Week #5 of EWP2010 wrapped up with continued CASA experimentation.

CASA:

During the week, CASA hosted the following National Weather Service participant:  Steve Nelson (WFO Atlanta, GA).

Steve was joined by CASA participants Ellen Bass, Jerry Brotzge, Kevin Kloesel and Brenda Philips.  During the week, several additional CASA staff and students, including Don Rude, Brendan Hogan, and Cedar League, also were in Oklahoma visiting emergency managers in the field during the real-time events.

The week got off to a fast start with a local tornado outbreak, with no time for training or preparing Steve for what to expect, how to use the WDSS-II system, or the communications protocol with emergency managers.  Monday (May 10) saw a total of at least 12 tornadoes touch down in the region, but with only one confirmed tornado within the CASA testbed.  The one tornado in the CASA domain was on the ground for ~ 10 minutes, but was unique – anticyclonic from a left-moving supercell.  The strong magnitude of the low-level velocity shear from CASA prompted Steve to issue a (in-house) warning on the storm, despite the anticyclonic rotation and unusual location relative to the parent supercell.  The rotation also was observed by KTLX and TDWR, but at a higher elevation.  The tornado was confirmed and classified as an EF-1.  Other tornadic supercells initiated within the testbed, but moved east prior to tornado formation.

Steve spent the remainder of the week reviewing both weaker real-time data as well as a series of case study events.  A strong cold front passed through the testbed at 4am Wed morning (May 12), which spawned at least one area of rotation as detected by CASA radar KCYR.  A small area of damage was reported to the NWS, which coincided with this observed vortex.  Several of the archived cases show similar results from supercell events.  Data from the May 13, 2009 event revealed several areas of rotation by CASA.  The squall line observed April 2, 2010, showed at least one supercell within the line, spawning two strong vortices, each with coincident damage at the ground.  The high spatial and temporal data provided by CASA allow the complete development and evolution of these vortices to be better tracked and warned in advance.

Additional tools, such as 3DVAR and real-time NWP (a.k.a., warn-on-forecast), were run operationally during the real-time events.  For the May 13 event, Steve first observed rotation within the 3DVAR display.  Similarly, the forecast for May 13 allowed Steve much greater insight into what mode of storms to expect.  Likewise, during the May 10 event the real-time NWP forecast predicted long-track supercells, with the location and timing very similar to what was observed.

Steve recognized a number of benefits and some challenges with the collaborative and adaptive radar network design.  The low-level scanning abilities and high space and time resolution provided significant benefits, particularly in observing and warning on strong low-level winds and tornadoes.  The greatest challenge was handling data overload.  CASA data were available on both AWIPS and WDSS-II, and Steve used both systems in real-time.  The primary need moving forward will be the development of visualization tools capable of easily displaying multiple radars and merged products.  The ability to quickly and easily move between products and radars will be critical to using the valuable information available by these new systems.

The CASA experiment has concluded for the spring.

PARISE:

PARISE has concluded its activities in the testbed for the spring.  In several weeks, an end-of-experiment quick summary will be prepared by the PARISE principle scientists.

A LOOK AHEAD:

Beginning 17 May, we will begin the second phase of our spring activities with two new experiments, a) an evaluation of experimental Multiple-Radar/Multiple-Sensor (MRMS) severe weather algorithm products, and b) an evaluation of GOES-R convective initiation and lightning mapping products.

Greg Stumpf, EWP2010 Operations Coordinator

Jerry Brotzge, CASA Scientist

Week #4 of EWP2010 wrapped up with continued CASA experimentation.

CASA:

During the week, CASA hosted the following National Weather Service participant:  Bill Martin (WFO Glasgow, MT).

A lack of severe weather during week #4 once again allowed ample time for careful review of archived case studies. Monday was spent reviewing CASA operations, forecaster-emergency manager communications, and familiarization of CASA visualization and scanning tools.  The remainder of the week was used for reviewing archived events and running through Don Rude’s comparison cases.

