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Recent Advances at the National Centers for Environmental
Prediction
“Where America’s Climate and Weather Services Begin”
Louis W. UccelliniDirector, NCEP
Millersville UniversityApril 8, 2004
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Overview
• Define NCEP• Status of Models• Recent Advancements
– Hurricane forecasts– Wave Watch III– QPF– Climate Model
• JCSDA• Future Plans for Community Models
– Ensembles– WRF– ESMF
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Define NCEP
4*As of 10/1/04*54 FTE
Total FTE: 429*131 Contractors/24 Visitors
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NCEP Center Locations
Space Environment Center Aviation Weather Center
NCEP Central Operations Climate Prediction Center Environmental Modeling Center Hydrometeorological Prediction Center Ocean Prediction Center
Storm Prediction Center
Tropical Prediction Center
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What Does NCEP Do?
Severe Storm Outlooks Fire Weather Outlooks Weather Forecasts to Day 7 Quantitative Precipitation
Forecasts to 5 days Marine Weather Discussions Model Discussions
Severe Weather Watches Hurricane Watches and
Warnings Aviation Warnings
(Convective, Turbulence, Icing) Climate Forecasts (Weekly to
Seasonal to Interannual) Marine High Seas Forecasts Solar Monitoring –
geomagnetic storm forecasts
Guidance to Support WFO/RFC National Products
Model Development and Applications, including Data AssimilationOcean Models for Climate Prediction; Coastal Ocean Forecast System; Wave ModelsSuper Computer, Workstation and Network Operations
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Employment Situation
• Employment situation– Total of 375 Civil Servants; 131 contractors; 24 visitors– Currently have 6 Student Interns (SCEP/STEP) – During the last 12 months
• 39 CS vacancies; 6 SCEPs; • Hired 28 contractors• 7 new visiting scientists• 14 Summer Hires (ORISE, GoHFAS, NOAA Educational
Partnership Programs)
– Projected growth through ’08: 50 – 60 (contractors/visiting scientists/postdocs)
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NCEP’s Future is Built Upon:
Climate-Weather-Water Linkages; for example Seasonal Hurricane Outlooks & Extratropical Storm patterns Meteorological-Hydrological forecasts Ocean and atmosphere coupled forecasts Atmosphere-Land Processes coupled forecasts
“Seamless Suite” of products through a collaborative approach Extension of predictability of Weather and Climate (from
snowstorms to ENSO); Improve the forecasts of Extreme Events Community Model Approach – Common Model Infrastructure Addressing uncertainty in forecasts – Ensemble modeling
NEW Collaborative Forecasting; Unified Model Infrastructure
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Status of Models
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Computing Capability
Commissioned/Operational IBM Supercomputer in Gaithersburg, MD (June 6, 2003)
$20M/Year $20M/Year InvestmentInvestment
•Receives Over 116 Million Global Observations Daily•Sustained Computational Speed: 450 Billion Calculations/Sec•Generates More Than 5.7 Million Model Fields Each Day•Global Models (Weather, Ocean, Climate)•Regional Models (Aviation, Severe Weather, Fire Weather)•Hazards Models (Hurricane, Volcanic Ash, Dispersion)•Backup for operational side: Fairmont, WV installation Fall’04
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NCEP Operational ModelsEta
12 km, 60 levels, 84 hrs at 0 , 6, 12 and 18Z
Global Forecast System (GFS)
T254 (~55 km) to 3.5 days (84 hrs), 64 levels
T170 (~75 km) to 7.5 days (180 hrs), 42 levels
T126 (~105 km) to 16 days (384 hrs), 28 levels
16 days (384 hrs)/4 times per day
RUC
20 km, 50 levels
12 hrs at 0,3,6,9,12,15,18,21Z
3 hrs at 1,2,4,5,7,8,10,11,13,14, 16,17,19,20,22,23Z
Climate
T62 (~200 km), 28 levels, 7 months (20 members)
Ensembles
global 10 members at 00, 06,12,18Z
T126 (~105 km) to 180 hrs, T62 (210 km) to 384 hrs
28 levels, 16 days (384 hrs)
regional 10 members at 0 and 12Z
48 km, 45 levels, 63 hrs from 9 and 21Z
Wave Model
global - 1.25 x 1.0 deg lat/lon
Alaskan Regional - .5 x .25 deg lat/lon
Western North Atlantic - .25 x .25 deg lat/lon
Eastern North Pacific - .25 x .25 deg lat/lon
1 level, 168 hrs/4 times per day
North Atlantic Hurricane (seasonal)
North Pacific Hurricane (seasonal)
.25 x .25 deg lat/lon
1 level
78 hours/4 times per day
GFDL Hurricane Model
coupled ocean-atmosphere
Two nests (0.5, 1/6 deg lat/lon)
42 levels
126 hrs at 00, 06, 12 and 18Z
Status of Distributed ModelsThe Workstation Eta
A means for providing real-time high-resolution numerical model data at the local level
Domain can be placed anywhere on the globe: size and resolution determined by user
Non-NWS use encouraged. About 140 international requests from countries such as China and Brazil (both with >5 users), Turkey and Thailand.
