David Kitzmiller (OHD/HL)Greg Stumpf (OST/MDL)

David Kitzmiller (OHD/HL)Greg Stumpf (OST/MDL)

NSSL Multiple-Radar / Multiple-Sensor (MRMS)

Decision Briefing

NSSL Multiple-Radar / Multiple-Sensor (MRMS)

Decision Briefing

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Purpose of briefing

Approval of the National Severe Storms Laboratory Multiple-Radar / Multiple-Sensor (MRMS) weather decision support system as an official NOAA Line Office Transition Project.

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Users requiring advanced radar-based products

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Background:Motivation for MRMS

• Current operational warning and QPE algorithms are based on limited single-radar data

Cones-of-silence, beam broadening at far ranges, terrain blockageVery limited environmental data input

• MRMS provides a more accurate and complete depiction of storms, their evolution, and precipitation characteristics

• Many forecasters have lost confidence in the single-radar algorithms and have resorted to time-consuming “base data analysis”

Becoming unfeasible to manage the “fire hose” of information from all radars and sensors during storm outbreaks

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Background:What is MRMS?

• A scientifically-sound framework for providing more accurate, more precise, and more timely hydrometeorological decision support data versus current single-radar algorithms.

Advanced techniques in data quality control, data integration, severe weather detection and diagnosis, precipitation estimation, and short-term forecasting.

A 3D/4D high-resolution grid of radar (and other observations) and derived severe weather & precipitation estimation products.

The result of 10+ years of published research, application development, and operational testing at NSSL, WFOs, RFCs, NCEP,

SPC, AWC, and the NOAA Hazardous Weather Testbed (HWT)

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Background:What is MRMS?

• MRMS = Multiple-Radar / Multiple-Sensor

• Multi-Radar: Exploits the overlapping coverage of the WSR-88D network and the Level-II real-time data feeds to build a seamless rapidly-updating high-resolution three-dimensional cube of radar data.

• Multi-Sensor: Objectively blends data from the multiple-radar 3D cubes with surface, upper air, lightning, satellite, rain gauges, and NWP environmental data, to produce highly-robust decision assistance products.

• Improvements demonstrated in QPE, severe weather diagnosis, warning decision efficiency, NWP, etc.

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MRMS Outputs

3D Reflectivity cube

3D Azimuthal Shear cube

2D products to support:

Hydro, Aviation, NWP, Severe Weather

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Current specs of NSSL experimental system

• Ingests data from national network of WSR-88D, Canadian, 1 tv, 2 TDWR radars

• Grid resolution of 1km x 1km x 5 minutes over the CONUS for 2D products; and with 31 vertical levels for 3D products

• Radar data go through an automated multi-sensor quality control (QC) to censor non-weather echoes

• Generating 1-km CONUS products every 5-min requires 48 Linux servers

• Servers and drives can be quickly configured, maintained, swapped out, and extended to add capacity for

Greater temporal and spatial resolutionDual Polarization data/productsAdditional radars (foreign, tv, mobile, PAR, CASA)

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Current MRMS Product Distribution

Operational RUC/HRRR

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MRMS Benefits Hydrology

Provides added precipitation estimation coverage in over 99% of the “radar hostile” regions (terrain, bright-band, hail).

Provides measured improvements in data QC removing false precipitation echoes, which improves the RTMA, and reduces inaccurate precipitation estimates and unnecessary flash flood warnings.

Greatly benefits the Western U.S., where there is a combination of major flooding vulnerability and radar coverage gaps.

Integrates lightning sensor data to apply advanced precipitation segregation (convective, stratiform) for more accurate rainfall rates“MRMS/Q2 provides precipitation estimates from

portions of southwest Texas, western New Mexico, south central Colorado and Mexico where few if any

other sources of precipitation data exist. This area has now experienced major flooding in two of the past four years due to dissipating tropical systems. The loss of Q2 would, in short, mean the loss of what we have seen to be our most accurate radar-based QPE.”

– Greg Story (West Gulf RFC).

The river stage forecast errors in some basins are reduced by up to 1 meter using MRMS/Q2. This improved accuracy will lead

to major savings in flood mitigation efforts (e.g.,

sandbagging, evacuations).