Many archived events were reviewed in displaced real-time, allowing for more “true-to-life” operational scenarios.   Several cases were reviewed twice – first with NEXRAD and TDWR data only, and then a second time including NEXRAD, TDWR and CASA and CASA products.   CASA products included 3DVAR and  NWP.   Topics raised throughout the week included emergency manager operations, data overload, multi-radar visualization, multi-sensor products, and NWP (“Warn-on-Forecast”) output.   One important issue going forward is how forecast information can be integrated easily and seamlessly into NWS operations.   Ideally, a data cube including all multi-sensor data will be available that shows real-time 3D analysis (at multiple scales) as well as projections into the future.   Otherwise, data overload could escalate as the number of radars and radar products are added.  As the case studies again showed, the low-level sampling and spatial resolution, as demonstrated by the CASA testbed, highlight many storm details that may be critical for future improvements in our warning capability.

The CASA experiment continues for one more week in the testbed before wrapping up for the spring.

PARISE:

PARISE has concluded its activities in the testbed for the spring.  In several weeks, an end-of-experiment quick summary will be prepared by the PARISE principle scientists.

A LOOK AHEAD:

Beginning 17 May, we will begin the second phase of our spring activities with two new experiments, a) an evaluation of experimental Multiple-Radar/Multiple-Sensor (MRMS) severe weather algorithm products, and b) an evaluation of GOES-R convective initiation and lightning mapping products.

Greg Stumpf, EWP2010 Operations Coordinator

Jerry Brotzge, CASA Scientist

For the CASA Hazardous Weather Testbed during the week of April 19th – 23rd the emphasis was on continuing to improve our procedures and process while maintaining readiness for possible weather events. As it turned out we did have interesting weather enter the IP1 testbed area on the night of April 22nd – 23rd, but only marginally severe thunderstorms.  No significant circulations were observed.  We added some new tools to our repertoire including a screen capture to Twitter using a Twitpic procedure on the WDSII console (technical issues prevented it from working on the AWIPS terminal). We also built a blogging tool accessible at http://casaradar.blogspot.com that captures information on all emails sent to response@casa.umass.edu (such as forecasts) as well as all tweets sent out by the casaradar and casaalert accounts. The blogger can also be sent email which will post at blogger@casaradar.com.  The CASA HWT Protocols document was updated based on these new tools and procedures as well as experience gained during the previous week of the HWT. On Tuesday we verified all the functionality during a test run using the April 2nd case study.  Wednesday had the potential for storms to enter the testbed after 8PM so we worked on further refinements to tools and procedures during the afternoon. The weather didn’t cooperate so we called it quits around 10PM that day.

On Thursday while we waited for the weather to develop (there were possible testbed incursions in early evening that did not materialize) Don and Steve ran through one of Don’s cases. During the evening hours, Steve ran both the WDSII and AWIPS terminals with Don’s help on setting up and looking at some of the wind products (3DVar, dual-dopppler) and “warn-on-forecast” NWP on web browsers on one monitor of the WDSII terminal. Rachel was the communicator on NWSchat, and monitored spotter locations (including Cedar who was out chasing with EM James Nimrod), and took snapshots of the WDSII and also from Weatherscope for inclusion on Twitter using Twitpic. Westy was monitoring all the tools and CASA system status – everything important went smoothly, although we did lose wireless connectivity to half the laptops (thankfully not the communicator one) around midnight that was fixed by Don’s expert network hacking skills. Despite the storm never really producing anything resembling a tornado or interesting circulation or winds we stuck with it until almost 4AM. On Friday we debriefed and recovered. Don and Steve ran through more of Don’s case.

We appreciate all the volunteer work done by OU folks during the week.

Timeline

Monday: Revised HWT procedures for the week.
Tuesday: Continued work on HWT procedures; worked on new functionality for communicator and technical issues with hardware and software; built CASA blog, with connections to two CASA twitter accounts and an email portal at blogger@casaradar.com Ran through CASA Case Study with Steve and Rachel as communicator.
Wednesday: Continued work on new functionality for communicator. On standby from 3PM on in case there was weather in the testbed. Nothing happened.
Thursday: Don and Steve worked on Don’s case in the early evening. Storm event started around 10PM and ended at 4AM.
Friday: Debrief at noon, Don and Steve continued working on Don’s case.

