National Mosaic and Quantitative National Mosaic and Quantitative Precipitation Estimation Project Precipitation Estimation Project

(NMQ)(NMQ)

Ken Howard, Dr. Jian Zhang, and Steve Ken Howard, Dr. Jian Zhang, and Steve VasiloffVasiloffNational Severe Storms LaboratoryNational Severe Storms Laboratory

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Strategic PartnershipsStrategic Partnerships

Federal Aviation AdministrationFederal Aviation AdministrationConvective Weather PDTConvective Weather PDT

Chuck Dempsey, Jason Wilhite and Dr. Robert MaddoxChuck Dempsey, Jason Wilhite and Dr. Robert MaddoxSRP, Salt River Project, Tempe, AZ, USASRP, Salt River Project, Tempe, AZ, USA

Dr. Paul Chiou, Dr. Chia Rong Chen, and Dr. PaoDr. Paul Chiou, Dr. Chia Rong Chen, and Dr. Pao--Liang ChangLiang ChangCentral Weather Bureau, Taipei, TaiwanCentral Weather Bureau, Taipei, Taiwan

Weather Decision Technologies, Norman, Oklahoma, USAWeather Decision Technologies, Norman, Oklahoma, USA

Scientific CollaboratorsScientific CollaboratorsMike Smith, George Smith, Mike Smith, George Smith, FengFeng Ding, Chandra Ding, Chandra KondraguntaKondragunta, Jon Roe,, Jon Roe,

and Gary Carterand Gary CarterNWS, Office of Hydrological DevelopmentNWS, Office of Hydrological Development

Dr. Marty Ralph and Dr. Dave KingsmillDr. Marty Ralph and Dr. Dave KingsmillNOAA, Environmental Technology LaboratoryNOAA, Environmental Technology Laboratory

Andy Edman and Kevin Warner Andy Edman and Kevin Warner NWS, Western Region HeadquartersNWS, Western Region Headquarters

Arthur HenkelArthur HenkelCaliforniaCalifornia--Nevada RFCNevada RFC

Dr. Thomas Dr. Thomas GrazianoGraziano and Mary and Mary MulluskyMulluskyNWS Office of Climate, Water, and Weather ServicesNWS Office of Climate, Water, and Weather Services

Steve HunterSteve HunterUSGS, Bureau of ReclamationUSGS, Bureau of Reclamation

Dr. Robert KuligowskiDr. Robert KuligowskiNOAA National Environmental Satellite, Data and Information ServNOAA National Environmental Satellite, Data and Information Serviceice

Dr. Dr. Curtis MarshallCurtis MarshallNOAA National Center for Environmental PredictionNOAA National Center for Environmental Prediction

What is NMQ?What is NMQ?The National Mosaic and QPE (NMQ) project is a The National Mosaic and QPE (NMQ) project is a collaborative initiative between NSSL, FAA, NCEP and the collaborative initiative between NSSL, FAA, NCEP and the NWS/Office of Hydrologic Development (OHD) and the NWS/Office of Hydrologic Development (OHD) and the NWS/Office of Climate, Water, and Weather Services NWS/Office of Climate, Water, and Weather Services (OCWWS) to address (among others) the pressing need for (OCWWS) to address (among others) the pressing need for –– highhigh--resolution national 3resolution national 3--D radar mosaics for D radar mosaics for

atmospheric data assimilation and severe weather atmospheric data assimilation and severe weather identification and predictionidentification and prediction

–– multi sensor QPE and short term QPF for all seasons, multi sensor QPE and short term QPF for all seasons, regions, and terrains in support of operational regions, and terrains in support of operational hydrometeorological products and distributed hydro hydrometeorological products and distributed hydro modelingmodeling

–– facilitating efficient and timely research to operations facilitating efficient and timely research to operations infusion of hydro meteorological applications and infusion of hydro meteorological applications and productsproducts

Objectives of NMQObjectives of NMQMaintain a scientifically sound, physically realistic realMaintain a scientifically sound, physically realistic real--time time system to develop and test techniques and methodologies for system to develop and test techniques and methodologies for physically realistic highphysically realistic high--resolution rendering of resolution rendering of hydrometeorological and meteorological processeshydrometeorological and meteorological processesCreate the infrastructure for communityCreate the infrastructure for community--wide research and wide research and development (R&D) of hydrometeorological applications in development (R&D) of hydrometeorological applications in support of monitoring and prediction of freshwater resources in support of monitoring and prediction of freshwater resources in the U.S. across a wide range of spacethe U.S. across a wide range of space--time scalestime scalesThrough the NMQ infrastructure, facilitate communityThrough the NMQ infrastructure, facilitate community--wide wide collaborative R&D and researchcollaborative R&D and research--toto--operations (RTO) of new operations (RTO) of new applications, techniques and approaches to precipitation applications, techniques and approaches to precipitation estimation (QPE), shortestimation (QPE), short--range precipitation forecasting (QPF), range precipitation forecasting (QPF), and severe weather monitoring and predictionand severe weather monitoring and predictionEstablish a ‘real time’ CONUS 3Establish a ‘real time’ CONUS 3--D radar data base for model D radar data base for model assimilationassimilation

NMQ System Network LocationNMQ System Network Location

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QuickTime™ and aTIFF (Uncompressed) decompressor

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NMQ_xrt Processing System NMQ_xrt Processing System Radar Data Sources

