NSSL Mesonet vehicle at the Exploratorium

The partnership is the result of a five-year educational grant with NOAA to co-develop interactive exhibits, learning experiences and professional development workshops for the learning institution.

NSSL retired researcher Dave Rust shared his thunderstorm electricity expertise and his skill at creating weather measuring instruments.  Dave pioneered the use of free-flying balloons and mobile laboratories to make observations, significantly advancing thunderstorm science.

Susan Cobb, NSSL meteorologist and science writer, shared her experience that includes forecasting for locations all over the world, and writing about weather science for all audiences. Susan worked with visitors to understand, experience and forecast weather in the San Francisco area and around the world.

Sean Waugh is a graduate student at the University of Oklahoma and an instrumentation specialist working with the NOAA NSSL.  He helped design and build seven Mobile Mesonets, storm research cars outfitted with weather instruments, computers, and communications equipment. Sean gave personal tours of the Mobile Mesonet and focused on ways NSSL collects data to learn more about storms.

The NOAA National Severe Storms Laboratory’s mission to improve our knowledge of severe weather and to develop new tools to better forecast and warn of its hazards has endured since its establishment in 1964. The Exploratorium first opened in 1969 and welcomes more than 500,000 visitors each year.

The bi-monthly charts on the left show tornado events summed for each period with the years increasing along the positive y-axis. The charts on the right use the same bi-monthly tornado sums for each period but years are re-ordered and ranked based on MEI. The strongest bi-monthly El Niño events are at the top of the y-axis while the strongest La Niña events are at the bottom of the y-axis. Years/months between the two extremes are ENSO neutral, or transition periods between the two phases.

Cook and Schaefer, 2008, found an increase in cool-season tornado events during ENSO cool-phase (La Niña) and this finding is borne out to some extent by the charts for the two bi-monthly periods of Dec-Jan and Jan-Feb. These two overlapping cool-season periods exhibit some correlation between summed tornadoes and MEI with no more than 12 percent of the variance (R²) in the summed tornadoes being accounted for by ENSO phase strength (stronger La Niña ~= more U.S. tornado activity).

The weak connection between ENSO cool-phase strength and more tornadoes is maintained, but to a lesser extent, for the Feb-Mar and Mar-Apr bi-monthly tornado events with R² values of 6 percent and 10 percent, respectively. All other bi-monthly periods throughout the year show very little or no correlation with ENSO phase strength indicating that there are clearly many other positive and negative influences that modulate tornado activity in the U.S. through most of the year. (The R², or proportion of variance, value is indicated in the upper left of each chart for each bi-monthly period where the years are ordered by ranked MEI value and is also indicated in the caption for each of these charts.)

It is interesting to note that in a couple of the strongest cool-season El Niño cases (1983 and 1998) tornado events appear to be above average when compared to other cool-season El Niño cases. This is especially true of the strongest El Niño case (based on MEI) of Dec 1982 through Jan 1983 (Dec-Jan right-hand chart below). Thus, a very strong El Niño (ENSO warm phase based on MEI) during the cool season does not necessarily result in weakly suppressed downstream tornado activity in the U.S. but may actually act to support more vigorous larger scale storm systems that, in turn, result in more tornadoes.

For additional information please contact Greg Carbin at SPC.

References:

Wolter, K., and M. S. Timlin, 1998: Measuring the strength of ENSO events – how does 1997/98 rank? Weather, 53, 315-324.

Cook, A.R., and J.T. Schaefer, 2008: The Relation of El Niño – Southern Oscillation (ENSO) to Winter Tornado Outbreaks. Mon. Wea. Rev., 136, 3121-3137.

Jan-Feb (Years in order)	Jan-Feb (Ranked by MEI), R2=12%
Feb-Mar (Years in order)	Feb-Mar (Ranked by MEI), R2=6%
Mar-Apr (Years in order)	Mar-Apr (Ranked by MEI), R2=10%
Apr-May (Years in order)	Apr-May (Ranked by MEI), R2<1%
May-Jun (Years in order)	May-Jun (Ranked by MEI), R2=2%
Jun-Jul (Years in order)	Jun-Jul (Ranked by MEI), R2<1%
Jul-Aug (Years in order)	Jul-Aug (Ranked by MEI), R2<1%
Aug-Sep (Years in order)	Aug-Sep (Ranked by MEI), R2<1%
Sep-Oct (Years in order)	Sep-Oct (Ranked by MEI), R2=1%
Oct-Nov (Years in order)	Oct-Nov (Ranked by MEI), R2<1%
Nov-Dec (Years in order)	Nov-Dec (Ranked by MEI), R2<1%
Dec-Jan (Years in order)	Dec-Jan (Ranked by MEI), R2=12%

That's no storm. That's a wind farm.