People
CASA personell: David Westbrook (M-F), Rachel Butterworth (T-F), Brendan Hogan (M-W), Don Rude (Th- Fri), Cedar League (Th-F), Brenda Phillips (M), Ellen Bass (T), Jerry Brotzge (OU)
Forecaster: Steve Hodanish, WFO Pueblo CO (Steve.Hodanish@noaa.gov)
Additional OU support from: Patrick Marsh (NSSL), Greg Stumpf (MDL), Darrel Kingfield (WDTB)

Jerry Brotzge, Univ., Oklahoma CASA Project Scientist

Week #2  of EWP2010 wrapped up with continued PARISE and CASA experimentation.  During the week, we hosted the following National Weather Service participants:

CASA: Steve Hodanish (WFO Pueblo, CO)
PARISE: Doug Cain (WFO Midland/Odessa, TX), John Cockrell (WFO Amarillo, TX), Andrea Lammers (WFO Louisville, KY), Brian Montgomery (WFO Albany, NY)

We managed to get some real-time weather in the Central Oklahoma domain last week, but it was non-severe and occurred overnight (2-3am).  CASA data collection was had by their participants, and more information will be provided in their project weekly summary.

With a new set of four NWS forecasters, the PARISE experiment repeated their exercise from Week 1.  As in Week 1, there were no real-time PAR data collection opportunities, so all exercises were conducted with archive case data sets.

Greg Stumpf, EWP2010 Operations Coordinator

The goal of the 2010 PARISE is to gain an understanding of the impact of temporal sampling on warning decision making, and warning lead time. During the first week, 13–16 April 2010, four NWS forecasters from the Southern Region, Eastern Region, and Central Region helped us address this goal by applying their warning decision expertise to five different playback cases sampled by the National Weather Radar Testbed Phased Array Radar (NWRT PAR). The forecasters worked each case in teams of two.

Before each case, forecasters developed situational awareness of the forcing mechanisms and near-storm environment in which the storms developed. This situational awareness allowed them to form a conceptual model of the storm type and severe weather threats they anticipated. Then they applied their warning decision expertise to interrogate the NWRT PAR data using the Warning Decision Support System – Integrated Information, and to issue warnings using a WarnGen tool similar to the one in AWIPS.  After each case, the teams discussed their warning decision process with a PAR scientist.  The case culminated with an overview of any severe weather that occurred, so that forecasters could self-evaluate their warning process.

The experiment wrapped up with a group discussion on participant’s experiences with NWRT PAR data and the PARISE as a whole. Forecasters said that they had a good experience and will encourage others at their office to participate next year. They enjoyed getting to work with rapid update data and experiencing how those data may change their current warning decision process. Forecasters also enjoyed getting to work with researchers and people from other NWSFOs.

Following analysis of the data collected during PARISE 2010, findings will be shared initially via conference papers in Fall 2010.

Pamela Heinselman, NSSL, PARISE Project Scientist

A primary goal for CASA during 2010 is to document the improvement in warning operations through the use of enhanced forecaster-emergency management communications.  The use of NWS personnel in the HWT allows us to test and refine how best to utilize CASA’s high-spatial (100 m) and temporal (1-minute) data, in coordination with field emergency managers (EMs).  Several particular areas of interest include the concepts of data overload, multi-sensor products, and the development of warn-on-forecast products and display.

The lack of severe weather in Central Oklahoma during Week #1 allowed CASA to refine its warning and communications operations.  Les Lemon (WDTB) spent much of the week with CASA PIs Brenda Philips and Ellen Bass refining the communication technologies to be used between the forecaster and EM.  Twitter and NWS Chat will be the primary means for communication, with additional use of Skype by some EMs and spotters.  Les spent Monday getting trained, learning about the latest products from CASA (e.g., new NWP forecasts available every 10 minutes!), and refined products (real-time 3DVAR analysis).  Tuesday through Thursday was spent reviewing and revising the interaction among the CASA forecasters and EMs.  Several EMs and spotters visited the HWT and practiced with various communication technologies.  Les spent Wednesday morning with Jerry Brotzge, Keith Brewster, Brenda, and Ellen in discussions on ways to improve the presentation of output from the real-time forecasts – in essence, how do we present “Warn-on-Forecast” information to forecasters already overwhelmed with data?   Friday ended with precipitation in the HWT – an opportunity to review CASA products one last time…but now with echoes!