Over 155 domestic users: WFOs, researchers and students at U.S universities
http://www.emc.ncep.noaa.gov/mmb/wrkstn_eta/
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Tiling for Higher Resolution Applications
• 6 High resolution
(all 8 km except 10 km Alaska) Window nested runs - once per day to 48 hours
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Tiling for Higher Resolution Applications
• Fire weather runs – 8
km NMM runs on demand in one of 26 areas of coverage, each about 900 km square up to 4/day
• Dispersion models run on demand using 4 km NMM for Homeland Security
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Recent Advancements
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Recent Advancements: Hurricanes
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NHC Yearly-averaged Atlantic Track Forecast Errors
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TPC Atlantic 72 hr Track Forecast Errors
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Hurricane MichelleOctober 29 - November 5, 2001
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Hurricane Claudette5-Day Hurricane Forecast
Radar 10:45 AMJuly 15, 2003
Error (nm) 12 h 24 h 36 h 48 h 72 h 96 h 120 h
OFCL 35 57 84 112 128 135 147
GFDL 32 56 88 121 163 233 273
GFS 38 66 93 121 193 218 301
# of cases 25 24 22 19 14 8 8
Hurricane Isabel
Thursday, 9/18/0312 PM EDT5-day forecast
3-day forecast
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NATIONAL HURRICANE CENTER ATLANTIC TRACK FORECAST ERRORS
NATIONAL HURRICANE CENTER ATLANTIC TRACK FORECAST ERRORS
12 24 36 48 72 96 120
Forecast Period (hours)
0
100
200
300
400
500
Err
or
(nau
tica
l mile
s)
1964-1973
1984-1993
1974-1983
1994-2002
Isabel
2003
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Recent Advancements: Wave Watch III
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• New model design with emphasis on transparency, vectorization and parallelization (plug compatible, portable).
• More general governing transport equation, allowing for later full coupling with ocean models.
WAVEWATCH III
new model required
• All models use GFS and ice edge information from NCEP's operational ice analysis. A special GFDL driven version of the Western North Atlantic and Eastern North Pacific wave model are run for hurricane wave prediction (72h forecast).
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Isabel 18/9/2003, 12 UTCnowcast
48h forecast24h forecast
12h forecast
Intensity and location of forecast waves consistent and confirmed by altimeter and buoy observations. At 48h forecast lower wave heights due to earlier landfall.
wave height 50+ ft (45+ ft)
Isabel at Field Research Facility Duck NC
pictures from US Army Corps Of Engineers Field Research Facility webcam
9/18 14:00 EDT 9/29 14:00 EDT
Maximum observed wave height at the end of the pier 26.6ft, which is roughly the maximum sustainable wave height for the local water depth. Wave height 2 miles offshore reported up to 49 ft.