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Polar Processing

Canadian Radar Network

WSR-88D

LDM

LDMFAA TDWR

NIDS L3FTP

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Product GenerationVerification Server

Q2 Servers

External Data Ingest

Mosaic Servers

NOAA Port

60 cpu 18 TB

NMQ_xrt Computational Tiles

NMQ_XRT CONUS 3-D Mosaic

Current124+ Radars1 km x 1 km x 500m21 vertical levels5 min updates cycle

Fall 2005135+ Radars1 km x 1 km x 200m 31 vertical levels<5 min update cycle

Summer 2006155+ Radars250x250 meter km x 131 vertical levels<5 min update cycle

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NMQ_xrt Conus CREFNMQ_xrt Conus CREF

NMQ Vertical LevelsNMQ Vertical Levels

NMQ 2D MosaicNMQ 2D Mosaic

B

C

A

Cross Sections from NMQ 3-D Mosaic

Dallas Hail Storm, 5/5/1995

Vertical Cross Section Loop (W-E)

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Horizontal Cross Section Loop

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Reflectivity QCReflectivity QC

Noise filterNoise filterRemove specklesRemove speckles

Sunbeam filterSunbeam filterRemove sun strobe echoesRemove sun strobe echoes

Vertical reflectivity gradient checkVertical reflectivity gradient checkRemove AP and clear air echoesRemove AP and clear air echoes

Satellite maskSatellite maskRemove AP, deep clear air echoes, and chaffRemove AP, deep clear air echoes, and chaff

Noise FilterNoise Filter

Sunbeam FilterSunbeam Filter

AP and Clear Air (biological)AP and Clear Air (biological)

BrightBright--Band Identification (BBID)Band Identification (BBID)((Gourley and Calvert, 2003Gourley and Calvert, 2003))

BB info will impact choice of objective analysis methods BB info will impact choice of objective analysis methods BBID steps:BBID steps:

–– 33--D Reflectivity FieldD Reflectivity Field–– Find Layer of Higher ReflectivityFind Layer of Higher Reflectivity–– Vertical Reflectivity GradientVertical Reflectivity Gradient–– Spatial/Temporal ContinuitySpatial/Temporal Continuity

33--D Spherical to Cartesian TransformationD Spherical to Cartesian Transformation(Zhang et al. 2003)(Zhang et al. 2003)

o oo

o+

No BB:Vertical linear interpolation

BB exists:Vertical and horizontal linear interpolation

BB

o

o

+No BB

Convective Case1: RHI, 263°Convective Case1: RHI, 263°

Raw Interpolated

Stratiform Case 2: RHI, 0°Stratiform Case 2: RHI, 0°

Raw Interpolated

Stratiform CaseStratiform CaseCAPPI at 2.3kmCAPPI at 2.3km

Raw Interpolated

Distance WeightingDistance Weighting

CREF_KLOT Mosaic CREF

NMQ 2 D ProductsNMQ 2 D Products(QC’d, UnQc’d, VPR corrected)(QC’d, UnQc’d, VPR corrected)

CREFCREFHREFHREFVILVILHISHISEcho topEcho topMax hght Max hght

NMQ 3D ProductsNMQ 3D Products(QC’d, UnQc’d, VPR corrected)(QC’d, UnQc’d, VPR corrected)

BREF (31 levels)BREF (31 levels)3D CREF3D CREFMulti Sensor QPEMulti Sensor QPE

Radar Only PCP (Dec. 11Radar Only PCP (Dec. 11-- Jan. 1)Jan. 1)

MS PCP (Dec. 11MS PCP (Dec. 11-- Jan. 1)Jan. 1)

Snow/Rain Mix MS PCP (Dec. 11Snow/Rain Mix MS PCP (Dec. 11-- Jan. 1)Jan. 1)

In ClosingIn Closing

•• NSSL has assembled the hardware, communication, and software NSSL has assembled the hardware, communication, and software infrastructure for the ‘real time’ creation and dissemination ofinfrastructure for the ‘real time’ creation and dissemination of high high resolution 3D radar reflectivity fields and products. resolution 3D radar reflectivity fields and products.

•• The NMQ project provides the foundation for the research and The NMQ project provides the foundation for the research and development towards highdevelopment towards high--resolution multisensor quantitative precipitation resolution multisensor quantitative precipitation estimation (QPE) for all seasons, regions and terrains in supporestimation (QPE) for all seasons, regions and terrains in support of t of hydrometeorological and hydrologic data assimilation and distribhydrometeorological and hydrologic data assimilation and distributed hydro uted hydro modeling.modeling.

•• The NMQ system is being developed as a NATIONAL community test bThe NMQ system is being developed as a NATIONAL community test bed ed for R&D and RTO of QPE, shortfor R&D and RTO of QPE, short--range QPF and severe weather range QPF and severe weather science/applications. The NMQ system and products could potentiascience/applications. The NMQ system and products could potentially lly ‘feed’ LEADS and other Unidata community based applications.‘feed’ LEADS and other Unidata community based applications.

•• NSSL seeks a collaboration with Unidata and Unidata partners toNSSL seeks a collaboration with Unidata and Unidata partners towards the wards the utilization and enhancement of the NMQ system as community educautilization and enhancement of the NMQ system as community educational tional and research/development system including the display and distriand research/development system including the display and distribution of bution of NMQ products.NMQ products.

Thank you!Thank you!

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