Jerry Botzge, Univ. Oklahoma, EWP2010 CASA Scientist

In a considerably ironic turn of events, we wrapped up the 2009 EWP merely (~10) hours before an EF1 tornado hit Norman, about 2-3 miles from the NWC…

As for the weekly summary, our forecasters for the week were:

Bill Ward (NWS Pacific Region HQ, Honolulu, HI)
Daniel Nietfeld (WFO Omaha, NE)
Gail Hartfield (WFO Raleigh, NC)
Steve Kieghton (WFO Blacksburg, VA)
Dan Miller (WFO Duluth, MN) [Observer]

We spent the early part of the week running realtime MR/MS and LMA IOPs, and the last couple of days running realtime and archive cases for PAR and CASA, as well as an LMA archive case.  Summary comments follow:

PAR

Used vertical slice cross-section.

Other circulations to the NW of the main circulation were somewhat confusing. [20090513 Stanley Draper Tornado]

Didn’t do much looping, and now that we are looking at it during the debrief, it looks good.

Would be nice to have a feature following cross-section.

Used CAPPI to help pick out storms that needed warnings.

Put CAPPI just above altitude of cap/lid, and when echo showed up, gave indication that storm broke the cap.

Could see evoluation of MARC signature and then surface divergence.

CASA

How would they use this in operations? Have the CASA data of multiple radars as a passive display, and use the 88D for the deep interrogation.

May need a separate person to watch the CASA radars, and communicate to the warning forecaster

Would be nice too have real-time dual-Doppler wind analysis, instead of the 10-min old 3DVAR. Real-time could also to retrieval to get omega field.

The sector wedges were not always centered on the correct spot during our real-time event on Wednesday.

Works better with isolated storms, but not lines of storms. It is trying to satisfy many users, and NWS is only one of those. Need data for model assimilation, etc.

Jumping around from radar to radar may cause folks to miss something important.

QLCS case on Wednesday – these are the kinds of cases that can hurt verification numbers – they are such quick spin-ups and are tiny. OAX realizes that the 5-minu updates of 88D are not sufficient. Time flew by and couldn’t believe how much time had gone by, but did not feel fatigued. Feels that once we can adjust to the rapid time evolution, we will appreciate this.

This group really feels that they will adjust to the rapid refresh and data “overload”! Has faith that WDTB will provide good training to deal with this.

LMA

Regarding the 20090210 archive…

Was nice to see spike in VILMA just before circulation tighten up. Tornado followed the peak. “Lightning jump”

Helpful additional tool to aid confidence.

10k GLM proxy was quite an adjustment. Prefer high-res.

Could be useful for investigating tropical tornadoes, sea-breeze convection, flash flood situations with warm rain processes with little CG – is there IC activity?

Very beneficial with winter storm convection, thundersnow, to help with snow rates, etc.

Would like to see these data sets with dual-pol data as well.

MR/MS

Forecasters, though warmed up to products like MESH, still feel an understandable need to to “calibrate” the product for their own uses.

There were concerns about the apparent discrepancy between some of the MR/MS “height of” products as compared to the AWIPS readouts.  More often than not, an additional (temporal) update would bring the two datasets into better agreement.

Overall Experience

Though we didn’t get to discuss the overall experience from the group, we did ge tsome good feedback on te idea of Decision Support Tools…

Kurt [Hondl] asks what kind of decision support tools could be used that has all these data sets available…

Would have to be pretty intelligent and robust, and not too many alarms at once.

But still would feel most comfortable going to the base data.

Will be a screen real-estate issue.

What’s the most effective way to visualize the base data. Plan views, cross-sections, color tables, isosurfaces, etc.

DSS tool should have the capability for users to set up their own “dashboard”.

The DSS tool should be tied to providing procedure suggestions.

Is this the SCAN model?

SCAN failed because the underlying algorithms fail.  Also, too many false alarms, hard to congifure and shut off alarms.

Kevin Manross (EWP Weekly Coordinator, 8-12 June 2009)

On Friday morning, the group got together to discuss June 4 activities and overall thoughts from their week in the HWT.