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Recent Advancements: QPF
HPC QPF Verification1-inch Threat Score
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Eta Model Performance MetricRatio of Annual 48h Precipitation Threat Score to 24h Score in 1999
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Day 1 0.5 .597 Dec ‘02
1.0 .483 Dec ‘02
2.0 .332 Nov ‘98
3.0 .374 Feb ‘81
Update 0.5 .557 Dec’02
1.0 .423 Dec ‘02
2.0 .286 Sep ‘79
Day 2 0.5 .507 Dec ‘02
1.0 .421 Jan ‘02
Day 3 0.5 .393 Jan ‘02
1.0 .331 Jan ‘02
All Time HPC QPF Threat Score Records
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Recent Advancements: Climate Model
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Climate Model
• Current operational climate model– 200 km, 28 levels, runs to 7 months each month– Linked to SSTs in Pacific basin only
• Improved operational climate model– Fully coupled ocean-atmosphere system
• NCEP operational Global Forecast System (GFS) atmospheric model
– 200 km resolution, 64 levels, model top 0.2 mb
• MOM3 ocean model (GFDL)– 100 km resolution, 40 levels, 30 km between 10 deg N and 10 deg S– Global; between 65 deg N and 75 deg S– Global Ocean Data Assimilation System (GODAS)
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Coupled Model Simulation ENSO SST cycles
Nino 3.4 SSTAnomalies
Simulated 2002-2040 (top)
Observed 1965-2003(bottom)
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Coupled Model Simulation SST Interannual Variability
Observed
64 Level Atm
28 Level Atm
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Examples of ENSO eventsSimulated El Nino 2015-2016 Simulated La Nina 2017-18
Real El Nino 1982-1983 Real La Nina 1988-1989
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Hindcast Skill Assessment
• Methodology– 5-member ensemble over 22 years from 1981-2002
– January and April initial conditions
– 9 month runs– Initial atmospheric states 0000 GMT 19, 20, 21, 22, and
23 for each month– Initial ocean states NCEP GODAS (Global Ocean Data
Assimilation System) 0000 GMT 21st of each month• Forced by Reanalysis 2 parameters
• Preliminary results– 10-15 member ensembles for full calibration runs
(ongoing)
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Hindcast Skill Assessment (cont)
• Hindcast skill– Estimated after bias correction for each year– Uses model climatology based on the other years– Anomaly correlation skill score for Nino 3.4 region
SST prediction– Skill maps for
• Global SST• U.S. temperature • U.S. precipitation
– Comparisons with • Operational dynamical forecast (CMP14)• Operational statistical forecast (NCEP CPC tools)
– Constructed Analog SST (CASST)
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Ensemble Mean
CMP14CASST
April ICEnsemble Mean – mean of 5 member ensemble
CMP14 – operational dynamical forecast
CASST – Constructed Analog SST (statistical forecast used by CPC)
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January IC
CASST
CMP14
Ensemble Mean
Ensemble Mean – mean of 5 member ensemble
CMP14 – operational dynamical forecast
CASST – Constructed Analog SST (statistical forecast used by CPC)
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JCSDA
Count
(Mill
ions)
Daily Upper Air Observation Count
2002
2003
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Joint Center for Satellite Data Assimilationcreated July 2, 2001
Increase uses of current satellite data in NWP models Develop the hardware/software systems needed to assimilate data from
the advanced satellite sensors Advance the common NWP models and data assimilation infrastructure Develop common fast radiative transfer system Assess the impacts of data from advanced satellite sensors on weather
and climate predictions Reduce the average time for operational implementations of new