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ROKN7 EFDN7 LOUN7 RNGN7 TRVN7 SWIN7 SIMN7

Med

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NMQ-RAD HPE-RAD

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MRMS BenefitsAviation

Facilitates NOAA meeting IOC and MOC NextGen radar based product requirements

Provides a straight forward research-to-operations (R2O) integration of advanced radar dependent aviation products without WSR-88D system dependencies or delays

A development platform already installed at FAA Tech Center will facilitate R2O of NextGen applications into the operational MRMS system.

The turbulence and icing solution portfolios can be implemented and configured to allow the creators to modify and improve solutions quickly in addition to expanding the capability to utilize gap filling and international radar networks.

MRMS is a viable platform to support the NOAA Convective Initiation (CI) project

“The MRMS system provides a flexible and efficient software computing architecture to accommodate rapid changes or additions to the NextGen objectives/requirements while

providing a straight forward research-to-operations (RTO) integration platform for

AWRP-funded, radar dependent, turbulence and icing solution portfolios without system dependencies or delays in implementation

within the WSR-88D system..” – FAA Reduced Weather Impact (RWI) plan

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MRMS BenefitsNWP

MRMS provides the only reliable, rapidly-available, quality-controlled, high-resolution 3D radar grid covering the CONUS.

The 3D reflectivity grid is used to derive a 3D latent heating field used to create convective cloud fields.

Model forecasts are improved using the MRMS data.

“…3D cloud and hydrometeor fields are not well sampled by conventional observing

systems and no single observing platform fully captures the needed information. The NSSL MRMS data have been absolutely critical to the success we had in the radar reflectivity data assimilation in the RUC, and its impact on the HRRR, and now in

the RR.” - Steve Weygandt (GSD)

Assimilation of MRMS into the RUC enables prediction of excessive rainfall amounts (up to 2” per 12 h), which are rarely generated by RUC without MRMS

ingest. These major rain events would go unforecasted without

MRMS data assimilation.

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MRMS Benefits Severe Weather

Improvements in warning decision efficiency (via HWT) allows more WFO resources to be directed to customer decision support during high impact events.

More accurate at the depiction of hail and mesocyclones makes warnings more precise and timely.

The hail swath and tornado track verification system provides the WFOs, Red Cross, and FEMA with rapid automated assessments of storm damage areas.

Complete CONUS coverage can be used to develop robust climatological archives for hail, rotating storms, and precipitation, benefiting agriculture, insurers, etc.

“Even today, the volume of radar data alone is such that it is nearly impossible

for a well-trained meteorologist to be assured they have interpreted all of the

relevant information.” - David Andra (WFO OUN SOO), commenting on the

need for a robust data integration system to control the “fire hose” of

multiple rapidly-updating data streams during WFO warning operations. “SPC routinely uses a number of real-time national (MRMS) fields to monitor

the evolution, intensity, and hazards associated with convective storms. The increased resolution of products and improved accuracy in hail size and

rainfall has been noted by many forecasters here.” - Steve Weiss (SPC SOO)

HWT Warnings

NWS Warnings

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Short-term impactsof not transitioning the full NSSL MRMS to operations

• Users must continue their dependence on a research-funded quasi-operational experimental prototype that is not maintained 24/7 and has no backup

Field offices and NCEPs are increasing their reliance on MRMS productsOHD 0-6h QPF system under development is dependent on MRMS radar input

• Multiple organizations might require their own stand-up systems to support their single-agency specific operational requirements

AWRP must fund the AWC Testbed to set up an interim MRMS solution now to meet FAA’s turbulence (NTDA) deliverables

• FAA development system at FAA Tech Center remains without NOAA-sponsored operational target

• The NCEP IBM-AIX MRMS system for the RUC is limitedNCEP-EMC must routinely upgrade NSSL software to IBM-AIX (requires extra staff time)Will not meet the needs of other agencies/centers (limited product suite)Product latency and i/o not adequate for short-fused warning ops

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Long-term impactsof not transitioning the full NSSL MRMS to operations

• OAR must continue to use NOAA research funding to maintain quasi-operational systems, versus advancing R&D

• Major Western U. S. hydrologic limitations in “radar-hostile” regions continue

• Warning decision efficiency continues to degrade and information overload grows