• want to transition from RPG-only algorithms to including NSE data into any radar algorithms
• If looking at 1 min radar scans…hard to keep tabs on changes in 0-1 km wind shear for example, or any other NSE parameter for that matter.  Would like to see an envionmental algorithm paired or integrated into radar algorithms
• The NSE data needs to be reliable and accurate, otherwise it would be detrimental

PUB/BOU/CYS IOP:

• Near end of IOP a storm moved right over the KCYS radar, MESH did it’s job using multiple radars to fill in the cone of silence.  However, MESH seemed to be overestimating compared to the reports that SHAVE were getting (1.00 inch vs. 1.7-1.9 inches)
• MESH tracks showed where storm had been going and was consistent, allowing the warning polygon to be oriented the right way

MR/MS Discussion

• MR/MS doesn’t account for refraction properties yet, though a QC check does eliminate much of the AP
• Mid-level rotation tracks were useful to help find a consistent track of the rotational signatures.  They also help confirm you have a supercell when the tracks are consistent
• Like examining the trends in -20C reflectivity
• Lots of the gridded products are redundant, containing the same type of information.  Have to be careful not to get tunnel vision when using all these gridded products. Redundancy also helps you transistion from products you are use to using to the new products and grow expertise and confidence.
• Be comfortable with the gridded products in order to properly integrate them into the warning decision process
• Plan view plot of scan-to-scan change would be useful…like change in MESH from scan-to-scan.  They all thought that trends were every bit as important as the max values reported.
• Google map displays:  really want those in their local offices

LMA

• impressive, never used the data before but very useful in areas were radar data may be lacking
• need research to see if LMA data vs. cloud to ground data in the early stages of storm formation means anything
• LMA is an average, then AWIPS smooths it further, thus losing information
• They like the high res appearence, how it is similar to radar reflectivity.
• Using it to help forecast when a storm first becomes severe, at the very least use it to get some led time on rapid intensification
• #1 killer in FL is lightning…Pete hopes that there is a focus on provided an improvment on service for lightning threat

CASA

• Need low-level altitude resolution that CASA provides.  This is crucial information the 88D can’t always provide.  This is a “big positive”
• A consideration with CASA is that it provides rapid scan updates that could give a few extra minutes of lead time, but won’t be more than a few minutes.  Selling point will not be verification scores but the one devastating tornado you catch that formed well below the 88D’s lowest scan
• Will see lots of signatures on CASA that haven’t been seen before and don’t currently know how to interpret.  Will be steep learning curve for these new/different signatures
• Used reflectivity quite a bit to infer presence of a tornado becuase with the high resolution in time and space they were able to see the “do-nut” signature common with tornadoes
• Will see a lot more low-level rotational signatures, do you warn on every little 30 sec dust whirl that shows up on CASA that you would never see with the 88D?  Obviously if each one is an actual tornado then yes, but gray area if they are very short lived and weak.  Could see a lot more warnings come out.
• 1 min data might be more tempting to hold off on a warning, waiting one more scan, then waiting one more scan.  Can ride the fence on warn/don’t warn a little longer.  Not sure if this might be a real impact, will need to do some research on this, maybe on the WES.
• Big learning curve and training will be needed to grow accustomed to 1 min updates

PAR

• Provided more rapid updates but didn’t have any other advantages, since resolution is about the same if not worse at the edges of the scan sector, and also the same elevation angles.
• Pete will take PAR data capabilities back to JAX with lots of excitement because it helps with the low-topped, weak signature supercells in tropical environments.  PAR allows for detection and tracking of rapidly evolving weakconvergent and rotational signatures.  PAR should also help with pulse-type storms because of rapid evolution, getting early detection of cores aloft that the 88D might miss.

Liz Quoetone and Paul Schlatter (EWP Weekly Coordinators, 1-5 June 2009)

2009 Spring Season – Week 4 – May 18-22

This was my second opportunity in as many years to serve as an Experimental Warning Program Weekly Coordinator. I would like to thank all of our National Severe Storms Laboratory facilitators and support staff, as well as the project scientists for CASA, PAR, LMA, and MRMS. It is not easy to share two teams of meteorologist evaluators across four projects – some using real-time data in rapidly evolving time windows. All involved approached the week with common goals, however, to pursue as much data as possible and draw upon our four evaluators’ experience and feedback. Everyone is motivated by a clear desire to improve the severe weather warning process.

