High resolution radar data and products over the Continental United States

High resolution radar data and products over the Continental United States

[email protected] Severe Storms Laboratory

Norman OK, USAhttp://www.wdssii.org/

April 19, 2023 [email protected] 2

Evolution of WDSS

1993-1998

Single-radar SCIT, MDA, TDA

Now part of RPG

1995-2000

Single-radar with multi-sensor input

NSE inputs

Scheduled for ORPG-8

2003 Multi-radar multi-sensor over regional domain

(1000km x 1000 km)

Gridded products

Shipped to select WFOs

Used in Storm Pred. Center

Product gen. for AWIPS?

2005 Multi-radar multi-sensor over CONUS

CONUS 1km grids

Available on the Internet

Used in SPC


What products? How often?

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


How does it work?

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.


Virtual volume composite

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


Why do QC?

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.


Impact of QC

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.

With QC’ed compositesraw


Second level of QC

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


What do we do with the composite?

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.


2D vs 3D

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


The 3D flow

Not just reflectivity.

Compute shear (Smith05) and low-level shear.

Process lightning


3D processing

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.


Example products

Extracted from the real-time generation on Jan. 11, 2006The day I created this presentation!We haven’t run the CONUS system in

Spring yet, so the severe weather products may be underwhelming.


Reflectivity products

Composite from 2D Composite from 3D

Height of Max Ref Which radars?


Azimuthal shear products

Azimuthal shear 0-3km MSL 30 minute rotation tracks


Severe weather diagnosis

Reflectivity at temp. levels

Echo top (18 dBZ)

VIL

Convection

Also:

Probability of Severe Hail

Maximum Expected Hail Size

VIL_Density

VIL_of_the_day

Other echo top dBZ levels


Short-term forecast

Reflectivity at T=0 Clusters

Reflectivity at T=30 (forecast) Southward motion


Precipitation estimates

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.

Ref closest to ground

2hr precip accum

Instantaneous precip rate


What do we do with these products?

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!

High resolution radar data and products over the Continental United States

Documents

process volume

d reflectivity

volume compositein

running volume

d radar mosaic

radar data tilt

level of qcthe radar

d composites