It’s time for yet another podcast of… That Weather Show… brought to you by the NOAA Weather Partners.  I’m Angelyn Kolodziej.

It’s always raining near Spearville, Kansas.  At least it appears to be when forecasters like Larry Ruthi look at radar displays.  Turns out, what looks like thunderstorms are actually rotating wind turbine blades.  Wind farms are popping up all over as renewable energy becomes a high priority for the nation.  But when they’re built near existing radars, new challenges arise for the NOAA National Weather Service.

Larry has worked at the Dodge City, Kansas Weather Forecast Office for more than sixteen years and has plenty of experience with this issue.

Wind Farm near Spearville, KS

Ruthi: “A wind farm on radar looks very much like an echo from a precipitation target or a shower or thunderstorm.  As the meteorological target moves through a wind farm – particularly if its close to the radar site – the return from the wind farm and the blades that are rotating around the antennas on the wind farm will mix with the return from the showers of t-storms and its a particular problem if its a severe weather event.”

So what’s causing this?  Let’s step back for a minute and talk about how the radar works.  A signal is sent out into the atmosphere.  That signal bounces off things like raindrops or hailstones and returns to the antenna.  The data are displayed for weather forecasters to use.  But the signal also reflects from non-weather objects like trees and mountains.  By detecting the lack of motion, radar can easily filter out these non-moving objects.  However, wind farms near the radar create a unique challenge.

Ruthi: “The towers don’t move but the blades rotate around the tops of those towers.  It makes it very difficult for our algorithm to filter those out.  So there’s a difficult conundrum that we’re dealing with there in trying to filter out the non-meteorological targets and still retaining as best we can the returns that we have from the meteorological targets.”

Wind turbine blade clutter near Montezuma, Kansas resembles a tornado signature.

The cluttered displays can be misleading for anyone using the radar data.  They can also affect the accuracy of forecasts.  Severe weather events like microbursts and tornadoes are sometimes difficult to identify.  Estimating rainfall in the area is also a challenge.

To work around this issue, forecasters must know the location and characteristics of wind farms on radar.  Scanning at higher altitudes can give forecasters a view above the rotating turbine blades.  Additional cooperative efforts may also be possible.

Ruthi: “There’s perhaps an opportunity to work together with the wind farm owners and managers to perhaps – for a short period of time each year when severe thunderstorms affect the wind farm area – to shut down the turbines that we would then be able to examine uncontaminated returns throughout the entire radar umbrella and make valid decisions without the problem of dealing with the wind farms.”

As for future wind farm development, it’s all about location, location, location.  Research shows wind farm impacts generally decrease the farther they are from the radar.  Reaching out to developers at early planning stages is a key focus for the National Weather Service.  By working together, everyone wins.  Larry and other forecasters have a clear view of the weather.  Developers build wind farms in strategic places.  And the public has access to cheaper, cleaner energy AND the best weather information possible.

Thanks for listening to another podcast of… That Weather Show… brought to you by the NOAA Weather Partners.

For more information about wind farm interaction with NEXRAD radar, visit: http://www.roc.noaa.gov/WSR88D/WindFarm/WindFarm_Index_GreatFalls.aspx?wid=*

Bright reds, oranges and yellows show tracks of where rotation was strongest as detected by NWS Doppler radars during the April 27, 2011 tornado outbreak.

NSSL has released an image documenting the rotation tracks of the devastating tornadoes on April 27. Bright reds and yellows show more intense circulations.

The image of the rotation tracks was produced by the On Demand Severe Weather Verification System, part of NSSL’s Warning Decision Support System – Integrated Information (WDSS-II) Multi-Radar/Multi Sensor platform. On Demand is a web-based tool that can be used to help confirm when and where severe weather occurred.

On Demand uses data gathered and sorted by WDSS-II to estimate the tracks of rotating storms and where hail fell. The rotation tracks or hail swath data can be overlaid on high-resolution street maps in Google Earth/Maps to pinpoint areas affected by the hazardous weather.