satellite technology from two years to one
Accelerate use of research and operational satellite data in operational numerical prediction models
Goals:
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JCSDA Partners
NASA/Goddard
Global Modeling & Assimilation Office
NOAA/NESDIS
Office of Research &
Applications
NOAA/OAR
Office of Weather and Air Quality
NOAA/NCEP
Environmental
Modeling Center
US Navy
Oceanographer of the Navy,Office of Naval Research (NRL)
US Air Force
AF Director of WeatherAF Weather Agency
PARTNERS
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JCSDA Road Map (2002 - 2010)
Improved JCSDA data assimilation science
2002 2004 2007 2008 2009 2005
OK
Deficiency
2003
Advanced JCSDA community-based radiative transfer model,Advanced data thinning techniques
Sci
ence
Ad
van
ce
By 2010, a numerical weather prediction community will be empowered to effectively assimilate increasing amounts of
advanced satellite observations
2010
AMSU, HIRS, SSM/I, Quikscat,
AVHRR, TMI, GOES assimilated
AIRS, ATMS, CrIS, VIIRS, IASI, SSM/IS, AMSR, more products assimilated
Pre-JCSDA data assimilation science
Radiative transfer model, OPTRAN, ocean microwave emissivity, microwave land emissivity model, and GFS data assimilation system were developed
The radiances of satellite sounding channels were assimilated into EMC global model under only clear atmospheric conditions. Some satellite surface products (SST, GVI and snow cover, wind) were used in EMC models
A beta version of JCSDA community-based radiative transfer model (CRTM) transfer model will be developed, including non-raining clouds, snow and sea ice surface conditions
The radiances from advanced sounders will be used. Cloudy radiances will be tested under rain-free atmospheres, and more products (ozone, water vapor winds) are assimilated
NPOESS sensors ( CMIS, ATMS…) GOES-R
The CRTM includes scattering & polarization from cloud, precip and surface
The radiances can be assimilated under all conditions with the state-of-the science NWP models
Resources:
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• JCSDA is funding 18 extramural research projects to develop the state of-the-art satellite data assimilation system (e.g. uses of cloudy radiances from advanced satellite instruments, uses of satellite snow and vegetation products)
• Preparation for uses of advanced satellite data such as METOP (IASI/AMSU/HSB), DMSP (SSM/IS) and EOS (Aqua AIRS, AMSR-E)
• NCEP global data assimilation system implemented into NASA Global Modeling and Assimilation Office (GMAO) forecast system
• JCSDA community-based radiative transfer model
• Snow and sea ice emissivity models for improving uses of satellite microwave sounding data over high latitudes
• Impact studies of POES AMSU, EOS AIRS, DMSP SSMIS on NWP through EMC parallel experiments
JCSDA FY03-04 Major Projects
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Recent Accomplishments Land emissivity model tested in NCEP operational models
Positive impacts with AMSU data over land (May,2002) Operational implementation (October, 2002)
Enabled use of microwave radiances over land
New Data used in NCEP operational models SSM/I, TRMM microwave imager precipitation estimates SSM/I, AMSU cloud liquid water GOES-10 IR radiances QuikSCAT data
Preparation for AIRS Computer installed at NASA to deliver data within 180 minutes of ingest Fast radiative model developed, documented, delivered, undergoing testing Sample data set delivered to NWP Centers
“Foundation” Science Issues and Priorities agreed to: Basis for AO
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Including QUIKSCAT data resulted in 3-8% improvement in 10 m winds vs. mid-latitude deep ocean buoys at 24-96 hr7-17% improvement for MSLP
Based on 40 forecasts from 45 days of GDAS (T170, L42) experiment.