Our week 4 visitors brought with them a wealth of experience gained from years in the National Weather Service. They were Les Lemon, Research Associate at the NWS Warning Decision Training Branch, Matthew Kramar, Senior Forecaster at NWSFO Sterling, Virginia, Rob Handel, Senior Forecaster at NWSFO Peachtree City/Atlanta, Georgia, and Mike Vescio, Meteorologist-in-Charge at NWSFO Pendleton, Oregon.

It seems (and at least one dataset – significant tornadoes in the NWSFO Norman, OK, forecast area – shows) that a relative minimum in severe weather often occurs in mid May, surrounded by more active periods at the beginning and end of the month. But no one could have anticipated the degree to which this lull would affect the entire continental United States in 2009. We missed an opportunity to study a small area of severe storms that occurred in Mike’s home County Warning Area of northeast Oregon on Monday, instead deciding to push through the seminars and training on our four project areas. We attempted (unsuccessfully) real time operations for the MRMS project in the Intermountain West on Tuesday, and with some rotating storms in Florida on Thursday. Our week was made, however, by a severe thunderstorm event that occurred in western Nebraska on Wednesday, and fell nicely into the 4-9 pm time frame.

We spent the rest of our time viewing archive datasets across CASA, PAR, and LMA. This set of forecasters impressed me with their attention to base data and their ability to place much of their conversation in the context of proven methodologies and peer-reviewed research. Many of their recommendations for display methods and product definitions went into the real time blog entries. Still more of their feedback went directly to the project scientists during archive case studies. Greg Stumpf and I tried to pull more of that feedback out of them during the weekly debrief on Friday, May 22^nd. A summary of that discussion is included below.

CASA Wind Prediction Exercise

Background: In addition to archive events in which forecasters simulate warning operations, CASA scientists are conducting an experiment in which forecasters – some given CASA and WSR-88D data and some given only WSR-88D data – are asked to estimate surface wind speeds. Oklahoma Mesonet data are used to verify the predictions.

Mike

We Need larger data window in time…leading up to the time at which we are asked to make a prediction (trends important)

Rob

There were numerous amorphous looking cells. I was looking for tighter refl gradients/more vigorous storms for wind.

Matthew

Looking for outflow boundaries/cold pools to undercut and decrease the wind potential

Mike

Knocking down wind speeds based on 88D experience. Always seems to run high. CASA was even higher.

Les

Should we warn for possible gusts, or an organized event?

Rob

With WSR-88D time scales, we are usually waiting for data… now it is always coming in very quickly with CASA. Do we really need the sector scan strategy? We like to know what to expect and to be comfortable knowing we will see the full picture with each scan

Rob/Mike

Willing to give up faster updates to get the full sector scans.

CASA Scientist Don Rule

The trade-off to eliminating sector scans is poorer performance of 3D VAR

Mike

Don’t put much effort into getting volume scans less than 1 minute. That should be sufficient.

Rob/Les

At what point is there diminishing return?

Greg

Live! I want the Data to eventually be a live movie loop…refresh every second or less.

Group

Lots of transient features, many are false

Greg

But some are real! Draper Lake tornado on 5/13/09, only had one 40 second volume scan of a TVS!

Note: Out of 27 forecasters who’ve gone through the experiment, best performer’s average error was + 5.5 knots. Worst performer + 17 kts (met grad student w/o operational experience).

Generally, those given CASA data would warn while those given only 88D data would not warn

When there are a lot of small radars, chances of getting the right viewing angle for radial velocity is much greater.

Other CASA Discussion

5/13/09 Case: Not just a tornado case, but a good sig wind case (RFD).

Two chasers who were in middle of Anadarko came in to look at data. Estimated at 120 mph (Greg: 2/3!), and a second surge. Tornado went to their SE. Since OEC power grid went down, sirens didn’t work. After generator, sirens went off 10 minutes late.

Multi-Doppler 3DVAR, compared to mesonet winds, very useful.

Classic case of occlusion, new meso did not produce tornado.

120 mph est., Doppler got 130mph (60-70 m.s).

When we see this amount of data, visualization capabilities become more critical, decision support. Data refreshes when you come off a data source, and the picture is different.

Les

same for all the rapid-refresh data sources.

Matthew

Display is hindering, not the immense quantity of data. Big take-away!

The eventual concept is that the user can add input to the MC&C to “override” some of the automation.