The WDSS-II system receives data in real-time from the nationwide networks of weather radars, satellites, surface observations and lightning detectors. WDSS-II then processes, analyzes and displays the data in a way that is useful to people who need to diagnose severe weather quickly.

The platform is being used by several local American Red Cross chapters, emergency managers and National Weather Service Forecast Offices for disaster assessment and response.

The April 27 Rotation Tracks file is available here for downloading and overlay on Google Earth:  http://ondemand.nssl.noaa.gov/RotationTrack1440min_20110428-085936.kmz

NWS forecaster Forrest Mitchell ties a parachute to the balloon.

It’s time for yet another podcast of… That Weather Show… brought to you by the NOAA Weather Partners.  I’m Angelyn Kolodziej.

“If it ain’t broke, don’t fix it”.

That saying certainly fits weather balloons.  Today, the NOAA National Weather Service relies on the same principles established over two centuries ago.  Here are the basics: A balloon uses gas to rise to a high altitude.  Attached to the balloon is a data-gathering device.  While rising, it measures things like temperature, pressure, and humidity.  The result is a three-dimensional snapshot of the atmosphere.  This is essential information for weather forecasts and research.  Once the balloon reaches maximum height, it bursts and descends back to Earth.

Preparing the radiosonde

This isn’t to say that things haven’t improved over the years.  When the French pioneered the technology in the late eighteen hundreds, scientists had to actually track down the fallen device to collect data.  This might not seem that bad… except that during the balloon’s rise, it can drift more than a hundred miles away.  You can imagine how difficult it was to find those things.

In the nineteen thirties, a solution arrived.  A radiosonde – equipped with a transmitter – now made it possible to have instant data feedback.

Even with all our advanced technology – weather balloons are still the best tool for the job.  Understanding the atmosphere above is crucial for forecasting the weather below.

Ready to launch!

Today there are nearly nine hundred ballooning stations worldwide – ninety-two by the National Weather Service.  The balloons are typically launched at the same time twice a day.  The data have many uses – from aviation and marine forecasts to climate research.

Call it an “oldie but goodie”… a “classic that never dies”… one things for sure, weather ballooning is here to stay.

Thanks for listening to another podcast of… That Weather Show… brought to you by the NOAA Weather Partners.

A truly remarkable number of wind events did occur in this recent event. In fact, while the number of wind reports across a 24 hour period remain preliminary and will need to be further reviewed by NWS meteorologists in the affected areas, it is likely that in the final analysis, the wind reports numbers alone will far exceed any other severe weather outbreak in the official records of the NWS. However, using wind reports alone can be misleading when attempting to put an event such as this into some meteorological and historical perspective.

The image above is a composite of 24 hours of base reflectivity data, taken approximately every three hours, to show the evolution of the squall line across the southern United States. The line traveled more than 800 miles in about 24 hours with an average speed of something between 30-40 mph. Clearly, surface wind speeds within the intense segments of the line must have been blowing harder to produce such a huge number of reports. However, there have been other recent examples of intense linear convection (squall lines), some moving across this same region of the country, with faster overall system motions.

At left are composites of four damaging wind events from 2009 that had overall system speeds greater than this most recent event. One big difference in these events, when compared with April 4-5, 2011, is that the linear extent of the squall line was more compact. The May 3, 2009 event covered 570 miles in eight hours at an average speed of more than 70 mph and only produced about 165 wind reports. Arguably, this was a more intense and faster-moving squall line than what occurred on April 4-5, 2011, but it was concentrated over a much smaller area.

Probably the one event of the four depicted from 2009 that comes closest in terms of areal extent to the recent outbreak is the February 11, 2009 squall line (upper left). This event produced more than 400 reports and traveled at an estimated forward speed approaching 50 mph. Even with a greater forward speed across some of the same general area of the country as the event on April 4-5, 2011, the total number of wind reports was less than half of those recently reported. This event, coming during the winter months, was in an environment characterized by generally weak instability but incredibly potent dynamics.

These examples serve to illustrate the point that severe weather episodes come in all shapes and sizes and, combined with secular trends in severe weather reporting, increasing population density, and information technologies allowing the rapid transmission of observations, make characterizing these events and placing them in historical perspective very difficult. April 4-5, 2011 was a very “big day” in terms of reports and squall line extent. But, how big a day was it when compared to other “big days”?