• NWS must continue to pay for inferior (4-bit, 2D) commercial mosaics

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Preferred Deployment Option

NCEP/NCO Linux Cluster:Will meet multiple agency requirements

Transition explored

Completed draft NCEP charter for implementation

Completed testing on Dell Blade server architecture and solid state drives

Has proven O&M expertise and robust backup capability

Eliminates NCEP staff costs for porting upgrades to IBM-AIX

Latency and i/o is adequate for short-fused warning ops

Will match specs of development platforms, facilitating R2O

Cost estimate (primary & backup):One time transition: $3 million

Annual O&M: $1 million

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Alternate Deployment Options

AWC/SPC

FAA Tech Center

Telecommunications Operations Center (TOC)

Private Industry

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In conclusion…

NSSL MRMS is a sole-source, scientifically-sound solution that meets many high-priority requirements for multiple agencies, including NextGen.

There is no other proven alternative national capability to integrate and optimize information from multiple radar networks (WSR-88D, TDWR, ASR) into a 4D data cube.

FACTOID: One new WSR-88D costs ~$10M and provides < 0.13M mi2 coverage

An MRMS System at NCEP:

* Will operate for 10 years at the same cost, a small % addition of the total cost of the

NEXRAD program

* Will provide >3.2M mi2 total CONUS coverage at $3 / sq mi (versus $100 / sq mi for one

radar)

* Will increase the coverage of all WSR-88Ds, combined, by 35%

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Discussion

Approval of the National Severe Storms Laboratory Multiple-Radar / Multiple-Sensor (MRMS) weather decision support system as an official NOAA Line Office Transition Project.

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Backup Slides

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What else comes with the “MRMS package”?

• Verification SystemsPrecipitationHail and Tornado

• Network monitoring system

• Development framework (like ADE, CODE)

A foundation for research and product development

Facilitates transition of Research to Operations

• Data Options:

Push

Pull (subscription)

Complex Data Retrievals (for locally-derived custom products)

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MRMS Benefits NOAA and Its Users and Partners

• Will provide a single-authority, operationally 24/7 maintained, seamless, scientifically-sound, high resolution 4D data cube of integrated radar and sensor data for multiple agencies

• Improvements in depictions of convective initiation, structure, and evolution for warnings, forecasts, air traffic routing

• An immediate target of opportunity for NextGen

• Will provide framework for research and development

• Will provide a clear R2O path for transition of new science to operations

• Will provide an analysis of record to more robustly understand severe weather and precipitation climatologies nationwide

• Will strengthen existing and establish new partnerships with multiple development and operational agencies

• Will save lives, property, aviation delays/accidents

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Advantages of MRMS

Integrate multiple-radar and multiple-sensor informationNo longer single-radar specific.More accuracy in detection and diagnosis (better sampling - more “eyes” looking at storms).

Rapid-update capabilityUses virtual volume scan concept.Better lead time (no more waiting until end of volume scan for guidance).

Automatically fill in outage gaps by other sensorsProvides better continuity of operations.

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Many single radars provide many different answers

KJAN

VIL = 34

KLIX

VIL = 52

KMOB

VIL = 45

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KLIX

VIL = 52

CELL ID RADAR RADAR RADAR VIL

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Is this the best detection?

Many single radars provide many different answers

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Multiple radars provide a single robust answer

KMOB

KLIX

KJAN

CELL ID VIL Max Dbz etc. etc.

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Or is this?

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Single radar data

Single Radar

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Blended 3D multi-radar data

Radars in network supplement each other:

Overlapping coverage

Fills in gaps from terrain blockage

Increased sampling frequency

Multiple Radars

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Single Radarv.

Multiple Radar

VIL TracksVertical Cross-Section

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http://nmq.ou.edu

NMQ: National mosaic and Multi-sensor QPE

NMQ: National mosaic and Multi-sensor QPE

• A suite of quantitative precipitation estimation algorithms

• Uses multi-sensor observations

• Products delivered to RFCs (AHIPS) and NWS FOs (FFMPA) for operational use

• An archive a precipitation products

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NMQ Precipitation Products

• Reflectivity ProductsVertical Profile of Reflectivity, Bright-band IdentificationHybrid-Scan Reflectivity (VPR corrected)

• Precipitation Products1-HR Precip, 3-HR, 6-HR, 12-HR, 24-HR, and 72-HR PrecipRadar only, Multi-Sensor, Radar with Gauge Bias CorrectionLocal Gauge BiasGauge-only Precip

