High resolution radar data and products over the Continental United States - PowerPoint PPT Presentation

High resolution radar data and products over the Continental United States

Valliappa.Lakshmanan@noaa.gov

National Severe Storms Laboratory

Norman OK, USA

http://www.wdssii.org/

lakshman@ou.edu

• Products:
• Gridded hail products
• Reflectivity at constant temperature levels and layer averages
• Low-level and mid-level shear and rotation tracks
• Short-term forecast fields
• Lightning Density
• More …
• Spatial Resolution:
• 0.01 deg x 0.01 deg [x 1km] resolution
• Approximately 1km x 1km throughout Continental United States.
• 1km in height
• Temporal resolution:
• 2D reflectivity mosaics every 2 minutes
• 3D and derived products every 5 minutes

lakshman@ou.edu

• The process for creating 2D composites:
• Ingest Level-II radar data tilt by tilt
• QC reflectivity data (Lak06, JAM, review)
• Create virtual volume composites
• Merge composites from all the CONUS radars (Lak06, WF, accepted)
• 2nd level of QC -- using satellite and surface temperature data.

lakshman@ou.edu

• In a traditional composite,
• Process volume-by-volume.
• Take maximum of all tilts.
• Need to wait for end of volume.
• In a virtual volume composite:
• Process tilt-by-tilt.
• Keep a running volume.
• Replace older data each time.
• Take maximum of most current tilts.
• No need to wait for end of volume scan.
• A virtual volume provides more timely data.

at19.5

at0.5

lakshman@ou.edu

• On a single-radar product, users may:
• want to see clear-air returns.
• tolerate more clutter
• tolerate test patterns, etc.
• On a multi-radar product, clutter and clear-air returns are distracting.

lakshman@ou.edu

raw

With QC’ed composites

• Left: What we would get if directly combined raw (virtual volume) reflectivity composite data
• Clear-air return, sun strobes, test patterns
• Right: combining QCed virtual volume reflectivity composite
• The QC is performed radar-by-radar
• Takes into account terrain, texture and vertical structure.

lakshman@ou.edu

• The radar QC is conservative
• Doesn’t always remove non-precipitation echo
• Especially if it is biological i.e. moving.
• A second level of QC looks at satellite and surface temperature and retains echo where there is likely to be clouds.

Bad data (bloom)

No clouds

lakshman@ou.edu

• The 2D radar mosaic is created every 2 minutes at 1km resolution.
• Converted to Grib2 and sent to the SPC.
• Put on the Internet:
• Snapshots with map background
• Converted to Geotiff
• Loadable with Google Earth or any GIS software.
• Google Earth does real-time loading
• Talk in IIPS on Tuesday
• http://wdssii.nssl.noaa.gov
• Not 24x7
• The software is licensed by some private companies
• They run it on their own machines.
• They take care of 24x7 reliability.

lakshman@ou.edu

• The 2D composite is cheap to create
• 5 dual-Xeon machines with 6 GB RAM
• But always provides an underestimate of true values.
• Need to compute in 3D
• Height of dBZ value important!
• Can incorporate NSE information by height
• A lot more products!
• The 3D products need:
• 5 dual-Xeon with 6 GB RAM
• 2 dual-Xeon with 16 GB RAM
• 64-bit architecture

composite from 2D: 45 dBZ

composite from 3D: 50 dBZ

lakshman@ou.edu

• Not just reflectivity.
• Compute shear (Smith05) and low-level shear.
• Process lightning

lakshman@ou.edu

• Combine QC’ed reflectivity in 3D
• Combine AzShear in 3D
• Compute hail diagnosis and layer averages.
• Compute storm motion from composite.
• Use it to advect storms for short-term forecast.

lakshman@ou.edu

• Extracted from the real-time generation on Jan. 11, 2006
• The day I created this presentation!
• We haven’t run the CONUS system in Spring yet, so the severe weather products may be underwhelming.

lakshman@ou.edu

Composite from 2D

Composite from 3D

Which radars?

Height of Max Ref

lakshman@ou.edu

30 minute rotation tracks

Azimuthal shear 0-3km MSL

lakshman@ou.edu

Also:

Probability of Severe Hail

Maximum Expected Hail Size

VIL_Density

VIL_of_the_day

Other echo top dBZ levels

Reflectivity at temp. levels

VIL

Convection

Echo top (18 dBZ)

lakshman@ou.edu

Reflectivity at T=0

Clusters

Southward motion

Reflectivity at T=30 (forecast)

lakshman@ou.edu

Instantaneous precip rate

Ref closest to ground

• Just the 88D algorithm on CONUS
• Uses hybrid scan reflectivity
• Convective/stratiform segregration based on presence of hail
• 88D Z/R relationships.
• Not multi-sensor
• QPESUMS-II under development at NSSL.

2hr precip accum

lakshman@ou.edu

• The 3D products are created every 5 minutes
• 1km resolution (0.01deg x 0.01deg x 1km)
• Converted to Grib2 and sent to the SPC.
• Put on the Internet (not all of them):
• Snapshots with map background
• Converted to Geotiff
• Loadable with Google Earth or any GIS software.
• Google Earth does real-time loading
• Talk in IIPS on Tuesday
• http://wdssii.nssl.noaa.gov
• Looking for the NWS to pick this up!

lakshman@ou.edu