Patrick

Scale issues – looking at 88D data, sometime you don’t look at the bigger picture (mesoscale). Same with CASA/PAR – may lose track of “88D scale” (storm scale). May take complete retooling of warning ops if we go to data at these scales.  From an operational perspective there is only so much you can process in real-time.

Les

Need some algorithms to process some of the data, but still need person in the loop.

Greg

Need to study the precursors and their differences between false and true signatures.

Lightning Mapping Array Discussion

Forecasters looked at 5/15/09 squall line.

First time they looked at 3D visualization of LMA data. Dots. Isosurfaces.

Mike

2D VILMA product seems most operationally practical. This could help you prioritize storms. 3D is “cool” though.

Matthew

Like the 3D information. I am used to 3D with GR Analyst.

Need a team of two. What can I see in 3D that I can’t get out of VILMA 2D product? Combined isosurfaces of dBZ and LMA density (Patrick’s Note: Not sure if this was said because Matt did this, or If he would like to see that capability).

Mike/Les

We need to learn what the lightning signatures are, and how they relate to severe reports. Les found from this one case May 15, 2009 – that lightning max density matched the location of strongest winds

Les

Training is also needed.

Group

Trends were very valuable for LMA data using WDSSII.

Jim Wilson

Trends only work if you couple the information with knowledge of the NSE.

Early trends broke more often. WDSSII version is more robust.

GLM proxy: Need to use it without the ground-based data to do a fair assessment.

Phased Array Radar (PAR) Discussion

Early May 2009 Storm… Isolated Supercell at Foss Reservoir (long range from 88Ds and PAR):

One group compared PAR to KTLX, one compared PAR to KFDR. The latter group gravitated toward the KFDR data due to the better spatial resolution, traded-off with the better time resolution.

Matthew

Very good clarity of data… spatially and temporally.

Oversampling… we like that.

Reflectivity seemed much lower on PAR than 88D.

That has a big effect on warning ops and Could make a difference in precip rates.

(Note: This is a known problem… vertical polarized and not as sensitive. Next step is to make PAR dual pol to address this problem.)

Patrick

In what events/environments is the PAR best suited?

Matthew

Events near the radar

Rob

Shorter Lifespan storms… rapid evolution

Or smaller scale features within a long lived storm

Adam

Was the vertical detail sufficient?

Les

For TS Erin case, all we needed was low level data. Give us even faster updates at low levels. Give us sub 0.5 degree tilts

5/13/09 OKC (Draper Lake) storm:

Patrick

In NWSFO Warning Operations… The initial Tornado Warning for Oklahoma/Cleveland Counties was based on fact that TDWR signature of convergent rotational RFD was minimally undercut by outflow. Then TVS developed.

8/19/07 T. S. Erin mini supercells:

Group

Without PAR, wouldn’t have issued as many warnings. Felt we overwarned with the PAR data.

7/16/06 downburst case done by two of the four forecasters.

Group

Mostly looking at rapid-evolution of descending cores.

Multi Radar / Multi Sensor Discussion

Real Time Data at http://wgserver.nssl.noaa.gov

Kevin

What other products would you like to see?

Matthew

User-definable interface for height of dbz products

Choose your dbz value and temperature level, etc.

Excerpts from the live blog during our MRMS real-time IOP on May 20:

Matthew and Mike note that for MESH the associated color tables are slightly different between Google Earth and AWIPS.  These need to be the same to avoid confusion about product times, and help the forecasters to “trust” the data on both platforms.

Rob has been looking at the Legacy Hail Algorithm on AWIPS to compare with the experimental products.  He discovered that the locally run Legacy Algorithm is not synced to updated environmental data.

The radar presentation had become quite impressive around 8 pm CDT. MESH indicated 2.88 inch diameter hail.  Les argued for baseball size hail in the warning.  Arthur and Patrick argued for something closer to 2 inch, based on reports (phone calls from the HWT and Local Storm Reports from CYS and LBF) throughout the evening that have been consistently lower than the MESH values. The reports have also indicated very heavy rain.  The storm does not have a very impressive mid level mesocyclone, and Les agreed that was a good reason to undercut MESH in the warning. Rob issued the warning, mentioning golf balls. The largest hail reported that day in this low population area was 1 inch.

