Warn-on-Forecast real-time 3DVAR in the Hazardous Weather Testbed

Travis Smith, Jidong Gao, Kristin Calhoun, Darrel Kingfield, Chenghao Fu, David Stensrud, Greg Stumpf & a cast of dozens

NSSL / CIMMS

Warn-on-Forecast real-time 3DVAR in

the Hazardous Weather Testbed

OverviewInitial demonstration of real-time data assimilation ability to NWS forecasters. (2010-2012)Simulated warning operations (2011-2012)Comparison of 3DVAR data to single-radar and MR/MS severe weather algorithms.

EWP 2012 Spring Experiment

Timeline5 weeks of real-time operations4-6 visiting forecasters per week (28 total)

• Product training prior to arrival• Leverage NWS Weather Event Simulator (WES)• New this year

Monday: 1pm – 9pm• EWP Orientation and real-time operations

Tuesday-Thursday: 8-hour flex shift• Start-time dependent on yesterday’s forecast• Ops start:12pm – 3pm • Ops end: 8pm – 11pm

Friday: 9am – 1pm• Debrief, discussion, and NWS/partners webinar

Overview

Training

Schedule

Virtual WES technology and training gave participants

exposure to products offsite

This allowed Monday to be an operations day, maximizing time

for forecaster feedback

New In 2012: AWIPS-2NWS Advanced Weather Interactive Processing System 2 (AWIPS-2) is the next generation operational forecasting platform

Provides a familiar environment for the forecasters to evaluate the datasets and issue warnings via WarnGen

Domain Manager forSubsetting Experimental

Datasets

10 Floating Radar ProductGenerators for Level-III

Data Generation

Flexible Environment AllowingAny WFO to be Used in Operations

Additional Features:

Some available products (AWIPS2)

Max Updraft

Max Divergence above 8km

Simulated Reflectivity

3D Wind field (barbs, streamlines, color fill)

Some available products (AWIPS2)

0-3 km Max Vorticity

Updraft Helicity

Time accumulations (tracks) of Maximum Vorticity, Updraft Helicity, and Updraft Speed

Real-time 3DVAR supercells 2010-2012

• Automated tracking / data mining (Lakshmanan et al)

• Max 3-7km vertical vorticity > 0.01 s-1

• Lifetime 60 minutes or more

218 total85 w/ tornado(s)176 w/ other report

Number of radars used in analysis

Radars within 230 km of an analyzed storm cell

Storm distribution by range to nearest radar

5-minute time steps

Colman Co, TX: 2250 UTC, 11 June 2012

Max Updraft + 1 km winds Storm-top Divergence

Updraft HelicityMR/MS Hail Size (MESH)

Colman Co, TX: 2255 UTC, 11 June 2012

Max Updraft + 1 km winds Storm-top Divergence

Updraft HelicityMR/MS Hail Size (MESH)

Colman Co, TX: 2300 UTC, 11 June 2012

Max Updraft + 1 km winds Storm-top Divergence

Updraft HelicityMR/MS Hail Size (MESH)

Max Updraft Speed versus MR/MS hail size

estimate

All cases: R = 0.39 w/95% confidence interval of +/- 0.05

Max updraft speedW

(ms-

1 )

Vorticity versus single-radar azimuthal shear

All cases: R = 0.75w/ 95% confidence interval of +/- 0.02.

Updraft Helicity Distribution

Updraft Helicity Distribution

Receiving Feedback

Surveys

Live-Blogging

Forecasters can provide their pre-warning decision

making thoughts and images in real-time

Forecasters providing feedback on the

strengths/weaknesses of the products

Dedicated face-to-face time between forecasters

and developers on the evaluated products

Present summary of results to a wide audience

Weekly debriefing and WDTB webinar

Favorite products:

Updraft intensity Vertical VorticityStorm-top divergenceUpdraft HelicityUseful when “trying to diagnose a large number of storms” and “sitting on the fence” (about issuing a warning)

Forecaster Feedback

Forecaster Feedback

“highlighted the most intense areas of the storm” provided “information on cycling mesocylones”

Favorite products:

Updraft intensity Vertical VorticityStorm-top divergenceUpdraft Helicity

More “efficient to view than existing algorithms” to diagnosis storm intensity and rotation

Forecaster Feedback

Favorite products:

Updraft intensity Vertical VorticityStorm-top divergenceUpdraft Helicity

Real-time data Issues:

Data Latency (approx 5 min)

Distance from Radar (lack of low-level input)

Bad data quality leads to bad 3DVARside lobe contamination, improper

dealiasing

Forecaster Feedback

Other related work“Virtual Volume Scan” radar data to put input data on the same timing as 3DVAR processing.

Improved radar QC

Online resources3DVAR real-time and archive images:• http://tiny.cc/3DVAREWP web site:• http://ewp.nssl.noaa.govEWP Blog:• https://secure.nssl.noaa.gov/projects/ewp/bl

og/

Archived WDTB webinars available:• http://www.wdtb.noaa.gov

/resources/HWT-EWP/