Impact of QuikSCAT Data
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Ongoing Activities (cont)JCSDA Announcement of Opportunity
1. Improve radiative transfer model1. UCLA – Advanced Radiative Transfer
2. UMBC – Including Aerosols in OPTRAN
3. NOAA/ETL – Fast microwave radiance assimilation studies
2. Prepare for advanced instruments1. U. Wisconsin – Polar winds assimilation
2. NASA/GSFC – AIRS and GPS assimilation
3. Advance techniques for assimilating cloud and precipitation information1. U. Wisconsin – Passive microwave assimilation of cloud and precipitation
4. Improve emissivity models and surface products1. Boston U. - Time varying Land & Vegetation
2. U. Arizona – Satellite obs for Snow Data Assimilation
3. Colo. State U. – Surface emissivity error analysis
4. NESDIS/ORA – Retrievals of real-time vegetation properties
5. Improve use of satellite data in ocean data assimilation1. U. Md – Ocean data assimilation bias correction
2. Columbia U. – Use of altimeter data
3. NRL (Monterey) – Aerosol contamination in SST Retrievals
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Future Plans for Community Models
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Future Plans• WRF
– Common model infrastructure for mesoscale (NCAR and NCEP Dynamic Core and Physics)
– Sustained by AF, Navy, NCEP, NCAR– Testing underway of all combinations
of 2dynamic cores and 2 physics packages at DoD Major Shared Resource Center (one month from each season)
– First operational implementation at NCEP by Oct ’04, implementation at AF by Spring, ‘05
•ESMF–Global common model infrastructure–NCAR, GFDL, NASA/GSFC, MIT, NCEP–Basis for next generation global data assimilation and forecast system
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Future Plans• Ensemble models
– SREF (10 members twice/day, 48 km, 45 levels, 63 hrs)– Global (10 members twice/day; 105 km to 84 hrs, 210 km
to 384 hrs; 28 levels)
GOAL: To create a North American Ensemble Forecast System with the Canadian Meteorological Centre
Dominant Precip Type63 hour forecast
Valid 12Z,December 5, 2002
Air Quality Prediction at NCEP
• Initial (1-5 years started FY2003) :
–1-day forecasts of surface ozone (O3) concentration
–Develop and validate in Northeastern US in 2 years
–Deploy Nationwide within 5 years
•Intermediate (5-7 years):–Develop and test capability to forecast particulate matter (PM) concentration
•Longer range (within 10 years):–Extend air quality forecast range to 48-72 hours
–Include broader range of significant pollutants
•Program has purchased additional computer power to perform AQF and promised this increment for perpetuity -92 -90 -88 -86 -84 -82 -80 -78 -76 -74 -72 -70 -68
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0 to 10 1 0 to 20 2 0 to 30 3 0 to 40 4 0 to 50
Spatial Evaluation vs ObsHourly Ozone (rms srror)
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Summary
• NCEP is positioned to deal with important strategic issues– Climate-weather-water linkage– Expand into “environmental” prediction– Extend predictive capabilities into week 2– Extend consistent predictive capabilities for
extreme events out to Day 7
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Summary (cont)• Based on Partnership with larger research community
– Community model approach (global and regional)– Active participation in field programs
• North American Monsoon Experiment• THORPEX
– Test Beds:• USWRP/Joint Hurricane Test Bed (TPC)• Hazardous Weather Forecast Test Bed (SPC) • Aviation Test Bed (AWC)• USWRP/Hydrometeorological Test Bed (HPC)
– Data Assimilation efforts through JCSDA
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End of Slides
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N.H. 500 mb Height Anomaly Correlation for Forecasts Days 3 (blue), 5 (aqua), and 7 (red)
Monthly Values and Annual Averages
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S.H. 500 mb Height Anomaly Correlation for Forecasts Days 3 (blue), 5 (aqua), and 7 (red)
Monthly Values and Annual Averages
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Organizational Structure NASA NOAA DOD
Joint Oversight Board of Directors:NOAA NCEP: L. Uccellini (Chair)
Goddard ESD : F. EinaudiNOAA ORA: M. ColtonNOAA OAR: J. Gaynor
Navy: S. Chang, R. McCoyUSAF: J. Lanicci, M. Farrar
Joint Center StaffCenter Director: John LeMarshall
Executive Directors: Stephen Lord - NWSFuzhong Weng - NESDIS
L. P. Riishogjaard – NASAPat Phoebus - NRLTechnical Liaisons:
DAO – D. DeeEMC – J. Derber
GMAO – M. RieneckerOAR – A. GasiewskiORA – D. TarpleyNavy – N. Baker
USAF – M. McAteeProgram Support: Ada Armstrong
George Ohring (NESDIS)
AdvisoryPanel
Rotating Chair
ScienceSteering
Committee