All of this week’s forecasters advocate intense use of base data in warning decision making.  Mike says “We are overloaded with derived radar products. Just give me the base data, and a better understanding of the environment (to improve warning decision making).”  Others agree that environmental data is key to warning decision making, but they also point out that there may be some tasks that algorithms can perform very well, thus freeing the human forecaster to tackle other problems.  The group also discussed certain scenarios in which algorithms can aide the forecaster during low staffing or broad geographical outbreaks.

Les and Rob particularly like the LMA and lightning trend data, as it is “Base data of a different kind.”  The forecasters, as a whole, liked the trend graphs for all types of data.  That was the most useful function of the data in Google Earth.

The group noted several areas, however, where the Google Earth data needs improving.  There is no time stamp, images are smoothed, and there is no cursor readout.  They would like the color tables to be synced to the respective products with which they were intended to be used, rather than requiring the forecaster to click on a product and then click on an appropriate color curve.  In its current state, forecasters feel the images in Google Earth are better suited to verification efforts by mapping MESH and rotation tracks to GIS data, than they are suited to warning decision making.

HWT Feedback

Mike

You are trying to run AWIPS because that’s what we have in the field, but the computational hurdles associated with AWIPS hindered real-time IOPs this week. Do we need that in this experimental environment?

Travis

Do you like the simulated warning ops, or the free-style discussion?

Group

We like both. Mike, though, prefers warning IOPs

Matthew

Good to do warning ops and then go back through it in a post-mortem

Google Earth:

Will there be more functionality in Google Earth? Add time of image on screen? Cursor readout?

Can do some stuff with the w2 GE plugin. Queries the server to get a data readout. Can draw a line to build a cross-section. Areal alarms if a parameter reaches a threshold.

http://wgserver.nssl.noaa.gov

Data Issues and Recommendations:

Need Near Storm Environment grids in Google Earth (and AWIPS2).

Consider the color curves so they match in all places – (AWIPS, WDSSII, GE).

Would like some sharp cutoffs at some of the values (catch forecaster’s attention rather than requiring them to sample the data all the time while juggling multiple data sets).

Recommend 60 dBZ, 62 dBZ Echo Tops

User-definable on-demand queriable interface for products. Should be a requirement before MRMS concept is introduced in AWIPS2.

Lot of the products geared toward up draft strength and hail.

Convergence/divergence products for wind, precursors for tornadoes too?

Need lots of 3D.

Need better interface to choose which radar to look at for a multi-radar display.

AWIPS was problematic this week, did we need it? Could we issue warnings in WDSSII?

Future HWT Operations:

Expand the training. Too much information to cram into the Monday that people arrive. Split the training across multiple days.

Were four projects too much stressed our time?

Most of the value is in the discussion…regardless of number of cases accomplished. (e.g., GOES-R – had a 1 hour discussion with them. Should be more next year.)

Need more than one week. Is 2-week stint ok? Individual forecasters would get to perform more case studies and IOPs. Overlap incoming with outgoing forecasters each week. What kind of shifts? If they are in town for two weeks, could people cover some night and weekend events? But we’d need more staff!

Random “out of season” HWT idea: Use collaboration tools, and run an IOP virtually using volunteer X-shift forecasters? That way, we can get more forecasters looking at products in real-time. How could we do this?

Approach to Case Studies:

Lot of cases were the same from the different platforms. How did that affect the investigation?

Didn’t hurt unless you’re not supposed to know what happened.

Amount of Near Storm Environment data available to forecasters prior to looking at archive data was increased in 2009… yet this set of forecasters wants MORE! Near Storm Environment Data.

Need something like SPC mesoanalysis grids in WDSSII, AWIPS, during spin-up.

Weather and Society * Integrated Studies (WAS*IS):

On May 21, CASA invited McClain County, OK, Emergency Manager, Ed Craven, to the HWT. He was very excited at the opportunity to participate and view data. Later the same day, Two chasers, one an emergency manager and one a former television meteorologist and aspiring emergency manager, who had a close encounter with a nighttime tornado that occurred in the CASA network, also visited the HWT to view data and provide ground truth.

Miscellaneous Comments:

Nice to have the interaction between the researchers and forecasters.

Lots of kudos were given to our weekly coordinator.

Patrick Burke (EWP Weekly Coordinator, 18-22 May 2009)