not the type of storm enthusiast that would deploy for every slight risk day issued by the Storm Predication Center.  I was more of a calculated storm chaser.  I opted more for textbooks and theories than going out in the field this is what I was accustom to in my undergraduate study.  

It was not until my second year at Texas Tech that I saw my first “live” tornado.  I had been out various times storm chasing with my buddies before that day. My previous chases were unsuccessful with respect to observing a tornado.   I still recall that moment when I saw my first tornado somewhere near Altus, OK.  It was such an adrenaline rush and thrilling experience. I was hooked after that day. 

While finishing my Ph.D. work at Saint Louis University, I still ventured out once in awhile in pursuit of these elusive weather phenomena.  During my time at Saint Louis University in the early 2000s, professional storm-chasing tours were becoming very popular.  I recalled having a conversation with a friend and discussing why we couldn’t get academic credits for storm chasing by providing our observations in a written report with data about our experiences.  In my academic journey, what I have learned is that visual observation helps to correlate the difficult theories much better than reading from a textbook alone.  


A LP supercell west of Julesburg, CO in 2013.
My belief is that as meteorologists, we are trained to be keen observers in and outside of our work environments.  Seeing weather phenomena up close is a way to understand them better, providing a natural connection with theories that cannot be taught in the classroom with still images.  In my current position as a professor of meteorology at Metropolitan State University of Denver (MSU Denver), I wanted to develop a course that would require students to experience “real” weather instead of looking at a computer screen or reading a textbook all the times. 



El Reno on May 31, 2013.
In recent years, numbers of programs that have started taking students out storm chasing officially (University of Illinois, SUNY Brockport, Rutgers University, Western Kentucky University, and College of DuPage to name a few). The trend of this type of a course/experience has been gaining popularity among 4-year institutions offering a bachelor degree in meteorology.  So during the summer of 2012, I teamed up with Scott Landolt (who works for NCAR, an alumnus of MSU Denver and an adjunct professor) to co-instruct a course that requires students to go out and experience real weather. The course is called, “Weather Analysis and Observation.”

Supercell west of Sidney, NE in 2014.

This field-based course is intended to combine classroom theories with actual field observations.  Students who are enrolled in this course are at various stages of their meteorological education.  This course requires students’ to make their own convective forecast in the morning, which they then discuss with other students and professors, take observations of basic weather variables at different stages of a storm’s evolution, and lastly, write a detailed report on their storm observation periods (SOP) after the course’s 2-week “observation” period is over. This report typically consists of a case-study analysis of multiple SOPs where they discuss initial forecasts, how the storms evolved, whether or not their forecasts verified and an explanation if it did not along with photographic evidences of the storm at various phases with explanations of the storm structures observed. Ultimately, the end goal of the course is for students to apply what they have learned in the field and be able to bring it back to the classroom environment.

Students taking in the awesomeness of real weather. 

Thursday, June 19, 2014

Identifying Low-Level Boundaries

During the convective season, strong thunderstorms will form, if all the ingredients are in place (moisture, instability, and lift), along some types of a boundary.  The low-level boundary can range from a synoptic scale front to a previous day storm’s outflow.  Often low-level boundaries act as a focus for the concentrated upward vertical motion necessary to initiate deep convection.  Moisture maximum along a boundary can enhance the strength of the updraft as well.  Finally, interaction between multiple boundaries can set off new convection.  Boundaries occur year round but the small-scale types are mainly a warm season phenomena.
Processes necessary for deep moist convection to occur. Adopted from Doswell (WAF, 1996).
Surface data is one of the best source to analyze low-level boundaries. Temperature and dew point temperature gradients are areas where boundaries tend to form. Pressure trough and wind shift can be used to locate low-level boundaries as well.  Discontinuity in low cloudiness or fog and in precipitation or precip-type (mainly cold season) can signal a possible existence of a low-level boundary.
The image shows the Denver Convergence Vorticity Zone (DCVZ) on June 8 2012 at 0200 UTC.
An example of a dryline that occurred on 1800 UTC May 4 2003.
Upper-air data can be used to locate low-level boundaries, as well but mainly on the larger scale (synoptic range).  Frontal inversion from a sounding can hint at a boundary that has already passed. In addition, plotting a 1000-500 mb thickness map can provide incite where a front is located. This method is very useful in analyzing an occluded front.

An example of a frontal inversion from Denver sounding on 10/26/20006 at 1200 UTC.
Finally, remote sensing data have proven to be robust ways on locating low-level boundaries. Initial precipitation echo pattern from a radar can verify an existence of a boundary.  While in clear air mode, a fine line on a radar display can provide the location of the low-level boundary.  Visible satellite imagery can reveal cloud lines (Cu, Cb or St) which shows correlation with low-level boundaries.  
FTG radar in clear air mode indicating a boundary east of Denver on Nov 2 2005.
Visible satellite image from June 19 2014 at 2045 UTC.  The circle indicates where a boundary has initiated thunderstorms.
Surface observations plotted with radar data on Aug 7 2010 at 2100 UTC.

Wednesday, June 11, 2014

The Importance of Short-Wave Troughs and How to Identify Them.