The greatest single-day annual wind event totals, for each year since 2005, are summarized in the table below.

The greatest values for any of the event characteristics are highlighted in red font. Please note the numbers for this most recent event remain preliminary, as already mentioned above. While the April 2-3, 2006 event had fewer than 50% of the wind reports of the 2011 event, it ended up with considerably more “significant” wind observations. The Storm Prediction Center (SPC) considers “significant wind” as any gust of 65 knots (75 mph) or greater. The 2006 event, coming at nearly the same time of year, had 38 thunderstorm wind gusts in excess of hurricane force. And, despite encompassing a more concentrated area of the Midwest, this outbreak required the issuance of three more watches from the SPC, and had a lot more warnings associated with it. Most of the fatalities that occurred in April 2006 were associated with tornadoes, not straight-line winds. The injuries from this event far exceed those reported so far for the most recent event.

There are other methods one could use for some of these recent events, including looking at the relatively dense automated observational network where thunderstorms and wind gusts are observed. Given the 1000+ wind reports from April 4-5, 2011 over such an expansive area, one would think several airport observations would record wind gusts in excess of 50 knots, along with thunder. A preliminary investigation into this question shows a total of less than 10 observations had thunder and wind gusts observed at or above 50 knots. There are only three observations on any hour in the 24 hour period that meet severe thunderstorm criteria (thunder with wind gust equal to or greater than 50 knots). When intra-hour special observations are included in this analysis, there are only three additional thunderstorm “PEAK WIND” gusts of 50 knots or greater that can be added to the total. The ratio of thunderstorm observations, to thunderstorm observations with gusts meeting severe criteria (>= 50 knots), and to overall wind damage reports, is another aspect of “big wind” outbreaks that can be used to measure their characteristics and place them into better meteorological perspective. This particular  investigation is very preliminary and any additional information on this approach may be released here on the U.S. Severe Weather Blog.

Ultimately, the most important aspect of these events from an NWS and SPC perspective is that we get the word out to the public that trouble is on the way. The map below shows the extensive nature of the NWS watches and warnings issued on April 4-5, 2001.

Video length: 4:20 min. [cc]

What is dual polarization technology? Why should you care? On this episode of That Weather Show, we answer those questions by using parodies of our favorite commercials.

Hosted by Cat Taylor, 2009 Miss Oklahoma International / Univ. of Oklahoma Meteorology Student.

Attendees enjoyed the event’s many activities and attractions spread throughout the National Weather Center – hourly weather balloon launches with local TV weather personalities, children’s activities, tours of the National Weather Service hallway, meeting the “Weather Friends,” about 40 vehicles entered in the Storm Chaser Car Show and viewing research vehicles involved in the recent VORTEX2 tornado project. The crew from Discovery Channel’s Storm Chasers signed autographs and took pictures with folks alongside their chase vehicle, the DOMINATOR.

More than 100 staff and student volunteers contributed to the event’s success.

Highlights from the Festival:

Schneider has been the science support branch chief at SPC since 1997. The branch is responsible for maintaining SPC’s leadership in science and technology and for supporting its national forecast mission. This includes collaborative scientific research efforts in the NOAA Hazardous Weather Testbed, a facility designed to support collaboration between research scientists and operational weather forecasters on specific topics that are of mutual interest, and accelerate the transition of promising new meteorological insights and technologies into advances in forecasting.

Schneider has spent his entire career at NOAA’s National Weather Service, first working at NCEP’s Environmental Modeling Center and then moving to the Hydrometeorological Prediction Center as its first science and operations officer. He earned his bachelor’s, master’s and Ph.D. degrees in atmospheric science from the University of Wisconsin at Madison.

“I have had a lifelong fascination with severe weather since a series of major tornado outbreaks in 1965 and 1967 near my childhood home in suburban Chicago,” Schneider said. “This fascination continues with every position at the National Weather Service and fuels my focus on improving severe weather warnings for the public.”

Author and co-author of numerous professional publications, Schneider also served as an associate editor of the American Meteorological Society Journal Weather and Forecasting for over a decade. He led the Storm Prediction Center’s efforts to improve severe weather forecasts issued by the National Weather Service and received a Department of Commerce Bronze Medal for his contributions in 2007.

Schneider replaces former SPC director Joseph Schaefer, who retired in January.