• Precipitation VerificationAutomated comparison to Stage-II, Stage-III, Stage-IV, HADS, MPE

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NMQ Precipitation Products

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Improvements over current operational products:

Vertical reflectivity profile correction

Adapted to mountainous terrain

Seamless hybrid scan minimizes effects of beam blockage on radials

Superior quality control to operational precip processing system

Supports a prototype 0-6h QPF with skill comparable to that of HPC forecasters

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NMQ Precipitation Products

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Cool season:

Number of HRAP grid boxes with

radar-reference correlations ≥ 0.50 and

≥ 0.70 were 26% and 35% higher for

NMQ than for PPS

Cool Season EffectiveRadar Coverage forPrecipitation:

Green:Areas where NMQPrecipitation improvesRadar-gauge correlation From poor-marginal to useful(correlation > 0.5)

Blue:Converse

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NMQ-RAD HPE-RAD

Median peak stage error (m) for 5 storm events on subbasinsof the Tar River, North Carolina, 2003-2006. Basins range in size from 2300 km2 (ROKN7) to 116 km2 (SIMN7).NMQ is from MRMS, HPE from operational NEXRAD PPS.

Assimilation of reflectivity (RUC DEV13)enables prediction of higher rainfall amounts,which are only rarely generated by RUC withoutradar ingest (NCEP OPER). This includesamounts up to 2 inches in 12 hours.

Weygandt, S., and S. Benjamin, 2007: Radar reflectivity-based initialization of precipitation systems using a diabatic digital filter within the Rapid Update

Cycle. Preprints, 18th Conf. Num. Wea. Pred., Park City, UT, Amer. Meteor. Soc., 1B.7.

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NMQ QC improves RTMA

The MRMS Quality Control (QC) algorithm significantly reduces non-precipitation echoes – a potential improvement to RTMA

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http://wdssii.nssl.noaa.gov

WDSS-II: Warning Decision Support System –

Integrated Information

WDSS-II: Warning Decision Support System –

Integrated Information

• A suite of data ingest and quality control processes

• Severe weather algorithms and applications

• Uses multi-sensor observations

• Products delivered to NCEP (SPC and AWC) and NWS FOs (OUN,FTW,TUL), CAPS, ESRL, NCAR and Environment Canada for operational use

• An archive of automated Hail Swath and Rotation Track information

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MRMS Severe Weather Algorithms

• 3D Reflectivity MosaicAutomated QC Neural NetworkVIL, EchoTop, Composite, IsothermsHail (Max Expected Size, Probability, Hail Swath)Kmeans/Segmotion Nowcast, Storm TrackingStorm Classification

• 3D VelocityVortex Detection & Diagnosis Algorithm (from Azimuthal Shear)Multi-Doppler Wind Analysis

• Multi-Sensor AlgorithmsLightning (NLDN & LMA)Near Storm Environment (from RUC numerical model analyses)Satellite

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MRMS Severe Weather Products

“Rotation Tracks”“Rotation Tracks”

“Hail Swaths”“Hail Swaths”

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NMQ/WDSS-IIComputational Infrastructure

The entire NMQ/WDSS-II processing system is composed of 2 Quad-Core AMD Opteron Processors (2.9 GHz with 32GB RAM) Linux servers from a single manufacturer (HP);

Servers and server drives can quickly be configured, maintained and swapped out;

Running RedHat 64-bit OS;

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Radar Data Ingest• Ingest base level 2 data from 158 tri-agency (DOC, DOD, DOT) 10 cm WSR-88D radars

• Ingest base level data from 33 5-cm radars from Environmental Canada/NCDC

• Ingest base level data from two TDWRs using direct connections

• Ingest commercial radars in addition to experimental radar systems such as CASA and PAR

• System designed to accommodate increasing access to radar systems and radar networks

WSR-88D

TDWR

Canadian Radars

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NMQ/WDSS-IIMosaic and Product Creation

Radar Ingest

4D grids & products Precipitation Products

Severe Weather Products

Aviation NextGen Weather Products

Products are disseminated in NetCDF, binary, AWIPS, N-AWIPS, GIS, and HRAP formats using the LDM protocol.

WSR-88D

TDWR

Canadian

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Multi-sensor Ingest