Short-wave (S/W) toughs are features in the general flow of the atmosphere that are very important when it comes to forecasting for convective and winter weather.  Short-waves tend to be more of "weather-makers" where as Long-waves (Rossby Waves) are "trend-makers." Multiple S/W troughs can be imbedded with in a Rossby Wave trough.  Shortwave troughs tend to move faster then its longer wavelength counterparts.

The images below are from a 500 mb analysis at 1200 UTC 22 September 2003.  The first image shows 6 Long-Waves around the Northern Hemisphere denoted by the blue line across each long-wave trough axis.  The second image depicts the 500 mb analysis across North America only.  Embedded with in the Rossby Wave trough across the central US are 3 S/W troughs moving around the it, denoted by blue axes.



Here is a quick table to show the differences between Long-waves and Short-waves.  This table is assuming the observer is at 40º latitude.  


General Characteristics:
Long-waves
Short-waves
Number of Waves

3-7 across hemisphere; typically 4-5

~ 15-40° (1275 - 3400 km) longitude wide, move through long wave troughs

Amplitude

Meridionally, on the order of several 1000 km
Meridionally, on the order of several hundred km, up to 1000 km

Wavelength

~50-120° longitude
(4250 - 10,200 km)
~10-40° longitude
(1275 - 3400 km)

Diagnosed best at

At 500 mb and above

At 500 mb and below

Movement

Generally eastward at 10-15 knots; but can remain quasi-stationary or even retrogress

Dominantly eastward with a northerly or southerly component; faster than the long wave troughs

Energy Regime

Barotropic or Equivalent Barotropic

Definitely baroclinic

*At 40º latitude, 1º longitude ~ 85 km and at 45º latitude, 1º longitude ~ 79 km.

Identifying a S/W trough at mid-levels of the troposphere is not always simple or straight forward, especially during the warm season (May-September). Here are some guidelines to help one to identify S/W troughs.

1)  Look for a trough in the height field.  In the cold season S/W troughs are usually easily diagnosed through a good contour analysis.  In the warm season, you may need to decrease the interval between heights to better define the trough (example, using a 30 gpm interval at 500 mb instead of the standard 60 gpm).

2)  Locate a wind shift across the trough axis.  Normally, winds should back as the S/W trough approaches an area and then veer after passage of a trough.  A 12-h wind shift change can be used over a station to help individuals to spot these trends (example, V30, B40).

3)  Analyze the isotherm pattern.  Isoplething isotherms at a 2ºC interval on upper-level maps can help to spot subtle cool pools or thermal troughs that may not show up in the height analysis.  Remember, heights of pressure surfaces are based on the mean temperature of the atmospheric column. Shallow cool pockets of air aloft may be masked by the height field since it is more sensitive to the mean temperature and not the level of analysis' temperature. 

4) Look at the mid-level dew points or dew point depressions.  Downstream from the S/W trough, you should observe higher dew points and lower dew point depressions than upstream from the trough axis. This assumption is based on the fact that there is generally upward vertical motion (UVM) downstream from the trough axis and downward vertical motion (DVM) upstream from the trough axis.  

5)  Review the surface cloud reports.  Typically, SW troughs aloft create mid-level cloudiness (i.e., altocumulus, altostratus, altocumulus castellanus) downstream from the trough axis.  This is associated with mid-level UVM associated with the S/W trough.

6)  Look at visible (VIS) and infrared (IR) satellite imagery. As noted in point (4), mid-level clouds are associated with S/W trough.  

7)  Analyze the water vapor (WV) channel.  Often jet streak can be found coming around the base of a S/W trough.  This feature may show up as a dark slot on the WV imagery.

8)  Review a sounding.  Soundings downstream from the S/W trough should show a middle tropospheric layer of higher dew points and low dew point depressions even if clouds are not see in the satellite imagery or surface cloud report.

9)  Look for vorticity maximum or "lobe" (elongated curved region) of vorticity.  As noted in point (2), S/W trough have cyclonic wind shift across their axis which will show up on a vorticity analysis. Remember, when performing vorticity analysis, be sure to use absolute vorticity and not relative vorticity.

10)  Analyze the height change field (isallohypses).  Similar to a frontal passage where an incoming front will have lower pressure tendency values ahead of it; the height field ahead of an approaching S/W trough should have negative values in the isallohypses field.

Hope these basic pointers about short-wave troughs will help you to become a better armchair forecaster.  

Buoyantly yours,

@docwx

About Me

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Denver, CO
I am an Associate Professor of Meteorology at Metropolitan State University of Denver (MSUDenver). I have been at Metro State since 2005, teaching various courses from Synoptic to Mesoscale Meteorology and everything in between. I also manage the weather lab at MSUDenver. While my duties are focused primarily on teaching, I remain active in serving the student body. I am the faculty advisor of the student chapter of the American Meteorological Society. In 2005, I received a Ph.D. in Meteorology from Saint Louis University for my research on processes associated with heavy banded snowfall in the Midwest under the tutorage of the late James T. Moore. My other degrees are from Millersville University of Pennsylvania (1998) for a B.S. in Meteorology and Texas Tech University (2001) for a M.S. in Atmospheric Science. My weather interests include but no exclusive to quasi-linear convective system (QLCS), mesoscale snowband, rapid cyclogenesis, severe local storm prediction, and numerical weather prediction refinement in operational forecasting. I am also a contributor to Weather5280 Team (http://www.weather5280.com).